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Ban J, Cheng J, Zhang C, Lu K, Zhou Z, Liu Z, Chen Y, Wang C, Cai W, Gong P, Luo Y, Tong D, Hu J, Guo X, Hao J, Li T. China's carbon-neutral policies will reduce short-term PM 2.5-associated excess incidence of cardiovascular diseases. ONE EARTH (CAMBRIDGE, MASS.) 2024; 7:497-505. [PMID: 38532982 PMCID: PMC10962059 DOI: 10.1016/j.oneear.2024.01.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 10/31/2023] [Accepted: 01/08/2024] [Indexed: 03/28/2024]
Abstract
China's carbon-neutral target could have benefits for ambient fine particulate matter (PM2.5)-associated mortality. Although previous studies have researched such benefits, the potential impact on cardiovascular disease incidence burden is yet to be investigated thoroughly. Here, we first estimate the association between short-term PM2.5 exposure and the incidence of stroke and coronary heart disease (CHD) via a case-crossover study before projecting future changes in short-term PM2.5-associated excess incidence across China from 2025 to 2060 under three different emission scenarios. We find that, compared to the 2015-2020 baseline, average PM2.5 concentrations nationwide in 2060 under SSP119 (an approximation of a carbon-neutral scenario) are projected to decrease by 81.07%. The short-term PM2.5-related excess incidence of stroke and CHD is projected to be reduced to 3,352 cases (95% confidence interval: 939, 5,738)-compared with 34,485 cases under a medium-emissions scenario (SSP245)-and is expected to be accompanied by a 95% reduction in the related economic burden. China's carbon-neutral policies are likely to bring health benefits for cardiovascular disease by reducing short-term PM2.5-related incidence burden.
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Affiliation(s)
- Jie Ban
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control (AEMPC), Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Jing Cheng
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, China
| | - Can Zhang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Kailai Lu
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Zhen Zhou
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Zhao Liu
- School of Linkong Economics and Management, Beijing Institute of Economics and Management, Beijing 100024, China
| | - Yidan Chen
- State Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC), School of Environment, Tsinghua University, Beijing 100084, China
| | - Can Wang
- State Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC), School of Environment, Tsinghua University, Beijing 100084, China
| | - Wenjia Cai
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, China
| | - Peng Gong
- Department of Earth Sciences and Geography, University of Hong Kong, Hong Kong Special Administrative Region 999077, China
| | - Yong Luo
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, China
| | - Dan Tong
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, China
| | - Jianlin Hu
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control (AEMPC), Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Xinbiao Guo
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, No. 38 Xueyuan Road, Beijing 100191, China
| | - Junwei Hao
- Department of Neurology, Xuanwu Hospital, Capital Medical University, National Center for Neurological Disorders, No. 45 Changchun Street, Xicheng District, Beijing 100053, China
- Key Laboratory for Neurodegenerative Diseases of Ministry of Education, No. 45 Changchun Street, Xicheng District, Beijing 100053, China
- Beijing Municipal Geriatric Medical Research Center, No. 45 Changchun Street, Xicheng District, Beijing 100053, China
| | - Tiantian Li
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
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Campbell PC, Tang Y, Lee P, Baker B, Tong D, Saylor R, Stein A, Huang J, Huang HC, Strobach E, McQueen J, Pan L, Stajner I, Sims J, Tirado-Delgado J, Jung Y, Yang F, Spero TL, Gilliam RC. Development and evaluation of an advanced National Air Quality Forecasting Capability using the NOAA Global Forecast System version 16. GEOSCIENTIFIC MODEL DEVELOPMENT 2022; 15:3281-3313. [PMID: 35664957 PMCID: PMC9157742 DOI: 10.5194/gmd-15-3281-2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
A new dynamical core, known as the Finite-Volume Cubed-Sphere (FV3) and developed at both NASA and NOAA, is used in NOAA's Global Forecast System (GFS) and in limited-area models for regional weather and air quality applications. NOAA has also upgraded the operational FV3GFS to version 16 (GFSv16), which includes a number of significant developmental advances to the model configuration, data assimilation, and underlying model physics, particularly for atmospheric composition to weather feedback. Concurrent with the GFSv16 upgrade, we couple the GFSv16 with the Community Multiscale Air Quality (CMAQ) model to form an advanced version of the National Air Quality Forecasting Capability (NAQFC) that will continue to protect human and ecosystem health in the US. Here we describe the development of the FV3GFSv16 coupling with a "state-of-the-science" CMAQ model version 5.3.1. The GFS-CMAQ coupling is made possible by the seminal version of the NOAA-EPA Atmosphere-Chemistry Coupler (NACC), which became a major piece of the next operational NAQFC system (i.e., NACC-CMAQ) on 20 July 2021. NACC-CMAQ has a number of scientific advancements that include satellite-based data acquisition technology to improve land cover and soil characteristics and inline wildfire smoke and dust predictions that are vital to predictions of fine particulate matter (PM2.5) concentrations during hazardous events affecting society, ecosystems, and human health. The GFS-driven NACC-CMAQ model has significantly different meteorological and chemical predictions compared to the previous operational NAQFC, where evaluation of NACC-CMAQ shows generally improved near-surface ozone and PM2.5 predictions and diurnal patterns, both of which are extended to a 72 h (3 d) forecast with this system.
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Affiliation(s)
- Patrick C. Campbell
- NOAA Air Resources Laboratory (ARL), College Park, MD, USA
- Center for Spatial Information Science and Systems, George Mason University, Fairfax, VA, USA
| | - Youhua Tang
- NOAA Air Resources Laboratory (ARL), College Park, MD, USA
- Center for Spatial Information Science and Systems, George Mason University, Fairfax, VA, USA
| | - Pius Lee
- NOAA Air Resources Laboratory (ARL), College Park, MD, USA
| | - Barry Baker
- NOAA Air Resources Laboratory (ARL), College Park, MD, USA
| | - Daniel Tong
- NOAA Air Resources Laboratory (ARL), College Park, MD, USA
- Center for Spatial Information Science and Systems, George Mason University, Fairfax, VA, USA
| | - Rick Saylor
- NOAA Air Resources Laboratory (ARL), College Park, MD, USA
| | - Ariel Stein
- NOAA Air Resources Laboratory (ARL), College Park, MD, USA
| | - Jianping Huang
- NOAA National Centers for Environmental Prediction (NCEP), College Park, MD, USA
- I.M. Systems Group Inc., Rockville, MD, USA
| | - Ho-Chun Huang
- NOAA National Centers for Environmental Prediction (NCEP), College Park, MD, USA
- I.M. Systems Group Inc., Rockville, MD, USA
| | - Edward Strobach
- NOAA National Centers for Environmental Prediction (NCEP), College Park, MD, USA
- I.M. Systems Group Inc., Rockville, MD, USA
| | - Jeff McQueen
- NOAA National Centers for Environmental Prediction (NCEP), College Park, MD, USA
| | - Li Pan
- NOAA National Centers for Environmental Prediction (NCEP), College Park, MD, USA
- I.M. Systems Group Inc., Rockville, MD, USA
| | - Ivanka Stajner
- NOAA National Centers for Environmental Prediction (NCEP), College Park, MD, USA
| | | | - Jose Tirado-Delgado
- NOAA NWS/STI, College Park, MD, USA
- Eastern Research Group, Inc. (ERG), College Park, MD, USA
| | | | - Fanglin Yang
- NOAA National Centers for Environmental Prediction (NCEP), College Park, MD, USA
| | - Tanya L. Spero
- US Environmental Protection Agency, Research Triangle Park, NC, USA
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McDermott-Levy R, Scolio M, Shakya KM, Moore CH. Factors That Influence Climate Change-Related Mortality in the United States: An Integrative Review. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18158220. [PMID: 34360518 PMCID: PMC8345936 DOI: 10.3390/ijerph18158220] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 07/23/2021] [Accepted: 07/29/2021] [Indexed: 12/02/2022]
Abstract
Global atmospheric warming leads to climate change that results in a cascade of events affecting human mortality directly and indirectly. The factors that influence climate change-related mortality within the peer-reviewed literature were examined using Whittemore and Knafl’s framework for an integrative review. Ninety-eight articles were included in the review from three databases—PubMed, Web of Science, and Scopus—with literature filtered by date, country, and keywords. Articles included in the review address human mortality related to climate change. The review yielded two broad themes in the literature that addressed the factors that influence climate change-related mortality. The broad themes are environmental changes, and social and demographic factors. The meteorological impacts of climate change yield a complex cascade of environmental and weather events that affect ambient temperatures, air quality, drought, wildfires, precipitation, and vector-, food-, and water-borne pathogens. The identified social and demographic factors were related to the social determinants of health. The environmental changes from climate change amplify the existing health determinants that influence mortality within the United States. Mortality data, national weather and natural disaster data, electronic medical records, and health care provider use of International Classification of Disease (ICD) 10 codes must be linked to identify climate change events to capture the full extent of climate change upon population health.
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Affiliation(s)
- Ruth McDermott-Levy
- M. Louise Fitzpatrick College of Nursing, Villanova University, Villanova, PA 19085, USA
- Correspondence:
| | - Madeline Scolio
- Department of Geography and the Environment, Villanova University, Villanova, PA 19085, USA; (M.S.); (K.M.S.)
| | - Kabindra M. Shakya
- Department of Geography and the Environment, Villanova University, Villanova, PA 19085, USA; (M.S.); (K.M.S.)
| | - Caroline H. Moore
- Georgia Baptist College of Nursing, Mercer University, Atlanta, GA 30341, USA;
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Waidyatillake NT, Campbell PT, Vicendese D, Dharmage SC, Curto A, Stevenson M. Particulate Matter and Premature Mortality: A Bayesian Meta-Analysis. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18147655. [PMID: 34300107 PMCID: PMC8303514 DOI: 10.3390/ijerph18147655] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Revised: 07/13/2021] [Accepted: 07/14/2021] [Indexed: 12/25/2022]
Abstract
BACKGROUND We present a systematic review of studies assessing the association between ambient particulate matter (PM) and premature mortality and the results of a Bayesian hierarchical meta-analysis while accounting for population differences of the included studies. METHODS The review protocol was registered in the PROSPERO systematic review registry. Medline, CINAHL and Global Health databases were systematically searched. Bayesian hierarchical meta-analysis was conducted using a non-informative prior to assess whether the regression coefficients differed across observations due to the heterogeneity among studies. RESULTS We identified 3248 records for title and abstract review, of which 309 underwent full text screening. Thirty-six studies were included, based on the inclusion criteria. Most of the studies were from China (n = 14), India (n = 6) and the USA (n = 3). PM2.5 was the most frequently reported pollutant. PM was estimated using modelling techniques (22 studies), satellite-based measures (four studies) and direct measurements (ten studies). Mortality data were sourced from country-specific mortality statistics for 17 studies, Global Burden of Disease data for 16 studies, WHO data for two studies and life tables for one study. Sixteen studies were included in the Bayesian hierarchical meta-analysis. The meta-analysis revealed that the annual estimate of premature mortality attributed to PM2.5 was 253 per 1,000,000 population (95% CI: 90, 643) and 587 per 1,000,000 population (95% CI: 1, 39,746) for PM10. CONCLUSION 253 premature deaths per million population are associated with exposure to ambient PM2.5. We observed an unstable estimate for PM10, most likely due to heterogeneity among the studies. Future research efforts should focus on the effects of ambient PM10 and premature mortality, as well as include populations outside Asia. Key messages: Ambient PM2.5 is associated with premature mortality. Given that rapid urbanization may increase this burden in the coming decades, our study highlights the urgency of implementing air pollution mitigation strategies to reduce the risk to population and planetary health.
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Affiliation(s)
- Nilakshi T. Waidyatillake
- Allergy and Lung Health Unit, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC 3010, Australia; (D.V.); (S.C.D.)
- Department of Medical Education, Melbourne Medical School, The University of Melbourne, Melbourne, VIC 3010, Australia
- Correspondence: (N.T.W.); (M.S.)
| | - Patricia T. Campbell
- Department of Infectious Diseases, Melbourne Medical School, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, VIC 3000, Australia;
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC 3010, Australia
| | - Don Vicendese
- Allergy and Lung Health Unit, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC 3010, Australia; (D.V.); (S.C.D.)
- Department of Mathematics and Statistics, La Trobe University, Bundoora, VIC 3086, Australia
| | - Shyamali C. Dharmage
- Allergy and Lung Health Unit, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC 3010, Australia; (D.V.); (S.C.D.)
| | - Ariadna Curto
- Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, VIC 3065, Australia;
| | - Mark Stevenson
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC 3010, Australia
- Transport Health and Urban Design Research Lab, Melbourne School of Design, The University of Melbourne, Melbourne, VIC 3010, Australia
- Correspondence: (N.T.W.); (M.S.)
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Xu J, Yao M, Wu W, Qiao X, Zhang H, Wang P, Yang X, Zhao X, Zhang J. Estimation of ambient PM 2.5-related mortality burden in China by 2030 under climate and population change scenarios: A modeling study. ENVIRONMENT INTERNATIONAL 2021; 156:106733. [PMID: 34218183 DOI: 10.1016/j.envint.2021.106733] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Revised: 05/23/2021] [Accepted: 06/21/2021] [Indexed: 02/08/2023]
Abstract
BACKGROUND Fine particulate matter (PM2.5) pollution is one of the most critical environmental and public health problems in China and has caused an enormous disease burden, especially long-term PM2.5 exposure. Global climate change represents another environmental challenge in the coming decades and is also an essential factor affecting PM2.5 pollution. Moreover, China has an aging population with a changing population size and falling age-standardized mortality rates. However, little evidence exists evaluating the potential impacts from climate change and population aging on the long-term PM2.5 exposure-related disease burden. This study quantifies the impacts of climate and population changes on changes in the disease burden attributed to long-term PM2.5 exposure from 2015 to 2030 in mainland China, which could add evidence for the revision of relevant environmental standards and health policies. METHODS This modeling study investigated long-term PM2.5 exposure-related mortality across China based on PM2.5 projections under Intergovernmental Panel on Climate Change Representative Concentration Pathways (RCPs) and population scenarios from shared socioeconomic pathways (SSPs). PM2.5 concentrations were simulated by the Weather Research and Forecasting (WRF) and Community Multiscale Air Quality (CMAQ) modeling systems. In addition, three types of population projections in 2030 relative to 2015 were set up as follows: (i) the population remained the same as that in 2015; (ii) the population size changed under SSPs, but the age structure remained the same; (iii) both the population size and age structure changed under SSPs. The global exposure mortality model (GEMM) was adopted to estimate PM2.5-related premature deaths. RESULTS Ambient PM2.5 concentrations decreased from 2015 to 2030 under the two climate and emission scenarios. Estimates of related premature mortality in 2030 declined compared with that in 2015 due to lower PM2.5 concentrations (RCP4.5: -16.8%; RCP8.5: -16.4%). If the age structure of the population remained unchanged and the population size changed under SSPs, the nonaccidental premature mortality also showed a decrease ranging from -18.6% to -14.9%. When both population size and age structure changed under SSPs, the population in China would become older. Nonaccidental premature mortality would sharply increase by 35.7-52.3% (with a net increase of 666-977 thousand) in 2030. CONCLUSION The PM2.5 pollution in 2030 under both RCP4.5 and RCP8.5 would slightly improve. The population sizes in 2030 projected by SSPs are relatively stable compared with that in 2015. However, the modest decrease due to air pollution improvement and stable population size would be offset by population aging.
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Affiliation(s)
- Jiayue Xu
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Minghong Yao
- Evidence-based Medicine Center and Cochrane China Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Wenjing Wu
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Xue Qiao
- Institute of New Energy and Low-carbon Technology, Sichuan University, No. 24, South Section One, First Ring Road, Chengdu 610065, China
| | - Hongliang Zhang
- Department of Environmental Science and Engineering, Fudan University, Shanghai 20043, China.
| | - Pengfei Wang
- Department of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, LA 70803, USA.
| | - Xiaocui Yang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Xing Zhao
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
| | - Juying Zhang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
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A Risk and Decision Analysis Framework to Evaluate Future PM 2.5 Risk: A Case Study in Los Angeles-Long Beach Metro Area. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18094905. [PMID: 34064536 PMCID: PMC8124696 DOI: 10.3390/ijerph18094905] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/27/2021] [Revised: 04/25/2021] [Accepted: 04/26/2021] [Indexed: 11/16/2022]
Abstract
This study examines the L.A.-Long Beach Metro area concerning the future risk of the PM2.5 concentration increase. Population expansion, economic growth, and temperature increase are incorporated to estimate the probability of the magnitude of PM2.5 emission increase. Three possible sectors for the reduction of PM2.5 emissions are considered: ocean-going vessels, refineries, and electricity-generating units. The decision of how best to allocate emissions-reduction efforts among these three sectors is analyzed using a quantitative and qualitative decision-analysis framework. For quantitative analysis, Expected Monetary Value (EMV) and Expected Utility (EU) methods are used to select the optimal sector to invest in. Based on the EMV calculation, the refineries sector is 3.5 times and 6.4 times more worthy of investment compared to the electricity-generating units and the ocean-going vessels sector, respectively. For the qualitative analysis, three criteria (investment efficiency, implementation difficulty, time to become effective) are considered in the decision-making process and sensitivity analysis is conducted to inform the ocean-going vessel sector is the optimal alternative for all possible scenarios. The refineries sector is more preferred than the electricity-generating units sector when the implementation difficulty's weight is smaller than 50%. This study provides a valuable risk and decision analysis framework for analyzing the air pollution problem associated with the future PM2.5 concentration increase caused by three risk factors: population growth, economic growth, and climate change.
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Fazli T, Dong X, Fu JS, Stephens B. Predicting U.S. Residential Building Energy Use and Indoor Pollutant Exposures in the Mid-21st Century. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:3219-3228. [PMID: 33591182 DOI: 10.1021/acs.est.0c06308] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
The extent to which climate change and other factors will influence building energy use and population exposures to indoor pollutants is not well understood. Here, we develop and apply nationally representative residential energy and indoor pollutant model sets to estimate energy use, indoor pollutant concentrations, and associated chronic health outcomes across the U.S. residential building stock in the mid-21st century. The models incorporate expected changes in meteorological and ambient air quality conditions associated with IPCC RCP 8.5 and assumptions for changes in housing characteristics and population movements while keeping other less predictable factors constant. Site and source energy consumption for residential space-conditioning are predicted to decrease by ∼37-43 and ∼20-31%, respectively, in the 2050s compared to those in a 2010s reference scenario. Population-average indoor concentrations of pollutants of ambient origin are expected to decrease, except for O3. Holding indoor emission factors constant, indoor concentrations of pollutants with intermittent indoor sources are expected to decrease by <5% (PM2.5) to >30% (NO2); indoor concentrations of pollutants with persistent indoor sources (e.g., volatile organic compounds (VOCs)) are predicted to increase by ∼15-45%. We estimate negligible changes in disability-adjusted life-years (DALYs) lost associated with residential indoor pollutant exposures, well within uncertainty, although the attribution among pollutants is predicted to vary.
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Affiliation(s)
- Torkan Fazli
- Department of Civil, Architectural, and Environmental Engineering, Illinois Institute of Technology, Chicago, Illinois 60616, United States
| | - Xinyi Dong
- Department of Civil and Environmental Engineering, University of Tennessee, Knoxville, Knoxville, Tennessee 37996, United States
| | - Joshua S Fu
- Department of Civil and Environmental Engineering, University of Tennessee, Knoxville, Knoxville, Tennessee 37996, United States
- Computational Earth Sciences Group, Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - Brent Stephens
- Department of Civil, Architectural, and Environmental Engineering, Illinois Institute of Technology, Chicago, Illinois 60616, United States
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Fann NL, Nolte CG, Sarofim MC, Martinich J, Nassikas NJ. Associations Between Simulated Future Changes in Climate, Air Quality, and Human Health. JAMA Netw Open 2021; 4:e2032064. [PMID: 33394002 PMCID: PMC7783541 DOI: 10.1001/jamanetworkopen.2020.32064] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
IMPORTANCE Future changes in climate are likely to adversely affect human health by affecting concentrations of particulate matter sized less than 2.5 μm (PM2.5) and ozone (O3) in many areas. However, the degree to which these outcomes may be mitigated by reducing air pollutant emissions is not well understood. OBJECTIVE To model the associations between future changes in climate, air quality, and human health for 2 climate models and under 2 air pollutant emission scenarios. DESIGN, SETTING, AND PARTICIPANTS This modeling study simulated meteorological conditions over the coterminous continental US during a 1995 to 2005 baseline and over the 21st century (2025-2100) by dynamically downscaling representations of a high warming scenario from the Community Earth System Model (CESM) and the Coupled Model version 3 (CM3) global climate models. Using a chemical transport model, PM2.5 and O3 concentrations were simulated under a 2011 air pollutant emission data set and a 2040 projection. The changes in PM2.5 and O3-attributable deaths associated with climate change among the US census-projected population were estimated for 2030, 2050, 2075, and 2095 for each of 2 emission inventories and climate models. Data were analyzed from June 2018 to June 2020. MAIN OUTCOMES AND MEASURES The main outcomes were simulated change in summer season means of the maximum daily 8-hour mean O3, annual mean PM2.5, population-weighted exposure, and the number of avoided or incurred deaths associated with these pollutants. Results are reported for 2030, 2050, 2075, and 2095, compared with 2000, for 2 climate models and 2 air pollutant emissions data sets. RESULTS The projected increased maximum daily temperatures through 2095 were up to 7.6 °C for the CESM model and 11.8 °C for the CM3 model. Under each climate model scenario by 2095, compared with 2000, an estimated additional 21 000 (95% CI, 14 000-28 000) PM2.5-attributable deaths and 4100 (95% CI, 2200-6000) O3-attributable deaths were projected to occur. These projections decreased to an estimated 15 000 (95% CI, 10 000-20 000) PM2.5-attributable deaths and 640 (95% CI, 340-940) O3-attributable deaths when simulated using a future emission inventory that accounted for reduced anthropogenic emissions. CONCLUSIONS AND RELEVANCE These findings suggest that reducing future air pollutant emissions could also reduce the climate-driven increase in deaths associated with air pollution by hundreds to thousands.
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Affiliation(s)
- Neal L. Fann
- Office of Air Quality Planning and Standards, Office of Air and Radiation, US Environmental Protection Agency, Research Triangle Park, North Carolina
| | - Christopher G. Nolte
- Center for Environmental Measurement and Modeling, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, North Carolina
| | - Marcus C. Sarofim
- Office of Atmospheric Programs, Office of Air and Radiation, US Environmental Protection Agency, Washington District of Columbia
| | - Jeremy Martinich
- Office of Atmospheric Programs, Office of Air and Radiation, US Environmental Protection Agency, Washington District of Columbia
| | - Nicholas J. Nassikas
- Department of Pulmonary, Critical Care, and Sleep Medicine, Alpert School of Medicine, Brown University, Providence, Rhode Island
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Gao Y, Zhang L, Zhang G, Yan F, Zhang S, Sheng L, Li J, Wang M, Wu S, Fu JS, Yao X, Gao H. The climate impact on atmospheric stagnation and capability of stagnation indices in elucidating the haze events over North China Plain and Northeast China. CHEMOSPHERE 2020; 258:127335. [PMID: 32563066 DOI: 10.1016/j.chemosphere.2020.127335] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Revised: 05/30/2020] [Accepted: 06/03/2020] [Indexed: 06/11/2023]
Abstract
In this study, the spatial pattern and temporal evolution of PM2.5 over North China Plain (NCP) and Northeast China (NEC) during 2014-2018 was investigated. The annual mean PM2.5 shows clear decreasing trends over time, but the seasonal mean PM2.5 as well as the seasonal total duration and frequency of haze days shows large inter-annual fluctuation. Based on the atmospheric stagnation index (ASI), this study examined the correlation between ASI and haze events over NCP and NEC. Detailed analysis indicates that location dependency exists of ASI in the capability of capturing the haze events, and the ability is limited in NCP. Therefore, we first propose two alternative methods in defining the ASI to either account for the lag effect or enlarge the threshold value of wind speed at 500 hPa. The new methods can improve the ability of ASI to explain the haze events over NEC, though marginal improvement was achieved in NCP. Furthermore, this study constructed the equation based on the boundary layer height and wind speed at 10-meter, apparently improving the ability in haze capture rate (HCR), a ratio of haze days during the stagnation to the total haze days. Based on a multi-model ensemble analyses under Representative Concentration Pathway (RCP) 8.5, we found that by the end of this century, climate change may lead to increases in both the duration and frequency of wintertime stagnation events over NCP. In contrast, the models predict a decrease in stagnant events and the total duration of stagnation in winter over NEC.
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Affiliation(s)
- Yang Gao
- Frontiers Science Center for Deep Ocean Multispheres and Earth System, Key Laboratory of Marine Environment and Ecology, Ministry of Education, Ocean University of China, Qingdao, 266100, China; Laboratory for Marine Ecology and Environmental Science, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266237, China.
| | - Lei Zhang
- Frontiers Science Center for Deep Ocean Multispheres and Earth System, Key Laboratory of Marine Environment and Ecology, Ministry of Education, Ocean University of China, Qingdao, 266100, China
| | - Ge Zhang
- Frontiers Science Center for Deep Ocean Multispheres and Earth System, Key Laboratory of Marine Environment and Ecology, Ministry of Education, Ocean University of China, Qingdao, 266100, China
| | - Feifan Yan
- Frontiers Science Center for Deep Ocean Multispheres and Earth System, Key Laboratory of Marine Environment and Ecology, Ministry of Education, Ocean University of China, Qingdao, 266100, China
| | - Shaoqing Zhang
- Key Laboratory of Physical Oceanography, Ministry of Education, Institute for Advanced Ocean Study, Frontiers Science Center for Deep Ocean Multispheres and Earth System (DOMES), Ocean University of China, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266100, China; International Laboratory for High-Resolution Earth System Prediction (iHESP), Qingdao, 266237, China; College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, 266100, China
| | - Lifang Sheng
- College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, 266100, China
| | - Jianping Li
- Key Laboratory of Physical Oceanography, Ministry of Education, Institute for Advanced Ocean Study, Frontiers Science Center for Deep Ocean Multispheres and Earth System (DOMES), Ocean University of China, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266100, China
| | - Minghuai Wang
- School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
| | - Shiliang Wu
- Atmospheric Sciences Program, Michigan Technological University, Houghton, MI, 49931, USA
| | - Joshua S Fu
- Department of Civil and Environmental Engineering, University of Tennessee, Knoxville, TN, USA
| | - Xiaohong Yao
- Frontiers Science Center for Deep Ocean Multispheres and Earth System, Key Laboratory of Marine Environment and Ecology, Ministry of Education, Ocean University of China, Qingdao, 266100, China; Laboratory for Marine Ecology and Environmental Science, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266237, China
| | - Huiwang Gao
- Frontiers Science Center for Deep Ocean Multispheres and Earth System, Key Laboratory of Marine Environment and Ecology, Ministry of Education, Ocean University of China, Qingdao, 266100, China; Laboratory for Marine Ecology and Environmental Science, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266237, China
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10
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von Schneidemesser E, Driscoll C, Rieder HE, Schiferl LD. How will air quality effects on human health, crops and ecosystems change in the future? PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2020; 378:20190330. [PMID: 32981439 PMCID: PMC7536027 DOI: 10.1098/rsta.2019.0330] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 07/28/2020] [Indexed: 05/30/2023]
Abstract
Future air quality will be driven by changes in air pollutant emissions, but also changes in climate. Here, we review the recent literature on future air quality scenarios and projected changes in effects on human health, crops and ecosystems. While there is overlap in the scenarios and models used for future projections of air quality and climate effects on human health and crops, similar efforts have not been widely conducted for ecosystems. Few studies have conducted joint assessments across more than one sector. Improvements in future air quality effects on human health are seen in emission reduction scenarios that are more ambitious than current legislation. Larger impacts result from changing particulate matter (PM) abundances than ozone burdens. Future global health burdens are dominated by changes in the Asian region. Expected future reductions in ozone outside of Asia will allow for increased crop production. Reductions in PM, although associated with much higher uncertainty, could offset some of this benefit. The responses of ecosystems to air pollution and climate change are long-term, complex, and interactive, and vary widely across biomes and over space and time. Air quality and climate policy should be linked or at least considered holistically, and managed as a multi-media problem. This article is part of a discussion meeting issue 'Air quality, past present and future'.
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Affiliation(s)
| | - Charles Driscoll
- Department of Civil and Environmental Engineering, Syracuse University, Syracuse, NY 13244, USA
| | - Harald E. Rieder
- Institute of Meteorology and Climatology, University of Natural Resources and Life Sciences, Vienna, Gregor-Mendel Strasse 33, 1180 Vienna, Austria
| | - Luke D. Schiferl
- Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY 10964, USA
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11
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Zhang Y, Yang P, Gao Y, Leung RL, Bell ML. Health and economic impacts of air pollution induced by weather extremes over the continental U.S. ENVIRONMENT INTERNATIONAL 2020; 143:105921. [PMID: 32623223 DOI: 10.1016/j.envint.2020.105921] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2019] [Revised: 06/14/2020] [Accepted: 06/19/2020] [Indexed: 06/11/2023]
Abstract
Extreme weather events may enhance ozone (O3) and fine particulate matter (PM2.5) pollution, causing additional adverse health effects. This work aims to evaluate the health and associated economic impacts of changes in air quality induced by heat wave, stagnation, and compound extremes under the Representative Concentration Pathways (RCP) 4.5 and 8.5 climate scenarios. The Environmental Benefits Mapping and Analysis Program-Community Edition is applied to estimate health and related economic impacts of changes in surface O3 and PM2.5 levels due to heat wave, stagnation, and compound extremes over the continental U.S. during past (i.e., 2001-2010) and future (i.e., 2046-2055) decades under the two RCP scenarios. Under the past and future decades, the weather extremes-induced concentration increases may lead to several tens to hundreds O3-related deaths and several hundreds to over ten thousands PM2.5-related deaths annually. High mortalities and morbidities are estimated for populated urban areas with strong spatial heterogeneities. The estimated annual costs for these O3 and PM2.5 related health outcomes are $5.5-12.5 and $48.6-140.7 billion U.S. dollar for mortalities, and $8.9-97.8 and $19.5-112.5 million for morbidities, respectively. Of the extreme events, the estimated O3- and PM2.5-related mortality and morbidity attributed to stagnation are the highest, followed by heat wave or compound extremes. Large increases in heat wave and compound extreme events in the future decade dominate changes in mortality during these two extreme events, whereas population growth dominates changes in mortality during stagnation that is projected to occur less frequently. Projected reductions of anthropogenic emissions under bothRCP scenarios compensate for the increased mortality due to increasedoccurrence for heat wave and compound extremes in the future. These results suggest a need to further reduce air pollutant emissions during weather extremes to minimize the adverse impacts of weather extremes on air quality and human health.
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Affiliation(s)
- Yang Zhang
- Department of Civil and Environmental Engineering, Northeastern University, Boston, MA 02115, USA; Marine, Earth, and Atmospheric Sciences, North Carolina State University, Raleigh, NC 27695, USA.
| | - Peilin Yang
- Marine, Earth, and Atmospheric Sciences, North Carolina State University, Raleigh, NC 27695, USA
| | - Yang Gao
- Key Laboratory of Marine Environment and Ecology, Ministry of Education of China, Ocean University of China, Qingdao, Shandong 266100, China
| | - Ruby L Leung
- Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, Washington 99354, USA
| | - Michelle L Bell
- School of Forestry & Environmental Studies, Yale University, New Haven, CT 06511, USA
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12
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Du M. Windows of opportunity for daily physical activity. PLoS One 2020; 15:e0238713. [PMID: 32966318 PMCID: PMC7510972 DOI: 10.1371/journal.pone.0238713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Accepted: 08/21/2020] [Indexed: 11/19/2022] Open
Abstract
Air pollution is a serious concern to people who want to engage in physical activities to improve and maintain their health. However, air quality data collected at the nearest monitoring site may not be the best source of information because the data may be incomplete (e.g., some pollutants are not monitored) or not representative. This paper puts forward a method that uses air quality data from a large area to derive a diurnal profile of air quality variation for that area and identify the time window in which the air quality is typically the best during a day. If people exercise in that time window then they can minimize their exposure to air pollution. Three years’ worth of air quality data in five California counties were analyzed to identify the general pattern of diurnal variation of air quality. The analysis shows the pattern of air quality variation is very similar among those five counties which represent diverse geographical and meteorological conditions. The analysis further reveals that in California air quality is generally the best in early mornings; as such, people should exercise in the early morning if their daily schedule allows it. A similar analysis can be performed for other areas to help people choose the best time window to exercise.
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Affiliation(s)
- Marvin Du
- College of Chemistry, University of California, Berkeley, CA, United States of America
- * E-mail:
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13
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Chen K, Vicedo-Cabrera AM, Dubrow R. Projections of Ambient Temperature- and Air Pollution-Related Mortality Burden Under Combined Climate Change and Population Aging Scenarios: a Review. Curr Environ Health Rep 2020; 7:243-255. [PMID: 32542573 DOI: 10.1007/s40572-020-00281-6] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
PURPOSE OF REVIEW Climate change will affect mortality associated with both ambient temperature and air pollution. Because older adults have elevated vulnerability to both non-optimal ambient temperature (heat and cold) and air pollution, population aging can amplify future population vulnerability to these stressors through increasing the number of vulnerable older adults. We aimed to review recent evidence on projections of temperature- or air pollution-related mortality burden (i.e., number of deaths) under combined climate change and population aging scenarios, with a focus on evaluating the role of population aging in assessing these health impacts of climate change. We included studies published between 2014 and 2019 with age-specific population projections. RECENT FINDINGS We reviewed 16 temperature projection studies and 15 air pollution projection studies. Nine of the temperature studies and four of the air pollution studies took population aging into account by performing age-stratified analyses that utilized age-specific relationships between temperature or air pollution exposures and mortality (i.e., age-specific exposure-response functions (ERFs)). Population aging amplifies the projected mortality burden of temperature and air pollution under a warming climate. Compared with a constant population scenario, population aging scenarios lead to less reduction or even increases in cold-related mortality burden, resulting in substantial net increases in future overall (heat and cold) temperature-related mortality burden. There is strong evidence suggesting that to accurately assess the future temperature- and air pollution-related mortality burden of climate change, investigators need to account for the amplifying effect of population aging. Thus, all future studies should incorporate age-specific population size projections and age-specific ERFs into their analyses. These studies would benefit from refinement of age-specific ERF estimates.
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Affiliation(s)
- Kai Chen
- Department of Environmental Health Sciences, Yale School of Public Health, 60 College Street, New Haven, CT, 06520-8034, USA. .,Yale Center on Climate Change and Health, Yale School of Public Health, 60 College Street, New Haven, CT, 06520-8034, USA.
| | - Ana Maria Vicedo-Cabrera
- Institute of Social and Preventive Medicine, University of Bern, 43 Mittelstrasse, 3012, Bern, Switzerland.,Oeschger Center for Climate Change Research, University of Bern, 4 Hochschulstrasse, 3012, Bern, Switzerland
| | - Robert Dubrow
- Department of Environmental Health Sciences, Yale School of Public Health, 60 College Street, New Haven, CT, 06520-8034, USA.,Yale Center on Climate Change and Health, Yale School of Public Health, 60 College Street, New Haven, CT, 06520-8034, USA
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14
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Developing Vulnerability Index to Quantify Urban Heat Islands Effects Coupled with Air Pollution: A Case Study of Camden, NJ. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 2020. [DOI: 10.3390/ijgi9060349] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Extreme heat events at urban centers in combination with air pollution pose a serious risk to human health. Among these are financially distressed cities and neighborhoods that are facing enormous challenges without the scientific and technical capacity for planning and mitigation. The city of Camden is one of those economically distressed areas with a predominantly minority population, a high unemployment rate, high poverty rates, and poor air quality (PM2.5 and ozone), and it remains vulnerable to heat events. This paper focuses on studying a coupled effect of Urban Heat Islands (UHIs) and Ozone-PM2.5 pollution at the neighborhood-scale in the city of Camden, using fine scale remotely sensed land-surface temperature and air quality data from the Community Multiscale Air Quality (CMAQ) Modelling System in the Geographic Information Systems (GIS) platform. To assess the impact of urban microclimate on the city of Camden, NJ, residents’ health, we identified several environmental and social parameters as the root causes of vulnerability imposed by extreme-heat and poor air quality. Vulnerability in terms of environment and social wellbeing was spatially quantified as two conceptual vulnerability-index models (i.e., environmental vulnerability index (EVI) and a social vulnerability index (SVI)) using multiple linear regression algorithm. Factors such as remotely sensed earth surface properties, built-environment components, air quality, and socio-economic data were incorporated in a holistic geographic approach to quantify the combined effect. Surface temperature gradient and Proportional Vegetation (Pv) generated from 30 m resolution Landsat 8 were sampled along with other variables in the city of Camden, NJ. Models incorporating Pv suggest better fit than models with normalized difference vegetation index (NDVI). Water fraction (33.5%, 32.4%), percentage imperviousness (32.5%, 32%), Pv (20.5%, 19.6%), and digital elevation model (DEM) (9%, 8%) have the highest contributions in both models. Two output maps identified the vulnerable neighborhoods in the city through comprehensive GIS analysis: Lanning Square, Bergen Square, Central Waterfront, Gateway, Liberty Park, and Parkside. This can provide useful information for planners and health officials in targeting areas for future interventions and mitigations.
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15
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Nassikas N, Spangler K, Fann N, Nolte CG, Dolwick P, Spero TL, Sheffield P, Wellenius GA. Ozone-related asthma emergency department visits in the US in a warming climate. ENVIRONMENTAL RESEARCH 2020; 183:109206. [PMID: 32035409 PMCID: PMC7167359 DOI: 10.1016/j.envres.2020.109206] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2019] [Revised: 01/29/2020] [Accepted: 01/30/2020] [Indexed: 06/10/2023]
Abstract
Ozone exposure is associated with higher risk of asthma-related emergency department visits. The meteorological conditions that govern ozone concentration are projected to be more favorable to ozone formation over much of the United States due to continued climate change, even as emissions of anthropogenic ozone precursors are expected to decrease by 2050. Our goal is to quantify the health benefits of a climate change mitigation scenario versus a "business-as-usual" scenario, defined by the United Nations Intergovernmental Panel on Climate Change Representative Concentration Pathways (RCPs) 4.5 and 8.5, respectively, using the health impact analytical program Benefits Mapping and Analysis Program - Community Edition (BenMAP - CE) to project the number of asthma ED visits in 2045-2055. We project an annual average of 3100 averted ozone-related asthma ED visits during the 2045-2055 period under RCP4.5 versus RCP8.5, with all other factors held constant, which translates to USD $1.7 million in averted costs annually. We identify counties with tens to hundreds of avoided ozone-related asthma ED visits under RCP4.5 versus RCP8.5. Overall, we project a heterogeneous distribution of ozone-related asthma ED visits at different spatial resolutions, specifically national, regional, and county levels, and a substantial net health and economic benefit of climate change mitigation.
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Affiliation(s)
- Nicholas Nassikas
- Department of Pulmonary, Critical Care, and Sleep Medicine, Brown University Alpert Medical School, Providence, RI, 02903, USA.
| | - Keith Spangler
- Department of Earth, Environmental, and Planetary Sciences, Brown University, Providence, RI, 02912, USA; Department of Epidemiology, Brown University School of Public Health, Providence, RI, 02903, USA; Institute at Brown for Environment and Society, Brown University, Providence, RI, 02912, USA
| | - Neal Fann
- U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, Research Triangle Park, NC, 27709, USA
| | - Christopher G Nolte
- U.S. Environmental Protection Agency, Office of Research and Development, Research Triangle Park, NC, 27709, USA
| | - Patrick Dolwick
- U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, Research Triangle Park, NC, 27709, USA
| | - Tanya L Spero
- U.S. Environmental Protection Agency, Office of Research and Development, Research Triangle Park, NC, 27709, USA
| | - Perry Sheffield
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York City, NY, 10029, USA
| | - Gregory A Wellenius
- Department of Epidemiology, Brown University School of Public Health, Providence, RI, 02903, USA
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16
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Yang P, Zhang Y, Wang K, Doraiswamy P, Cho SH. Health impacts and cost-benefit analyses of surface O 3 and PM 2.5 over the U.S. under future climate and emission scenarios. ENVIRONMENTAL RESEARCH 2019; 178:108687. [PMID: 31479977 DOI: 10.1016/j.envres.2019.108687] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Revised: 07/12/2019] [Accepted: 08/22/2019] [Indexed: 06/10/2023]
Abstract
Health impacts of surface ozone (O3) and fine particulate matter (PM2.5) are of major concern worldwide. In this work, the Environmental Benefits Mapping and Analysis Program tool is applied to estimate the health and economic impacts of projected changes in O3 and PM2.5 in the U.S. in future (2046-2055) decade relative to current (2001-2010) decade under the Representative Concentration Pathway (RCP) 4.5 and 8.5 climate scenarios. Future annual-mean O3 reductions under RCP 4.5 prevent ~1,800 all-cause mortality, 761 respiratory hospital admissions (HA), and ~1.2 million school loss days annually, and result in economic benefits of ~16 billion, 29 million, and 132 million U.S. dollars (USD), respectively. By contrast, the projected future annual-mean O3 increases under RCP8.5 cause ~2,400 mortality, 941 respiratory HA, and ~1.6 million school loss days annually and result in economic disbenefits of ~21 billion, 36 million, and 175 million USD, respectively. Health benefits of reduced O3 double under RCP4.5 and health dis-benefits of increased O3 increase by 1.5 times under RCP8.5 in future with 2050 population and baseline incidence rate. Because of the reduction in projected future PM2.5 over CONUS under both scenarios, the annual avoided all-cause deaths, cardiovascular HA, respiratory HA, and work loss days are ~63,000 and ~83,000, ~5,300 and ~7,000, ~12,000 and ~15,000, and ~7.8 million and ~10 million, respectively, leading to economic benefits of ~560 and ~740 billion, ~240 and ~320 million, ~450 and ~590 million, and ~1,400 and ~1,900 million USD for RCP4.5 and 8.5, respectively. Health benefits of reduced PM2.5 for future almost double under both scenarios with the largest benefits in urban areas. RCP8.5 projects larger health and economic benefits due to a greater reduction in PM2.5 but with a warmer atmosphere and higher O3 pollution than RCP4.5. RCP4.5 leads to multiple-benefit goals including reduced O3 and PM2.5, reduced mortality and morbidity, and saved costs. Greater reduction in future PM2.5 under RCP4.5 should be considered to achieve larger multi-benefits.
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Affiliation(s)
- Peilin Yang
- Department of Marine, Earth, and Atmospheric Sciences, North Carolina State University, Raleigh, NC, 27695, USA
| | - Yang Zhang
- Department of Marine, Earth, and Atmospheric Sciences, North Carolina State University, Raleigh, NC, 27695, USA.
| | - Kai Wang
- Department of Marine, Earth, and Atmospheric Sciences, North Carolina State University, Raleigh, NC, 27695, USA
| | - Prakash Doraiswamy
- Air Quality and Exposure Center, RTI International, Durham, NC, 27709, USA
| | - Seung-Hyun Cho
- Air Quality and Exposure Center, RTI International, Durham, NC, 27709, USA
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17
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Requia WJ, Jhun I, Coull BA, Koutrakis P. Climate impact on ambient PM 2.5 elemental concentration in the United States: A trend analysis over the last 30 years. ENVIRONMENT INTERNATIONAL 2019; 131:104888. [PMID: 31302483 DOI: 10.1016/j.envint.2019.05.082] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/18/2019] [Revised: 05/06/2019] [Accepted: 05/31/2019] [Indexed: 05/02/2023]
Abstract
Weather impacts on the chemical composition of PM2.5 varies significantly over space and time given the diversity of particle components and the complex mechanisms governing particle formation and removal. In this study, we employed generalized additive models (GAMs) to estimate weather-associated changes in PM2.5 composition in the US during 1988-2017. We considered seven components of ambient PM2.5, which included elemental carbon (EC), organic carbon (OC), nitrate, sulfate, sodium, ammonium, and silicon. The impact of long-term weather changes on each PM2.5 component was defined in our study as "weather penalty". During our study period, temperature increased in four regions, including the Industrial Midwest and Northeast during the warm and cold season; and Upper Midwest and West in the cold season. Wind speed decreased in the both seasons. Relative humidity increased in the warm season and decreased in the cold season. The weather changes between 1988 and 2017 were associated with most PM2.5 components during both warm and cold seasons. The direction and the magnitude of the weather penalty varied considerably over the space and season. In the warm season, our findings suggest a nationwide weather penalty for EC, OC, nitrate, sulfate, sodium, ammonium, and silicon of 0.04, 0.21, 0.04, 0.35, -0.01, 0.05, and 0.01 μg/m3, respectively. In the cold season, the estimated total penalty was 0.04, 0.21, 0.06, 0.04, -0.01, -0.02, and 0.02 μg/m3, respectively.
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Affiliation(s)
- Weeberb J Requia
- Harvard University, Department of Environmental Health, School of Public Health, Boston, MA, United States.
| | - Iny Jhun
- Harvard University, Harvard Medical School, Boston, MA, United States
| | - Brent A Coull
- Harvard University, Department of Biostatistics, School of Public Health, Boston, MA, United States
| | - Petros Koutrakis
- Harvard University, Department of Environmental Health, School of Public Health, Boston, MA, United States
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18
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Hong C, Zhang Q, Zhang Y, Davis SJ, Tong D, Zheng Y, Liu Z, Guan D, He K, Schellnhuber HJ. Impacts of climate change on future air quality and human health in China. Proc Natl Acad Sci U S A 2019; 116:17193-17200. [PMID: 31405979 PMCID: PMC6717307 DOI: 10.1073/pnas.1812881116] [Citation(s) in RCA: 107] [Impact Index Per Article: 21.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
In recent years, air pollution has caused more than 1 million deaths per year in China, making it a major focus of public health efforts. However, future climate change may exacerbate such human health impacts by increasing the frequency and duration of weather conditions that enhance air pollution exposure. Here, we use a combination of climate, air quality, and epidemiological models to assess future air pollution deaths in a changing climate under Representative Concentration Pathway 4.5 (RCP4.5). We find that, assuming pollution emissions and population are held constant at current levels, climate change would adversely affect future air quality for >85% of China's population (∼55% of land area) by the middle of the century, and would increase by 3% and 4% the population-weighted average concentrations of fine particulate matter (PM2.5) and ozone, respectively. As a result, we estimate an additional 12,100 and 8,900 Chinese (95% confidence interval: 10,300 to 13,800 and 2,300 to 14,700, respectively) will die per year from PM2.5 and ozone exposure, respectively. The important underlying climate mechanisms are changes in extreme conditions such as atmospheric stagnation and heat waves (contributing 39% and 6%, respectively, to the increase in mortality). Additionally, greater vulnerability of China's aging population will further increase the estimated deaths from PM2.5 and ozone in 2050 by factors of 1 and 3, respectively. Our results indicate that climate change and more intense extremes are likely to increase the risk of severe pollution events in China. Managing air quality in China in a changing climate will thus become more challenging.
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Affiliation(s)
- Chaopeng Hong
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, 100084 Beijing, China
| | - Qiang Zhang
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, 100084 Beijing, China;
| | - Yang Zhang
- Department of Marine, Earth, and Atmospheric Sciences, North Carolina State University, Raleigh, NC 27695
| | - Steven J Davis
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, 100084 Beijing, China
- Department of Earth System Science, University of California, Irvine, CA 92697
- Department of Civil and Environmental Engineering, University of California, Irvine, CA 92697
| | - Dan Tong
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, 100084 Beijing, China
| | - Yixuan Zheng
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, 100084 Beijing, China
| | - Zhu Liu
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, 100084 Beijing, China
| | - Dabo Guan
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, 100084 Beijing, China
| | - Kebin He
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, 100084 Beijing, China
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, 100084 Beijing, China
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19
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Wolfe P, Davidson K, Fulcher C, Fann N, Zawacki M, Baker KR. Monetized health benefits attributable to mobile source emission reductions across the United States in 2025. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 650:2490-2498. [PMID: 30296769 PMCID: PMC7259328 DOI: 10.1016/j.scitotenv.2018.09.273] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2018] [Revised: 09/11/2018] [Accepted: 09/20/2018] [Indexed: 04/13/2023]
Abstract
By-products of mobile source combustion processes, such as those associated with gasoline- and diesel-powered engines, include direct emissions of particulate matter as well as precursors to particulate matter and ground-level ozone. Human exposure to fine particulate matter with an aerodynamic diameter smaller than 2.5 μm (PM2.5) is associated with increased incidence of premature mortality and morbidity outcomes. This study builds upon recent, detailed source-apportionment air quality modeling to project the health-related benefits of reducing PM2.5 from mobile sources across the contiguous U.S. in 2025. Updating a previously published benefits analysis approach, we develop national-level benefit per ton estimates for directly emitted PM2.5, SO2/pSO4, and NOX for 16 mobile source sectors spanning onroad vehicles, nonroad engines and equipment, trains, marine vessels, and aircraft. These benefit per ton estimates provide a reduced-form tool for estimating and comparing benefits across multiple mobile source emission scenarios and can be applied to assess the benefits of mobile source policies designed to improve air quality. We found the benefit per ton of directly emitted PM2.5 in 2025 ranges from $110,000 for nonroad agriculture sources to $700,000 for onroad light duty gas cars and motorcycles (in 2015 dollars and based on an estimate of PM-related mortality derived from the American Cancer Society cohort study). Benefit per ton values for SO2/pSO4 range from $52,000 for aircraft sources (including emissions from ground support vehicles) to $300,000 for onroad light duty diesel emissions. Benefit per ton values for NOX range from $2100 for C1 and C2 marine vessels to $7500 for "nonroad all other" mobile sources, including industrial, logging, and oil field sources. Benefit per ton estimates increase approximately 2.26-fold when using an alternative concentration response function to derive PM2.5-related mortality. We also report benefit per ton values for the eastern and western U.S. to account for broad spatial heterogeneity patterns in emissions reductions, population exposure and air quality benefits.
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Affiliation(s)
- Philip Wolfe
- ORISE participant hosted by the US EPA, Ann Arbor, MI 48105, United States of America
| | - Kenneth Davidson
- US EPA, Office of Transportation and Air Quality, Air-6, San Francisco, CA 94105, United States of America.
| | - Charles Fulcher
- US EPA, Office of Air Quality Planning and Standards, Research Triangle Park, NC 27711, United States of America.
| | - Neal Fann
- US EPA, Office of Air Quality Planning and Standards, Research Triangle Park, NC 27711, United States of America.
| | - Margaret Zawacki
- US EPA, Office of Transportation and Air Quality, Ann Arbor, MI 48105, United States of America.
| | - Kirk R Baker
- US EPA, Office of Air Quality Planning and Standards, Research Triangle Park, NC 27711, United States of America.
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Saari RK, Mei Y, Monier E, Garcia-Menendez F. Effect of Health-Related Uncertainty and Natural Variability on Health Impacts and Cobenefits of Climate Policy. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2019; 53:1098-1108. [PMID: 30624913 DOI: 10.1021/acs.est.8b05094] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
Climate policy can mitigate health risks attributed to intensifying air pollution under climate change. However, few studies quantify risks of illness and death, examine their contribution to climate policy benefits, or assess their robustness in light of natural climate variability. We employ an integrated modeling framework of the economy, climate, air quality, and human health to quantify the effect of natural variability on U.S. air pollution impacts under future climate and two global policies (2 and 2.5 °C stabilization scenarios) using 150 year ensemble simulations for each scenario in 2050 and 2100. Climate change yields annual premature deaths related to fine particulate matter and ozone (95CI: 25 000-120 000), heart attacks (900-9400), and lost work days (3.6M-4.9M) in 2100. It raises air pollution health risks by 20%, while policies avert these outcomes by 40-50% in 2050 and 70-88% in 2100. Natural variability introduces "climate noise", yielding some annual estimates with negative cobenefits, and others that reach 100% of annual policy costs. This "noise" is three times the magnitude of uncertainty (95CI) in health and economic responses in 2050. Averaging five annual simulations reduces this factor to two, which is still substantially larger than health-related uncertainty. This study quantifies the potential for inaccuracy in climate impacts projected using too few annual simulations.
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Affiliation(s)
- Rebecca K Saari
- Civil and Environmental Engineering , University of Waterloo , 200 University Avenue West , Waterloo , Ontario , Canada , N2L 3G1
| | - Yufei Mei
- Civil and Environmental Engineering , University of Waterloo , 200 University Avenue West , Waterloo , Ontario , Canada , N2L 3G1
| | - Erwan Monier
- Joint Program on the Science and Policy of Global Change , Massachusetts Institute of Technology , Cambridge , Massachusetts 02139 , United States
| | - Fernando Garcia-Menendez
- Department of Civil, Construction and Environmental Engineering , North Carolina State University , Raleigh , North Carolina 27695 , United States
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Abstract
This article on exposome and asthma focuses on the interaction of patients and their environments in various parts of their growth, development, and stages of life. Indoor and outdoor environments play a role in pathogenesis via levels and duration of exposure, with genetic susceptibility as a crucial factor that alters the initiation and trajectory of common conditions such as asthma. Knowledge of environmental exposures globally and changes that are occurring is necessary to function effectively as medical professionals and health advocates.
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Affiliation(s)
- Ahila Subramanian
- Department of Allergy and Clinical Immunology, Respiratory Institute, Cleveland Clinic, Cleveland Clinic Lerner College of Medicine, CWRU School of Medicine, 9500 Euclid Avenue/A90, Cleveland, OH 4419, USA
| | - Sumita B Khatri
- Department of Pulmonary and Critical Care Medicine, Respiratory Institute, Cleveland Clinic, Cleveland Clinic Lerner College of Medicine, CWRU School of Medicine, 9500 Euclid Avenue/A90, Cleveland, OH 4419, USA.
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22
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Ford B, Val Martin M, Zelasky SE, Fischer EV, Anenberg SC, Heald CL, Pierce JR. Future Fire Impacts on Smoke Concentrations, Visibility, and Health in the Contiguous United States. GEOHEALTH 2018; 2:229-247. [PMID: 32159016 PMCID: PMC7038896 DOI: 10.1029/2018gh000144] [Citation(s) in RCA: 100] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2018] [Revised: 06/26/2018] [Accepted: 06/27/2018] [Indexed: 05/21/2023]
Abstract
Fine particulate matter (PM2.5) from U.S. anthropogenic sources is decreasing. However, previous studies have predicted that PM2.5 emissions from wildfires will increase in the midcentury to next century, potentially offsetting improvements gained by continued reductions in anthropogenic emissions. Therefore, some regions could experience worse air quality, degraded visibility, and increases in population-level exposure. We use global climate model simulations to estimate the impacts of changing fire emissions on air quality, visibility, and premature deaths in the middle and late 21st century. We find that PM2.5 concentrations will decrease overall in the contiguous United States (CONUS) due to decreasing anthropogenic emissions (total PM2.5 decreases by 3% in Representative Concentration Pathway [RCP] 8.5 and 34% in RCP4.5 by 2100), but increasing fire-related PM2.5 (fire-related PM2.5 increases by 55% in RCP4.5 and 190% in RCP8.5 by 2100) offsets these benefits and causes increases in total PM2.5 in some regions. We predict that the average visibility will improve across the CONUS, but fire-related PM2.5 will reduce visibility on the worst days in western and southeastern U.S. regions. We estimate that the number of deaths attributable to total PM2.5 will decrease in both the RCP4.5 and RCP8.5 scenarios (from 6% to 4-5%), but the absolute number of premature deaths attributable to fire-related PM2.5 will double compared to early 21st century. We provide the first estimates of future smoke health and visibility impacts using a prognostic land-fire model. Our results suggest the importance of using realistic fire emissions in future air quality projections.
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Affiliation(s)
- B. Ford
- Department of Atmospheric ScienceColorado State UniversityFort CollinsCOUSA
| | - M. Val Martin
- Leverhulme Centre for Climate Change Mitigation, Department of Animal and Plant SciencesUniversity of SheffieldSheffieldUK
| | - S. E. Zelasky
- Department of Environmental Sciences and EngineeringUniversity of North Carolina at Chapel HillChapel HillNCUSA
| | - E. V. Fischer
- Department of Atmospheric ScienceColorado State UniversityFort CollinsCOUSA
| | - S. C. Anenberg
- Department of Environmental and Occupational HealthThe George Washington UniversityWashingtonDCUSA
| | - C. L. Heald
- Department of Civil and Environmental EngineeringMassachusetts Institute of TechnologyCambridgeMAUSA
- Department of Earth, Atmospheric and Planetary SciencesMassachusetts Institute of TechnologyCambridgeMAUSA
| | - J. R. Pierce
- Department of Atmospheric ScienceColorado State UniversityFort CollinsCOUSA
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Chen K, Fiore AM, Chen R, Jiang L, Jones B, Schneider A, Peters A, Bi J, Kan H, Kinney PL. Future ozone-related acute excess mortality under climate and population change scenarios in China: A modeling study. PLoS Med 2018; 15:e1002598. [PMID: 29969446 PMCID: PMC6029756 DOI: 10.1371/journal.pmed.1002598] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2018] [Accepted: 05/30/2018] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Climate change is likely to further worsen ozone pollution in already heavily polluted areas, leading to increased ozone-related health burdens. However, little evidence exists in China, the world's largest greenhouse gas emitter and most populated country. As China is embracing an aging population with changing population size and falling age-standardized mortality rates, the potential impact of population change on ozone-related health burdens is unclear. Moreover, little is known about the seasonal variation of ozone-related health burdens under climate change. We aimed to assess near-term (mid-21st century) future annual and seasonal excess mortality from short-term exposure to ambient ozone in 104 Chinese cities under 2 climate and emission change scenarios and 6 population change scenarios. METHODS AND FINDINGS We collected historical ambient ozone observations, population change projections, and baseline mortality rates in 104 cities across China during April 27, 2013, to October 31, 2015 (2013-2015), which included approximately 13% of the total population of mainland China. Using historical ozone monitoring data, we performed bias correction and spatially downscaled future ozone projections at a coarse spatial resolution (2.0° × 2.5°) for the period April 27, 2053, to October 31, 2055 (2053-2055), from a global chemistry-climate model to a fine spatial resolution (0.25° × 0.25°) under 2 Intergovernmental Panel on Climate Change Representative Concentration Pathways (RCPs): RCP4.5, a moderate global warming and emission scenario where global warming is between 1.5°C and 2.0°C, and RCP8.5, a high global warming and emission scenario where global warming exceeds 2.0°C. We then estimated the future annual and seasonal ozone-related acute excess mortality attributable to both climate and population changes using cause-specific, age-group-specific, and season-specific concentration-response functions (CRFs). We used Monte Carlo simulations to obtain empirical confidence intervals (eCIs), quantifying the uncertainty in CRFs and the variability across ensemble members (i.e., 3 predictions of future climate and air quality from slightly different starting conditions) of the global model. Estimates of future changes in annual ozone-related mortality are sensitive to the choice of global warming and emission scenario, decreasing under RCP4.5 (-24.0%) due to declining ozone precursor emissions but increasing under RCP8.5 (10.7%) due to warming climate in 2053-2055 relative to 2013-2015. Higher ambient ozone occurs under the high global warming and emission scenario (RCP8.5), leading to an excess 1,476 (95% eCI: 898 to 2,977) non-accidental deaths per year in 2053-2055 relative to 2013-2015. Future ozone-related acute excess mortality from cardiovascular diseases was 5-8 times greater than that from respiratory diseases. Ozone concentrations increase by 15.1 parts per billion (10-9) in colder months (November to April), contributing to a net yearly increase of 22.3% (95% eCI: 7.7% to 35.4%) in ozone-related mortality under RCP8.5. An aging population, with the proportion of the population aged 65 years and above increased from 8% in 2010 to 24%-33% in 2050, will substantially amplify future ozone-related mortality, leading to a net increase of 23,838 to 78,560 deaths (110% to 363%). Our analysis was mainly limited by using a single global chemistry-climate model and the statistical downscaling approach to project ozone changes under climate change. CONCLUSIONS Our analysis shows increased future ozone-related acute excess mortality under the high global warming and emission scenario RCP8.5 for an aging population in China. Comparison with the lower global warming and emission scenario RCP4.5 suggests that climate change mitigation measures are needed to prevent a rising health burden from exposure to ambient ozone pollution in China.
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Affiliation(s)
- Kai Chen
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, China
- Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Arlene M. Fiore
- Department of Earth and Environmental Sciences and Lamont–Doherty Earth Observatory of Columbia University, Palisades, New York, United States of America
| | - Renjie Chen
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Shanghai, China
- School of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education and Key Laboratory of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai, China
| | - Leiwen Jiang
- Asian Demographic Research Institute, School of Sociology and Political Science, Shanghai University, Shanghai, China
- National Center for Atmospheric Research, Boulder, Colorado, United States of America
| | - Bryan Jones
- Marxe School of Public and International Affairs, Baruch College, New York, New York, United States of America
| | | | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Jun Bi
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, China
| | - Haidong Kan
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Shanghai, China
- School of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education and Key Laboratory of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai, China
| | - Patrick L. Kinney
- Department of Environmental Health, Boston University School of Public Health, Boston, Massachusetts, United States of America
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24
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Simulation of Climate Change Impact on Emergency Medical Services Clients Caused by Air Pollution. HEALTH SCOPE 2018. [DOI: 10.5812/jhealthscope.57786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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25
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Abstract
PURPOSE OF REVIEW Air pollution significantly affects health, causing up to 7 million premature deaths annually with an even larger number of hospitalizations and days of sick leave. Climate change could alter the dispersion of primary pollutants, particularly particulate matter, and intensify the formation of secondary pollutants, such as near-surface ozone. The purpose of the review is to evaluate the recent evidence on the impacts of climate change on air pollution and air pollution-related health impacts and identify knowledge gaps for future research. RECENT FINDINGS Several studies modelled future ozone and particulate matter concentrations and calculated the resulting health impacts under different climate scenarios. Due to climate change, ozone- and fine particle-related mortalities are expected to increase in most studies; however, results differ by region, assumed climate change scenario and other factors such as population and background emissions. This review explores the relationships between climate change, air pollution and air pollution-related health impacts. The results highly depend on the climate change scenario used and on projections of future air pollution emissions, with relatively high uncertainty. Studies primarily focused on mortality; projections on the effects on morbidity are needed.
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Affiliation(s)
- H Orru
- Department of Family Medicine and Public Health, University of Tartu, Ravila 19, 50411, Tartu, Estonia.
- Department of Public Health and Clinical Medicine, Umea University, Umea, Sweden.
| | - K L Ebi
- Center for Health and the Global Environment, University of Washington, Seattle, WA, USA
| | - B Forsberg
- Department of Public Health and Clinical Medicine, Umea University, Umea, Sweden
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26
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Zhang Y, Smith SJ, Bowden JH, Adelman Z, West JJ. Co-benefits of global, domestic, and sectoral greenhouse gas mitigation for US air quality and human health in 2050. ENVIRONMENTAL RESEARCH LETTERS : ERL [WEB SITE] 2017; 12:114033. [PMID: 33204303 PMCID: PMC7668559 DOI: 10.1088/1748-9326/aa8f76] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
Reductions in greenhouse gas (GHG) emissions can bring ancillary benefits of improved air quality and reduced premature mortality, in addition to slowing climate change. Here we study the co-benefits of global and domestic GHG mitigation on US air quality and human health in 2050 at fine resolution using dynamical downscaling of meteorology and air quality from global simulations to the continental US, and quantify for the first time the co-benefits from foreign GHG mitigation. Relative to the reference scenario from which RCP4.5 was created, global GHG reductions in RCP4.5 avoid 16000 PM2.5-related all-cause deaths yr-1 (90% confidence interval, 11700-20300), and 8000 (3600-12400) O3-related respiratory deaths yr-1 in the US in 2050. Foreign GHG mitigation avoids 15% and 62% of PM2.5- and O3-related total avoided deaths, highlighting the importance of foreign mitigation for US health. GHG mitigation in the US residential sector brings the largest co-benefits for PM2.5-related deaths (21% of total domestic co-benefits), and industry for O3 (17%). Monetized benefits for avoided deaths from ozone and PM2.5 are $137 ($87-187) per ton CO2 at high valuation and $45 ($29-62) at low valuation, of which 31% are from foreign GHG reductions. These benefits likely exceed the marginal cost of GHG reductions in 2050. The US gains significantly greater air quality and health co-benefits when its GHG emission reductions are concurrent with reductions in other nations. Similarly, previous studies estimating co-benefits locally or regionally may greatly underestimate the full co-benefits of coordinated global actions.
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Affiliation(s)
- Yuqiang Zhang
- Environmental Sciences and Engineering Department, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Now at Environmental Protection Agency, Research Triangle Park, NC 27709, USA
| | - Steven J. Smith
- Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park, MD 20740, USA
| | - Jared H. Bowden
- Institute for the Environment, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Zachariah Adelman
- Environmental Sciences and Engineering Department, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Institute for the Environment, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - J. Jason West
- Environmental Sciences and Engineering Department, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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Dionisio KL, Nolte CG, Spero TL, Graham S, Caraway N, Foley KM, Isaacs KK. Characterizing the impact of projected changes in climate and air quality on human exposures to ozone. JOURNAL OF EXPOSURE SCIENCE & ENVIRONMENTAL EPIDEMIOLOGY 2017; 27:260-270. [PMID: 28120830 PMCID: PMC8958429 DOI: 10.1038/jes.2016.81] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2016] [Accepted: 11/23/2016] [Indexed: 05/21/2023]
Abstract
The impact of climate change on human and environmental health is of critical concern. Population exposures to air pollutants both indoors and outdoors are influenced by a wide range of air quality, meteorological, behavioral, and housing-related factors, many of which are also impacted by climate change. An integrated methodology for modeling changes in human exposures to tropospheric ozone (O3) owing to potential future changes in climate and demographics was implemented by linking existing modeling tools for climate, weather, air quality, population distribution, and human exposure. Human exposure results from the Air Pollutants Exposure Model (APEX) for 12 US cities show differences in daily maximum 8-h (DM8H) exposure patterns and levels by sex, age, and city for all scenarios. When climate is held constant and population demographics are varied, minimal difference in O3 exposures is predicted even with the most extreme demographic change scenario. In contrast, when population is held constant, we see evidence of substantial changes in O3 exposure for the most extreme change in climate. Similarly, we see increases in the percentage of the population in each city with at least one O3 exposure exceedance above 60 p.p.b and 70 p.p.b thresholds for future changes in climate. For these climate and population scenarios, the impact of projected changes in climate and air quality on human exposure to O3 are much larger than the impacts of changing demographics. These results indicate the potential for future changes in O3 exposure as a result of changes in climate that could impact human health.
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Affiliation(s)
- Kathie L. Dionisio
- National Exposure Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, RTP, NC, USA
| | - Christopher G. Nolte
- National Exposure Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, RTP, NC, USA
| | - Tanya L. Spero
- National Exposure Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, RTP, NC, USA
| | - Stephen Graham
- Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, RTP, NC, USA
| | | | - Kristen M. Foley
- National Exposure Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, RTP, NC, USA
| | - Kristin K. Isaacs
- National Exposure Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, RTP, NC, USA
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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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