Assessing Ozone-Related Health Impacts under a Changing Climate

Climate change may increase the frequency and intensity of ozone episodes in future summers in the United States. However, only recently have models become available that can assess the impact of climate change on O(3) concentrations and health effects at regional and local scales that are relevant to adaptive planning. We developed and applied an integrated modeling framework to assess potential O(3)-related health impacts in future decades under a changing climate. The National Aeronautics and Space Administration–Goddard Institute for Space Studies global climate model at 4° × 5° resolution was linked to the Penn State/National Center for Atmospheric Research Mesoscale Model 5 and the Community Multiscale Air Quality atmospheric chemistry model at 36 km horizontal grid resolution to simulate hourly regional meteorology and O(3) in five summers of the 2050s decade across the 31-county New York metropolitan region. We assessed changes in O(3)-related impacts on summer mortality resulting from climate change alone and with climate change superimposed on changes in O(3) precursor emissions and population growth. Considering climate change alone, there was a median 4.5% increase in O(3)-related acute mortality across the 31 counties. Incorporating O(3) precursor emission increases along with climate change yielded similar results. When population growth was factored into the projections, absolute impacts increased substantially. Counties with the highest percent increases in projected O(3) mortality spread beyond the urban core into less densely populated suburban counties. This modeling framework provides a potentially useful new tool for assessing the health risks of climate change

Comparison of multiple PM2.5 exposure products for estimating health benefits of emission controls over New York State, USA

Ambient exposure to fine particulate matter (PM2.5) is one of the top global health concerns. We estimate the PM2.5-related health benefits of emission reduction over New York State (NYS) from 2002 to 2012 using seven publicly available PM2.5 products that include information from ground-based observations, remote sensing and chemical transport models. While these PM2.5 products differ in spatial patterns, they show consistent decreases in PM2.5 by 28%–37% from 2002 to 2012. We evaluate these products using two sets of independent ground-based observations from the New York City Community Air Quality Survey (NYCCAS) Program for an urban area, and the Saint Regis Mohawk Tribe Air Quality Program for a remote area. Inclusion of satellite remote sensing improves the representativeness of surface PM2.5 in the remote area. Of the satellite-based products, only the statistical land use regression approach captures some of the spatial variability across New York City measured by NYCCAS. We estimate the PM2.5-related mortality burden by applying an integrated exposure-response function to the different PM2.5 products. The multi-product mean PM2.5-related mortality burden over NYS decreased by 5660 deaths (67%) from 8410 (95% confidence interval (CI): 4570–12 400) deaths in 2002 to 2750 (CI: 700–5790) deaths in 2012. We estimate a 28% uncertainty in the state-level PM2.5 mortality burden due to the choice of PM2.5 products, but such uncertainty is much smaller than the uncertainty (130%) associated with the exposure-response function

Simulated Effects of Climate Change on Summertime Nitrogen Deposition in the Eastern US

It is anticipated that climate change may impact regional-scale air quality and atmospheric deposition in the coming decades. To simulate the effects of climate change on nitrogen (N) deposition across numerous watersheds in the eastern US, we applied the NASA Goddard Institute for Space Studies General Circulation Model (GISS-GCM), Fifth Generation Pennsylvania State University/National Center for Atmospheric Research Mesoscale Model (MM5), Sparse Matrix Operator Kernel Emissions (SMOKE) modeling system, and the US Environmental Protection Agency Community Multiscale Air Quality (CMAQ) Model. Keeping chemical initial and boundary conditions, land use, and anthropogenic area and point source emissions fixed, this modeling system was applied over five summers (June–August) from 1993 to 1997 and five summers from 2053 to 2057. Over these eastern US watersheds, the modeling system estimated 3–14% increases in summertime N deposition as a result of climate change. This increase is primarily due to the direct effects of climate change on atmospheric conditions and chemistry. Wet N deposition is predicted to increase as a result of increased precipitation, while dry N deposition is predicted to increase as higher surface temperatures favor gas-phase nitric acid to particulate nitrate. The simulated increase suggests that additional reductions in N oxides and/or ammonia may be needed to fully realize the anticipated benefits of planned reduction strategies, including the Clean Air Interstate Rule (CAIR)

Modeling the Impact of Global Climate and Regional Land use Change on Regional Climate and Air Quality Over the Northeastern United States

In recent years, the focus of global climate change research has shifted towards the assessment of regional scale consequences. This paper describes the design and initial results of a modeling study aimed at simulating the effects of global climate change and regional land use change on climate and air quality over the northeastern United States in order to project the associated public health impacts in the region. To this end, modeling tools on a variety of scales are being linked. Specifically, regional climate models are linked to both a global climate model and a regional land-use change model. Outputs from regional climate simulations are subsequently used both to assess changes in public health due to heat stress and to simulate regional and urban air quality. Finally, results from these air quality simulations are coupled to health impact models. This paper focuses on the air quality modeling aspect of the project. Global and regional climate change could conceivably alter regional and urban air quality in a variety of ways through both direct and indirect effects. Rising temperatures could have a direct effect on chemical reaction rates and mixed-layer heights, while changes in synoptic circulation patterns might influence the transport and mixing of pollutants as well as the occurrence of conditions conducive to high ozone concentrations. Additionally, anthropogenic emissions of the ozone precursors NOx and VOC are also expected to change in future decades, and it is necessary to understand whether future ozone air quality is more sensitive to changes in emissions or changes in climate. In this paper, we present initial results from regional-scale simulations for 3-months summer seasons under current and future climate conditions

Comparison of multiple PM2.5 exposure products for estimating health benefits of emission controls over New York State, USA

Ambient exposure to fine particulate matter (PM _2.5 ) is one of the top global health concerns. We estimate the PM _2.5 -related health benefits of emission reduction over New York State (NYS) from 2002 to 2012 using seven publicly available PM _2.5 products that include information from ground-based observations, remote sensing and chemical transport models. While these PM _2.5 products differ in spatial patterns, they show consistent decreases in PM _2.5 by 28%–37% from 2002 to 2012. We evaluate these products using two sets of independent ground-based observations from the New York City Community Air Quality Survey (NYCCAS) Program for an urban area, and the Saint Regis Mohawk Tribe Air Quality Program for a remote area. Inclusion of satellite remote sensing improves the representativeness of surface PM _2.5 in the remote area. Of the satellite-based products, only the statistical land use regression approach captures some of the spatial variability across New York City measured by NYCCAS. We estimate the PM _2.5 -related mortality burden by applying an integrated exposure-response function to the different PM _2.5 products. The multi-product mean PM _2.5 -related mortality burden over NYS decreased by 5660 deaths (67%) from 8410 (95% confidence interval (CI): 4570–12 400) deaths in 2002 to 2750 (CI: 700–5790) deaths in 2012. We estimate a 28% uncertainty in the state-level PM _2.5 mortality burden due to the choice of PM _2.5 products, but such uncertainty is much smaller than the uncertainty (130%) associated with the exposure-response function

Associations between ozone and morbidity using the Spatial Synoptic Classification system

<p>Abstract</p> <p>Background</p> <p>Synoptic circulation patterns (large-scale tropospheric motion systems) affect air pollution and, potentially, air-pollution-morbidity associations. We evaluated the effect of synoptic circulation patterns (air masses) on the association between ozone and hospital admissions for asthma and myocardial infarction (MI) among adults in North Carolina.</p> <p>Methods</p> <p>Daily surface meteorology data (including precipitation, wind speed, and dew point) for five selected cities in North Carolina were obtained from the U.S. EPA Air Quality System (AQS), which were in turn based on data from the National Climatic Data Center of the National Oceanic and Atmospheric Administration. We used the Spatial Synoptic Classification system to classify each day of the 9-year period from 1996 through 2004 into one of seven different air mass types: dry polar, dry moderate, dry tropical, moist polar, moist moderate, moist tropical, or transitional. Daily 24-hour maximum 1-hour ambient concentrations of ozone were obtained from the AQS. Asthma and MI hospital admissions data for the 9-year period were obtained from the North Carolina Department of Health and Human Services. Generalized linear models were used to assess the association of the hospitalizations with ozone concentrations and specific air mass types, using pollutant lags of 0 to 5 days. We examined the effect across cities on days with the same air mass type. In all models we adjusted for dew point and day-of-the-week effects related to hospital admissions.</p> <p>Results</p> <p>Ozone was associated with asthma under dry tropical (1- to 5-day lags), transitional (3- and 4-day lags), and extreme moist tropical (0-day lag) air masses. Ozone was associated with MI only under the extreme moist tropical (5-day lag) air masses.</p> <p>Conclusions</p> <p>Elevated ozone levels are associated with dry tropical, dry moderate, and moist tropical air masses, with the highest ozone levels being associated with the dry tropical air mass. Certain synoptic circulation patterns/air masses in conjunction with ambient ozone levels were associated with increased asthma and MI hospitalizations.</p