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HomeMy WebLinkAbout03-14-2017 Item 1, KallenPolicyAnalysis EXECUTIVE SUMMARY Angela Dills is the Gimelstob-Landry Distinguished Professor of Regional Economic Development at Western Carolina University. Sietse Goffard is a director’s analyst at the Consumer Financial Protection Bureau and a researcher in the Department of Economics at Harvard University. Jeffrey Miron is director of economic studies at the Cato Institute and director of undergraduate studies in the Department of Economics at Harvard University. The views expressed in this paper do not necessarily represent the views of the Consumer Financial Protection Bureau or the federal government. I n November 2012 voters in the states of Colorado and Washington approved ballot initiatives that legalized marijuana for recreational use. Two years later, Alaska and Oregon followed suit. As many as 11 other states may consider similar measures in November 2016, through either ballot initiative or legisla- tive action. Supporters and opponents of such initiatives make numerous claims about state-level marijuana legalization. Advocates think legalization reduces crime, raises tax revenue, lowers criminal justice expenditures, improves public health, bolsters traffic safety, and stimulates the economy. Critics argue that legalization spurs marijuana and other drug or alcohol use, increases crime, diminishes traffic safety, harms public health, and lowers teen educa- tional achievement. Systematic evaluation of these claims, however, has been largely absent. This paper assesses recent marijuana legalizations and related policies in Colorado, Washington, Oregon, and Alaska. Our conclusion is that state marijuana legalizations have had minimal effect on marijuana use and related outcomes. We cannot rule out small effects of legalization, and insuffi- cient time has elapsed since the four initial legalizations to allow strong inference. On the basis of available data, how- ever, we find little support for the stronger claims made by either opponents or advocates of legalization. The absence of significant adverse consequences is especially striking given the sometimes dire predictions made by legalization opponents. September 16, 2016 | Number 799 Dose of Reality The Effect of State Marijuana Legalizations By Angela Dills, Sietse Goffard, and Jeffrey Miron 2“The absence of significant adverse consequences is especially striking given the sometimes dire predictions made by legalization opponents.” INTRODUCTION In November 2012 the states of Colorado and Washington approved ballot initiatives that legalized marijuana for recreational use under state law. Two years later, Alaska and Oregon followed suit.1 In November 2016 as many as 11 other states will likely consider sim- ilar measures, through either ballot initiative or state legislative action.2 Supporters and critics make numerous claims about the effects of state-level marijuana legalization. Advocates think that legalization reduces crime, raises revenue, lowers criminal justice expenditure, improves public health, improves traffic safety, and stimulates the econ- omy.3 Critics argue that legalization spurs mari- juana and other drug or alcohol use, increases crime, diminishes traffic safety, harms public health, and lowers teen educational achieve- ment.4 Systematic evaluation of those claims after legalization, however, has been limited, particularly for Oregon and Alaska.5 This paper assesses the effect to date of marijuana legalization and related policies in Colorado, Washington, Oregon, and Alaska. Each of those four legalizations occurred re- cently, and each rolled out gradually over sever- al years. The data available for before and after comparisons are therefore limited, so our as- sessments of legalization’s effect are tentative. Yet some post-legalization data are available, and considerable data exist regarding earlier marijuana policy changes—such as legaliza- tion for medical purposes—that plausibly have similar effects. Thus available information pro- vides a useful if incomplete perspective on what other states should expect from legalization or related policies. Going forward, additional data may allow stronger conclusions. Our analysis compares the pre- and post- policy-change paths of marijuana use, other drug or alcohol use, marijuana prices, crime, traffic accidents, teen educational outcomes, public health, tax revenues, criminal justice expenditures, and economic outcomes. These comparisons indicate whether the outcomes display obvious changes in trend around the time of changes in marijuana policy. Our conclusion is that state-level marijuana legalizations to date have been associated with, at most, modest changes in marijuana use and related outcomes. Our estimates cannot rule out small changes, and related literature finds some effects from earlier marijuana policy changes such as medicalization. But the strong claims about legalization made by both opponents and supporters are not apparent in the data. The absence of significant adverse consequences is especially striking given the sometimes dire pre- dictions made by legalization opponents. The remainder of the paper proceeds as follows. The next section outlines the recent changes in marijuana policy in the four states of interest and discusses the timing of those changes. Subsequent sections examine the be- havior of marijuana use and related outcomes before and after those policy changes. A final section summarizes and discusses implications for upcoming legalization debates. HISTORY OF STATE-LEVEL MARIJUANA LEGALIZATIONS Until 1913 marijuana was legal throughout the United States under both state and fed- eral law.6 Beginning with California in 1913 and Utah in 1914, however, states began out- lawing marijuana, and by 1930, 30 states had adopted marijuana prohibition.7 Those state- level prohibitions stemmed largely from anti- immigrant sentiment and in particular racial prejudice against Mexican migrant workers, who were often associated with use of the drug. Prohibition advocates attributed ter- rible crimes to marijuana and the Mexicans who smoked it, creating a stigma around mari- juana and its purported “vices.”8 Meanwhile, film productions like Reefer Madness (1936) presented marijuana as “Public Enemy Num- ber One” and suggested that its consumption could lead to insanity, death, and even homi- cidal tendencies.9 Starting in 1930, the Federal Bureau of Nar- cotics pushed states to adopt the Uniform State Narcotic Act and to enact their own measures to control marijuana distribution.10 Following 3“Individual states have been backing away from marijuana prohibition since the 1970s.” the model of the National Firearms Act, in 1937 Congress passed the Marijuana Tax Act, which effectively outlawed marijuana under federal law by imposing a prohibitive tax; even strict- er federal laws followed thereafter.11 The 1952 Boggs Act and 1956 Narcotics Control Act es- tablished mandatory sentences for drug-related violations; a first-time offense for marijuana possession carried a minimum sentence of 2 to 10 years in prison and a fine of up to $20,000.12 Those mandatory sentences were mostly re- pealed in the early 1970s but reinstated by the Anti-Drug Abuse Act under President Ronald Reagan. The current controlling federal legis- lation is the Controlled Substances Act, which classifies marijuana as Schedule I. This cat- egory is for drugs that, according to the Drug Enforcement Administration (DEA), have “no currently accepted medical use and a high po- tential for abuse” as well as a risk of “potentially severe psychological or physical dependence.”13 Despite this history of increasing federal action against marijuana (and other drugs), individual states have been backing away from marijuana prohibition since the 1970s. Be- ginning with Oregon 11 states14 decriminal- ized possession or use of limited amounts of marijuana between 1973 and 1978.15 A second wave of decriminalization began with Nevada in 2001; nine more states and the District of Columbia have since joined the list.16 Fully 25 states and the District of Columbia have gone further by legalizing marijuana for medical purposes. In some states, these medical re- gimes approximate de facto legalization. The most dramatic cases of undoing state prohibitions and departing from federal poli- cy have occurred in the four states (Colorado, Washington, Oregon, and Alaska) that have legalized marijuana for recreational as well as medical purposes. We next examine these four states in detail. Colorado In 1975 Colorado became one of the first states to decriminalize marijuana after a land- mark report by the presidentially appointed Shafer Commission recommended lower pen- alties against marijuana use and suggested al- ternative methods to discourage heavy drug use. Decriminalization made possessing less than an ounce of marijuana a petty offense with a $100 fine. In November 2000 Colorado legalized medical marijuana through a statewide ballot initiative. The proposal, known as Amendment 20 or the Medical Use of Marijuana Act, passed with 54 percent voter support. It authorized patients and their primary caregivers to pos- sess up to two ounces of marijuana and up to six marijuana plants. Patients also needed a state- issued Medical Marijuana Registry Identifica- tion Card with a doctor’s recommendation. State regulations limited caregivers to prescrib- ing medical marijuana to no more than five pa- tients each. The number of licensed medical marijuana patients initially grew at a modest rate. Then, in 2009, after Colorado’s Board of Health aban- doned the caregiver-to-patient ratio rule, the medical marijuana industry took off.17 That same year, in the so-called “Ogden Memo,”18 the U.S. Department of Justice signaled it would shift resources away from state medical marijuana issues and refrain from targeting pa- tients and caregivers.19 Thus, although medical marijuana remained prohibited under federal law, the federal government would tend not to intervene in states where it was legal. Within months, medical marijuana dispensaries pro- liferated. Licensed patients rose from 4,800 in 2008 to 41,000 in 2009. More than 900 dispen- saries operated by the end of 2009, according to law enforcement.20 In fall 2006 Colorado voters considered Amendment 44, a statewide ballot initiative to legalize the recreational possession of up to one ounce of marijuana by individuals aged 21 or older. Amendment 44 failed, with 58 per- cent of voters opposed. In November 2012, however, Colorado voters passed Amendment 64 with 55 percent support, becoming one of the first two states to relegal- ize recreational marijuana. The ballot initiative authorized individuals aged 21 and older with valid government identification to grow up to six 4“In November 2012 Wash-ington joined Colorado in legalizing recreational marijuana.” plants and to purchase, possess, and use up to one ounce of marijuana.21 Colorado residents could now buy up to one ounce of marijuana in a single transaction, whereas out-of-state residents could purchase 0.25 ounces.22 In light of Amendment 64, Colorado’s gov- ernment passed new regulations and taxes to prepare for legalized recreational marijuana use. A ballot referendum dubbed Proposition AA that was passed in November 2013 imposed a 15 percent tax on sales of recreational marijuana from cultivators to retailers and a 10 percent tax on retail sales (in addition to the existing 2.9 per- cent state sales tax on all goods). Local govern- ments in Colorado were permitted to impose additional taxes on retail marijuana.23 Following about a year of planning, Colo- rado’s first retail marijuana businesses opened on January 1, 2014. Each business was required to pay licensing fees of several hundred dollars and adhere to other requirements. Washington In 1971 Washington’s legislature began loos- ening its marijuana laws and decreed that pos- session of less than 40 grams would be charged as a misdemeanor. The state legalized medical marijuana in 1998 after a 1995 court case in- volving a terminal cancer patient being treated with marijuana brought extra attention to the issue and set the stage for a citizen-driven bal- lot initiative. In November 1998 state voters approved Initiative 692, known as the Wash- ington State Medical Use of Marijuana Act, with 59 percent in favor. Use, possession, sale, and cultivation of marijuana became legal un- der state law for patients with certain medical conditions that had been verified by a licensed medical professional. Initiative 692 also im- posed dosage limits on the drug’s use. By 2009 an estimated 35,500 Washingtonians had pre- scriptions to buy medical marijuana legally. In November 2012 Washington joined Colo- rado in legalizing recreational marijuana. Vot- ers passed ballot Initiative 502 with 56 percent in support amid an 81 percent voter turnout at the polls. The proposal removed most state prohibitions on marijuana manufacture and commerce, permitted limited marijuana use for adults aged 21 and over, and established the need for a licensing and regulatory framework to gov- ern the state’s marijuana industry. Initiative 502 further imposed a 25 percent excise tax levied three times (on marijuana producers, processors, and retailers) and earmarked the revenue for research, education, healthcare, and substance- abuse prevention, among other purposes.24 Legal possession of marijuana took effect on December 6, 2012. A year and a half later, Wash- ington’s licensing board began accepting appli- cations for recreational marijuana shops. After some backlog, the first four retail stores opened on July 8, 2014. As of June 2016, several hundred retail stores were open across the state. Oregon In October 1973 Oregon became the first state to decriminalize marijuana upon passage of the Oregon Decriminalization Bill. The bill eliminated criminal penalties for possession of up to an ounce of marijuana and downgraded the offense from a “crime” to a “violation” with a fine of $500 to $1,000.25 State law continued to out- law using marijuana in public, growing or selling marijuana, and driving under the influence. In 1997, state lawmakers attempted to recriminalize marijuana and restore jail sentences as punish- ment for possessing less than one ounce, and Or- egon’s governor signed the bill. Activists gathered swiftly against the new law, however, and forced a referendum; the attempt to recriminalize ended up failing by a margin of 2 to 1.26 Oregon medicalized marijuana by ballot initiative in November 1998, with 55 percent support. The Oregon Medical Marijuana Act legalized cultivation, possession, and use of marijuana by prescription for patients with spe- cific medical conditions.27 A new organization was set up to register patients and caregivers. In 2004 voters turned down a ballot proposal to increase to 6 pounds the amount of marijuana a patient could legally possess. Six years later, voters also rejected an effort to permit medi- cal marijuana dispensaries, but the state legis- lature legalized them in 2013.28 As of July 2016, Oregon’s medical marijuana program counted 5“As of June 2016, Oregon had 426 locations where consumers could legally purchase recreational marijuana.” nearly 67,000 registered patients, the vast ma- jority claiming to suffer severe pain, persistent muscle spasms, and nausea.29 Recreational marijuana suffered several de- feats before eventual approval. In 1986 the Or- egon Marijuana Legalization for Personal Use initiative failed with 74 percent of voters op- posed.30 In November 2012, a similar measure also failed, even as neighboring Washington passed its own legalization initiative. Oregon Ballot Measure 80 would have allowed personal marijuana cultivation and use without a license, plus unlimited possession for those over age 21. To oversee the new market, the measure would have established an industry-dominated board to regulate the sale of commercial marijuana. This proposal failed with more than 53 percent of the electorate voting against it.31 Full legalization in Oregon finally passed on November 4, 2014, when voters approved Measure 91, officially known as the Oregon Legalized Marijuana Initiative. This measure legalized recreational marijuana for individu- als over age 21 and permitted possession of up to eight ounces of dried marijuana, along with four plants, with the Oregon Liquor Con- trol Commission regulating sales of the drug. More than 56 percent of voters cast ballots in favor of the initiative, making Oregon the third state in the nation (along with Alaska) to legalize recreational marijuana.32 Oregon’s legislature then adopted several laws to regulate the marijuana industry. Leg- islators passed a 17 percent state sales tax on marijuana retail sales and empowered local jurisdictions to charge their own additional 3 percent sales tax.33 Later, the state legislature gave individual counties the option to ban marijuana sales if at least 55 percent of voters in those counties opposed Measure 91.34 Legal sales went into effect on October 1, 2015. As of June 2016, Oregon had 426 loca- tions where consumers could legally purchase recreational marijuana.35 Alaska Alaska’s debate over marijuana policy be- gan with a 1972 court case. Irwin Ravin, an at- torney, was pulled over for a broken taillight and found to be in possession of marijuana. Ravin refused to sign the traffic ticket while he was in possession of marijuana so that he could challenge the law. Ultimately, the Alaska Su- preme Court deemed marijuana possession in the privacy of one’s home to be constitution- ally protected, and Ravin v. State established legal precedent in Alaska for years to come.36 Alaska’s legislature decriminalized mari- juana in 1975, two years after Oregon. Persons possessing less than one ounce in public—or any amount in one’s own home—could be fined no more than $100, a fine eliminated in 1982. Marijuana opponents, however, mobilized lat- er in the decade as law enforcement busted a number of large, illegal cultivation sites hidden in residences. A voter initiative in November 1990 proposed to ban possession and use of marijuana even in one’s own home, punishable by 90 days of jail time and a $1,000 fine. The initiative passed with 54 percent support.37 In 1998 Alaska citizens spearheaded an initiative to legalize medical marijuana, and 69 percent of voters supported it. Registered patients consuming marijuana for health con- ditions certified by a doctor could possess up to one ounce of marijuana or up to six plants.38 Advocates then turned to recreational le- galization. A ballot initiative in 2000 proposed legalizing use for anyone 18 years and older and regulating the drug “like an alcoholic bever- age.” The initiative failed, with 59 percent of voters opposed. Voters considered a similar ballot measure in 2004 but again rejected it. A third ballot initiative on recreational marijuana legalization passed in November 2014 with 53 percent of voters in support. It permitted adults aged 21 and over to pos- sess, use, and grow marijuana. It also legalized manufacture and sale. The law further created a Marijuana Control Board to regulate the in- dustry and establish excise taxes. State regulators had originally planned to start issuing applications to growers, proces- sors, and stores in early to mid-2016. At the time of this writing, retail marijuana shops are not yet open. This delay, along with data limi- 6“Our analysis examines whether the trends in marijuana use and related outcomes changed substantially after these dates.” tations, makes it difficult to evaluate post-legal- ization outcomes in Alaska. KEY DATES To determine the effect of marijuana legal- ization and similar policies on marijuana use and related outcomes, we examine the trends in use and outcomes before and after key pol- icy changes. We focus mostly on recreational marijuana legalizations, because earlier work has covered other modifications of marijuana policy such as medicalization.39 The specific dates we consider, derived from the discussion above, are as follows: Colorado ■2001, after legalization of medical mari- juana ■2009, after liberalization of the medical marijuana law ■2012, after legalization of recreational marijuana ■2014, after the first retail stores opened under state-level legalization Washington ■1998, after legalization of medical mari- juana ■2012, after legalization of recreational marijuana ■2014, after the first retail stores opened under state-level legalization Oregon ■1998, after legalization of medical mari- juana ■2013, after the state legislature legalized medical marijuana dispensaries ■2014, after legalization of recreational marijuana ■2015, after the first retail stores opened under state-level legalization Alaska ■1990, after voters recriminalized marijuana ■1998, after legalization of medical mari- juana ■2014, after legalization of recreational marijuana Our analysis examines whether the trends in marijuana use and related outcomes changed substantially after these dates. Observed chang- es do not necessarily implicate marijuana policy because other factors might have changed as well. Similarly, the absence of changes does not prove that policy changes had no effect; the abundance of potentially confounding variables makes it possible that, by coincidence, a policy change was approximately offset by some oth- er factor operating in the opposite direction. Thus, our analysis focuses on the factual out- comes of marijuana legalization, rather than on causal inferences. DRUG USE Arguably the most important potential ef- fect of marijuana legalization is on marijuana use or other drug or alcohol use. Opinions dif- fer on whether increased use is problematic or desirable, but because other outcomes depend on use, a key step is to determine how much policy affects use. If such effects are small, then other effects of legalization are also likely to be small. Figure 1 shows past-year use rates in Colo- rado for marijuana and cocaine, along with past-month use rates for alcohol.40 The key fact is that marijuana use rates were increasing modestly for several years before 2009, when medical marijuana became readily available in dispensaries, and continued this upward trend through legalization in 2012. Post-legalization use rates deviate from this overall trend, but only to a minor degree. The data do not show dramatic changes in use rates corresponding to either the expansion of medical marijuana or legalization. Similarly, cocaine exhibits a mild downward trend over the time period but shows no obvious change after marijuana policy changes. Alcohol use shows a pattern similar to marijuana: a gradual upward trend but no obvious evidence of a response to mari- juana policy. 7“The limited available data for Colorado and Alaska show no obvious effect of legalization on youth marijuana use.” Figure 2 graphs the same variables in Wash- ington State. As in Colorado, marijuana, co- caine, and alcohol use proceed along preexist- ing trends after changes in marijuana policy. Figure 3 presents analogous data for Ore- gon.41 Legalization only took effect in 2015 (i.e., after the end of currently available substance use data), inhibiting any measurement of the effect of policy on data observed thus far. How- ever, as in other legalizing states, past-year mar- ijuana use has been rising since the mid-2000s. Figure 4 presents data on current (past- month) marijuana use by youth from the Youth Risk Behavior Survey, a survey of health be- haviors conducted in middle schools and high schools. Data are unfortunately unavailable for Washington and Oregon. The limited available data for Colorado and Alaska show no obvious effect of legalization on youth marijuana use. All those observed patterns in marijuana use might provide evidence for a cultural explanation behind legalization: as marijuana becomes more commonplace and less stigmatized, residents and legislators become less opposed to legalization. In essence, rising marijuana use may not be a con- sequence of legalization, but a cause of it. Consistent with this possibility, Figure 5 plots, for all four legalizing states, data on perceptions of “great risk” from smoking marijuana monthly.42 All four states exhibit a steady downward trend, indicating that fewer people associate monthly marijuana use with high risk. These downward trends predate legalization, consistent with the view that changing attitudes toward marijuana fostered both policy changes and increasing use rates. Interestingly, risk perceptions rose in Colo- rado in 2012–2013, immediately following legal- ization. This rise may have resulted from public safety and anti-legalization campaigns that cau- tioned residents about the dangers of marijuana use. Data on marijuana prices may also shed light on marijuana use. One hypothesis before legaliza- tion was that use might soar because prices would plunge. For example, Dale Gieringer, director of California’s NORML (National Organization for Reform of Marijuana Laws) branch, testified in 2009 that in a “totally unregulated market, the Figure 1Colorado National Survey on Use and Health Results (all respondents, aged 12+) Source: National Survey on Drug Use and Health, Substance Abuse and Mental Health Services Administration (SAMHSA), http://www.samhsa.gov/data/population-data-nsduh/reports?tab=33. 8 Figure 3Oregon National Survey on Drug Use and Health Results (all respondents, aged 12+) Source: National Survey on Drug Use and Health, Substance Abuse and Mental Health Services Administration (SAMHSA), http://www. samhsa.gov/data/population-data-nsduh/reports?tab=33. Figure 2Washington State National Survey on Drug Use and Health Results (all respondents, aged 12+) Source: National Survey on Drug Use and Health, Substance Abuse and Mental Health Services Administration (SAMHSA), http://www. samhsa.gov/data/population-data-nsduh/reports?tab=33. 9 Figure 4Youth Risk Behavior Survey Past Month Marijuana Use Source: Youth Risk Behavior Survey, Centers for Disease Control and Prevention, http://www.cdc.gov/healthyyouth/data/yrbs/data.htm. Figure 5Perception of Risk Source: National Survey on Drug Use and Health, Substance Abuse and Mental Health Services Administration (SAMHSA), http://www.samhsa. gov/data/population-data-nsduh/reports?tab=33. 10 Figure 6Colorado Marijuana Prices Source: Priceofweed.com, http://www.priceofweed.com/prices/United-States/Colorado.html. Source: Priceofweed.com, http://www.priceofweed.com/prices/United-States/Washington.html. Figure 7Washington Marijuana Prices 11“Overall, these data suggest no major drop in marijuana prices after legalization and conse-quently less likelihood of soaring use because of cheaper marijuana.” price of marijuana would presumably drop as low as that of other legal herbs such as tea or tobac- co—on the order of a few dollars per ounce—100 times lower than the current prevailing price of $300 per ounce.”43 A separate study by the Rand Corporation44 estimated that marijuana prices in California would fall by 80 percent after legaliza- tion.45 Using data from Price of Weed (priceof- weed.com), which crowdsources real-time infor- mation from thousands of marijuana buyers in each state, we derive monthly average prices of marijuana in Colorado, Washington, and Oregon.46 See Figures 6, 7, and 8. In Colorado, monthly average prices were declining even before legalization and have re- mained fairly steady since. The cost of high- quality marijuana hovers around $230 per ounce while that of medium-quality marijuana remains around $190. The opening of shops in January 2015 seems to have had little effect. In Washington State, marijuana prices have been similarly steady and have converged almost exactly to Colorado prices—roughly $230 for high-quality marijuana and $200 for medium-quality marijuana. Oregon prices show a rise after legalization, catching up to Colorado and Washington levels. Although we cannot draw a conclusive picture on the basis of consumer-reported data, the convergence of pric- es across states makes sense. This convergence is also consistent with the idea that legalization helped divert marijuana commerce from the black market to legalized retail shops.47 Overall, these data suggest no major drop in marijuana prices af- ter legalization and consequently less likelihood of soaring use because of cheaper marijuana. HEALTH AND SUICIDES Previous studies have suggested a link be- tween medicalization of marijuana and a lower overall suicide rate, particularly among demo- graphics most likely to use marijuana in general (males ages 20 to 39).48 In fact, supporters believe that marijuana can be an effective treatment for Source: Priceofweed.com, http://www.priceofweed.com/prices/United-States/Oregon.html. Figure 8Oregon Marijuana Prices 12 Figure 10Suicide Rates for Males 20–39 Years Old Source: Centers for Disease Control and Prevention, CDC Wonder Portal, http://wonder.cdc.gov/. Figure 9Annual Suicide Rates (per 100,000 people) Source: Centers for Disease Control and Prevention, CDC Wonder Portal, http://wonder.cdc.gov/. 13“Suicide rates in all four states trend slightly upward, but it is difficult to see any associ-ation between marijuana legalization and any changes in these trends.” bipolar disorder, depression, and other mood disorders—not to mention a safer alternative to alcohol. Moreover, the pain-relieving element of medical marijuana may help patients avoid more harmful prescription painkillers and tranquiliz- ers.49 Conversely, certain studies suggest exces- sive marijuana use may increase the risk of de- pression, schizophrenia, unhealthy drug abuse, and anxiety.50 Some research also warns about long-lasting cognitive damage if marijuana is con- sumed regularly, especially at a young age.51 Figure 9 displays the overall yearly suicide rate per 100,000 people in each of the four legalizing states between 1999 and 2014.52 Figure 10 pres- ents the analogous suicide rate for males aged 20 through 39 years.53 Suicide rates in all four states trend slightly upward during the 15-year-long pe- riod, but it is difficult to see any association be- tween marijuana legalization and any changes in these trends. These findings contrast with many previous studies, so it is possible that any effects will take longer to appear. In addition, previous research has suggested a link between medical marijuana and a lower suicide rate; it is not obvi- ous that recreational marijuana would lead to the same result, or that legalization of recreational marijuana after medical marijuana is already le- galized would have much of an extra effect.54 Data on treatment center admissions provide a proxy for drug abuse and other health hazards associated with misuse. Figures 11 and 12 plot rates of annual admissions involving marijuana and alcohol to publicly funded treatment cen- ters in Colorado55 and King County, Washington (which encompasses Seattle).56 Marijuana admis- sions in Colorado were fairly steady over the past decade but began falling in 2013 and 2014, just as legalization took effect. Alcohol admissions began declining around the same time. In King County, admissions for marijuana and alcohol continued their downward trends after legaliza- tion. These patterns suggest that extreme growth in marijuana abuse has not materialized, as some critics had warned before legalization. Figure 11Colorado Treatment Admissions Source: Rocky Mountain High Intensity Drug Trafficking Area (RMHIDTA) report, “The Legalization of Marijuana in Colorado: The Impact” (Vol. 3, September 2015), http://www.rmhidta.org/html/2015%20final%20legalization%20of%20marijuana%20in%20colorado%20the%20impact.pdf. 14 CRIME In addition to substance use and health outcomes, legalization might affect crime. Op- ponents think these substances cause crime through psychopharmacological and other mechanisms, and they note that such substances have long been associated with crime, social de- viancy, and other undesirable aspects of society.57 Although those perspectives first emerged in the 1920s and 1930s, marijuana’s perceived associa- tions with crime and deviancy persist today.58 Before referendums in 2012, police chiefs, governors, policymakers, and concerned citizens spoke up against marijuana and its purported links to crime.59 They also argued that expanding drug commerce could increase marijuana com- merce in violent underground markets and that legalization would make it easy to smuggle the substance across borders where it remained pro- hibited, thus causing negative spillover effects.60 Proponents argue that legalization reduces crime by diverting marijuana production and sale from the black market to legal venues. This shift may be incomplete if high tax rates or sig- nificant regulation keeps some marijuana ac- tivity in gray or black markets, but this merely underscores that more legalization means less crime. At the same time, legalization may re- duce the burden on law enforcement to patrol for drug offenses, thereby freeing budgets and manpower to address larger crimes. Legaliza- tion supporters also dispute the claim that marijuana increases neurological tendencies toward violence or aggression.61 Figure 13 presents monthly crime rates from Denver, Colorado, for all reported violent crimes and property crimes.62 Both metrics remain es- sentially constant after 2012 and 2014; we do not observe substantial deviations from the illustrat- ed cyclical crime pattern. Other cities in Colo- rado mirror those findings. Analogous monthly crime data for Fort Collins, for example, reveal no increase in violent or property crime.63 Figure 14 shows monthly violent and prop- erty crime rates as reported by the Seattle Po- lice Department.64 Both categories of crime Figure 12Treatment Admissions by Drug—King County, Washington Source: University of Washington Alcohol and Drug Abuse Institute, http://adai.washington.edu/pubs/cewg/Drug%20Trends_2014_final.pdf. 15 Figure 13Denver Monthly Crime Rate (violent and property crime rates per 100,000 residents) Source: Denver Police Department, Monthly Crime Reports, https://www.denvergov.org/content/denvergov/en/police-department/ crime-information/crime-statistics-maps.html. Population data source: U.S. Census Bureau Estimates, http://www.census.gov/popest/ data/intercensal/index.html. Source: Seattle Police Department, Online Crime Dashboard, http://www.seattle.gov/seattle-police-department/crime-data/crime- dashboard. Population data source: U.S. Census Bureau Estimates. http://www.census.gov/popest/data/intercensal/index.html. Figure 14Seattle Monthly Crime Rate 16“All told, crime in Seattle has neither soared nor plummeted in the wake of legaliza-tion.” declined steadily over the past 20 years, with no major deviations after marijuana liberalization. Property crime does appear to spike in 2013 and early 2014, and some commentators have posited that legalization drove this increase.65 That connection is not convincing, however, since property crime starts to fall again after the opening of marijuana shops in mid-2014. All told, crime in Seattle has neither soared nor plummeted in the wake of legalization.66 Monthly violent and property crime re- mained steady after legalization in Portland, Or- egon, as seen in Figure 15.67 Portland provides an interesting case because of its border with Wash- ington. Between 2012 and 2014, Portland (and the rest of Oregon) prohibited the recreational use of marijuana, while marijuana sales and consump- tion were fully legal in neighboring Washingto- nian towns just to the north. This situation cre- ates a natural experiment that allows us to look for spillover effects in Oregon. Figure 15 suggests that legalization in Washington and the opening of stores there did not produce rising crime rates across the border. Elsewhere in Oregon, we see no discernible changes in crime trends before and after legalization or medical marijuana liber- alization.68 ROAD SAFETY We next evaluate how the incidence of traf- fic accidents may have changed in response to marijuana policy changes. Previous literature and political rhetoric suggest two contrasting hy- potheses. One holds that legalization increases traffic accidents by spurring drug use and there- by driving under the influence. This hypothesis presumes that marijuana impairs driving abil- ity.69 The opposing theory argues legalization improves traffic safety because marijuana substi- tutes for alcohol, which some studies say impairs driving ability even more.70 Moreover, some con- sumers may be able to drive better if marijuana serves to relieve their pain. Figure 15Portland Monthly Crime Rate Source: Portland Police Bureau Neighborhood Statistics, http://www.portlandonline.com/police/crimestats/. Population data source: U.S. Census Bureau Estimates, http://www.census.gov/popest/data/intercensal/index.html. 17 Figure 16Colorado Car Crashes and Fatality Rate Source: Colorado Department of Transportation, http://www.coloradodot.info/library/traffic/traffic-manuals-guidelines/safety-crash-data/ fatal-crash-data-city-county/fatal-crashes-by-city-and-county/. Figure 17Washington Car Crashes and Fatality Rate Source: Washington Traffic Safety Commission, Quarterly Target Zero Reports, http://wtsc.wa.gov/research-data/quarterly-target-zero- data/. 18 Rhetoric from experts and government of- ficials has been equally divided. Kevin Sabet, a former senior White House drug policy adviser, warned that potential consequences of Colora- do’s legalization could include large increases in traffic accidents.71 A recent Associated Press ar- ticle noted that “fatal crashes involving marijuana doubled in Washington after legalization.”72 Yet Coloradan law enforcement agents are them- selves unsure whether legal marijuana has led to an increase in accidents.73 Research by Radley Balko, an opinion blogger for the Washington Post and an author on drug policy, claims that, overall, “highway fatalities in Colorado are at near-historic lows” in the wake of legalization.74 Figure 16 presents the monthly rate of fatal accidents and fatalities per 100,000 residents in Colorado.75 No spike in fatal traffic acci- dents or fatalities followed the liberalization of medical marijuana in 2009.76 Although fa- tality rates have reached slightly higher peaks in recent summers, no obvious jump occurs after either legalization in 2012 or the open- ing of stores in 2014.77 Likewise, neither mari- juana milestone in Washington State appears to have substantially affected the fatal crash or fatality rate, as illustrated in Figure 17.78 In fact, more granular statistics reveal that the fatality rate for drug-related crashes was virtu- ally unchanged after legalization.79 Figure 18 depicts the crash fatality rate in Oregon.80 Although few post-legalization data were available at the time of publication, we observe no signs of deviations in trend after the opening of medical marijuana dispensaries in 2013. We can also test for possible spillover ef- fects from neighboring Washington. Legaliza- tion there in 2012 and the opening of marijuana shops in 2014 do not seem to materially affect road fatalities in Oregon in either direction. Finally, Figure 19 presents annual data on crash fatality rates in Alaska; these show no discernible increase after legalization and may even decline slightly. Figure 18Oregon Car Crash Fatality Rate Source: Oregon Department of Transportation, online Crash Summary Reports and in-person data request. Special thanks to Theresa Heyn and Coleen O’Hogan, http://www.oregon.gov/ODOT/TD/TDATA/pages/car/car_publications.aspx. 19 YOUTH OUTCOMES Much of the concern surrounding marijuana legalization relates to its possible effect on youths. Many observers, for example, fear that expanded legal access—even if officially limited to adults age 21 and over—might increase use by teenagers, with negative effects on intelligence, educational outcomes, or other youth behaviors.81, 82 Figure 20 displays the total number of school suspensions and drug-related suspensions in Col- orado public high schools during each academic year.83 Total suspensions trend downward over time, with a slight bump after 2014, but that bump was not one driven by drug-related causes. Drug- related suspensions appear to rise after medical marijuana commercialization in 2009 but stay level after full legalization and the opening of re- tail shops. Figure 21 shows public high school ex- pulsions, both overall and drug-related. It reveals a parallel bump in drug-related expulsions right after marijuana liberalization in 2009, but expul- sions drop steeply thereafter. In fact, by 2014, ex- pulsions drop back to their previous levels. We also consider potential effects on aca- demic performance. Standardized test scores measuring the reading proficiency of 8th and 10th graders in Washington State show no indication of significant positive or negative changes caused by legalization, as illustrated in Figure 22.84 Although some studies have found that frequent marijuana use impedes teen cog- nitive development, our results do not suggest a major change in use, thereby implying no major changes in testing performance. ECONOMIC OUTCOMES Changing economic and demographic out- comes are unlikely to be significant effects of marijuana legalization, simply because marijua- na is a small part of the overall economy. Nev- ertheless, we consider this outcome for com- pleteness. Before legalization, many advocates thought that legalization could drive a robust influx of residents, particularly young individu- als enticed to move across state lines to take ad- Figure 19Alaska Car Crashes and Fatalities Source: Alaska Highway Safety Office, http://www.dot.state.ak.us/stwdplng/hwysafety/fars.shtml. 20 Figure 20School Suspensions—Colorado Source: Colorado Department of Education, 10-Year Trend Data, http://www.cde.state.co.us/cdereval/suspend-expelcurrent. Figure 21School Expulsions—Colorado Source: Colorado Department of Education, http://www.cde.state.co.us/cdereval/suspend-expelcurrent. 21 vantage of loose marijuana laws. More recently, various news articles say housing prices in Col- orado (particularly around Denver) are soaring at growth rates far above the national average, perhaps as a consequence of marijuana legaliza- tion. One analyst went so far as to say that mari- juana has essentially “kick-started the recovery of the industrial market in Denver” and led to record-high rent levels.85 Figure 23 sheds doubt on these extreme claims by presenting the Case-Shiller Home Price Index for Denver, Seattle, and Portland, along with the national average.86 Data show that home prices in all three cities have been rising steadily since mid-2011, with no apparent booms after mari- juana policy changes. Housing prices in Denver did rise at a robust rate after January 2014, when marijuana shops opened, but this increase was in step with the national average. Furthermore, marijuana legalization in all four legalizing states had, at most, a trivial ef- fect on population growth.87 Whereas some people may have moved across states for mari- juana purposes, any resulting growth in popu- lation has been small and unlikely to cause noticeable increases in housing prices or total economic output. Advocates also argue that legalization boosts economic activity by creating jobs in the mari- juana sector, including “marijuana tourism” and other support industries, thereby boost- ing economic output.88 Marijuana production and commerce do employ many thousands of people, and Colorado data provide some hint of a measurable effect on employment. As Fig- ure 24 indicates, the seasonally adjusted unem- ployment rate began to fall more dramatically after the start of 2014, which coincides with the opening of marijuana stores.89 These gains, however, have yet to be seen in Washington, Or- egon, and Alaska. One hypothesis may be that Colorado, as the first state to open retail shops, benefitted from a “first mover advantage.” If more states legalize, any employment gains will become spread out more broadly, and marijuana tourism may diminish. Figure 22Washington Standardized Test Scores Source: Washington State Office of the Superintendent of Public Instruction, http://reportcard.ospi.k12.wa.us/. 22 Figure 23Case Shiller Home Price Index Source: S&P Core Logic Case-Shiller Home Price Indices, http://us.spindices.com/index-family/real-estate/sp-corelogic-case-shiller. Figure 24Unemployment Rates Source: Bureau of Labor Statistics, Local Area Unemployment Statistics, http://www.bls.gov/lau/. Note: Rates are seasonally adjusted. 23 Figure 25Marijuana Tax Revenues—Colorado (all values are nominal) Source: Colorado Department of Revenue, https://www.colorado.gov/pacific/revenue/colorado-marijuana-tax-data. Figure 26Marijuana Tax Revenues—Washington (all values are nominal) Source: Washington State Department of Revenue, http://dor.wa.gov/Content/AboutUs/StatisticsAndReports/stats_MMJTaxes.aspx; Initiative 502 Data, http://www.502data.com/. 24 Figure 27State Correctional Expenditures (all values are nominal) Source: United States Census Bureau, American FactFinder Database, http://factfinder.census.gov/. Figure 28State Police Protection Expenditures (all values are nominal) Source: United States Census Bureau, American FactFinder Database, http://factfinder.census.gov/. 25“One area where legal marijuana has reaped unexpectedly large benefits is state tax revenue.” Data from the Bureau of Economic Analysis show little evidence of significant gross domes- tic product (GDP) increases after legalization in any state.90 Although it is hard to disentan- gle marijuana-related economic activity from broader economic trends, the surges in eco- nomic output predicted by some proponents have not yet materialized. Similarly, no clear changes have occurred in GDP per capita. One area where legal marijuana has reaped unexpectedly large benefits is state tax revenue. Colorado, Washington, and Oregon all impose significant excise taxes on recreational marijuana, along with standard state sales taxes, other local taxes, and licensing fees. As seen in Figure 25, Col- orado collects well over $10 million per month from recreational marijuana alone.91 In 2015 the state generated a total of $135 million in recre- ational marijuana revenue, $35 million of which was earmarked for school construction projects. These figures are above some pre-legalization forecasts, although revenue growth was disap- pointingly sluggish during the first few months of sales.92 A similar story has unfolded in Washing- ton, as illustrated in Figure 26, where recreational marijuana generated approximately $70 million in tax revenue in the first year of sales93—double the original revenue forecast.94 Oregon only began taxing recreational marijuana in January 2016, so data are still preliminary; however, state officials report revenues of $14.9 million so far, well above the initial estimate of $2.0 million to $3.0 million for the entire calendar year.95 The tax revenues in these states may decline. Limited post-legalization data prevent us from ruling out small changes in marijuana use or other outcomes. As additional post-legal- ization data become available, expanding this analysis will continue to inform the debate. The data so far provide little support for the strong claims about legalization made by ei- ther opponents or supporters. NOTES 1. In November 2014, the District of Columbia voted overwhelmingly in favor of Initiative 71, which legalized the use, possession, and cultiva- tion of limited amounts of marijuana in the pri- vacy of one’s home. It also permitted adults age 21 and over to “gift”—or transfer—up to two ounces of marijuana provided no payment or other ex- change of goods or services occurred. Selling mar- ijuana or consuming it in public, however, remain criminal violations. In addition, because of ongo- ing federal prohibition, marijuana remains illegal on federal land, which makes up 30 percent of the District. Therefore, we do not examine data for D.C. For more, see http://mpdc.dc.gov/marijuana. 2. In June 2016, the California secretary of state an- nounced that a ballot referendum on marijuana legal- ization would occur in November, after a state cam- paign amassed enough signatures to put the question to a vote. Other likely candidates include Arizona, Florida, Maine, Massachusetts, Michigan, Missouri, Nevada, New York, Rhode Island, and Vermont. Or- ganizations and private citizens in additional states have raised the idea of ballot initiatives but have not yet garnered the requisite signatures to hold a vote. See Jackie Salo, “Marijuana Legalization 2016: Which States Will Consider Cannabis This Year,” Interna- tional Business Times, December 30, 2015, http://www. ibtimes.com/marijuana-legalization-2016-which- states-will-consider-cannabis-year-2245024. 3. Ethan Nadelmann, for example, has asserted that legalization is a “smart” move that will help end mass incarceration and undermine illicit criminal organizations. See Nadelmann, “Marijuana Legal- ization: Not If, But When,” HuffingtonPost.com, November 3, 2010, http://www.huffingtonpost. com/ethannadelmann/marijuana-legalization- no_b_778222.html. Former New Mexico governor and current Lib- ertarian Party presidential candidate Gary Johnson has also advocated marijuana legalization, predicting that the measure will lead to less overall substance abuse because individuals addicted to alcohol or other substances will find marijuana a safer alternative. See Kelsey Osterman, “Gary Johnson: Legalizing Mari- juana Will Lead to Lower Overall Substance Abuse,” RedAlertPolitics.com, April 24, 2013, http://redalertpo litics.com/2013/04/24/gary-johnson-legalizing-mar ijuana-will-lead-to-less-overall-substance-abuse/. 26 Denver Police Chief Robert White argues that violent crime dropped almost 9 percent in 2012. See Sadie Gurman, “Denver’s Top Law Enforce- ment Officials Disagree: Is Crime Up or Down?” Denver Post, January 22, 2014, http://www.denver post.com/2014/01/22/denvers-top-law-enforce ment-officers-disagree-is-crime-up-or-down/. 4. Colorado governor John Hickenlooper (D) opposed initial efforts to legalize marijuana be- cause he thought the policy would, among other things, increase the number of children using drugs. See Matt Ferner, “Gov. John Hickenlooper Oppos- es Legal Weed,” HuffingtonPost.com, September 12, 2012, http://www.huffington post.com/2012/09/12/ gov-john-hickenlooper-opp_n_1879248.html. Former U.S. attorney general Edwin Meese III, who is now the Heritage Foundation’s Ron- ald Reagan Distinguished Fellow Emeritus, and Charles Stimson have argued that violent crime surges when marijuana is legally abundant and that the economic burden of legalization far out- strips the gain. See Meese and Stimson, “The Case against Legalizing Marijuana in California,” Heri- tage Foundation, October 3, 2010, http://www. heritage.org/research/commentary/2010/10/the- case-against-legalizing-marijuana-in-california. Kevin Sabet, a former senior White House drug policy adviser in the Obama administration, has called Colorado’s marijuana legalization a mis- take, warning that potential consequences may include high addiction rates, spikes in traffic acci- dents, and reductions in IQ. See Sabet, “Colorado Will Show Why Legalizing Marijuana Is a Mis- take,” Washington Times, January 17, 2014, http:// www.washingtontimes.com/news/2014/jan/17/ sabet-marijuana-legalizations-worst-enemy/. The former director of the Drug Enforcement Administration, John Walters, claims that “what we [see] in Colorado has the markings of a drug use epidemic.” He argues that there is now a thriv- ing black market in marijuana in Colorado and that more research on marijuana’s societal effects needs to be completed before legalization should be considered. See Walters, “The Devastation That’s Really Happening in Colorado,” Weekly Standard, July 10, 2014, http://www.weeklystandard .com/the-devastation-thats-really-happening-in- colorado/article/796308. John Walsh, the U.S. attorney for Colorado, de- fended the targeted prosecution of medical mari- juana dispensaries located near schools by citing figures from the Colorado Department of Educa- tion showing dramatic increases in drug-related school suspensions, expulsions, and law enforce- ment referrals between 2008 and 2011. See John Ingold, “U.S. Attorney John Walsh Justifies Fed- eral Crackdown on Medical-Marijuana Shops,” Denver Post, January 20, 2012, http://www.denver post.com/2012/01/19/u-s-attorney-john-walsh- justifies-federal-crackdown-on-medical-marijuana- shops-2/. Denver District Attorney Mitch Morrissey points to the 9 percent rise in felony cases submit- ted to his office during the 2008–11 period, after Colorado’s marijuana laws had been partially lib- eralized, as evidence of marijuana’s social effects. See Sadie Gurman, “Denver’s Top Law Enforce- ment Officials Disagree: Is Crime Up or Down?” Denver Post, January 22, 2014, http://www.denver- post.com/2014/01/22/denvers-top-law-enforce- ment-officers-disagree-is-crime-up-or-down/. Other recent news stories that report criticisms of marijuana liberalization include Jack Healy, “After 5 Months of Legal Sale, Colorado Sees the Downside of a Legal High,” New York Times, May 31, 2014, http://www.nytimes.com/2014/06/01/us/ after-5-months-of-sales-colorado-sees-the-down- side-of-a-legal-high.html, and Josh Voorhees, “Go- ing to Pot, Slate.com, May 21, 2014, http://www.slate. com/articles/news_and_politics/politics/2014/05/ colorado_s_pot_experiment_the_unintended_ consequences_of_marijuana_legalization.html. Also, White House policy research indicates that marijuana is the drug most often linked to crime. See Rob Hotakainen, “Marijuana Is Drug Most Often Linked to Crime,” McClatchy News Service, May 23, 2013, http://www.mcclatchydc. com/news/politics-government/article24749413. html. 5. MacCoun et al. (2009) review the decriminaliza- tion literature from the first wave of decriminaliza- tions in the 1970s, noting a lack of response. See MacCoun et al.,“Do Citizens Know Whether Their State Has Decriminalized Marijuana? Assessing the 27 Perceptual Component of Deterrence Theory.” Re- view of Law and Economics 5 (2009): 347–71. Analysis of the recent U.S. state legalizations is more limited. Some noteworthy studies include Jeffrey Miron, “Marijuana Policy in Colorado,” Cato Insti- tute Working Paper no. 24, 2014; Andrew A. Monte et al., “The Implications of Marijuana Legalization in Colorado,” Journal of the American Medical Asso- ciation 313, no. 3 (2015): 241–42; Stacy Salomonsen- Sautel et al., “Trends in Fatal Motor Vehicle Crash- es Before and After Marijuana Commercializa- tion in Colorado,” Drug and Alcohol Dependence 140 (2014): 137–44, which found a statistically sig- nificant uptick in drivers involved in a fatal motor vehicle crash after commercialization of medical marijuana in Colorado; Beau Kilmer et al., “Altered State?: Assessing How Marijuana Legalization in California Could Influence Marijuana Consump- tion and Public Budgets,” Occasional Paper, Rand Drug Policy Research Center, Santa Monica, CA, 2010; Angela Hawken et al., “Quasi-Legal Cannabis in Colorado and Washington: Local and National Implications,” Addiction 108, no. 5 (2013): 837–38; and Howard S. Kim et al., “Marijuana Tourism and Emergency Department Visits in Colorado,” New England Journal of Medicine, 374 (2016): 797–98. For an analysis of whether Colorado has im- plemented its legalization in a manner consistent with the law, see John Hudak, “Colorado’s Rollout of Legal Marijuana Is Succeeding,” Governance Studies Series, Brookings Institution, Washing- ton, D.C., July 31, 2014, http://www.brookings. edu/~/media/research/files/papers/2014/07/colo rado-marijuana-legalization-succeeding/cepm mjcov2.pdf. International evidence from Portu- gal (Glenn Greenwald, “Drug Decriminalization in Portugal,” Cato Institute White Paper, 2009, http://object.cato.org/sites/cato.org/files/pubs/ pdf/greenwald_whitepaper.pdf), the Netherlands (Robert J. MacCoun, “What can we learn from the Dutch cannabis coffeeshop system,” Addic- tion 2011: 1-12 and Ali Palali and Jan C. van Ours, “Distance to Cannabis Shops and Age of Onset of Cannabis Use,” Health Economics 24, 11 (2015): 1482-1501, parts of Australia (Jenny Williams and Anne Line Bretteville-Jensen, “Does Liberalizing Cannabis Laws Increase Cannabis Use?” Journal of Health Economics 36 (2014): 20-32) and parts of London (Nils Braakman and Simon Jones, “Can- nabis Depenalization, Drug Consumption and Crime–Evidence from the 2004 Cannabis Declas- sification in the UK,” Social Science and Medicine 115(2014): 29-37) suggest little to no effects of these laws on drug use. Jérôme Adda et al., “Crime and the Depenalization of Cannabis Possession: Evidence from a Policing Experiment,” Journal of Political Economy, 122, no. 5 (2014): 1130-1201 con- sider depenalization in a London borough, find- ing declines in crime caused by the police shifting enforcement to non-drug crime. 6. Opium, cocaine, coca leaves, and other deriva- tives of coca and opium had been essentially out- lawed in 1914 by the Harrison Narcotic Act. See C. E. Terry, “The Harrison Anti-Narcotic Act,” American Journal of Public Health 5, no. 6 (1915): 518, http://www.ncbi.nlm.nih.gov/pmc/articles/PMC 1286619/?page=1. 7. “When and Why Was Marijuana Outlawed,” Schaffer Library of Drug Policy, http://druglibrary. org/schaffer/library/mj_outlawed.htm. 8. Ibid. 9. Mathieu Deflem, ed., Popular Culture, Crime, and Social Control, vol. 14, Sociology of Crime, Law and Deviance (Bingley, UK: Emerald Group Publishing, 2010), p. 13, https://goo.gl/ioAoVY. 10. Kathleen Ferraiolo, “From Killer Weed to Popular Medicine: The Evolution of Drug Control Policy, 1937–2000,” The Journal of Policy History 19 (2007): 147–79, https://muse.jhu.edu/article/ 217587. 11. David Musto, “Opium, Cocaine and Marijuana in American History,” Scientific American 20-27 (July 1991), http://www.ncbi.nlm.nih.gov/pubmed/1882226. 12. United Nations Office on Drugs and Crime, “Traffic in Narcotics, Barbiturates and Amphet- amines in the United States,” https://www.unodc. org/unodc/en/data-and-analysis/bulletin/bulle- tin_1956-01-01_3_page005.html. 13. “Drug Schedules,” U.S. Drug Enforcement 28 Administration, https://www.dea.gov/druginfo/ ds.shtml. 14. The 11 states were Oregon (1973), Alaska (1975), California (1975), Colorado (1975), Maine (1975), Minnesota (1976), Ohio (1976), Mississippi (1977), New York (1977), North Carolina (1977), and Ne- vada (1978). See Rosalie Pacula et al., “Marijuana Decriminalization: What Does It Mean for the United States?” (National Bureau of Economic Research Working Paper no. 9690, NBER and RAND Corporation, Cambridge, MA, January 2004), http://www.rand.org/content/dam/rand/ pubs/working_papers/2004/RAND_WR126.pdf. 15. Not all states followed such a straightforward path towards marijuana liberalization. Alaska, for example, decriminalized marijuana use and posses- sion in one’s home in 1975. In 1990, however, a voter initiative recriminalized possession and use of mari- juana. See the section on Alaska for more details. 16. “States That Have Decriminalized,” National Organization for the Reform of Marijuana Laws, http://norml.org/aboutmarijuana/item/states- that-have-decriminalized. 17. “The Legalization of Marijuana in Colorado: The Impact. A Preliminary Report,” Rocky Moun- tain HIDTA 1 (August 2013): 3, http://www.rm hidta.org/html/final%20legalization%20of%20 mj%20in%20colorado%20the%20impact.pdf. 18. David Ogden, the deputy attorney general at the time, issued a memorandum stating it would be unwise to “focus federal resources . . . on indi- viduals whose actions are in clear and unambiguous compliance with existing state law providing for the medical use of marijuana.” See “Memorandum for Selected United State Attorneys on Investigations and Prosecutions in States Authorizing the Medical Use of Marijuana,” U.S. Department of Justice, Oc- tober 19, 2009. https://www.justice.gov/opa/blog/ memorandum-selected-united-state-attorneys- investigations-and-prosecutions-states. 19. The Ogden Memorandum did not perma- nently resolve confusion about the role of federal law in state marijuana policy. In 2011, the Depart- ment of Justice issued another memo entitled the “Cole Memo” which somewhat backpedaled on the Ogden Memo’s position; it cautioned that “the Ogden Memorandum was never intended to shield such activities from federal enforcement ac- tion and prosecution, even where those activities purport to comply with state law.” It was not until 2013 when those in the marijuana industry received a clear answer. A third memo unambiguously out- lined the eight scenarios in which federal authori- ties would enforce marijuana laws in states where the substance was legal. Beyond those eight priori- ties, the federal government would leave marijuana law enforcement to local authorities. For more, see “Guidance Regarding the Ogden Memo in Juris- dictions Seeking to Authorize Marijuana for Medi- cal Use,” U.S. Department of Justice, June 29, 2011, https://www.justice.gov/sites/default/files/oip/ legacy/2014/07/23/dag-guidance-2011-for-medical- marijuana-use.pdf. See also “Guidance Regarding Marijuana Enforcement,” U.S. Department of Jus- tice, August 29, 2013, https://www.justice.gov/iso/ opa/resources/30520 13829132756857467.pdf. 20. “The Legalization of Marijuana in Colorado: The Impact. A Preliminary Report,” Rocky Moun- tain HIDTA 1 (August 2013): 4, http://www.rm hidta.org/html/final%20legalization%20of%20 mj%20in%20colorado%20the%20impact.pdf. 21. “Amendment 64: Use and Regulation of Mari- juana,” City of Fort Collins, Colorado, http:// www.fcgov.com/mmj/pdf/amendment64.pdf. 22. Ibid. 23. Numerous counties, including Denver County and others, have enacted local taxes on top of state taxes. In Denver, retail marijuana products are subject to a local sales tax of 3.65 percent in addi- tion to a special marijuana tax of 3.5 percent. See “City and County of Denver, Colorado: Tax Guide, Topic No. 95,” City of Denver (revised April 2015), https://www.denvergov.org/Portals/571/documents/ TaxGuide/Marijuana-Medical_and_Retail.pdf. 24. This system of three separate taxes was eventu- 29 ally replaced by a single, 37 percent excise tax levied at the retail point of sale in July 2015. See “FAQs on Taxes,” Washington State Liquor and Cannabis Board, http://www.liq.wa.gov/mj2015/faqs-on- taxes. See also Rachel La Corte, “Washington State Pot Law Overhaul: Marijuana Tax Reset at 37 Per- cent,” Associated Press, The Cannabist, July 1, 2015, http://www.thecannabist.co/2015/07/01/washing- ton-state-pot-law-overhaul-marijuana-tax-reset-at- 37-percent/37238/. 25. “State by State Laws: Oregon,” National Orga- nization for the Reform of Marijuana Laws, 2006, http://norml.org/laws/item/oregon-penalties-2. 26. See “Oregon Legislature Ends 24 Years of Mari- juana Decriminalization,” National Organization for the Reform of Marijuana Laws, news release, July 3, 1997, http://norml.org/news/1997/07/03/ oregon-legislature-ends-24-years-of-marijuana- decrimnalization/. See also “State by State Laws: Oregon,” National Organization for the Reform of Marijuana Laws, 2006. 27. “Medical Marijuana Rules and Statutes: Or- egon Medical Marijuana Act,” Oregon Health Authority, June 2016, http://public.health.oregon. gov/DiseasesConditions/ChronicDisease/Medical MarijuanaProgram/Pages/legal.aspx#ors. 28. “Oregon Medical Marijuana Allowance Mea- sure 33 (2004),” Ballotpedia, https://ballotpedia. org/Oregon_Medical_Marijuana_Allowance_ Measure_33_(2004). 29. “Oregon Medical Marijuana Program Statis- tics,” Oregon Health Authority, July 2016, https:// public.health.oregon.gov/diseasesconditions/ chronicdisease/medicalmarijuanaprogram/pages/ data.aspx. 30. “Oregon Marijuana Legalization for Personal Use, Ballot Measure 5 (1986),” Ballotpedia, https:// ballotpedia.org/Oregon_Marijuana_Legalization_ for_Personal_Use,_Ballot_Measure_5_(1986). 31. “Oregon Cannabis Tax Act Initiative, Measure 80 (2012),” Ballotpedia, https://ballotpedia.org/Oregon_ Cannabis_Tax_Act_Initiative,_Measure_80_(2012). 32. “Measure 91,” Oregon Liquor Control Com- mission, https://www.oregon.gov/olcc/marijuana/ Documents/Measure91.pdf. 33. Several counties in Oregon have enacted their own local taxes. 34. As of June 2016, 87 municipalities and 19 coun- ties in Oregon had prohibited recreational marijua- na businesses or producers in their jurisdiction. See “Record of Cities/Counties Prohibiting Licensed Recreational Marijuana Facilities,” Oregon Liquor Control Commission, https://www.oregon.gov/ olcc/marijuana/Documents/Cities_Counties_RMJ OptOut.pdf. 35. “Medical Marijuana Dispensary Directory,” Oregon Health Authority http://www.oregon.gov/ oha/mmj/Pages/directory.aspx. 36. Ravin v. State, 537 F.2d 494 (Alaska 1975). 37. “Alaska Marijuana Criminalization Initiative, Measure 2 (1990),” Ballotpedia, https://ballotpedia. org/Alaska_Marijuana_Criminalization_Initiative_ Measure_2_(1990). 38. “Ballot Measure 8: Bill Allowing Medical Use of Marijuana,” Alaska Division of Elections, http:// www.elections.alaska.gov/doc/oep/1998/98bal8. htm. 39. Recent work includes the following: D. Mark Anderson et al., “Medical Marijuana Laws and Suicides by Gender and Age,” American Journal of Public Health 104, no. 1 (December 2014): 2369–76; D. Mark Anderson et al., “Medical Marijuana Laws and Teen Marijuana Use,” American Law and Eco - nomic Review 17, no. 2 (2015): 495–528; Choo, Esther K et al., “The Impact of State Medical Marijuana Legislation on Adolescent Marijuana Use,” Journal of Adolescent Health, forthcoming. Yu-Wei Luke Chu, “Do Medical Marijuana Laws Increase Hard-Drug Use?” Journal of Law and Eco- nomics 58, no. 2 (May 2015): 481–517; Gorman, Dennis M. and J. Charles Huber, Jr. “Do Medical Cannabis 30 Laws Encourage Cannabis Use?” The International Journal of Drug Policy, 18, no. 3 (Ma7 2007): 160–67; S. Harper et al., “Do Medical Marijuana Laws In- crease Marijuana Use? Replication Study and Ex- tension,” Annals of Epidemiology 22(2012): 207-212; Sarah D. Lynne-Landsman et al., “Effects of State Medical Marijuana Laws on Adolescent Marijuana Use,” American Journal of Public Health, 103(2013): 1500-1506; Karen O’Keefe and Mitch Earleywine, “Marijuana Use by Young People: The Impact of State Medical Marijuana Laws,” manuscript, Mari- juana Policy Project (2011) and Hefei Wen et al., “The Effect of Medical Marijuana Laws on Mari- juana, Alcohol, and Hard Drug Use,” NBER Work- ing Paper no. 20085, National Bureau of Economic Research, Cambridge, MA, 2014, which found that medical marijuana laws led to a relatively small in- crease in marijuana use by adults over age 21 and did nothing to change use of hard drugs. Rosalie Liccardo Pacula et al., “Assessing the Effects of Medical Marijuana Laws on Marijuana and Alcohol Use: The Devil Is in the Details,” NBER Working Paper no. 19302, National Bu- reau of Economic Research, Cambridge, MA, 2015, found that legalizing home cultivation and medical marijuana dispensaries were associated with higher marijuana use, while other aspects of medical marijuana liberalization were not. Choo et al., “The Impact of State Medical Mari- juana Legislation on Adolescent Marijuana Use,” Journal of Adolescent Health 55, no. 2 (2014): 160–66, found no statistically significant differences in adolescent marijuana use after state-level medical marijuana legalization. 40. Data are reported as two-year averages. Data are from “National Survey on Drug Use and Health 2002–2014,” Center for Behavioral Health Sta- tistics and Quality, Substance Abuse and Mental Health Services Administration, http://www.icpsr. umich.edu/icpsrweb/content/SAMHDA/help/ nsduh-estimates.html. 41. No post-legalization data were available for Alaska. 42. State-level data from “National Survey on Drug Use and Health, 2002–2014,” Center for Behavioral Health Statistics and Quality. 43. Dale H. Gieringer, director, California NORML, “Testimony on the Legalization of Marijuana,” Testimony before the California As- sembly Committee on Public Safety, October 28, 2009, http://norml.org/pdf_files/AssPubSafety_ Legalization.pdf. 44. Rand Corporation, “Legalizing Marijuana in California Would Sharply Lower the Price of the Drug,” news release, July 7, 2007, http://www.rand. org/news/press/2010/07/07.html. 45. These analyses consider legalization at both the federal and state levels which would allow ad- ditional avenues for lower prices such as economies of scale, although also additional avenues for higher prices because of federal taxation and advertising. 46. The website Price of Weed allows anyone to submit anonymous data about the price, quantity, and quality of marijuana he or she purchases, as well as where the marijuana was purchased. Founded in 2010, the website has logged hundreds of thousands of entries across the country, and many analysts and journalists look to it as a source of marijuana price data. It has obvious limitations: the data are not a random sample; the consumer reports do not dis- tinguish between marijuana bought through legal means and through the black market; self-reported data may not be accurate; and the data are probably from a self-selecting crowd of marijuana enthusi- asts. Nevertheless, Price of Weed provides large samples of real-time data. To reduce the impact of inaccurate submissions, the website automatically removes the bottom and top 5 percent of outliers when calculating its average prices. We were not able to calculate meaningful marijuana price aver- ages from Alaska because of a relatively low num- ber of entries from that state. 47. One further trend we observe in all three states is a widening price gap between high-qual- ity and medium-quality marijuana. Among other things, this gap may be the result of fewer infor- mation asymmetries in the marijuana market. On the black market, it can be hard to know the true 31 quality of a product. Marijuana trade is complex, with hundreds of different strains and varieties. Yet in the black market, consumers often have a difficult time differentiating between them and may end up paying similarly high prices for medi- um- and high-quality marijuana. In all three states, the gap between the prices rose after legalization, suggesting that consumers have had an easier time distinguishing between different qualities and strains of marijuana. 48. Anderson, Rees, and Sabia, “Medical Marijua- na Laws and Suicides by Gender and Age.” 49. D. Mark Anderson et al., “High on Life?: Medi- cal Marijuana and Suicide,” Cato Institute Research Briefs in Economic Policy, no. 17, January 2015, http://www.southerncannabis.org/wp-content/up loads/2015/01/marijuana-suicide-study.pdf. David Powell et al., “Do Medical Marijuana Laws Reduce Addictions and Deaths Related to Pain Killers?” NBER Working Paper no. 21345, National Bureau of Economic Research, Cam- bridge, MA, July 2015. 50. See, for example, Zammit et al., “Self-reported Cannabis Use as a Risk Factor for Schizophrenia in Swedish Conscripts of 1969,” British Medical Jour- nal 325 (2002); Henquet et al., “Prospective Cohort Study of Cannabis Use, Predisposition for Psycho- sis, and Psychotic Symptoms in Young People,” British Medical Journal (December 2004); Gold- berg, “Studies Link Psychosis, Teenage Marijuana Use,” Boston Globe, January 26, 2006; Shulman, “Marijuana Linked to Heart Disease and Depres- sion,” U.S. News, May 14, 2008. See also Jan C. van Ours et al., “Cannabis Use and Suicidal Ideation,” Journal of Health Economics 32, no. 3 (2013): 524–37; Jan C. van Ours and Jenny Williams, “The Effects of Cannabis Use on Physi- cal and Mental Health,” Journal of Health Econom- ics 31, no. 4 (July 2012): 564–77; Jan C. van Ours and Jenny Williams, “Cannabis Use and Mental Health Problems,” Journal of Applied Econometrics 26, no. 7 (November 2011): 1137–56; and Jenny Williams and Christopher L. Skeels, “The Impact of Cannabis Use on Health,” De Economist 154, no. 4 (December 2006): 517–46. 51. National Institute on Drug Abuse, “What Are Marijuana’s Long-Term Impacts on the Brain?” Research Report Series, March 2016, https://www. drugabuse.gov/publications/research-reports/mar ijuana/how-does-marijuana-use-affect-your-brain- body. Kelly and Rasul evaluate the depenalization of marijuana in a London borough and find large in- creases in hospital admissions related to hard drug use, particularly among younger men. See Elaine Kelly and Imran Rasul, “Policing Cannabis and Drug Related Hospital Admissions: Evidence from Administrative Records,” Journal of Public Economics 112 (April 2014): 89–114. 52. “Detailed Mortality Statistics,” Centers for Dis- ease Control and Prevention, WONDER Online Databases, http://wonder.cdc.gov/. 53. Ibid. 54. The link between medical marijuana and low- er suicide rates may stem partly from the fact that medical marijuana can substitute for other, more dangerous painkillers and opiates. Research by Anne Case and Angus Deaton found suicides and drug poisonings led to a marked increase in mor- tality rates of middle-aged white non-Hispanic men and women in the United States between 1999 and 2013. Other studies have linked opioid and painkiller overdoses to a recent surge in self- inflicted drug-related deaths and suicides. Medi- cal marijuana, as a less risky pain reliever, may thus help lessen the rate of drug deaths and suicides. For more, see Case and Deaton, “Rising Morbid- ity and Mortality in Midlife among White Non- Hispanic Americans in the 21st Century,” National Academy of Sciences 112, no. 49 (November 2015), http://www.pnas.org/content/112/49/15078. 55. Kevin Wong and Chelsey Clarke, The Legal- ization of Marijuana in Colorado: The Impact Vol. 3 (Denver: Rocky Mountain High Intensity Drug Trafficking Area, September 2015), http://www. rmhidta.org/html/2015%20final%20legaliza tion%20of%20marijuana%20in%20colorado %20the%20impact.pdf. 56. Caleb Banta-Green et al., “Drug Abuse 32 Trends in the Seattle-King Country Area: 2014,” Report, University of Washington Alcohol and Drug Abuse Institute, Seattle, June 17, 2015, http://adai.washington.edu/pubs/cewg/Drug%20 Trends_2014_final.pdf. 57. David Musto, “Opium, Cocaine and Marijua- na in American History,” Scientific American, no. 1 (July 1991): 40–47, http://www.ncbi.nlm.nih.gov/ pubmed/1882226. 58. U.S. Drug Enforcement Administration, “The Dangers and Consequences of Marijuana Abuse,” U.S. Department of Justice, Washington, May 2014, p. 24, https://www.dea.gov/docs/dangers-con sequences-marijuana-abuse.pdf. 59. For example, Sheriff David Weaver of Douglas County, Colorado, warned in 2012, “Expect more crime, more kids using marijuana, and pot for sale everywhere.” See Matt Ferner, “If Legalizing Mari- juana Was Supposed to Cause More Crime, It’s Not Doing a Very Good Job,” The Huffington Post, July 17, 2014, http://www.huffingtonpost.com/2014/07/17/ marijuana-crime-denver_n_5595742.html. 60. Jeffrey Miron, “Marijuana Policy in Colorado,” Cato Institute Working Paper, October 23, 2014, http://object.cato.org/sites/cato.org/files/pubs/pdf/ working-paper-24_2.pdf. 61. “Marijuana Is Safer Than Alcohol: It’s Time to Treat It That Way,” Marijuana Policy Project, Washington, https://www.mpp.org/marijuana-is- safer/. See also Peter Hoaken and Sherry Stewart, “Drugs of Abuse and the Elicitation of Human Aggressive Behavior,” Addictive Behaviors 28: (2003): 1533–54, http://www.ukcia.org/research/ AgressiveBehavior.pdf. 62. Denver Police Department, Uniform Crime Reporting Program, “Monthly Citywide Data— National Incident-Based Reporting System,” http:// www.denvergov.org/police/PoliceDepartment/Crime Information/CrimeStatisticsMaps/tabid/441370/ Default.aspx. 63. Fort Collins crime data yield similar factual conclusions, showing no consistent rise in crime following either the November 2012 legalization or the January 2014 opening of stores. 64. “Crime Dashboard,” Seattle Police Depart- ment, http://www.seattle.gov/seattle-police-depart ment/crime-data/crime-dashboard. 65. Sierra Rayne, “Seattle’s Post-Marijuana Legal- ization Crime Wave,” American Thinker, Novem- ber 13, 2015, http://www.americanthinker.com/ blog/2015/11/seattles_postmarijuana_legalization_ crime_wave.html. 66. Elsewhere in Washington State, this conclu- sion seems equally robust. Tacoma, a large city in northeastern Washington where stores have opened, has generally seen stable crime trends be- fore and after legalization. Total monthly offens- es, violent crime, and property crime have shown no significant deviation from their recent trends. See Kellie Lapczynski, “Tacoma Monthly Crime Data,” Washington Association of Sheriffs and Police Chiefs, 2015, p377–78, http://www.waspc. org/assets/CJIS/crime%20in%20washington%20 2015.small.pdf. 67. “City of Portland—Neighborhood Crime Sta- tistics,” Portland Police Bureau, http://www.port landonline.com/police/crimestats/. 68. In Salem, Oregon, violent crime, property crime, and drug offenses show no significant jumps post-legalization. Although Salem is farther from the border with Washington, there are no indica- tions of major spillover effects between 2012 and 2014. See Linda Weber, “Monthly Crime Statistics,” Salem Police Department, 2015, http://www.cityof salem.net/Departments/Police/HowDoI2/Pages/ CrimeStatistics.aspx. Alaska is not covered in this section because reliable recent crime data for major Alaskan cities were unavailable at the time of writing. 69. For a review of this issues, see Rune Elvik, “Risk of Road Accident Associated with the Use of Drugs: A Systematic Review and Meta-Anal- ysis of Evidence from Epidemiological Studies,” Accident Analysis and Prevention 60 (2013): 254–67, 33 doi:10.1016/j.aap.2012.06.017, http://www.ncbi. nlm.nih.gov/pubmed/22785089. 70. Academic studies examining this issue have suggested a possible substitution effect. A 2015 report by the Governors Highway Safety Organi- zation cited one study revealing that marijuana- positive fatalities rose by 4 percent after legaliza- tion in Colorado. However, another study from the same report discovered no change in total traffic fatalities in California after its decriminal- ization of the drug in 2011. See also Andrew Sewell et al., “The Effect of Cannabis Compared with Al- cohol on Driving,” American Journal on Addictions 18, no. 3 (2009): 185–93, http://www.ncbi.nlm.nih. gov/pmc/articles/PMC2722956/. 71. Kevin A. Sabet, “Colorado Will Show Why Legalizing Marijuana Is a Mistake,” Washington Times, January 17, 2014, http://www.washington times.com/news/2014/jan/17/sabet-marijuana-legal izations-worst-enemy/. 72. Associated Press, “Fatal Crashes Involving Marijuana Doubled in Washington after Legaliza- tion,” The Oregonian, August 20, 2015, http://www. oregonlive.com/marijuana/index.ssf/2015/08/fa- tal_crashes_involving_mariju.html. 73. Noelle Phillips and Elizabeth Hernandez, “Colorado Still Not Sure Whether Legal Marijua- na Made Roads Less Safe,” Denver Post, December 29, 2015, http://www.denverpost.com/2015/12/29/ colorado-still-not-sure-whether-legal-marijuana- made-roads-less-safe/. 74. Radley Balko, “Since Marijuana Legaliza- tion, Highway Fatalities in Colorado Are at Near- Historic Lows,” Washington Post, August 5, 2014, https://www.washingtonpost.com/news/the-watch/ wp/2014/08/05/since-marijuana-legalization-high way-fatalities-in-colorado-are-at-near-historic-lows/. 75. These data include any kinds of crashes on all types of roads, as recorded by each state’s depart- ment of transportation. See Colorado Department of Transportation’s “Fatal Accident Statistics by City and County,” http://www.coloradodot.info/ library/traffic/traffic-manuals-guidelines/safety- crash-data/fatal-crash-data-city-county/fatal- crashes-by-city-and-county. 76. Annual crash data from the National Highway Traffic Safety Administration (NHTSA) confirm these findings. Our analysis uses state-level traffic accident data from individual state transporta- tion departments because their data are mostly reported monthly and have a shorter reporting time lag than NHTSA data. For NHTSA data, see “State Traffic Safety Information,” NHTSA, http://www-nrd.nhtsa.dot.gov/departments/nrd- 30/ncsa/STSI/8_CO/2014/8_CO_2014.htm. 77. We additionally analyzed fatality rates for acci- dents involving alcohol impairment. Similarly, this time series shows no clear signs of significant swings after marijuana policy changes, suggesting that any substitution effect associated with marijuana has been small compared to overall drunk driving. 78. Washington Traffic Safety Commission, 2015, http://wtsc.wa.gov/research-data/crash-data/. 79. Washington State police routinely test drivers involved in car crashes for traces of various sub- stances. The official legalization of marijuana use at the end of 2012 appears to have had at most a neg- ligible effect on crash fatalities. The Washington Traffic Safety Commission recorded a total of 62 marijuana-related crash fatalities in 2013, compared to 61 in 2012. There does seem to be a temporary increase in fatalities caused by marijuana-related crashes around the same time as the establishment of Washington’s first marijuana shops. Neverthe- less, any sort of spike seems to have been tempo- rary. In the first six months following the opening of stores, 46 crash fatalities were tied to using mari- juana while driving; over the following six months, that number dropped to 32. 80. Monthly data on fatal crashes themselves were not available. Monthly 2015 data were also not available at the time of writing. 81. For instance, Meier et al. analyze a large sample of individuals tracked from birth to age 38 and find 34 that those who smoked marijuana most heavily prior to age 18 lost an average of eight IQ points, a highly significant drop. See Madeline Meier et al., “Persistent Cannabis Users Show Neuropsycho- logical Decline from Childhood to Midlife,” Pro - ceedings of the National Academy of Sciences 109, no. 40 (2012): E2657–E2664, http://www.ncbi.nlm. nih.gov/pubmed/22927402. However, other studies have found results that rebut Meier et al. Mokrysz et al. examine an even larger sample of adolescents and, after control- ling for many potentially confounding variables, discover no significant correlation between teen marijuana use and IQ change. See Claire Mokrysz et al., “Are IQ and Educational Outcomes in Teen- agers Related to Their Cannabis Use? A Prospective Cohort Study,” Journal of Psychopharmacology 30, no. 2 (2016): 159–68, http://jop.sagepub.com/con tent/30/2/159. 82. Cobb-Clark et al. show that much of relation- ship between marijuana use and educational out- comes is likely due to selection, although there is possibly some causal effect in reducing university entrance scores. See Deborah A. Cobb-Clark et al., “‘High’-School: The Relationship between Early Marijuana Use and Educational Outcomes,” Economic Record 91, no. 293 (June 2015): 247–66. Evidence in McCaffrey et al. supports this selec- tion explanation of the association between mari- juana use and educational outcomes. See Daniel F. McCaffrey et al., “Marijuana Use and High School Dropout: The Influence of Unobservables,” Health Economics 19, no. 11 (November 2010): 1281–99. Roebuck et al. suggest that chronic marijuana use, not more casual use, likely drives any relation- ship between marijuana use and school attendance. See M. Christopher Roebuck et al., “Adolescent Marijuana Use and School Attendance,” Economics of Education Review 23, no. 2 (2004), 133–41. Marie and Zölitz estimate grade improvements are likely due to improved cognitive functioning among students whose nationalities prohibited them from consuming marijuana. See Olivier Marie and Ulf Zölitz, “‘High’ Achievers? Cannabis Access and Academic Performance,” CESifo Working Pa- per Series no. 5304, Center for Economic Studies and Ifo Institute, Munich, 2015. Van Ours and Williams review the literature concluding that cannabis may reduce educational outcomes, particularly with early onset of use. See Jan van Ours and Jenny Williams, “Cannabis Use and Its Effects on Health, Education and Labor Market Success,” Journal of Economic Surveys, 29, no. 5 (December 2015): 993–1010. For additional evidence on likely negative effects of early onset of use see also Paolo Rungo et al., “Pa- rental Education, child’s grade repetition, and the modifier effect of cannabis use,” Applied Econom- ics Letters 22(3)(2015): 199-203; Jan C. van Ours and Jenny Williams, “Why Parents Worry: Initiation into Cannabis Use by Youth and Their Educational Attainment,” Journal of Health Economics 28, no. 1 (2009): 132–42; and Pinka Chatterji, “Illicit Drug Use and Educational Attainment,” Health Economics 15, no. 5 (2006): 489–511. 83. “Suspension/Expulsion Statistics,” Colorado Department of Education, 2015, http://www.cde. state.co.us/cdereval/suspend-expelcurrent. 84. “Washington State Report Card, 2013–14 Re- sults,” Washington State Office of the Superin- tendent of Public Instruction, http://reportcard. ospi.k12.wa.us/summary.aspx?groupLevel=Distr ict&schoolId=1&reportLevel=State&year=2013- 14&yrs=2013-14. 85. Sarah Berger, “Colorado’s Marijuana Indus- try Has a Big Impact on Denver Real Estate: Report,” International Business Times, October 20, 2015, http://www.ibtimes.com/colorados-marijua- na-industry-has-big-impact-denver-real-estate- report-2149623. 86. “S&P/Case-Schiller Denver Home Price In- dex,” S&P Dow Jones Indices, http://us.spindices. com/indices/real-estate/sp-case-shiller-co-denver- home-price-index/. 87. U.S. Department of Commerce, Bureau of Economic Analysis, http://www.bea.gov/iTable/ iTable.cfm?reqid=70&step=1&isuri =1&acrdn=1# reqid=70&step=30&isuri=1&7022=36&7023=0&7 024=non-indust3000&7027=1&7001=336&7028=- &7031=0&7040=-083=levels&7029=36&7090=70. 35 88. As an example, Oregon state legislator Ann Lininger wrote an op-ed predicting a “jobs boom” in southern Oregon after marijuana le- galization. See Lininger, “Marijuana: Will Le- galization Create an Economic Boom?” The Huffington Post. October 1, 2015. http://www. huffingtonpost.com/ann lininger/marijuana- will-legalizati_b_8224712.html. 89. “Local Area Unemployment Statistics,” Bureau of Labor Statistics, http://www.bls.gov/lau/. 90. U.S. Department of Commerce, Bureau of Economic Analysis, http://www.bea.gov/iTable/ iTa blecfm?reqid=70&step=1&isuri=1&acrdn=1#r eqid=70&step=10&isuri=1&7003=200&7035=-. 91. Colorado Department of Revenue, “Colorado Marijuana Tax Data,” Colorado Official State Web Portal, https://www.colorado.gov/pacific/revenue/ colorado-marijuana-tax-data. 92. Tom Robleski, “Up in Smoke: Colorado Pot Biz Not the Tax Windfall Many Predicted,” Janu- ary 2015, http://www.silive.com/opinion/columns/ index.ssf/2015/01/up_in_smoke_colorado_pot_ biz_n.html. 93. Washington State Department of Revenue, “Marijuana Tax Tables,” http://dor.wa.gov/Content/ AboutUs/StatisticsAndReports/stats_MMJTaxes. aspx and http://www.502data.com/. 94. “Washington Rakes in Revenue from Marijuana Taxes,” RT (Russia Today televi- sion channel), July 13, 2015, https://www.rt.com/ usa/273409-washington-state-pot-taxes/. 95. Oregon Department of Revenue, “Marijuana Tax Program Update,” Joint Interim Committee on Marijuana Legalization, May 23, 2016, https:// olis.leg.state.or.us/liz/2015I1/Downloads/Com- mit teeMeetingDocument/90434. Published by the Cato Institute, Policy Analysis is a regular series evaluating government policies and offering proposals for reform. Nothing in Policy Analysis should be construed as necessarily reflecting the views of the Cato Institute or as an attempt to aid or hinder the passage of any bill before Congress. Contact the Cato Institute for reprint permission. All policy studies can be viewed online at www.cato.org. 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Tupy (July 12, 2016) 794. Options for Federal Privatization and Reform Lessons from Abroad by Chris Edwards (June 28, 2016) www.thelancet.com/psychiatry Vol 2 July 2015 601 Articles Medical marijuana laws and adolescent marijuana use in the USA from 1991 to 2014: results from annual, repeated cross-sectional surveys Deborah S Hasin, Melanie Wall, Katherine M Keyes, Magdalena Cerdá, John Schulenberg, Patrick M O’Malley, Sandro Galea, Rosalie Pacula, Tianshu Feng Summary Background Adolescent use of marijuana is associated with adverse later eff ects, so the identifi cation of factors underlying adolescent use is of substantial public health importance. The relationship between US state laws that permit marijuana for medical purposes and adolescent marijuana use has been controversial. Such laws could convey a message about marijuana acceptability that increases its use soon after passage, even if implementation is delayed or the law narrowly restricts its use. We used 24 years of national data from the USA to examine the relationship between state medical marijuana laws and adolescent use of marijuana. Methods Using a multistage, random-sampling design with replacement, the Monitoring the Future study conducts annual national surveys of 8th, 10th, and 12th-grade students (modal ages 13–14, 15–16, and 17–18 years, respectively), in around 400 schools per year. Students complete self-administered questionnaires that include questions on marijuana use. We analysed data from 1 098 270 adolescents surveyed between 1991 and 2014. The primary outcome of this analysis was any marijuana use in the previous 30 days. We used multilevel regression modelling with adolescents nested within states to examine two questions. The fi rst was whether marijuana use was higher overall in states that ever passed a medical marijuana law up to 2014. The second was whether the risk of marijuana use changed after passage of medical marijuana laws. Control covariates included individual, school, and state-level characteristics. Findings Marijuana use was more prevalent in states that passed a medical marijuana law any time up to 2014 than in other states (adjusted prevalence 15·87% vs 13·27%; adjusted odds ratio [OR] 1·27, 95% CI 1·07–1·51; p=0·0057). However, the risk of marijuana use in states before passing medical marijuana laws did not diff er signifi cantly from the risk after medical marijuana laws were passed (adjusted prevalence 16·25% vs 15·45%; adjusted OR 0·92, 95% CI 0·82–1·04; p=0·185). Results were generally robust across sensitivity analyses, including redefi ning marijuana use as any use in the previous year or frequency of use, and reanalysing medical marijuana laws for delayed eff ects or for variation in provisions for dispensaries. Interpretation Our fi ndings, consistent with previous evidence, suggest that passage of state medical marijuana laws does not increase adolescent use of marijuana. However, overall, adolescent use is higher in states that ever passed such a law than in other states. State-level risk factors other than medical marijuana laws could contribute to both marijuana use and the passage of medical marijuana laws, and such factors warrant investigation. Funding US National Institute on Drug Abuse, Columbia University Mailman School of Public Health, New York State Psychiatric Institute. Introduction In the USA, adolescent marijuana use has increased since the mid-2000s.1,2 Adolescent use, especially regular use, is associated with increased likelihood of harmful eff ects, including short-term impairments in memory, coordination, and judgment, and longer-term risks of altered brain development, cognitive impairments,3–5 unemployment,6 psychiatric symptoms and substance addiction.1,7 Therefore, identifi cation of factors underlying adolescent use is of substantial importance. To aff ect prevalence nationally, factors must aff ect wide segments of the population; state laws permitting the use of marijuana for medical purposes have been proposed as one such factor.8–10 Since 1996, 23 US states and the District of Columbia have passed medical marijuana laws, and other states are considering such laws. Although the specifi c provisions of state medical marijuana laws diff er,11 they all have a common purpose: to legalise the use of marijuana for medical purposes. However, by conveying a message about acceptability or an absence of harmful health consequences, passage of such laws could aff ect youth perception of harms, leading to increased prevalence of marijuana use in the years immediately after the law has passed, even with delayed implementation or narrow limits on use. Whether medical marijuana laws are associated with increased use of marijuana by adolescents has been debated. Some commentators have suggested that these Lancet Psychiatry 2015; 2: 601–08 Published Online June 16, 2015 http://dx.doi.org/10.1016/ S2215-0366(15)00217-5 See Comments page 572 See Online for a podcast interview with Deborah Hasin Department of Epidemiology (Prof D S Hasin PhD, K M Keyes PhD, M Cerdá Dr PH, Prof S Galea MD) and Department of Biostatistics (Prof M Wall PhD), Mailman School of Public Health, Columbia University, New York, NY, USA; Department of Psychiatry, Columbia University Medical Center, New York, NY, USA (Prof D S Hasin, Prof M Wall); New York State Psychiatric Institute, New York, NY, USA (Prof D S Hasin, Prof M Wall); Research Foundation of Mental Hygiene, New York, NY, USA (T Feng MS); Department of Psychology (Prof J Schulenberg PhD) and Institute for Social Research (Prof J Schulenberg, Prof P M O’Malley PhD), University of Michigan, Ann Arbor, MI, USA; RAND Corporation, Santa Monica, CA, USA (Prof R Pacula PhD); and National Bureau of Economic Research, Cambridge, MA, USA (Prof R Pacula) Correspondence to: Prof Deborah Hasin, Department of Psychiatry, Columbia University Medical Center, New York, NY 10032, USA deborah.hasin@gmail.com Articles 602 www.thelancet.com/psychiatry Vol 2 July 2015 laws have no eff ect, or actually discourage use.12,13 Others suggest that these laws increase adolescent use of marijuana through various mechanisms,8 such as sending a message that use is acceptable.9,10 In 2013, 19% of high school seniors (generally aged 17 and 18 years) reported that they would try marijuana or use it more often if it were legalised for general use.14 In a study of adolescents in paediatric practices in states that had not passed medical marijuana laws,15 55% thought that passing such a law would “make it easier for teens to start to smoke marijuana for fun”. These fi ndings suggest that the legal status of marijuana, including medical marijuana laws, could increase adolescent use of marijuana. Previously, we showed that adolescent16 and adult17 marijuana use was more prevalent in US states with medical marijuana laws than in states without such laws. However, we examined only fairly short periods, and the studies did not address whether this increased prevalence preceded or followed passage of the law.18,19 One study suggested that after 2009, a confl uence of federal and local factors predicted greater adolescent marijuana use in Colorado, a state with a medical marijuana law, than in 39 other states without such laws.20 Other studies (of four21 and fi ve states;22 seven states in total because of overlap) did not show increased adolescent use after medical marijuana laws were passed. All these studies were limited by the small sample sizes, the few states included with medical marijuana laws, and years examined, leaving questions about whether the absence of eff ect might be due to insuffi cient statistical power or the particular states studied. Examination of a greater number of participants, years, and states should more defi nitively establish whether the passage of medical marijuana laws predicts a subsequent increase in adolescent marijuana use. We therefore examined the relationship between state medical marijuana laws and adolescent marijuana use using 24 years of yearly survey data (1991–2014) from repeated annual, cross-sectional surveys that included more than 1 million adolescents in the 48 contiguous states, of which 21 had passed medical marijuana laws Research in context Evidence before this study If passage of a state law legalising marijuana for medical use conveyed a public message to adolescents that marijuana use was acceptable or did not lead to adverse eff ects, this law could quickly increase adolescent use of marijuana, even if the law was implemented slowly or had provisions that tightly restricted marijuana use. To identify studies relevant to this issue, we searched PubMed for English-language articles with the term, “medical marijuana”. As of April 6, 2015, 449 articles with this term were published, the fi rst in 1978, and all the rest since 1994. Most articles were opinion pieces about the pros and cons of medical marijuana use, regarding either its medicinal benefi ts, or implications for society. To be considered relevant to the present study, we reviewed reports with empirical fi ndings that were based on general-population surveys with state-based samples, had marijuana use as an outcome, and compared states with and without medical marijuana laws, or states before and after passage of such laws. We identifi ed two reports showing overall higher rates of marijuana use in states with medical marijuana laws, one in adolescents and the other in adults, with one replication of the adolescent result. Comparison of Colorado, a state with a medical marijuana law, with states without medical marijuana laws found suggestive but inconclusive evidence regarding the eff ects of the law on adolescent marijuana use. Two studies, that in combination examined seven states that passed medical marijuana laws did not show increased prevalence of adolescent marijuana use after the laws were passed, relative to the prevalence before the laws were passed. However, limitations in the number of states examined, number of years, and sample sizes left unclear whether the absence of diff erences in marijuana use pre-law and post-law were real or due to limitations of the methods. Added value of this study Our study, which included data from annual national surveys spanning 24 years (1991–2014) for 1 098 270 adolescents in 48 US states, provides two pieces of defi nitive evidence about medical marijuana laws and adolescent use of marijuana. First, across all survey years, overall adolescent marijuana use was higher in states that had ever passed medical marijuana laws than in states that did not have these laws, but the increased use was present in states both before and after the laws were passed. Second, our comprehensive study showed no evidence for an increase in adolescent use of marijuana in the year of passage of a medical marijuana law, or in the fi rst or second years after passage. These results were consistent across several sensitivity analyses that used a diff erent defi nition of the marijuana outcome variable, that removed one state at a time from the sample to establish whether one state was unduly aff ecting the overall results (none did), or whether a state medical marijuana law provided for dispensaries. Implications of all the available evidence Our two main fi ndings, in conjunction with other evidence, suggest that state-level factors other than medical marijuana laws infl uence adolescent marijuana use. Because both human studies and animal models show that early adolescent use of marijuana increases the risk of important adverse eff ects in adulthood, the identifi cation of large-scale societal factors that increase the risk of early use is crucial. Our study fi ndings suggest that the debate over the role of medical marijuana laws in adolescent marijuana use should cease, and that resources should be applied to identifying the factors that do aff ect risk. Articles www.thelancet.com/psychiatry Vol 2 July 2015 603 by 2014 (fi gure 1). Controlling for individual-level, school-level, and state-level factors, we addressed two questions. The fi rst was whether adolescents were generally at higher risk for marijuana use in states that ever passed a medical marijuana law by 2014 than adolescents in other states. This question extends our previous work16,17 by greatly increasing the number of years considered and controlling for potentially important state and individual covariates. The second question was whether adolescents in states that had passed medical marijuana laws were at higher risk of marijuana use in the years immediately after passage of the law than adolescents in those states before passage of the law. Methods Study design and participants Since 1991, the Monitoring the Future study has conducted national, annual cross-sectional surveys of adolescents in school grades 8, 10, and 12 (modal ages 13–14, 15–16, and 17–18 years, respectively), in about 400 schools each year (mean schools per year 409·3 [SD 17·34]; range 377–435 schools per year) in the 48 contiguous US states. Monitoring The Future surveys use a multistage, random sampling design with replacement. The stages include geographical area, schools within area (with probability proportionate to school size), and students within school. Up to 350 students per grade, per school are included, with classrooms randomly selected within schools. Schools participate for two consecutive years. Non- participating schools are replaced with others matched for location, size, and urbanicity. Data were collected from students via self-administered questionnaires.23 Measures24 and data collection pro- cedures have remained consistent across years.14 Students completed questionnaires in classrooms or larger group administrations. Monitoring the Future study re- presentatives distributed and collected question naires using standardised procedures to maintain con fi dentiality.14 Self-administered forms and the data collection procedures are designed to maximise the validity of substance use reporting. Low quantities of non-responses, high pro- portions of students consistently reporting illicit drug use, and strong construct validity have previously been reported for the Monitoring the Future study.21 Advance notice to parents and students about the study included that participation was voluntary and responses were either anonymous (for 8th and 10th graders) or confi dential (for 12th graders; responses of 12th graders are not anonymised so that they can participate in follow- up studies).14 All Monitoring the Future study procedures were reviewed and approved by the University of Michigan Institutional Review Board.14 Measures The primary outcome was any marijuana use within the previous 30 days versus no use, a binary individual-level variable previously used in time-trend analysis of Monitoring the Future data.25 We also examined any marijuana use within the past 12 months, similarly dichotomised, in sensitivity analyses. Our main exposure was “state-level medical marijuana law”, represented in the analysis by two state-level variables. The fi rst was a binary variable that showed whether a state passed a medical marijuana law by 2014 (21 had passed such laws), irrespective of the year that it passed. We used this variable to compare risk of adolescent marijuana use in states that had ever passed a medical marijuana law with risk in states that had not. The second was a time-varying binary variable for each year (1991–2014) and state (48 states) indicating whether the state had passed a medical marijuana law that year or not, as established through review of state policies by legal scholars, economists, and policy analysts at the RAND Corporation.11 We defi ned the variable for state– year as the year that the law was passed (appendix p 1). This variable enabled us to examine adolescents within states before and after passage of medical marijuana laws, in conjunction with adolescents in states that never passed a medical marijuana law. States that have passed medical marijuana laws permitting medical marijuana dispensaries might diff er from states whose medical marijuana laws do not permit dispensaries in terms of marijuana availability, public perceptions, and potency.26 We therefore explored an alternative defi nition11 of our yearly state medical marijuana law variable, re-coding it as a three-level variable: no medical marijuana law, a medical marijuana law not permitting dispensaries, and a medical marijuana law permitting dispensaries. The latter category was defi ned as implicitly permitting dispensing via caregivers and amounts per patient, or explicit acknowledgment of dispensaries as either permitted or not declared illegal (p 1 of the appendix shows the years that states were coded positive by this defi nition). See Online for appendix Figure 1: US states with medical marijuana laws as of 2014, and years of passage WA OR NV (2000) CA (1996) AZ (2010) NM (2007) CO (2000) MT (2004) IL (2013) MI (2008) ME (1999) ID WY UT ND SD NE KS OK TX IA MO AR LA MS AL TN NC VA WV PA NY (2014) OH IN KY SC GA FL MN (2014) WI NH (2013) VT (2004) MA (2012) RI (2006) CT (2012) NJ (2010) DE (2006) MD (2003) (1998) (1998) States with medical marijuana laws For Monitoring the Future see www.monitoringthefuture.org Articles 604 www.thelancet.com/psychiatry Vol 2 July 2015 School-level control variables included the number of students per grade within school; public versus private school; and urban or suburban (ie, within metropolitan statistical areas)27 versus rural schools. State-level control variables included the proportion of each state’s population who were male, white, aged 10–24 years, and older than 25 years without high-school education. We used US census values from 1990, 2000, and 2010 for survey years 1991–95, 1996–2005, and 2006–14, respectively. Individual covariates included age, gender, ethnic origin (white, black, Hispanic, Asian, mixed, and other), grade (when combining grades), and socioeconomic status (highest parental education categorised as high school not completed, high-school graduate or equivalent, some university education, or a 4-year university degree or higher). Statistical analysis We conducted multilevel logistic regression modelling of adolescents nested within states to address whether marijuana use was higher overall in states that passed a medical marijuana law at any point between 1991 and 2014 than in other states; and whether the risk of marijuana use changed after a medical marijuana law was passed compared with the risk before the law passed, controlling for the contemporaneous risk of use overall in other states (appendix pp 6 and 7). For these analyses, we used SAS Proc Glimmix code (version 9.4). We controlled for the non-linear historical trend in marijuana use across the 24 years with a piece-wise cubic spline. Covariates at an individual, school, and state level were controlled (appendix pp 6 and 7). We fi tted a single multilevel model to the entire study dataset that simultaneously addressed both research questions through specifi cation of the two primary predictors: a dichotomous indicator of whether a state passed a medical marijuana law any time between 1991 and 2014, coded 1 for all individuals in the states with a law before 2014 (irrespective of year passed) and 0 for all others; and a time-varying indicator coded 0 for individuals in states in the years before a medical marijuana law passed (including states with no medical marijuana laws before 2014) and 1 for individuals in states in the years during and after the law passed). The time-varying indicator provides a diff erence-in-diff erence estimator of change in risk due to marijuana laws in which the contrast is between the average within-state change in risk of use before versus after the law passed, compared with the aggregated contemporaneous average change in risk of use in states that do not pass such a law. We fi rst fi tted the multilevel model combining 8th, 10th, and 12th grades, and then refi tted the model including and testing an interaction with grade to obtain grade-specifi c medical marijuana law eff ects. The latter was done because the prevalence of marijuana use diff ers by grade, and thus risk factors could diff er as well. We present adjusted odds ratios (ORs) and 95% CIs for the combined and grade-specifi c eff ects, and state- specifi c log OR estimates (pre-law vs post-law) for the 21 states that passed such laws. We derived adjusted prevalence estimates aggregated for the states with and without medical marijuana laws for each year from the multilevel logistic model, aggregating across years and also plotted by year. State-specifi c log OR estimates in the post-passage years compared with the pre-passage years are presented for the 21 states that passed laws. Estimation and testing of the state-level predictors with the multilevel model did not require inclusion of sampling weights, because the model directly in- corporated all individual-level and school-level variables related to the sampling design.28 Within the Monitoring the Future study, not all states had data available for every year and grade; the multilevel model addresses this diffi culty by smoothing eff ects across missing years and grades with state-level random eff ects (allowing for the eff ects of covariates—eg, ethnic origin—to vary by state). We used multiple imputation (Proc MI, SAS version 9.4) at the individual level to handle missing covariate data (range 2·98% [age] to 8·05% [parental education]; appendix pp 2, 6). We conducted fi ve sets of sensitivity analyses to determine the robustness of the fi ndings. First, the binary marijuana use variable was replaced with an ordered categorical outcome indicating frequency of past-month use (0, 1–2, 3–5, 6–9, 10–19, 20–39, or 40 + occasions), modelled with cumulative odds. Second, the time-varying variable indicating medical marijuana law was re-coded as positive in three diff erent ways to allow for delayed eff ects (lag) between passage of the law and changes in population behaviour: recoding the state– year variable positive starting the year following passage Adjusted prevalence Adjusted odds ratio (95% CI) p value Medical marijuana law passed by 2014 Medical marijuana law not passed by 2014 Combined grades 15·87% 13·27%1·27 (1·07–1·51)0·0057 8th grade 7·22% 6·95%1·18 (0·98–1·44)0·0871 10th grade 18·02% 15·04%1·23 (1·01–1·49)0·0352 12th grade 22·36% 17·83%1·35 (1·11–1·63)0·0024 Table shows marijuana use in the previous 30 days. Modal ages of students: 8th grade 13–14 years; 10th grade 15–16 years; 12th grade 17–18 years. Adjusted prevalences encompassing years 1991 to 2014 were derived from the multilevel model, with distributions of covariates fi xed at grade-specifi c overall US distributions averaged across all 24 years. The model controlled for sex, age, race, education of parents, class size, whether educated at an urban or rural school, public or private school, and state-aggregated percentage who were male, percentage who were white, percentage with no high school education, and percentage aged 11–24 years. The model also included a state random intercept, and state-specifi c cubic spline polynomials to control for trend with a knot at the years 1998 and 2006. See appendix p 4 for absolute numbers. Table 1: Adolescent use of marijuana in the 48 US contiguous states between 1991 and 2014 Articles www.thelancet.com/psychiatry Vol 2 July 2015 605 if the medical marijuana law was passed after July; recoding the variable as positive in the year following passage for all states with medical marijuana laws; recoding the variable as positive 2 years following passage for all states with medical marijuana laws (appendix p 7). Third, we replaced the binary state–year law variable with the three-level dispensary variable. Fourth, we replaced use in the past month with use in the past year. Fifth, to ensure that no state unduly infl uenced the results, the multilevel model was refi tted 48 times, removing one state each time. Sensitivity analyses used a model that combined eff ects across grades, and a model with grade-by-law interaction to identify grade-specifi c eff ects. Role of the funding source The funders of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. The corresponding author had full access to all the data in the study and had fi nal responsibility for the decision to submit for publication. Results By 2014, 21 of the 48 contiguous states had passed a medical marijuana law (fi gure 1, appendix p 1). Across the 21 states, the mean number of years since the law was passed was 6·76 (SD 6·06), and the median number of years was 4·0 (see appendix, p 7 for more detail). Between 1991 and 2014, the Monitoring the Future study surveyed a total of 1 134 734 (408 942 in 8th grade, 370 449 in 10th grade, and 355 343 in 12th grade). After we excluded students who were missing marijuana data, 1 098 270 (96·8%) remained for analysis: 396 310 8th graders (96·9%), 361 400 10th graders (97·6%), and 340 560 12th graders (95·8%). Of all selection sample units, 95–99% obtained one or more participating schools in all study years. Previous studies have shown no time trend in school participation.29 Student response rates were 81–91% for almost all years and grades (mean response rates for 1991–2013). Most non-responses were because of absenteeism; less than 1% of students declined participation in the survey when asked in the school to complete the questionnaire. Marijuana use in the previous 30 days was more prevalent in states that passed a medical marijuana law between 1991 and 2014 than in those that had not (adjusted prevalence 15·87% vs 13·27%; adjusted OR 1·27, 95% CI 1·07–1·51, p=0·0057). This fi nding did not diff er by grade (table 1; interaction of grade and state medical marijuana law status, p=0·33). This eff ect, aggregated across years before and after passage of marijuana laws, suggests that, overall, states with a medical marijuana law had an increased prevalence of marijuana use even before the law was passed (fi gure 2). Aggregating across grade, the risk of marijuana use did not signifi cantly change after passage of a medical marijuana law (adjusted prevalence 16·25% pre-law vs 15·45% post-law; adjusted OR 0·92, 95% CI 0·82–1·04, p=0·185). The interaction between grade and risk before and after the law passed was signifi cant (p=0·001), suggesting diff erential results by grade (table 2). Among 8th graders, marijuana use decreased signifi cantly after passage of medical marijuana laws (table 2), but no signifi cant change was found before versus after passage in 10th or 12th graders (table 2). Substantial state-to-state variability was found for pre- passage versus post-passage risk of adolescent marijuana use (fi gure 3). States also varied in whether the eff ects of medical marijuana laws diff ered signifi cantly by grade. Adjusted prevalence Adjusted odds ratio (95% CI) p value Before law passed After law passed Combined grades 16·25% 15·45%0·92 (0·82–1·04)0·185 8th grade 8·14% 6·05%0·73 (0·63–0·84)<0·0001 10th grade 17·94% 18·27%1·02 (0·90–1·17)0·738 12th grade 22·68% 22·02%0·96 (0·84–1·10)0·581 Table shows marijuana use in the previous 30 days. Modal ages of students: 8th grade 13–14 years; 10th grade 15–16 years; 12th grade 17–18 years. Adjusted prevalences derived from the multilevel model that also includes states that did not pass medical marijuana laws to control for historical trends. Distributions of covariates were fi xed at grade-specifi c overall US distributions averaged over varying numbers of years before and after the law was passed, depending on when the change in law occurred. See appendix p 5 for absolute numbers. Table 2: Adolescent use of marijuana before and after passage of medical marijuana in the 21 US contiguous states that passed medical marijuana laws up to 2014 Figure 2: Adjusted prevalence of US adolescent marijuana use* by year (1991–2014), school grade, and whether states had medical marijuana laws *Marijuana use refers to use in the previous 30 days. Modal ages of students: 8th grade 13–14 years; 10th grade 15–16 years; 12th grade 17–18 years. Adjusted prevalence estimates are derived from the multilevel model, fi t to all 24 years of Monitoring the Future data from the 48 contiguous US states, with individual, school, and state- level covariates fi xed at the age-specifi c overall US distributions each year. The 21 states with medical marijuana laws passed them in varying years, thus the yearly prevalence estimates for these states are aggregated irrespective of whether the state had passed a law yet. 0 Year Year Year1990199520002005201020151990199520002005201020151990199520002005 201020150·05 0·10Adjusted prevalence0·15 0·20 0·25 0·30 ABCGrade 8 Grade 10 Grade 12 Average across 27 states without medical marijuana laws Average across 21 states with medical marijuana laws Articles 606 www.thelancet.com/psychiatry Vol 2 July 2015 Sensitivity analyses did not meaningfully aff ect results (appendix p 3). Modelling frequency of use in the previous 30 days, the overall eff ect of medical marijuana laws on adolescent use before versus after passage of the law remained non-signifi cant, although (as for the overall results), use was signifi cantly reduced in 8th but not 10th or 12th graders. Recoding the year of passage to model delayed eff ects did not change the fi ndings for adolescents overall, nor did our re-analyses that incorporated dispensary information or use of marijuana in the previous year. Finally, rerunning 48 models with interaction by grade, removing one state at a time, results were all signifi cant for 8th graders (adjusted OR 0·69–0·75) but not for 10th or 12th graders (data available on request). Discussion In this analysis of repeated annual, cross-sectional survey data we examined whether adolescent use of marijuana was greater in US states that eventually passed medical marijuana laws, and whether adolescent marijuana use increased in these states after passage of such laws. Compared with previous reports, we used data from a much larger sample, and included many more states (48) and years (24). Controlling for important covariates, states that had ever enacted a medical marijuana law up to 2014 had higher prevelance of adolescent marijuana use than did other states. However, importantly, the analyses of use pre-law versus post-law did not indicate that adolescent marijuana use increased after passage of NM OR MA WA VT ME MD RI IL AZ MN CT NJ CA MI NY CO US overall MA AZ WA OR MD MN VT CA NM NV IL DE CO NY ME CT NJ NH MI US overall MT WA RI OR MA MN CO DE ME NM NH MD IL CT NJ CA NY MI AZ US overall MT WA MA NM OR DE RI MD NV VT MN CO IL CA AZ ME NH CT NJ NY MI US overall –0·75US stateUS state–0·50 –0·25 0 0·25 –1·0 –0·5 0 0·5 –0·75 –0·50 –0·25 0 0·25 0·50 –0·5 0 0·5 A Combined grades C 10th graders B 8th graders B 12th graders Figure 3: State-specifi c risk of adolescent marijuana use before versus after passage of state medical marijuana laws Modal ages of students: 8th grade 13–14 years; 10th grade 15–16 years; 12th grade 17–18 years. Figure shows log odds ratio (95% CI) for marijuana use in the previous 30 days. Values >0 indicate increased log odds ratios of the last month of marijuana use in the post-passage year compared with the pre-passage years; values <0 indicate a decrease. Post-passage includes the year in which the medical marijuana law was passed. State estimates for each grade are not shown when a state did not have pre-passage or post-passage data from the Monitoring the Future study within that grade. For 8th graders, NV did not have pre-law data and VT did not have any data for this grade. For 10th graders, MT did not have pre-law data and RI did not have any data for this age group. For 12th graders DE, MT, and NV did not have pre-law data and NH did not have post-law data. Articles www.thelancet.com/psychiatry Vol 2 July 2015 607 medical marijuana laws. To our knowledge, these fi ndings, consistent with those from earlier studies,10,21,22 provide the strongest empirical evidence yet that medical marijuana laws do not account for increased use of marijuana in US adolescents. Whether medical marijuana laws increase availability through diversion, or change adolescent approval of marijuana, is unknown. Irrespective of this point, our fi ndings suggest that medical marijuana laws did not infl uence these factors suffi ciently to raise adolescent marijuana use. However, because adolescent norms could aff ect risk of later adult marijuana use, and because national trends in marijuana use might yield diff erent results in the future, the eff ects that these laws could have on adolescent attitudes towards the acceptability and riskiness of marijuana use (also assessed in the Monitoring the Future study) warrant further investigation. Compared with states that had never passed a medical marijuana law by 2014, adolescent marijuana use overall was higher in states that had passed such a law, a diff erence particularly noticeable in 12th graders. Because this diff erence did not occur after the law was passed, these states might diff er from the others on common factors yet to be identifi ed (eg, norms surrounding marijuana use25 or marijuana availability). Investigation of these factors is warranted. The post-law decrease in marijuana use among 8th graders was unexpected but robust across main and sensitivity analyses (appendix p 3). One explanation for this fi nding is that 10th and 12th graders had already formed attitudes towards marijuana and hence were not infl uenced by medical marijuana laws, but the younger 8th graders had more modifi able attitudes and beliefs about marijuana, and were less likely to view marijuana as recreational after states authorised its use for medical purposes. Unlike 10th and 12th graders, 8th graders show little evidence of an increase in use since 2005 (fi gure 3). Also, perhaps the passage of medical marijuana laws and increasingly positive public attitudes towards marijuana have focused parental vigilance and counter-eff orts against use in the youngest adolescents. These and other explanations should be investigated. Until 2011, no states allowed recreational marijuana use, but four states (Colorado, Washington, Alaska, and Oregon) and the District of Columbia have now passed laws permitting adult recreational use. Concerns exist that, at least to some extent, eff orts to legalise medical marijuana are actually concealed eff orts to eventually legalise recreational use.30,31 Because we examined only laws governing medical use, this report does not address the debate about legal recreational use. Research into the relationship between legalisation of recreational marijuana and adolescent marijuana use is important, but such associations cannot be inferred from the present study. Our study has several limitations. We did not examine additional variations in state medical marijuana laws (eg, the amount of marijuana permitted, or approved illnesses), but they merit future investigation. Marijuana use was self-reported, which is a shortcoming of large- scale surveys. However, data were collected in confi dential circumstances, and fi ndings from methodological studies support the validity of this method in the Monitoring the Future study.29 The survey did not include adolescents who were temporarily absent from or do not attend school; this population should also be studied. Also, some states had only short periods after passage of medical marijuana laws, which limited the detection of longer- term eff ects in those states. Thus, analyses should be repeated after more years of data have accumulated. Finally, results might not be generalisable to states that are considering but have not passed medical marijuana laws. These states have lower prevalences of marijuana use than do states with these laws, so the eff ect of medical marijuana laws on adolescent use in these states could diff er. Analyses should be repeated if more states pass medical marijuana laws. However, our study also has notable strengths. We analysed a sample of more than 1 million adolescents from 48 US states, with the most comprehensive time span yet in terms of years examined. Consistency in measures, data collection methods over time, and consistently excellent response rates ruled out many issues with the methods as alternative explanations of study fi ndings, as did the sophisticated statistical methods that we used along with controls for important state, school, and individual covariates. In a large set of 54 sensitivity analyses, only one model suggested a diff erent result, lending support to the robustness of our fi ndings. Self-administered forms and data collection procedures were designed to maximise the validity of substance-use reporting. The validity of our report is supported by low quantities of non-responses, high proportions of students consistently reporting illicit drug use, and strong construct validity. The absence of a time trend in school participation suggests that school non-response did not aff ect trends. In conclusion, the results of this study showed no evidence for an increase in adolescent marijuana use after passage of state laws permitting use of marijuana for medical purposes. Whether access to a substance for medical purposes should be determined by legislation rather than biomedical research and regulatory review is debatable.30 However, concerns that increased adolescent marijuana use is an unintended eff ect of state medical marijuana laws seem unfounded. In view of the potential for harm from early use,3–5,32–35 other factors infl uencing wide segments of the population need to be investigated. Contributors DSH, MW, KMK, MC, JS, PMO’M, SG, and RLP designed the study. MW took particular responsibility for the statistical analysis plan, and KMK, JS, and PMO’M for use of datasets from Monitoring the Future study to address the research questions. DSH was responsible for obtaining funds and prepared the fi rst and fi nal drafts of the report. Articles 608 www.thelancet.com/psychiatry Vol 2 July 2015 15 Schwartz RH, Cooper MN, Oria M, Sheridan MJ. Medical marijuana: a survey of teenagers and their parents. Clin Pediatr 2003; 42: 547–51. 16 Wall MM, Poh E, Cerdá M, Keyes KM, Galea S, Hasin DS. Adolescent marijuana use from 2002 to 2008: higher in states with medical marijuana laws, cause still unclear. Ann Epidemiol 2011; 21: 714–16. 17 Cerdá M, Wall M, Keyes KM, Galea S, Hasin D. Medical marijuana laws in 50 states: investigating the relationship between state legalization of medical marijuana and marijuana use, abuse and dependence. Drug Alcohol Depend 2012; 120: 22–27. 18 Harper S, Strumpf EC, Kaufman JS. Do medical marijuana laws increase marijuana use? Replication study and extension. Ann Epidemiol 2012; 22: 207–12. 19 Wall MM, Poh E, Cerdá M, Keyes KM, Galea S, Hasin DS. Commentary on Harper S, Strumpf EC, Kaufman JS. Do medical marijuana laws increase marijuana use? Replication study and extension. Ann Epidemiol 2012; 22: 536–37. 20 Schuermeyer J, Salomonsen-Sautel S, Price RK, et al. Temporal trends in marijuana attitudes, availability and use in Colorado compared to non-medical marijuana states: 2003–11. Drug Alcohol Depend 2014; 140: 145–55. 21 Lynne-Landsman SD, Livingston MD, Wagenaar AC. Eff ects of state medical marijuana laws on adolescent marijuana use. Am J Public Health 2013; 103: 1500–06. 22 Choo EK, Benz M, Zaller N, Warren O, Rising KL, McConnell KJ. The impact of state medical marijuana legislation on adolescent marijuana use. J Adolesc Health 2014; 55: 160–66. 23 University of Michigan. The Interuniversity Consortium for Political and Social Research, Monitoring the Future (MTF) Series. https://www.icpsr.umich.edu/icpsrweb/ICPSR/series/35 (accessed June 1, 2015). 24 Johnston LD, Bachman JG, O’Malley PM, Schulenberg JE. Monitoring the Future: a continuing study of American ICPSR 33902 youth (8th-grade and 10th-grade surveys), 2011. http://www. icpsr.umich.edu/fi les/NAHDAP/33902-User_guide.pdf (accessed June 1, 2015). 25 Keyes KM, Schulenberg JE, O’Malley PM, et al. The social norms of birth cohorts and adolescent marijuana use in the United States, 1976–2007. Addiction 2011; 106: 1790–800. 26 Sevigny EL, Pacula RL, Heaton P. The eff ects of medical marijuana laws on potency. Int J Drug Policy 2014; 25: 308–19. 27 United States Census Bureau. Metropolitan and micropolitan statistical areas main. https://www.census.gov/population/metro/ (accessed April 15, 2014). 28 Little RJA. To model or not to model? Competing modes of inference for fi nite population sampling. J Am Stat Assoc 2004; 99: 546–56. 29 Johnston LD, O’Malley PM, Bachman JG, Schulenberg JE. Monitoring the Future national survey results on drug use, 1975–2010: Volume 1, secondary school students. Ann Arbor: Institute for Social Research, The University of Michigan; 2011. 30 Kleber HD, DuPont RL. Physicians and medical marijuana. Am J Psychiatry 2012; 169: 564–68. 31 Fischer B, Kuganesan S, Room R. Medical marijuana programs: implications for cannabis control policy—observations from Canada. Int J Drug Policy 2015; 26: 15–9. 32 Degenhardt L, Whiteford HA, Ferrari AJ, et al. Global burden of disease attributable to illicit drug use and dependence: fi ndings from the Global Burden of Disease Study, 2010. Lancet 2013; 382: 1564–74. 33 Brook JS, Adams RE, Balka EB, Johnson E. Early adolescent marijuana use: risks for the transition to young adulthood. Psychol Med 2002; 32: 79–91. 34 Chatterji P. Illicit drug use and educational attainment. Health Econ 2006; 15: 489–511. 35 Lynskey M, Hall W. The eff ects of adolescent cannabis use on educational attainment: a review. Addiction 2000; 95: 1621–30. MW did the analyses and supervised the work of TF in doing the analyses. RLP provided defi nitions of medical marijuana laws and their variations as determined by herself and her group of experts at RAND. All authors contributed to subsequent versions of the report, and approved the fi nal version. Declaration of interests We declare no competing interests. Acknowledgments The design, data collection, and management of the Monitoring the Future study was sponsored by the National Institute on Drug Abuse (NIDA), US National Institutes of Health, and done at the Institute for Social Research at the University of Michigan (MI, USA; grant number R01DA001411). The analysis, interpretation of the data, and preparation, review, and approval of the report was funded by NIDA grant R01DA034244. We received additional support from the National Institute on Alcohol Abuse and Alcoholism (grant numbers K05AA014223 for DSH and K01AA021511 for KMK); NIDA (grant number K01DA030449 for MC), the Department of Epidemiology, Mailman School of Public Health (SG), and the New York State Psychiatric Institute (DH, MW). References 1 Volkow ND, Compton WM, Weiss SR. Adverse health eff ects of marijuana use. N Engl J Med 2014; 371: 879. 2 Secades-Villa R, Garcia-Rodriguez O, Jin CJ, Wang S, Blanco C. Probability and predictors of the cannabis gateway eff ect: a national study. Int J Drug Policy 2015; 26: 135–42. 3 Meier MH, Caspi A, Ambler A, et al. Persistent cannabis users show neuropsychological decline from childhood to midlife. Proc Natl Acad Sci USA 2012; 109: E2657–664. 4 Renard J, Krebs MO, Jay TM, Le Pen G. Long-term cognitive impairments induced by chronic cannabinoid exposure during adolescence in rats: a strain comparison. Psychopharmacology (Berl) 2013; 225: 781–90. 5 O’Shea M, McGregor IS, Mallet PE. Repeated cannabinoid exposure during perinatal, adolescent or early adult ages produces similar longlasting defi cits in object recognition and reduced social interaction in rats. J Psychopharmacol 2006; 20: 611–21. 6 Compton WM, Gfroerer J, Conway KP, Finger MS. Unemployment and substance outcomes in the United States 2002–2010. Drug Alcohol Depend 2014; 142: 350–53. 7 Davis GP, Compton MT, Wang S, Levin FR, Blanco C. Association between cannabis use, psychosis, and schizotypal personality disorder: fi ndings from the National Epidemiologic Survey on Alcohol and Related Conditions. Schizophr Res 2013; 151: 197–202. 8 Thurstone C, Lieberman SA, Schmiege SJ. Medical marijuana diversion and associated problems in adolescent substance treatment. Drug Alcohol Depend 2011; 118: 489–92. 9 O’Connor A. Marijuana use growing among teenagers. http://well. blogs.nytimes.com/2011/12/14/marijuana-growing-in-popularity- among-teenagers/?_php=true&_type=blogs&_r=0 (accessed April 16, 2014). 10 Khatapoush S, Hallfors D. “Sending the wrong message”: did medical marijuana legalization in California change attitudes about and use of marijuana? J Drug Issues 2004; 34: 751–70. 11 Pacula RL, Boustead AE, Hunt P. Words can be deceiving: a review of variation among legally eff ective medical marijuana laws in the United States. J Drug Policy Anal 2014; 7: 1–19. 12 O’Keef K, Earleywine M, Mirken B. Marijuana use by young people: the impact of state medical marijuana laws. 2008. http://docs.mpp. org/pdfs/general/TeenUseReport_0608.pdf (accessed April 16, 2014). 13 ProCon.org. Would allowing the medical use of marijuana send the wrong message to our children and our society? 2014. http:// medicalmarijuana.procon.org/view.answers.php?questionID= 000238#answer-id-000840 (accessed May 23, 2014). 14 Johnston LD, O’Malley PM, Bachman JG, Schulenberg JE, Miech RA. Monitoring the Future national survey results on drug use, 1975–2013: Volume 1, Secondary school students: Ann Arbor: Institute for Social Research, The University of Michigan; 2014. The press has been lapping it up like….well, water: the allegation that marijuana cultivation in California is contributing to the state’s drought crisis. The situation has led to ​local governments passing “urgency” ordinances​ naming the drought as an emergency, and stepping up enforcement against medical marijuana gardens with the same claim. Police are issuing ​press releases​ tallying up the supposed water usage for eradicated crops (which, like their dollar amounts, seem quite inflated). A recent release from the Tulare county sheriff’s department alleged that a 12,000-plant marijuana grow (raided by, among other agencies, the National Guard) was slurping up 61,555 gallons of water a day. Let’s look at the numbers: It’s ​estimated by the Emerald Growers Association​ that, based on final yield, growing marijuana requires an average of one gallon of water per pound, per day. With a 150-day outdoor growing cycle, that amounts to 150 gallons per pound. Indoor growers have estimated their water use at 150-450 gallons per pound, including flushing. With a pound weighing 454 grams, that means cannabis uses, at most, one gallon per gram, and possibly only 1/3 that much. One joint is about a half a gram, so that the water needed to produce one joint is somewhere between 1/6 and ½ gallon. How does this compare to other crops, or inebriants? A glass of wine takes 15-30 gallons of water per glass to produce; beer slightly less. ​A tomato requires 3.3 gallons of water,​ on average, while ​a handful of almonds​ takes 5 gallons (one gallon per nut), and a 1/3-pound hamburger requires 330 gallons. This chart compares the water consumption for single servings of different foods and beverages with that of cannabis, in gallons: Statewide, what is the water footprint for cannabis versus other crops? Cal NORML estimates that in-state annual consumption for California is about 2 million pounds, or one billion grams. That figure could be multiplied by a factor of four to account for marijuana that is diverted out of state. At the high-end estimate of one gallon per gram, that means the cannabis crop in California, licit and illicit, uses around 12,000 acre-feet of water yearly if grown indoors; one third of that if grown outdoors. That compares favorably to grapes, which use 2.2 million acre-feet, rice at 2.8 million-acre feet, and almonds, which soak up 3.7 million acre-feet of water yearly. Overall 35-45 million acre-feet of water is used for agriculture in California, some 80% of the state's developed water supply. (Sources: http://www.motherjones.com/environment/2014/02/wheres-californias-water-...​ and http://www.nrdc.org/water/files/ca-water-supply-solutions-ag-efficiency-...​) This chart compares total water consumption by crop in California to cannabis’s consumption (in millions of acre-feet): The biggest users alfalfa, which requires over 5 million acre-feet of water yearly, ​70% of which goes to feed dairy cows.​ According to an estimate by professor Robert Glennon from Arizona College of Law, ​California is exporting 100 billion gallons of water a year​ to China in the form of alfalfa hay. Fracking​ uses an estimated 80 billion gallons of water yearly, about the same as strawberries. Certainly, there are localized problems regarding water and cannabis cultivation in California. Cal NORML and other groups are in favor of sound environmental regulations and licensing of commercial-sized crops. But put into context, we can see that we can’t use the drought as an excuse to further vilify marijuana. Also see: ​Is Pot Cultivation Starving Us of Water?​ Keith Humphreys, July 2, 2015 Image from "The Humorous Hemp Primer," published by the German government in 1942, the same year the US Government published Hemp for Victory. August 3, 2015 - California NORML has written to Scott Bauer of California Fish and Wildlife questioning his often-repeated estimation that marijuana plants use 5-10 gallons of water every day throughout their growing season (June-October). This figure has been extrapolated to cause law enforcement to overestimate the water consumption of gardens they raid, much as they have always overestimated plant yields and prices. Public officials such as Sacramento County supervisor Roberta MacGlashen have cited the figure as a reason ​to double fines on marijuana patients,​ meaning growing even a single outdoor plant in the county can be cause for a fine of up to $1000/day. The Sacramento Bee ​has editorialized against using water on any outdoor cannabis plants. From what Cal NORML has been able to uncover, Fish and Wildlife did not measure or calculate their water usage estimate,​ but rather lifted data from a 2010 paper from the Humboldt Growers Association and other sources, such as a paper from Chris Van Hook of Clean Green Certification that was written in 2013 to encourage cannabis farmers to store water. Articles co-authored by Bauer in ​Bioscience​ and ​PLOS​ both cite ​a 2010 Humboldt Growers Association calculation​ of six gallons/plant each day, based on commonly used irrigation methods (towards the end of the document). But while HGA farmers tend to grow extremely large plants, those eradicated in the wild generally receive far less attention, meaning they are much smaller and therefore require only a fraction of the water used on plants that look more like trees (see photos). The authors averaged ​an estimate by Mendocino Sheriff Tom Allman​ that large marijuana plants require one gallon of water per day and ​Van Hook's statement​ that in extremely hot weather, large plants can use up to 15 gallons per day to bolster their figure. In an email communication, Van Hook told Cal NORML that at the time he collected data (in 2010) for his 2013 paper, "water was not an issue. I have seen some real improvements since then which is a testament to California agriculture. Just like any agriculture when a problem arises responsible farmers work to improve. I would like to see a new study with some of the water saving improvements I have seen out in the field.” Bauer and his co-authors state: Water use data for marijuana cultivation are virtually nonexistent in the published literature, and both published and unpublished sources for this information vary greatly, from as low as 3.8 liters up to 56.8 liters per plant per day. This is quite a wide range. They continue: The 22.7 liter (6 gallon) figure falls near the middle of this range, and was based on the soaker hose and emitter line watering methods used almost exclusively by the MCSs we have observed. However, how long or often the crops were watered cannot be known from this information. They continue: Because these water demand estimates were used to evaluate impacts of surface water diversion from streams, we also excluded plants and greenhouses in areas served by municipal water districts. Which is exactly what the Sacramento Board of Supervisors oversees. Legal experts say it’s questionable whether or not growers charged criminally can also be subjected to fines under local ordinances, so it’s likely that Sacramento’s ordinance will affect only backyard growers. COMING UP WITH BETTER DATA So far, Sacramento NORML and Cal NORML have canvassed growers from 11 outdoor farms in El Dorado, Placer, Humboldt and Mendocino counties. Water usage has ranged from 1 gallon/plant to 3.5 gallons, although plants were not necessarily watered daily, and less water was used while the plants were still immature. Growers also often scale back on watering at the end of the season, to encourage flowering. Six gallons a day is possible for July and August, but not for 150 days, said one farmer from Mendocino county. ​The average number of gallons used on plants daily was 2.30 in NORML’s study. The more pertinent way to look at the issue is in gallons of water per gram of marijuana bud produced.​ A representative from the Mendocino Cannabis Policy Council said his members tend to grow 2-4 pound plants, with the yield directly related to the amount of water used. Roughly, MCPC and Emerald Growers Association estimate that an average of 1 pound (454 grams) is yielded using an average of one gallon per growing day. So a two-pound plant would require an average of two gallons per growing day, and a four-pound plant would use four gallons. Using the gallon/day/pound ratio means one gallon yields about two grams of processed bud at a growing season of 240 days (a figure which can be reduced down to 90 days with the use of light-depravation techniques). Two growers in Humboldt county said that they reliably grow two-pound plants watering with 2.5 gallons/day (but not necessarily every day). Taken in total, both estimated that it took an average 2/3 of a gallon daily to yield one pound of bud, one saying he multiplied that by 100 growing days. A farmer in Mendocino who uses water conservation techniques estimates using only 0.3 daily gallons per pound of bud. Adding in two farms in the Sacramento area, one that got 1.22 grams/gallon (using Smart Pots that may have lead to evaporation) and a second that yielded 0.87 grams/gallon, ​Cal NORML calculates an average of 0.72 gallons of water is needed to produce a gram of marijuana, no matter how many plants are grown or how big they are. Since a “joint” of marijuana is about 1/2 of a gram, this means a dose of medical marijuana requires less than half a gallon of water. A hamburger requires over 100 gallons of water to produce, and a serving of rice takes around 50 gallons. (Source: ​UNESCO via LA Times​). TURNING WATER INTO WINE VS. WEED We have also investigated the often-repeated statement that marijuana uses twice as much water as do wine grapes, from ​the Bioscience article. Using the author’s figure of 22 L (6 gallons) of water per plant per day from June - October, they state: ...if we assume a planting density of 130,000 plants per km2, water application rates would be approximately 430 million L per km2 of outdoor-grown marijuana per growing season. For comparison, wine grapes on the California north coast are estimated to use a mean of 271 million L of water per km2 of vines per growing season. Marijuana is therefore estimated to be almost two times more “thirsty” than wine grapes, the other major irrigated crop in the region. But let’s look at the output from those acres planted, and the total acreage. Estimates say that about 150-160 gallons of wine are produced per ton of grapes. The amount of grapes grown per acre of land can vary from 2-30 tons, with 4 tons seeming to be the most commonly used figure. Using 8 tons of grapes per acre, we calculate that 26 gallons of water are required to produce a 4-ounce glass of wine. This comes close to the 26-29 gallons/serving of wine from UNESCO data. (For some reason the LA Times, citing UNESCO, says it takes 3.48 gallons of water to produce an ounce of wine, which is why ​we had previously reported it took about 15 gallons of water per glass; calculating directly from UNESCO the figure is 7 gallons per ounce and 28 gallons per glass.) By contrast, we estimate that between 1-1.5 tons of marijuana are produced per acre. Using Fish & Wildlife’s figure of 430 million L per km2, this means ​between 0.63-0.95 gallons of water are used per 1/2 gram serving of marijuana, or 27-41 times less than the water it takes to produce a glass of wine. Now let’s look total acreage. In 2014, ​the USDA reports​ that the total acreage of wine grapes grown in California was 615,000. Our estimates for total acreage of marijuana required for California consumption is 800 acres (with no space between plants); 3000 acres would be a ballpark figure. That ups the differential by a factor of 200, meaning ​overall wine production uses 5000-8000 times more water than does marijuana in California. Wine production has been extremely damaging to rivers and creeks​ in critical salmon-spawning streams. For the past several years, Emerald Growers and other groups have been ​educating farmers about fish-friendly growing practices​ and the ​Small Farmers Association drought management plan calls for goals of 1/2 gallon to 1 gallon per plant for daily use. CULTIVATION BANS IMPEDE WATER REGULATORS Certainly, Cal NORML is concerned about severe, localized problems regarding large marijuana farms and water use. Bauer's articles are about local problems that the press has wildly extrapolated on. PLOS study co-author Lori Pottinger said in answer to an email from Cal NORML "I hope we conveyed that this was a localized problem, that was certainly the intent." Taking a statewide view, even using Bauer’s figures marijuana uses a tiny portion of the water used yearly in the state on almonds (3.7 million acre-feet); grapes (2.8 million acre-feet) and rice (2.2 million acre-feet). Commercial agriculture in California uses an estimated 25-45 million acre-feet of water. By comparison, ​the cannabis industry is estimated to use a mere 3000-15,000 acre feet of water per year.​ ​That means cannabis cultivation uses 0.04 percent or less of all the water used for agriculture in California. In fact, at ​a recent hearing in the Capitol on the drought,​ all the fisheries experts spoke about the problems in the Delta (e.g. Shasta Dam and the Thermolito) but all the law enforcement panelists focused on the Emerald Triangle. Big Ag, in the form of rice farmer and Congressman Doug LaMalfa and his successor ​Sen. Jim Nielsen,​ and ​billionaire pomegranate and pistachio farmer Stuart Resnick via his contributee Sen. Dianne Feinstein,​ have been instrumental in keeping water flowing to farms. Coincidentally(?) LaMalfa, Nielsen and Feinstein are all against marijuana legalization. Ironically, counties like Sacramento, Butte, Shasta, Tehama and Fresno that have cultivation bans will be unable to sign up farmers for ​the Central Valley Water Board’s pilot program regulating water use and discharge,​ due to be finalized in October. Cal NORML has long worked for regulation of commercial marijuana gardens at a state level, and is participating in discussions about AB 266 and AB 243, which would finally provide oversight on the state’s 19-year-old medical marijuana law. Marijuana Odor Perception: Studies Modeled From Probable Cause Cases Richard L. Doty,1,3 Thomas Wudarski,1 David A. Marshall,1,2 and Lloyd Hastings1 The 4th Amendment of the United States Constitution protects American citizens against unreasonable search and seizure without probable cause. Although law enforcement officials routinely rely solely on the sense of smell to justify probable cause when entering vehicles and dwellings to search for illicit drugs, the accuracy of their perception in this regard has rarely been questioned and, to our knowledge, never tested. In this paper, we present data from two empirical studies based upon actual legal cases in which the odor of marijuana was used as probable cause for search. In the first, we simulated a situation in which, during a routine traffic stop, the odor of packaged marijuana located in the trunk of an automobile was said to be detected through the driver’s window. In the second, we investigated a report that marijuana odor was discernable from a considerable distance from the chimney effluence of diesel exhaust emanating from an illicit California grow room. Our findings suggest that the odor of marijuana was not reliably discernable by persons with an excellent sense of smell in either case. These studies are the first to examine the ability of humans to detect marijuana in simulated real-life situations encountered by law enforcement officials, and are particularly relevant to the issue of probable cause. KEY WORDS: marijuana; psychophysics; law; olfaction; magnitude estimation. The 4th Amendment of the United States Constitution protects American citizens against unreasonable search and seizure without probable cause. Probable cause for search occurs when known facts and circumstances of a reasonably trustworthy nature are sufficient to justify a person of reasonable caution and prudence in the belief that a crime has been or is being committed (Draper v. United States, 1959). Although this definition is common to most legal textbooks, the subjective nature of this justification can be problematic in practical application. This issue becomes 1Smell and Taste Center, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania. 2Dr. David A. Marshall is deceased. 3To whom correspondence should be addressed to Smell and Taste Center, University of Pennsylvania Medical Center, 5 Ravdin Building, 3400 Spruce Street, Philadelphia, Pennsylvania 19104; e-mail: doty@ mail.med.upenn.edu. Law and Human Behavior, Vol. 28, No. 2, April 2004 ( C° 2004) 223 0147-7307/04/0400-0223/1 C° 2004 American Psychology-Law Society/Division 41 of the American Psychology Association particularly troubling when the sensory perception of weak stimuli, such as faint odors, is the basis for search. Law enforcement officers often justify searches with their sense of smell when other more tangible criteria are not present. This type of encounter often occurs when the odor of marijuana (Cannabis sativa L.) is the basis for probable cause for entering vehicles and dwellings to search for illicit drugs (e.g., United States of America v. Boger, 1990; United States of America v. Ellis, 1998; United States of America v. Reilly, 1994; United States of America v. Shates, 1995). Unfortunately, little research exists on the human capacity to detect marijuana’s odor in either laboratory or specific real-life situations, despite its widespread acceptance by law enforcement. This dearth of information bears considerable legal consequence, because courts often accept the argument, prima facie, that marijuana’s odor can always be detected. In one instance, for example, police officers reported the smell of marijuana when a subsequent search revealed only cocaine (United States of America v. Harris, 1994). This case exemplifies the misappropriate use of smell for probable cause, and clearly illustrates a grave problem that must be addressed. It is generally believed that the characteristic marijuana odor can be discerned from a wide variety of C. sativa plants, regardless of their geographic origin, strain, extent of processing, and tetrahydrocannabinol (THC) content. However, such beliefs are based largely on anecdote, and there is a disturbing absence of quantitative information on this topic. One study reports that all volatile oils prepared from freshly collected C. Sativa buds have a characteristic marijuana smell (Ross & El Sohly, 1996), although no formal organoleptic investigation was made. It is not clear whether subtle differences exist in the smell of these oils, but it has been suggested that the essential oil of C. sativa may differ enough among geographic locations to serve as a chemical marker for general origin or type (Hemphill, Turner, & Mahlberg, 1980). However, the considerable variability in the chemical composition of such volatiles among plants even from the same location may make such discernment extremely difficult, if not impossible (Hood & Barry, 1978). The present studies arose from the need to better understand the nature of marijuana’s odor and whether humans can discern this odor in situations modeled from “real-life” law enforcement encounters. The first set of experiments investigated a situation in which the arresting officer reportedly discerned processed marijuana within an automobile trunk from the passenger compartment. In this work, we initially determined whether marijuana odor was discernible through the walls of the plastic bag containing the marijuana. Following confirmation of this point, we determined whether this discernment could occur inside the passenger’s compartment of a car when the trunk contained the same packaged marijuana. The second set of experiments was based upon a situation present in an illicit marijuana grow house in northern California. In the grow house, odors from immature Cannabis sativa plants were combined with diesel exhaust from a generator and expelled out through a chimney. Law enforcement officials reported being able to smell the marijuana from a road several hundred yards away, and subsequently used this odor as probable cause for a search. In this second set of studies, we first sought to determine whether the odor of immature marijuana plants differs in quality or intensity from that of mature marijuana plants. We then investigated whether participants 224 Doty, Wudarski, Marshall, and Hastings were able to smell marijuana odor from a mixture emanating from immature C. sativa plants when combined with diesel engine exhaust. The ratio of marijuana odor to exhaust was modeled from the chimney effluence of the illicit California grow room. EXPERIMENT 1 Study 1 The purpose of this study was to determine whether a group of men and women could distinguish the odor of packaged marijuana from that of a matched blank odor source. Methods Participants. Five men and four women recruited from advertisements placed on community bulletin boards served as participants. None reported being a smoker of marijuana, and all were nonusers of tobacco products. Most were in their “20s” (median = 27 years) and all reported being in good general health. All were medication-free, and scored within normal limits on the University of Pennsylvania Smell Identification Test (UPSIT), a standardized olfactory test (Doty, 1995; Doty, Shaman, & Dann, 1984). Test Procedures. Prior to formal testing, the participants familiarized themselves with the odor of a sample of processed Mexican marijuana supplied by the New Jersey Attorney General’s Office. A State law enforcement official was present during the testing and was custodian of the marijuana. Formal testing was performed in a 14 £ 17 ft2 room with excellent air circulation. Each participant was blindfolded and led in one at a time at approximately 5-min intervals, at which point they were asked to sniff two garbage bags in succession (“Hefty” brand, 2-ply, 1.5 mil). One contained five 1-pound packets of pressed and processed Mexican marijuana and the other newspapers crushed and bundled in a similar fashion. Each participant was then required to report the bag that smelled most like marijuana. Half of the participants received the marijuana-containing bag first, so as to counterbalance test order. Results All nine participants reliably and unequivocally reported the garbage bag containing marijuana to have a marijuana-like smell, and none reported the control garbage bag as having such an odor (Binomial test, p < .002). Study 2 The purpose of this study was to assess whether participants can reliably smell, from the driver’s compartment of an automobile, the odor of the marijuanacontaining garbage bag housed in the trunk. Marijuana Odor Perception 225 Methods Participants. The nine participants described in Experiment 1, who were now experienced in recognizing the odor of marijuana, participated in this study. Test Procedures. This experiment was designed to simulate the conditions present when a 1983 2-door Chevrolet was searched for the presence of marijuana. Thus, the same automobile was provided by the State of New Jersey for this study, and the temperature at testing was only 0.6±C different than on the day of the arrest. In the real- life situation, the estimated time that the marijuana had remained in the closed trunk prior to driving away from the procurement site was 20 min, followed by 10 min within the trunk with the heater on and the windows shut. In this study, four test sessions were conducted with either the marijuana or blank bag in the trunk compartment of the automobile. The bag was placed in the trunk for 20 min, and then the automobile was driven for 10 min. The automobile was then parked in the street where an experimenter monitored the participants and recorded their responses. This study was conducted double blind with neither the tester nor the participant knowing what was in the trunk. A technician was aware of which bag was placed in the trunk during each of the trials, and did not communicate this to anyone else involved until after the study. During each of the four test sessions, the nine panel members were led individually at 2-min intervals to the driver’s side of the automobile. The following instructions were then read to the participant: “When the driver gets out, sniff in the front seat area, and in the back seat area, and tell me if you smell the odor of marijuana. Tell me your response, yes or no, after you have finished sampling and the driver has gotten back into the car and closed the door.” This process was repeated three times within each test session, providing a total of 27 trials per session. The participants were sequestered out of view of the automobile between trials, so they had no knowledge as to whether the odorant stimulus was changed or remained the same during the test session. After each session was completed, the stimulus bag was removed from the trunk and the trunk lid remained open for 5 min to permit airing out before the subsequent session. Results Six of the nine participants reported no marijuana odor being present on any of the six marijuana trials or any of the six nonmarijuana trials (Table 1). In aggregate the number of false positives (9.26%; 5 of 54 trials) was essentially the same as the number of correct positives (12.96%; 7 of 54 trials). A one-tailed Fisher exact probability test revealed no meaningful difference between the hit and false positive rates (p > .20). EXPERIMENT 2 Experiment 2 was conducted in a state sanctioned medical Cannabis growing facility in Northern California. We first addressed whether nonbudding and budding 226 Doty, Wudarski, Marshall, and Hastings Table 1. Hit and False Positive Rates for Identifying the Odor of Marijuana in Experiment 1, Study 2 Participant Gender Hit rate False alarm rate 1 Male 0 of 6 0 of 6 2 Male 0 of 6 0 of 6 3 Male 0 of 6 0 of 6 4 Female 0 of 6 0 of 6 5 Female 0 of 6 0 of 6 6 Female 0 of 6 0 of 6 7 Male 2 of 6 3 of 6 8 Male 1 of 6 0 of 6 9 Female 4 of 6 2 of 6 Totals 7 of 54 5 of 54 marijuana plants produce similar odors. We then investigated if low levels of diesel exhaust fumes could mask the odor of immature marijuana plants. Study 1 Methods Participants. Five men and one woman, ranging in age from 20 to 57 (M = 41.5 years, SD = 14.3), served as participants. These individuals were recruited by word of mouth from the neighborhood surrounding the California grow facility, and all reported being in good general health. All exhibited above average smell function, as measured by the UPSIT (Doty, 1995; Doty, Shaman, & Dann, 1984) Stimuli and Test Procedures. The test stimuli consisted of four immature (nonbudding) female Cannabis plants, one mature (budding) female Cannabis plant, one female tomato plant (Lycopersicon), and one empty container containing planting soil. Only one mature Cannabis plant was used because the odor from this Cannabis plant was distinctive. Female plants were used because they produce more flower biomass than male plants, and are preferred by marijuana growers. Cannabinoids, such as 19- tetrahydrocannabinal, tend to be particularly concentrated in the flowerrelated bracts (Turner, Hemphill, & Mahlberg, 1980). Polyethylene bags with no discernable odor were placed over each of the plants or the planting pot containing soil. The bags were positioned to collect the vapors emanating from the plant and associated potting soil. These vapors were sniffed by participants through a 20-cm long, 2.54-cm odorless PVC tube inserted through a slit in the bags. The temperature of the room in which testing occurred was »21±C. Although all six participants indicated that they were aware of the smell of marijuana, we provided a sample to ensure familiarization with the odor. The participants were not informed of the positioning of the stimulus pots on the sampling table, and wore opaque goggles to preclude visual input. Each participant was guided to the stimulus plant by an experimenter, who inserted the tube into the plant environs. The experimenter then positioned the participant’s hands on the tube so as to enabling them to sniff through its end. The order of smelling the stimuli was systematically counterbalanced both between participants Marijuana Odor Perception 227 and within trial sessions of the same participant to preclude confounding by order effects. At least 45 s was interspersed between trials to minimize possible adaptation effects. The sniffing tubes were also cleaned with ethanol and water after use to eliminate any residual odors that accumulated during the test session. The task of the participants was to report not only whether or not marijuana odor was present, but to quantitatively compare the relative intensity of the total odor using a magnitude estimation procedure. In this procedure odors are related relative to one another without a standardized scale (termed the free-modulus method). Because magnitude estimation numbers are ratio in nature, an assignment by a given participant of 25 to a stimulus theoretically is perceived half as intense as an assignment of 50. This method is well documented in the psychophysical and organoleptic sensory literature (Doty, 1975; Marks, 1988; Moskowitz, Dravnieks, Cain, & Turk, 1974). The judgments were collected on three separate occasions, resulting in a total of 126 trials within the whole study. The median of the three intensity judgments for each participant was used as the intensity test measure. Results The identification data of the six participants revealed that: (i) the mature Cannabis plant was always rated as having a characteristic marijuana odor; (ii) three of the four immature Cannabis plants never were found to have a distinctive marijuana odor; (iii) one of the four immature Cannabis plants was always rated as having a marijuana-like smell; and (iv) the potting soil alone was always reported as having an odor, but never as having a marijuana-like odor. The median magnitude estimates of the odor intensity for the potting soil, immature marijuana, mature marijuana, and tomato plant stimuli were calculated, and because magnitude estimation numbers are arguably ratio in nature, we determined ratios of the rated intensities relative to the baseline estimates of potting soil. These ratios are presented in Table 2. Table 2. Magnitude Intensity Estimates Adjusted in Relation to the Intensity Estimates of Potting Soil for Participants in Study 1 of Experiment 2 Median odor intensity estimates in relation to those of potting soil Participant Immature Cannabis Mature Cannabis Immature Lycopersicon (Tomato plant) 1 1.28 57.14 0.57 2 2.00 10.00 2.00 3 1.00 2.00 1.00 4 0.97 1.11 0.69 5 0.83 3.33 1.33 6 2.00 5.00 1.50 Note. For example, the first participant found the odor of immature marijuana to be 1.28 times more intense than the odor of potting soil alone, whereas the second found this odor to be two times more intense than that of the potting soil. 228 Doty, Wudarski, Marshall, and Hastings It is clear from Table 2 that all six participants found the volatiles emanating from the mature marijuana plant to be more intense than the volatiles emanating from the immature marijuana plants or from the tomato plant. Statistical analysis using the nonparametric Wilcoxin matched-pairs signed ranks test revealed that volatiles emanating from the mature Cannabis plant were judged as having a significantly stronger odor than both the volatiles from the immature Cannabis plant and the tomato plant (p < .025). Additionally, the intensities of the immature Cannabis plants did not differ significantly from the tomato plant. Study 2 The purpose of Experiment 2 was to determine whether diesel exhaust odor could mask the odor of volatiles from Cannabis sativa L under a specific set of “realworld” circumstances. We aimed to conservatively model, within reasonable bounds, a situation present in the aforementioned California grow room where the exhaust of volatiles from immature Cannabis sativa plants were combined with diesel exhaust from a generator and expelled outside through a chimney. In effect, we sought to determine whether the odor of marijuana volatiles could be discerned from the background of diesel exhaust odor under conditions similar, or even more stringent, to those in this specific situation. Methods Participants. Five of the 10 participants in this experiment were the male par- ticipants of Study 1. One new participant was a female, and the other four new participants were male. The UPSIT was administered to three of these additional individuals and all were within normal limits. The remaining participants reported no problems smelling, although their sense of smell was not formally evaluated. Three of the five new participants reported having intimate knowledge of the smell of marijuana and admitted to being occasional or regular marijuana smokers. Procedures. We employed an olfactometer capable of providing, for nasal sam- pling, a mixture of diesel exhaust and Cannabis volatiles in the relative proportions estimated to have been present within the chimney effluence of the illicit marijuana grow room (see Fig. 1). In this system, clean room air was pumped into two identical 114-l galvanized steel chambers at a rate of 68 l/min. In one of the 114-l chambers, two marijuana plants (»38 cm high) were situated; the other housed identical containers and potting soil, but no plants. To produce and maintain a temperature in these chambers equivalent to that present in the illicit grow room (approximately 27±C), digital temperature probes and 150-watt light bulbs were placed within them. The chamber temperatures were continuously monitored and the intensity of the light bulbs adjusted via a rheostat to maintain the temperatures at the desired level (range: 25±–28±C). It should be noted that the two Cannabis plants employed in this study were selected from a larger number of similar plants available to us at the growing facility. We did not wish to bias the selection procedure, so none of these plants had been Marijuana Odor Perception 229 Fig. 1. Schematic diagram of olfactometer that allowed for mixing of diesel odor and marijuana volatiles for sampling by participants. signifies ball valves. previously smelled. Each was assigned a number, and the two numbers chosen were determined using a random process. The output of the olfactometer was channeled through a PVC pipe to a sampling port from which the participants made their observations. During the intertrial intervals, the test mixture was directed from the sniffing port. The basic parameters that had to be met or exceeded in the simulation were derived from measurements of the illicit California grow room and were as follows: (i): the volume of the air in the grow room (190.5 m3); (ii) the number of immature plants reportedly housed in the grow room (440); (iii) the air flow through the grow room (calculated at 65.14 l/min); and (iv) the empirically determined flow rate of diesel engine exhaust (3.8 m3 per minute at 19±C). The degree of dispersion of chimney effluent into the ambient air, which would dilute the effluent considerably and make detection even more difficult, was not included in the model. In the original situation, one plant occupied 0.43 m3. However, the plants in the original illicit grow room were somewhat larger than those available to us for study. Therefore, because one plant originally occupied 0.43 m3, we placed two plants in the galvanized steel container (114 l). This provided a cushion of error to compensate for differences in plant density and any minor errors that may be present elsewhere in the model (e.g., differences between actual and measured flow rates). Additionally, a higher ratio of marijuana (or potting soil chamber) air to diesel exhaust effluent was employed to make even more conservative the test as to whether marijuana odor could be discerned within diesel exhaust. The psychophysical paradigm consisted of 20 test trials given to 17 of the test participants. The number of trials of three participants was abbreviated because of schedule conflicts, resulting in 19 trials in two cases and 15 trials in the remaining case. In sum, 193 total trials were completed in the experiment. On half of the trials the diesel exhaust was presented with no marijuana odor (i.e., just the odor of potting 230 Doty, Wudarski, Marshall, and Hastings soil), and on the other half the diesel exhaust was presented with the volatiles emitted from the marijuana plants and their potting soil. After switching the valves to a new test condition, 3–5 min were allowed to pass before testing commenced to insure adequate purging of the odors from the previous test condition. The entire test session lasted approximately 3 hr. Each participant was tested individually and was instructed not to discuss his or her responses with the other participants. No information regarding the probability of a marijuana trial relative to a blank trial was provided. All participants received testing on a specific trial before the olfactometer was reset for the next trial. The task of each participant on each trial was to answer two basic questions: (i) do you smell diesel exhaust?; and (ii) do you smell marijuana odor? Results No convincing evidence was present in the data that any of the participants could reliably detect the marijuana odor embedded in the diesel fumes. A onesided Fisher exact probability test revealed no meaningful difference between the hit (6 of 96 trials) and false positive (3 of 96 trials) rates, implying that this level of responding to the diesel + marijuana vapor stimulus is within a range expected by chance. Hence, the data provided no statistical support for the notion that human participants can discern marijuana odor from diesel odor under the conditions of this experiment. GENERAL DISCUSSION In Experiment 1, we demonstrated that the odor arising from 2.5 kg of processed Mexican C. sativa is clearly discernable through a tightly sealed garbage bag sniffed at point- blank range. However, when the marijuana-containing garbage bag was placed in the trunk of an automobile under conditions analogous to those present in an actual search and seizure operation, there was no convincing evidence that the marijuana odor could be discerned. In Experiment 2, we demonstrated that odors emanating from immature female marijuana plants are much less intense on average than odorous volatiles emanating from mature female marijuana plants. We also discovered no marijuana-like odor could be discerned in most immature marijuana plants. Consequently, participants were also unable to discern the odor of immature marijuana plants when they are mixed with diesel exhaust fumes in a ratio modeled from a real-life growing situation in an illicit California grow room. This failure to accurately discern marijuana was nearly absolute, with low false alarm and false positive rates. This presumably reflects, on the part of participants familiar with this odor, the expectation of a distinct marijuana smell that rarely, if ever, presented itself. A more liberal criterion, that is, a tendency to make both higher hit and false alarm rates, would be expected in persons who would have greater benefit in detecting the presence of marijuana, as might occur in some law enforcement situations. These studies represent the first step in better understanding the nature of marijuana’s odor and situations in which it can be perceived. However, these experiments Marijuana Odor Perception 231 are potentially limited to the rather specific conditions under which they were per- formed, and by the relatively small number of participants tested. Thus, their findings need not necessarily generalize to other, even seemingly similar, situations. For example, temperature is known to influence the release and diffusion of molecules from plant products. The inability to detect marijuana located in the trunk of a car from the driver’s window may be different in on a hot summer day than under the winter conditions present in Experiment 1. The participants of Experiment 1 had limited experience with marijuana odor, unlike the participants of Experiment 2. The degree to which use, or long-term experience with, marijuana-containing products on the ability of participants to recognize marijuana odor is unknown. In general, participants who are formally trained to recognize tastes and odors perform better on psychophysical tests, suggesting that training can alter some indices of performance (Smith, Doty, Burlingame, & McKeown, 1993). The contention that law enforcement officers may be more accurate than laypersons in detecting marijuana by odor, however, requires substantiation. Other factors, including gender and age, may have a much more salient influence on the ability to smell and to detect marijuana at low concentrations (Doty et al., 1984). Just as with canines, standardized procedures are needed to establish the smell ability of law enforcement officers who are called on to testify about odors of elicit drugs. Importantly, one must not overlook the fact that expectation or suggestion can often dictate the likelihood of a person believing that they smell an odor, a common problem in environmental annoyance issues. In the field of olfactory psychophysics, some participants report detecting odors even on blank trials (van Langenhove & Schamp, 1989). This phenomenon is illustrated by a demonstration described by William James, the eminent nineteenth Century psychologist (James, 1890). Professor James told a classroom of students that he was about to open a small bottle with a very strong odor in it, and that they were to raise their hands when they first noticed the smell. A few minutes after removing the bottle top, students in the first rows of the lecture hall began raising their hands, and in a matter of minutes the whole room was filled with raised hands. In fact, the bottle had no discernible smell, containing only the vapors of water and a dying agent used to the make the water look dark! The present findings throw into question, in two specific instances, the validity of observations made by law enforcement officers using the sense of smell to discern the presence of marijuana. Although these instances reflect a very small set of studies with very specific constraints, they do suggest that a blanket acceptance of testimony based upon reported detection of odors for probable cause is questionable and that empirical data to support or refute such testimony in specific cases is sorely needed. ACKNOWLEDGMENTS This work was supported, in part, by funds from the Attorney General’s Office of the State of New Jersey and from the United States District Court, Northern District of California, San Francisco, California. 232 Doty, Wudarski, Marshall, and Hastings Marijuana Odor Perception 233 REFERENCES Doty, R. L. (1975). An examination of relationships between the pleasantness, intensity, and concentration of 10 odorous stimuli. Perception and Psychophysics, 17, 492–496. Doty, R.L. (1995). The Smell Identification TestTM administration manual (3rd ed.). Haddon Heights, NJ: Sensonics, Inc. Doty, R. L., Shaman, P., Applebaum, S. L., Giberson, R., Siksorski, L., & Rosenberg, L. (1984). Smell identification ability: Changes with age. Science, 226, 1441–1443. Doty, R. L., Shaman, P., & Dann, M. (1984). Development of the University of Pennsylvania Smell Identification Test: A standardized microencapsulated test of olfactory function. Physiology and Behavior, 32, 489–502. Draper v. United States, 358 U.S. 307, 79 S.Ct. 329, 3 L.Ed.2d 327 (1959). Hemphill, J. K., Turner, J. C., & Mahlberg, P. G. (1980). Cannabinoid content of individual plant organs from different geographical strains of Cannabis sativa L. Journal of Natural Products, 43, 112–122. Hood, L. V. S., & Barry, G. T. (1978). Headspace volatiles of marijuana and hashish: Gas chromatographic analysis of samples of different geographic origin. Journal of Chromatography, 166, 499–506. James, W. (1890). Principles of psychology. New York: Holt. Marks, L. E. (1988). Magnitude estimation and sensory matching. Perception and Psychophysics, 43, 511–525. Moskowitz, H. R., Dravnieks, A., Cain, W. S., & Turk, A. (1974). Standardized procedure for expressing odor intensity. Chemical Senses and Flavour, 1, 235–237. Ross, S. A., & El Sohly, M. A. (1996). The volatile oil composition of fresh and air-dried buds of Cannabis sativa. Journal of Natural Products, 59, 49–51. Smith, R. S., Doty, R. L., Burlingame, G. K., & McKeown, D. A. (1993). Smell and taste function in the visually impaired. Perception and Psychophysics, 53, 649–655. Turner, J. C., Hemphill, J. K., & Mahlberg, P. G. (1980). Trichomes and cannabinoid content of developing leaves and bracts of Cannabis sativa L. (Cannabaceae). American Journal of Botany, 67, 1397–1406. United States of America v. Ronald J. Boger, 755 F. Supp. 333 (1990). United States of America v. Deborah Ellis, 15 F. Supp. 2d 1025 (1998). United States v. Harris, 31 F.3d 153, 156 (4th Cir. 1994). United States of America v. Keven C. Reilly, 875 F. Supp. 108 (1994). United States of America v. Norris Shates, 915 F. Supp. 1483 (1995). Van Langenhove, H., & Schamp, N. (1989). Encyclopedia of environmental control technology (Vol. 2, pp. 935–963). Houson: Gulf Publishing. Marijuana Equivalency in Portion and Dosage August 10, 2015 Prepared for the Colorado Department of Revenue An assessment of physical and pharmacokinetic relationships in marijuana production and consumption in Colorado The authors are grateful for suggestions and assistance from Lewis Koski, Ron Kammerzell, Jim Burack, Dr. Franjo Grotenhermen, M.D., Dr. Kari Franson, M.D., and all the businesses that hosted the team and contributed information to this study. Any omissions or errors are the sole responsibility of the report team. This report was commissioned under Colorado HB 14-1361. The Colorado Department of Revenue retained the University of Colorado, Leeds School of Business, Business Research Division, in partnership with the Marijuana Policy Group, and BBC Research & Consulting, to produce an unbiased and scientifi c report for the purpose of rulemaking by Colorado stakeholders. Version 12 / August 10, 2015 Corresponding author: Adam Orens aorens@mjpolicygroup.com Authors Adam Orens Miles Light Jacob Rowberry Jeremy Matsen Brian Lewandowski MPG Marijuana Policy Group Marijuana Equivalency in Portion and Dosage An assessment of physical and pharmacokinetic relationships in marijuana production and consumption in Colorado 4 Equivalency Report Table of Contents EXECUTIVE SUMMARY 6 Physical Equivalency 6 Pharmacokinetic Equivalency 7 Market Price Equivalency 8 OVERVIEW AND MOTIVATION 11 Production, Price, and Dosing Equivalencies 11 Use of Metrc™ Data 12 PREVAILING MIP PRODUCTION TECHNIQUES 13 THC vs. THCa 13 Production Technique Summary 13 Hydrocarbon Extraction Process 14 Carbon Dioxide Extraction Process 15 Butter and Cooking Oils 15 Other Solvents 16 PHYSICAL EQUIVALENCY CALCULATIONS 17 Alternate Methodology 21 PHARMACOLOGICAL EQUIVALENCIES 23 Enumeration of THC Uptake Methods for Marijuana 23 THC, THCa, 11-OH-THC and THC-COOH 24 Identifi cation of THC Uptake and Benchmarking 24 Role of the Blood-Brain-Barrier (BBB) 27 Constructing Dosing Equivalencies for Marijuana Products 28 Identifi cation of Parameter Values 30 A Worked Example 33 Resulting Equivalency Tables 34 Oils, Tinctures, Lotions, and Less Common Uptake Methods 35 MARKET PRICE COMPARISON 36 REFERENCES 41 TERMS & ACRONYMS 44 6 Equivalency ReportEXECUTIVE SUMMARYgrown in Colorado and may not share similarities with product in other regions. Overall, the study is designed to meet the requirements of Colorado House Bill 14-1361 and focuses solely on the retail adult-use marijuana market in Colorado. PHYSICAL EQUIVALENCY Physical equivalencies were calculated in two ways – a THC equivalency, and a physical production equivalency. Physical equivalencies were calculated for the major concentrate and infused product manufacturing tech- niques, including butane hash oil, CO2 oil, ethanol, and water. Physical production equivalency is calculated by isolating the marijuana trim and shake inputs and deter- mining a yield ratio. The THC methodology provides an equivalent amount of THC in various forms of marijuana products based on recent state testing information Table ES-1 shows equivalency factors for both methodologies by solvent type. The physical equivalencies in Table ES-1 show that between 347 and 413 edibles of 10mg strength can be produced from an ounce of marijuana, depending on the solvent type and production method. For concentrates, between 3.10 and 5.50 grams of concentrate are equiv- alent to an ounce of fl ower marijuana. The THC equivalency factors in Table ES-1 can be inter- preted as showing units with equivalent amounts of THC based on recent state testing data. For instance, given the uniform dosage amounts of edibles in Colorado,434 edibles of 10mg strength and one ounce of fl ower mari- juana at average potency have an equivalent amounts of THC. For concentrates, between 6.91 and 8.50 grams of concentrate (depending on solvent) and an ounce of fl ower marijuana at average potency have an equivalent amount of THC. The original legislation to legalize and regulate marijuana in Colorado does not explicitly restrict marijuana concen- trates and infused edibles. Over time, these marijuana products have become more popular, prompting new legislation to remedy the omission. House Bill 14-1361 now stipulates limits upon marijuana fl ower portions, “or their equivalent.” This study provides scientifi c and data driven evidence in order to understand these equivalencies. The results provide comparisons between marijuana fl ower, concen- trates and infused products specifi cally for Colorado’s marijuana market. Equivalency can be viewed from three perspec- tives: production, dosing, and market price. The fi rst perspective relates to physical production, where infused edibles or concentrates are traced back into their corre- sponding weight of fl ower or trim inputs. This enables the conversion from non-fl ower products into a common fl ower-based denominator, so that aggregate use can be measured across different marijuana product types. The second perspective uses pharmacology to develop a dose-equivalent measure across product types. The results equate the dosing effects between inhaled and ingested marijuana products. Finally, the third perspective uses Colorado potency and market data to convert mari- juana retail prices into their unit-THC equivalents. These THC-based prices are then compared across product types. A powerful and reassuring fi nding is that Colo- rado’s market prices refl ect, almost identically, the dosing equivalencies found in the pharmacological review. The pricing perspective is a new methodology, made possible by analyzing recently collected data from Colorado’s retail marijuana market. The information contained in this report is specifi c to Colorado in 2015. Production techniques are constantly evolving, and the marijuana included in this study was Executive Summary Equivalency Report 7 EXECUTIVE SUMMARYThe conversion factors described above are the fi rst of their kind. They can be useful for state-level production management. The conversions allow units of infused edibles and concentrates to be denominated by fl ower weight, and then added to fl ower sales, in order to determine retail market demand and supply. PHARMACOKINETIC EQUIVALENCY An important compliment to the physical THC relation- ships identifi ed in this study is the pharmacological perspective. If the purpose of the equivalency legislation is to limit transactions or possession to a reasonable “dose” of concentrates and marijuana products for residents and non-residents, then the medical effects described here will be useful to construct a set of equivalencies between marijuana product types. Pharmacokinetic equivalency incorporates fi ndings from medical and pharmacological publications to inform marijuana stakeholders about the dosing process. The authors created a new mathematical construct that can compare ingested and smoked marijuana products in a consistent manner. The pharmacokinetic model compares inhaled and ingested products using a dose ratio. The calculations are based upon different uptake routes and speeds for the psychoactive compounds related to marijuana use (e.g., THC and 11-OH-THC). Other compounds, such as cannabinoids, are not included here because the legislation relates only to retail use. The base pharma- cokinetic equivalency ratio is 1 to 5.71. This means that one milligram of THC in edible form, is equivalent to 5.71 milligrams of THC in smokable form. Table ES-1. One Ounce Equivalents by Solvent Type Source: Author calculations based on metrc™ data. 1-Ounce Flower Equivalents Physical Equivalency THC Equivalency Amount Amount Amount Amount Edibles Concentrate (g) Edibles Concentrate (g) Solvent Type (10mg) (Avg. Potency) (10mg) (Avg. Potency) Butane 391.07 5.46 434.35 6.91 CO2 346.96 4.84 434.35 8.07 Butter/Lipid 413.49 N/A 434.35 N/A Ethanol N/A 5.44 N/A 7.37 Water N/A 3.10 N/A 8.50 8 Equivalency ReportEXECUTIVE SUMMARYtypical prices for the products themselves. The middle portion shows the price after conversion—in cents per milligram THC (₵/MGTHC). Finally, the bottom portion computes the price-ratio between products using the THC price measure. Table ES-3 shows the price of marijuana fl ower, or buds, is $14.03 when purchased by the gram, or $264 when an ounce is purchased. When converted to THC, the same product costs 8.25 cents per milligram THC when purchased by the gram, and 6.10 ₵/MGTHC for an ounce, refl ecting some volume-pricing. Similarly, a typical 100mg THC edible product costs $24.99, a 40mg product is $19.81, and a single-serve 10mg THC edible costs $6.60. When converted, the THC price for these products equals 24.99 ₵/MGTHC, 35.00 ₵/MGTHC, and 66.00 ₵/MGTHC respectively, for these goods. Finally, concentrates cost $55.00 for a typical 1 gram wax portion, and a typical 500mg vaporizing cartridge costs $66.00. The THC prices are 8.46 ₵/MGTHC and 18.86 ₵/MGTHC, respectively. Using the THC prices, the edibles to fl ower price ratio is 3.03 (edible THC per fl ower THC) for the 100mg edible product, 3.00 for the 80mg product, and 4.24 for the 40mg product. The 10mg single-serving ratio is 8.00, which we believe refl ects a minimum price for small portions. Table ES-2 shows the pharmacokinetic equivalencies, and the corresponding serving equivalencies, using data from Colorado. Pharmacokinetic equivalencies indicate that 83 ten- milligram infused edible products is equivalent to one ounce of marijuana fl ower in Colorado. About 7.72 grams of concentrate is equivalent to an ounce of fl ower marijuana. MARKET PRICE EQUIVALENCY For comparison, a third equivalency approach was developed by the study team. This is the “market price equivalency” method. As with the physical equivalencies, this methodology was previously not possible. We use metrc™ data to convert retail store market prices into a price per unit of THC across different products. These new THC-based prices refl ect the inherent value of each product from a psychoactive dose viewpoint. They reveal the price that consumers are willing to pay for the psycho- active experience (the high) yielded from each type of product. Table ES-3 below shows representative marijuana product pricing in Colorado’s retail market. The top portion shows Table ES-2. Pharmacokinetic Dosage Equivalency Source: Author calculations based on metrc™ data. Average THC Potency Effective Uptake Ratio 1 Gram Equivalent 1 Ounce Equivalent Buds/Flower 17.1% 1.00 1 Gram 1 Ounce Edibles N/A 5.71 3 Servings 83 Servings Concentrates 62.1% 1.00 0.28 Grams 7.72 Grams Equivalency Report 9 EXECUTIVE SUMMARYThe ratio for wax/shatter is 1.03 for a 1 gram container, and 2.28 for a 500mg vaporizer cartridge. The higher price ratio for vaporizing equipment may refl ect higher packaging costs. In general, the price ratios shown in Table ES-3 are notable because they match—quite closely—to the phar- macokinetic equivalency ratios. This means that although the market participants may not have completed their own pharmacokinetic research, they naturally have gravi- tated toward this result, based simply upon trial and error. The remainder of this report provides details regarding the data, the methodologies, and previous scientifi c fi ndings used to construct our results. 10 Equivalency ReportEXECUTIVE SUMMARYTable ES-3. THC Market Price Equivalencies Note: 1. Prices taken from a sample of online retail menus for Colorado stores. 2. Ratios may not necessarily apply to other states.. Source: Colorado Storefront menus, calculations by the report study team. THC Market Price Ratios in Colorado Indicative Prices by Weight ($) Buds/Flower 1 Gram 1/8 Oz 1/4 Oz 1 Ounce Most Common $14.03 $41.27 $82.54 $264.14 Discounted $12.38 $33.03 $66.06 $239.43 Edibles 100 MG 80 MG 40 MG 10 MG Edible Variety $24.99 $19.81 $14.00 $6.60 Concentrates 1 Gram 500 MG 250 MG Wax / Shatter $55.00 -- -- -- Vape Cartridge -- $66.00 $46.00 -- Equivalent Market Price (Cents per MG THC) Buds/Flower 1 Gram 1/8 Oz 1/4 Oz 1 Ounce Most Common 8.25 6.94 6.94 6.10 Discounted 7.28 5.55 5.55 5.53 Edibles 100 MG 80 MG 40 MG 10 MG Edible Variety 24.99 24.76 35.00 66.00 Concentrates 1 Gram 500 MG 250 MG Wax / Shatter 8.46 -- -- -- Vape Cartridge -- 18.86 26.29 -- THC Market Price Equivalencies (Price Ratios in THC Units) Buds/Flower 1 Gram 1/8 Oz 1/4 Oz 1 Ounce Most Common 1.00 1.00 1.00 1.00 Edibles 100 MG 80 MG 40 MG 10 MG Edible Variety 3.03 3.00 4.24 8.00 Concentrates 1 Gram 500 MG 250 MG Wax / Shatter 1.03 -- -- -- Vape Cartridge -- 2.28 3.19 -- Equivalency Report 11 SECTION ISECTION IISECTION IIISECTION IVSECTION VThe fi rst perspective is from a physical production view- point, where servings of infused edibles or concentrates are converted into the respective weight of marijuana fl ower or trim needed as inputs to production. To construct these equivalencies, average yield and potency is esti- mated by the consultants after a series of interviews with Marijuana Infused Product (MIP) manufacturers, and by analyzing the state’s Marijuana Enforcement Tracking Reporting Compliance (metrc™) database to isolate input and output packages at MIPs for various concentrates and infused edibles. This metric will provide a bridge between concentrate and infused edible output and plant material inputs. The second perspective computes equivalencies from a dosing viewpoint. The dosing perspective provides stakeholders with a pharmacological model that equates the dosing effect between inhaled and ingested mari- juana products. The pharmacological approach resolves the disparity between weight-based THC content in mari- juana products, so that a dose-equivalent measure can be established. Finally, the third perspective computes the market price of THC across product types in the Colorado market- place. The pricing perspective is a new methodology. It was made possible by manipulating recently collected data from Colorado’s retail marijuana market. By using statewide inventory and testing data, the study team can convert retail marijuana store price for fl ower, concen- trates, and infused edibles into a price with a common denominator—THC. The study team found that the pricing structure in stores refl ects, almost exactly, the phar- macokinetic dosing equivalencies found in this report. This suggests that although no individual has explicitly measured the dosing effect of different products, that the marketplace refl ects the dosing value for each product implicitly. The original legislation to legalize and regulate marijuana in Colorado for adult use did not include explicit purchase restrictions on marijuana concentrates and infused edibles. As these marijuana products grew more popular in 2014, up to 35 percent1 of statewide retail sales, legis- lation was enacted under House Bill 14-1361 to remedy the omission. The legislation does so by stipulating limits upon marijuana fl ower portions, “or their equivalent.” This study provides unbiased, scientifi c information that can be used to suggest appropriate equivalencies between fl ower and alternative marijuana products. It is a summary of how different marijuana products are produced and consumed in accordance with House Bill 14-1361, which requires the state to conduct a study to establish equivalencies. The information in this study can be used to convert concentrate and infused products into their fl ower weight equivalents from both a production and consumption viewpoint. From a production viewpoint, the fi ndings can be used to translate marijuana product unit sales into their weight equivalent. This will improve the measurement of aggregate marijuana demand, by using a common denominator. From a consumption viewpoint, the fi ndings here can be used to establish an equivalent “dose” amount between non-fl ower products and fl ower weight. Overall, the study is designed to meet the requirements of House Bill 14-1361 and focuses solely on the retail adult-use marijuana market. Issues related to medical marijuana are not addressed in this study. PRODUCTION, PRICE, AND DOSING EQUIVALENCIES This study investigates marijuana equivalencies from three perspectives: production, price, and dosing. 1 Based upon statewide retail sales, May – September 2014. Overview and Motivation 12 Equivalency ReportSECTION ISECTION IISECTION IIISECTION IVSECTION Vremove outliers and questionable records. The sample sizes used in the analysis represent the largest samples we could pull from the system that we believed would give reliable results. The report is organized as follows: Section II provides a summary of prevailing MIP production techniques, followed by the calculation of production equivalencies in Section III. In Section IV, a pharmacokinetic model is developed and dosing equivalencies are defi ned. Section V explains the market price equivalency methods and fi ndings, and Section VI provides a brief summary of the study fi ndings. Following Section VI is a dictionary of marijuana terms used here, as well as a reference list for the interested reader. The science and data related to marijuana, its use, and regulation are inherently complex. The purpose of this report is to synthesize state-level marijuana data with existing manufacturing and medical research in order to construct easy-to-understand ratios between marijuana product types. The resulting information can be used to establish a set of rules that are defensible, operable, transparent and systematic. Over time, as new information evolves, these fi ndings may be reviewed and adjusted to refl ect the most current research available. This analysis and report is developed for use by stake- holders in Colorado’s retail marijuana market. It is assumed that the reader of this report is an informed, intelligent public policy offi cial or individual with experience and understanding of Colorado’s retail and medical marijuana markets. The objective of this report is to provide a clear and understandable synthesis of relationships between marijuana product types. USE OF METRC™ DATA This study would not have been possible before the state inventory tracking system was established. The system allows a viewpoint of the entire state marketplace from “seed to sale”, providing a powerful data arena from which to determine key statistics, such as potency levels, production ratios, and consumption rates, to name a few. Colorado’s inventory tracking platform, metrc™, requires data to be uploaded from every cannabis business. As a result, there is some underlying variability due to user input error by MIPs, cultivations, and retail stores. During this study and during previous studies over the past 18 months, the study team has reconciled most disparities by conducting thorough checks, and through vendor interviews to ensure that data is being interpreted correctly. Over the course of this research, the investi- gators applied generally accepted statistical methods to Equivalency Report 13 SECTION ISECTION IISECTION IIISECTION IVSECTION Vthrough various refi ning techniques to produce a refi ned oil in various consistencies. Potential solvents include hydrocarbons, carbon dioxide, butter/cooking oils/ lipids, ether, ethanol, isopropyl alcohol, water, and dry extraction methods. Several extraction methods involving hydrocarbons and carbon dioxide were borrowed from long-standing methods used in the fragrance and food industries. Over the course of the interviews, it became apparent that while any of the aforementioned solvents can produce a marijuana concentrate or other infused product, commercial producers prefer hydrocarbon, carbon dioxide, and butter/lipid extraction processes. Inter- viewees cited solvent costs, effi ciencies in production, This section provides descriptions of marijuana infused product concentrate production techniques used in commercial MIPs in Colorado. The information contained in this section was obtained through a series of interviews conducted between April 24 and June 18, 2015. The voluntary industry outreach process consisted of 11 in-person interviews, facility tours, and phone interviews with MIP operators and testing facilities. No identi- fying information of specifi c facilities is included in this report to protect the privacy and intellectual property of interviewees. The interviews consisted of the following business types organized by primary production process: • Butane/hydrocarbon concentrates (4); • Carbon dioxide concentrates (2); • Butter-based edibles (2); • Butane/hydrocarbon edibles (2); and • Carbon dioxide edibles (1). In addition to the individual interviews, the study team attended two industry group meetings at the request of the Marijuana Industry Group (MIG) and the Cannabis Business Alliance (CBA). The meetings allowed member businesses to ask questions and provide their input to the study in group format. PRODUCTION TECHNIQUE SUMMARY Several cannabinoid extraction techniques are used in the production of marijuana concentrates and edibles. The majority involve using a solvent process where solvents are introduced to marijuana plant material to form a concentrate. The solvents are then removed THC vs. THCa Marijuana fl ower is often said to contain THC, but this is not technically true. The plant contains “THCa”, which is not psychoactive in its natural state. THC is created through decarboxylation. Decarboxylation is the process of heating THCa, which naturally occurs in cannabis plants, to activate THC that can be absorbed in the body through ingestion. In the process, the THCa loses carbon and oxygen mole- cules, and about 12.3 percent of its weight. This weight reduction is calculated using the molecular weight of THCa and THC. Although the report authors refer to both THC and THCa throughout the report, the reader can interpret the terms as synonomous. Prevailing MIP Production Techniques 14 Equivalency ReportSECTION ISECTION IISECTION IIISECTION IVSECTION Vand output product quality as reasons for using these preferred solvents. Metrc™ data confi rmed that these three solvents account for over 93 percent of edibles production in the state. The interview participants used variations on the three major solvent processes shown above. Each process is described in more detail below. HYDROCARBON EXTRACTION PROCESS Hydrocarbon extraction uses any number of hydro- carbons as the principal solvent. Butane and propane are the most common solvents used in commercial opera- tions. When cannabis plant matter comes in contact with the hydrocarbons; cannabinoids, terpenes, and other compounds dissolve into the solvent. The hydrocarbon solvent and cannabinoid mixture is purged using vacuum ovens to remove the solvents. The purging process leaves only cannabinoids and other desired compounds in a refi ned concentrate. Hydro- carbon concentrates are often called butane hash oil Table II-1. Butane Extraction Weight Yields and THCa Potency Product Type Primary Input Input Potency (% THCa) Weight Yield (%) Output Potency (% THCa) MIP 1 BHO Wax/Shatter Trim 12-20 12-22 60-80 MIP 2 BHO Wax/Shatter Trim 15-20 10-25 70-95 MIP 3 BHO Wax/Shatter Trim 10-20 10-20 65-90 MIP 4 BHO (edibles) Trim 10-17 15-20 65-80 Source: MIP interviews April - June 2015. (BHO), shatter, or wax. All of these products refer to slightly different refi ning techniques that occur after the BHO is extracted from the plant matter. BHO and other variants contain a high concentration of THCa, often between 60 percent and 95 percent, depending on the amount of refi nement and quality of inputs. If BHO is used to make infused edible products, it must be decarboxylated. Decarboxylation converts the THCa in cannabis plants into psychoactive THC. Decarboxylation requires heating the BHO to 240°F–250°F until bubbling dissipates to achieve desired results. BHO sold for smoking or vaporizing does not require decarboxylation. Table II-1 shows information on weight yields and THCa potency for hydrocarbon extractions obtained during the industry outreach process. Weight yield is the ratio of output weight to input weight. THCa potency is obtained from metrc™ as part of the mandatory testing for potency and safety. Table II-1 presents THCa for all establishments regardless if the end product is a concentrate or edible. Equivalency Report 15 SECTION ISECTION IISECTION IIISECTION IVSECTION VThe refi ning process removes plant waxes, chlorophyll, or other undesirable elements. Similar to BHO, CO2 oil contains THCa concentrations between 60 percent and 85 percent, depending on the amount of refi nement and quality of inputs. CO2 extractions must be decarboxylated to make edible products. An increasing number of edible products are made with decarboxylated CO2 oil as the active ingre- dient. The decarboxylation process with CO2 oil is similar to BHO. Table II-2 shows weight yields and THCa potency for CO2 extractions obtained during the industry outreach process. Table II-2 presents THCa for all establishments regardless if the end product is a concentrate or edible. BUTTER AND COOKING OILS Perhaps the most widely known method for extracting cannabis for edible preparations involves the use of butter, coconut oil, and other cooking oils. Cannabinoids are fat soluble, and MIPs add cannabis to butter and other oils and the mixture is heated to 240°F–250°F. CARBON DIOXIDE EXTRACTION PROCESS Carbon dioxide (CO2) fl uid extraction techniques have been used for various industrial applications in the food and cosmetic industries. CO2 at very high (supercritical) or low (subcritical) pressures is used to extract canna- binoids from plant material. Different combinations of temperature and pressure are used in the extraction. CO2 is a popular solvent due to its lack of toxicity and its perception as a less dangerous form of cannabis concentrate. CO2 oils are a popular ingredient in vapor- izing concentrates for use with a stationary vaporizer or a portable vaporizer pen. CO2 fractionations2 at different pressures in the production process can yield different product consistencies and compositions. Plant waxes remain in varying amounts in the raw extraction, which is often refi ned further using various techniques involving an ethanol wash or refrig- eration techniques called winterization. 2 Fractionation is a separation process in which a certain quantity of a mixture (gas, solid, liquid, suspension or isotope) into a number of smaller quantities (fractions) in which the composition varies accord- ing to a pressure or temperature gradient. Product Type Primary Input Input Potency (% THCa) Weight Yield (%) Output Potency (% THCa) MIP 1 CO2 Oil Trim 12-17 10-15 80-85 MIP 2 CO2 Oil Trim 15-17 8-12 70-80 MIP 3 CO2 Oil (edibles) Trim 10-15 8-10 60-65 Table II-2. CO2 Extraction Weight Yields and THCa Potency Source: MIP interviews April - June 2015. 16 Equivalency ReportSECTION ISECTION IISECTION IIISECTION IVSECTION VProduct Type Primary Input Input Potency (% THCa) Weight Yield (%) Output Potency (% THC) MIP 1 Butter edibles Trim 10-15 3-4 1.9-2.5 MIP 2 Butter edibles Trim 15-22 2.75-3.25 2.0-2.8 Table II-3. Butter and Oil Extraction Weight Yields and THCa Potency Source: MIP interviews April - June 2015. While these methods are employed in Colorado for some commercial production, no MIPs in the interview group reported use of these methods on a commercial scale. These extraction methods are in use for small production batches and represent less than 7 percent of the market.3 The interviewees often referred to these products as a “cottage” or “artisanal” market. In the following section, metrc™ data is used to provide production equivalency calculations for alcohol and water based extraction methods in addition to the methods encountered in the interviews (hydrocarbon, CO2, and butter/oil). 3 Based upon author calculations from metrc™ data. Some MIPS vary this process by decarboxylating the plant material before adding it to the butter. Then plant material is strained and the butter is brought back to room temperature. MIPs are required to test each batch of cannabis butter or oil for potency. After a batch of butter is made and tested for potency, the MIP may add additional butter or oil if necessary to adjust the potency in accordance to its recipe. Then the cannabis butter or oil is measured in the recipe to determine the appropriate potency for each batch of baked edible products. The butter MIP oper- ators indicated that they have formed relationships with wholesale suppliers for trim, and they generally know the potency range of their raw cannabis butter, but natural variation exists in each package of plant material used to produce butter-based edibles. Table II-3 shows weight yields and THC potency for butter and oil extractions obtained during the industry outreach process. OTHER SOLVENTS Marijuana concentrates and infused products can also be manufactured using a host of other solvents, including isopropyl alcohol, ethanol, vegetable glycerin, water, and dry/solventless (kief). Equivalency Report 17 SECTION ISECTION IISECTION IIISECTION IVSECTION VThe study team built a genealogy of packages that traces them through the production process and correlates input packages of trim and fl ower to output packages of mari- juana concentrates and infused products at MIP facilities. Once an input and output package is linked, the study team mines the state inventory data to obtain identifying information about the production process and package contents. Equivalency calculations are provided for extraction processes that use butter and cooking oils, butane/hydrocarbons, CO2, water, and alcohol/ethanol as primary solvent. The calculations provide information on the yield on weight and input/output THC amounts for each production process. For example, in butane hash oil (BHO) manufacturing, if a production batch starts with 1,000 grams of trim and yields 180 grams of BHO, then we calculate a weight yield of 18 percent. The study team then queries the testing database to obtain THCa and THC fi gures for trim, fl ower, concentrates, and edibles to obtain potency infor- mation for production inputs and outputs. The process diagram in Figure III-1 shows the data collection process in metrc™ for weight yield and potency. In this section, metrc™ data is used to identify statewide average conversions of marijuana plant inputs into mari- juana product outputs. Together with the MIP production structure defi ned above, these two sections combine to produce conversion rates between plant-based inputs and infused or concentrated outputs. The study team developed two types of physical equiva- lency calculations: a simple THC conversion and a more nuanced physical conversion. The physical conversion traces the marijuana through the concentrate and edible production process and matches inputs (marijuana plant material) with outputs (concentrates and infused products). The THC conversion presents a more basic equivalency that quantifi es equal amounts of THC in marijuana concentrates, edibles, and plant material. The equivalencies are organized by the major solvents used in production. Inventory tracking data is used to trace the path between cultivation centers, marijuana infused products (MIP) manufacturers, and fi nal retail centers. Disparate data sources needed to be translated and combined in order to complete this task. For example, marijuana packaging data provides information about product contents and source, facility information is used to categorize package owners and transfers. Transfer manifests provide an accounting of shipments of intermediate and fi nal products between facilities, and testing results are used to establish potency among product types. After plants are harvested and cured, marijuana fl ower and trim are registered as “packages.” The packages are transferred to retail stores for sale or to MIPs for further processing. Package records contain identifying infor- mation about package contents and the facilities on either end of a package transfer. Physical Equivalency Calculations 18 Equivalency ReportSECTION ISECTION IISECTION IIISECTION IVSECTION VFigure III-1. Physical Equivalency Calculation Process ●Output package ●Concentrate amount (g) ●Input amount use (g) ●Category name (concentrate) ●Extraction method ●Category name (bud, shake/trim) INPUT PACKAGE REPACKS OUTPUT PACKAGE FACILITY INFO PACKAGES TRANSFER & REPACKS YIELD ON WEIGHT By extraction method (solvent) THC/THCa POTENCY By extraction method (solvent) POTENCY TEST POTENCY TEST Equivalency Report 19 SECTION ISECTION IISECTION IIISECTION IVSECTION VThe fi gures in Table III-2 show between 9.7 and 17.1 percent concentrate weight yield rates on non-butter solvents with relatively narrow confi dence intervals. Using butane as an example, a 1,000-gram production batch of trim yields on average 171 grams of BHO with a mean potency of 71.7 percent THCa. These calculations have a sample size of over 11,500 for weight yield and over 5,600 for potency. The calculation process provides the weight yield and potency fi gures in Table III-2. Table III-2 provides the mean weight yield, 95 percent confi dence interval range and sample size for each solvent type included in the analysis. Table III-2 also provides information on potency testing for each solvent type. Marijuana fl ower and shake/ trim potency is also included.4 4 Testing results display combined THCa and THC for each solvent type. Butter and oil potency is listed as amounts of THC due to decar- boxylation. All other solvent types contain almost exclusively THCa. Solvent Yield Calculations Potency Calculations Bud % Shake/ Trim % Mean Weight Yield 95% Lower Bound Weight Yield 95% Upper Bound Weight Yield (n) Mean THC/ THCa % 95% Lower Bound % THC/ THCa 95% Upper Bound % THC/ THCa (n) Butane 17.11% 16.76% 17.46% 11,514 71.67% 71.20% 72.14% 5,606 11.43% 88.57% CO2 15.18% 14.80% 15.55% 7,257 61.39% 60.27% 62.51% 1,950 3.51% 96.49% Butter 504.50% 484.69% 524.32% 599 2.57% 2.04% 3.09% 216 9.72% 90.28% Water 9.72% 9.01% 10.43% 1,270 58.30% 56.34% 60.26% 266 9.91% 90.09% Alcohol/ Ethanol 17.06% 14.37% 19.76% 241 67.17% 64.08% 70.25% 201 16.46% 83.54% Flower 17.47% 17.41% 17.53% 26,023 Shake/Trim 15.53% 15.26% 15.80% 1,591 Table III-2. Marijuana Concentrate Yield and Potency Source: Author calculations based on metrc™ data. 20 Equivalency ReportSECTION ISECTION IISECTION IIISECTION IVSECTION VThe butter “yield” rate differs from other solvents because it is a different production process. The butter yield results can be interpreted as the weight of cannabis butter produced per weight of plant input. For example, 100 grams of cannabis in a production batch would yield on average 502 grams of cannabis butter at a mean THC of 2.57 percent or 25 mg of THC per gram of butter.)5 The yield and potency fi gures described above are inputs to the physical equivalency calculations. For concentrates sold or transferred directly to retail stores, the fi gures in Table III-2 provide the information for an equivalency. For marijuana edibles, these fi gures are supplemented by several intermediate calculations shown in Table III-3. All fi gures from Table III-2 are converted from percentages into milligrams per gram, as shown in Table III-3. This conversion is necessary because edibles in the adult use 5 The butter yield rate was the most difficult to interpret because of the many weight units that can be used to describe the prepared can- nabis butters. There is also the possibility that some manufacturers re- port the output units after additional non-psychoactive butter is added to the cannabis butter. The 5-to-1 yield ratio is somewhat higher than what was discussed in our interviews. The authors have elected to use the metrc™ data due to the amount of data (1,623 records) that sup- port the figures in Table III-2. Table III-3. Edibles Intermediate Calculations Source: Author calculations based on metrc™ data. Solvent mg THC/g Solvent g Solvent per 10 mg Edible g Trim per 10 mg Edible Butter 25.70 0.39 0.08 Butane 716.70 0.014 0.08 CO2 613.90 0.016 0.09 retail market are sold in two standard sizes (10mg and 100mg)6 based on the amount of THC contained in the edible product. The calculations in Table III-3 show the average potency of each solvent used in edibles production, the amount of solvent necessary to produce an edible product with 10mg of THC, and the amount of marijuana plant material necessary to produce 10mg edible product. On average, between .08 and .09 grams (or 80–90 mg) of plant material is required to make an edible product containing 10mg of THC. Table III-4 shows equivalency calculations based on the physical approach described in Table III-3. Equivalencies are organized by solvent type and shown for edibles and concentrates. The process estimates the amount of plant material used in each 10 mg and 100 mg edible package and provides a calculation of the amount of edible packages that can be produced from an ounce of dried marijuana fl ower. For concentrates available directly for sale, the study team provides estimates of the amount of plant material used to make one gram of concentrate at average potency for each solvent type. Similar conversions for an ounce and a quarter-ounce of marijuana fl ower are provided. Table III-4 provides estimates of the amount of trim used in each production process and then converts trim amounts to fl ower equivalents using a THC-based conversion factor derived from the testing data presented in Table III-2.7 6 Two dosages are outlined in state statute. One is 10mg., which represents a standard dose of THC. The second is 100 mg., which contains 10 servings and represents the maximum amount of THC allowed in an edible retail marijuana infused product. 7 Trim has on average 15.53 percent THC and flower has on aver- age 17.47 percent THC; therefore, a conversion ratio is calculated at 1.125. Equivalency Report 21 SECTION ISECTION IISECTION IIISECTION IVSECTION VALTERNATE METHODOLOGY A second, simpler methodology is presented in Table III-5 that employs THC as the common unit for conversion between the various forms of marijuana products. This methodology calculates an equivalent amount of THC in various forms of marijuana products based on the testing information shown in Table III-2. The equivalency factors in Table III-5 can be interpreted as showing units with equivalent amounts of THC. For instance, given the uniform dosage amounts of edibles The physical equivalencies in Table III-4 show that about between 347 and 413 edibles of 10 mg strength can be produced from an ounce of marijuana, depending on the solvent type and production method. For concentrates, between 3.10 and 5.50 grams of concentrate are equiv- alent to an ounce of fl ower marijuana. The conversion factors described above can be useful for state-level production management. The conversions allow units of infused edibles and concentrates to be expressed in equivalent fl ower weight, and then added to fl ower sales, in order to determine retail market demand and supply. Product Type Solvent Purchase Amount Trim Used in Production Flower Equivalency Ratio Ounce Equivalent Quarter-Oz Equivalent Edible Butter 10 mg 0.08 g 0.07 g 413.49 each 103.37 each Edible Butter 100 mg 0.77 g 0.69 g 41.35 each 10.34 each Edible Butane 10 mg 0.08 g 0.07 g 391.07 each 97.77 each Edible Butane 100 mg 0.82 g 0.72 g 39.11 each 9.78 each Edible CO2 10 mg 0.09 g 0.08 g 346.96 each 86.74 each Edible CO2 100 mg 0.92 g 0.82 g 34.70 each 8.67 each Concentrate Butane 1 g 5.84 g 5.20 g 5.46 g 1.36 g Concentrate CO2 1 g 6.59 g 5.86 g 4.84 g 1.21 g Concentrate Ethanol 1 g 5.86 g 5.21 g 5.44 g 1.36 g Concentrate Water 1 g 10.29 g 9.15 g 3.10 g 0.77 g Table III-4. Physical Equivalency Calculations Source: Author calculations based on metrc™ data. 22 Equivalency ReportSECTION ISECTION IISECTION IIISECTION IVSECTION VTable III-5. Simple THC Equivalency Calculations Source: Author calculations based on metrc™ data. Product Type Solvent Purchase Amount THC Amount THCa Amount Flower Equivalency Ratio Ounce Equivalent Quarter-Oz Equivalents Edible Butter 10 mg 10 mg 11.40 mg 0.07 g 434.35 each 108.59 each Edible Butter 100 mg 100 mg 114.03 mg 0.65 g 43.43 each 10.86 each Edible Butane 10 mg 10 mg 11.40 mg 0.07 g 434.35 each 108.59 each Edible Butane 100 mg 100 mg 114.03 mg 0.65 g 43.43 each 10.86 each Edible CO2 10 mg 10 mg 11.40 mg 0.07 g 434.35 each 108.59 each Edible CO2 100 mg 100 mg 114.03 mg 0.65 g 43.43 each 10.86 each Concentrate Butane 1 g 0.72 g 0.72 g 4.10 g 6.91 g 1.73 g Concentrate CO2 1 g 0.61 g 0.61 g 3.51 g 8.07 g 2.02 g Concentrate Ethanol 1 g 0.67 g 0.67 g 3.84 g 7.37 g 1.84 g Concentrate Water 1 g 0.58 g 0.58 g 3.34 g 8.50 g 2.12 g For retail concentrates equivalency calculations, the THC/ THCa conversion is not necessary because concentrates are not decarboxylated for direct retail sale. The THC in one gram of concentrate is equivalent to between 3.05g and 3.75g of marijuana fl ower at average potency. Ounce and quarter-ounce equivalents are also provided in Table III-5. in Colorado, all 10mg strength edibles have an amount of THC equivalent to 60 mg (0.06 g) of fl ower marijuana at the average potency. A conversion rate of 1.14 is applied to convert THC in infused products back to THCa in fl ower due to weight loss in the decarboxylation process involved in manufacturing edibles.8 8 Decarboxylation is the process of heating THCa, which naturally occurs in cannabis plants, to activate THC that can be absorbed in the body through ingestion. In the process, the THCa loses a carbon dioxide molecule and about 12.3 percent of its weight. Conversion calculation from THC back to THCa uses 1/(1-.123) or 1.14. This weight reduction is calculated using the molecular weight of THCa and THC obtained from Steep Hill Labs http://steephilllab.com/re- sources/cannabinoid-and-terpenoid-reference-guide/. Equivalency Report 23 SECTION ISECTION IISECTION IIISECTION IVSECTION VTHC derivatives) can be delivered to the recipient in a number of ways. Each method translates into a different net amount of THC entering the bloodstream and the brain. • Flower smoking: Over the past 30 years, smoking has been the most common method to consume mari- juana. Based upon 2014-15 data, the THC content in Colorado retail fl ower lies between 8-22 percent, with a mean estimate of roughly 17 percent. Therefore, one gram of marijuana fl ower contains 170 milligrams of THC, on average. However, a large portion of that THC is destroyed during the smoking process. In this report, we itemize the uptake rates and the potential loss of THC through smoking, during the process of inhalation, exhaling, and blood-clearance. The process is further complicated by the transfer process of THC from the blood plasma, into the brain itself. • THC ingestion: Alternatively, THC can be infused into edible products such as baked goods or candies, and then eaten. By state law, each serving of edibles is limited to no more than 10 milligrams of THC content. THC, when ingested, will be absorbed at different levels, depending upon other foods in the stomach, and upon the chemical nature of the pre-existing foods. As with smoked products, a majority of the THC is not absorbed by digestion. Various studies, which will be discussed below, suggest that between 6-20 percent of the THC content in an edible product is metabolized and absorbed into the bloodstream. However, ingestion and processing by the liver has been found to create an important THC byproduct that subsequently boosts the psychoactive effect of THC. This research will be discussed later in this section. An important compliment to the physical THC relation- ships identifi ed in this study is the pharmacological perspective. If the purpose of the equivalency legislation is to limit transactions or possession to a reasonable “dose” of concentrates and marijuana products for residents and non-residents, then the medical effects described here will be useful to construct a set of equivalencies between marijuana products. There are several methods to consume marijuana such as intravenous, oral mucosal, ingested, transdermal, and inhaled. The two most popular methods for consumption are ingestion and inhalation. We focus upon these two methods in this study. The remaining methods are either reviewed briefl y or are provided as references for the interested reader. The reader should understand that this section does not represent a clinical study. Instead, this section uses fi ndings from other studies to inform marijuana stake- holders about the dosing process, and it provides a new mathematical construct that can compare ingested and smoked marijuana products in a consistent manner. Therefore, this report should be considered to be a policy- driven study that leverages medical literature to provide scientifi c evidence during the construction of dose equiv- alencies between various marijuana products. This section focuses upon the psychoactive components of marijuana, primarily THC and related chemicals, and does not focus upon the medicinal effects of marijuana because the fi ndings and resulting regulations will be applied only to Colorado’s retail marijuana market, under House Bill 14-1361. ENUMERATION OF THC UPTAKE METHODS FOR MARIJUANA The psychoactive component of marijuana, THC (and Pharmacological Equivalencies 24 Equivalency ReportSECTION ISECTION IISECTION IIISECTION IVSECTION Vrelationship between THCa and THC is explained at the beginning of this report. THC itself is the primary psychoactive component in marijuana, but there are also related chemicals that have been found to have an amplifi cation effect upon the base blood levels of THC. In particular, when THC is ingested, it is then oxidized and converted by the liver into the active metabolite named 11-hydroxy-THC (11-OH-THC) [see 23, 25], and 11-nor-9-Carboxy-THC (THC-COOH), a secondary, non-psychoactive metabolite.10 Recent studies have found that 11-OH-THC penetrates the brain barrier more quickly than regular THC, causing a markedly-higher psychoactive effect. We cite a number of studies below, to estimate the relative potency of 11-OH-THC versus regular THC in blood levels, in order to more accurately characterize the psychoactive effects between ingestion and inhalation of THC. IDENTIFICATION OF THC UPTAKE AND BENCHMARKING This section describes THC uptake, delivery methods, and related dosing. The dosing relationships between uptake methods (smoking and ingesting) can be quite different from the physical weight relationships that were identifi ed in the fi rst half of this report. One relationship is pharmacokinetic, while the other is purely physical. Comparing Peak Effect vs. Aggregate Effect It is also important to recognize the differences between “peak effects” or “aggregate effects.” The former measure identifi es the most intense moment experienced by a subject during a dosage event with marijuana. This can 10 THC-COOH is a non-psychoactive metabolite formed in the liver when THC is ingested or smoked. Due to its inactive nature, it is not factored into equivalency calculations See source 9 in references section. • Concentrate smoking or “dabbing:” This method also uses smoking as the uptake method, but the material contains very high concentrations of THCa. The typical THC content in concentrated forms of mari- juana varies between 60-80 percent, although rates as high as 95 percent have sometimes been observed. By heating and smoking these concentrates, the uptake ratios are similar to smoking marijuana fl ower, but the ratios of THC to fl ower-based cannabinoids may be different, creating a different type of psychoactive effect. THC, THCA, 11-OH-THC AND THC-COOH9 The underlying chemistry for marijuana, and its psycho- active elements is complex and beyond the policy scope of this report. A large number of clinical studies and medical fi ndings are cited later in this section. This subsection provides a brief and concise overview of the main psychoactive component in marijuana, THC. In addition to THC, there are cannabinoids, typically labeled using a root form, CBD, and then enumerated, such as “CBD-A” or “CBD-B.” Many cannabinoids contain psycho- active elements as well, but the type of effect caused by those cannabinoids is not typically as strong as THC. Because this study is designed for the retail market, and not the medical market, only the psychoactive THC and THC related chemicals are considered. The reader is reminded that marijuana fl ower (or buds) does not contain THC itself, but instead contains THCa (Tetrahydrocannabinolic Acid), a precursor to THC. The 9 Please note that this sub-section is an overview of report findings. In order to be concise, only a few of the specific technical references and citations are provided here. Instead, most citations are provided, combined, and enumerated during the longer, technical exposition at the bottom of this section. Equivalency Report 25 SECTION ISECTION IISECTION IIISECTION IVSECTION Vbe characterized as the “peak intensity” of the high. The latter measure calculates the integral, or area under the curve where the curve relates to blood-levels of THC and 11-OH-THC over time. Typically, smoking produces a higher peak effect, as THC enters the blood stream through lung tissue. But THC levels are also quickly reduced when smoked, as the body works to clean contaminants from the bloodstream. Conversely, edible products absorb much more slowly, so that the effect is delayed compared to smoking. However, the digestion and oxidization process last much longer. For example, Figure IV-1 shows the THC and related chemicals in the blood stream over time. As shown, THC concentrations peaked 90 minutes after ingestion, and 11-OH-THC peaked slightly later, at approximately 110 minutes. Levels of these psychoactives remained elevated for approximately 300 minutes, or fi ve hours, and non-active THC-COOH remained elevated for 1,400 minutes (almost 24 hours). In contrast, smoking concentrations were much higher, and shorter. Figure IV-2, taken from the “California NORML Guide Interpreting Drug Test Results,”11 combines results from smoking and ingested THC to reveal the relative magnitude of blood plasma levels. 11 Sourced from: http://www.canorml.org/healthfacts/drugtestguide/ drugtestdetection.html#fn03. Last visited on June 13, 2015. Figure IV-1. An Example of Blood Plasma Concentration Rates of THC Derivatives Over Time, After Oral Ingestion of Marijuana Products. From Nadulski et. Al. (2005). 26 Equivalency ReportSECTION ISECTION IISECTION IIISECTION IVSECTION VIndeed, for the psychoactive effects to occur, the THC must penetrate the blood-brain barrier and connect directly to the brain. This means that even though blood- plasma THC levels are 10 times higher when smoking versus ingesting THC, the psychoactive effect may not be 10 times as intense, because THC is not necessarily reaching the brain at the same rate as it fl ows in the blood plasma. As discussed earlier, 11-OH-THC has an extenuating effect. According to Perez-Reyes, et. al. [26], it has been found to penetrate the brain membrane approximately four times faster than THC. This suggests 11-OH-THC will contribute more rapidly to the psychoactive effects than THC. Also, by elongating the amount of time that THC is elevated in the blood plasma when THC is ingested and processed by the liver, there is more time for the THC Figure IV-2 shows that THC plasma concentrations are more than 10 times higher for smoked cannabis compared to ingested cannabis. The more recent fi ndings from Nadulski, et. Al. (2005) suggest that while THC and 11-OH-THC levels peak much earlier than suggested by Law, et al. (1984), the relative magnitudes are similar. Peak levels were 5-6 ng/mL in the Nadulski study, and approximately 8 ng/mL in the Law study. These fi ndings suggest that either smoked marijuana experiences are signifi cantly more intense, or—as scien- tists suggest—that 11-OH-THC produces an extenuated effect, compared to base THC. It also suggests that the relationship between blood-plasma THC levels do not necessarily correspond to psychoactive effects in a strictly-linear fashion. Figure IV-2. Comparison of Inhaled Versus Ingested THC Elements References: (A-B) Smoked dose based on data from M. Huestis , J. Henningfield and E. Cone,M. Huestis , J. Henningfield and E. Cone. [08] M. Huestis , J. Henning- field and E. Cone,“Blood Cannabinoids. I. Absorption of THC and Formation of 11-OH-THC and THCCOOH During and After Smoking Marijuana”, Journal of Analytic Toxicology, Vol. 16: 276-282 (1992). (C) Oral dose based on data from B. Law et al. ([03] B. Law et al, “Forensic aspects of the metabolism and excre- tion of cannabinoids following oral ingestion of cannabis resin,” J. Pharm. Pharmacol. 36: 289-94 (1984).) Equivalency Report 27 SECTION ISECTION IISECTION IIISECTION IVSECTION Vblood is slower, as discussed earlier. Next, the so-called “High perfusion” tissues begin absorbing THC, followed by “Low perfusion” tissues, and fi nally, fat tissues. ROLE OF THE BLOOD-BRAIN- BARRIER (BBB) A barrier, or sheath, separates the brain from the human body blood stream. There are several descriptions of the BBB.12 In general, the BBB is a highly selective permeable 12 See, for example: Blood-Brain Barrier: Drug Delivery and Brain Pathology, edited by David Kobiler, Shlomo Lustig, Shlomo Shapira, 2012. Springer Science & Business Media, Dec 6, 2012. A clear description for the lay person can also be found on Wikipedia: https:// en.wikipedia.org/wiki/Blood%E2%80%93brain_barrier. Accessed on June 16, 2015. to penetrate the brain membrane and therefore a higher ratio of absorption of THC and other psychoactives into the brain fl uid. Together, this suggests that lower concentrations of THC in blood plasma do not necessarily imply that consumers are experiencing a lower intensity of psychoactivity. Instead, the level of THC and 11-OH-THC, combined with the time these metabolites have to penetrate the blood brain barrier, will determine the comparative psycho- active effects between inhaling and ingesting marijuana products. The different rates of tissue absorption are shown more clearly in Figure IV-3. Here, blood plasma levels are the immediate recipients of THC, yielding high rates of THC concentration. However, rate of brain absorption from the Figure IV-3. Distribution of THC in the Body. Blood and Brain Absorption Rates Differ Signifi cantly. References: Nahas, G. G. (1975) Marijuana: toxicity and tolerance. In Medical Aspects of Drug Abuse (ed. R. W. Richter), pp. 16-36. Balti- more, MD: Harper & Row. 28 Equivalency ReportSECTION ISECTION IISECTION IIISECTION IVSECTION V“effective” THC within the brain itself. The share of THC that actually passes through the BBB and into the brain during the short period when blood-plasma levels are high is estimated to be approximately 35 percent. Just over one-third of the THC in the blood plasma is captured by the brain before it is cleaned out by the body’s pulmonary system. CONSTRUCTING DOSING EQUIVALENCIES FOR MARIJUANA PRODUCTS This is the fi rst time that data from an offi cial marijuana market is combined with medical research to develop scientifi cally-based relationships between marijuana products. The estimates refl ect the best-available data and knowledge as of the report publication. Over time, we hope that further research can be used to improve upon the methods here, and to refi ne the estimates as knowledge of the subject matter continues to improve. In order to synthesize the various pharmacokinetics of marijuana uptake into a simple, actionable metric, we suggest using a THC conversion factor. The conversion factor for purposes of dosing will compare the amount of weight-based THC contained in smokable products, such as marijuana fl ower and concentrates, with the amount of weight-based THC contained in ingested THC products such as edibles. For example, if the THC conversion factor for dosing equals 1:5, this means that one milligram of THC in edible form (ingested) is roughly equal, from a dosing perspective, to 5 milligrams of THC in a smokable form. This section will provide a basic conversion factor model that synthesizes the scientifi c fi ndings discussed earlier, in order to construct the THC conversion model. barrier that separates the circulating (pulmonary) blood from the brain extracellular fl uid that circulates in the central nervous system. The blood–brain barrier is formed by brain endothelial cells, which are connected by tight junctions with a high electrical resistivity. The BBB allows water and some gases to pass through, as well as lipid- soluble molecules. It also allows the selective transport of molecules, such as glucose and amino acids that are crucial to neural functioning. The BBB will often prevent the entry of lipophilic, potential neurotoxins by way of the so-called active transport mechanism. A small number of regions in the brain do not have a blood–brain barrier. The BBB is an important factor that limits the fl ow of THC between the body’s blood plasma and the brain, where it creates the psychoactive effects. Where THC is allowed to penetrate the BBB, the rate of penetration is slow. In contrast, scientists have found that the rate of penetration for 11-OH-THC is much faster. The selective permeability of the BBB causes a compe- tition. On the one hand is the BBB/THC passage rate allowed by the BBB, and on the other hand is the meta- bolic clearance rate for toxins in blood-plasma. The BBB slowly allows THC to pass through the membrane, causing the psychoactive effects. But at the same time, the body’s metabolism will purify the blood stream, rapidly removing the THC from blood-plasma. This competition causes a decrease in THC effectiveness from inhalation, compared to the slower, steadier THC supply from ingestion. As shown in Figure IV-2, the concentration of THC in the blood stream is much higher when inhaled than when ingested. But due to blood plasma clearance, the ratio quickly falls to relatively low levels (e.g., in 30 minutes). The limitations incurred by the BBB suggest that much of the THC in the blood-plasma is therefore lost, because the BBB slows conversion of blood-plasma THC into Equivalency Report 29 SECTION ISECTION IISECTION IIISECTION IVSECTION VFor edibles, a similar approach can be used. Edibles come in various shapes and sizes, but are required to contain 10 milligrams or less of THC per serving. This allows for a direct uptake comparison of THC content into effective THC uptake from ingestion. In edibles, the metabolism of THC into 11-OH-THC is an important consideration. It is also important to acknowledge that the slow, steady release of THC and 11-OH-THC into the blood stream allows most, if not all, of the THC derivatives to pass through the BBB. Thus, the equation below implicitly assumes a blood-brain THC retention share of 100 percent for edible marijuana. The total uptake equivalent, UE, is a function of the THC absorption rate in the stomach, θ, and amount of THC in the product, by weight, ω. Next, the absorbed portion of THC is metabolized into two components, THC and 11-OH-THC, where THC enters the blood stream linearly, but 11-OH-THC, which can pass the BBB more rapidly, receives a conversion factor, y. As with inhaled THC, the share ratio of THC uptake can be constructed simply by dividing by the weight of the THC content in the product: Finally, a simple equivalency ratio can be derived from the share-value uptake ratios. This equivalency ratio, R, is used to denote the relative psychoactive effect that is embodied in edible versus smokable marijuana products. The THC conversion factor is based upon a combination of fi ndings. Among them are: the typical THC loss rate during the smoking process; the typical loss rate of THC for ingested products; the absorption rate of THC vs. 11-OH-THC in the brain; and the estimated comparative psychoactive intensity of THC versus 11-OH-THC. For clarity, the uptake relationship can be parameterized and displayed mathematically. The following equations explain the relationship between each pharmacoki- netic fi nding and the overall impact of that fi nding upon the equivalency factor between inhaled and ingested products. First, the effective uptake of THC or THC derivatives from inhalation can be simplifi ed using the following formula: The total uptake U, is the product of the fl ower weight, w, times the THC/THCa content. This yields the THC weight available for inhaling. This amount is then scaled by the share of THC captured during the inhalation, αΙΝ, and also by the share of THC retained in the lungs after exhalation, αΕΧ. These inputs determine the level of THC that will ultimately be absorbed into the subject’s blood plasma. Finally, the share of THC that passes through the BBB from the blood-plasma is denoted by β. The product of these parameters reveals the effective THC uptake from inhalation of activated THC. The uptake ratio for the THC content alone can be obtained by simply dividing by the marijuana fl ower weight and THC concentration (cw). After doing this, we denote uI to be the uptake conversion factor. It is: 30 Equivalency ReportSECTION ISECTION IISECTION IIISECTION IVSECTION VFor the purposes of this study, R is the key ratio that can be used to compare edible products with smokable products, from a policy standpoint. IDENTIFICATION OF PARAMETER VALUES Each of the parameters in these equations has been studied to some degree. Some studies are directly relevant to specifi c parameter values, while others are only tangentially relevant, since they were each written for different purposes than this equivalency study. Relevant studies are cited numerically and are included in the references section. For these reasons, this study utilizes a range of values that is based on existing research. This range of values is used to determine a point estimate for the equivalency ratio (R), which is the equivalent dose impact of 1 milligram of THC in edible form, in milligrams of THC in smokable form. Studies related to αΙΝ and αΕΧ The physical uptake of THC through smoking has been Symbol Table Symbol Description Relevant Literature U, u Uptake equivalent amount of THC, in weight terms, and unit-free terms, for edibles (E), and for inhalation (I). Calculated as a function of parameterized values from this report. C THC concentration rate in marijuana fl ower.Based upon testing observations from Colorado retailers and dispensaries. W Weight of marijuana fl ower. αΙΝ, αΕΧ Share of captured THC during marijuana smoke inhalation, and after exhalation, respectively. Scientifi c laboratory studies of marijuana smoking. See See [20], [30], [31]. β Brain fl uid retention rate from blood plasma. θ Absorption rate of THC when ingested in the form of an edible product. [25], [24], [21], [19], and [13] are studies on oral consumption of marijuana, and its effects upon the human body. ω Weight of THC in edible form, in milligrams. y Effective impact of 11-OH-THC that is metabolized by the liver. Pharmacokinetic studies by [5], [1], [2], [21], and [26]. R Equivalency ratio – the equivalent dose impact of 1 milligram of THC in edible form, in milligrams of THC in smokable form. Calculated as a function of parameterized values from this report. Equivalency Report 31 SECTION ISECTION IISECTION IIISECTION IVSECTION Vbioavailability of a smoked dose of THC is between the range of 0.10 and 0.25.“ [10] “Bioavailability following the smoking route was reported as 2−56%, due in part to intra- and inter-subject variability in smoking dynamics, which contributes to uncertainty in dose delivery. The number, duration, and spacing of puffs, hold time, and inhalation volume, or smoking topography, greatly infl uences the degree of drug exposure.” [8] “The apparent absorption fraction calculated in the current study was in a similar range of previous fi ndings on THC, showing an oral bioavailability of 6 %, and inhalation of 18 % (frequent smokers) or 23 % (heavy smokers).” [5] “A systemic bioavailability of 23 ± 16% and 27 ± 10% for heavy users versus 10 ± 7% and 14 ± 1% for occa- sional users of the drug was reported.” [7] “Pulmonary bioavailability varies from 10 to 35 percent of an inhaled dose and is determined by the depth of inhalation along with the duration of puffi ng and breath-holding.” Studies related to β The role of the blood brain barrier (BBB) in THC and 11-OH-THC uptake is an important factor in determining equivalencies, as this function limits the fl ow of THC between the body’s blood plasma and the brain, where it creates the psychoactive effects. As previously indicated, where THC is allowed to penetrate the BBB, the rate of penetration is slow. Below is a section from M. Huestis (2007)[10], that highlights the diffi culty of THC passing through the BBB: “Adams and Martin studied the THC dose required to induce pharmacological effects in humans. They deter- mined that 2−22 mg of THC must be present in a cannabis discussed as part of various marijuana smoking experi- ments. Numerous studies examine the absorption of THC through smoking cannabis. The results of these studies vary, with one study putting the range of absorption from 2 percent - 56 percent. A study by Perez-Reyes found that absorption varied widely due to various factors, including marijuana potency, the amount of unchanged THC available in the smoke inhaled, amount of THC lost in side-stream smoke, method of smoking (i.e., cigarette or pipe) and the amount of THC passed through the upper respiratory tract. [12] A thorough examination of these studies leads to a more reasonable range of absorption through smoking of 10-25 percent. [5, 2, 10, 8, 7] This value range will be used in this study for calculations related to smoking equivalencies. Below are relevant excerpts from the medical literature, related to the uptake ratios of inhalation and exhalation for THC absorption: [12] “The factor of absorption from smoking varies in terms of THC uptake and the actual amount of THC that is absorbed through smoking of marijuana. The factors that affect uptake ratios of smoking include, (1) the potency of the marijuana smoked; (2) the amount of unchanged THC present in the smoke inhaled (i.e., the amount of THC not destroyed by pyrolysis); (3) the amount of THC lost in side-stream smoke; (4) the method of smoking (cigarette vs. pipe smoking); and (5) the amount of THC trapped in the mucosa of the upper respiratory tract. These iden- tifi ed factors have made exact uptake ratios of THC diffi cult to determine, and therefore studies to this point have produced a range of THC absorption.” [2] “Past studies indicate that smoking cannabis turns approximately 50% of the THC content into smoke, with the remainder lost by heat or from smoke that is not inhaled. Up to 50% of inhaled smoke is exhaled again, and some of the remaining smoke undergoes localized metabolism in the lung. The end result is that the estimated 32 Equivalency ReportSECTION ISECTION IISECTION IIISECTION IVSECTION VTHC can be observed up to seven days after dosing.13 Based upon the slow BBB permeability, and the relatively rapid blood clearance rate, this study assumes that only a portion, equal to 35 percent, of THC blood plasma levels end up being absorbed by receptors in the brain when smoking. The comparative rate for ingestion will be much higher, as the liver metabolizes THC more slowly, leading to a long, sustained level of blood plasma THC and 11-OH-THC. Studies related to θ The process of THC absorption through ingestion is more straightforward. While there can be variation in this value, depending upon the stomach contents, rate of metab- olism and a number of other factors [2,13]. Grotenhermen and Schwilke et al. fi nd that the rate lies between 6-12 percent absorption, while Borgelt, Franson, Nussbaum, and Wang suggest that the rate is between 5-20 percent, with the rates typically on the lower range of absorption. Given this information, this study assumes 10 percent as a reasonable rate of THC absorption through ingestion. [2, 6, 13] These studies conclude that the absorption rate of THC through oral administration will be typically be less than that of smoking, with metabolism of THC into 11-OH-THC in the liver as a key factor in the low absorption of THC in this process. 13 Most of this literature is motivated to identify specific cutoff points to be considered legally “intoxicated” by THC and similar compounds. A non-psychoactive derivative of THC is 11-nor-9-carboxy-THC (THC- COOH), which is the most common trace substance used to detect marijuana use. New research focuses upon THC and 11-OH-THC since allowable levels are now needed, rather than presence alone. Colorado, for example, has a 5 µg/liter “permissible inference” law, as a cutoff value for legal intoxication of marijuana. cigarette to deliver 0.2−4.4 mg of THC, based on 10−25% bioavailability for smoked THC. Only 1% of this dose at peak concentration was found in the brain, indicating that only 2−44 μg of THC penetrates to the brain.” [Section 2.2: Distribution] The competition between blood plasma concentra- tions and brain tissue concentrations is described by researchers as hysteresis, an indication that the cognitive effects of THC do not occur immediately when THC blood-plasma levels are elevated, but instead, they occur after the THC has been absorbed by various body tissues (primarily, the brain). The dosing effects are said to occur after the blood level and tissue THC concentrations are equal. The following passage from Cone and Huestis (1993) describes this: “THC is rapidly absorbed and distributed to tissues; initial changes in blood concentrations are out of phase (hysteresis) with physiological and behavioral changes. Once blood/tissue equilibrium is established, a direct correlation of THC blood concentration and effect is observed.” [Abstract] Several studies that were motivated by THC driving impairment purposes have measured the rate of blood plasma clearance. An example is Hartman, et. al. (2015), this team measures the blood plasma clearance for THC after dosing THC using a vaporizing pen. The early clearance of THC was shown to be rapid, with concen- tration rates falling from a peak of 60 μg/liter 10 minutes after dosing, down to 15 μg/liter 30 minutes after dosing (and 20 minutes after the peak), and then to approxi- mately 8 μg liter 90 minutes after dosing. Small levels of Equivalency Report 33 SECTION ISECTION IISECTION IIISECTION IVSECTION Van average potency of 17 percent.14 This implies that just over 0.5 grams (588 milligrams) of typical marijuana fl ower in Colorado contains 100 milligrams of THC (or THCa). From the worked example, an equivalent 100 milligrams of THC from an edible product would yield the equivalent effect of 3,361 milligrams (or 3.36 grams) of marijuana in fl ower form. Due to each of the pharmacokinetic effects that are presented in this study, 100 milligrams of THC content in a smokable form, yields 7.88 milligrams of THC into the brain itself. In contrast, 100 milligrams of THC content in edible form yields a much higher ratio of 45.0 milligrams. 14 Based upon 28,023 laboratory test samples reported between October 2014 and May 2015. A WORKED EXAMPLE For concreteness, a worked example is provided in Table IV-4. This example compares the uptake ratios for THC derivatives for 100 milligrams of THC that is either inhaled or ingested. The result from Table IV-4 is that the equivalency ratio, R, equals 5.71, after fi ndings from the medical literature are used to calibrate each of the uptake ratio parameters. This means that one milligram of THC in edible form, is equivalent to 5.71 milligrams of THC that is available in smokable form. In the example above, which is based upon observa- tions taken from metrc™, marijuana fl ower, or bud, has Differential Uptake Equivalency: Inhaled vs. Ingested THC 100 mg Example Inhaled THC from Marjiuana Flower Ingested THC from Edible THC in Smokable Flower 100 Edible Package: (100 MG) 100 THC Content 17% Rate of Absorption 10% % of Content Inhaled 50% THC absorption (mg) 10 % of Inhaled Air Exhaled 45% 11-OH-THC Conversion 3.5 Gross THC Absorption (mg) 22.5 11-OH-THC / THC Equivalent: 35.00 Blood Cycle De-Rate Factor 35% Effective THC Infusion to Brain (mg) 7.88 Effective THC Infusion to Brain (mg) 45.00 Equivalencies Flower Weight (mg) 588 Flower Weight Equivalent (mg) 3,361 THC Equivalancy Ratio 1 THC Equivalency Ratio 5.71 Table IV-4. Example of Marijuana Equivalency Between Inhaled and Ingested Uptake Methods Source: Author’s calculations, combined with published medical research findings and statistical data from metrc™. 34 Equivalency ReportSECTION ISECTION IISECTION IIISECTION IVSECTION VThe equivalency ratio, R, can now be combined with THC content in various products, in order to construct more user-friendly conversion factors between product types. Table IV-5 lists common weights of marijuana fl ower that are purchased from retail and medical outlets in Colorado. Next to these weights are the number of units, based upon serving size, that are considered “equivalent” from a dosing perspective. For example, the purchase limit for an out-of-state patron at a retail marijuana store is one quarter of one ounce. This purchase limit would corre- spond to 21 units or servings of THC in edible form. If the edible is packaged in 100 milligram packages, then two 100 milligram packages could be purchased, plus one 10 milligram unit. That would fulfi ll the patron’s daily limit purchase amount of marijuana. For enforcement purposes, residents and non-residents alike are allowed to possess up to one ounce of mari- juana fl ower at a given time. This one ounce amount corresponds to 83 units or servings of edible products. It can be packaged in the form of eight 100 mg packages of servings, plus three 10 mg additional individually- wrapped servings. One gram of smokable marijuana corresponds to three 10 mg servings of edible products. Of course, any combination of these amounts is also possible. For example, an out of state patron can purchase 1/8 ounce of marijuana fl ower, and can also purchase 10.5 servings (105 mg) of THC in edible form. Similarly, a resident who is 21 years or older could legally possess ½ ounce of marijuana fl ower, plus another 41.5 servings of THC in edible form. For concentrates, the ratio of concentrate THC to fl ower THC is “one to one,” because both are inhaled. Thus, the conversion factors between smoked concentrates (e.g., “dabbing”) and smoked fl ower products are based solely upon the THC potency embodied in the weight of Conversion Factors Edibles (Weight to 10mg Units) 0.25 Oz of Flower equals: 21 10mg Edible Units 1 Oz of Flower equals: 83 10mg Edible Units 1 Gram of Flower equals: 3 10mg Edible Units Concentrates (Weight to Weight) 0.25 Oz of Flower equals: 1.9 Grams Concentrate 1 Oz of Flower equals: 7.7 Grams Concentrate 1 Gram of Flower equals: 0.3 Grams Concentrate Potency (THC share of weight)62%Based upon metrc™ Data Figure IV-5. Conversion Factors between Marijuana Flower Weight and Non-fl ower Product Units Source: Author’s calculations, combined with medical literature findings and metrc™ data. As discussed earlier, this is caused by a number of factors, including the time-curve of THC and 11-OH-THC blood-plasma levels in the blood and the share of that THC that can pass through the blood brain barrier. RESULTING EQUIVALENCY TABLES For policy purposes, Table IV-5 is constructed to compare different quantities of fl ower to their equivalent edible serving sizes. Concentrates are also included, using the average potency found from laboratory testing in Colorado between October 2014 and May 2015. Equivalency Report 35 SECTION ISECTION IISECTION IIISECTION IVSECTION Vthe product itself. In Colorado, the average concentration ratio for wax or shatter type concentrates was 62 percent, based upon data collected between October 2014 and May 2015. Using this ratio, combined with the 17 percent average THC ratio in Colorado marijuana fl ower, the smoked THC conversion factors can be easily computed. For example, using the concentrate to fl ower THC ratios above, the result is 62/17 = 3.65. For concentrates, the daily limit corresponding to one- quarter ounce of fl ower, is 1.9 grams of wax or shatter concentrate. Similarly, one ounce of fl ower equals 7.7 grams of concentrate, and one gram equals 0.3 grams of concentrate. OILS, TINCTURES, LOTIONS, AND LESS COMMON UPTAKE METHODS In Colorado, the share of edibles and concentrates in total demand has increased substantially. This demand growth precipitated the need for further regulatory oversight for these products. There also exists a large array of addi- tional uptake methods for consuming marijuana. These include the sublingual approach (using tinctures), dermal (using lotions), and intravenous, among other methods. These methods are not considered here, because a full investigation into each method is beyond the scope of this report, and because the current demand levels for these methods are relatively low. If the demand shares for these methods grows and becomes more important, then some investigation is warranted. 36 Equivalency ReportSECTION ISECTION IISECTION IIISECTION IVSECTION Von the following page displays typical marijuana products and prices for the Colorado recreational market. How do we know that this product menu is “representative” of other menus along the Front Range? From an economic viewpoint, this menu is “representative” because the market for marijuana is relatively competitive. If this menu were signifi cantly more expensive, or signifi cantly less expensive than other menus, then the company would not sell much product, or they would be selling more product than they can produce in a given period. Similarly, if the relative pricing between product types were skewed, then buyers would only purchase selected items that are relatively inexpensive, and they would not purchase the items that are relatively more expensive. So, in addition to being “representative” in gross price, the menu here is also representative in relative price—the relationship between prices from this menu will be similar to the offerings from most Colorado retail stores. The prices listed in Table V-6 are displayed in terms of gross weight – either for marijuana fl ower or the weight of THC within a non-fl ower product. Until now, it was not possible to compare different products in Colorado, because there was no common denominator. However, using metrc™ data, this study fi nds the average potency of most popular marijuana strains to be quite narrow, between 16.5 and 17.7 percent of THCa. Therefore, we can use a midpoint value of 17 percent as the average expected potency in Colorado marijuana fl ower sold at the retail level. Using this potency, the menu in Table V-6, listed in dollars per weight or unit, can be converted into a uniform menu, using the weight of THC (or THCa). The most convenient unit of measure is “cents per milligram of THC” (₵/MGTHC). There is a third method to consider equivalencies between marijuana products in Colorado’s retail marijuana market. This is the “market price equivalency” method. From an economic viewpoint, this method is considered to be more direct than other methods, because it compares the price per unit of THC across different products, thereby refl ecting the price that consumers are willing to pay—on a THC basis—for each product type. Until now, it was not possible to compare market prices based upon THC content. By using mandated potency tests for fl ower and concentrates, an average potency rate can be applied, and then compared to edibles, which are marketed with fi xed levels of THC content. Prices for marijuana products are easily found on most storefront websites. Unlike many retail consumption products, the market for marijuana is relatively homogeneous. This is different from tobacco, where consumers identify products by brand name (Marlboro, or Camels). The homogeneity of marijuana suggests that market pricing should be based primarily upon the potency of the drug, rather than by advertising or marketing infl uences. Most consumers of marijuana are purchasing the product for its psychoactive properties. To the extent that the product supplies more doses, the supplier can sell the product at a higher price. Therefore, from an economic viewpoint, there should be a positive, and relatively linear, relationship between the psychoactive ingredient provided by marijuana products and the price paid for it. This relationship can be compared across different product types, and used as supporting or detracting evidence for the dosage equivalencies computed in the previous section. Recent marijuana prices were obtained from various Colorado vendors, and a table of representative prices has been constructed. The product menu in Figure V-6 Market Price Comparison Equivalency Report 37 SECTION ISECTION IISECTION IIISECTION IVSECTION VRepresentative Recreational Menu Prices — June 15, 2015 Flower Price by Weight ($USD) 1 gram 1 eighth 1 quarter 1 half-oz 1 oz Indica Ghost OG 14.03 41.27 82.54 148.58 264.14 Triangle Kush X Ghost OG 14.03 41.27 82.54 148.58 264.14 Sativa Glass Slipper 12.38 33.03 66.06 132.12 239.43 Hybrid White Master Kush 14.03 41.27 82.54 148.58 264.14 KING CHEM 12.38 33.03 66.06 132.10 239.43 Edibles THC MG Price (each) Highly Edible 100 mg 24.99 Incredibles Boulder Bar 100 mg 23.11 80 mg Dr. J’s AM capsules 80 mg 19.81 Gaia’s Garden Garden Drops 80 mg 19.81 Incredibles Peanut Budda 50 mg 19.81 40 mg Blue Kudu Chocolate 40 mg 14.00 Gaia’s Garden Single Serving Lollipop 10 mg 6.60 Gaia’s Garden Single Serving Karma Kandy 10 mg 6.60 Sweetgrass Snickerdoodle Cookie 10 mg 5.00 Concentrates THC MG Price (g) O-Pen Vape Cartridge 500 mg 66.00 Co2 Oil 61.92 Mahatma Shatter 61.92 TC Labs Shatter (Strain Specifi c) 55.00 O-Pen Vape Cartridge 250 mg 46.00 Figure V-6. Market Pricing for Marijuana Products in Colorado, Priced in Dollars by Weight or by Unit Source: Marijuana storefront websites, accessed on June 15, 2015. 38 Equivalency ReportSECTION ISECTION IISECTION IIISECTION IVSECTION VThe price ratios shown in Table V-7 on the following page are notable because they refl ect—quite closely— the pharmacokinetic results found earlier. That is, the standard market pricing for edibles, when compared by THC content, has a 3:1 ratio, just as the product equiva- lency tables would suggest. This means that although the market participants may not have completed their own pharmacokinetic research, they naturally have gravitated toward this result, based simply upon trial and error. Of course, there are some products at the edge of the pricing structure, where the price ratio for THC is higher than 3:1. For example, the “Single Serving Lollipop” is priced at 66 ₵/MGTHC, which results in an 8:1 ratio. This pricing relates mostly to the fact that pricing for very small servings (e.g., single servings) have a lower bound, due to packaging and marketing. The price of a single serving lollipop is $6.60, mainly due to a lower price bound for marijuana products in general. Products that contain more than a single 10 mg serving of THC are all priced more closely to the 3:1 ratio than the single-serving units. To summarize, the market price method for equivalency supports our earlier pharmacokinetic work. Market forces have led to a pricing structure that refl ects a roughly 3:1 ratio between smoked THC products and edible THC products. Equivalency Report 39 SECTION ISECTION IISECTION IIISECTION IVSECTION VRepresentative Recreational Menu Prices — June 15, 2015 Flower Price: Cents per mg THC 1 gram 1 eighth 1 quarter 1 half-oz 1 oz Indica Strains Ghost OG 8.25 6.94 6.94 6.24 6.10 Triangle Kush X Ghost OG 8.25 6.94 6.94 6.24 6.10 Sativa Strains Glass Slipper 7.28 5.55 5.55 5.55 5.53 Hybrid Strains White Master Kush 8.25 6.94 6.94 6.24 6.10 KING CHEM 7.28 5.55 5.55 5.55 5.53 Edibles Price: Cents per mg THC Price Ratio: (per 1 g of Ghost OG) Highly Edible 100 mg 24.99 3.03 Incredibles Boulder Bar 100 mg 23.11 2.80 80 mg Dr. J’s AM capsules 80 mg 24.76 3.00 Gaia’s Garden Garden Drops 80 mg 24.76 3.00 Incredibles Peanut Budda 50 mg 39.62 4.80 40 mg Blue Kudu Chocolate 40 mg 35.00 4.24 Gaia’s Garden Single Serving Lollipop 10 mg 66.00 8.00 Gaia’s Garden Single Serving Karma Kandy 10 mg 66.00 8.00 Sweetgrass Snickerdoodle Cookie 10 mg 50.00 6.06 Concentrates Price: Cents per mg THC Price Ratio: (per 1 g of Ghost OG) O-Pen Vape Cartridge 500 mg 18.86 2.28 Co2 Oil 9.53 1.15 Mahatma Shatter 9.53 1.15 TC Labs Shatter (Strain Specifi c) 8.46 1.03 O-Pen Vape Cartridge 250 mg 26.29 3.19 Figure V-7. Comparison of Market Pricing Between Flower and Non-fl ower Products, Priced in Cents per Milligram of THC Content Note: Conversions based upon average potency for flower and concentrate products in Colorado, determined through required testing of flower and concentrates. Source: Colorado storefront menus, accessed on June 15, 2015. Equivalency Report 41 REFERENCES10.) Huestis MA. Human Cannabinoid Pharmacoki- netics. Chemistry & Biodiversity. , 2007;(4):1770–1804. doi: 10.1002/cbdv.200790152. 11.) Nadulski T, et al. Simultaneous and sensitive analysis of THC, 11-OH-THC, THC-COOH, CBD, and CBN by GC-MS in plasma after oral application of small doses of THC and cannabis extract. Journal of analytical toxicology. 2005;29(8):782-789. 12.) Perez-Reyes M. Marijuana smoking: factors that infl uence the bioavailability of tetrahydrocannabinol. NIDA Res. Monogr 99. 1990;42-62. 13.) Schwilke EW, et al. 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Infused product — A marijuana product which is intended to be consumed orally, including but not limited to, any type of food, drink, or pill. Edibles — Any cannabis product which is consumed orally and digested is considered an edible. Hydrocarbon extractions — Any extraction process that uses hydrocarbons such as butane or propane. metrc™ — Marijuana Enforcement Tracking, Reporting and Compliance is the required seed-to-sale tracking system that tracks Retail Marijuana from either the seed or immature plant stage until the Retail Marijuana or Retail Marijuana Product is sold to a customer at a Retail Mari- juana Store or is destroyed. Marijuana Infused Product manufacturer (“MIP”) — An entity licensed to purchase Retail Marijuana; manufacture, prepare, and package Retail Marijuana Product; and sell Retail Marijuana and Retail Marijuana Product only to other Retail Marijuana Products Manufacturing Facilities and Retail Marijuana Stores. Supercritical extractions — When a substance is heated and pressurized beyond its critical point, it turns into a supercritical fl uid capable of working as a solvent to strip away oils and essential compounds. It is used in a variety of industries for botanical extractions with several different types of fl uid, but in the cannabis world, it generally refers to CO2 extractions. Supercritical extraction by nature is not particularly selective in terms of what it extracts, so many CO2 processors need to utilize a secondary solvent such as ethanol or hexane in order to remove waxes and chlorophyll prior to delivering a fi nished product. Butane hash oil ( “BHO, dabs, shatter, wax”) — A non- polar hydrocarbon which is used as a solvent in many other industries such as essential oil extraction, butane is especially well-suited for stripping cannabis buds or trim of their cannabinoids, terpenes, and other essential oils while leaving behind the majority of unwanted chlorophyll and plant waxes. In this extraction method, the solvent washes over the plant material and is then purged off from the resulting solution using a variety of techniques and variables such as heat, vacuum and agitation. Cannabinoid — any of the chemical compounds that are the active principles of marijuana. Cannabinoids include THC, THCa, CBD, CBDa, CBN, and other natu- rally occurring compounds. CO2 extraction — When high pressure is applied to CO2, it becomes a liquid that is capable of working as a solvent, stripping away cannabinoids and essential oils from plant material. This process is called supercritical extraction and is the most common method of making hash oil using CO2 instead of a hydrocarbon solvent such as butane. CO2 extractions can take many of the same textures as BHO, but generally they tend to be more oily and less viscous. Concentrate — Refers to any product which refi nes fl owers into something more clean and potent. This umbrella term includes any type of hash, solventless (kief), as well as any hash oils (BHO, CO2 oil, shatter, wax, etc.) and indicates that these products are a concen- trated form of cannabis, carrying a much higher potency. Decarboxylate — The process of converting THCa and CBDa into THC and CBD is an essential part of the process if you wish to consume cannabis orally. Decar- boxylation occurs at around 240 degrees Fahrenheit, converting THCa and CBDa into THC and CBD, respec- tively. Though the acid forms of these cannabinoids have some medicinal benefi ts, normally decarboxylation is Terms & Acronyms Equivalency Report 45 TERMS & ACRONYMSTHC — Tetrahydrocannabinol (THC) is the main canna- binoid found in the cannabis plant and is responsible for the majority of the plant’s psychoactive properties. THC has lots of medical benefi ts including analgesic properties, though perhaps its most defi ned quality is its tendency to increase appetite. CBD acts as an antagonist to THC, reducing its psychoactive effects. THCa — Tetrahydrocannabinolic acid (THCa) is the most prominent compound in fresh, undried cannabis.The compound does not have psychoactive effects in its own right, unless it is decarboxylated and converted into THC. Trim — After harvest, the cannabis plant is generally trimmed of its leaf matter, leaving behind only the buds. Trimming refers to the actual act of removing the leaves, while trim refers to the leftover leaves, which can be used for making concentrates and infused products. Vacuum purge — After extraction, most concentrates require further refi ning in order to remove the solvent which is remaining in the product. In order to do this, concentrate makers have utilized vacuum ovens and devices which serve to reduce the atmospheric pressure on the concentrate, which speeds up the process of removing the solvent. Starting in 2017 the State of California will begin issuing Licenses based on cannabis businesses that have already secured the following Local Permits: CULTIVATION Type 1 - Outdoor 5,000 sq ft Type 2 - Outdoor 5,001 sq ft - 10,000 sq ft Type 3 - Outdoor 10,001 sq ft - 1 Acre Type 1A - Mixed Light 5,000 sq ft Type 2A - Mixed Light 5,001 sq ft - 10,000 sq ft Type 3A - Mixed Light 10,001sq ft - 22,000 sq ft Type 1B - Indoor 5,000 sq ft Type 2B - Indoor 5,001 sq ft - 10,000 sq ft Type 3B - Indoor 10,001sq ft - 22,000 sq ft Type 1C Type 4 - Nursery - ​Non Flowering Plants - NO Plant Count MANUFACTURING Type 6 - Manufacturer 1​ - Non-Volatile Solvents - Water Hash, Live Rosin, CO2 Type 7 - Manufacturer 2​ - Light Hydrocarbon Extraction - Butane, Propane, and Hexane TESTING Type 8 - Testing​ - All Cannabis and Cannabis Products will need to be tested. DISPENSARY; GENERAL & MIXED LICENSE TYPES Type 10 - Dispensary - ​Brick and Mortars Type 10A​ - Dispensary; No more than three sites. - Also known as the 3:1:4 Model, 3 Dispensaries, 1 Manufacturing, and up to 8 x 22,000 sq foot grows. DISTRIBUTION/TRANSPORT HUB Type 11 - Distribution - ​Think alcohol distribution model. Type 12 - Transporter ​- Going to have to move it in secure vehicles until it is descheduled by the DEA. slonorml.org “Are you ready?” slonorml.org slocountynorml@gmail.com​ - 805-464-7420 - ​facebook.com/SanLuisObispoNORML/