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Tian Y, Duan M, Cui X, Zhao Q, Tian S, Lin Y, Wang W. Advancing application of satellite remote sensing technologies for linking atmospheric and built environment to health. Front Public Health 2023; 11:1270033. [PMID: 38045962 PMCID: PMC10690611 DOI: 10.3389/fpubh.2023.1270033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 09/01/2023] [Indexed: 12/05/2023] Open
Abstract
Background The intricate interplay between human well-being and the surrounding environment underscores contemporary discourse. Within this paradigm, comprehensive environmental monitoring holds the key to unraveling the intricate connections linking population health to environmental exposures. The advent of satellite remote sensing monitoring (SRSM) has revolutionized traditional monitoring constraints, particularly limited spatial coverage and resolution. This innovation finds profound utility in quantifying land covers and air pollution data, casting new light on epidemiological and geographical investigations. This dynamic application reveals the intricate web connecting public health, environmental pollution, and the built environment. Objective This comprehensive review navigates the evolving trajectory of SRSM technology, casting light on its role in addressing environmental and geographic health issues. The discussion hones in on how SRSM has recently magnified our understanding of the relationship between air pollutant exposure and population health. Additionally, this discourse delves into public health challenges stemming from shifts in urban morphology. Methods Utilizing the strategic keywords "SRSM," "air pollutant health risk," and "built environment," an exhaustive search unfolded across prestigious databases including the China National Knowledge Network (CNKI), PubMed and Web of Science. The Citespace tool further unveiled interconnections among resultant articles and research trends. Results Synthesizing insights from a myriad of articles spanning 1988 to 2023, our findings unveil how SRMS bridges gaps in ground-based monitoring through continuous spatial observations, empowering global air quality surveillance. High-resolution SRSM advances data precision, capturing multiple built environment impact factors. Its application to epidemiological health exposure holds promise as a pioneering tool for contemporary health research. Conclusion This review underscores SRSM's pivotal role in enriching geographic health studies, particularly in atmospheric pollution domains. The study illuminates how SRSM overcomes spatial resolution and data loss hurdles, enriching environmental monitoring tools and datasets. The path forward envisions the integration of cutting-edge remote sensing technologies, novel explorations of urban-public health associations, and an enriched assessment of built environment characteristics on public well-being.
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Affiliation(s)
- Yuxuan Tian
- Faculty of Environmental Science and Engineering, Kunming University of Science and Technology, Kunming, Yunnan, China
| | - Mengshan Duan
- Faculty of Environmental Science and Engineering, Kunming University of Science and Technology, Kunming, Yunnan, China
| | - Xiangfen Cui
- Faculty of Environmental Science and Engineering, Kunming University of Science and Technology, Kunming, Yunnan, China
| | - Qun Zhao
- Faculty of Environmental Science and Engineering, Kunming University of Science and Technology, Kunming, Yunnan, China
| | - Senlin Tian
- Faculty of Environmental Science and Engineering, Kunming University of Science and Technology, Kunming, Yunnan, China
| | - Yichao Lin
- Guizhou Research Institute of Coal Mine Design Co., Ltd., Guiyang, China
| | - Weicen Wang
- China Academy of Urban Planning Design, Beijing, China
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Rohra H, Pipal AS, Satsangi PG, Taneja A. Revisiting the atmospheric particles: Connecting lines and changing paradigms. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 841:156676. [PMID: 35700785 DOI: 10.1016/j.scitotenv.2022.156676] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 06/09/2022] [Accepted: 06/09/2022] [Indexed: 06/15/2023]
Abstract
Historically, the atmospheric particles constitute the most primitive and recent class of air pollutants. The science of atmospheric particles erupted more than a century ago covering more than four decades of size, with past few years experiencing major advancements on both theoretic and data-based observational grounds. More recently, the plausible recognition between particulate matter (PM) and the diffusion of the COVID-19 pandemic has led to the accretion of interest in particle science. With motivation from diverse particle research interests, this paper is an 'old engineer's survey' beginning with the evolution of atmospheric particles and identifies along the way many of the global instances signaling the 'size concept' of PM. A theme that runs through the narrative is a 'previously known' generational evolution of particle science to the 'newly procured' portfolio of knowledge, with important gains on the application of unmet concepts and future approaches to PM exposure and epidemiological research.
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Affiliation(s)
- Himanshi Rohra
- Department of Chemistry, Savitribai Phule Pune University, Pune 411007, India
| | - Atar Singh Pipal
- Centre for Environmental Sustainability and Human Health, Ming Chi University of Technology, Taishan, New Taipei 243089, Taiwan
| | - P G Satsangi
- Department of Chemistry, Savitribai Phule Pune University, Pune 411007, India
| | - Ajay Taneja
- Department of Chemistry, Dr. Bhimrao Ambedkar University, Agra 282002, India.
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3
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Aim in Climate Change and City Pollution. Artif Intell Med 2022. [DOI: 10.1007/978-3-030-64573-1_290] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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4
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Torres P, Sirmacek B, Hoyas S, Vinuesa R. Aim in Climate Change and City Pollution. Artif Intell Med 2021. [DOI: 10.1007/978-3-030-58080-3_290-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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Sorek-Hamer M, Chatfield R, Liu Y. Review: Strategies for using satellite-based products in modeling PM 2.5 and short-term pollution episodes. ENVIRONMENT INTERNATIONAL 2020; 144:106057. [PMID: 32889481 DOI: 10.1016/j.envint.2020.106057] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Revised: 08/06/2020] [Accepted: 08/10/2020] [Indexed: 06/11/2023]
Abstract
Short-term air pollution episodes motivate improved understanding of the association between air pollution and acute morbidity and mortality episodes, and triggers required mitigation plans. A variety of methods have been employed to estimate exposure to air pollution episodes, including GIS-based dispersion models, interpolation between sparse monitoring sites, land-use regression models, optimization models, line- or area-dispersion plume models, and models using information from imaging satellites, often including land-use and meteorological variables. There has been increasing use of satellite-borne aerosol products for assessing short-term air quality events. They provide better spatial coverage, but currently at the price of low temporal coverage and rather crude spatial resolution. This is a brief review on using satellite data for modeling short-term air quality and pollution events. The review can be pursued as a practical guide for modeling air quality with satellite-based products, as it includes important questions that should be considered in both the study design as well as the model development stages. Progress in this field is detailed and includes published models and their use in environmental and health studies. Both current and future satellite-borne capabilities are covered. It also provides links to access and download relevant datasets and some example R code for data processing and modeling.
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Affiliation(s)
- Meytar Sorek-Hamer
- NASA Ames Research Center, Moffett Field, CA, United States; Universities Space Research Association (USRA), Mountain View, CA, United States.
| | | | - Yang Liu
- Emory University, Rollins School of Public Health, Atlanta, GA, United States
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6
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Earth Observation Data Supporting Non-Communicable Disease Research: A Review. REMOTE SENSING 2020. [DOI: 10.3390/rs12162541] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
A disease is non-communicable when it is not transferred from one person to another. Typical examples include all types of cancer, diabetes, stroke, or allergies, as well as mental diseases. Non-communicable diseases have at least two things in common—environmental impact and chronicity. These diseases are often associated with reduced quality of life, a higher rate of premature deaths, and negative impacts on a countries’ economy due to healthcare costs and missing work force. Additionally, they affect the individual’s immune system, which increases susceptibility toward communicable diseases, such as the flu or other viral and bacterial infections. Thus, mitigating the effects of non-communicable diseases is one of the most pressing issues of modern medicine, healthcare, and governments in general. Apart from the predisposition toward such diseases (the genome), their occurrence is associated with environmental parameters that people are exposed to (the exposome). Exposure to stressors such as bad air or water quality, noise, extreme heat, or an overall unnatural surrounding all impact the susceptibility to non-communicable diseases. In the identification of such environmental parameters, geoinformation products derived from Earth Observation data acquired by satellites play an increasingly important role. In this paper, we present a review on the joint use of Earth Observation data and public health data for research on non-communicable diseases. We analyzed 146 articles from peer-reviewed journals (Impact Factor ≥ 2) from all over the world that included Earth Observation data and public health data for their assessments. Our results show that this field of synergistic geohealth analyses is still relatively young, with most studies published within the last five years and within national boundaries. While the contribution of Earth Observation, and especially remote sensing-derived geoinformation products on land surface dynamics is on the rise, there is still a huge potential for transdisciplinary integration into studies. We see the necessity for future research and advocate for the increased incorporation of thematically profound remote sensing products with high spatial and temporal resolution into the mapping of exposomes and thus the vulnerability and resilience assessment of a population regarding non-communicable diseases.
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Contribution of Satellite-Derived Aerosol Optical Depth PM 2.5 Bayesian Concentration Surfaces to Respiratory-Cardiovascular Chronic Disease Hospitalizations in Baltimore, Maryland. ATMOSPHERE 2020; 11:209. [PMID: 33981453 PMCID: PMC8112581 DOI: 10.3390/atmos11020209] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/04/2022]
Abstract
The fine particulate matter baseline (PMB), which includes PM2.5 monitor readings fused with Community Multiscale Air Quality (CMAQ) model predictions, using the Hierarchical Bayesian Model (HBM), is less accurate in rural areas without monitors. To address this issue, an upgraded HBM was used to form four experimental aerosol optical depth (AOD)-PM2.5 concentration surfaces. A case-crossover design and conditional logistic regression evaluated the contribution of the AOD-PM2.5 surfaces and PMB to four respiratory-cardiovascular hospital events in all 99 12 km2 CMAQ grids, and in grids with and without ambient air monitors. For all four health outcomes, only two AOD-PM2.5 surfaces, one not kriged (PMC) and the other kriged (PMCK), had significantly higher Odds Ratios (ORs) on lag days 0, 1, and 01 than PMB in all grids, and in grids without monitors. In grids with monitors, emergency department (ED) asthma PMCK on lag days 0, 1 and 01 and inpatient (IP) heart failure (HF) PMCK ORs on lag days 01 were significantly higher than PMB ORs. Warm season ORs were significantly higher than cold season ORs. Independent confirmation of these results should include AOD-PM2.5 concentration surfaces with greater temporal-spatial resolution, now easily available from geostationary satellites, such as GOES-16 and GOES-17.
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Téllez-Rojo MM, Rothenberg SJ, Texcalac-Sangrador JL, Just AC, Kloog I, Rojas-Saunero LP, Gutiérrez-Avila I, Bautista-Arredondo LF, Tamayo-Ortiz M, Romero M, Hurtado-Díaz M, Schwartz JD, Wright R, Riojas-Rodríguez H. Children's acute respiratory symptoms associated with PM 2.5 estimates in two sequential representative surveys from the Mexico City Metropolitan Area. ENVIRONMENTAL RESEARCH 2020; 180:108868. [PMID: 31711659 DOI: 10.1016/j.envres.2019.108868] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/17/2019] [Revised: 09/26/2019] [Accepted: 10/27/2019] [Indexed: 05/22/2023]
Abstract
BACKGROUND Respiratory diseases are a major component of morbidity in children and their symptoms may be spatially and temporally exacerbated by exposure gradients of fine particulate matter (PM2.5) in large polluted urban areas, like the Mexico City Metropolitan Area (MCMA). OBJECTIVES To analyze the association between satellite-derived and interpolated PM2.5 estimates with children's (≤9 years old) acute respiratory symptoms (ARS) in two probabilistic samples representing the MCMA. METHODS We obtained ARS data from the 2006 and 2012 National Surveys for Health and Nutrition (ENSaNut). Two week average exposure to PM2.5 was assessed for each household with spatial estimates from a hybrid model with satellite measurements of aerosol optical depth (AOD-PM2.5) and also with interpolated PM2.5 measurements from ground stations, from the Mexico City monitoring network (MNW-PM2.5). We used survey-adjusted logistic regressions to analyze the association between PM2.5 estimates and ARS reported on children. RESULTS A total of 1,005 and 1,233 children were surveyed in 2006 and 2012 representing 3.1 and 3.5 million children, respectively. For the same years and over the periods of study, the estimated prevalence of ARS decreased from 49.4% (95% CI: 44.9,53.9%) to 37.8% (95% CI: 34,41.7%). AOD-PM2.5 and MNW-PM2.5 estimates were associated with significantly higher reports of ARS in children 0-4 years old [OR2006 = 1.29 (95% (CI): 0.99,1.68) and OR2006 = 1.24 (95% CI: 1.08,1.42), respectively]. We observed positive non-significant associations in 2012 in both age groups and in 2006 for children 5-9 years old. No statistically significant differences in health effect estimates of PM2.5 were found comparing AOD-PM2.5 or MNW-PM2.5 for exposure assessment. CONCLUSIONS Our findings suggest that PM2.5 is a risk factor for the prevalence of ARS in children and expand the growing evidence of the utility of new satellite AOD-based methods for estimating health effects from acute exposure to PM2.5.
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Affiliation(s)
- Martha M Téllez-Rojo
- Center for Nutrition and Health Research, National Institute of Public Health, Cuernavaca, Morelos, Mexico
| | - Stephen J Rothenberg
- Department of Environmental Health, Center for Population Health Research, National Institute of Public Health, Cuernavaca, Morelos, Mexico
| | - José Luis Texcalac-Sangrador
- Department of Environmental Health, Center for Population Health Research, National Institute of Public Health, Cuernavaca, Morelos, Mexico.
| | - Allan C Just
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Itai Kloog
- Department of Geography and Environmental Development, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | | | - Iván Gutiérrez-Avila
- Center for Nutrition and Health Research, National Institute of Public Health, Cuernavaca, Morelos, Mexico
| | - Luis F Bautista-Arredondo
- Center for Nutrition and Health Research, National Institute of Public Health, Cuernavaca, Morelos, Mexico
| | - Marcela Tamayo-Ortiz
- Center for Nutrition and Health Research, National Institute of Public Health, Cuernavaca, Morelos, Mexico; National Council of Science and Technology Fellowship, Mexico City, Mexico
| | - Martín Romero
- Center for Research in Surveys and Evaluation, National Institute of Public Health, Cuernavaca, Morelos, Mexico
| | - Magali Hurtado-Díaz
- Department of Environmental Health, Center for Population Health Research, National Institute of Public Health, Cuernavaca, Morelos, Mexico
| | - Joel D Schwartz
- Department of Environmental Health, Harvard School of Public Health, Boston, MA, USA
| | - Robert Wright
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Horacio Riojas-Rodríguez
- Department of Environmental Health, Center for Population Health Research, National Institute of Public Health, Cuernavaca, Morelos, Mexico
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Hurtado-Díaz M, Cruz JC, Texcalac-Sangrador JL, Félix-Arellano EE, Gutiérrez-Ávila I, Briseño-Pérez AA, Saavedra-Lara N, Tobías A, Riojas-Rodríguez H. Short-term effects of ambient temperature on non-external and cardiovascular mortality among older adults of metropolitan areas of Mexico. INTERNATIONAL JOURNAL OF BIOMETEOROLOGY 2019; 63:1641-1650. [PMID: 31407098 DOI: 10.1007/s00484-019-01778-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2018] [Revised: 07/18/2019] [Accepted: 07/31/2019] [Indexed: 05/21/2023]
Abstract
Multi-city studies assessing the association between acute exposure to temperature and mortality in Latin American are limited. To analyze the short-term effect of changes in temperature (increase and decrease) on daily non-external and cardiovascular mortality from 1998 to 2014, in people 65 years old and over living in 10 metropolitan areas of Mexico. Analyses were performed through Poisson regression models with distributed lag non-linear models. Statistical comparison of minimum mortality temperature (MMT) and city-specific cutoffs of 24-h temperature mean values (5th/95th and 1st/99th percentiles) were used to obtain the mortality relative Risk (RR) for cold/hot and extreme cold/extreme hot, respectively, for the same day and lags of 0-3, 0-7, and 0-21 days. A meta-analysis was conducted to synthesize the estimates (RRpooled). Significant non-linear associations of temperature-mortality relation were found in U or inverted J shape. The best predictors of mortality associations with cold and heat were daily temperatures at lag 0-7 and lag 0-3, respectively. RRpooled of non-external causes was 6.3% (95%CI 2.7, 10.0) for cold and 10.2% (95%CI 4.4, 16.2) for hot temperatures. The RRpooled for cardiovascular mortality was 7.1% (95%CI 0.01, 14.7) for cold and 7.1% (95%CI 0.6, 14.0) for hot temperatures. Results suggest that, starting from the MMT, the changes in temperature are associated with an increased risk of non-external and specific causes of mortality in elderly people. Generally, heat effects on non-external and specific causes of mortality occur immediately, while cold effects occur within a few days and last longer.
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Affiliation(s)
- Magali Hurtado-Díaz
- National Institute of Public Health, Av. Universidad No. 655 Colonia Santa María Ahuacatitlán, 62100, Cuernavaca, Morelos, Mexico
| | - Julio C Cruz
- National Institute of Public Health, Av. Universidad No. 655 Colonia Santa María Ahuacatitlán, 62100, Cuernavaca, Morelos, Mexico
| | - José L Texcalac-Sangrador
- National Institute of Public Health, Av. Universidad No. 655 Colonia Santa María Ahuacatitlán, 62100, Cuernavaca, Morelos, Mexico
| | - Eunice E Félix-Arellano
- National Institute of Public Health, Av. Universidad No. 655 Colonia Santa María Ahuacatitlán, 62100, Cuernavaca, Morelos, Mexico
| | - Iván Gutiérrez-Ávila
- National Institute of Public Health, Av. Universidad No. 655 Colonia Santa María Ahuacatitlán, 62100, Cuernavaca, Morelos, Mexico
| | - Arely A Briseño-Pérez
- Fielding School of Public Health, Center for Health Sciences, University of California, 650 Charles E. Young Dr. South, Los Angeles, CA, 90095-1772, USA
| | - Nenetzen Saavedra-Lara
- National Institute of Public Health, Av. Universidad No. 655 Colonia Santa María Ahuacatitlán, 62100, Cuernavaca, Morelos, Mexico
| | - Aurelio Tobías
- Institute of Environmental Assessment and Water Research (IDAEA) - Spanish Council for Scientific Research (CSIC), C/Jordi Girona 18-26, 08034, Barcelona, Spain
| | - Horacio Riojas-Rodríguez
- National Institute of Public Health, Av. Universidad No. 655 Colonia Santa María Ahuacatitlán, 62100, Cuernavaca, Morelos, Mexico.
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Wang H, Gao Z, Ren J, Liu Y, Chang LTC, Cheung K, Feng Y, Li Y. An urban-rural and sex differences in cancer incidence and mortality and the relationship with PM 2.5 exposure: An ecological study in the southeastern side of Hu line. CHEMOSPHERE 2019; 216:766-773. [PMID: 30391899 DOI: 10.1016/j.chemosphere.2018.10.183] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/30/2018] [Revised: 10/23/2018] [Accepted: 10/26/2018] [Indexed: 05/28/2023]
Abstract
This study investigates the urban-rural and sex differences in the increased risks of the ten most common cancers in China related to high PM2.5 concentration in the southeastern side of Hu line. Pearson correlation coefficient is estimated to reveal how the cancers closely associated with PM2.5 long-term exposure. Then linear regression is conducted to evaluate sex- and area-specific increased risks of those cancers from high level PM2.5 long-term exposure. The major finding is with the increase of every 10 μg/m3 of annual mean PM2.5 concentration, the increase of relative risks for lung cancer incidence and mortality are 15% and 23% for males, and 22% and 24% for females in rural area. For urban area, the increase of relative risk for ovarian cancer incidence is 9% for females, while that for prostatic cancer increases 17% for males. For leukemia, the increase of relative risks for incidence and mortality are 22% and 19% for females in rural area, while in urban area the increase of relative risk for mortality is 9% for males and for incidence is 6% for females. It is also found that with increased PM2.5 exposure, the risks for ovarian and prostatic cancer rise significantly in urban area, while risks for lung cancer and leukemia rise significantly in rural area. The results demonstrate the higher risks for lung cancer and leukemia with increased PM2.5 exposure are more significant for female. This study also suggests that the carcinogenic effects of PM2.5 have obvious sex and urban-rural differences.
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Affiliation(s)
- Hong Wang
- Key Laboratory of Meteorological Disaster of Ministry of Education, Collaborative Innovation Centre on Forecast and Evaluation of Meteorological Disasters, School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing, 210044, China
| | - Zhiqiu Gao
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China.
| | - Jingzheng Ren
- Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong, SAR, China.
| | - Yibo Liu
- Jiangsu Key Laboratory of Agricultural Meteorology, School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | | | - Kevin Cheung
- Department of Environment and Geography, Macquarie University, Sydney, Australia
| | - Yun Feng
- Shanghai General Hospital, Shanghai, China
| | - Yubin Li
- Key Laboratory of Meteorological Disaster of Ministry of Education, Collaborative Innovation Centre on Forecast and Evaluation of Meteorological Disasters, School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing, 210044, China
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Dietrich D, Dekova R, Davy S, Fahrni G, Geissbühler A. Applications of Space Technologies to Global Health: Scoping Review. J Med Internet Res 2018; 20:e230. [PMID: 29950289 PMCID: PMC6041558 DOI: 10.2196/jmir.9458] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2017] [Revised: 03/21/2018] [Accepted: 04/22/2018] [Indexed: 12/27/2022] Open
Abstract
Background Space technology has an impact on many domains of activity on earth, including in the field of global health. With the recent adoption of the United Nations’ Sustainable Development Goals that highlight the need for strengthening partnerships in different domains, it is useful to better characterize the relationship between space technology and global health. Objective The aim of this study was to identify the applications of space technologies to global health, the key stakeholders in the field, as well as gaps and challenges. Methods We used a scoping review methodology, including a literature review and the involvement of stakeholders, via a brief self-administered, open-response questionnaire. A distinct search on several search engines was conducted for each of the four key technological domains that were previously identified by the UN Office for Outer Space Affairs’ Expert Group on Space and Global Health (Domain A: remote sensing; Domain B: global navigation satellite systems; Domain C: satellite communication; and Domain D: human space flight). Themes in which space technologies are of benefit to global health were extracted. Key stakeholders, as well as gaps, challenges, and perspectives were identified. Results A total of 222 sources were included for Domain A, 82 sources for Domain B, 144 sources for Domain C, and 31 sources for Domain D. A total of 3 questionnaires out of 16 sent were answered. Global navigation satellite systems and geographic information systems are used for the study and forecasting of communicable and noncommunicable diseases; satellite communication and global navigation satellite systems for disaster response; satellite communication for telemedicine and tele-education; and global navigation satellite systems for autonomy improvement, access to health care, as well as for safe and efficient transportation. Various health research and technologies developed for inhabited space flights have been adapted for terrestrial use. Conclusions Although numerous examples of space technology applications to global health exist, improved awareness, training, and collaboration of the research community is needed.
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Affiliation(s)
- Damien Dietrich
- Hopitaux Universitaires de Genève, eHealth and Telemedicine Division, Geneva, Switzerland
| | - Ralitza Dekova
- Hopitaux Universitaires de Genève, eHealth and Telemedicine Division, Geneva, Switzerland
| | - Stephan Davy
- Hopitaux Universitaires de Genève, eHealth and Telemedicine Division, Geneva, Switzerland
| | - Guillaume Fahrni
- Hopitaux Universitaires de Genève, eHealth and Telemedicine Division, Geneva, Switzerland
| | - Antoine Geissbühler
- Hopitaux Universitaires de Genève, eHealth and Telemedicine Division, Geneva, Switzerland
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12
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Assessment and Improvement of MISR Angstrom Exponent and Single-Scattering Albedo Products Using AERONET Data in China. REMOTE SENSING 2017. [DOI: 10.3390/rs9070693] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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13
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Modelling Seasonal GWR of Daily PM2.5 with Proper Auxiliary Variables for the Yangtze River Delta. REMOTE SENSING 2017. [DOI: 10.3390/rs9040346] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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14
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Chudnovsky AA, Koutrakis P, Kostinski A, Proctor SP, Garshick E. Spatial and temporal variability in desert dust and anthropogenic pollution in Iraq, 1997-2010. JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION (1995) 2017; 67:17-26. [PMID: 28001122 PMCID: PMC5179983 DOI: 10.1080/10962247.2016.1153528] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/15/2023]
Abstract
UNLABELLED Satellite imaging has emerged as a method for monitoring regional air pollution and detecting areas of high dust concentrations. Unlike ground observations, continuous data monitoring is available with global coverage of terrestrial and atmospheric components. In this study we test the utility of different sources of satellite data to assess air pollution concentrations in Iraq. SeaWiFS and MODIS Deep Blue (DB) aerosol optical depth (AOD) products were evaluated and used to characterize the spatial and temporal pollution levels from the late 1990s through 2010. The AOD and Ångström exponent (an indicator of particle size, since smaller Ångström exponent values reflect a source that includes larger particles) were correlated on 50 × 50 km spatial resolution. Generally, AOD and Ångström exponent were inversely correlated, suggesting a significant contribution of coarse particles from dust storms to AOD maxima. Although the majority of grid cells exhibited this trend, a weaker relationship in other locations suggested an additional contribution of fine particles from anthropogenic sources. Tropospheric NO2 densities from the OMI satellite were elevated over cities, also consistent with a contribution from anthropogenic sources. Our analysis demonstrates the use of satellite imaging data to estimate relative pollution levels and source contributions in areas of the world where direct measurements are not available. IMPLICATIONS The authors demonstrated how satellite data can be used to characterize exposures to dust and to anthropogenic pollution for future health related studies. This approach is of a great potential to investigate the associations between subject-specific exposures to different pollution sources and their health effects in inaccessible regions and areas where ground monitoring is unavailable.
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Affiliation(s)
- A Alexandra Chudnovsky
- a Tel-Aviv University , Department of Geography and Human Environment , Tel-Aviv , Israel
- b Department of Environmental Health , Harvard T.H. Chan School of Public Health , Boston , MA , USA
| | - Petros Koutrakis
- b Department of Environmental Health , Harvard T.H. Chan School of Public Health , Boston , MA , USA
| | - Alex Kostinski
- c Michigan Technological University , Houghton , MI , USA
| | - Susan P Proctor
- d Military Performance Division , U.S. Army Research Institute of Environmental Medicine , Natick , MA , USA
- e Department of Environmental Health , Boston University School of Public Health , Boston , MA , USA
- f Research Service, VA Boston Healthcare System , Boston , MA , USA
| | - Eric Garshick
- g Pulmonary, Allergy, Sleep, and Critical Care Medicine Section , Medical Service, VA Boston Healthcare System , Boston , MA , USA
- h Channing Division of Network Medicine , Brigham and Women's Hospital, Harvard Medical School , Boston , MA , USA
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15
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Abstract
PURPOSE OF REVIEW Particulate matter air pollution is a ubiquitous exposure linked with multiple adverse health outcomes for children and across the life course. The recent development of satellite-based remote-sensing models for air pollution enables the quantification of these risks and addresses many limitations of previous air pollution research strategies. We review the recent literature on the applications of satellite remote sensing in air quality research, with a focus on their use in epidemiological studies. RECENT FINDINGS Aerosol optical depth (AOD) is a focus of this review and a significant number of studies show that ground-level particulate matter can be estimated from columnar AOD. Satellite measurements have been found to be an important source of data for particulate matter model-based exposure estimates, and recently have been used in health studies to increase the spatial breadth and temporal resolution of these estimates. SUMMARY It is suggested that satellite-based models improve our understanding of the spatial characteristics of air quality. Although the adoption of satellite-based measures of air quality in health studies is in its infancy, it is rapidly growing. Nevertheless, further investigation is still needed in order to have a better understanding of the AOD contribution to these prediction models in order to use them with higher accuracy in epidemiological studies.
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Affiliation(s)
- Meytar Sorek-Hamer
- Department of Geography and Environmental Development, Ben-Gurion University, Beer Sheva, Israel
- Civil and Environmental Engineering, Technion, Haifa, Israel
| | - Allan C. Just
- Department of Preventive Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Itai Kloog
- Department of Geography and Environmental Development, Ben-Gurion University, Beer Sheva, Israel
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16
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Comparison of Four Ground-Level PM2.5 Estimation Models Using PARASOL Aerosol Optical Depth Data from China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2016; 13:180. [PMID: 26840329 PMCID: PMC4772200 DOI: 10.3390/ijerph13020180] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/09/2015] [Revised: 01/19/2016] [Accepted: 01/25/2016] [Indexed: 11/16/2022]
Abstract
Satellite remote sensing is of considerable importance for estimating ground-level PM2.5 concentrations to support environmental agencies monitoring air quality. However, most current studies have focused mainly on the application of MODIS aerosol optical depth (AOD) to predict PM2.5 concentrations, while PARASOL AOD, which is sensitive to fine-mode aerosols over land surfaces, has received little attention. In this study, we compared a linear regression model, a quadratic regression model, a power regression model and a logarithmic regression model, which were developed using PARASOL level 2 AOD collected in China from 18 January 2013 to 10 October 2013. We obtained R (correlation coefficient) values of 0.64, 0.63, 0.62, and 0.57 for the four models when they were cross validated with the observed values. Furthermore, after all the data were classified into six levels according to the Air Quality Index (AQI), a low level of statistical significance between the four empirical models was found when the ground-level PM2.5 concentrations were greater than 75 μg/m3. The maximum R value was 0.44 (for the logarithmic regression model and the power model), and the minimum R value was 0.28 (for the logarithmic regression model and the power model) when the PM2.5 concentrations were less than 75 μg/m3. We also discussed uncertainty sources and possible improvements.
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17
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Kumar M, Singh RS, Banerjee T. Associating airborne particulates and human health: Exploring possibilities: Comment on: Kim, Ki-Hyun, Kabir, E. and Kabir, S. 2015. A review on the human health impact of airborne particulate matter. Environment International 74 (2015) 136-143. ENVIRONMENT INTERNATIONAL 2015; 84:201-202. [PMID: 26093957 DOI: 10.1016/j.envint.2015.06.002] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/15/2015] [Accepted: 06/02/2015] [Indexed: 06/04/2023]
Affiliation(s)
- M Kumar
- Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi, India
| | - R S Singh
- Department of Chemical Engineering and Technology, Indian Institute of Technology, Banaras Hindu University, Varanasi, India
| | - T Banerjee
- Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi, India.
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18
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Yang Y, Cao Y, Li W, Li R, Wang M, Wu Z, Xu Q. Multi-site time series analysis of acute effects of multiple air pollutants on respiratory mortality: a population-based study in Beijing, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2015; 508:178-87. [PMID: 25478654 DOI: 10.1016/j.scitotenv.2014.11.070] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/04/2014] [Revised: 10/26/2014] [Accepted: 11/21/2014] [Indexed: 05/22/2023]
Abstract
In large cities in China, the traffic-related air pollution has become the focus of attention, and its adverse effects on health have raised public concerns. We conducted a study to quantify the association between exposure to three major traffic-related pollutants - particulate matter < 10 μm in aerodynamic diameter (PM10), carbon monoxide (CO) and nitrogen dioxide (NO2) and the risk of respiratory mortality in Beijing, China at a daily spatiotemporal resolution. We used the generalized additive models (GAM) with natural splines and principal component regression method to associate air pollutants with daily respiratory mortality, covariates and confounders. The GAM analysis adjusting for the collinearity among pollutants indicated that PM10, CO and NO2 had significant effects on daily respiratory mortality in Beijing. An interquartile range increase in 2-day moving averages concentrations of day 0 and day 1 of PM10, CO and NO2 corresponded to 0.99 [95% confidence interval (CI): 0.30, 1.67], 0.89 (95% CI: 0.27, 1.51) and 0.95 (95% CI: 0.29, 1.61) percent increase in daily respiratory mortality, respectively. The effects were varied across the districts. The strongest effects were found in two rural districts and one suburban district but significant in only one district. In conclusion, high level of several traffic-related air pollutants is associated with an increased risk of respiratory mortality in Beijing over a short-time period. The high risk found in rural areas suggests a potential susceptible sub-population with undiagnosed respiratory diseases in these areas. Although the rural areas have relatively lower air pollution levels, they deserve more attention to respiratory disease prevention and air pollution reduction.
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Affiliation(s)
- Yang Yang
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China
| | - Yang Cao
- Unit of Biostatistics, Division of Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm 17177, Sweden.
| | - Wenjing Li
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China
| | - Runkui Li
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Meng Wang
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China
| | - Zhenglai Wu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China
| | - Qun Xu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China.
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Xiao Q, Ma Z, Li S, Liu Y. The impact of winter heating on air pollution in China. PLoS One 2015; 10:e0117311. [PMID: 25629878 PMCID: PMC4309400 DOI: 10.1371/journal.pone.0117311] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2014] [Accepted: 12/20/2014] [Indexed: 11/24/2022] Open
Abstract
Fossil-fuel combustion related winter heating has become a major air quality and public health concern in northern China recently. We analyzed the impact of winter heating on aerosol loadings over China using the MODIS-Aqua Collection 6 aerosol product from 2004–2012. Absolute humidity (AH) and planetary boundary layer height (PBL) -adjusted aerosol optical depth (AOD*) was constructed to reflect ground-level PM2.5 concentrations. GIS analysis, standard statistical tests, and statistical modeling indicate that winter heating is an important factor causing increased PM2.5 levels in more than three-quarters of central and eastern China. The heating season AOD* was more than five times higher as the non-heating season AOD*, and the increase in AOD* in the heating areas was greater than in the non-heating areas. Finally, central heating tend to contribute less to air pollution relative to other means of household heating.
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Affiliation(s)
- Qingyang Xiao
- Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America
| | - Zongwei Ma
- Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, China
| | - Shenshen Li
- Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America
- State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Beijing, China
| | - Yang Liu
- Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America
- * E-mail:
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20
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Xu Z, Liu Y, Ma Z, Li S, Hu W, Tong S. Impact of temperature on childhood pneumonia estimated from satellite remote sensing. ENVIRONMENTAL RESEARCH 2014; 132:334-41. [PMID: 24834830 DOI: 10.1016/j.envres.2014.04.021] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/21/2014] [Revised: 04/07/2014] [Accepted: 04/10/2014] [Indexed: 05/20/2023]
Abstract
The effect of temperature on childhood pneumonia in subtropical regions is largely unknown so far. This study examined the impact of temperature on childhood pneumonia in Brisbane, Australia. A quasi-Poisson generalized linear model combined with a distributed lag non-linear model was used to quantify the main effect of temperature on emergency department visits (EDVs) for childhood pneumonia in Brisbane from 2001 to 2010. The model residuals were checked to identify added effects due to heat waves or cold spells. Both high and low temperatures were associated with an increase in EDVs for childhood pneumonia. Children aged 2-5 years, and female children were particularly vulnerable to the impacts of heat and cold, and Indigenous children were sensitive to heat. Heat waves and cold spells had significant added effects on childhood pneumonia, and the magnitude of these effects increased with intensity and duration. There were changes over time in both the main and added effects of temperature on childhood pneumonia. Children, especially those female and Indigenous, should be particularly protected from extreme temperatures. Future development of early warning systems should take the change over time in the impact of temperature on children's health into account.
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Affiliation(s)
- Zhiwei Xu
- School of Public Health and Social Work & Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia
| | - Yang Liu
- Rollins School of Public Health, Emory University, Atlanta, GA, United States
| | - Zongwei Ma
- Rollins School of Public Health, Emory University, Atlanta, GA, United States
| | - Shenghui Li
- School of Public Health, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Wenbiao Hu
- School of Public Health and Social Work & Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia
| | - Shilu Tong
- School of Public Health and Social Work & Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia.
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22
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Hyder A, Lee HJ, Ebisu K, Koutrakis P, Belanger K, Bell ML. PM2.5 exposure and birth outcomes: use of satellite- and monitor-based data. Epidemiology 2014; 25:58-67. [PMID: 24240652 PMCID: PMC4009503 DOI: 10.1097/ede.0000000000000027] [Citation(s) in RCA: 119] [Impact Index Per Article: 11.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
BACKGROUND Air pollution may be related to adverse birth outcomes. Exposure information from land-based monitoring stations often suffers from limited spatial coverage. Satellite data offer an alternative data source for exposure assessment. METHODS We used birth certificate data for births in Connecticut and Massachusetts, United States (2000-2006). Gestational exposure to PM2.5 was estimated from US Environmental Protection Agency monitoring data and from satellite data. Satellite data were processed and modeled by using two methods-denoted satellite (1) and satellite (2)-before exposure assessment. Regression models related PM2.5 exposure to birth outcomes while controlling for several confounders. Birth outcomes were mean birth weight at term birth, low birth weight at term (<2500 g), small for gestational age (SGA, <10th percentile for gestational age and sex), and preterm birth (<37 weeks). RESULTS Overall, the exposure assessment method modified the magnitude of the effect estimates of PM2.5 on birth outcomes. Change in birth weight per interquartile range (2.41 μg/m) increase in PM2.5 was -6 g (95% confidence interval = -8 to -5), -16 g (-21 to -11), and -19 g (-23 to -15), using the monitor, satellite (1), and satellite (2) methods, respectively. Adjusted odds ratios, based on the same three exposure methods, for term low birth weight were 1.01 (0.98-1.04), 1.06 (0.97-1.16), and 1.08 (1.01-1.16); for SGA, 1.03 (1.01-1.04), 1.06 (1.03-1.10), and 1.08 (1.04-1.11); and for preterm birth, 1.00 (0.99-1.02), 0.98 (0.94-1.03), and 0.99 (0.95-1.03). CONCLUSIONS Under exposure assessment methods, we found associations between PM2.5 exposure and adverse birth outcomes particularly for birth weight among term births and for SGA. These results add to the growing concerns that air pollution adversely affects infant health and suggest that analysis of health consequences based on satellite-based exposure assessment can provide additional useful information.
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Affiliation(s)
- Ayaz Hyder
- From the a School of Public Health, Yale University, New Haven, CT; bDepartment of Environmental Health, Harvard School of Public Health, Harvard University, Boston, MA; cand School of Forestry and Environmental Studies, Yale University, New Haven, CT
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