Identifying Patterns and Sources of Fine and Ultrafine Particulate Matter in London Using Mobile Measurements of Lung-Deposited Surface Area.

We performed more than a year of mobile, 1 Hz measurements of lung-deposited surface area (LDSA, the surface area of 20-400 nm diameter particles, deposited in alveolar regions of lungs) and optically assessed fine particulate matter (PM2.5), black carbon (BC), and nitrogen dioxide (NO2) in central London. We spatially correlated these pollutants to two urban emission sources: major roadways and restaurants. We show that optical PM2.5 is an ineffective indicator of tailpipe emissions on major roadways, where we do observe statistically higher LDSA, BC, and NO2. Additionally, we find pollutant hot spots in commercial neighborhoods with more restaurants. A low LDSA (15 µm2 cm-3) occurs in areas with fewer major roadways and restaurants, while the highest LDSA (25 µm2 cm-3) occurs in areas with more of both sources. By isolating areas that are higher in one source than the other, we demonstrate the comparable impacts of traffic and restaurants on LDSA. Ratios of hyperlocal enhancements (ΔLDSA:ΔBC and ΔLDSA:ΔNO2) are higher in commercial neighborhoods than on major roadways, further demonstrating the influence of restaurant emissions on LDSA. We demonstrate the added value of using particle surface in identifying hyperlocal patterns of health-relevant PM components, especially in areas with strong vehicular emissions where the high LDSA does not translate to high PM2.5.

Comparison of pesticide concentrations observed in community water systems to predictions from U.S. regulatory aquatic exposure models.

The Variable Volume Water Model (VVWM), the receiving water body model for the USEPA regulatory assessment of aquatic pesticide exposures, is composed of a set of static and quasistatic receiving water body conceptual models, but research comparing performance of these models to observations is limited. The water body models included are the constant volume (CVol), constant volume with overflow (CVO), and varying volume with overflow (VVO) models. This work quantified the performance of these three VVWM conceptual models compared with atrazine observations in 50 community water systems (CWSs), and the effect of alternative conceptual models on estimated environmental concentrations of pesticides in regulatory screening assessments. The 50 selected CWSs most relevant to the static and quasistatic VVWM concepts were small in size, with estimated time to peak flow of <1.5 d for consistency with the daily runoff assumption in USEPA landscape Pesticide Root Zone Model (PRZM). The CVO and VVO conceptual models resulted in similar distributions of bias across CWSs with the median result being close to no bias, but the CVol model resulted in overestimation in the majority of CWSs with median model bias near three times the observed values. At present, the CVol conceptual model parameterized with conservative input assumptions has been the regulatory standard invoked in VVWM, yet our results showed that a more physically correct conceptual model (CVO or VVO) could be invoked in regulatory exposure modeling for ecological risk assessment, reducing structural model bias while still allowing users to introduce conservative model inputs for screening purposes.

Characterizing Elevated Urban Air Pollutant Spatial Patterns with Mobile Monitoring in Houston, Texas.

Diverse urban air pollution sources contribute to spatially variable atmospheric concentrations, with important public health implications. Mobile monitoring shows promise for understanding spatial pollutant patterns, yet it is unclear whether uncertainties associated with temporally sparse sampling and instrument performance limit our ability to identify locations of elevated pollution. To address this question, we analyze 9 months of repeated weekday daytime on-road mobile measurements of black carbon (BC), particle number (PN), and nitrogen oxide (NO, NO2) concentrations within 24 census tracts across Houston, Texas. We quantify persistently elevated, intermittent, and extreme concentration behaviors at 50 m road segments on surface streets and 90 m segments on highways relative to median statistics across the entire sampling domain. We find elevated concentrations above uncertainty levels (±40%) within portions of every census tract, with median concentration increases ranging from 2 to 3× for NO2, and >9× for NO. In contrast, PN exhibits elevated concentrations of 1.5-2× the domain-wide median and distinct spatial patterns relative to other pollutants. Co-located elevated concentrations of primary combustion tracers (BC and NOx) near 30% of metal recycling and concrete batch plant facilities within our sampled census tracts are comparable to those measured within 200 m of highways. Our results demonstrate how extensive mobile monitoring across multiple census tracts can quantitatively characterize urban air pollution source patterns and are applicable to developing effective source mitigation policies.

AGRO-2014: A time dependent model for assessing the fate and food-web bioaccumulation of organic pesticides in farm ponds: Model testing and performance analysis.

A time-dependent environmental fate and food-web bioaccumulation model is developed to improve the evaluation of the behaviour of non-ionic hydrophobic organic pesticides in farm ponds. The performance of the model was tested by simulating the behaviour of 3 hydrophobic organic pesticides, i.e., metaflumizone (CAS Number: 139968-49-3), kresoxim-methyl (CAS Number: 144167-04-4) and pyraclostrobin (CAS Number: 175013-18-0), in microcosm studies and a Bluegill bioconcentration study for metaflumizone. In general, model-calculated concentrations of the pesticides were in reasonable agreement with the observed concentrations. Also, calculated bioaccumulation metrics were in good agreement with observed values. The model's application to simulate concentrations of organic pesticides in water, sediment and biota of farm ponds after episodic pesticide applications is illustrated. It is further shown that the time dependent model has substantially better accuracy in simulating the concentrations of pesticides in farm ponds resulting from episodic pesticide application than corresponding steady-state models. The time dependent model is particularly useful in describing the behaviour of highly hydrophobic pesticides that have a potential to biomagnify in aquatic food-webs.

A refined ecological risk assessment for California red-legged frog, Delta smelt, and California tiger salamander exposed to malathion.

The California red-legged frog (CRLF), Delta smelt (DS), and California tiger salamander (CTS) are 3 species listed under the United States Federal Endangered Species Act (ESA), all of which inhabit aquatic ecosystems in California. The US Environmental Protection Agency (USEPA) has conducted deterministic screening-level risk assessments for these species potentially exposed to malathion, an organophosphorus insecticide and acaricide. Results from our screening-level analyses identified potential risk of direct effects to DS as well as indirect effects to all 3 species via reduction in prey. Accordingly, for those species and scenarios in which risk was identified at the screening level, we conducted a refined probabilistic risk assessment for CRLF, DS, and CTS. The refined ecological risk assessment (ERA) was conducted using best available data and approaches, as recommended by the 2013 National Research Council (NRC) report "Assessing Risks to Endangered and Threatened Species from Pesticides." Refined aquatic exposure models including the Pesticide Root Zone Model (PRZM), the Vegetative Filter Strip Modeling System (VFSMOD), the Variable Volume Water Model (VVWM), the Exposure Analysis Modeling System (EXAMS), and the Soil and Water Assessment Tool (SWAT) were used to generate estimated exposure concentrations (EECs) for malathion based on worst-case scenarios in California. Refined effects analyses involved developing concentration-response curves for fish and species sensitivity distributions (SSDs) for fish and aquatic invertebrates. Quantitative risk curves, field and mesocosm studies, surface-water monitoring data, and incident reports were considered in a weight-of-evidence approach. Currently, labeled uses of malathion are not expected to result in direct effects to CRLF, DS or CTS, or indirect effects due to effects on fish and invertebrate prey. Integr Environ Assess Manag 2018;14:224-239. © 2017 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Development of groundwater pesticide exposure modeling scenarios for vulnerable spring and winter wheat-growing areas.

Wheat crops and the major wheat-growing regions of the United States are not included in the 6 crop- and region-specific scenarios developed by the US Environmental Protection Agency (USEPA) for exposure modeling with the Pesticide Root Zone Model conceptualized for groundwater (PRZM-GW). The present work augments the current scenarios by defining appropriately vulnerable PRZM-GW scenarios for high-producing spring and winter wheat-growing regions that are appropriate for use in refined pesticide exposure assessments. Initial screening-level modeling was conducted for all wheat areas across the conterminous United States as defined by multiple years of the Cropland Data Layer land-use data set. Soil, weather, groundwater temperature, evaporation depth, and crop growth and management practices were characterized for each wheat area from publicly and nationally available data sets and converted to input parameters for PRZM. Approximately 150 000 unique combinations of weather, soil, and input parameters were simulated with PRZM for an herbicide applied for postemergence weed control in wheat. The resulting postbreakthrough average herbicide concentrations in a theoretical shallow aquifer were ranked to identify states with the largest regions of relatively vulnerable wheat areas. For these states, input parameters resulting in near 90th percentile postbreakthrough average concentrations corresponding to significant wheat areas with shallow depth to groundwater formed the basis for 4 new spring wheat scenarios and 4 new winter wheat scenarios to be used in PRZM-GW simulations. Spring wheat scenarios were identified in North Dakota, Montana, Washington, and Texas. Winter wheat scenarios were identified in Oklahoma, Texas, Kansas, and Colorado. Compared to the USEPA's original 6 scenarios, postbreakthrough average herbicide concentrations in the new scenarios were lower than all but Florida Potato and Georgia Coastal Peanuts of the original scenarios and better represented regions dominated by wheat crops. Integr Environ Assess Manag 2017;13:992-1006. © 2017 The Authors. Integrated Environmental Assessment and Management Published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Ecological risk assessment for aquatic invertebrate communities exposed to imidacloprid as a result of labeled agricultural and nonagricultural uses in the United States.

A probabilistic ecological risk assessment (ERA) was conducted to determine the potential effects of acute and chronic exposure of aquatic invertebrate communities to imidacloprid arising from labeled agricultural and nonagricultural uses in the United States. Aquatic exposure estimates were derived using a higher-tier refined modeling approach that accounts for realistic variability in environmental and agronomic factors. Toxicity was assessed using refined acute and chronic community-level effect metrics for aquatic invertebrates (i.e., species or taxon sensitivity distributions) developed using the best available data. Acute and chronic probabilistic risk estimates were derived by integrating the exposure distributions for different use patterns with the applicable species or taxon sensitivity distributions to generate risk curves, which plot cumulative probability of exceedance versus the magnitude of effect. Overall, the results of this assessment indicated that the aquatic invertebrate community is unlikely to be adversely affected by acute or chronic exposure to imidacloprid resulting from currently registered uses of imidacloprid in the United States. Environ Toxicol Chem 2017;36:1375-1388. © 2016 SETAC.

Ecological risk assessment for Pacific salmon exposed to dimethoate in California.

A probabilistic risk assessment of the potential direct and indirect effects of acute dimethoate exposure to salmon populations of concern was conducted for 3 evolutionarily significant units (ESUs) of Pacific salmon in California. These ESUs were the Sacramento River winter-run chinook, the California Central Valley spring-run chinook, and the California Central Valley steelhead. Refined acute exposures were estimated using the Soil and Water Assessment Tool, a river basin-scale model developed to quantify the impact of land-management practices in large, complex watersheds. Both direct effects (i.e., inhibition of brain acetylcholinesterase activity) and indirect effects (i.e., altered availability of aquatic invertebrate prey) were assessed. Risk to salmon and their aquatic invertebrate prey items was determined to be de minimis. Therefore, dimethoate is not expected to have direct or indirect adverse effects on Pacific salmon in these 3 ESUs. Environ Toxicol Chem 2017;36:532-543. © 2016 SETAC.

A probabilistic approach for estimating the spatial extent of pesticide agricultural use sites and potential co-occurrence with listed species for use in ecological risk assessments.

A crop footprint refers to the estimated spatial extent of growing areas for a specific crop, and is commonly used to represent the potential "use site" footprint for a pesticide labeled for use on that crop. A methodology for developing probabilistic crop footprints to estimate the likelihood of pesticide use and the potential co-occurrence of pesticide use and listed species locations was tested at the national scale and compared to alternative methods. The probabilistic aspect of the approach accounts for annual crop rotations and the uncertainty in remotely sensed crop and land cover data sets. The crop footprints used historically are derived exclusively from the National Land Cover Database (NLCD) Cultivated Crops and/or Pasture/Hay classes. This approach broadly aggregates agriculture into 2 classes, which grossly overestimates the spatial extent of individual crops that are labeled for pesticide use. The approach also does not use all the available crop data, represents a single point in time, and does not account for the uncertainty in land cover data set classifications. The probabilistic crop footprint approach described herein incorporates best available information at the time of analysis from the National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL) for 5 y (2008-2012 at the time of analysis), the 2006 NLCD, the 2007 NASS Census of Agriculture, and 5 y of NASS Quick Stats (2008-2012). The approach accounts for misclassification of crop classes in the CDL by incorporating accuracy assessment information by state, year, and crop. The NLCD provides additional information to improve the CDL crop probability through an adjustment based on the NLCD accuracy assessment data using the principles of Bayes' Theorem. Finally, crop probabilities are scaled at the state level by comparing against NASS surveys (Census of Agriculture and Quick Stats) of reported planted acres by crop. In an example application of the new method, the probabilistic crop footprint for soybean resulted in national and statewide soybean acreages that are within the error bounds of the average reported NASS yearly soybean acreage over the same time period, whereas the method using only NLCD resulted in an acreage that is over 4 times the survey acreage. When the probabilistic crop footprint for soybean was used in a co-occurrence analysis with listed species locations, the number of potentially proximal species identified was half the number based on the standard NLCD crop footprint method (276 species with the probabilistic crop footprint vs 511 for the conventional method). The probabilistic crop footprint methodology allows for a more comprehensive and representative understanding of the potential pesticide use footprint co-occurrence with endangered species locations for use in effects determinations.

Evaluation of AGRO-2014 for Predicting Hydrophobic Organic Chemical Concentrations in Ponds.

Highly hydrophobic organic chemicals (HOCs), like pyrethroids, adsorb strongly to eroded soil and suspended sediment. Therefore, total suspended solids (TSS) concentration in the water column of receiving waters is important for determining the proportion of chemical in the sediment-sorbed vs. the dissolved (bioavailable) state. However, most current regulatory exposure models, such as the Exposure Analysis Modeling System (EXAMS) and Variable Volume Water Model (VVWM), do not include dynamic modeling of TSS. The objective of this study is to compare the performance of those models for simulating observed pesticide concentrations in small water bodies with an updated version of the AGRO model, called AGRO-2014, which includes dynamic sediment processes. The paper also evaluates the importance of explicitly modeling sediment dynamics for HOCs. We calibrated AGRO-2014 for small, static, water bodies using published pyrethroid mesocosm data. To improve the basis for intermodel comparison, AGRO-2014 includes the same algorithm for temperature-dependent degradation found in EXAMS and VVWM, direct acceptance of organic C partition coefficient () inputs, and acceptance of user-defined pesticide loading durations. Differences in sediment processes in AGRO-2014, EXAMS, and VVWM significantly affected predicted concentrations of high- compounds for standardized loading scenarios, whereas differences between the models were less evident for compounds with lower sorption to sediments. AGRO-2014 simulations of drift and slurry pyrethroid applications to ponds closely matched observed concentrations, while EXAMS and VVWM simulations underestimated the observations. The publicly available AGRO-2014 model offers improvements over other models for predicting concentrations of HOC compounds in small water bodies.