Rapid determination of residues of pesticides in honey by µGC-ECD and GC-MS/MS: Method validation and estimation of measurement uncertainty according to document No. SANCO/12571/2013

A simple and straightforward method for simultaneous determination of residues of 13 pesticides in honey samples (acrinathrin, bifenthrin, bromopropylate, cyhalothrin-lambda, cypermethrin, chlorfenvinphos, chlorpyrifos, coumaphos, deltamethrin, fluvalinate-tau, malathion, permethrin and tetradifon) from different pesticide classes has been developed and validated. The analytical method provides dissolution of honey in water and an extraction of pesticide residues by n-Hexane followed by clean-up on a Florisil SPE column. The extract was evaporated and taken up by a solution of an injection internal standard (I-IS), ethion, and finally analyzed by capillary gas chromatography with electron capture detection (GC-µECD). Identification for qualitative purpose was conducted by gas chromatography with triple quadrupole mass spectrometer (GC-MS/MS). A matrix-matched calibration curve was performed for quantitative purposes by plotting the area ratio (analyte/I-IS) against concentration using a GC-µECD instrument. According to document No. SANCO/12571/2013, the method was validated by testing the following parameters: linearity, matrix effect, specificity, precision, trueness (bias) and measurement uncertainty. The analytical process was validated analyzing blank honey samples spiked at levels equal to and greater than 0.010 mg/kg (limit of quantification). All parameters were satisfactorily compared with the values established by document No. SANCO/12571/2013. The analytical performance was verified by participating in eight multi-residue proficiency tests organized by BIPEA, obtaining satisfactory z-scores in all 70 determinations. Measurement uncertainty was estimated according to the top-down approaches described in Appendix C of the SANCO document using the within-laboratory reproducibility relative standard deviation combined with laboratory bias using the proficiency test data.     

Development,validation of QuEChERS-based method for simultaneous determination of multiclass pesticide residue in milk,and evaluation of the matrix effect

Extraction and quantification of pesticide residue from the milk matrix at or below the established maximum residue limit (MRL) is a challenging task for both analytical chemists and the regulatory institutions to take corrective actions for the human health and safety. The main aim of the study is to develop a simple rapid and less expensive QuEChERS extraction and cleanup method for simultaneous analysis of 41 multiclass pesticide residue in milk by gas chromatography-electron capture detector (GC-ECD), followed by confirmation of the residues with gas chromatography-mass spectrometer (GC-MS). Effect of sorbent type, temperature, spiking concentration, matrix effect (ME), measurement uncertainty (MU), inter- and intra-assay repeatability, reproducibility of recovery, and trueness of the results were investigated to validate the effectiveness of the method. Limit of determination (LOD) and limit of quantitation (LOQ) for all the analytes ranged within 0.001–0.02 and 0.002–0.05 µg mL^?1, respectively. The % recovery of all the pesticides ranged between 91.38 and 117.56% with relative standard deviation (RSD) below 2.79%. The MU for all the analytes was ≤29% of respective LOQs, and except for few pesticides, the ME was largely negative. The method fulfilled all the SANTE guidelines and thus can be extended for routine analysis of multiclass pesticide residue in milk.     

Modeling cold soak evaporative vapor emissions from gasoline-powered automobiles using a newly developed method

ABSTRACT

Volatile organic compounds (VOCs) evaporate and vent from a vehicle’s fuel tank to its evaporative control system when the vehicle is both driven and parked. VOCs making it past the control system are emissions. Driving and parking activity, fuel volatility, and temperature strongly affect vapor generation and the effectiveness of control technologies, and the wide variability in these factors and the sensitivity of emissions to these factors make it difficult to estimate evaporative emissions at the macro level. Established modeling methods, such as COPERT and MOVES, estimate evaporative emissions by assuming a constant in-use canister condition and consequently contain critical uncertainty when real conditions deviate from that standard condition. In this study, we have developed a new method to model canister capacity as a representative variable, and estimated emissions for all parking events based on semi-empirical functions derived from real-world activity data and laboratory measurements. As compared to chamber measurements collected during this study, the bias of the MOVES diurnal tank venting simulation ranges from ?100% to 129%, while the bias for our method’s simulation is 1.4% to 8.5%. Our modeling method is compared to the COPERT and MOVES models by estimating evaporative emissions from a Euro-3/4/5 and a Tier 2 vehicle in conditions representative for Chicago, IL, and Guangzhou, China. Estimates using the COPERT and MOVES methods differ from our method by ?56% to 120% and ?100% to 25%, respectively. The study highlights the importance for continued modeling improvement of the anthropogenic evaporative emission inventory and for tightened regulatory standards.

Implications: The COPERT and MOVES methodologies contain large uncertainties for estimating evaporative emissions, while our modeling method is developed based on chamber measurements to estimate evaporative emissions and can properly address those uncertainties. Modeling results suggested an urgent need to complete evaporative emissions inventories and also indicated that tightening evaporative emission standards is urgently needed, especially for warm areas.     

Quantification of Variability and Uncertainty in Lawn and Garden Equipment NOx and Total Hydrocarbon Emission Factors

Abstract

Variability refers to real differences in emissions among multiple emission sources at any given time or over time for any individual emission source. Variability in emissions can be attributed to variation in fuel or feedstock composition, ambient temperature, design, maintenance, or operation. Uncertainty refers to lack of knowledge regarding the true value of emissions. Sources of uncertainty include small sample sizes, bias or imprecision in measurements, nonrepresentativeness, or lack of data. Quantitative methods for characterizing both variability and uncertainty are demonstrated and applied to case studies of emission factors for lawn and garden (L&G) equipment engines. Variability was quantified using empirical and parametric distributions. Bootstrap simulation was used to characterize confidence intervals for the fitted distributions. The 95% confidence intervals for the mean grams per brake horsepower/hour (g/hp-hr) emission factors for two-stroke engine total hydrocarbon (THC) and NO_x emissions were from -30 to +41% and from -45 to +75%, respectively. The confidence intervals for four-stroke engines were from -33 to +46% for THCs and from -27 to +35% for NO_x. These quantitative measures of uncertainty convey information regarding the quality of the emission factors and serve as a basis for calculation of uncertainty in emission inventories (Els).     

Estimation of measurement uncertainty associated to the determination of pesticide residues: a case study

In the analytical analysis the measurement uncertainty is a quantitative indicator of the confidence describing the range around a reported or experimental result within which the true value can be expected. Several approaches can be used to estimate the measurement uncertainty associated to the analysis of pesticide residues: a) the top-down, the estimation can be referred to default values; b) the bottom-up the estimation is related to the uncertainty sources. Concerning the bottom-up approach, the following contributions have been investigated: weight of sample, calibration solutions, final volume of sample and intermediate repeatability studies. The commodity/residue combination selected in this study was celery/tau-fluvalinate pesticide. Tau-fluvalinate is a broad-spectrum insecticide in the pyrethroid class of pesticides. The Maximum Residue Limit (MRL) of tau-fluvalinate in celery has been set at 0.01 mg/kg. The tau- Fluvalinate showed two chromatographic peaks. Since the individual standards are not available, the two peaks were integrated separately and the instrumental responses were added. The total residue was calculated on the basis of resulted peaks. The present work aims to compare the uncertainty estimated by experimental data using repeated analysis (n = 12) of a real sample and a spiked sample. The relative expanded uncertainty for two data set, incurred and spiked, was 22 % and 20 %, respectively. No differences were observed from repeated determinations of real samples and spiked samples.     

Efficacy of new mass-trapping devices against Bactrocera oleae (Diptera tephritidae) for minimizing pesticide input in agroecosystems

Decreasing pesticide use in olive groves is central to controlling pathogens and pests such as Bactrocera oleae. This has led to the development of mass trapping devices which not only minimize pesticide use but, with improved efficacy of attractants, also decrease costs associated with pest control and ensures that the quality of olive oil is safe for human consumption. This study was undertaken to test a new device which utilizes reduced quantities of both insecticide (lambda-cyalothrin) as well as the female olive fly pheromone (1,7-dioxaspiro-(5.5)-undecane). The new device was tested against an older device manufactured by the same company. The use of plastic polymers as substrate for encapsulating the pheromone allowed for a slower pheromone release, prolonging the efficacy and duration and thus reducing costs. The density of adult populations was monitored using yellow chromotropic traps that were checked every ten days and the degree of olive infestation, as determined by preimago stages, was assessed by analyzing 100 drupes per plot. Infestation analyses were performed every ten days. The control plot had the lowest density of adults and the highest drupe infestation rate. The new devices were more effective than the older devices in both attracting adults and controlling infestation of drupes. Moreover, the new devices containing reduced amounts of pheromone and insecticide were cheaper and exhibited longer functional efficacy. In addition to the slower release of attractants, the plastic polymers used in these newer devices were also more resistant to mechanical and weather degradations. Results demonstrate that mass trapping can indeed be an effective means of controlling B. oleae via eco-sustainable olive farming.     

Assuring the quality of data in the pesticide residue laboratory

Abstract

The importance of quality control procedures to the collection of pesticide residue data is discussed. The equipment requirements of an adequate, safe pesticide residue laboratory are presented. Equipment maintenance, personnel training, and preservation of samples is also reviewed. Appropriate objectives for an intra‐laboratory quality control program are outlined.     

Validation of a QuEChERS-based gas chromatographic method for analysis of pesticide residues in Cassia angustifolia (senna)

A simple multi-residue method based on modified QuEChERS (Quick, Easy, Cheap, Effective, Rugged and Safe) approach was established for the determination of 17 organochlorine (OC), 15 organophosphorous (OP) and 7 synthetic pyrethroid (SP) pesticides in an economically important medicinal plant of India, Senna (Cassia angustifolia), by gas chromatography coupled to electron capture and flame thermionic detectors (GC/ECD/FTD) and confirmation of residues was done on gas chromatograph coupled with mass spectrometry (GC-MS). The developed method was validated by testing the following parameters: linearity, limit of detection (LOD), limit of quantification (LOQ), matrix effect, accuracy–precision and measurement uncertainty; the validation study clearly demonstrated the suitability of the method for its intended application. All pesticides showed good linearity in the range 0.01–1.0 μg mL^?1 for OCs and OPs and 0.05–2.5 μg mL^?1 for SPs with correlation coefficients higher than 0.98. The method gave good recoveries for most of the pesticides (70–120%) with intra-day and inter-day precision < 20% in most of the cases. The limits of detection varied from 0.003 to 0.03 mg kg^?1, and the LOQs were determined as 0.01-0.049 mg kg^?1. The expanded uncertainties were <30%, which was distinctively less than a maximum default value of ±50%. The proposed method was successfully applied to determine pesticide residues in 12 commercial market samples obtained from different locations in India.     

Nature of the field-to-field distribution of pesticide residues

The supervised trial datasets (1950), consisting of a minimum of five residue values and selected by the experts of FAO/WHO Joint Meeting on Pesticide Residues for recommending maximum residue levels between 1997 and 2011, were evaluated to obtain information on the typical spread of residue values in individual datasets. The typical relative standard deviation, CV, of field-to-field variation of pesticide residues was about 80%. The spread of residues in datasets is independent from the chemical structure of pesticides, residue level, pre-harvest interval and number of values in the datasets. The CV ranges within the Codex commodity groups and between groups overlapped and their difference were not statistically significant. The number of residues below the limit of quantification (LOQ) affects the CV at various extents depending on the ratio of LOQ/R _mean. The combined uncertainty of the highest residue in a dataset significantly affects the CV of the dataset. The lowest and intermediate ones have less influence. The residues in different fields receiving the same treatment vary within large range: 55%, 72%, 78%, 86% and 89% of the 25,766 residues values were, respectively, within 3, 4, 5, 6 and 7 times the median value of the corresponding dataset.     

Pesticide residue dynamics in passion fruits: Comparing field trial and modelling results

We evaluated the exposure to pesticides from the consumption of passion fruits and subsequent human health risks by combining several methods: (i) experimental field studies including the determination of pesticide residues in/on passion fruits, (ii) dynamic plant uptake modelling, and (iii) human health risk assessment concepts. Eight commonly used pesticides were applied onto passion fruits cultivated in Colombia. Pesticide concentrations were measured periodically (between application and harvest) in whole fruits and fruit pulp. Measured concentrations were compared with predicted residues calculated with a dynamic and crop-specific pesticide uptake model, namely dynamiCROP. The model accounts for the time between pesticide application and harvest, the time between harvest and consumption, the amount of spray deposition on plant surfaces, uptake processes, dilution due to crop growth, degradation in plant components, and reduction due to food processing (peeling). Measured and modelled residues correspond well (r² = 0.88-0.99), with all predictions falling within the 90% confidence interval of the measured values. A mean error of 43% over all studied pesticides was observed between model estimates and measurements. The fraction of pesticide applied during cultivation that is eventually ingested by humans is on average 10⁻⁴-10⁻⁶, depending on the time period between application and ingestion and the processing step considered. Model calculations and intake fractions via fruit consumption based on experimental data corresponded well for all pesticides with a deviation of less than a factor of 2. Pesticide residues in fruits measured at recommended harvest dates were all below European Maximum Residue Limits (MRLs) and therefore do not indicate any violation of international regulatory thresholds.     

Relating error bounds for maximum concentration estimates to diffusion meteorology uncertainty

The intent of this paper is to relate the magnitude of the error bounds of data, used as inputs to a Gaussian dispersion model, to the magnitude of the error bounds of the model output, which include the estimates of the maximum concentration and the distance to that maximum. The research specifically addresses the uncertainty in estimating the maximum concentrations from elevated buoyant sources during unstable atmospheric conditions, as these are most often of practical concern in regulatory decision making. A direct and quantitative link between the nature and magnitude of the input uncertainty and modeling results has not been previously investigated extensively. The ability to develop specific error bounds, tailored to the modeling situation, allows more informed application of the model estimates to the air quality issues.In this study, a numerical uncertainty analysis is performed using the Monte-Carlo technique to propagate the uncertainties associated with the model input. Uncertainties were assumed to exist in four model input parameters: (1) wind speed, (2) standard deviation of lateral wind direction fluctuations, (3) standard deviation of vertical wind direction fluctuations, and (4) plume rise. For each simulation, results were summarized characterizing the uncertainty in four features of the ground-level concentration pattern predicted by the model: (1) the magnitude of the maximum concentration, (2) the distance to the maximum concentration, and (3) and (4) the areas enclosed within the isopleths of 50% and 25% of the error-free estimate of maximum concentration.The authors conclude that the error bounds for the estimated maximum concentration and the distance to the maximum can be double that of the error bounds for individual model input parameters. The model output error bounds for the areas enclosed within isopleth values can be triple the error bounds of the input. It was not our intent to cover all possible combinations for the error in the input parameters. Ours was a much more limited goal of providing a lower bound estimate of model uncertainty in which we assume the input is reasonably well characterized and there is no bias in the input. These results allow estimation of minimum bounds on errors in model output when considering reasonable input error bounds.     

Alterations in liver marker enzymes and recovery ability of cyprinids as indicators of aquatic pollution

Information on the detection of pesticides in fresh water Lakes of Kashmir (Dal and Mansbal) through GC–MS technique is scarce, and also the recovery in biochemical parameters (AST, ALT and ALP) of fish after transferring them to clean media has not been reported yet. The water samples were collected from three sites and analyzed for their pesticide profile by dispersive liquid–liquid micro extraction (DLLME) followed by GC–MS. Influence of pesticides on liver marker enzymes of Cyprinus carpio and Carassius carassius was also investigated. The results obtained showed the presence of three main pesticides viz. chlorpyrifros, dimethoate and dichlorvos in waters of Dal Lake whereas no pesticide was detected in waters of Mansbal. The higher values for AST, ALT and ALP activities and decrease in protein content were obtained in the samples from the Dal Lake compared with those from Mansbal Lake (p < 0.05). These data when compared with the values found in C. carpio and C. carassius from both the Dal Lake and Mansbal Lake kept under laboratory conditions after 15, 30, 45 and 60 days of maintenance in clean media found that during depuration, all the enzyme activities came down significantly (p < 0.05) indicating the compensatory response by the fish against the pesticide stress. Therefore, these parameters could be used as indicators of pesticide pollution in aquatic organisms and were recommended for environmental monitoring for investigating the mechanism involved in the recovery pattern.

     

Diffusion-controlled toluene reference material for VOC emissions testing: International interlaboratory study

The measurement of volatile organic compound (VOC) emissions from building products and materials by manufacturers and testing laboratories, and the use of the test results for labeling programs, continue to expand. One issue that hinders wide acceptance for chamber product testing is the lack of a reference material to validate test chamber performance. To meet this need, the National Institute of Standards and Technology (NIST) and Virginia Tech (VT) have developed a prototype reference material that emits a single VOC similar to the emissions of a diffusion-controlled building product source with a dynamic emissions profile. The prototype material has undergone extensive testing at NIST and a pilot interlaboratory study (ILS) with four laboratories. The next development step is an evaluation of the prototype source in multiple-sized chambers of 14 laboratories in seven countries. Each laboratory was provided duplicate specimens and a test protocol. Study results identified significant issues related to the need to store the source at a subzero Celsius temperature until tested and possible inconsistencies in large chambers. For laboratories using a small chamber and meeting all the test method criteria, the results were very encouraging with relative standard deviations ranging from 5% to 10% across the laboratories.

Implications: Currently, the chamber performance of laboratories conducting product VOC emissions testing is assessed through interlaboratory studies (ILS) using a source with an unknown emission rate. As a result, laboratory proficiency can only be based on the mean and standard deviation of emission rates measured by the participating ILS laboratories. A reference material with a known emission rate has the potential to provide an independent assessment of laboratory performance as well as improve the quality of interlaboratory studies. Several international laboratories with different chamber testing systems demonstrated the ability to measure the emission rate of such a reference material within an acceptable measurement uncertainty.     

Persistence and biodegradation of carbaryl in soils

Abstract

The persistence of the methylcarbamate pesticide carbaryl was studied in four soils under flooded conditions. A substantial portion of the pesticide was recovered from all soils even after 15 days of its application, with the recovery ranging from 37% in an alluvial soil to 73% in an acid sulfate soil. The degradation of carbaryl was more rapid under flooded conditions than under nonflooded conditions. A bacterium, Pseudomonas cepacia, isolated from a flooded soil amended with a related methylcarbamate pesticide carbofuran, degraded carbaryl in a mineral medium supplemented with yeast extract.     

Predicting emissions from oil and gas operations in the Uinta Basin,Utah

In this study, emissions of ozone precursors from oil and gas operations in Utah’s Uinta Basin are predicted (with uncertainty estimates) from 2015–2019 using a Monte-Carlo model of (a) drilling and production activity, and (b) emission factors. Cross-validation tests against actual drilling and production data from 2010–2014 show that the model can accurately predict both types of activities, returning median results that are within 5% of actual values for drilling, 0.1% for oil production, and 4% for gas production. A variety of one-time (drilling) and ongoing (oil and gas production) emission factors for greenhouse gases, methane, and volatile organic compounds (VOCs) are applied to the predicted oil and gas operations. Based on the range of emission factor values reported in the literature, emissions from well completions are the most significant source of emissions, followed by gas transmission and production. We estimate that the annual average VOC emissions rate for the oil and gas industry over the 2010–2015 time period was 44.2E+06 (mean) ± 12.8E+06 (standard deviation) kg VOCs per year (with all applicable emissions reductions). On the same basis, over the 2015–2019 period annual average VOC emissions from oil and gas operations are expected to drop 45% to 24.2E+06 ± 3.43E+06 kg VOCs per year, due to decreases in drilling activity and tighter emission standards.

Implications: This study improves upon previous methods for estimating emissions of ozone precursors from oil and gas operations in Utah’s Uinta Basin by tracking one-time and ongoing emission events on a well-by-well basis. The proposed method has proven highly accurate at predicting drilling and production activity and includes uncertainty estimates to describe the range of potential emissions inventory outcomes. If similar input data are available in other oil and gas producing regions, then the method developed here could be applied to those regions as well.     

Combined effect of diuron and simazine on photosystem II photochemistry in a sandy soil and soil amended with solid olive-mill waste

Diuron (3-(3,4-dichlorophenyl)- = 1,1-dimethylurea) and simazine (6-chloro-N ², N ⁴-diethyl-1,3,5-triazine-2,4-diamine) are soil-applied herbicides used in olive crops. The objective of this study is to investigate the effect of these herbicides on Photosystem II photochemistry of Olea europaea L., and whether the amendment of soil with an organic waste (OW) from olive oil production industry modifies this effect. For this purpose, herbicide soil adsorption studies, with unamended and OW-amended soil, and chlorophyll fluorescence measurements in adult olive leaves, after one, two and three weeks of soil herbicide treatment and/or OW amendment, were performed. Soil application of these herbicides reduced the efficiency of Photosystem II photochemistry of olive trees due to chronic photoinhibition, and this effect is counterbalanced by the addition of OW to the soil. OW reduces herbicide uptake by the plant due to an increase in herbicide adsorption.     

Spatio-temporal variations of selected pesticide residues in the Kurose River in Higashi-Hiroshima city,Japan

ABSTRACT

This study investigated spatio-temporal variations of selected pesticide residues in the Kurose River in Higashi-Hiroshima city (Hiroshima Prefecture), Japan. Water samples were collected from the river at seven sites every month for 1 year (March 2016 to February 2017). Pesticide residues were extracted from the samples by a solid phase extraction using Sep Pack C₁₈ cartridges. Once extracted, the samples were analyzed for cyanazine, simetryn, fenarimol, isoprothiolane, and diazinon using a reversed-phase high-performance liquid chromatography ultraviolet visible (HPLC-UV Vis) system. The limits of detection were 3.60, 4.10, 2.80, 6.50, and 7.30 ng L^-1 for cyanazine, simetryn, fenarimol, isoprothiolane, and diazinon, respectively. Good recovery rates (88%–102%), and mean percent relative standard deviation range (1.00%–5.70%) (n = 6) were obtained with a spiking at 0.20 µg L^-1. The maximum concentrations of 282, 391, 60, 1086, and 1194 ng L^-1 were obtained for cyanazine, simetryn, isoprothiolane, fenarimol, and diazinon, respectively. Cyanazine was the most frequently detected pesticide (64% of the samples, n = 84), followed by simetryn (58%), and then diazinon (57%). The highest and lowest pesticide concentrations were measured during the periods May–June, and January–February, respectively. Principal component analysis revealed three principal components in which the pesticides were linked to dissolved organic matter and total suspended solids. The major water quality parameters (electrical conductivity, pH, Na⁺, K⁺, Mg²⁺, Ca²⁺, NH₄⁺, NO₃^?, Cl^?, SO₄^2?, NO₂^?, and temperature) showed no clear trends for these pesticides. The presence of simetryn and isoprothiolane was largely attributed to rice paddy farms, whereas diazinon was associated mostly with vegetable farms and orchards. The diazinon and isoprothiolane patterns were consistent with their use of controlling insects and fungi in the prefecture. The maximum diazinon concentration detected was higher than the human safe level specified by the European Union (100 ng L^-1) in Council Directive 98/83/EC. This is of concern because of the bioconcentration potential of these residues in fish and other marine animals consumed by humans.     

The persistence and disappearance by washoff and dryfall of methoxychlor from soybean foliage—a preliminary study

Abstract

The persistence and disappearance (washoff or dryfall) of methoxychlor [2,2‐bis(p‐methoxypheny1)‐1,1,1‐trichloroethane] from mature soybean [Glycine max (L.) Merrill] foliage was investigated in a small field plot study under natural rainfall conditions in 1977 and 1978. Residue analyses were conducted using whole plant samples‐ Methoxychlor washoff rate was 8±4% of the amount on plants (prior to rain) per centimeter of rainfall, regardless of time after application. Total seasonal washoff for 1978 accounted for 33.5% of the applied pesticide; however, 30.5% of the total loss was removed by washoff on the second day after application. Dryfall or dislodgeable residue accounted for less than 1% of the amount applied. The amount of dryfall was significantly greater in plots entered by workers than in those where entry was avoided. More than 19% of the applied methoxychlor was lost as a result of through‐fall to the ground during application to the plots. Statistical analyses indicated that within‐sample variation for mechanical chopping of plant samples was significantly smaller at the 5% level than for a hand chopping method. Results from this study will be useful in defining research objectives for the development of algorithms to describe the behavior of foliar‐applied compounds. Such algorithms are necessary for estimating runoff losses of insecticides to water bodies.     

Evaluation of nitrogen dioxide photolysis rates in an urban area using data from the 1997 Southern California Ozone Study

The photolysis of nitrogen dioxide and formaldehyde are two of the most influential reactions in the formation of photochemical air pollution, and their rates are computed using actinic flux determined from a radiative transfer model. In this study, we compare predicted and measured nitrogen dioxide photolysis rate coefficients (j_NO2). We used the Tropospheric Ultraviolet-Visible (TUV) radiation transfer model to predict j_NO2 values corresponding to measurements performed in Riverside, California as part of the 1997 Southern California Ozone Study (SCOS’97). Spectrally resolved irradiance measured at the same site allowed us to determine atmospheric optical properties, such as aerosol optical depth and total ozone column, that are needed as inputs for the radiative transfer model. Matching measurements of aerosol optical depth, ozone column, and j_NO2 were obtained for 14 days during SCOS’97. By using collocated measurements of the light extinction caused by aerosols and ozone over the full height of the atmosphere as model input, it was possible to predict sudden changes in j_NO2 resulting from atmospheric variability. While the diurnal profile of the rate coefficient was readily reproduced, j_NO2 model predicted values were found to be consistently higher than measured values. The bias between measured and predicted values was 17–36%, depending on the assumed single scattering albedo. By statistical analysis, we restricted the most likely values of the single scattering albedo to a range that produced bias on the order of 20–25%. It is likely that measurement error is responsible for a significant part of the bias. The aerosol single scattering albedo was found to be a major source of uncertainty in radiative transfer model predictions. Our best estimate indicates its average value at UV-wavelengths for the period of interest is between 0.77 and 0.85.     

Quantification of variability and uncertainty in lawn and garden equipment NOx and total hydrocarbon emission factors

Variability refers to real differences in emissions among multiple emission sources at any given time or over time for any individual emission source. Variability in emissions can be attributed to variation in fuel or feedstock composition, ambient temperature, design, maintenance, or operation. Uncertainty refers to lack of knowledge regarding the true value of emissions. Sources of uncertainty include small sample sizes, bias or imprecision in measurements, nonrepresentativeness, or lack of data. Quantitative methods for characterizing both variability and uncertainty are demonstrated and applied to case studies of emission factors for lawn and garden (L&G) equipment engines. Variability was quantified using empirical and parametric distributions. Bootstrap simulation was used to characterize confidence intervals for the fitted distributions. The 95% confidence intervals for the mean grams per brake horsepower/hour (g/hp-hr) emission factors for two-stroke engine total hydrocarbon (THC) and NOx emissions were from -30 to +41% and from -45 to +75%, respectively. The confidence intervals for four-stroke engines were from -33 to +46% for THCs and from -27 to +35% for NOx. These quantitative measures of uncertainty convey information regarding the quality of the emission factors and serve as a basis for calculation of uncertainty in emission inventories (EIs).