Hybrid Modeling Approach to Estimate Exposures of Hazardous Air Pollutants (HAPs) for the National Air Toxics Assessment (NATA).

A hybrid air quality model has been developed and applied to estimate annual concentrations of 40 hazardous air pollutants (HAPs) across the continental United States (CONUS) to support the 2011 calendar year National Air Toxics Assessment (NATA). By combining a chemical transport model (CTM) with a Gaussian dispersion model, both reactive and nonreactive HAPs are accommodated across local to regional spatial scales, through a multiplicative technique designed to improve mass conservation relative to previous additive methods. The broad scope of multiple pollutants capturing regional to local spatial scale patterns across a vast spatial domain is precedent setting within the air toxics community. The hybrid design exhibits improved performance relative to the stand alone CTM and dispersion model. However, model performance varies widely across pollutant categories and quantifiably definitive performance assessments are hampered by a limited observation base and challenged by the multiple physical and chemical attributes of HAPs. Formaldehyde and acetaldehyde are the dominant HAP concentration and cancer risk drivers, characterized by strong regional signals associated with naturally emitted carbonyl precursors enhanced in urban transport corridors with strong mobile source sector emissions. The multiple pollutant emission characteristics of combustion dominated source sectors creates largely similar concentration patterns across the majority of HAPs. However, reactive carbonyls exhibit significantly less spatial variability relative to nonreactive HAPs across the CONUS.

Analysis of mobile source air toxics (MSATs)--near-road VOC and carbonyl concentrations.

UNLABELLED: Exposures to mobile source air toxics (MSATs) have been associated with numerous adverse health effects. While thousands of air toxic compounds are emitted from mobile sources, members of a subset of compounds are considered high priority due to their significant contribution to cancer and noncancer health risks and the contribution of mobile sources to total exposure as evaluated by the U.S. Environmental Protection Agency (EPA) National-Scale Air Toxics Assessments (NATA). These pollutants include benzene, 1,3-butadiene, ethylbenzene, acrolein, acetaldehyde, formaldehyde, naphthalene, polycyclic organic matter, and diesel particulate matter/organic gases. This study provided year-long trends of benzene, 1,3-butadiene, acrolein, acetaldehyde, and formaldehyde in Las Vegas, NV Results indicated that MSAT concentrations often did not exhibit trends typical of other primary emitted pollutants in this study. Instead, other mobile sources beyond the highway of interest contributed to the measured values, including a major arterial road, a large commercial airport, and a nearby parking lot. The data were compared with relevant census-tract NATA estimates, with estimated ambient 1,3-butadiene concentrations similar to the measured values. Measured benzene values were much lower relative to the NATA total ambient benzene concentrations. Measured acrolein values were much higher relative to the NATA total acrolein concentrations. Measured acetaldehyde and formaldehyde values were also higher relative to the NATA total acetaldehyde and formaldehyde concentrations for all wind conditions and downwind conditions. Some possible explanations for these differences include nearby sources influencing the measured values; meteorological influences that may not be well captured by the NATA modeling regime; chemical reactivity of measured compounds; and additional explanatory variables may be needed for certain urban areas in order to accurately disaggregate anthropogenic air toxics emissions. IMPLICATIONS: Comparison of air toxics concentrations measured at four long-term near-road sites in Las Vegas, NV, show generally good agreement with the EPA 2005 NATA total ambient concentrations. Measured concentrations did not compare as well with EPA 2005 NATA for the on-road mobile portion of the ambient concentrations. This highlights the complexity of air toxic emission sources and impacts in urban areas, especially around large highway facilities; NATA's inability to capture local-scale meteorology and fine-scale ambient gradients; and that additional explanatory variables may be needed for certain urban areas in order to accurately disaggregate anthropogenic air toxics emissions.

An Examination of National Cancer Risk Based on Monitored Hazardous Air Pollutants.

BACKGROUND: Hazardous air pollutants, or air toxics, are pollutants known to cause cancer or other serious health effects. Nationwide cancer risk from these pollutants is estimated by the U.S. EPA National Air Toxics Assessment. However, these model estimates are limited to the totality of the emissions inventory used as inputs, and further, they cannot be used to examine spatial and temporal trends in cancer risk from hazardous air pollutants. OBJECTIVES: To complement model estimates of nationwide cancer risk, we examined trends in cancer risk using monitoring data from 2013 to 2017 across the 27 U.S. National Air Toxics Trends Stations. METHODS: For each monitoring site, we estimated cancer risk by multiplying the annual concentration for each monitored pollutant by its corresponding unit risk estimate. We examined the 5-y average (2013-2017) cancer risk across sites and the population levels and demographics within 1-mi of the monitors, as well as changes in estimated cancer risk over time. Finally, we examined changes in individual pollutant concentrations and their patterns of covariance. RESULTS: We found that the total estimated cancer risk is higher for urban vs. rural sites, with the risk at seven urban sites (of 21) above 75 in 1 million. Furthermore, while most pollutant concentrations have not changed over the time period explored, we found 38 site-pollutant combinations that significantly declined and 12 that significantly increased between 2013 and 2017. We also identified a positive correlation between estimated cancer risk and percent of the population within 1-mi of a monitor that is low income. DISCUSSION: Long-term trends show that annual mean concentrations of most measured air toxics have declined. Our evaluation of a more recent snapshot in time finds that most pollutant concentrations have not changed from 2013 to 2017. This analysis of cancer risk based on monitored values provides an important complement to modeled nationwide cancer risk estimates and can further inform future approaches to mitigate risk from exposure to hazardous air pollutants. https://doi.org/10.1289/EHP8044.

Combining regional- and local-scale air quality models with exposure models for use in environmental health studies.

Population-based human exposure models predict the distribution of personal exposures to pollutants of outdoor origin using a variety of inputs, including air pollution concentrations; human activity patterns, such as the amount of time spent outdoors versus indoors, commuting, walking, and indoors at home; microenvironmental infiltration rates; and pollutant removal rates in indoor environments. Typically, exposure models rely upon ambient air concentration inputs from a sparse network of monitoring stations. Here we present a unique methodology for combining multiple types of air quality models (the Community Multi-Scale Air Quality [CMAQ] chemical transport model added to the AERMOD dispersion model) and linking the resulting hourly concentrations to population exposure models (the Hazardous Air Pollutant Exposure Model [HAPEM] or the Stochastic Human Exposure and Dose Simulation [SHEDS] model) to enhance estimates of air pollution exposures that vary temporally (annual and seasonal) and spatially (at census-block-group resolution) in an urban area. The results indicate that there is a strong spatial gradient in the predicted mean exposure concentrations near roadways and industrial facilities that can vary by almost a factor of 2 across the urban area studied. At the high end of the exposure distribution (95th percentile), exposures are higher in the central district than in the suburbs. This is mostly due to the importance of personal mobility factors whereby individuals living in the central area often move between microenvironments with high concentrations, as opposed to individuals residing at the outskirts of the city. Also, our results indicate 20-30% differences due to commuting patterns and almost a factor of 2 difference because of near-roadway effects. These differences are smaller for the median exposures, indicating the highly variable nature of the reflected ambient concentrations. In conjunction with local data on emission sources, microenvironmental factors, and behavioral and socioeconomic characteristics, the combined source-to-exposure modeling methodology presented in this paper can improve the assessment of exposures in future community air pollution health studies.

Projection of hazardous air pollutant emissions to future years.

Projecting a hazardous air pollutant (HAP) emission inventory to future years can provide valuable information for air quality management activities such as prediction of program successes and helping to assess future priorities. We have projected the 1999 National Emission Inventory for HAPs to numerous future years up to 2020 using the following tools and data: the Emissions Modeling System for Hazardous Air Pollutants (EMS-HAP), the National Mobile Inventory Model (NMIM), emission reduction information resulting from national standards and economic growth data. This paper discusses these projection tools, the underlying data, limitations and the results. The results presented include total HAP emissions (sum of pollutants) and toxicity-weighted HAP emissions for cancer and respiratory noncancer effects. Weighting emissions by toxicity does not consider fate, transport, or location and behavior of receptor populations and can only be used to estimate relative risks of direct emissions. We show these projections, along with historical emission trends. The data show that stationary source programs under Section 112 of the Clean Air Act Amendments of 1990 and mobile source programs which reduce hydrocarbon and particulate matter emissions, as well as toxic emission performance standards for reformulated gasoline, have contributed to and are expected to continue to contribute to large declines in air toxics emissions, in spite of economic and population growth. We have also analyzed the particular HAPs that dominate the source sectors to better understand the historical and future year trends and the differences across sectors.

A modeling framework for characterizing near-road air pollutant concentration at community scales.

In this study, we combine information from transportation network, traffic emissions, and dispersion model to develop a framework to inform exposure estimates for traffic-related air pollutants (TRAPs) with a high spatial resolution. A Research LINE source dispersion model (R-LINE) is used to model multiple TRAPs from roadways at Census-block level for two U.S. regions. We used a novel Space/Time Ordinary Kriging (STOK) approach that uses data from monitoring networks to provide urban background concentrations. To reduce the computational burden, we developed and applied the METeorologically-weighted Averaging for Risk and Exposure (METARE) approach with R-LINE, where a set of selected meteorological data and annual average daily traffic (AADT) are used to obtain annual averages. Compared with explicit modeling, using METARE reduces CPU-time by 88-fold (46.8h versus 32min), while still retaining accuracy of exposure estimates. We show two examples in the Piedmont region in North Carolina (~105,000 receptors) and Portland, Maine (~7000 receptors) to characterize near-road air quality. Concentrations for NOx, PM2.5, and benzene in Portland drop by over 40% within 200m away from the roadway. The concentration drop in North Carolina is less than that in Portland, as previously shown in an observation-based study, showing the robustness of our approach. Heavy-duty diesel vehicles (HDDV) contribute over 55% of NOx and PM2.5 near interstate highways, while light-duty gasoline vehicles (LDGV) contribute over 50% of benzene to urban areas where multiple roadways intersect. Normalized mean error (NME) between explicit modeling and METARE in Portland ranges from 12.6 to 14.5% and normalized mean bias (NMB) ranges from -12.9 to -11.2%. When considering a static emission rate (i.e. the emission does not have temporal variability), both NME and NMB improved (10.5% and -9.5%). Modeled concentrations in Detroit, Michigan at an array of near-road monitors are within a factor of 2 of observed values for CO but not NOx.

Meeting report: Estimating the benefits of reducing hazardous air pollutants--summary of 2009 workshop and future considerations.

BACKGROUND: Quantifying the benefits of reducing hazardous air pollutants (HAPs, or air toxics) has been limited by gaps in toxicological data, uncertainties in extrapolating results from high-dose animal experiments to estimate human effects at lower doses, limited ambient and personal exposure monitoring data, and insufficient economic research to support valuation of the health impacts often associated with exposure to individual air toxics. OBJECTIVES: To address some of these issues, the U.S. Environmental Protection Agency held the Workshop on Estimating the Benefits of Reducing Hazardous Air Pollutants (HAPs) in Washington, DC, from 30 April to 1 May 2009. DISCUSSION: Experts from multiple disciplines discussed how best to move forward on air toxics benefits assessment, with a focus on developing near-term capability to conduct quantitative benefits assessment. Proposed methodologies involved analysis of data-rich pollutants and application of this analysis to other pollutants, using dose-response modeling of animal data for estimating benefits to humans, determining dose-equivalence relationships for different chemicals with similar health effects, and analysis similar to that used for criteria pollutants. Limitations and uncertainties in economic valuation of benefits assessment for HAPS were discussed as well. CONCLUSIONS: These discussions highlighted the complexities in estimating the benefits of reducing air toxics, and participants agreed that alternative methods for benefits assessment of HAPs are needed. Recommendations included clearly defining the key priorities of the Clean Air Act air toxics program to identify the most effective approaches for HAPs benefits analysis, focusing on susceptible and vulnerable populations, and improving dose-response estimation for quantification of benefits.

Modeling population exposures to outdoor sources of hazardous air pollutants.

Accurate assessment of human exposures is an important part of environmental health effects research. However, most air pollution epidemiology studies rely upon imperfect surrogates of personal exposures, such as information based on available central-site outdoor concentration monitoring or modeling data. In this paper, we examine the limitations of using outdoor concentration predictions instead of modeled personal exposures for over 30 gaseous and particulate hazardous air pollutants (HAPs) in the US. The analysis uses the results from an air quality dispersion model (the ASPEN or Assessment System for Population Exposure Nationwide model) and an inhalation exposure model (the HAPEM or Hazardous Air Pollutant Exposure Model, Version 5), applied by the US. Environmental protection Agency during the 1999 National Air Toxic Assessment (NATA) in the US. Our results show that the total predicted chronic exposure concentrations of outdoor HAPs from all sources are lower than the modeled ambient concentrations by about 20% on average for most gaseous HAPs and by about 60% on average for most particulate HAPs (mainly, due to the exclusion of indoor sources from our modeling analysis and lower infiltration of particles indoors). On the other hand, the HAPEM/ASPEN concentration ratio averages for onroad mobile source exposures were found to be greater than 1 (around 1.20) for most mobile-source related HAPs (e.g. 1, 3-butadiene, acetaldehyde, benzene, formaldehyde) reflecting the importance of near-roadway and commuting environments on personal exposures to HAPs. The distribution of the ratios of personal to ambient concentrations was found to be skewed for a number of the VOCs and reactive HAPs associated with major source emissions, indicating the importance of personal mobility factors. We conclude that the increase in personal exposures from the corresponding predicted ambient levels tends to occur near locations where there are either major emission sources of HAPs or when individuals are exposed to either on- or nonroad sources of HAPs during their daily activities. These findings underscore the importance of applying exposure-modeling methods, which incorporate information on time-activity, commuting, and exposure factors data, for the purposes of assigning exposures in air pollution health studies.

Inhalation exposure and risk from mobile source air toxics in future years.

Modeling of inhalation exposure and risks resulting from exposure to mobile source air toxics can be used to evaluate impacts of reductions from control programs on overall risk, as well as changes in relative contributions of different source sectors to risk, changes in contributions of different pollutants to overall risk, and changes in geographic distributions of risk. Such analysis is useful in setting regulatory priorities, and informing the decision-making process. In this paper, we have conducted national-scale air quality, exposure, and risk modeling for the US in the years 2015, 2020, and 2030, using similar tools and methods as the 1999 National-Scale Air Toxics Assessment. Our results suggest that US Environmental Protection Agency emission control programs will substantially reduce average inhalation cancer risks and potential noncancer health risks from exposure to mobile source air toxics. However, cancer risk and noncancer hazard due to inhalation of air toxics will continue to be a public health concern.