A Systematic Review of The Impact of Commercial Aircraft Activity on Air Quality Near Airports.

Commercial airport activity can adversely impact air quality in the vicinity of airports, and millions of people live close to major airports in the United States. Because of these potential impacts, a systematic literature review was conducted to identify peer reviewed literature on air quality near commercial airports and assess the quality of the studies. The systematic review included reference database searches in PubMed, Web of Science, and Google Scholar, inclusive of years 2000 through 2020. We identified 3,301 articles, and based on the inclusion and exclusion criteria developed, seventy studies were identified for extraction and evaluation using a combination of supervised machine learning and manual screening techniques. These studies consistently showed that ultrafine particulate matter (UFP) is elevated in and around airports. Furthermore, many studies show elevated levels of particulate matter under 2.5 microns in diameter (PM2.5), black carbon, criteria pollutants, and polycyclic aromatic hydrocarbons as well. Finally, the systematic review, while not focused on health effects, identified a limited number of on-topic references reporting adverse health effects impacts, including increased rates of premature death, pre-term births, decreased lung function, oxidative DNA damage and childhood leukemia. More research is needed linking particle size distributions to specific airport activities, and proximity to airports, characterizing relationships between different pollutants, evaluating long-term impacts, and improving our understanding of health effects.

Contribution of mobile sources to secondary formation of carbonyl compounds.

In the 2014 National Air Toxics Assessment (NATA), the carbonyl compounds formaldehyde and acetaldehyde were identified as key cancer risk drivers and acrolein was identified as one of the three air toxics that drive most of the noncancer risk. In this assessment, averaged across the Continental United States, about 75% of ambient formaldehyde and acetaldehyde, and about 18% of acrolein, is formed secondarily. This study was conducted to estimate the potential contribution to these secondarily formed carbonyl compounds from mobile sources. To develop such estimates, we conducted several CMAQ runs, where emissions are set to zero for different mobile source sectors, to determine their potential contribution. Although zeroing out emissions from an individual sector can offer only a rough approximation of how the sector might contribute to overall secondary concentrations, our results suggest that across the U. S., mobile sources contribute about 6-18% to secondary formaldehyde, 0-10% to secondary acetaldehyde, and 0-70% to secondary acrolein, depending on location. Implications: Photochemical modeling of carbonyl compounds was conducted with emissions set to zero for various mobile source sectors to determine their contribution to secondary concentrations. Results indicated mobile sources contributed to total and secondary concentrations of formaldehyde, acetaldehyde, and acrolein in many locations across the U.S. with acrolein the dominant contributor in some locations. However, biogenic sources dominated secondary formaldehyde and acetaldehyde, and fires dominated secondary acrolein.

Development of organic gas exhaust speciation profiles for nonroad spark-ignition and compression-ignition engines and equipment.

UNLABELLED: The composition of exhaust emissions from nonroad engines and equipment varies based on a number of parameters, including engine type, emission control technology, fuel composition, and operating conditions. Speciated emissions data which characterize the chemical composition of these emissions are needed to develop chemical speciation profiles used for air quality modeling and to develop air toxics inventories. In this paper, we present results of an extensive review and analysis of available exhaust speciation data for total organic gases (TOG) for spark ignition (SI) engines running on gasoline/ethanol blends now in widespread use, and compression ignition (CI) engines running on diesel fuel. We identified two data sets best suited for development of exhaust speciation profiles. Neither of these data sets have previously been published. We analyzed the resulting speciation profiles for differences in SI engine exhaust composition between 2-stroke and 4-stroke engines using E0 (0% ethanol) and E10 (10% ethanol) blends, and differences in CI engine exhaust composition among engines meeting different emission standards. Exhaust speciation profiles were also analyzed to compare differences in maximum incremental reactivity (MIR) values; this is a useful indicator for evaluating how organic gases may affect ozone formation for air quality modeling. Our analyses found significant differences in speciated emissions from 2-stroke and 4-stroke SI engines, and between engines running on E0 and E10 fuels. We found significant differences in profiles from pre-Tier 1 CI engines, engines meeting Tier 1 standards, and engines meeting Tier 2 standards. Although data for nonroad CI engines meeting tier 4 standards with control devices such as particulate filters and selective catalyst reduction (SCR) devices were not available, data from highway CI engines suggest these technologies will substantially change profiles for nonroad CI engines as well (EPA, 2014c). IMPLICATIONS: The nonroad engine data sets analyzed in this study will substantially improve exhaust speciation profiles used to characterize organic gas emissions from nonroad engines. Since nonroad engines are major contributors to ambient air pollution, these profiles can considerably improve U.S. emission inventories for gaseous air toxics emitted from nonroad engines. The speciation profiles developed in this paper can be used to develop more accurate emission inputs to chemical transport models, leading to more accurate air quality modeling.

Creating locally-resolved mobile-source emissions inputs for air quality modeling in support of an exposure study in Detroit, Michigan, USA.

This work describes a methodology for modeling the impact of traffic-generated air pollutants in an urban area. This methodology presented here utilizes road network geometry, traffic volume, temporal allocation factors, fleet mixes, and emission factors to provide critical modeling inputs. These inputs, assembled from a variety of sources, are combined with meteorological inputs to generate link-based emissions for use in dispersion modeling to estimate pollutant concentration levels due to traffic. A case study implementing this methodology for a large health study is presented, including a sensitivity analysis of the modeling results reinforcing the importance of model inputs and identify those having greater relative impact, such as fleet mix. In addition, an example use of local measurements of fleet activity to supplement model inputs is described, and its impacts to the model outputs are discussed. We conclude that with detailed model inputs supported by local traffic measurements and meteorology, it is possible to capture the spatial and temporal patterns needed to accurately estimate exposure from traffic-related pollutants.

Development and evaluation of alternative approaches for exposure assessment of multiple air pollutants in Atlanta, Georgia.

Measurements from central site (CS) monitors are often used as estimates of exposure in air pollution epidemiological studies. As these measurements are typically limited in their spatiotemporal resolution, true exposure variability within a population is often obscured, leading to potential measurement errors. To fully examine this limitation, we developed a set of alternative daily exposure metrics for each of the 169 ZIP codes in the Atlanta, GA, metropolitan area, from 1999 to 2002, for PM(2.5) and its components (elemental carbon (EC), SO(4)), O(3), carbon monoxide (CO), and nitrogen oxides (NOx). Metrics were applied in a study investigating the respiratory health effects of these pollutants. The metrics included: (i) CS measurements (one CS per pollutant); (ii) air quality model results for regional background pollution; (iii) local-scale AERMOD air quality model results; (iv) hybrid air quality model estimates (a combination of (ii) and (iii)); and (iv) population exposure model predictions (SHEDS and APEX). Differences in estimated spatial and temporal variability were compared by exposure metric and pollutant. Comparisons showed that: (i) both hybrid and exposure model estimates exhibited high spatial variability for traffic-related pollutants (CO, NO(x), and EC), but little spatial variability among ZIP code centroids for regional pollutants (PM(2.5), SO(4), and O(3)); (ii) for all pollutants except NO(x), temporal variability was consistent across metrics; (iii) daily hybrid-to-exposure model correlations were strong (r>0.82) for all pollutants, suggesting that when temporal variability of pollutant concentrations is of main interest in an epidemiological application, the use of estimates from either model may yield similar results; (iv) exposure models incorporating infiltration parameters, time-location-activity budgets, and other exposure factors affect the magnitude and spatiotemporal distribution of exposure, especially for local pollutants. The results of this analysis can inform the development of more appropriate exposure metrics for future epidemiological studies of the short-term effects of particulate and gaseous ambient pollutant exposure in a community.

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.

Resolving local-scale emissions for modeling air quality near roadways.

A large body of literature published in recent years suggests increased health risk due to exposure of people to air pollution in close proximity to roadways. As a result, there is a need to more accurately represent the spatial concentration gradients near roadways to develop mitigation strategies. In this paper, we present a practical, readily adaptable methodology, using a "bottom-up" approach to develop a detailed highway vehicle emission inventory that includes emissions for individual road links. This methodology also takes advantage of geographic information system (GIS) software to improve the spatial accuracy of the activity information obtained from a Travel Demand Model. In addition, we present an air quality modeling application of this methodology in New Haven, CT. This application uses a hybrid modeling approach, in which a regional grid-based model is used to characterize average local ambient concentrations, and a Gaussian dispersion model is used to provide texture within the modeling domain because of spatial gradients associated with highway vehicle emissions and other local sources. Modeling results show substantial heterogeneity of pollutant concentrations within the modeling domain and strong spatial gradients associated with roadways, particularly for pollutants dominated by direct emissions.

Chromium Renderserver: scalable and open remote rendering infrastructure.

Chromium Renderserver (CRRS) is software infrastructure that provides the ability for one or more users to run and view image output from unmodified, interactive OpenGL and X11 applications on a remote, parallel computational platform equipped with graphics hardware accelerators via industry-standard Layer 7 network protocols and client viewers. The new contributions of this work include a solution to the problem of synchronizing X11 and OpenGL command streams, remote delivery of parallel hardware accelerated rendering, and a performance analysis of several different optimizations that are generally applicable to a variety of rendering architectures. CRRS is fully operational, Open Source software. imagery and sending it to a remote viewer.

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.