Search

We evaluate fine particulate matter (PM2.5) exposure-response models to propose a consistent set of global effect factors for product and policy assessments across spatial scales and across urban and rural environments. Relationships among exposure concentrations and PM2.5-attributable health effects largely depend on location, population density, and mortality rates. Existing effect factors build mostly on an essentially linear exposure-response function with coefficients from the American Cancer Society study. In contrast, the Global Burden of Disease analysis offers a nonlinear integrated exposure-response (IER) model with coefficients derived from numerous epidemiological studies covering a wide range of exposure concentrations. We explore the IER, additionally provide a simplified regression as a function of PM2.5 level, mortality rates, and severity, and compare results with effect factors derived from the recently published global exposure mortality model (GEMM). Uncertainty in effect factors is dominated by the exposure-response shape, background mortality, and geographic variability. Our central IER-based effect factor estimates for different regions do not differ substantially from previous estimates. However, IER estimates exhibit significant variability between locations as well as between urban and rural environments, driven primarily by variability in PM2.5 concentrations and mortality rates. Using the IER as the basis for effect factors presents a consistent picture of global PM2.5-related effects for use in product and policy assessment frameworks.

Semivolatile organic compounds (SVOCs) are ubiquitous in the indoor environment and a priority for exposure assessment because of the environmental health concerns that they pose. Direct air-to-skin dermal uptake has been shown to be comparable to the inhalation intake for compounds with certain chemical properties. In this study, we aim to further understand the transport of these types of chemicals through the skin, specifically through the stratum corneum (SC). Our assessment is based on collecting three sequential forehead skin wipes, each hypothesized to remove pollutants from successively deeper skin layers, and using these wipe analyses to determine the skin concentration profiles. The removal of SVOCs with repeated wipes reveals the concentration profiles with depth and provides a way to characterize penetration efficiency and potential transfer to blood circulation. We used a diffusion model applied to surface skin to simulate concentration profiles of SVOCs and compared them with the measured values. We found that two phthalates, dimethyl and diethyl phthalates, penetrate deeper into skin with similar exposure compared to other phthalates and targeted SVOCs, an observation supported by the model results as well. We also report the presence of statistically significant declining patterns with skin depth for most SVOCs, indicating that their diffusion through the SC is relevant and eventually can reach the blood vessels in the vascularized dermis. Finally, using a nontarget approach, we identified skin oxidation products, linked to respiratory irritation symptoms, formed from the reaction between ozone and squalene.

The work addresses current knowledge gaps regarding causes for correlations between environmental and biomarker measurements and explores the underappreciated role of variability in disaggregating exposure attributes that contribute to biomarker levels. Our simulation-based study considers variability in environmental and food measurements, the relative contribution of various exposure sources (indoors and food), and the biological half-life of a compound, on the resulting correlations between biomarker and environmental measurements. For two hypothetical compounds whose half-lives are on the order of days for one and years for the other, we generate synthetic daily environmental concentrations and food exposures with different day-to-day and population variability as well as different amounts of home- and food-based exposure. Assuming that the total intake results only from home-based exposure and food ingestion, we estimate time-dependent biomarker concentrations using a one-compartment pharmacokinetic model. Box plots of modeled R2 values indicate that although the R2 correlation between wipe and biological (e.g., serum) measurements is within the same range for the two compounds, the relative contribution of the home exposure to the total exposure could differ by up to 20%, thus providing the relative indication of their contribution to body burden. The novel method introduced in this paper provides insights for evaluating scenarios or experiments where sample, exposure, and compound variability must be weighed in order to interpret associations between exposure data.

Passenger cars in the United States (U.S.) rely primarily on petroleum-derived fuels and contribute the majority of U.S. transportation-related greenhouse gas (GHG) emissions. Electricity and biofuels are two promising alternatives for reducing both the carbon intensity of automotive transportation and U.S. reliance on imported oil. However, as standalone solutions, the biofuels option is limited by land availability and the electricity option is limited by market adoption rates and technical challenges. This paper explores potential GHG emissions reductions attainable in the United States through 2050 with a county-level scenario analysis that combines ambitious plug-in hybrid electric vehicle (PHEV) adoption rates with scale-up of cellulosic ethanol production. With PHEVs achieving a 58% share of the passenger car fleet by 2050, phasing out most corn ethanol and limiting cellulosic ethanol feedstocks to sustainably produced crop residues and dedicated crops, we project that the United States could supply the liquid fuels needed for the automobile fleet with an average blend of 80% ethanol (by volume) and 20% gasoline. If electricity for PHEV charging could be supplied by a combination of renewables and natural-gas combined-cycle power plants, the carbon intensity of automotive transport would be 79 g CO2e per vehicle-kilometer traveled, a 71% reduction relative to 2013.

Organophosphorus (OP) pesticides are used in agriculture and several are registered for home use. As young children age they may experience different pesticide exposures due to varying diet, behavior, and other factors. We measured six OP dialkylphosphate (DAP) metabolites (three dimethyl alkylphosphates (DMAP) and three diethyl alkylphosphates (DEAP)) in urine samples collected from ~400 children living in an agricultural community when they were 6, 12, and 24 months old. We examined bivariate associations between DAP metabolite levels and determinants such as age, diet, season, and parent occupation. To evaluate independent impacts, we then used generalized linear mixed multivariable models including interaction terms with age. The final models indicated that DMAP metabolite levels increased with age. DMAP levels were also positively associated with daily servings of produce at 6- and 24-months. Among the 6-month olds, DMAP metabolite levels were higher when samples were collected during the summer/spring versus the winter/fall months. Among the 12-month olds, DMAP and DEAP metabolites were higher when children lived ≤ 60 meters from an agricultural field. Among the 24-month-olds, DEAP metabolite levels were higher during the summer/spring months. Our findings suggest that there are multiple determinants of OP pesticide exposures, notably dietary intake and temporal and spatial proximity to agricultural use. The impact of these determinants varied by age and class of DAP metabolite.

Abstract Background Studies report that residential use of pesticides in low-income homes is common because of poor housing conditions and pest infestations; however, exposure data on contemporary-use pesticides in low-income households is limited. We conducted a study in low-income homes from urban and agricultural communities to: characterize and compare house dust levels of agricultural and residential-use pesticides; evaluate the correlation of pesticide concentrations in samples collected several days apart; examine whether concentrations of pesticides phased-out for residential uses, but still used in agriculture (i.e., chlorpyrifos and diazinon) have declined in homes in the agricultural community; and estimate resident children's pesticide exposures via inadvertent dust ingestion. Methods In 2006, we collected up to two dust samples 5-8 days apart from each of 13 urban homes in Oakland, California and 15 farmworker homes in Salinas, California, an agricultural community (54 samples total). We measured 22 insecticides including organophosphates (chlorpyrifos, diazinon, diazinon-oxon, malathion, methidathion, methyl parathion, phorate, and tetrachlorvinphos) and pyrethroids (allethrin-two isomers, bifenthrin, cypermethrin-four isomers, deltamethrin, esfenvalerate, imiprothrin, permethrin-two isomers, prallethrin, and sumithrin), one phthalate herbicide (chlorthal-dimethyl), one dicarboximide fungicide (iprodione), and one pesticide synergist (piperonyl butoxide). Results More than half of the households reported applying pesticides indoors. Analytes frequently detected in both locations included chlorpyrifos, diazinon, permethrin, allethrin, cypermethrin, and piperonyl butoxide; no differences in concentrations or loadings were observed between locations for these analytes. Chlorthal-dimethyl was detected solely in farmworker homes, suggesting contamination due to regional agricultural use. Concentrations in samples collected 5-8 days apart in the same home were strongly correlated for the majority of the frequently detected analytes (Spearman ρ = 0.70-1.00, p < 0.01). Additionally, diazinon and chlorpyrifos concentrations in Salinas farmworker homes were 40-80% lower than concentrations reported in samples from Salinas farmworker homes studied between 2000-2002, suggesting a temporal reduction after their residential phase-out. Finally, estimated non-dietary pesticide intake for resident children did not exceed current U.S. Environmental Protection Agency's (U.S. EPA) recommended chronic reference doses (RfDs). Conclusion Low-income children are potentially exposed to a mixture of pesticides as a result of poorer housing quality. Historical or current pesticide use indoors is likely to contribute to ongoing exposures. Agricultural pesticide use may also contribute to additional exposures to some pesticides in rural areas. Although children's non-dietary intake did not exceed U.S. EPA RfDs for select pesticides, this does not ensure that children are free of any health risks as RfDs have their own limitations, and the children may be exposed indoors via other pathways. The frequent pesticide use reported and high detection of several home-use pesticides in house dust suggests that families would benefit from integrated pest management strategies to control pests and minimize current and future exposures.

BackgroundWe measured 34 metabolites of current-use pesticides and other precursor compounds in urine samples collected twice during pregnancy from 538 women living in the Salinas Valley of California, a highly agricultural area (1999-2001). Precursors of these metabolites included fungicides, carbamate, organochlorine, organophosphorus (OP), and pyrethroid insecticides, and triazine and chloroacetanilide herbicides. We also measured ethylenethiourea, a metabolite of the ethylene-bisdithiocarbamate fungicides. Repeat measurements of the compounds presented here have not been reported in pregnant women previously. To understand the impact of the women's regional environment on these findings, we compared metabolite concentrations from the CHAMACOS (Center for the Health Assessment of Mothers and Children of Salinas) cohort with U.S. national reference data for 342 pregnant women sampled by the National Health and Nutrition Examination Survey (1999-2002).ResultsThe eight metabolites detected in > 50% of samples [2,4-dichlorophenol (2,4-DCP); 2,5-dichlorophenol (2,5-DCP); 1- and 2-naphthol; ortho-phenylphenol (ORTH); para-nitrophenol (PNP); 2,4,6-trichlorophenol (2,4,6-TCP); and 3,4,6-trichloro-2-pyridinol (TCPy)] may be related to home or agricultural pesticide use in the Salinas Valley, household products, and other sources of chlorinated phenols. More than 78% of women in this study had detectable levels of at least one of the OP pesticide-specific metabolites that we measured, and > 30% had two or more. The 95th percentile values of six of the most commonly detected (> 50%) compounds were significantly higher among the CHAMACOS women after controlling for age, race, socioeconomic status, and smoking [(2,4-DCP; 2,5-DCP; ORTH; PNP; 2,4,6-TCP; and TCPy); quantile regression p < 0.05].ConclusionsFindings suggest that the CHAMACOS cohort has an additional burden of precursor pesticide exposure compared with the national sample, possibly from living and/or working in an agricultural area.

The general European population has a total intake of dioxins and dioxin-like chemicals near the limit recommended by the European Union, making additional exposure above background levels undesirable. For populations living near dioxin contaminated sites additional exposure may occur by intake of locally produced food, inhalation of particles, dermal contact with soils, or by other exposure pathways. Risk assessment tools are required to estimate risks associated with contaminated sites and to set priorities for site remediation. Here, we review several multimedia models that can be applied as tools to support risk assessment. We then and present a strategy to select, apply, evaluate and adapt a model to address a specific situation. The case study we consider is a risk assessment of generic background dioxin exposure in Sweden, and we compare the predictions with environmental observations and exposure data from Sweden. Arguments are presented for selecting the CalTOX model for this case study. We demonstrate the application, evaluation and adaptation of the model, and discuss the requirements for extending the analysis to conduct risk assessment for subpopulations living near dioxin contaminated sites.

Polycyclic aromatic hydrocarbons (PAHs) and particulate matter (PM) are co-pollutants emitted as by-products of combustion processes. Convincing evidence exists for PAHs as a primary toxic component of fine PM (PM2.5). Because PM2.5 is listed by the US EPA as a "Criteria Pollutant," it is monitored regularly at sites nationwide. In contrast, very limited data is available on measured ambient air concentrations of PAHs. However, between 1999-2001, ambient air concentrations of PM2.5 and benzo(a)pyrene (BaP) are available for California locations. We use multivariate linear regression models (MLRMs) to predict ambient air levels of BaP in four air basins based on reported PM2.5 concentrations and spatial, temporal and meteorological variables as variates. We obtain an R2 ranging from 0.57-0.72 among these basins. Significant variables (p

Urban population density may influence transportation demand, e.g., as expressed through average daily vehicle-kilometers traveled in private motor vehicles per capita. In turn, changes in transportation demand influence total passenger vehicle emissions to which populations are exposed. Population density can also influence the fraction of total emissions that are inhaled by the exposed urban population. Equations are presented that describe these relationships for an idealized representation of an urban area. Using analytic solutions to these equations, we investigate the effect of three changes in urban population and urban land area (infill, sprawl, and constant-density growth) on per capita inhalation intake of primary pollutants from passenger vehicles. For the system considered, the magnitude of these effects depends on density–emissions elasticity (εe); a normalized derivative relating change in population density to change in vehicle emissions. For example, based on the idealized representation of the emissions-to-intake relationship presented herein, if urban population increases, then per capita intake is less with infill development than with constant density growth if εe is -0.5, the reverse is true.

Reliable estimates of inhalation intake of air pollution and its distribution among a specified population are important for environmental epidemiology, health risk assessment, urban planning, and environmental policy. We computed distributional characteristics of the inhalation intake of five pollutants for a group of ~25,000 people (~29,000 person-days) living in California’s South Coast Air Basin. Our approach incorporates four main inputs: temporally resolved information about people’s location (latitude and longitude), microenvironment, and activity level; temporally and spatially explicit model determinations of ambient concentrations; stochastically determined microenvironmental adjustment factors relating the exposure concentration to the ambient concentration; and, age-, gender-, and activity-specific breathing rates. Our study is restricted to pollutants of outdoor origin, i.e. it does not incorporate intake in a microenvironment from direct emissions into that microenvironment. Median estimated inhalation intake rates (μgd-1) are 53 for benzene, 5.1 for 1,3-butadiene, 8.7x10-4 for hexavalent chromium in fine particulate matter (Cr-PM2.5), 30 for diesel fine particulate matter (DPM2.5), and 68 for ozone. For the four primary pollutants studied, estimated median intake rates are higher for non-whites and for individuals in low-income households than for the population as a whole. For ozone, a secondary pollutant, the reverse is true. Accounting for microenvironmental adjustment factors, population mobility and temporal correlations between pollutant concentrations and breathing rates affects the estimated inhalation intake by 40% on average. The approach presented here could be extended to quantify the impact on intakes and intake distributions of proposed changes in emissions, air quality, and urban infrastructure.

In Life Cycle Assessment and Comparative Risk Assessment potential human exposure to toxic pollutants can be expressed as the human intake fraction (iF), representing the fraction of the quantity emitted that enters the human population. To assess model uncertainty in the human intake fraction, ingestion and inhalation iFs of 367 substances emitted to air and freshwater were calculated with two commonly applied multi-media fate and exposure models, CalTOX and USES-LCA. Comparison of the model outcomes reveal that uncertainty in the ingestion iFs was up to a factor of 70. The uncertainty in the inhalation iFs was up to a factor of 865,000. The comparison showed that relatively few model differences account for the uncertainties found. An optimal model structure in the calculation of human intake fractions can be achieved by including (1) rain and no-rain scenarios, (2) a continental sea water compartment, (3) drinking water purification, (4) pH-correction of chemical properties, and (5) aerosol-associated deposition on plants. Finally, vertical stratification of the soil compartment combined with a chemical-dependent soil depth may be considered in future intake fraction calculations.