Matthew Woody

Current and Future Particulate-Matter-Related Mortality Risks in the United States from Aviation Emissions During Landing and Takeoff

Demand for air travel is projected to increase in the upcoming years, with a corresponding influence on emissions, air quality, and public health. The trajectory of health impacts would be influenced by not just emissions growth, but also changes in nonaviation ambient concentrations that influence secondary fine particulate matter (PM(2.5) ) formation, population growth and aging, and potential shifts in PM(2.5) concentration-response functions (CRFs). However, studies to date have not systematically evaluated the individual and joint contributions of these factors to health risk trajectories. In this study, we simulated emissions during landing and takeoff from aircraft at 99 airports across the United States for 2005 and for a 2025 flight activity projection scenario. We applied the Community Multiscale Air Quality (CMAQ) model with the Speciated Modeled Attainment Test (SMAT) to determine the contributions of these emissions to ambient concentrations, including scenarios with 2025 aircraft emissions and 2005 nonaviation air quality. We combined CMAQ outputs with PM(2.5) mortality CRFs and population projections, and evaluated the influence of changing emissions, nonaviation concentrations, and population factors. Given these scenarios, aviation-related health impacts would increase by a factor of 6.1 from 2005 to 2025, with a factor of 2.1 attributable to emissions, a factor of 1.3 attributable to population factors, and a factor of 2.3 attributable to changing nonaviation concentrations which enhance secondary PM(2.5) formation. Our study emphasizes that the public health burden of aviation emissions would be significantly influenced by the joint effects of flight activity increases, nonaviation concentration changes, and population growth and aging.

Chemical transport model simulations of organic aerosol in southern California: model evaluation and gasoline and diesel source contributions

Gasoline- and diesel-fueled engines are ubiquitous sources of air pollution in urban environments. They emit both primary particulate matter and precursor gases that react to form secondary particulate matter in the atmosphere. In this work, we updated the organic aerosol module and organic emissions inventory of a three-dimensional chemical transport model, the Community Multiscale Air Quality Model (CMAQ), using recent, experimentally derived inputs and parameterizations for mobile sources. The updated model included a revised volatile organic compound (VOC) speciation for mobile sources and secondary organic aerosol (SOA) formation from unspeciated intermediate volatility organic compounds (IVOCs). The updated model was used to simulate air quality in southern California during May and June 2010, when the California Research at the Nexus of Air Quality and Climate Change (CalNex) study was conducted. Compared to the Traditional version of CMAQ, which is commonly used for regulatory applications, the updated model did not significantly alter the predicted organic aerosol (OA) mass concentrations but did substantially improve predictions of OA sources and composition (e.g., POA–SOA split), as well as ambient IVOC concentrations. The updated model, despite substantial differences in emissions and chemistry, performed similar to a recently released research version of CMAQ (Woody et al., 2016) that did not include the updated VOC and IVOC emissions and SOA data. Mobile sources were predicted to contribute 30–40 % of the OA in southern California (half of which was SOA), making mobile sources the single largest source contributor to OA in southern California. The remainder of the OA was attributed to non-mobile anthropogenic sources (e.g., cooking, biomass burning) with biogenic sources contributing to less than 5 % to the total OA. Gasoline sources were predicted to contribute about 13 times more OA than diesel sources; this difference was driven by differences in SOA production. Model predictions highlighted the need to better constrain multi-generational oxidation reactions in chemical transport models.

Estimating state-specific contributions to PM2.5- and O3-related health burden from residential combustion and electricity generating unit emissions in the United States

Background: Residential combustion (RC) and electricity generating unit (EGU) emissions adversely impact air quality and human health by increasing ambient concentrations of fine particulate matter (PM2.5) and ozone (O3). Studies to date have not isolated contributing emissions by state of origin (source-state), which is necessary for policy makers to determine efficient strategies to decrease health impacts. Objectives: In this study, we aimed to estimate health impacts (premature mortalities) attributable to PM2.5 and O3 from RC and EGU emissions by precursor species, source sector, and source-state in the continental United States for 2005. Methods: We used the Community Multiscale Air Quality model employing the decoupled direct method to quantify changes in air quality and epidemiological evidence to determine concentration–response functions to calculate associated health impacts. Results: We estimated 21,000 premature mortalities per year from EGU emissions, driven by sulfur dioxide emissions forming PM2.5. More than half of EGU health impacts are attributable to emissions from eight states with significant coal combustion and large downwind populations. We estimate 10,000 premature mortalities per year from RC emissions, driven by primary PM2.5 emissions. States with large populations and significant residential wood combustion dominate RC health impacts. Annual mortality risk per thousand tons of precursor emissions (health damage functions) varied significantly across source-states for both source sectors and all precursor pollutants. Conclusions: Our findings reinforce the importance of pollutant-specific, location-specific, and source-specific models of health impacts in design of health-risk minimizing emissions control policies. Citation: Penn SL, Arunachalam S, Woody M, Heiger-Bernays W, Tripodis Y, Levy JI. 2017. Estimating state-specific contributions to PM2.5- and O3-related health burden from residential combustion and electricity generating unit emissions in the United States. Environ Health Perspect 125:324–332; http://dx.doi.org/10.1289/EHP550

Assessing Model Characterization of Single Source Secondary Pollutant Impacts Using 2013 SENEX Field Study Measurements

Aircraft measurements made downwind from specific coal fired power plants during the 2013 Southeast Nexus field campaign provide a unique opportunity to evaluate single source photochemical model predictions of both O3 and secondary PM2.5 species. The model did well at predicting downwind plume placement. The model shows similar patterns of an increasing fraction of PM2.5 sulfate ion to the sum of SO2 and PM2.5 sulfate ion by distance from the source compared with ambient based estimates. The model was less consistent in capturing downwind ambient based trends in conversion of NOX to NOY from these sources. Source sensitivity approaches capture near-source O3 titration by fresh NO emissions, in particular subgrid plume treatment. However, capturing this near-source chemical feature did not translate into better downwind peak estimates of single source O3 impacts. The model estimated O3 production from these sources but often was lower than ambient based source production. The downwind transect ambient measurements, in particular secondary PM2.5 and O3, have some level of contribution from other sources which makes direct comparison with model source contribution challenging. Model source attribution results suggest contribution to secondary pollutants from multiple sources even where primary pollutants indicate the presence of a single source.

Photochemical model evaluation of 2013 California wild fire air quality impacts using surface, aircraft, and satellite data

The Rim Fire was one of the largest wildfires in California history, burning over 250,000 acres during August and September 2013 affecting air quality locally and regionally in the western U.S. Routine surface monitors, remotely sensed data, and aircraft based measurements were used to assess how well the Community Multiscale Air Quality (CMAQ) photochemical grid model applied at 4 and 12 km resolution represented regional plume transport and chemical evolution during this extreme wildland fire episode. Impacts were generally similar at both grid resolutions although notable differences were seen in some secondary pollutants (e.g., formaldehyde and peroxyacyl nitrate) near the Rim fire. The modeling system does well at capturing near-fire to regional scale smoke plume transport compared to remotely sensed aerosol optical depth (AOD) and aircraft transect measurements. Plume rise for the Rim fire was well characterized as the modeled plume top was consistent with remotely sensed data and the altitude of aircraft measurements, which were typically made at the top edge of the plume. Aircraft-based lidar suggests O3 downwind in the Rim fire plume was vertically stratified and tended to be higher at the plume top, while CMAQ estimated a more uniformly mixed column of O3. Predicted wildfire ozone (O3) was overestimated both at the plume top and at nearby rural and urban surface monitors. Photolysis rates were well characterized by the model compared with aircraft measurements meaning aerosol attenuation was reasonably estimated and unlikely contributing to O3 overestimates at the top of the plume. Organic carbon was underestimated close to the Rim fire compared to aircraft data, but was consistent with nearby surface measurements. Periods of elevated surface PM2.5 at rural monitors near the Rim fire were not usually coincident with elevated O3.

Modeling the Air Quality and Public Health Benefits of Increased Residential Insulation in the United States

According to the Residential Energy Consumption Survey (RECS), homes in the United States consume approximately 10 quadrillion BTUs of energy each year, including electricity consumption for cooling, various fuels utilized for space heating, and other end uses. Electricity consumption will influence emissions from power plants, and these along with direct residential fuel combustion will also contribute to emissions of multiple key pollutants, with corresponding air quality and health impacts. We have developed models to quantify the energy savings associated with increased residential insulation and to estimate in monetary terms the environmental and public health benefits. We are considering both retrofits to existing housing and new construction, focusing on the 2012 International Energy Conservation Code (IECC), which specifies R-values and U-factors by climate zone and a number of other structural components and design specifications. We are applying EnergyPlus to a series of template files to estimate energy savings by fuel type and state, for both retrofits and new construction. To determine the emissions reductions related to reduced electricity generation, we used EPA’s AVERT tool. AVERT uses the basic attributes of electricity dispatch modeling to determine the power plants most likely influenced by energy efficiency programs, and provides the direct nitrogen oxide (NOx), sulfur dioxide (SO2), and carbon dioxide (CO2) emissions reductions on a plant-by-plant basis. For residential combustion, we used EPA’s AP-42 database and other resources to quantify direct emissions by fuel type (including natural gas, fuel oil, and wood). To model the health benefits of the criteria pollutant emissions, we linked the emissions reductions due to increased energy efficiency with the Community Multiscale Air Quality (CMAQ) model. We developed a series of simulations using CMAQ v4.7.1 instrumented with the Decoupled Direct Method (DDM), an advanced sensitivity analysis technique that allows us to estimate the influence of individual pollutants from individual sources or regions. We considered direct residential combustion by state, leveraging Census and housing start data to determine spatial patterns of emissions within states, and modeled individual power plants in geographic groupings using a design of experiments that allow us to estimate the impacts for all major power plants on the grid. We focused on fine particulate matter and ozone concentrations, as the key drivers of monetized health impacts. As CMAQ provides concentration estimates by grid cell, we are able to determine total public health benefits in terms of avoided mortality and morbidity as well as the distribution of those benefits for directly modeled facilities and locations. We estimate 19,000 premature deaths per year associated with EGU emissions, with more than half of the EGU-related health impacts attributable to emissions from seven states with significant coal combustion. We also estimate 10,000 premature deaths per year associated with residential combustion emissions, driven by primary PM2.5 emissions. In general, primary PM2.5 health damage functions are an order of magnitude larger than those of secondary PM2.5 precursors. Our findings reinforce the significance of source-specific assessment of air quality and health impacts for developing public health policies.

Future Year Air Quality Change Due to Growth in Aircraft Emissions and Changes in Climate

Increased growth in aviation activity in the future is projected to show increased emissions from this sector, and hence approximately proportional increases in concentrations if other factors were unchanging. However, emissions from other anthropogenic sources are generally expected to decrease due to several projected emissions control measures, and changes in climate will also occur. In this study, we evaluated air quality changes due to growth in aviation activities from 2005 to 2025, focusing on 99 major U.S. airports with aircraft activity data during landing and takeoff (LTO) activity developed for a growth scenario in 2025. We also assessed changes in climate based upon IPCC RCP 4.5 projections scenario, and used dynamically downscaled meteorology from the Climate Earth System Model (CESM) to WRF over the continental U.S. We performed six annual simulations at 36-km resolution using the WRF-SMOKE-CMAQ modeling system for 2005 and 2025, with and without aircraft emissions, and with and without changes in future year climate from CESM/WRF. We focused on assessing the incremental changes in O3, NO2 and PM2.5 due to changes in emissions (due to aircraft and non-aviation sources) and meteorology. We see a net increase in annual average PM2.5 due to aviation increase from a factor of 5.5 (2025 vs. 2005) without incorporating change in climate to 5.9 with change in climate. Similarly, the changes in summer season average of daily maximum 8-h O3 due to aviation changes from a factor of 3.1–3.3 with change in climate. Both these changes translate to about a ∼7 % additional increase in the future year that we attribute as the “climate penalty” factor. Detailed analyses of the O3 changes show that the effect of change in climate is more pronounced at higher end of concentrations, where the grid-cells with values exceeding the U.S. NAAQS of 75 ppb see a 60 % increase due to change in climate. The changes in 1-h NO2 due to aircraft increase by a factor of ∼2 in 2025 vs. 2005, with increases around major airports being as high as a factor of 6.

An Investigation of the Impacts of Aviation Emissions on Future Air Quality and Health

Recent estimates of the growth in demand for aviation indicate that passenger counts may double or even triple by the year 2025, with a corresponding projected increase in emissions from the aviation sector. This would contribute to approximately proportional increases in concentrations and health effects if other factors were unchanging, but background emissions from non-aviation anthropogenic sources are generally expected to decrease due to several emissions control measures that are likely to be in place, and population size and age distribution will change over time. In this study, we evaluated changes in air quality and health risk due to growth in aviation activities from the year 2005 to 2025, focusing on 99 major U.S. airports with aircraft activity data for landing and takeoff (LTO) based on Terminal Area Forecasts (TAFs) developed for a sample growth scenario under the Next Generation Air Transportation System (NextGen) for 2025. We performed four annual simulations using the MM5-SMOKE-CMAQ modeling system for the year 2005 and 2025, with and without aircraft emissions. We obtained non-aviation emissions for 2005 from EPA’s 2005 National Emissions Inventory (NEI), and projected these to the year 2025. In performing the health risk analyses, we applied the EPA’s Speciated Modeled Attainment Test (SMAT) to the CMAQ results, and compared the air quality and health risk results on a pre-SMAT and post-SMAT basis. Our findings illustrated that each of the time-varying components – background concentrations, emissions, and population patterns – contributes significantly to growth in projected health risks over time, with significant differences in trends by particle constituent and region of the country. The relative importance of various particle constituents also depended significantly on the SMAT process, although secondary sulfate and nitrate particles dominated health risk in all scenarios. These conclusions provide an indication of the factors influencing health risk over time and the resulting areas in which interventions may be most effective.