Global_Environmental_Research_Vol.27No.1
64/80

Annex 1 Full list of publications included in the study. 58 Study Location California, USA Study duration February 1 – December 31, 2020 June 5 – July 6, 2012 Colorado, USA Portugal October 2017 15 African countries 2005 – 2015 Northern South America February 2010 – February 2018 September 2013 – February 2014 India 2000 – 2016 749 cities in 43 countries and regions, globally Brazil 2003 – 2018 Equatorial Asia September 1 – December 2015 Mato Grosso, Brazil July 1, 2004 – December 31, 2005 November 2018 Weekly clinic visit counts for AD or San Francisco, USA 2003 – 2010 10 southern European cities in Spain, France, Italy and Greece Contiguous United States (without Hawaii) early 21st century (2000–2010) midcentury (2040–2050) late century (2090–2099) Health Outcome Confirmed COVID-19 cases Respiratory and cardiovascular emergency department visits Mortality Infant mortality All-cause mortality Cardiovascular and respiratory mortality Chronic Obstructive Pulmonary Disease (COPD) Respiratory emergency visits Seeking treatment for Acute Respiratory Infection All-cause mortality Cardiovascular mortality Respiratory mortality Mortality All-cause Mortality Low birth weight at term itch Natural mortality Cardiovascular mortality Respiratory mortality All-cause mortality Data Collection Method Sohrabinia, M. and Khorshiddoust, A.M. (2007) Application of satellite data and GIS in studying air pollutants in Tehran. Habitat International, 31(2): 268–275. https://doi.org/10.1016/j.habitatint. 2007.02.003 Sorek-Hamer, M., Chatfield, R. and Liu, Y. (2020) Review: Strategies for using satellite-based products in modeling PM2.5 and short-term pollution episodes. Environment International, 144: 106057. https://doi.org/10.1016/j.envint.2020.106057 Stowell, J.D., Geng, G., Saikawa, E., Chang, H.H., Fu, J., Yang, C.-E., Zhu, Q., Liu, Y. and Strickland, M.J. (2019) Associations of wildfire smoke PM2.5 exposure with cardiorespiratory events in Colorado 2011–2014. Environment International, 133, 105151. https://doi.org/10.1016/j.envint.2019.105151 Taylor, D. (2010) Biomass burning, humans and climate change in Southeast Asia. Biodiversity and Conservation, 19(4): 1025–1042. https://doi.org/10.1007/s10531-009-9756-6 Thomas, A.S., Escobedo, F.J., Sloggy, M.R. and Sánchez, J.J. (2022) A burning the socio-demographic and environmental justice aspects of the wildfire literature. PLOS ONE, 17(7): e0271019. https://doi.org/10.1371/journal.pone.0271019 Valari, M., Menut, L. and Chatignoux, E. (2011) Using a chemistry transport model to account for the spatial variability of exposure concentrations in epidemiologic air pollution studies. Journal of the Air & Waste Management Association, 61(2): 164–179. https://doi.org/10.3155/1047-3289.61.2.164 Vohra, K., Vodonos, A., Schwartz, J., Marais, E.A., Sulprizio, M.P. and Mickley, L.J. (2021) Global mortality from outdoor fine particle pollution generated by fossil fuel combustion: Results from GEOS-Chem. Environmental Research, 195: 110754. https://doi.org/10.1016/j.envres.2021.110754 Wani, M.A., Mishra, A.K., Sharma, S., Mayer, I.A. and Ahmad, M. (2021) Source profiling of air pollution and its association with Ademu, et al., 2022 Alman, et al., 2016 Augusto, et al., 2020 Bachwenkizi, et al., 2021 Ballesteros-Gonzales, et al., 2020, 2020 Chakrabarti, et al., 2019 Chen, et al., 2021 Cobelo, et al., 2023 Crippa, et al., 2016 Da Silva, et al., 2014 Fadadu, et al., 2021 Faustini, et al., 2019 Ford, et al., 2018 aer.p20171134 issue: Reviewing S. VALENZUELA et al. Station monitoring Weather Research and Forecasting Model with Chemistry (WRF-Chem); Model for Ozone and Related chemical Tracers (MOZART-4); National Center for Environmental Protection’s North American Mesoscale Forecast System (NCEP/NAM); NCAR Fire Inventory (FINN); SMARTFIRE framework; EPA surface network Satellite imaging using the Navy Aerosol Analysis and Prediction System (NAAPS) Station monitoring (52 fixed air quality monitoring stations) Chemical transport model (GEOS-Chem); Satellite monitoring; Ground based observations Chemical transport model using Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem) Moderate-Resolution Imaging Spectroradiometer (MODIS) Chemical transport model (GEOS-Chem) Fire Information for Resource Management System (FIRMS) provided by NASA; Copernicus Atmosphere Monitoring Service (CAMS); Meteorological variables from the ERA-Interim model; Pixel-based classification of Landsat satellite images by MapBiomas Weather Research and Forecasting model (version 3.5) with Chemistry (WRF-Chem) Coupled Aerosol and Trace Gas Transport Model to the Brazilian Developments of the Regional Atmospheric Modeling System (CATT-BRAMS Model) and Center for Weather Forecasting and Climate Studies of the National Institute for Space Research (INPE-CPTEC) Station monitoring and satellite-based smoke plume density scores rom the Bay Area Air Quality Management District Navy Aerosol Analysis and Prediction System (NAAPS) model; Satellite measurements and fire-related smoke plumes Community Atmospheric Model v4 with an interactive gas‐aerosol scheme (CAM‐Chem); Community Earth System Model (CESM); Community Land Model (CLM) v4.5 acute respiratory infections in the Himalayan-bound region of India. Environmental Science and Pollution Research, 28(48): 68600–68614. https://doi.org/10.1007/s11356-021-15413-0 World Health Organization (2022, December 19) Ambient (outdoor) air pollution. https://www.who.int/news-room/fact-sheets/detail/ ambient-(outdoor)-air-quality-and-health#:~:text=The%20combined%20effects%20of%20ambient,premature%20deaths%20worldwide%20in%202019 (accessed 14 November 2023) Wu, Y., Li, S., Xu, R., Chen, G., Yue, X., Yu, P., Ye, T., Wen, B., De Sousa Zanotti Stagliorio Coêlho, M., Saldiva, P.H.N. and Guo, Y. (2023) Wildfire-related PM2.5 and health economic loss of mortality in Brazil. Environment International, 174: 107906. https://doi.org/10.1016/j.envint.2023.107906 Xie, X., Semanjski, I., Gautama, S., Tsiligianni, E., Deligiannis, N., Rajan, R., Pasveer, F. and Philips, W. (2017) A review of urban air pollution monitoring and exposure assessment methods. ISPRS International Journal of Geo-Information, 6(12): 389. https://doi.org/10.3390/ijgi6120389 Yao, W., Zhao, Y., Chen, R., Wang, M., Song, W. and Yu, D. (2023) Emissions of toxic substances from biomass burning: A review of methods and technical influencing factors. Processes, 11(3): 853. https://doi.org/10.3390/pr11030853 Zou, J., Lu, N., Jiang, H., Qin, J., Yao, L., Xin, Y. and Su, F. (2022) Performance of air temperature from ERA5-Land reanalysis in coastal urban agglomeration of Southeast China. Science of The Total Environment, 828: 154459. https://doi.org/10.1016/ j.scitotenv.2022.154459 Zou, Y., O’Neill, S.M., Larkin, N.K., Alvarado, E.C., Solomon, R., Mass, C., Liu, Y., Odman, M.T. and Shen, H. (2019) Machine learning-based integration of high-resolution wildfire smoke simulations and observations impact assessment. International Journal of Environmental Research and Public Health, 16, 2137. https://doi.org/10.3390/ijerph16122137 for regional health

元のページ  ../index.html#64

このブックを見る