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Transient climate and ambient health impacts due to national solid fuel cookstove emissions. Proc Natl Acad Sci U S A 2017; 114:1269-1274. [PMID: 28115698 DOI: 10.1073/pnas.1612430114] [Citation(s) in RCA: 47] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Residential solid fuel use contributes to degraded indoor and ambient air quality and may affect global surface temperature. However, the potential for national-scale cookstove intervention programs to mitigate the latter issues is not yet well known, owing to the spatial heterogeneity of aerosol emissions and impacts, along with coemitted species. Here we use a combination of atmospheric modeling, remote sensing, and adjoint sensitivity analysis to individually evaluate consequences of a 20-y linear phase-out of cookstove emissions in each country with greater than 5% of the population using solid fuel for cooking. Emissions reductions in China, India, and Ethiopia contribute to the largest global surface temperature change in 2050 [combined impact of -37 mK (11 mK to -85 mK)], whereas interventions in countries less commonly targeted for cookstove mitigation such as Azerbaijan, Ukraine, and Kazakhstan have the largest per cookstove climate benefits. Abatement in China, India, and Bangladesh contributes to the largest reduction of premature deaths from ambient air pollution, preventing 198,000 (102,000-204,000) of the 260,000 (137,000-268,000) global annual avoided deaths in 2050, whereas again emissions in Ukraine and Azerbaijan have the largest per cookstove impacts, along with Romania. Global cookstove emissions abatement results in an average surface temperature cooling of -77 mK (20 mK to -278 mK) in 2050, which increases to -118 mK (-11 mK to -335 mK) by 2100 due to delayed CO2 response. Health impacts owing to changes in ambient particulate matter with an aerodynamic diameter of 2.5 μm or less (PM2.5) amount to ∼22.5 million premature deaths prevented between 2000 and 2100.
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Silva RA, Adelman Z, Fry MM, West JJ. The Impact of Individual Anthropogenic Emissions Sectors on the Global Burden of Human Mortality due to Ambient Air Pollution. ENVIRONMENTAL HEALTH PERSPECTIVES 2016; 124:1776-1784. [PMID: 27177206 PMCID: PMC5089880 DOI: 10.1289/ehp177] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/09/2015] [Revised: 01/01/2016] [Accepted: 04/26/2016] [Indexed: 05/11/2023]
Abstract
BACKGROUND Exposure to ozone and fine particulate matter (PM2.5) can cause adverse health effects, including premature mortality due to cardiopulmonary diseases and lung cancer. Recent studies quantify global air pollution mortality but not the contribution of different emissions sectors, or they focus on a specific sector. OBJECTIVES We estimated the global mortality burden of anthropogenic ozone and PM2.5, and the impact of five emissions sectors, using a global chemical transport model at a finer horizontal resolution (0.67° × 0.5°) than previous studies. METHODS We performed simulations for 2005 using the Model for Ozone and Related Chemical Tracers, version 4 (MOZART-4), zeroing out all anthropogenic emissions and emissions from specific sectors (All Transportation, Land Transportation, Energy, Industry, and Residential and Commercial). We estimated premature mortality using a log-linear concentration-response function for ozone and an integrated exposure-response model for PM2.5. RESULTS We estimated 2.23 (95% CI: 1.04, 3.33) million deaths/year related to anthropogenic PM2.5, with the highest mortality in East Asia (48%). The Residential and Commercial sector had the greatest impact globally-675 (95% CI: 428, 899) thousand deaths/year-and in most regions. Land Transportation dominated in North America (32% of total anthropogenic PM2.5 mortality), and it had nearly the same impact (24%) as Residential and Commercial (27%) in Europe. Anthropogenic ozone was associated with 493 (95% CI: 122, 989) thousand deaths/year, with the Land Transportation sector having the greatest impact globally (16%). CONCLUSIONS The contributions of emissions sectors to ambient air pollution-related mortality differ among regions, suggesting region-specific air pollution control strategies. Global sector-specific actions targeting Land Transportation (ozone) and Residential and Commercial (PM2.5) sectors would particularly benefit human health. Citation: Silva RA, Adelman Z, Fry MM, West JJ. 2016. The impact of individual anthropogenic emissions sectors on the global burden of human mortality due to ambient air pollution. Environ Health Perspect 124:1776-1784; http://dx.doi.org/10.1289/EHP177.
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Affiliation(s)
| | | | | | - J. Jason West
- Address correspondence to J.J. West, 146B Rosenau Hall CB #7431, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 USA. Telephone: (919) 843-3928. E-mail:
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53
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Influence of Grid Resolution in Modeling of Air Pollution from Open Burning. ATMOSPHERE 2016. [DOI: 10.3390/atmos7070093] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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54
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Madaniyazi L, Nagashima T, Guo Y, Pan X, Tong S. Projecting ozone-related mortality in East China. ENVIRONMENT INTERNATIONAL 2016; 92-93:165-172. [PMID: 27104674 DOI: 10.1016/j.envint.2016.03.040] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2015] [Revised: 03/25/2016] [Accepted: 03/28/2016] [Indexed: 06/05/2023]
Abstract
BACKGROUND The concentrations of ozone (O3) in China are increasing, especially in East China, but its future trends and potential health impacts remain to be explored. OBJECTIVES The objective was to assess future trends in O3 concentrations and related premature death in East China between 2005 and 2030. METHODS First, a global chemical transport model (MIROC-ESM-CHEM) and regional chemical transport modelling system (including the Weather Research and Forecasting model and the Community Multiscale Air Quality model) were combined to estimate daily O3 concentrations in 2005 and 2030 in East China under the "current legislation" (CLE) and "maximum technically feasible reduction" (MFR) scenarios which were applied globally. O3 concentrations were then linked with population projections, mortality projections, and O3-mortality associations to estimate changes in O3-related mortality in East China. RESULTS The annual mean O3 concentration was projected to increase in East China between 2005 and 2030 under the CLE scenario, while decrease under the MFR scenario. Under the CLE scenario, O3-attributable health burden could increase by at least 40,000 premature deaths in East China, without considering the population growth. Under the MFR scenario, the health burden could decrease by up to 260,000 premature deaths as a result of the reduction in O3 concentration with a static population. However, when the population growth was considered, O3-attributable health burden could increase by up to 46,000 premature deaths in East China under the MFR scenario. CONCLUSIONS The results suggest that the health burden attributable to O3 may increase in East China in 2030.
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Affiliation(s)
- Lina Madaniyazi
- School of Public Health and Social Work, Kelvin Grove, QLD 4059, Australia
| | - Tatsuya Nagashima
- Center for Regional Environmental Research (Regional Atmospheric Modelling Section), National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan
| | - Yuming Guo
- School of Public Health, University of Queensland, Herston, QLD 4006, Australia
| | - Xiaochuan Pan
- School of Public Health, Peking University, Beijing, China
| | - Shilu Tong
- School of Public Health and Social Work, Kelvin Grove, QLD 4059, Australia.
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55
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Heo J, Adams PJ, Gao HO. Public Health Costs of Primary PM2.5 and Inorganic PM2.5 Precursor Emissions in the United States. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2016; 50:6061-70. [PMID: 27153150 DOI: 10.1021/acs.est.5b06125] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Current methods of estimating the public health effects of emissions are computationally too expensive or do not fully address complex atmospheric processes, frequently limiting their applications to policy research. Using a reduced-form model derived from tagged chemical transport model (CTM) simulations, we present PM2.5 mortality costs per tonne of inorganic air pollutants with the 36 km × 36 km spatial resolution of source location in the United States, providing the most comprehensive set of such estimates comparable to CTM-based estimates. Our estimates vary by 2 orders of magnitude. Emission-weighted seasonal averages were estimated at $88,000-130,000/t PM2.5 (inert primary), $14,000-24,000/t SO2, $3,800-14,000/t NOx, and $23,000-66,000/t NH3. The aggregate social costs for year 2005 emissions were estimated at $1.0 trillion dollars. Compared to other studies, our estimates have similar magnitudes and spatial distributions for primary PM2.5 but substantially different spatial patterns for precursor species where secondary chemistry is important. For example, differences of more than a factor of 10 were found in many areas of Texas, New Mexico, and New England states for NOx and of California, Texas, and Maine for NH3. Our method allows for updates as emissions inventories and CTMs improve, enhancing the potential to link policy research to up-to-date atmospheric science.
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Affiliation(s)
| | | | - H Oliver Gao
- School of Civil and Environmental Engineering, Cornell University , Ithaca, New York 14853, United States
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56
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West JJ, Cohen A, Dentener F, Brunekreef B, Zhu T, Armstrong B, Bell ML, Brauer M, Carmichael G, Costa DL, Dockery DW, Kleeman M, Krzyzanowski M, Künzli N, Liousse C, Lung SCC, Martin RV, Pöschl U, Pope CA, Roberts JM, Russell AG, Wiedinmyer C. "What We Breathe Impacts Our Health: Improving Understanding of the Link between Air Pollution and Health". ENVIRONMENTAL SCIENCE & TECHNOLOGY 2016; 50:4895-904. [PMID: 27010639 DOI: 10.1021/acs.est.5b03827] [Citation(s) in RCA: 159] [Impact Index Per Article: 19.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
Air pollution contributes to the premature deaths of millions of people each year around the world, and air quality problems are growing in many developing nations. While past policy efforts have succeeded in reducing particulate matter and trace gases in North America and Europe, adverse health effects are found at even these lower levels of air pollution. Future policy actions will benefit from improved understanding of the interactions and health effects of different chemical species and source categories. Achieving this new understanding requires air pollution scientists and engineers to work increasingly closely with health scientists. In particular, research is needed to better understand the chemical and physical properties of complex air pollutant mixtures, and to use new observations provided by satellites, advanced in situ measurement techniques, and distributed micro monitoring networks, coupled with models, to better characterize air pollution exposure for epidemiological and toxicological research, and to better quantify the effects of specific source sectors and mitigation strategies.
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Affiliation(s)
- J Jason West
- Environmental Sciences & Engineering, University of North Carolina at Chapel Hill , Chapel Hill, North Carolina 27599, United States
| | - Aaron Cohen
- Health Effects Institute, Boston, Massachusetts 02110, United States
| | - Frank Dentener
- European Commission, Joint Research Centre, Institute for Environment and Sustainability, I. 21027 Ispra, Italy
| | - Bert Brunekreef
- Institute for Risk Assessment Sciences, Universiteit Utrecht, and Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht , 3584 CJ Utrecht, The Netherlands
| | - Tong Zhu
- State Key Lab for Environmental Simulation and Pollution Control, College of Environmental Science and Engineering, Peking University , Beijing 100871, China
| | - Ben Armstrong
- Social and Environmental Health Research, London School of Hygiene & Tropical Medicine , London WC1E 7HT, United Kingdom
| | - Michelle L Bell
- School of Forestry & Environmental Studies, Yale University , New Haven, Connecticut 06511, United States
| | - Michael Brauer
- School of Population and Public Health, University of British Columbia , Vancouver, British Columbia V6T 1Z3, Canada
| | - Gregory Carmichael
- Chemical and Biochemical Engineering, University of Iowa , Iowa City, Iowa 52242, United States
| | - Dan L Costa
- Air, Climate & Energy Research Program, Office of Research & Development, Environmental Protection Agency, Durham, North Carolina 27705, United States
| | - Douglas W Dockery
- Harvard T. H. Chan School of Public Health , Boston, Massachusetts 02115, United States
| | - Michael Kleeman
- Civil and Environmental Engineering, University of California at Davis , Davis, California 95616, United States
| | - Michal Krzyzanowski
- Environmental Research Group, King's College London, London SE1 9NH, United Kingdom
| | - Nino Künzli
- Epidemiology and Public Health, Swiss Tropical and Public Health Institute , Basel, Switzerland
- University of Basel , Basel, Switzerland
| | - Catherine Liousse
- Laboratoire d' Aérologie, CNRS-Université de Toulouse , Toulouse 31400, France
| | | | - Randall V Martin
- Physics and Atmospheric Science, Dalhousie University , Halifax, Nova Scotia B3H 4R2, Canada
- Harvard-Smithsonian Center for Astrophysics, Cambridge, Massachusetts 02138, United States
| | - Ulrich Pöschl
- Multiphase Chemistry Department, Max Planck Institute for Chemistry, 55128 Mainz, Germany
| | - C Arden Pope
- Economics, Brigham Young University , Provo, Utah 84602, United States
| | - James M Roberts
- Earth System Research Laboratory, Chemical Sciences Division, National Oceanic & Atmospheric Administration, Boulder, Colorado 80305, United States
| | - Armistead G Russell
- Civil & Environmental Engineering, Georgia Institute of Technology , Atlanta, Georgia 30332, United States
| | - Christine Wiedinmyer
- Atmospheric Chemistry Observations and Modeling Laboratory, National Center for Atmospheric Research, Boulder, Colorado 80301, United States
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57
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Li Y, Henze DK, Jack D, Kinney PL. The influence of air quality model resolution on health impact assessment for fine particulate matter and its components. AIR QUALITY, ATMOSPHERE, & HEALTH 2016; 9:51-68. [PMID: 28659994 PMCID: PMC5484574 DOI: 10.1007/s11869-015-0321-z] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/19/2023]
Abstract
Health impact assessments for fine particulate matter (PM2.5) often rely on simulated concentrations generated from air quality models. However, at the global level, these models often run at coarse resolutions, resulting in underestimates of peak concentrations in populated areas. This study aims to quantitatively examine the influence of model resolution on the estimates of mortality attributable to PM2.5 and its species in the USA. We use GEOS-Chem, a global 3-D model of atmospheric composition, to simulate the 2008 annual average concentrations of PM2.5 and its six species over North America. The model was run at a fine resolution of 0.5 × 0.66° and a coarse resolution of 2 × 2.5°, and mortality was calculated using output at the two resolutions. Using the fine-modeled concentrations, we estimate that 142,000 PM2.5-related deaths occurred in the USA in 2008, and the coarse resolution produces a national mortality estimate that is 8 % lower than the fine-model estimate. Our spatial analysis of mortality shows that coarse resolutions tend to substantially underestimate mortality in large urban centers. We also re-grid the fine-modeled concentrations to several coarser resolutions and repeat mortality calculation at these resolutions. We found that model resolution tends to have the greatest influence on mortality estimates associated with primary species and the least impact on dust-related mortality. Our findings provide evidence of possible biases in quantitative PM2.5 health impact assessments in applications of global atmospheric models at coarse spatial resolutions.
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Affiliation(s)
- Ying Li
- Department of Environmental Health, College of Public Health, East Tennessee State University, PO Box 70682, Johnson City, TN, USA
| | - Daven K Henze
- Department of Mechanical Engineering, University of Colorado at Boulder, 1111 Engineering Drive UCB 427, Boulder, CO, USA
| | - Darby Jack
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, 722 West 168th Street, New York, NY, USA
| | - Patrick L Kinney
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, 722 West 168th Street, New York, NY, USA
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58
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Silva RA, West JJ, Lamarque JF, Shindell DT, Collins WJ, Dalsoren S, Faluvegi G, Folberth G, Horowitz LW, Nagashima T, Naik V, Rumbold ST, Sudo K, Takemura T, Bergmann D, Cameron-Smith P, Cionni I, Doherty RM, Eyring V, Josse B, MacKenzie IA, Plummer D, Righi M, Stevenson DS, Strode S, Szopa S, Zeng G. The effect of future ambient air pollution on human premature mortality to 2100 using output from the ACCMIP model ensemble. ATMOSPHERIC CHEMISTRY AND PHYSICS 2016; 16:9847-9862. [PMID: 29250104 PMCID: PMC5730074 DOI: 10.5194/acp-16-9847-2016] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
Ambient air pollution from ground-level ozone and fine particulate matter (PM2.5) is associated with premature mortality. Future concentrations of these air pollutants will be driven by natural and anthropogenic emissions and by climate change. Using anthropogenic and biomass burning emissions projected in the four Representative Concentration Pathway scenarios (RCPs), the ACCMIP ensemble of chemistry-climate models simulated future concentrations of ozone and PM2.5 at selected decades between 2000 and 2100. We use output from the ACCMIP ensemble, together with projections of future population and baseline mortality rates, to quantify the human premature mortality impacts of future ambient air pollution. Future air pollution-related premature mortality in 2030, 2050 and 2100 is estimated for each scenario and for each model using a health impact function based on changes in concentrations of ozone and PM2.5 relative to 2000 and projected future population and baseline mortality rates. Additionally, the global mortality burden of ozone and PM2.5 in 2000 and each future period is estimated relative to 1850 concentrations, using present-day and future population and baseline mortality rates. The change in future ozone concentrations relative to 2000 is associated with excess global premature mortality in some scenarios/periods, particularly in RCP8.5 in 2100 (316 thousand deaths/year), likely driven by the large increase in methane emissions and by the net effect of climate change projected in this scenario, but it leads to considerable avoided premature mortality for the three other RCPs. However, the global mortality burden of ozone markedly increases from 382,000 (121,000 to 728,000) deaths/year in 2000 to between 1.09 and 2.36 million deaths/year in 2100, across RCPs, mostly due to the effect of increases in population and baseline mortality rates. PM2.5 concentrations decrease relative to 2000 in all scenarios, due to projected reductions in emissions, and are associated with avoided premature mortality, particularly in 2100: between -2.39 and -1.31 million deaths/year for the four RCPs. The global mortality burden of PM2.5 is estimated to decrease from 1.70 (1.30 to 2.10) million deaths/year in 2000 to between 0.95 and 1.55 million deaths/year in 2100 for the four RCPs, due to the combined effect of decreases in PM2.5 concentrations and changes in population and baseline mortality rates. Trends in future air pollution-related mortality vary regionally across scenarios, reflecting assumptions for economic growth and air pollution control specific to each RCP and region. Mortality estimates differ among chemistry-climate models due to differences in simulated pollutant concentrations, which is the greatest contributor to overall mortality uncertainty for most cases assessed here, supporting the use of model ensembles to characterize uncertainty. Increases in exposed population and baseline mortality rates of respiratory diseases magnify the impact on premature mortality of changes in future air pollutant concentrations and explain why the future global mortality burden of air pollution can exceed the current burden, even where air pollutant concentrations decrease.
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Affiliation(s)
- Raquel A Silva
- Environmental Sciences and Engineering, University of North Carolina, Chapel Hill, North Carolina, USA
| | - J Jason West
- Environmental Sciences and Engineering, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Jean-François Lamarque
- NCAR Earth System Laboratory, National Center for Atmospheric Research, Boulder, Colorado, USA
| | - Drew T Shindell
- Nicholas School of the Environment, Duke University, Durham, North Carolina, USA
| | - William J Collins
- Department of Meteorology, University of Reading, Reading, United Kingdom
| | - Stig Dalsoren
- CICERO, Center for International Climate and Environmental Research-Oslo, Oslo, Norway
| | - Greg Faluvegi
- NASA Goddard Institute for Space Studies and Columbia Earth Institute, New York, New York, USA
| | | | - Larry W Horowitz
- NOAA Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey, USA
| | | | - Vaishali Naik
- NOAA Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey, USA
| | | | - Kengo Sudo
- Earth and Environmental Science, Graduate School of Environmental Studies, Nagoya University, Nagoya, Japan
| | - Toshihiko Takemura
- Research Institute for Applied Mechanics, Kyushu University, Fukuoka, Japan
| | - Daniel Bergmann
- Lawrence Livermore National Laboratory, Livermore, California, USA
| | | | - Irene Cionni
- Agenzia Nazionale per le Nuove Tecnologie, l'Energia e lo Sviluppo Economico Sostenibile (ENEA), Bologna, Italy
| | - Ruth M Doherty
- School of GeoSciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Veronika Eyring
- Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
| | - Beatrice Josse
- GAME/CNRM, Meteo-France, CNRS-Centre National de Recherches Meteorologiques, Toulouse, France
| | - I A MacKenzie
- School of GeoSciences, University of Edinburgh, Edinburgh, United Kingdom
| | - David Plummer
- Canadian Centre for Climate Modeling and Analysis, Environment Canada, Victoria, British Columbia, Canada
| | - Mattia Righi
- Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
| | - David S Stevenson
- School of GeoSciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Sarah Strode
- NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
- Universities Space Research Association, Columbia, Maryland, USA
| | - Sophie Szopa
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE-CEA-CNRS-UVSQ, Gif-sur-Yvette, France
| | - Guang Zeng
- National Institute of Water and Atmospheric Research, Lauder, New Zealand
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59
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Li Y, Henze DK, Jack D, Henderson BH, Kinney PL. Assessing public health burden associated with exposure to ambient black carbon in the United States. THE SCIENCE OF THE TOTAL ENVIRONMENT 2016; 539:515-525. [PMID: 26383853 PMCID: PMC4761114 DOI: 10.1016/j.scitotenv.2015.08.129] [Citation(s) in RCA: 49] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/01/2015] [Revised: 08/17/2015] [Accepted: 08/25/2015] [Indexed: 05/21/2023]
Abstract
Black carbon (BC) is a significant component of fine particulate matter (PM2.5) air pollution, which has been linked to a series of adverse health effects, in particular premature mortality. Recent scientific research indicates that BC also plays an important role in climate change. Therefore, controlling black carbon emissions provides an opportunity for a double dividend. This study quantifies the national burden of mortality and morbidity attributable to exposure to ambient BC in the United States (US). We use GEOS-Chem, a global 3-D model of atmospheric composition to estimate the 2010 annual average BC levels at 0.5×0.667° resolution, and then re-grid to 12-km grid resolution across the continental US. Using PM2.5 mortality risk coefficient drawn from the American Cancer Society cohort study, the numbers of deaths due to BC exposure were estimated for each 12-km grid, and then aggregated to the county, state and national level. Given evidence that BC particles may pose a greater risk on human health than other components of PM2.5, we also conducted sensitivity analysis using BC-specific risk coefficients drawn from recent literature. We estimated approximately 14,000 deaths to result from the 2010 BC levels, and hundreds of thousands of illness cases, ranging from hospitalizations and emergency department visits to minor respiratory symptoms. Sensitivity analysis indicates that the total BC-related mortality could be even significantly larger than the above mortality estimate. Our findings indicate that controlling BC emissions would have substantial benefits for public health in the US.
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Affiliation(s)
- Ying Li
- Department of Environmental Health, College of Public Health, East Tennessee State University, Johnson City, TN, USA
| | - Daven K Henze
- Department of Mechanical Engineering, University of Colorado at Boulder, Boulder, CO, USA
| | - Darby Jack
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Barron H Henderson
- Department of Environmental Engineering Sciences, University of Florida, Gainesville, FL, USA
| | - Patrick L Kinney
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA.
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60
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Ford B, Heald CL. Exploring the Uncertainty Associated with Satellite-Based Estimates of Premature Mortality due to Exposure to Fine Particulate Matter. ATMOSPHERIC CHEMISTRY AND PHYSICS 2016; 16:3499-3523. [PMID: 28649266 PMCID: PMC5482289 DOI: 10.5194/acp-16-3499-2016] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
The negative impacts of fine particulate matter (PM2.5) exposure on human health are a primary motivator for air quality research. However, estimates of the air pollution health burden vary considerably and strongly depend on the datasets and methodology. Satellite observations of aerosol optical depth (AOD) have been widely used to overcome limited coverage from surface monitoring and to assess the global population exposure to PM2.5 and the associated premature mortality. Here we quantify the uncertainty in determining the burden of disease using this approach, discuss different methods and datasets, and explain sources of discrepancies among values in the literature. For this purpose we primarily use the MODIS satellite observations in concert with the GEOS-Chem chemical transport model. We contrast results in the United States and China for the years 2004-2011. Using the Burnett et al. (2014) integrated exposure response function, we estimate that in the United States, exposure to PM2.5 accounts for approximately 2% of total deaths compared to 14% in China (using satellite-based exposure), which falls within the range of previous estimates. The difference in estimated mortality burden based solely on a global model vs. that derived from satellite is approximately 14% for the U.S. and 2% for China on a nationwide basis, although regionally the differences can be much greater. This difference is overshadowed by the uncertainty in the methodology for deriving PM2.5 burden from satellite observations, which we quantify to be on the order of 20% due to uncertainties in the AOD-to-surface-PM2.5 relationship, 10% due to the satellite observational uncertainty, and 30% or greater uncertainty associated with the application of concentration response functions to estimated exposure.
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Affiliation(s)
- Bonne Ford
- Department of Atmospheric Science, Colorado State University, Fort Collins, CO, USA
- Correspondence to: B. Ford ()
| | - Colette L. Heald
- Department of Civil and Environmental Engineering and Department of Earth, Atmospheric and Planetary Sciences, MIT, Cambridge, MA, USA
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61
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Martenies SE, Wilkins D, Batterman SA. Health impact metrics for air pollution management strategies. ENVIRONMENT INTERNATIONAL 2015; 85:84-95. [PMID: 26372694 PMCID: PMC4648637 DOI: 10.1016/j.envint.2015.08.013] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/03/2015] [Revised: 08/11/2015] [Accepted: 08/24/2015] [Indexed: 05/24/2023]
Abstract
Health impact assessments (HIAs) inform policy and decision making by providing information regarding future health concerns, and quantitative HIAs now are being used for local and urban-scale projects. HIA results can be expressed using a variety of metrics that differ in meaningful ways, and guidance is lacking with respect to best practices for the development and use of HIA metrics. This study reviews HIA metrics pertaining to air quality management and presents evaluative criteria for their selection and use. These are illustrated in a case study where PM2.5 concentrations are lowered from 10 to 8μg/m(3) in an urban area of 1.8 million people. Health impact functions are used to estimate the number of premature deaths, unscheduled hospitalizations and other morbidity outcomes. The most common metric in recent quantitative HIAs has been the number of cases of adverse outcomes avoided. Other metrics include time-based measures, e.g., disability-adjusted life years (DALYs), monetized impacts, functional-unit based measures, e.g., benefits per ton of emissions reduced, and other economic indicators, e.g., cost-benefit ratios. These metrics are evaluated by considering their comprehensiveness, the spatial and temporal resolution of the analysis, how equity considerations are facilitated, and the analysis and presentation of uncertainty. In the case study, the greatest number of avoided cases occurs for low severity morbidity outcomes, e.g., asthma exacerbations (n=28,000) and minor-restricted activity days (n=37,000); while DALYs and monetized impacts are driven by the severity, duration and value assigned to a relatively low number of premature deaths (n=190 to 230 per year). The selection of appropriate metrics depends on the problem context and boundaries, the severity of impacts, and community values regarding health. The number of avoided cases provides an estimate of the number of people affected, and monetized impacts facilitate additional economic analyses useful to policy analysis. DALYs are commonly used as an aggregate measure of health impacts and can be used to compare impacts across studies. Benefits per ton metrics may be appropriate when changes in emissions rates can be estimated. To address community concerns and HIA objectives, a combination of metrics is suggested.
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Affiliation(s)
- Sheena E Martenies
- Environmental Health Sciences, School of Public Health, University of Michigan, 1415 Washington Heights, Ann Arbor, MI 48109, USA
| | - Donele Wilkins
- Green Door Initiative, 5555 Conner Street Suite 1017A, Detroit, MI 48213, USA
| | - Stuart A Batterman
- Environmental Health Sciences, School of Public Health, University of Michigan, 1415 Washington Heights, Ann Arbor, MI 48109, USA.
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Holt J, Selin NE, Solomon S. Changes in inorganic fine particulate matter sensitivities to precursors due to large-scale US emissions reductions. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2015; 49:4834-41. [PMID: 25816113 DOI: 10.1021/acs.est.5b00008] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
We examined the impact of large US emissions changes, similar to those estimated to have occurred between 2005 and 2012 (high and low emissions cases, respectively), on inorganic PM2.5 sensitivities to further NOx, SO2, and NH3 emissions reductions using the chemical transport model GEOS-Chem. Sensitivities to SO2 emissions are larger year-round and across the US in the low emissions case than the high emissions case due to more aqueous-phase SO2 oxidation. Sensitivities to winter NOx emissions are larger in the low emissions case, more than 2× those of the high emissions case in parts of the northern Midwest. Sensitivities to NH3 emissions are smaller (∼40%) in the low emissions case, year-round, and across the US. Differences in NOx and NH3 sensitivities indicate an altered atmospheric acidity. Larger sensitivities to SO2 and NOx in the low emissions case imply that reducing these emissions may improve air quality more now than they would have in 2005; conversely, NH3 reductions may not improve air quality as much as previously assumed.
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Affiliation(s)
- Jareth Holt
- †Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Building 54-1711, Cambridge, Massachusetts 02139, United States
| | - Noelle E Selin
- †Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Building 54-1711, Cambridge, Massachusetts 02139, United States
- ‡Engineering Systems Division, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Susan Solomon
- †Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Building 54-1711, Cambridge, Massachusetts 02139, United States
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63
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Turner MD, Henze DK, Hakami A, Zhao S, Resler J, Carmichael GR, Stanier CO, Baek J, Sandu A, Russell AG, Nenes A, Jeong GR, Capps SL, Percell PB, Pinder RW, Napelenok SL, Bash JO, Chai T. Differences between magnitudes and health impacts of BC emissions across the United States using 12 km scale seasonal source apportionment. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2015; 49:4362-4371. [PMID: 25729920 DOI: 10.1021/es505968b] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
Recent assessments have analyzed the health impacts of PM2.5 from emissions from different locations and sectors using simplified or reduced-form air quality models. Here we present an alternative approach using the adjoint of the Community Multiscale Air Quality (CMAQ) model, which provides source-receptor relationships at highly resolved sectoral, spatial, and temporal scales. While damage resulting from anthropogenic emissions of BC is strongly correlated with population and premature death, we found little correlation between damage and emission magnitude, suggesting that controls on the largest emissions may not be the most efficient means of reducing damage resulting from anthropogenic BC emissions. Rather, the best proxy for locations with damaging BC emissions is locations where premature deaths occur. Onroad diesel and nonroad vehicle emissions are the largest contributors to premature deaths attributed to exposure to BC, while onroad gasoline emissions cause the highest deaths per amount emitted. Emissions in fall and winter contribute to more premature deaths (and more per amount emitted) than emissions in spring and summer. Overall, these results show the value of the high-resolution source attribution for determining the locations, seasons, and sectors for which BC emission controls have the most effective health benefits.
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Affiliation(s)
- Matthew D Turner
- †Mechanical Engineering Department, University of Colorado, Boulder, Colorado 80309, United States
| | - Daven K Henze
- †Mechanical Engineering Department, University of Colorado, Boulder, Colorado 80309, United States
| | - Amir Hakami
- ‡Department of Civil and Environmental Engineering, Carleton University, Ottawa, Ontario K1S 5B6, Canada
| | - Shunliu Zhao
- ‡Department of Civil and Environmental Engineering, Carleton University, Ottawa, Ontario K1S 5B6, Canada
| | - Jaroslav Resler
- §Nonlinear Modeling, Institute of Computer Science, Prague 182 07, Czech Republic
| | - Gregory R Carmichael
- ∥Department of Chemical and Biochemical Engineering, University of Iowa, Iowa City, Iowa 52242, United States
| | - Charles O Stanier
- ∥Department of Chemical and Biochemical Engineering, University of Iowa, Iowa City, Iowa 52242, United States
| | - Jaemeen Baek
- ∥Department of Chemical and Biochemical Engineering, University of Iowa, Iowa City, Iowa 52242, United States
| | - Adrian Sandu
- ⊥Computer Science, Virginia Tech, Blacksburg, Virginia 24061, United States
| | | | - Athanasios Nenes
- ▲School of Chemical and Biomolecular Engineering, Georgia Tech, Atlanta, Georgia 30332, United States
| | - Gill-Ran Jeong
- ◇Korea Institute of Atmospheric Prediction Systems, Seoul 156-849, Republic of Korea
| | - Shannon L Capps
- □Atmospheric Modeling and Analysis Division, U.S. EPA, Research Triangle Park, North Carolina 27711, United States
| | - Peter B Percell
- ◆Department of Geosciences, University of Houston, Houston, Texas 77004, United States
| | - Rob W Pinder
- □Atmospheric Modeling and Analysis Division, U.S. EPA, Research Triangle Park, North Carolina 27711, United States
| | - Sergey L Napelenok
- □Atmospheric Modeling and Analysis Division, U.S. EPA, Research Triangle Park, North Carolina 27711, United States
| | - Jesse O Bash
- □Atmospheric Modeling and Analysis Division, U.S. EPA, Research Triangle Park, North Carolina 27711, United States
| | - Tianfeng Chai
- ■College of Computer, Mathematical, and Natural Sciences, University of Maryland, College Park, Maryland 20742, United States
- △Air Resources Laboratory, National Oceanic and Atmospheric Administration, College Park, Maryland 20740, United States
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64
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Future premature mortality due to O3, secondary inorganic aerosols and primary PM in Europe--sensitivity to changes in climate, anthropogenic emissions, population and building stock. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2015; 12:2837-69. [PMID: 25749320 PMCID: PMC4377936 DOI: 10.3390/ijerph120302837] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/10/2014] [Revised: 02/09/2015] [Accepted: 02/25/2015] [Indexed: 11/17/2022]
Abstract
Air pollution is an important environmental factor associated with health impacts in Europe and considerable resources are used to reduce exposure to air pollution through emission reductions. These reductions will have non-linear effects on exposure due, e.g., to interactions between climate and atmospheric chemistry. By using an integrated assessment model, we quantify the effect of changes in climate, emissions and population demography on exposure and health impacts in Europe. The sensitivity to the changes is assessed by investigating the differences between the decades 2000-2009, 2050-2059 and 2080-2089. We focus on the number of premature deaths related to atmospheric ozone, Secondary Inorganic Aerosols and primary PM. For the Nordic region we furthermore include a projection on how population exposure might develop due to changes in building stock with increased energy efficiency. Reductions in emissions cause a large significant decrease in mortality, while climate effects on chemistry and emissions only affects premature mortality by a few percent. Changes in population demography lead to a larger relative increase in chronic mortality than the relative increase in population. Finally, the projected changes in building stock and infiltration rates in the Nordic indicate that this factor may be very important for assessments of population exposure in the future.
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Morita H, Yang S, Unger N, Kinney P. Global health impacts of future aviation emissions under alternative control scenarios. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2014; 48:14659-67. [PMID: 25412200 PMCID: PMC4270391 DOI: 10.1021/es5055379] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/11/2014] [Accepted: 11/20/2014] [Indexed: 05/09/2023]
Abstract
There is strong evidence of an association between fine particulate matter less than 2.5 μm (PM2.5) in aerodynamic diameter and adverse health outcomes. This study analyzes the global excess mortality attributable to the aviation sector in the present (2006) and in the future (three 2050 scenarios) using the integrated exposure response model that was also used in the 2010 Global Burden of Disease assessment. The PM2.5 concentrations for the present and future scenarios were calculated using aviation emission inventories developed by the Volpe National Transportation Systems Center and a global chemistry-climate model. We found that while excess mortality due to the aviation sector emissions is greater in 2050 compared to 2006, improved fuel policies (technology and operations improvements yielding smaller increases in fuel burn compared to 2006, and conversion to fully sustainable fuels) in 2050 could lead to 72% fewer deaths for adults 25 years and older than a 2050 scenario with no fuel improvements. Among the four health outcomes examined, ischemic heart disease was the greatest cause of death. Our results suggest that implementation of improved fuel policies can have substantial human health benefits.
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Affiliation(s)
- Haruka Morita
- Mailman
School of Public Health, Columbia University, 722 West 168th Street, New York, New York 10032, United States
| | - Suijia Yang
- Mailman
School of Public Health, Columbia University, 722 West 168th Street, New York, New York 10032, United States
| | - Nadine Unger
- School
of Forestry and Environmental Studies, Yale
University, 195 Prospect
Street, New Haven, Connecticut 06511, United States
| | - Patrick
L. Kinney
- Mailman
School of Public Health, Columbia University, 722 West 168th Street, New York, New York 10032, United States
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66
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Chang ET, Adami HO, Bailey WH, Boffetta P, Krieger RI, Moolgavkar SH, Mandel JS. Validity of geographically modeled environmental exposure estimates. Crit Rev Toxicol 2014; 44:450-66. [PMID: 24766059 DOI: 10.3109/10408444.2014.902029] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Geographic modeling is increasingly being used to estimate long-term environmental exposures in epidemiologic studies of chronic disease outcomes. However, without validation against measured environmental concentrations, personal exposure levels, or biologic doses, these models cannot be assumed a priori to be accurate. This article discusses three examples of epidemiologic associations involving exposures estimated using geographic modeling, and identifies important issues that affect geographically modeled exposure assessment in these areas. In air pollution epidemiology, geographic models of fine particulate matter levels have frequently been validated against measured environmental levels, but comparisons between ambient and personal exposure levels have shown only moderate correlations. Estimating exposure to magnetic fields by using geographically modeled distances is problematic because the error is larger at short distances, where field levels can vary substantially. Geographic models of environmental exposure to pesticides, including paraquat, have seldom been validated against environmental or personal levels, and validation studies have yielded inconsistent and typically modest results. In general, the exposure misclassification resulting from geographic models of environmental exposures can be differential and can result in bias away from the null even if non-differential. Therefore, geographic exposure models must be rigorously constructed and validated if they are to be relied upon to produce credible scientific results to inform epidemiologic research. To our knowledge, such models have not yet successfully predicted an association between an environmental exposure and a chronic disease outcome that has eventually been established as causal, and may not be capable of doing so in the absence of thorough validation.
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Affiliation(s)
- Ellen T Chang
- Health Sciences Practice, Exponent, Inc. , Menlo Park, CA, Bowie, MD, and Bellevue, WA , USA
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