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Each of the three genes was cloned into separateepisomal vectors, transformed into A. nidulans, and the resulting transformants were grown on CD-ST agar plates . Following 5 days of growth in CD-ST, the sample media were extracted and analyzed by liquid chromatography-mass spectrometry . To obtain compounds for structural determination, we first optimized the culturing conditions to get high titers from shake flask culture. By examining the organic extracts from cells and media separately, we determined that most of the compounds were secreted into the media. We also observed that a spore inoculum size of 104 spores/mL led to the highest titers of the four compounds whereas inoculum sizes of 108 spores/mL and higher gave low production of target compounds . Notably, when the molecules were produced at high titers, A. nidulans adopted a morphology of globular pellets. As the titer drops upon increased inoculum size, A. nidulans grew as dispersed filaments . The unnatural pairing can compromise the performance of overall biosynthesis by a “ratelimiting” component such as Ti_OvaBC. Aside from the molecular recognition of the acyl chain by the SAT domain active site, a successful acyl chain transfer also requires complementary protein-protein interactions between HRPKS ACP domain and NRPKS SAT domain.Previous studies have shown that although for some non-cognate HRPKS-NRPKS pairs, acyl chain could occur and new products emerged without any protein engineering efforts,4×4 flood tray for others replacement of SAT domain is necessary to compensate for the otherwise undermined inter-domain communication.While the sequence identity between ACPs of Ti_OvaA and Ma_OvaA is 62%, the identities between NRPKS SAT of Ti_OvaB and Ma_OvaB is lowered to 48%.

Such moderate sequence identity between the SAT domains implies that the recognition sites between ACP from noncognate HRPKS and SAT can be weakened or even abolished. Therefore, to generate a combination that exclusively produces 3 at a higher titer, protein engineering endeavors that improve the compatibility between unnatural HRPKS and NRPKS enzymes are necessary. Alternatively, further genome mining of related clusters may lead to one that can produce olivetolic acid robustly in a heterologous host. In summary, we have discovered a novel platform to produce OA and its analogs from filamentous fungi. The platform consists of an HRPKS and an NRPKS, known to produce resorcylic acid moieties in tandem, and a separate TE enzyme. This platform represents a new strategy to produce these cannabinoid precursors in microbes without relying on the OAS and OAC found in Cannabis sativa.Small quantities of olivetolic acid are produced in Cannabis sativa and chemical synthesis of the compound has proven to be difficult. Therefore, we hypothesized utilizing a Design of Experiments approach on our novel platform can further increase titer and thereby effectively solve the issue of low production. With regards to increasing production of fungal secondary metabolites and enzyme expression, DOE has proven to be an effective tool. DOE has been used for increased secondary metabolite production in bacteria, increased lipase production in fungi, increased xylanase production in fungi, and increased lignocellulolytic production in fungi, amongst other uses. We therefore sought to utilize a DOE approach to optimize the olivetolic acid and olivetolic acid analogs’ titer produced by our novel platform. DOE has proven to be more effective than one-factor at a time analysis because it greatly reduces the number of experiments needed and considers the interactive effects that factors can have with each other. The DOE approach begins at screening and ends at optimization and predictive modeling. First, screening is done to identify the factors that are most significant in the parameter response.

We decided to focus our DOE approach on the media that our A. nidulans strain producing olivetolic acid and its analogs is cultured in. Since our DOE approach is focused on media, we tested the effects that nine different components have on the production of sphaerophorolcarboxylic acid, olivetolic acid, and the analogs. Utilizing JMP statistical software, we performed an initial screening run of 24 experiments in order to identify the 3-5 most significant facts. To perform the screening experiments, we had to decide between a variety of screening platforms provided by JMP. JMP offers two types of screening designs: classical screening designs which include fractional, factorial, Plackett-Burman, regular fractional factorial, Cotter, and mixed-level designs and main effects screening designs: screening designs focused on measuring main effects with negligible interactions between the factors. We opted for a classical screen design because we wanted to include the interactions between factors and considered the different types from there.Two-level full fractional factorial designs account for all the combination of the factor levels. Two-level refers to a high value and a low value for the factor tested. The total number of runs for this design is the product of the factor levels. For example, for a two level full fractional design, the total number of runs would be 2n where n is the number of factors tested. The design also estimates that all of the effects are uncorrelated and that there are no interactions between the factors, i.e., the factors are orthogonal to each other.From a screening point of view, we determined the full fractional factorial design to be inefficient and cumbersome to do since it would require us to generate 29 types of media to test. The next classical screening design to consider was two-level regular fractional factorial.Two-level regular fractional factorial designs are similar to full fraction factorial designs; however, instead of the number of runs being equal to 2n where n is the number of factors tested, regular fractional factorial design runs are equal to 2n-k where k<n. In other words, a two-level regular fractional factorial is just a fraction of the full two-level fractional factorial design and therefore like the full factorial design, considers all the factors to be orthogonal to each other.

Since we could determine the fraction we would use, this was seen as an adequate design to choose; however, we wanted to consider some interactions between factors we determined to not follow through with this design and next looked at Cotter designs. Cotter designs are useful due to the ability to test a large number of factors in a small number of runs and are also useful if one is interested in the interaction between factors. Cotter designs are upheld by what is known as the principle of effect sparsity. These designs operate under the assumption that if one of the components of the sum of factors has an active effect , the sum of the factors will display the response.However, this can be potentially misleading and lead to false negatives if for example, one factor has a positive effect on the response, while the other factor has a negative effect, therefore totaling the sum of the factors to be zero/near zero, and therefore failing to show an effect. We determined not to go through with this design due to the false negative risks. We proceeded then briefly to mixed level designs. Mixed level designs are typically used when screening categorical or discrete factors containing varied factor levels.For example, one can be screening for the effect that light and a four-level media component have on the titer of a metabolite. Since we desired to keep the screen simple with just two levels for our factors since and we did not have any qualitative factors,hydroponic tray we proceeded to our last design, the Plackett-Burman design. Plackett-Burman designs are somewhat like regular fractional factorial designs except the total number of runs are a multiple of four rather than a power of two. Additionally, interactive effects between factors in a Plackett-Burman design are only partially confounded by the main effects which differs from regular fractional factorial where the interactive effects are completely confounded by the main effects and are therefore indistinguishable from each other.Plackett Burman designs are typically utilized when testing for the main effects among a variety of factors and so with this in mind, we chose to utilize the Plackett-Burman design as our screening design. We implemented the two-level Plackett-Burman design and generated 24 runs to test, with each run being a different media composition. For the two levels , we determined these values to input: temperature , pH , starch , NaCl , dextrose , yeast extract , casein acidic digest , trace elements , and 20x nitrate salts . We cultured the strain in these different medias, assaying the titer in media sets of 4 with CD-ST as the control media in each run. We inputted the data into the JMP software and performed analysis of variance and generated a Pareto chart from ANOVA and noted the results. ANOVA is a widely used tool to determine if there are statistical differences between means of different groups.

It is a collection of different statistical models and is used to determine whether the variance of a specific effect or factor interaction is statistically significant.The Pareto chart puts the ANOVA data in a simple to understand form, displaying whether the factor or factor interaction has exceeded the t- value limit and Bonferroni limit. The t-value refers to the value of the difference relative to the variation of the data tested. It is a value that represents the ratio of the difference between the estimated value of factor and its hypothesized value to its standard error.126 The Bonferroni limit is the value from the Bonferroni method that answers which factors means are significantly different from each other. Factors and factor interactions above the Bonferroni limit indicate that they are statistically significant and have a great effect on the parameter response, factors and interactions between the t-value limit and Bonferroni limit are indicated as potentially significant, and factors and interactions below the t-value limit are noted as insignificant.Based on the Pareto chart, we noted that increased temperature, addition of dextrose, addition of yeast extract, and addition of NaCl all had values above the Bonferroni limit indicating that these factors significantly affected the titer. However, three of values were all labeled blue indicating a negative result. Increased nitrate salts which had a negative effect on the media based on its blue distinction had a t-value greater than the t-limit but lower than the Bonferroni limit whereas increased casein acidic digest and increased starch which were also labeled blue had t-values lower than the t-limit indicating that these factors are not statistically significant. For factors having a positive effect on the titer labeled orange, NaCl salt had a tvalue greater than the Bonferroni limit indicating its statistically significance and increased nitrate salts had a t-value lower than the t-limit indicating it is not significant. From the screening data, we proceeded with two factors for our optimization experiments: NaC1 and nitrate salts. Although it was tabulated as not significant, we chose to include nitrate salts mainly because we did not want to optimize just one factor and since nitrate salts were already included in the media. We also included addition of MgSO4 since that was noted in the literature to increase metabolite production.Once we obtained the three factors, we utilized the response surface methodology optimization approach for optimization of the media, seeking to add these factors to our CD-ST media containing starch, trace elements, and casein acidic digest as the base since these factors had no statistical significance towards the titer. RSM is a widely used method for modeling/predictive modeling.RSM optimizes the factors correlating to a response with the inclusion of the effects interactions between the factors have. RSM has proven to be just as effective in modeling as a 3-level full factorial design, but its advantage is that RSM greatly reduces the number of experiments needed to form an accurate model. As an example, in a 3- level factorial design utilizing 3 factors, one would need to do 27 experiments to get an accurate model as opposed to the 15 experiments one would need for a central composite design RSM approach. As the number of factors increase, the difference between the number of experiments needed for a 3-level full factorial design vs a central composite design RSM approach greatly increases, which is why RSM is the advantageous approach. Reports of the effectiveness of increasing secondary metabolite production in fungi with the RSM approach have been recorded. Talukdar et al. observed a 7-fold increase in antibiotic production of Penicillium verruculosum MKH7 utilizing an RSM approach on the media used.

Under these conditions the integrated system was able to produce cold and dehumified air that is in the safe range for server racks. In this case the return air from server is considered for first stage cooling air which has lower relative humidity and higher potential for evaporative cooling.However, the system is able to provide only 97CFM of air flow under these conditions, which is less than the maximum air flow demand for each server rack. This suggests that the current integrated SOFC-LDD system cannot continuously provide all the power and cooling required for the server rack if it is operated continuously at 12kW. However, both the server demand dynamics and day-night weather variations, could lead to dynamic conditions that with some storage of the concentrated solution could be well-matched to the server demands for power and for cooling and dehumidification. Next step will consider these dynamics for several real-world weather and server power. For the second weather condition with 35˚C and 45%RH the system can produce 96CFM cold and dry air for each server rack. In this case the outside air is considered for the first stage cooling air. Please note that the SOFC system is running based upon design operating conditions for the system. Further investigation is needed to evaluate the SOFC system available heat under different operating conditions that could produce higher quality exhaust heat likely at the expense of electrical efficiency. The results are presented for two scenarios; in first scenario, liquid desiccant provides dehumidified air for one single server rack for the entire year,indoor weed growing accessories the fuel cell runs at full load, and the dehumidifier is sized based on server rack, and the regenerator is sized based on FC exhaust.

In second scenario, liquid desiccant provides dehumidified air for two rows , Fuel cell runs at 70% load, dehumidifier is sized based on cooling required for two rows, and regenerator is sized based on equivalent of two rows fuel cell exhaust. The reason for row level fuel cells running at 70% and in rack level running at 100% is that when fuel cell provides power for only one rack, it is more likely that the single server rack runs at full load, however, when several fuel cells provide power for 20 racks, the load of serves will be balanced to the data center overall utilization .Figure 64 to Figure 69 show dehumidifier results for Illinois. In dehumidifier, two air streams are send to the system, one is the supply air which is a mixture of outside air and return air and the second stream is the cooling air that is send to the dehumidifier to keep the temperature constant by evaporative cooling. Figure 64 and Figure 65 show the supply air and cooling air inlet and outlet temperature. The temperature of the streams stays almost the same even though the dehumidification is an exothermic process, which is due to the indirect evaporation of water to the second air stream. Figure 66 shows the amount of return air. For Illinois during May to September dehumidification is needed. Other time of the year the humidity of supply air is within the acceptable range. As the outside air humidity is higher the use of return air increases due to its lower humidity compared to outdoor air. However, the return air percentages depend both on temperature and humidity of outdoor air and return air to keep the supply air humidity within the acceptable range for servers. Figure 67 shows the humidity ratio of inlet and outlet supply air. The SOFC systems installed at NFCRC are BlueGEN cogeneration systems. BlueGEN is a commercially available CHP unit, built and sold by SOLIDpower. Figure 87 shows the eight BlueGEN units as installed in the NFCRC laboratory.

Operating on natural gas, each unit can produce power modulated from 500We to 2kWe ; however, it achieves its highest net electrical efficiency of 62% at a 1.5kWe output. The BlueGEN systems are typically operated and controlled remotely by SOLIDpower. However, through an online human machine interface, the power output profile and as a result fuel utilization are controllable by the user. To be able to install the BlueGEN we need to provide six connections: fuel , electrical, flue gas, internet, water, and drain connections. BlueGEN requires an uninterrupted supply of natural gas, and it only operates on the second family of gases . Gas supply pressure to the BlueGEN appliance must be 9–20mbar so an Elster Jeavons gas pressure regulator is used to avoid fluctuations due to variations in the main gas supply pressure.The BlueGEN systems require an electrical connection to successfully operate during startup and to export the electricity produced during normal operation. For electrical connection the grid availability is 208VAC 3 phase, 60 hertz. Each fuel cell needs 120VAC 1 phase, 60 hertz. 3 transformers are used where two of them provide electrical connection needed for six BlueGENs and one of them runs two BlueGENs. The main water supply pressure must be at least 1bar and no more than 10bar . During operation, the appliance can consume up to 30litres of water per day, depending on heat and condensate recovery. The BlueGEN appliance has an internal water storage tank for the process water and this tank will fill from the main water supply intermittently. The water consumption rate may be up to 1 liter per minute when this tank is filling. Operation of water needs to be uninterrupted. Wastewater is ejected from the BlueGEN appliance under pressure . The main water supply connection, drain, and overflow rejection connection configuration can be seen in Figure 88. Water is distributed in a manifold to each fuel cell line and each fuel cell has its own valve for water shut down.

For water rejection line, overflow and wastewater will be collected in a tank through a sloped pipe and then will be pumped to the drain. Figure 89 and Figure 90 show the pump used for fuel cell water rejection connection, manifold, and valves for fuel cell supply water, respectively. Looking at SOFC dynamic data, it is observed that BlueGEN electrical efficiency is the highest, roughly 64%, at full load. BlueGEN efficiency is the lowest at 30% at 300W of output . The BlueGEN system is recommended to run between 1500W and 500W. At the lowest recommended power, the efficiency is roughly 43%. As expected, at loads lower than the nominal power current density drops, and because of lower polarization, voltage increases. Experimental results show that BlueGEN control system is designed to keep air flow constant and that it changes the fuel utilization and fuel flow proportional to the output power. BlueGEN stack temperature difference is designed to stay at 50℃ at full load. The experimental results show that by reducing the load, the temperature difference decreases. The exit temperature drops below the inlet temperature at 700W. At low current density the endothermicity of reformation reaction is higher that exothermicity of electrochemical reaction which causes temperature drop along the cell. Note that while electrochemical efficiency increases at part-load, fuel utilization is lowered to maintain the overall thermal balance so that the overall system efficiency drops at part-load conditions. At these part-load conditions the fuel cell stack operates at overall endothermic conditions, which must be matched by heat from the thermal oxidizer that converts the unspent fuel at the lower fuel utilization conditions.In another dynamic test,rolling benches the BlueGEN system was tested through the following profile shown in Figure 95 in 24h for 42 days. During this cycle, the power decreases between 1500W to 500W with 100W increments. In each power step the system is given 1 hour to reach to steady state and then it has 15 minutes to ramp down to the next power level. At this writing the BlueGEN system has been running for more than 6000hr from the time of installation at the NFCRC. Figure 104 shows the power profile of BlueGEN system over this 6000h operating period. After 4000 hours of steady-state operation the system runs the first dynamic load Figure 93, then after a couple of days of steady operation it goes through the 24h dynamic load cycles for 1000hr followed by the one-week dynamic cycle. Figure 105 shows the voltage change over the 600hr operation. The system operation is divided to three region and Table 22 shows the degradation results for each of the regions of operation. During the first 1000hr of operation as the system is new the degradation rate is twice that of the regular steady-state operation. Also, the system degrades twice as fast as steady-state operation while operating under highly dynamic operating conditions.

As the system degrades, the fuel consumption increases and as a result the overall system efficiency drops. For cell level tests, experiments were carried out using a commercial anode supported solid oxide cell. The cell anode side consists of two layers, a thick Ni-YSZ anode support acting as the mechanical support, current collector and gas diffusion layer, and the other is the functional layer with a more dense structure near the electrode-electrolyte interface . The electrolyte consists of 8% mol Y2O3-ZrO2 on which Gadolinium Doped Ceria oxide barrier layer is deposited to prevent the formation of insulating SrZrO3. The cathode active layer was made up oflanthanum strontium cobalt ferric oxide in contact with the cathode current collector of similar thermal expansion. The cell had an active area of 12.6cm2 . The experimental setup of the single cell used for each of the three 1000hr tests is shown in Figure 107. The furnace keeps the temperature at constant. The JV scan and EIS measurements were performed with a Zahner Zennium impedence analyzer. Zanher positive terminal connects to the cathode and the negative terminal to anode. The voltage response is also measured via the same system. During EIS measurements constant loads of 0.1, 0.5, and 0.9A/cm2 were applied to the cell. For applying constant loas of 0.5A/cm2 during the 1000hr polarization a load box is connected to the setup. The fuel cell air and fuels are supplied by Voegtlin Red-y smart series mass flow controllers. The purity level of hydrogen, nitrogen and ammonia used in the experiments are 99.999%, 99.999% and 99.99% respectively. Nitrogen and hydrogen are stored as compressed gases while ammonia is stored in liquid form in commercial cylinders.The single-cells were tested with three different fuel composition as shown in Each test runs on a pristine single cell SOFC. Cell 1 on pure H2, cell 2 on H2-N2 case, and cell 3 on NH3 directly, which includes the internal decomposition reaction . A nominal operating temperature of 750°C is chosen for the tests. After mounting each cell, each SOFC cell is reduced in H2 and N2 atmosphere. Each cell runs for 1000hr at 0.5A/cm2 to compare long term effect of different fuel on SOFC degradation. Dynamic current density – Voltage scans were performed every 100hr from Open Circuit Voltage to 700mV at 5mV/s with 1mV resolution. The JV scans are followed by three EIS measurements at 0.1, 0.5, and 0.9A/cm2 and 200mA perturbation signal for a frequency range of 1KHz to 200KHz. The quality of EIS spectra was verified using the Kramer Kronig’s test. The overall test duration of test for each cell was 47 days. Table 23 to compare the degradation effects between in-situ and ex-situ ammonia reforming with that of pure hydrogen for a duration of 1000h. Each test runs on a pristine single cell SOFC. Cell 1 on pure H2, cell 2 on H2-N2 case, and cell 3 on NH3 directly, which includes the internal decomposition reaction . A nominal operating temperature of 750°C is chosen for the tests. After mounting each cell, each SOFC cell is reduced in H2 and N2 atmosphere. Each cell runs for 1000hr at 0.5A/cm2 to compare long term effect of different fuel on SOFC degradation. Dynamic current density – Voltage scans were performed every 100hr from Open Circuit Voltage to 700mV at 5mV/s with 1mV resolution. The JV scans are followed by three EIS measurements at 0.1, 0.5, and 0.9A/cm2 and 200mA perturbation signal for a frequency range of 1KHz to 200KHz. The quality of EIS spectra was verified using the Kramer Kronig’s test.

Adolescent substance users have also been found to exhibit abnormalities in brain function, structure, and volume. However, given the nature of human studies, it is difficult to establish a causal link between early life exposure and the development of these conditions, especially as drug co-use is not often considered and may partially explain inconsistent findings noted in prior studies. Nicotine acts in the brain via the neuronal nicotinic acetylcholine receptors, which are ligand-gated ion channels expressed on both presynaptic and postsynaptic membranes. Rodent models have shown that adolescent nicotine exposure alone may lead to behavioral alterations during adulthood. For instance, in male and female rats, adolescent nicotine enhances nicotine reward and intake during adulthood. Nicotine during adolescence has also been shown to increase depression-associated behaviors, decrease exploratory activity, and induce deficits in context conditioning to shock-associated cues in adult rats. However, in these studies, differences were not found with anxiety associated behaviors, extinction of contextual conditioning, or cued fear responses. In mice, sex dependent effects have been noted, with adolescent nicotine consumption leading to decreased anxiety-associated behaviors in adult females, but not males. With regard to cannabinoids, Δ9-tetrahydrocannabinol has been classified as the main psychoactive component in cannabis and exerts its actions on cannabinoid 1 and cannabinoid 2 receptors in the brain and periphery. Differential patterns of expression for these receptors are found across adolescent development and between males and females,drying room and notably CB1 receptors exhibit the highest level of expression during the developmental period of mid-adolescence.

Following THC administration in adolescence, adult female, but not male, rats exhibit depression-associated behaviors, but no changes in anxiety-associated or general locomotor behaviors were observed. Interestingly, the depression-associated behavioral effects found in females were paralleled by significantly reduced CB1 receptor expression and activity in the amygdala, ventral tegmental area and nucleus accumbens, whereas similar changes were not found in the ventral tegmental area and nucleus accumbens of males. Further, administration of WIN 55,212–2, a CB1 and CB2 specific agonist, during adolescence has similarly been shown to increase depressive-like behaviors, as well as palatable food intake, during adulthood in male rats. Together, these prior findings demonstrate that early life exposure to either nicotine or cannabinoid agonists alone can alter later affective and cognitive function, which introduces the possibility of potential synergistic or opposing effects under co-use conditions. In the current studies, we sought to examine whether nicotine and cannabinoid coexposure during mid-adolescence would result in altered affective and reward-seeking behavior during adulthood. While prior studies have examined each drug and/or behavioral measure independently, the current investigations represent the first study of a co-exposure condition, which is commonly found in human subjects, and the resulting effects on multiple cognitive and affective measures. To this end, adolescent mice were exposed to the cannabinoid receptor agonist, WIN55,212–2, and/or nicotine and then assessed for cognitive, anxiety-related and depression-related behaviors during adulthood.

Drug exposure occurred during postnatal day 38–49, which corresponds to mid-adolescence in rodents or ~13–17 years of age in humans. Based on prior evidence of differential responses for males and females with drug-related effects and baseline receptor expression, male and female mice were examined in a within-sex manner. Further, given that significant differences were found in behavioral measures at the moderate dose of the cannabinoid agonist, a second study was then conducted to examine whether these effects would be maintained with a lower dose of the cannabinoid agonist. Together, these studies provide evidence that adolescent drug exposure alters affective and reward-related behaviors during adulthood in a sex- and drug-dependent manner.Male and female wildtype C57BL/6J mice were derived from breeders in our laboratory animal facilities. Mice were maintained in an environmentally controlled vivarium on a 12 h reversed light/dark cycle. Food and water were provided ad libitum until behavioral training commenced. During food training, subjects were mildly food restricted to 85–90% of their free-feeding bodyweight, and water was provided ad libitum. Following food training and the lever reversal task, food and water were again provided ad libitum for at least 5 days prior to subsequent behavioral assessments. All experiments were conducted in strict accordance with the NIH Guide for the Care and Use of Laboratory Animals and approved by the Institutional Animal Care and Use Committee at the University of California, Irvine.The cannabinoid receptor agonist WIN55,212–2 mesylate was dissolved in vehicle containing 1% DMSO, 1% Tween-80, and 98% saline . The doses of WIN55,212–2 administered were 2 or 0.2mg/kg intraperitoneally .

The moderate dose of WIN was selected based on prior studies demonstrating altered neural function with adolescent exposure in mice and rats, and the low dose of WIN was selected since this amount of drug has been shown to sustain daily reinforcing self-administration behavior in adolescent rats. -Nicotine hydrogen tartrate salt was dissolved in 0.9% sterile saline and adjusted to pH 7.4. Nicotine was administered at a dose of 0.36 mg/kg, subcutaneous ; this dose is within the rewarding range of the dose response function that also elicits a behavioral response in adolescent C57BL/6J mice. Peripheral injections were administered at a volume of 10 mL/kg.On PND 70, subjects were mildly food restricted and trained to press a lever in an operant chamber for food pellets under a fixedratio 5, time out 20 s schedule of reinforcement. Each session was performed using 2 retractable levers . Completion of the response criteria on the active lever resulted in the delivery of a food pellet. Responses on the inactive lever were recorded but had no scheduled consequences. Once stable responding was achieved , the lever assignment was switched to examine cognitive flexibility. In the reversal task, the previous inactive lever became active, in that food pellets were earned in accordance with the established FR5TO20s schedule. In contrast, the previously active lever became inactive, in which responses were recorded but without scheduled consequence. All behavioral responses were automatically recorded by Med Associates software.The elevated plus maze was composed of 4 opaque runways 5 cm wide and 35 cm in length, which were elevated 40 cm from the floor. Two opposing closed runways had opaque walls 15 cm in height, whereas the other two opposing sides did not contain walls . Subjects were placed in the center portion of the elevated plus maze and behavior was recorded for 5 min with a video camera. Behavior was scored by two blinded experimenters with ANY-maze software.Subjects were habituated to sucrose pellet consumption for 2 days prior to sucrose testing, during which time 60 mg of sucrose pellets was provided for each subject in the home cage. On the third day, subjects were individually examined in home cage conditions, but were single housed and provided 200 mg of total sucrose pellets in a dish. All subjects were maintained under ad libitum full food conditions, and thus were not food restricted during testing. Sucrose eaten was recorded at specified intervals by experimenters blinded to the group condition. At the end of each session, experimenters examined the cage for breakage or disintegration of sucrose pellets; this occurred on only a few occasions and in these instances, the remnant amount was calculated and included in the final mg amount of sucrose remaining. Mice were required to consume at least one 20mg sucrose pellet within the first 30-min time period for inclusion in the study.Subjects were examined for their daily intake of mouse chow. Mice were restricted to daily feeding sessions of 6 hr periods. During these sessions, subjects were individually housed and provided full access to consume 6–8 grams of standard chow , and water was provided in the feed cages ad libitum. Food was weighed prior to and after each session. After 3 days of habituation to the feeding protocol, data were collected on the fourth day and analyzed across groups.A cylindrical tank was filled with room temperature water at a level of 15cm from the bottom of the tank. For testing, each subject was held by the tail, and slowly placed in the water. Mice were videotaped for the 5 min swim test duration. Analysis of distance traveled was assessed with AnyMaze software,how to trim cannabis and the quantity of immobility bouts was hand scored by two separate experimenters to ensure accurate assessments.Given that these studies sought to investigate the effects of drug exposure relative to the control condition within each sex, statistical comparisons were performed separately for males and females based on this a priori hypothesis. Data were analyzed by a t-test, one-way or two-way ANOVA with Prism 7 software , as appropriate. Data obtain across sessions was analyzed with a repeated measures two-way ANOVA. Significant main or interaction effects were followed by Bonferroni post-hoc comparison with correction for multiple comparisons.

The criterion for significance was set at α = 0.05.In an initial cohort, we assessed whether drug condition would affect change in body weight during the duration of the drug injections from postnatal day 38 to PND 49 . Change in body weight was also compared to adulthood at PND70, prior to the commencement of behavioral assessments. Groups did not differ in body weight at PND 38 following random group assignment.For both males and females, post-hoc tests revealed significant differences between the number of active and inactive lever presses for all groups from sessions 3–7, but the groups did not differ from one another when comparing responding among drug conditions on each lever. After establishing consistent responding on the active lever, cognitive flexibility was examined in the reversal task. Subjects were required to switch their lever pressing behavior, as the active and inactive lever assignments were reversed. After establishing consistent responding on the active lever, cognitive flexibility was examined in the reversal task. Subjects were required to switch their lever pressing behavior, as the active and inactive lever assignments were reversed. Given the growing incidence of nicotine and cannabis experimentation during adolescence, we sought to examine whether such exposure would lead to altered behavioral effects during adulthood. In these studies, we found that male adolescent exposure to a moderate dose of the cannabinoid receptor agonist, WIN55,212–2 , led to increased cognitive flexibility in a learning reversal task, decreased anxiety-associated behaviors, and increased natural reward consumption, but no differences in general locomotor or depression-related behavior. Interestingly, the co-exposure condition of both nicotine and the moderate dose of WIN led to similar behavioral profiles as WIN alone in these measures, suggesting that a potentiative or additive effect was not present for these behaviors. However, with regard to the number of lane crosses in the elevated plus maze, the nicotine and WIN co-exposure condition appeared to exert a counteractive effect on the WIN-induced increase in exploratory behavior at the moderate dose, suggesting an opposing effect with adolescent exposure to both drugs. With regard to females, the moderate dose of WIN induced a lower body weight during the adolescent period, but co-exposure with nicotine appeared to exert an opposing effect that resulted in no difference from the control condition. However, these effects of WIN on body weight were transitory, as the difference in females did not persist into adulthood. For the behavioral assessments, female subjects were overall more resistant to the long-term effects of adolescent drug exposure. Group differences were only found in the sucrose consumption test, in which the moderate dose WIN females exhibited decreased natural reward consumption compared to the control females. However, differences from the control were not found with the female nicotine and WIN co-exposure condition for sucrose consumption, suggesting that the presence of nicotine ameliorated the actions of WIN on reward circuitry during the adolescent period. In contrast, adolescent exposure to a low dose of WIN had no effect on physiological or behavioral measures, either alone or in the presence of nicotine, for both males and females. Taken together, these findings demonstrate that while adolescent cannabinoid agonist exposure at a moderate dose exerts variable effects on both physiological and behavioral measures in males and females, co-administration of nicotine surprisingly counteracted some of these effects by normalizing to control levels. While prior studies have examined the effects of adolescent exposure of either nicotine or WIN alone on later behaviors, the current findings represent the first examination of the effects of co-exposure during mid-adolescence and subsequent long-term effects on adult behavior. This age range was selected based on the correlation to human adolescence with higher levels of experimentation and more recurrent patterns of drug consumption than that found in younger individuals. With regard to nicotine alone, opposing effects have been found in male Sprague-Dawley rats with increased depression-associated behaviors, but no difference in anxiety-associated behaviors, during adulthood. However, these behavioral differences were only found at higher nicotine doses approximately twice that administered in the current study.

The San Francisco Medical Cannabis Act sets up a permitting system for MCDs and places certain restrictions on their location and operation. Speaking directly to the issue of crime, Section 3308 of the Act states that dispensaries must “provide and maintain adequate security on the premises, including lighting and alarms reasonably designed to ensure the safety of persons and protect the premises from theft.” The Act further requires that all MCDs comply with California state law as well as guidelines written in 2008 by then-Attorney General Jerry Brown entitled “Guidelines For The Security And Non-Diversion Of Marijuana Grown For Medical Use”. Brown’s guidelines state that “a properly organized and operated collective or cooperative that dispenses medical marijuana through a storefront may be lawful under California law” if they meet certain requirements, including: operating on a not-for-profit basis, obtaining all of the relevant permits and licenses, taking steps to verify that their members are qualified patients or caregivers under state law, acquiring and distributing only marijuana that has been cultivated legally, prohibiting sales to non-members, and providing adequate security . Regarding security, Brown states that MCDs must “provide adequate security to ensure that patients are safe and that the surrounding homes or businesses are not negatively impacted by nuisance activity such as loitering or crime.” Expanding on this theme, the San Francisco Medical Cannabis Act prohibits “any breach of peace… or any disturbance of public order or decorum by any tumultuous,cannabis grow room riotous or disorderly conduct” within permitted MCDs.MCDs are required to submit security plans as part of their permit application.This study examines whether such security protocols amount to capable guardianship, which is an effective deterrent against crime according to routine activities theory .

In cities that do not regulate MCDs, it is difficult to determine when and where dispensaries operate, and for how long. It is also much more difficult, in the case of unregulated dispensaries, to infer whether MCDs implement security protocols amounting to capable guardianship against crime, from a routine activities perspective . Simply put, San Francisco is the largest California city to have enacted meaningful legislation with respect to MCDs. It has done so in a way that reasonably controls for crime, at least in theoretical terms. Thus it provides an excellent case study for analyzing the spatial relationship between crime and locally regulated MCDs. All data analyzed in this study are for the year 2010, a year in which there were 26 permitted MCDs in San Francisco. Although it is too early to say, it is possible, due to the current federal crackdown on MCDs in California and MCDs, that 2010 will end up being the last full year for which this type of analysis can be conducted. Since research for this project began in the summer of 2011, at least ten Bay Area MCDs have closed, including five in San Francisco, under pressure from Melinda Haag, the US Attorney for the Northern District of California.Not surprisingly, Haag’s justification for the crackdown is that MCD’s attract crime and endanger communities. Crime data were collected from the San Francisco Police Department in late 2011. The Crime Analysis Unit provided lists of serious crimes reported in 2010 along with the date and approximate location of each crime. Here, “serious crimes” refer to those classified as Part I offenses by the Federal Bureau of Investigation in its Uniform Crime Reports. The crime variables used in this analysis include measures of “violent crime” as well as “property crime” ; both as total counts and as rates per 1,000 residents. The lists of crimes and addresses were geocoded and aggregated into census tracts using ArcGIS software.Geocoding refers to the process by which tabular data are attributed spatial components by a geodatabase.

Geocoding resulted in a successful match for more than 98% of all crimes, which were the aggregated into census tracts using a “spatial join” analysis. The remaining 1-2% of crimes were discarded from analysis. In addition, some reported crimes were removed from analysis because their geocoding confidence ratings were below 95%. In the end 43,688 reported crimes were analyzed out of the original 44,422 for which the San Francisco Police Department provided 2010 data. For the purpose of analysis, these crime measures were aggregated together by census tract. This measure was then transformed by natural logarithm to address a right-skewed distribution . The primary independent variable under examination is the density of MCDs. Lists of MCD names and addresses were compiled using information provided by the San Francisco Department of Public Health. These MCDs were located across 16 census tracts primarily in the downtown area, as illustrated by Maps 4.1 and 4.2. The MCD addresses were geocoded to 100%. As with crime frequency, data for MCDs are presented in two forms. Descriptive statistics presented in Table 4.1 include MCD density as the number of dispensaries per square mile in a given census tract. For the regression analyses presented by Table 4.2, this variable is transformed by natural logarithm to address a right-skewed distribution.Crime rates by census tract are presented by Maps 4.1 and 4.2 . All data presented are for the year 2010. MCD locations are marked by green crosses. These addresses were obtained from the San Francisco Department of Public Health. Crime rates were calculated using data obtained from the San Francisco Police Department. Census tracts are assigned to one of five classes based on their crime rates. Because crime rates were transformed by natural logarithm to address a right-skewed distribution, units are not given. As Maps 4.1 and 4.2 illustrate, MCDs are largely concentrated in downtown San Francisco. This could confound the relationship between MCD density and crime. Downtown areas are densely populated and highly trafficked. In terms of routine activities theory , they contain larger numbers of likely offenders and suitable targets.

The high rate and volume of human activity also poses a challenge in terms of guardianship. Thus it is likely that these areas will have high rates of crime, independent of any other factor . This potentially confounding factor highlights the need to consider other variables in the forthcoming analysis, namely, the “exogenous sources of social disorganization” identified by Sampson and Groves . The story told by Maps 4.1 and 4.2 is too simple to be of use to policymakers wishing to understand the relationship between MCDs and crime. Alongside MCD density, it is also important to analyze socioeconomic disadvantage, family stability, and residential turnover. I discuss these factors in the following section.In addition to the primary variables already discussed, data were also collected for several neighborhood characteristics that could potentially confound the relationship between MCDs and crime. These neighborhood characteristics are drawn from social disorganization theory, which associates higher rates of crime with socioeconomic disadvantage, family disruption, residential instability, and population heterogeneity . From these, the present study examines the criminogenic effect of poverty, unemployment, percent of single-parent households, percent of housing units that are vacant, and percent of the population between the ages of 18 and 24. Demographic data are collected from the American Community Survey database of the United States Census Bureau via the American FactFinder website, as well as the Demographic Research Unit of the California Department of Finance. With regard to the census data, variables are constructed from the ACS 5-year estimates for the year 2010.Criminological research has found that indicators of socioeconomic disadvantage—including poverty and unemployment—have been associated with higher crime rates . In the present study economic data are collected from the ACS. The U.S. Census Bureau calculates the poverty status of individuals based on whether their total income in the past 12 months falls below the applicable poverty threshold,grow trays which is determined by age, family size, and family composition . The 2010 poverty thresholds range from $11,139 for a single individual living alone to $42,156 for a family of eight or more people living in the same household.For the present analysis, “poverty” means the number of individuals with incomes under their applicable poverty threshold in the past twelve months, divided by the total number of people for whom poverty status is calculated within a given tract.According to the United States Census Bureau, an individual is considered unemployed if he or she did not have a job and has been actively looking for work during the last four weeks and was available to start a job at the time of the survey . “Unemployment”, in the present analysis, means the unemployment rate in each tract as estimated by the ACS.

Research examining crime rates in the United States during the 1990’s suggests that the job market can provide powerful explanations for criminal behavior . Poverty and unemployment are important measures in the model currently being tested, as they control for varying levels of socioeconomic disadvantage across city neighborhoods, which according to social disorganization theory affect crime rates in significant ways .In this study I use “family stability” as an inverse measure of family disruption. I calculate family stability by taking the number of individuals living in married couple family housing and dividing it by the number of people living in single-parent family households. Scholars of both routine activities theory and social disorganization theory predict that higher concentrations of married-couple families are associated with lower crime rates in urban areas, because more parents can provide more supervision and therefore more social control. From a routine activities perspective, both “family stability” and “residential stability” correspond with the notion of capable guardianship. According to social disorganization theory, residential turnover weakens a community’s social cohesion and therefore its ability to deter and prevent crime within its territory. In this study I use vacancy rates as measure of residential instability. I calculate “vacancy” by dividing the number of vacant housing units within a census tract by the total number of units within that tract. Data for this measure comes from the Census 2010 Redistricting Plan.Another indicator of residential turnover discussed in the criminological literature is the percent of the sample population that is young . The idea is that neighborhoods with a high concentration of young adults will have correspondingly fewer older adults and children, which results in a lack of social cohesion and crime-preventive capacity much in the same way as the other precursors of “social disorganization” already discussed. The variable “percent young” was constructed using ACS population estimates by dividing the total number of individuals between the ages of 18 and 29 by the total tract population.Although they are not of particular theoretical interest, the following measures are included as demographic control variables: population size, percent of the population that is male, and percent of land that is commercially zoned. Population size and gender composition are adapted from the 2010 Census. “Percent of land commercially zoned” was calculated in ArcGIS using zoning shape files provided by the San Francisco Planning Department. Tables 4.1 and 4.2 present descriptive statistics for the measures analyzed in this study. Here the crime data are provided as total counts by category, but in the regression analysis that follows the crime variables are transformed by natural logarithm to address a right-skewed distribution . All other variables are presented as described in the previous section. A total of 189 census tracts within San Francisco are analyzed using data for the year 2010. Five census tracts were removed from analysis because only partial data were available; these were low population tracks with no MCDs and therefore their loss is not analytically significant. Of the tracts analyzed, the average population size is 4,234. The average crime rate is 197.38 property crimes per year . The average violent crime rate is much lower: only 28.65 reported instances per year . According to the results of regression analyses presented in Table 4.3, the current model is better at explaining property crime than it is violent crime. The simplest explanation for this is that substantially more property crimes are committed on a yearly basis than violent crimes, as illustrated by Table 4.1 below on the following page.Descriptive statistics for the independent variables analyzed by this study are also presented in Table 4.2 These include “% Unemployed” and “% Under Poverty” as measures of socioeconomic disadvantage; “% of Housing Units Vacant” and “% of Population Ages 18-29” and measures of residential instability; and “% In Married-Couple Families” as a measure of family stability .

Potential transmission routes of SARS-CoV-2 from animals and animal products are shown in Fig. 2. While SARS-CoV-2 does not cause food borne illness, the virus has caused enormous disruptions to the global food supply chain. The risk of SARS-CoV-2 to food safety was detailed elsewhere . Animal product industries usually rely on the presence of metallic surfaces and the maintenance of low humidity and low temperature . However, these conditions can be favorable for the viability and transmissibility of SARS-CoV-2. While there was a significant reduction and exponential decay in the infectious titer, SARS-CoV-2 remained viable in aerosols for up to 3 h, on plastics for up to 72 h, and on stainless steel for up to 48 h after application . The viability of the virus on different environmental surfaces is shown in Table 1. In addition to rapid work speed and multiple long shifts, food industry workplaces tend to be very crowded with employees in close proximity to one another. Additionally, because of the loud mechanical noise, workers tend to talk louder or shout. These factors can increase the chances of the transmission of SARS-CoV-2 to the co-workers. In many industries, there is a significant number of younger employees. If the manpower in food industry mainly consists of youthful workforce, there can also be a high possibility of having an infected asymptomatic employee who could infect other employees. Infectious bronchitis is an avian disease caused by infectious bronchitis virus, a member of genus Gammacoronavirus in the family Coronaviridae, and is a major respiratory disease of poultry affecting lungs, kidney,drying cannabis and the reproductive tract and causing tremendous economic losses in the poultry industry worldwide . It causes multiple characteristic consequences such as kidney damage, decreased egg production, and deteriorated egg quality .

Another significant problem of infectious bronchitis is its rapid spread. Within 48 h, the whole flock can be infected and remains as a reservoir, even after recovery. The infection usually spreads horizontally from hen to hen, but not from hen to chick. It is still possible that the infection gets transmitted via contaminated eggshells in the hatcheries . Although chickens are not known to be infected with SARS-CoV-2 through the intranasal route, COVID-19 can still have economic negative impacts on the poultry industry . Different poultry species are susceptible to coronaviruses infections leading to the development of enteric diseases, respiratory diseases, and kidney diseases. Examples include turkey infected with Turkey coronavirus , quail infected with Quail coronavirus , guineafowl infected with Guineafowl coronavirus , and pheasant infected with Pheasant coronavirus .Porcine coronaviruses belong to four genera: Alphacoronavirus, Betacoronavirus, Gammacoronavirus, and D . The porcine epizootic diarrhea virus and the transmissible gastroenteritis virus are alphacoronaviruses of swine which infect epithelial cells of the gastrointestinal tract. Another alphacoronavirus named the porcine respiratory coronavirus has no affinity to the gastrointestinal tract. A fourth alphacoronavirus is swine acute diarrhea syndrome coronavirus , which causes acute diarrhea syndrome in piglets. A betacoronavirus is porcine haemagglutinating encephalomyelitis virus , while a deltacoronavirus is porcine deltacoronavirus . Due to similarities in protein characteristics, swine can be potential reservoir for the transmission of SARS-CoV and SARS-CoV-2 . PDCoV is an emerging swine pathogen. Importantly, it was recently detected from three sick Haitian children and is now recognized as a zoonotic pathogen .Coronaviruses of ruminants include bovine coronavirus which infects cattle, sheep, goat, buffalo, llamas, alpacas, and can cause respiratory distress . Examples include bubaline coronavirus that infects water buffalo, alpaca coronavirus that infects alpaca, and dromedary camel coronavirus that infects camels .

In addition, MERS-CoV causes infections in respiratory tracts of camels. The seroprevalence of MERS-CoV in dromedaries was reported to be more than 90% in different countries in Africa, Asia, and the Middle East . There is not enough evidence to suggest that cattle might have play a role in the COVID-19 pandemic. In a study on six animals, only two cattle tested positive for the virus in nasal swabs and showed specific seroconversion, indicating low susceptibility of cattle to SARS-CoV-2 infection . However, close contact of infected humans with large numbers of cattle may still lead to anthropozoonotic infections in cattle . The reason for the low susceptibility to infection is the low expression of ACE2 in the respiratory tracts of these ruminants . The SARS-CoV-2 outbreak in December, 2019 has been linked to Huanan Seafood Market in Wuhan, China . A second wave in June 2020 has been traced to Xinfadi Seafood Market in Beijing, China . Frozen seafood items contaminated with SARS-CoV-2 have been reported in China . Salmon-attached SARS-CoV-2 stayed in a viable status for at least 8 days at 4 ◦C, and 2 days at 25 ◦C . It is noteworthy that at 4 ◦C is the temperature of refrigerators, cold rooms, and transport carriers for storage of fish before selling in the fish or seafood market. Thus, the import and export of frozen and refrigerated fish can be a source of transmission of fish-attached SARS-CoV-2 across countries and continents. Imported frozen cod package surfaces from China showed signs of contamination by SARS-CoV-2 . This calls for strict inspection measures for the detection of SARS-CoV-2 in imported and exported fish during the pandemic . Evidence suggests that cold-storage foods may present a risk for the transmission of SARS-CoV-2 between different countries . Ferrets and cats have been shown to be permissive to infections with SARS-CoV-2 .

Cats were also susceptible to airborne transmission . SARS-CoV-2 infection has also been reported in dogs, tigers, and lions . Other susceptible species include mice, golden hamsters, minks, and non-human primates . Clinical signs in ferrets involved fever and loss of appetite . Both cats and non-human primates were asymptomatic . The main features of animals experimentally infected with SARS-CoV-2 are presented in Table 2. The supply chain of animal feed raw materials has been negatively impacted due to animal movement restrictions resulting from the pandemic-triggered lock downs. Regular patterns of production, supply, and consumption were severely disrupted . Thus, farm animals have been deprived from important feed ingredients in their diets. It has been reported that more than dairy farms have faced shortages of dry feed intake in Pakistan as a result of the pandemic . International cessations in exports and imports of animals’ feeds hampered the supply of several basic raw ingredients that are important for raising and fostering livestock . These raw ingredients include mixtures of carbohydrates, proteins, fats, minerals, and vitamins. As an example, Argentina-the world leader in soybean meal exports – had to reduce its exports of soybean, a critical feed ingredient, by half into feed manufacturing factories . Similarly, Brazil and U.S. have also faced hurdles in their soy meal and corn exports . Local restrictions have been impacted animal feed ingredients, as evidenced by pastoralists in African dry lands who were unable to feed their animals, typically fed on natural plants . International and local restrictions have naturally led to increased costs of animal feed materials, which impacted animal farms in different countries. In Bangladesh, there has been a 3.7% hike in dairy feed price . In India and many regions in Africa, the prices of key animal feed ingredients have increased by 15% as a result of the pandemic . In the United Kingdom, the prices of soy meal, wheat, corns, molasses,curing cannabis and other important animal feed stuffs have increased due to COVID-19 . The COVID-19 pandemic has jolted the livestock production. Pivotal livestock farming materials have been largely unavailable. These include frozen semen aliquoted in a semen straw for artificial insemination of livestock, replacement stocks , equipment , and animal feed additives , 2020. Veterinary healthcare services and other animal health preventative services have been greatly reduced during the pandemic . This caused significant delays in diagnosis and treatment of diseases. The reductions and delays resulted in halting the progress in prevention, control, and eradication of different animal and zoonotic diseases. Since zoonotic disease can also impact humans, the pandemic-triggered disruptions jeopardized human health in addition to animal health.

Furthermore, COVID-19 has negatively impacted food safety inspections, animal health extension services, and disease surveillance efforts which were important checks to prevent the spread of zoonotic diseases and other infections that impact human and animal health . This can create ripe conditions for future outbreaks and pandemics that can be detrimental to livestock health and human health . Amid the COVID-19 situation, markets have been disrupted throughout the world which ultimately affected animal production . The closure of animal markets and restrictions on export and import operations have deprived livestock producers from precious local and global marketing opportunities . In addition, intermediaries who collect animals and animal products and then process or sell them after fattening have been hit hard, which caused farmers to lose their links to major buyers . Thus, there was a sharp decline in animal processing and slaughtering capacities which further added to the turmoil in the livestock market . This has impacted both animals and animal products such as milk, eggs, and meat. Some farmers had to cull their animals or dump their animal products such as milk, which caused them significant income losses. According to the FAO, these losses have been especially severe on women who were unable to obtain the necessary nutrients for their small ruminants and poultry . The wide scale market disruption that resulted from the pandemic has impacted the agricultural workforce and caused staff shortages and layoffs in the labor force associated with animal production . There is a significant proportion of migrant workers in the livestock industry and meat plants . Many of them had to return to their home countries due to the lock downs, closures, and other measures that were implemented during the pandemic . During the peak of the pandemic, China closed livestock and poultry trading and slaughter markets in most of the nation, which results in labor shortage in slaughterhouses . Other causes for labor shortage include childcare, quarantine, and sick leave, which led to a 30% absence rate in some slaughterhouses in France and to similar issues in other countries in Africa and Asia . Owing to these factors and to other factors, the process of bringing animals and animal products to local or global markets faced multiple hurdles. The problem of labor shortage has had significant impacts on countries in South and Southeast Asia. In India, labor shortage has led to 23% food grain production loss . Labor shortage has also led to food insecurity concerns and hunger concerns for daily wage workers in the farm and non-farm sectors in Bangladesh . Food insecurity has also emerged as a major pandemic-related concern in Nepal and other countries . The worldwide demand for meat has been increasing in recent years for many factors including the rapid growth of population in many parts of the world . However, working in slaughterhouses and meat packing plants has been considered a major risk for COVID-19 infection during the pandemic . Workers in meat plants and slaughterhouses in Germany, England, Wales, and Portugal have reportedly been infected with SARS-CoV-2. . The Portugal outbreak led to short-term closure of the poultry slaughterhouse and the implementation of strict hygienic measures including health screening of all employees, adding new bathing areas, and replacing old disinfectants with stronger ones . Previous reports confirmed the presence of rotaviruses and coronaviruses in raw milk and dairy products . MERS-CoV has been shown to survive for prolonged periods in milk . The microbial composition of milk is influenced by the hygienic conditions of the animal, the animal’s feed and water, air quality, environment, and equipment used for milking . To minimize transmission of food borne pathogens, milk and dairy products are subjected to the process of pasteurization . Although some studies suggested that SARS-CoV-2 can spread via food products as it can remain viable on inanimate surfaces for hours to days , there is no proof that SARS-CoV-2 can spread directly through food, milk, milk products, or eggs . However, it is always a good practice to understand the sources of contamination of dairy products and to try to minimize all possible routes of contamination . The COVID-19 pandemic caused global economic losses and significant negative impacts on the agri-food sector, including farming, crop production, and animal production systems .

A particular con- figuration considered in this study is upward flame spread in the flue space between corrugated cardboard, which is typical of warehouse storage arrangements. The model was extended to account for both convective and radiative heat transfer by incorporating convective and radiative heat transfer correlations. This segregated approach effectively uses a non-dimensional parameter to represent the mass transfer processes, the gas phase heat transfer by including an appropriate convective heat transfer correlation, and radiative heat transfer effects that are based on previous studies.Previous studies have attempted to model some of the large-scale effects of warehouse fires by measuring the relevant parameters using bench-scale test methods. One such effort by Hamins and McGrattan constructed single cell replicates of a Group A plastic commodity. The purpose of the Group A plastic tests was to provide input parameters into a computational fluid dynamics model using a measured heat release rate as the thermal loading input for a large-scale warehouse fire. The model predictions were unable to describe the detailed fire growth in storage applications. Several studies have addressed the issue of upward flame spread on corrugated cardboard surfaces. Grant and Drysdale modeled the flame spread along corrugated cardboard during the early growth stages of a warehouse fire by adapting the linearized Satio, Quintiere, and Williams flame spread model with Karlsson’s burnout length and solving numerically. Dimensional parameters that were obtained experimentally were used as inputs to numerically model the flame height, velocity of the flame front, and pyrolysis front progression as a two-dimensional problem. Good agreement between the experimental results and the numerical results were obtained,industrial drying racks although the model was found to be sensitive to averaged input parameters, such as the forward heat flux from the flame.

Alvares et al. studied the effects of panel separation on vertical flame spread and mass-loss rates in small-scale corrugated cardboard tests to determine the rate of fire growth along vertical flues in warehouses. Continued efforts by Ingason and de Ris and Ingason have identified the importance of the commodity configuration, the mode of heat transfer, and the flue spacing of commodity boxes in warehouse fires. Ingason’s work identified some of the dominant factors in the large-scale warehouse fire growth process, and emphasized the importance of separating the material properties of the fuel from the heat transfer and flow conditions that can result due to the various configurations of the fuel packages. Experimental correlations of rack-storage fires are available in previous literature, including heat release rates, boxed in-rack flame heights, in-rack plume temperatures, and heat fluxes. In separating the warehouse fire problem into two distinct phenomena, it then becomes a problem of defining the material properties , flow conditions , and heat transfer . Work performed by de Ris and Orloff [15], de Ris et al. [16], Foley [17], and Foley and Drysdale [18]served to characterize the mode of heat transfer from an upward propagating flame in a warehouse configuration and to quantify the convective and radiative heat transfer that drives the upward flame spread process in the gas phase. Variations in the heat transfer from the small-scale to the largescale was shown by de Ris et al. [16] to be related by similarity effects that are present in buoyant, turbulent boundary layer flows. This result can be used to extend the analytical results that were developed for heat and mass transfer in laminar boundary layers to turbulent boundary layers. In the early stages of a warehouse fire, before the fire sprinklers are activated, the mass transfer is intrinsically coupled to the material properties of the stored commodity, packing material, and outer corrugated cardboard covering. Due to the different burning behavior of each material, which is also a function of the packing and orientation, the problem of classifying a commodity based on its fire hazard is a complex one.

A general approach for describing the heat, mass, and momentum transfer by way of differential equations for simple geometries such as a droplet, flat horizontal, and vertical plate are discussed extensively in previous fire literature.As explained in a recent publication, a number of improved laminar boundary layer types of theories result in formulas that are more complicated than Eq. 3, but the results are qualitatively the same. In larger tests that were previously performed, the fluctuating flames and the incipient turbulence raise questions about the degree of applicability of such theorems. For these reasons, this simple description of the mass transfer, Eq. 3, was chosen in this study over other relevant expressions. In this study, the B-number is primarily a function of the material properties of a given fuel and it is obtained in a controlled experimental environment by assuming that the primary mode of heat transfer at the bench-scale is convection. This assumption is reasonable for the small, laminar flames observed in this study. In examining Eq. 2, the B-number can be considered to be a ratio of the available energy to the energy required to gasify a given fuel . Thus, the B-number is intrinsic to the properties of a material and is therefore independent of a particular scale. This allows for the results from the bench-scale tests to be used as a material input for the prediction of large-scale warehouse fire behavior. Figure 3 shows a schematic of the experimental setup. A total of 9 tests were conducted using two different samples: single-wall corrugated cardboard and polystyrene . The samples measured 5 cm wide by 20 cm in height. This aspect ratio was selected because laminar flames were the primary focus of the bench-scale tests due to the more controllable environment for isolating material properties and separating gas-phase phenomena, and upwardly-spreading flames typically become turbulent above 20 cm, which is accounted for in a later section when large-scale warehouse fires are considered.

For the bench-scale tests, a transition to a turbulent regime was not considered for simplicity, which agreed with visual observations. For this study, the sample width was fixed at 5 cm to minimize the amount of variance between the tests and because a smaller sample size may affect the amount of combustible gases generated by the fuel due to significant diffusion of the fuel to the sides of the sample. The typical mass of the samples was 4 g for corrugated cardboard and 36 g for polystyrene. Corrugated cardboard and polystyrene were chosen to be tested because they are the components of a Group A plastic commodity that is used to represent a worst-case fire scenario in large-scale warehouse tests. Additionally, corrugated cardboard is typically the first item to ignite and sustain flame spread in a warehouse fire. The measured quantities for each test included the mass-loss rate, flame height, and pyrolysis height. The corrugated cardboard used in these tests was identical to the con- figuration and thickness that is used to package standard Group A plastics, and of the same type used in the small-scale tests that were performed by the authors in Part I. The corrugated cardboard samples were of a type ‘C’ flute with a nominal thickness of 4 mm and 135 flutes per meter width [37] as shown in Figure 4. All of the tests were performed with the flutes aligned vertically along the 20 cm dimension,commercial greenhouse benches which is similar to the orientation of the flutes in an upright commodity box. The polystyrene samples were 3 mm thick as shown in Figure 4. The mode of ignition for the tests was a small aluminum tray measuring 5 x 0.5 x 0.5 cm that was placed at the base of the sample and contained a thin strip of glass fiber insulation soaked with n-heptane. This ensured a uniform mode of flaming ignition along the base of the fuel sample. The corrugated cardboard tests used 0.25 mL of n-heptane for ignition, whereas the polystyrene tests used 0.75 mL of n-heptane because it took a longer time for the polystyrene samples to ignite. After initial ignition of the n-heptane, the n-heptane typically burned out within 5-10 seconds and only served to ignite the fuel sample uniformly along the bottom edge. All of the fuel samples were insulated on the back and sides with 0.64 mm thick fiberboard insulation to isolate the burning to the front face of the samples only. The samples were secured in place by the insulating fiberboard sheets that were supported by four metal screws attached to the 1.9 cm thick fiberboard base .

All of the corrugated cardboard tests burned to completion and self-extinguished once the fuel was depleted. The polystyrene samples were manually extinguished after the flame reached a pyrolysis height of about 10 cm due to excessive smoke production and dripping on the bench-scale apparatus. However, the dripping and deformation of the polystyrene was not considered to be significant during the time frame considered in the results because the sample size in the experiment was small, and a significant accumulation of melted polystyrene was not observed during this time period. The mass lost by the specimen was measured continuously using a load cell with an accuracy of ± 0.5 g as specified by the manufacturer. This is approximately 12% of the nominal initial mass of the corrugated cardboard samples and 2% of the nominal initial mass of the polystyrene samples. To measure the flame heights and record the burning history of the tests, video and still images were captured using a Sony Handycam HRR-SR5 model camera and a Canon EOS-5D digital single-lens reflex camera. Figure 5 depicts a visual time history of the vertical flame spread along a corrugated cardboard sample. The images were then loaded onto a computer, and a MATLAB image processing script was used to visually determine the flame heights as a function of time from each test. The flame height was defined as the tip of an attached yellow flame and was selected visually from each picture by using the script. The processed images and resulting flame heights were consistent with visual comparisons from the test videos. Similar to the flame heights, observations of the visual charring on the corrugated cardboard was used to determine the location of the pyrolysis front. For the polystyrene samples, visual bubbling and charring from the video were used to determine the location of the pyrolysis front. The corrugated cardboard and polystyrene tests were fairly repeatable, and the heights of the pyrolysis front in the laminar regime were fairly similar; thus, a best-fit functional approximation of the pyrolysis heights was made. This approximation was later used to determine an average mass-loss rate per unit area , and finally, a B-number was calculated for each test. After the maximum pyrolysis height was reached, a constant height of 20 cm or 10 cm was assumed, which represents the entire surface of the front face of the sample. The results described in this section are based on a total of 9 bench scale tests that were performed using the two samples that were discussed in Section 3. After ignition along the base of the samples, the flame spread in the upward direction along the fuel samples. Due to edge effects along the fuel sample, a small amount of two-dimensional flame spread occurred in the experiment. As the excess pyrolyzate burned above the pyrolysis zone, the unburned fuel above the pyrolysis zone was heated to its ignition temperature and the flame spread in the upward direction at an increasing rate. As described in Section 3, the mass-loss rates were trimmed to the time period during upward flame spread along the samples. During the period of upward flame spread, the average value of ˙m00f for corrugated cardboard was within a range of 7.3 − 7.9 · 10−4 g/cm2 –s, and for polystyrene was within a range of 6.7−6.8·10−4 g/cm2 –s. Figures 6 & 6 show the flame heights that were measured in the bench-scale experiments for corrugated cardboard and polystyrene and the least-squares fit to the pyrolysis height that was used to determine the area burning, and later the average B-numbers for the corrugated cardboard and polystyrene samples. Using an average value from all of the tests that were performed on a given material sample, the B-number for corrugated cardboard was calculated to be 1.7 and for polystyrene was calculated as 1.4 .

To see how the risk characterization might change if different thresholds were selected, a comparison with the ODTC50 ranges from AIHA and the RELs from California was conducted . In the states that have legalized cannabis use medicinally and by adults, the cultivation in warehouses has led to nuisance odor complaints. The grow cycle includes a budding stage with “skunk” odor notes. Most cultivation warehouses stagger the growth cycles, so budding is an ongoing occurrence. As a best practice, exhaust ventilation is passed through an activated carbon filter; however, the efficiency is typically 50-98% , so odorous compounds are still emitted. Colorado has required odor management plans certified by an industrial hygienist to ensure best practices are implemented. In 2003, California was the first state to allow medicinal cannabis use . In 2018, cultivation for adult use became legal . Today, regions throughout the state – such as Sonoma County, Sacramento County and Greater Palm Springs – are managing the side-by-side growth of the indoor-cultivation industry and nearby residences. The first study to report Odor Activity Values for odorants emitted from cannabis identified a list of over 20 substances, which were different than those traditionally associated with cannabis odor . OAVs could only be calculated for those odorants that had existing ODTC50 values in the literature. Samples were not living cannabis plants, but rather fresh, old and desiccated cannabis, and some monitoring was outside storage bags to simulate a person being pulled over by police while transporting cannabis. The most odorous compounds based on OAVs are listed in Table 4.8 and provide a starting point for future odor research.

There are substantial uncertainties in the risk assessment of odorants,greenhouse bench top the greatest being how likely it is that the individual odorants monitored actually are the main contributors to the overall odor sensed. Missing the key odorants invalidates the study. OPM can help identify key odorants that have been compiled into odor wheels . The exposure measurements tend to have less uncertainty than the thresholds against which they are evaluated. ODTC50 values typically range over several orders of magnitude, and the health hazard thresholds incorporate one-to-three orders of magnitude of uncertainty factors in their extrapolation from animal data. Even under controlled conditions using test odorants, panelist threshold testing by dilutions resulted in inter laboratory variation in results up to 4-fold . Accordingly, most risk characterizations are crude, screening-level evaluations that require further refinement if thresholds are approached by exposure estimates. For the experimental and epidemiology studies, all suffer from the problem of self reporting and the inherent variability in human response, which clearly varies by sex, age, pre-existing health conditions and prior experiences. Epidemiological studies of odor and health have notably weak exposure assessments, and experimental studies suffer the lack of standardized exposure methods and difficulty carrying out blinded studies . So far, no toxicological study has been able to separate the health effects of odors from those of the co-pollutants in the mixture . The health effects reported by residents living near odor sources may be due to odorless co-pollutants with odor serving as a marker of exposure . Few epidemiology studies, however, look at this possibility. Proximity to an odor source would be a determinant; however, residence distance to the source was often a poor predictor of odor induced health complaints. The sole experimental study of odor , which was discussed in Section 4.3, could not separate the effects of odors from those of co-pollutants in the mixture. Risk perception plays a large role in how exposures to odors can lead to annoyance and outrage. Risk perception has been defined as how the exposed judge the severity of the risk and involves personal and cultural values and attitudes.

Different perceptions of risk are applied to involuntary, imposed exposures, man-made sources and the unfamiliar. Odors often encompass all three of these factors. Key worries from odor exposures include long-term health ailments such as asthma or lung cancer , ability to socialize at one’s own property that is odor impacted, and potential decrease in property value . These perceived risks likely are experienced disproportionately by disadvantaged communities. The air monitoring of the community north of Denver was funded by USEPA as an environmental justice study , and a community well-being study followed shortly thereafter . Participants took an online survey four times over a year. The results at the community level showed that odor-impacted communities had no difference in well-being than the control communities. Individual results, however, showed that respondents who reported that the air was “very fresh” or “odor is highly acceptable” had higher levels of well-being. This finding supports other studies that indicate that unpleasant odors lead to annoyance, general psychological stress, and reduced quality of life. Researchers in Australia studied environmental justice and odors around Melbourne . They used a novel cluster approach to represent communities affected by odor and concluded that self-reported odor exposure correlated with indicators of socio economic disadvantage in the community clusters affected by odor.Large gaps exist in the dataset used to evaluate the health risks posed by odors. Chief among these is the lack of dose-response studies for total odor exposure rather than just for individual odorants. Only a single experimental study of odor mixture exposure and health effects has been conducted . Clearly, more studies are needed, especially measuring physiological and psychological responses simultaneously so correlations can be determined. Longitudinal “before-and-after” epidemiology studies are needed to determine the magnitude of impact of installing an odor-emitting facility near a neighborhood.

For example, the large health-effects study in California after the natural gas leak in Aliso Canyon would benefit from pre-leak community health data. To aid exposure assessment, analytical techniques and sampling require improvement. For one set of odorants – additives to natural gas to impart odor – broad availability of laboratories with the capability to measure sulfur compounds at sufficiently low detection limits is both a health and a safety need . Both short- and long-term health-effect studies of these natural gas additives are also needed. Self-reporting of health symptoms, which is subjective, needs to be replaced with objective measure to make scientific progress in odor risk assessment. Odors add a substantial layer of complexity to traditional human health risk assessment. First, they lead to two types of sensory responses – irritation and smell – that are entwined. Together or separately, these senses, when overwhelmed, can lead to either transitory or more permanent health effects. In addition, odorless co-pollutants can contribute to adverse effects, and their contribution is difficult to separate from that of the odor. Odors are typically mixtures of individual odorants and other airborne compounds, and both odor assessment and conventional risk assessment more easily assess single compounds rather than mixtures. The variability in human responses to odors adds a large degree of uncertainty to any assessment. As with the human health thresholds derived through dose-response bench marking and extrapolation,botanicare rolling benches the odor detection thresholds often have several orders of magnitude of variability between studies and panels. Odor characteristics and the individual’s past experience with the odor, sex, age, culture, mood, personality and health status all influence odor perception. Risk characterizations that use such thresholds are crude at best, and a portion of the population will continue to sense the odor even below the threshold. Several case studies demonstrate that odor thresholds and health thresholds can be applied to odorant exposures to estimate sensory and health effects. How well this odorant-by odorant approach addresses the health risks to communities is an area in need of further research and objective methods. Although there is a general sentiment that marijuana decriminalization has no effect on demand, the more careful evaluations conducted on samples from the United States and Australia have inconclusive findings. For example, studies of decriminalization in South Australia and in the Australian Capital Territory report no changes in marijuana use associated with this legal change, and no differences in marijuana use between these regions and non-decriminalization regions of Australia. However, two recent studies using individual level data from the National Drug Strategy Household Surveys do find a positive effect of decriminalization . In theory, any deterrent effect of levels of marijuana sanctioning should be mediated by citizens’ perceptions of their certainty and severity.Various lines of evidence suggest that citizens may have distorted or biased beliefs about sanctioning threats . Thus, a possible explanation for the inconsistency in decriminalization effects in the literature is that citizens’ perceptions may not vary in accordance with differences in law or enforcement. To address this question we examined data on knowledge of U.S. state laws from the 2001 National Survey on Drug Use and Health . The NSDUH is an annual national household survey of the non-institutionalized U.S. population 12 years and older conducted by the Substance Abuse and Mental Health Administration . It is the primary source of information on the prevalence of use of illegal drugs for the U.S. population.

Since 1999, approximately 70,000 individuals have been interviewed each year across the United States with at least 900 respondents in each of the 50 states. Great care is taken to ensure that information on illicit drug use is accurately reported. For example, the questions on illicit drug use are self-administered through a computer assisted interview survey, no names are used or collected during the interview, and interviews are conducted in private settings away from other people in the household.In 2001, the NSDUH included questions for the first time pertaining to the individual’s knowledge of state marijuana laws. All individuals taking the survey were asked, “What is the maximum legal penalty in for first offense possession of an ounce or less of marijuana for your own use?” Possible responses were a fine, probation, community service, possible prison sentence, mandatory prison sentence, and Don’t know. Information on the weighted fraction of the state sample reporting specific penalties were aggregated to the state level and made available to us by the Office of Applied Studies at the Substance Abuse and Mental Health Services Administration . To these state aggregated data we merged information on each state’s statutory penalties associated with possession of one ounce of marijuana for first time offenders.The penalties represent laws in effect as of January 1, 2001, and were collected and analyzed by a team of lawyers and policy analysts at the MayaTech Corporation. Penalties that were captured include the minimum and maximum jail term, minimum and maximum fine, conditional discharge provisions, and expungement provisions for the lowest two quantity trigger amounts, which capture amounts of one ounce or less for all states.The conditional discharge variable reflects instances where compliance with the specified conditions leads to a dismissal of charges. The first column of Table 2 presents the fraction of the state population reporting a particular maximum penalty across all states, regardless of the state’s actual penalties. On average we see that nearly one-third of the population do not know what the maximum penalty is for marijuana possession offences in their state and another third believe that possible or mandatory jail is the maximum offence. What is particularly surprising is the result that 6% of the population reports that mandatory jail is the maximum offence for possession of an ounce of marijuana. This is surprising because no U.S. state requires a mandatory jail time for marijuana possession offences. To evaluate whether individuals understood the maximum penalty for possession of marijuana in their state, we differentiated states based on their statutory provision of jail sentences. We first separated states based on whether they were recognized in the literature as having a decriminalization policy or not . Although we showed in Table 1 that these policies do not reflect actual differences in the criminal status of marijuana offences, it may be the case that the mere label that has been applied to these states for the past 25 years might generate a greater awareness of the state’s actual penalties for those living within these states. If people living in decriminalized states were actually aware of this labeled policy , then we would expect that they would be less likely to report jail as the maximum penalty and more likely to report fines, probation, or community service as the maximum penalty than people living in non-decrim states.

The panel is held in an air conditioned room with no scents or in the field at the location of the odor. Panelists are trained to distinguish odor mixtures and the intensity of each odorant. Panelists are presented with mixtures of 2, 3, and 4 standard odorants and are asked to identify the odor characteristics and the intensity of each odorant. Panelists are then ready to analyze actual environmental odor samples.Before panelists are exposed to samples, a safety evaluation determines that the odorant concentrations are below safety thresholds . Samples are presented in bags and smelled by panelists, who then write down the odor notes and odor intensities. The leader then leads a discussion, and panelists may alter their decisions. Breaks are taken to avoid odor fatigue or health symptoms . The first challenge with OPM is that it usually requires confirmation by GC-sensory analysis to identify the odorant . The second challenge is that OPM usually operates outside the range of its calibration. The calibrated intensity scores are in the range 4 to 12, yet individual panelist scores – as well as the overall geometric mean – are usually in the 1 to 3 range. Such below-range extrapolations are not allowed in sound analytics. Data sets from analytical chemistry instruments have the same challenge and the temptation to extrapolate lower than the method detection limit. A concern is that there is no evidence that OPM is reproducible across panels . The group discussion may lead to the dominant person biasing others despite instructions to conduct independent evaluations . Substantial training is required. A similar approach to OPM is used in dentistry research for mouth odor .

The scale is 0 to 5 ,cannabis drying racks commercial and extrapolations to 0 are used to predict the ODTC50. This approach has led to good agreement with ODTC50 values from the literature. Another odor-intensity measurement system is used more widely than OPM. ASTM Standard E544 uses various vials with dilutions of n-butanol in water to assign n-butanol-equivalent concentrations to the intensity of a given sample. The upper limit of this equivalency scale appears to be the saturation limit of n-butanol in water rather than a sensory upper limit. The intensity of the odor sample is expressed in mg/L of n-butanol, with a larger value of indicating a stronger odorant. Whole-sample, undiluted total odor analysis is relatively straightforward. Determining the odor notes can lead to indications of the source and even a subset of the individual odorants. An odor-intensity rating of the overall mixture, however, is more controversial and less useful. Duration information can be added to a decision-making matrix, too. For example, a field panel made observations using OPM at three off-site and four on-site locations at a trash transfer station .As an odor mixture is diluted, the odor notes and hedonic tones change and eventually, after sufficient dilution, the concentration of the final detectable odorant drops below its odor detection threshold so the diluted sample becomes “odorless” . The amount of dilution required to reach this point is considered an indicator of the odor intensity of the initial, undiluted sample, which is problematic because the final detectable odorant may not be indicative of the odorant that dominated the odor of the undiluted sample . Relying on dilution quantities to indicate the intensity of the total odor is crude at best and misleading at worst. Further, presenting a dilution quantity as a measure related to the mass of odorants in the undiluted sample, when in reality it measures only the final detectable odorant, adds an unknown amount of uncertainty to such claims.

For a single odorant in isolation, dilution-to-threshold tests are more straightforward. Although the odor note and hedonic tone of the odorant change as concentration changes, sometimes flipping from unpleasant to pleasant, the interactions with other odorants are not factors. Complaints about single odorants are typically limited to the chemical and petroleum industries, however. Research on single odorants is used to tease apart the underpinnings of total odor in mixtures . Dilution of field samples can mimic the dilution that occurs from source to fenceline. Figure 3.5 includes the “unmasking” of musty odor note that was initially covered up by a more dominant fecal and sulfur odor notes at a WWTP . On-site workers would experience the fecal and sulfur odors, while nearby residents complained of musty odors.Portable dilution instruments can be used by field investigators . In the United States, such instruments include the Nasal Ranger® and Scentroid SM100 . Both mix the ambient air being sampled with odorless air at variable ratios. The ratio at which the odor disappears is defined as the dilution-to-threshold ratio. This term tends to be reserved for field measurements, while OU tends be reserved for indoor panels. Both are dilution levels and not mass-based concentrations. A mixture of odorants was tested using both devices . The Nasal Ranger®, which has settings from 2 to 60 dilutions, performed well between 3 and 30 dilutions. For the Scentroid SM100, which has set points from 3 to 101 dilutions, the settings were about half what the test actually showed, possibly due to odorant sorption to internal surfaces. Field dilution devices avoid the need for sample collection, storage and transport. They may have sorption issues, however, and appear to be better suited for low odor concentrations.Field odor measurements may also involve a panel, such as the use of OPM at an impacted school near a landfill site in California , a trash transfer station in California and a landfill in France .

For the landfill study , an abbreviated version of the grid and plume methods discussed next were applied on a single day as well as OPM. The dominant odor notes were “rotten vegetable” and “rancid,” which had high or medium odor intensities. According to the landfill odor wheel, the associated odorants were fatty acids and sulfur compounds , which have very low odor thresholds. Confirmation of odorants by GC-MS-sensory was not performed. In Europe, field panels are central to the grid and plume methods . Figure 3.6 includes general guidance for such a field panel, Figure 3.7 shows how the grid method is applied, and Figure 3.8 shows how the plume method is applied. Both methods require trained panelists to decide whether they recognize an odor note selected from a list. The grid method is applied over a sufficiently long period of time to provide a representative map of the exposure of the population to recognizable odors. Field panelists write down their observations every 10 seconds for 10 minutes . If 6 of those observations are a recognized odor note, then the label “odor hour” is applied . The plume method is used to determine the area in which an odor plume can be perceived under specific meteorological conditions. The odor-plume boundary is where the odor no longer is detectable, and panelists mark yes/no on a map as they walk through and out of the plume. Adding OPM to the grid or plume method provides an intensity scale and can indicate suspected odorants from odor wheels .To confirm and support the sensory analysis of environmental odor exposures, traditional analytical chemistry air monitoring methods are used. A substantial review of analytical and sensory methods for odor measurement was conducted previously . The methods that have advanced since then are the focus of this section . The other methods are covered briefly for completeness. The comparative advantages and disadvantages of these methods are discussed in Section 4.4. Chemical analysis is most appropriate in cases where known single odorants are responsible for an odor,vertical grow racks as opposed to diverse mixtures of odorants. The list of odorous compounds that may be measured is virtually endless. For example, over 400 odorants were detected from swine facilities . Although the level of each odorant was low, the overall mixture led to extremely strong odor intensities. In this case and others, sensory measurements lead to better estimates of odor intensity than analytical measurements. Analytical measurements are only performed for risk assessment when method detection limits are sufficiently low to be below the hazard benchmarks of concern. To achieve such, the human nose is typically required for odor assessment. Although the identification and quantification of specific odorants does not directly indicate the potential odor nuisance, the information is useful for identifying and tracking odor sources . Further, it can help indicate the reactions leading to odorant formation, especially microbial reactions at WWTPs, landfills and composting sites.Gas chromatography, which separates and quantifies odorants, is useful for complex mixtures of chemicals at trace levels, especially on-site where concentrations are higher. Recent advances include two-dimensional and multidimensional gas chromatography , which decrease the analytical problems associated with peak overlap. Both aid in odorant identification. Although detection reaches ppb levels , trace odorants still go undetected, as do odorants that are unstable during sample collection and transport . Identification of unknown peaks from gas chromatography is typically by mass spectrometry and its libraries of thousands of known compounds. However, even knowing the identity of an odorant does not tell how it contributes to the overall odor of a mixture. Such instruments are expensive, as is there operation and maintenance.

A new, albeit even more expensive, instrument has been used for odor investigations called “selected ion flow tube mass spectrometry” . It is transportable and can detect and quantify the concentrations of 20 to 50 odorants real-time, even if the levels are changing rapidly. The SIFT-MS instrument directly measures components of the air by first using chemical ionizing agents on the sample followed by mass spectrometry . The chemical ionizing agents include cations and anions . The analyte concentration is found from the ratio of the product ion counts to the reagent ion counts, the flow rate, and instrument calibration. Low-ppb detection has been achieved.Gas chromatography with a sensory port , often performed in tandem with mass spectrometry , is a hybrid technique that brings together the separation of odorants and the sensitivity of the human nose. The sensory port allows the analyst to smell the eluting compounds at the same time the instrument detector makes a reading. When successful, it can indicate which odorants contribute to the total odor. Recent advances in GC-sensory methods include improved GC-port interfaces, increasing the number of simultaneous panelists , bi-dimensional GC techniques and sophisticated data processing . Disease detection is an emerging use of GC-sensory.Gas-specific sensors can target key odorants but not the total odor. They are often portable, relatively inexpensive, and continuously log data. The most common gas-specific sensors are for hydrogen sulfide and ammonia. Detection is through chemical, electrochemical, catalytic or optical signals. Some can reach ppb levels. Hydrogen sulfide, however, does not account for the entire odor nuisance. At WWTPs, hydrogen sulfide levels can be well controlledand monitored continuously, yet nuisance odor complaints persist . Benzene, a carcinogen, is a problem emitted from oil refineries and gasoline stations, as well as from the semiconductor industry. Advanced sensors using metal-oxide detectors have been developed that can work in various levels of humidity and interferants .Improved sensor technologies and advanced computational techniques have merged to produce non-specific gas-sensor arrays that try to mimic the human sense of smell. Often called an “electronic nose” or “e-nose,” a bank of up to 30 sensors generates a complex electronic signal that is processed through computer algorithms. The result is a reading – but not a true “fingerprint” – for a known odor that then can be compared to signals from future samples to see if they match. When properly calibrated, e-noses should continuously detect the presence of odors in ambient air, estimate concentrations of odors, and attribute the odor to a specific odor source . The sensors are typically a variety of metal oxides, conducting polymers and oscillating quartz crystals; however, new sensor materials are under development continually. As with all sensors, they are subject to the effects of temperature and humidity, degradation, poisoning and the need for frequent re-calibration to address drift. It is difficult to find e-noses used outside of research laboratories , which confirmed the observation by Muñoz et al. that their initial promotion had been overly optimistic. Nonetheless, e-noses developed within laboratories, plus accompanying field tests, have led to numerous publications and several recent reviews of the emerging field. Under controlled situations, e-noses have monitored odors.

PKS gene constructs were transformed into E. coli BL21-. For protein isolation, cultures were grown to an OD of approximately 0.6 at 37 C when transcription of the cDNA inserts was induced with IPTG and cultures were grown for an additional 10–12 h at 28  C. His-tagged protein was isolated from the bacteria using the MagneHis Protein Purification System . PKS enzyme assays contained 4 lg protein, 100 mM KPO4 , 5 mM malonyl-CoA, and either 250 lM hexanoyl-CoA or 67.5 lM 4-coumaroyl-CoA as substrates. Boiled protein was assayed in parallel with all reactions. All negative controls showed a lack of product formation. Reactions were incubated for 1 h at 30  C, dried in a Speed Vac, resuspended in 40 ll methanol, and applied to Agilent Tech 1200 HPLC with a Spherisorb 6 l ODS2 separation column. Products and reactants were resolved across a gradient of 1% H3PO4 to 100% acetonitrile with molecular weights determined by LC-MS.Quantitative reactions were performed as described previously using primers listed in Supplementary Table 4B at JXB online. Equivalent quantities of RNA isolated from glands and inflorescence associated leaves were used to generate the respective single stranded cDNAs. qPCR reactions containing equal quantities of gland or leaf cDNA were run in duplicate along with reactions containing standards consisting of 100-fold sequential dilutions of isolated target fragments, on a Lightcyler qPCR machine . Lightcycler software was used to generate standard curves covering a range of 106 to which gland and leaf data were compared. Two biological replicates were used to generate the means and standard deviations shown in Supplementary Table 4A at JXB online. These values were used to compute the gland over leaf ratios and P-values shown in Supplementary Table 4A at JXB online.

Raw relative expression data, means, standard deviations, P-values from gland versus leaf t tests, qPCR primer sequences,clone rack and representative real-time qPCR tracings are shown in Supplementary Table 4A at JXB online.Anatomical study revealed that glands located on mature floral bracts of female plants are the site of enhanced secondary metabolism leading to the production of THCA and other compounds in Cannabis sativa . These glands are located on multicellular stalks and typically are composed of eight cells . The outer gland surface is composed of a smooth capsule covered by a membrane. The capsule contains exudates derived from the gland cells . The weakly attached glands can easily be separated from the bracts and purified as shown in Fig. 1E and F. An EST library was constructed using RNA isolated from purified glands. Over 100 000 ESTs were cloned. Plasmid DNA was isolated and sequenced from over 2000 clones. Because of the directed orientation of cDNA insertion, sequences are expected to represent the coding strand. After the removal of vectoronly, poor quality sequences, and sequences obviously originating from organelles or ribosomal RNA, the remaining sequences were clustered into 1075 unigenes . Overall, 111 of the unigenes were contigs containing two or more closely related ESTs . Only 14 contigs lacked a similar sequence in the NCBI database. Nine hundred and sixty four of the ESTs were only found once and of these 710 were similar to sequences in the NCBI database . The top three unigenes representing the greatest number of ESTs encoded proteins related to metallothionein, RD22-like BURP domain-containing proteins, and chitin binding hevein-like proteins . All three of these proteins have functions related to biotic or abiotic stress responses . Gene Ontology analysis was performed on the sequence dataset . An analysis of biological function indicates that 27% of the unigenes encode proteins with metabolic activity.

Unigenes with NCBI matches encoding proteins with unknown function comprise 14% of the total and another 28% are predicted to be involved in various cellular processes such as protein synthesis and protein degradation.The specific biochemical steps leading to THCA are proposed to begin with a reaction involving a type III PKS enzyme that catalyses the synthesis of olivetolic acid from hexanoyl-CoA and three molecules of malonyl-CoA . Malonyl-CoA is derived from the carboxylation of acetyl-CoA. ESTs encoding acetyl-CoA carboxylase were identified. Hexanoyl-CoA could be produced by more than one pathway in the trichomes. One route to produce hexanoyl-CoA would involve the early termination of the fatty acid biosynthetic pathway, yielding hexanoyl-ACP . The hexanoyl moiety would then be transferred to CoA by the action of an ACP-CoA transacylase or it would be cleaved by the action of a thioesterase, yielding n-hexanol, which would then be converted into n-hexanoyl-CoA by the action of acyl-CoA synthase. Most of the enzymes needed for this route are represented in the EST database, except for thetransacylase and 2,3-trans-enoyl-ACP reductase . A second route to hexanoyl-CoA would involve the production of hexanol from the breakdown of the fatty acid linoleic acid via the lipoxygenase pathway . A survey of the sequenced ESTs revealed candidate genes encoding the enzymes needed to synthesize linoleic acid from acetyl-CoA by the typical fatty acid biosynthetic pathway in plastids followed by the production of hexanol from linoleic acid via the LOX pathway. An third pathway related to the biosynthesis of branched chain amino acids has been proposed to be involved in the production of short-chain and medium-chain fatty acids . However, the enzymes in this pathway [2-isopropylmalate synthase, 3-isopropylmalate dehydratase, 3-isopropylmalate dehydrogenase, and 2- oxoisovalerate dehydrogenase ] were not represented in the Cannabis trichome EST library.

After the formation of olivetolic acid, a prenyltransferase is proposed to add a prenyl group derived from geranyl diphosphate to create cannabigerolic acid. GPP is derived from the fusion of two isoprene units . Two different biochemical pathways support the synthesis of isoprenoids in plants . Within the list of unigenes all but one of the enzymatic activities needed to convert pyruvate and glyceraldehyde-3-phosphate into isopentenyl and dimethylallyl diphosphate via the methylerythritol 4-phosphate pathway were represented . This finding is consistent with isotopic studies showing that the GPP cannabinoid precursors are synthesized via this pathway . The formation of GPP is mediated by GPP synthase. Several unigenes related to GPP synthase were identified , however, they were more closely related to other terpene synthases. In particular, CAN36 and CAN55, which possibly were derived from the same gene, and the closely related CAN37, are most similar to hop sesquiterpene synthases HISTS1 and HISTS2 , with an average identity of 56% over the first 160 amino acid residues . CAN41 is most similar to hop monoterpene synthase HIMTS2 .The nature of the prenyltransferase is unknown. However, previous studies identified a soluble aromatic geranylpyrophosphate:olivetolate geranyltransferase in the extract of young leaves with the appropriate activity . The only EST encoding a predicted prenyltransferase was CAN121. However, the encoded protein is more closely related to members of the membrane-bound chloroplast-localized family of prenyltransferases than to soluble prenyltransferases . The final step in the pathway is mediated by THCA synthase, which mediates the conversion of cannabigerolic acid to THCA . Two ESTs with sequences identical to the previous reportedly THCA synthase were identified .Whereas the nature of the prenyltransferase responsible for the synthesis of cannabigerolic acid is unknown, three unigenes, CAN24, CAN383, and CAN1069, comprising eight, one, and two ESTs, respectively, could encode the PKS activity needed to synthesize olivetolic acid. These were therefore characterized in more detail. All three unigenes were represented by individual ESTs encoding complete PKS polypetides. These were sequenced and compared to related PKS sequences . CAN1069 was identical to a previously identified Cannabis gene encoding a chalcone synthase, and is the most closely related of the PKS sequences to other known chalcone synthases from hop and Arabidopsis . The relationships of hop phlorisovalerophenone synthase , which mediates the conversion of malonyl-CoA and isovaleryl-CoA to phlorisovalerophenone, to CAN24 and CAN383 is less clear . CAN24 and CAN383 show 64.6% identity and are nearly equally similar to hop VPS at 71.2% and 72.0%, respectively. The enzymatic activities encoded by CAN24 and CAN1069 were explored in detail. The coding regions of the two genes were inserted into the pHis8 vector in frame with a His8 tag. The tagged proteins were purified on a nickel-containing magnetic bead matrix and were assayed for chalcone and olivetol/olivetolic acid synthase activities . Recombinant protein from CAN1069, but not CAN24,hydroponic shelves produced reaction products when incubated with coumaroyl-CoA and malonyl-CoA . The reaction products were analysed by LC-MS and peak 2 was found to have a molecular mass and absorption spectrum consistent with naringenin , the major product of chalcone synthases. Both CAN24 and CAN1069 were capable of using malonyl-CoA and hexanoyl-CoA as reaction substrates and LC-MS indicated that products of these enzymes were the same, but neither molecular mass nor the absorption spectrum of this product matched olivetol or olivetolic acid . Results similar to CAN24 were obtained using protein purified from CAN383 .

Genes required for THCA production are probably more highly expressed in glands of pistillate inflorescences because this is where THCA is most highly concentrated. To test this hypothesis, the relative expression levels in isolated glands versus young inflorescence-associated leaves of selected unigenes were compared using real-time qPCR. The identity of the genes assayed and the differences in relative expression levels are listed in Table 2 and in Supplementary Table 4A at JXB online. Consistent with this hypothesis, THCA synthase expression was 437 times higher in isolated glands than in leaves. CAN24 was expressed 1600 times higher in glands of the inflorescence than in associated leaves. CAN1069 encoding CHS was also more highly expressed in glands than leaves . The expression of a third PKS, CAN383, was expressed at similar levels in glands and leaves . These results are not explained by poorRNA isolation from leaves as unigene CAN219 encoding chlorophyll A/B binding protein showed elevated leaf expression levels . The activities of several housekeeping genes were also tested. A relatively modest increase in levels of histone H2A and beta tubulin expression in glands compared to leaves was detected. The increase in expression levels of these latter two genes might reflect a combination of the heightened metabolic activity and the unique cellular structure of glandular trichomes. Two different pathways could provide the hexanol required for olivetolic acid synthesis, as shown in Fig. 2. Expression levels provide support for the de novo pathway as a primary source, given that CAN498, CAN82, and CAN915 were much more highly expressed in glands than leaves , whereas the relative expression of genes encoding enzymes in the lipid breakdown pathway were depressed or modestly elevated in glands.Eighty Cannabis unigenes were similar to transcription factors found in Arabidopsis and 11 contain MYB DNA binding domains . Expression of four MYB genes in isolated glands and leaves was compared by real-time qPCR . CAN833 and CAN738 exhibited 954-fold and 586-fold higher expression in glands, respectively, whereas CAN483 and 792 showed more modest induction in glands. None of the other putative transcription factors that were assayed showed the same degree of differential expression as CAN833 and CAN738 .The identities of the most abundant ESTs derived from the glandular trichomes of Cannabis sativa are consistent with the protective function of plant glands. For example, themost abundant ESTs encoded a protein closely related to type II metallothioneins. These proteins bind heavy metals such as Cd, Zn, and Cu, and their proposed primary function is the maintenance of Cu tolerance . The second most abundant class of ESTs encoded an RD22-like BURP domain containing protein. This class of proteins contains a hydrophobic Nterminal signal peptide, and an N-terminal conserved region followed by a series of small repeats . The BURP domain of approximately 230 amino acids is located in the C-terminal region. The function of RD22-like proteins is unknown but some members of this class of genes are induced by dehydration . The third most abundant ESTs encoded a protein containing a hevein domain. Hevein domains contain a conserved 43-amino acid motif that binds chitin and members of this protein class are known for anti-fungal activity . The unique secondary metabolism in Cannabis may also play a role in plant defence. Synthesis of THCA is extracellular and results in hydrogen peroxide production, which has general antimicrobial properties , and a recent report further indicates that THCA may directly inhibit microbial growth . The analysis of gland-derived ESTs has identified nearly all the candidate genes required for THCA synthesis from primary metabolic products.

Wind direction, speed and temperature are measured using a hand-held Kestrel 1000 meter, and the cloudiness and weather are noted. More sophistical meteorological data has been used to calculate the back-trajectory of odor plumes using data from the National Weather Service in MesoWest plus the HYSPLIT dispersion model. Odor investigation data is captured in an in-house database that is rather old and does not allow for easy queries. Since 2010, the number of odor complaints per year has risen from around 3,400 to 7,500, decreasing in 2017 to 6,000 . Odor complaints are received by phone or via their website, which is also available through their app.No electronic nose technology is currently used although a report surveyed dozens of emerging technologies . The authors noted that e-noses were primarily used for quality control for food and other products, and that a large effort would be required for field tests for environmental odor detection. Two major case studies from SCAQMD are informative. The first case is metallic odors in the industrialized section of the City of Paramount that began in 2013 . Nickel and hexavalent chromium were detected in air samples. Three businesses with metal-related operations were identified and many community meetings were held to address both odor and air toxics concerns. Under an Order for Abatement, one company was required to take measures to reduce odors in July 2017. They improved air pollution controls in their grinding room and made other improvements, and the number of odor complaints decreased. The second case is the coastal area of Seal Beach, Huntington Beach, and Long Beach that experienced “gas/sulfur/chemical” odors . To help find the allusive source, sampling was performed between March 2017 and October 2018 in partnership with local fire departments. SUMMA canisters were analyzed for the presence of volatile organic compounds,vertical farming equipment suppliers and samples collected in Tedlar™ bags were analyzed for total reduced sulfur compounds.

Crude oil was the likely source of the compounds detected, and in October 2018 a violation was issued to an oil tanker that, upon inspection, had 7 out of 10 pressure release devices leaking . Portable hydrocarbon-sensing devices and gas imaging cameras were used to detect the leaks. Monitoring for other sources using a forward-looking infrared camera and further sample collection are ongoing. To address the beach communities’ health concerns from the intermittent exposures, and to put the monitoring data into context, a “frequently asked questions” document was created . The conclusions were that the levels of hydrogen sulfide were below the 30 ppb one-hour state standard, the levels of specific hydrocarbons were below their acute limits, and that cancer risk was not at a level of concern due to the intermittent nature of the exposures.The Bay Area Air Quality Management District , headquartered in San Francisco, sets an odor limit of 5 dilutions-to-threshold at or beyond the facility fenceline, which is applied after at least 10 complaints are received within a 90-day period . Further investigation is required if a further 5 complaints are received within the next 90 days. Interviews with staff provided recent information and insights into investigation techniques currently used. Although still found in their local regulations, the use of odor panels to evaluate samples captured in bags ended over five years ago. The primary concern was that employees, who served as the panelists, were worried about exposures to unknown compounds and experienced negative sensations. Using air monitoring results for specific odorants and comparing the concentrations to odor detection threshold concentration was considered not in line with odor being a sensory nuisance . Lacking any quantifiable sensory method, air inspectors now conduct source-by-source investigations using their own sense of smell with moderate success. An inspection is triggered when 5 or more independent complaints are received and can result in a Violation Notice. Although their “Odor Policies and Procedures” is currently being revised, BAAQMD has several experiences worth sharing.

When an odor complaint is received during office hours, within 15 minutes it is assigned to an air inspector who has 30 minutes to contact the complainant. They then meet, experience the smell together and walk toward the source together. No sensory descriptors or training are used. They also explore upwind. If the odor is verified, the source is contacted and, if needed, inspected to see if in violation of the permit. Prior attempts to use field olfactometry offered no advantages to the above method. A database developed in-house manages the case load. Regarding odor management plans that facilities have submitted, the air inspectors found substantial difficulties. Such plans are difficult to enforce, different for each site, written by a third party , and require large amounts of staff review time. Regardless, they are commonly found at WWTPs and trash transfer stations. A prior contract with Envirosuite Inc. was not continued due to the substantial requirements for meteorological data. The project tried to use advanced backtracking technology, based on real-time fine-scale meteorological modelling, to instantly plot and visualize the trajectory of an odor complaint, thereby identifying its likely cause. A current challenge is the overlapping odors found in Milpitas, which have resulted in thousands of complaints. To fingerprint and identify which sources are contributing to the ongoing odors, BAAQMD issued in March 2019 a request for proposals . A community group that meets quarterly is conducting a parallel study. Another challenge is the increase in composting operations, which are often malodorous. Finally, an emerging area of concern is cannabis cultivation, particularly within and around Santa Rosa, California. To understand the operations, BAAQMD staff toured a cannabis cultivation facility and will visit again.To become a “verified complaint,” air inspectors from the Sacramento Municipal Air Quality District rely on the definition of nuisance being about the complainant’s perception and try to verify that. Upon meeting the complainant, the air inspector logs their own description of the odor and sees if it matches that of the complainant. Standardized smell vocabulary would be useful. A verified odor nuisance can lead to a Notice of Violation, which in turn can lead to an Abatement Order that shuts down the facility. The owner must then sue to re open the facility. SMAQMD is considering trying a field olfactometer like neighboring air districts have. Previous tests conducted at the source of an odor need to be translated to fenceline concentrations experienced by the neighborhood.

A current challenge is a rendering facility. California law, the Right-to-Farm Act, exempts such facilities from nuisance law, however. Another challenge is a sweet potato drying operation that has rotting odors. Also, the Zero Waste initiatives are sending more scraps to compost facilities, which are exempt from air regulations, so solid waste programs handle the complaints . Even pleasant aromas can become nuisance odors. A blueberry smell from a food factory was intense enough to trigger migraines. Masking has been done using cherry “perfume” at a solid waste landfill. Complaints are logged into a database that contains over 13,000 records since 1996. The data was transitioned from MS Access to MS Sharepoint, which sends automated e-mails and allows for logging from the field. Responses to questions were received by e-mail from the Feather River Air Quality Management District . Nuisance odor complaints are infrequent and primarily regarding agricultural operations, which are exempt from investigation. For other sources, air inspectors gather from the complainant the type of odor, location, wind direction, topography and any adverse effects experienced. All complaints are investigated, and the air inspectors rely on their own sense of smell and best judgment to trace the odor to the source. The source usually acts immediately to mitigate the problem.Air inspectors from Placer County Air Quality Management District respond to all odor complainants. They drive to the complainant and try to verify the odor, even if they need to wait for an intermittent odor. If detected,grow light shelves they then try to identify the source. No cases have ended up in court, just resolved by mutual settlement. Past experience with a field olfactometer was not helpful due to the transient nature of most odors. The major source of odor complaints is a landfill. The dispersion modelling was not helpful, and sampling was sent for odor intensity testing by a panel. A spray coating did not stop the odor, nor did a cherry/citrus mist at the perimeter. The latter actually magnified the odor. Another nearby source, bioenergy wood piles, was blamed for the odors by the landfill.The San Joaquin Valley Air Quality Management District covers eight counties. Once a complaint is received, the air inspector visits the complainant to determine the type of odor, time of day and GPS location. Driving around, the source is identified. If the source is a permitted facility, the air inspector goes on-site to review the permit and inquire about any upsets or disruptions. If not permitted, the air inspector talks with the source and offers compliance assistance and education. The air inspector always circles back to the complainant to communicate the findings. A senior air inspector often accompanies a new inspector to provide mentoring. Once source of odor complaints was from residents who disagreed with urban planning decisions. Other complaints were from a WWTP that had a pond go anaerobic and a rendering plant, which is now closed. Their database could serve as a model for other air districts. It was developed in-house, which was expensive, but the functionality is impressive. The database is on-line, smart phone friendly, interfaces with their app and, thus, can collect photos and videos. The system sends automated notifications to inspectors by text or e-mail.

It also includes mapping features.Three odor experts in the Colorado were interviewed by phone. Adam Wozniak, an odor expert in the stationary sources program, provided an overview of Colorado’s approaches to nuisance odor investigation. Colorado has the same number of stationary air pollution sources as California, yet a much smaller population. A recent case was odors from a bio-fuel operator north of Denver, which required community meetings. A study of odor’s impact on wellbeing in North Denver has been published . Colorado has 25 odor inspectors at the state level. Most complaints, however, are delegated to the local officers. Both state and local air inspectors are certified annually on how to conduct sensory investigations through a class offered every other month. Odor inspectors are trained to avoid the use of odor notes and instead focus on “detectability,” which is a faint sense that an odor is present, rather than “recognition,” which is a clear sense that an odor is present and can be described. Inspectors’ ability to detect odor intensity, on a scale of 0 to 10, is tested using a “detectability rating test” , and those with extreme senses of smell are disqualified from odor inspections. The Colorado odor regulation from the 1970s, Regulation 2, is a bit of a curse. Regulation 2 codifies field olfactometry dilution-to-threshold limits that are violations when exceeded, namely 2:1 for hog odors, 7:1 for residential/commercial odors, and 15:1 for other land uses . Regulation 2 is a problem because the public complains of odors well below these limits, generally around 2:1 or 3:1. Regardless, to comply with the regulation, field olfactometers are used, primarily the Nasal Ranger® because the more affordable Scentometer is no longer manufactured. The Nasal Ranger® has been customized to meet the dilutions required for Colorado . Persistent complaints receive a 10-day evaluation with follow-up 14 to 30 days later. The evaluation includes mapping of odor frequency, wind direction, and upwind locations. Due to the relatively high D/T limits, few violations occur, and none have ended up in litigation. More commonly, the public is upset with the agency that no violation was triggered. All complaints are tracked in CACTIS software, as is all inspection work. William Brennan at Denver Public Health and Environment was also interviewed by phone. Legal adult use of cannabis began in Colorado in 2014, and today over 350 cannabis cultivation facilities are found within the city limits of Denver. A sharp increase in odor complaints accompanied the rapid growth. Some were probably from disgruntled voters who opposed the legalization. An advisory work group was formed to tackle the issue and included a variety of stakeholders that attended 10 meetings. New odor regulations were developed that now require cannabis growers, edibles manufacturers, and a few other industries to submit Odor Management Plans. An outline is provided as well as example plans.