Listed below are known citations to the NASA Socioeconomic Data and Applications Center (SEDAC) Satellite-Derived Environmental Indicators data collection. The data collection, and specific data set (if known), being cited are beneath each citation. Citations to multiple collections/sets are listed on separate lines. If a publication cites remotely sensed earth observation data, whether from NASA or another source, those instruments and/or platforms are listed as well.
List last updated on 3 October 2023.

Ai, H., Wang, M., Zhang, Y.-J., & Zhu, T.-T. (2022). How does air pollution affect urban innovation capability? Evidence from 281 cities in China. Structural Change and Economic Dynamics, 61, 166-178. doi:10.1016/j.strueco.2022.02.012
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Aina, Y. A. (2017). Achieving smart sustainable cities with GeoICT support: The Saudi evolving smart cities. Cities, 71, 49-58. doi:10.1016/j.cities.2017.07.007
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Aina, Y. A., van der Merwe, J., & Alshuwaikhat, H. (2014). Spatial and temporal variations of satellite-derived multi-year particulate data of Saudi Arabia: An exploratory analysis. International Journal of Environmental Research and Public Health, 11(11), 11152-11166. doi:10.3390/ijerph111111152
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Al Faisal, A., Rahman, M. M., & Haque, S. (2022). Retrieving spatial variation of aerosol level over urban mixed land surfaces using Landsat imageries: Degree of air pollution in Dhaka Metropolitan Area. Physics and Chemistry of the Earth, Parts A/B/C, 126, 103074. doi:10.1016/j.pce.2021.103074
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)
NASA REMOTE SENSING (MODIS)
REMOTE SENSING (Landsat)

Alberti, M., & Wang, T. (2022). Detecting patterns of vertebrate biodiversity across the multidimensional urban landscape. Ecology Letters, 25(4), 1027-1045. doi:10.1111/ele.13969
Satellite-Derived Environmental Indicators (Global Summer Land Surface Temperature (LST) Grids, v1)
U.S. Census Grids (Summary File 1, v1 (2010))

Aldhous, P. (2019). These maps show how many cities are much hotter than their surroundings.  Retrieved from https://www.buzzfeednews.com/article/peteraldhous/summer-urban-heat-island-maps
Satellite-Derived Environmental Indicators (Global Urban Heat Island (UHI) Data Set, v1)

Alnwisi, S. M. M., Chai, C., Acharya, B. K., Qian, A. M., Zhang, S., Zhang, Z., . . . Lin, H. (2022). Empirical dynamic modeling of the association between ambient PM2.5 and under-five mortality across 2851 counties in Mainland China, 1999–2012. Ecotoxicology and Environmental Safety, 237, 113513. doi:10.1016/j.ecoenv.2022.113513
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Amegbor, P. M. (2022). Early-life environmental exposures and anaemia among children under age five in Sub-Saharan Africa: An insight from the Demographic & Health Surveys. Science of The Total Environment, 832, 154957. doi:10.1016/j.scitotenv.2022.154957
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Amegbor, P. M., Borges, S. S., Pysklywec, A., & Sabel, C. E. (2022). Effect of individual, household and regional socioeconomic factors and PM2.5 on anaemia: A cross-sectional study of sub-Saharan African countries. Spatial and Spatio-temporal Epidemiology, 40, 100472. doi:10.1016/j.sste.2021.100472
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Amegbor, P. M., Yankey, O., Davies, M., & Sabel, C. E. (2022). Individual and contextual predictors of overweight or obesity among women in Uganda: a spatio-temporal perspective. GeoJournal, 87, 3793-3813. doi:10.1007/s10708-021-10466-7
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1) - 10.7927/H4ZK5DQS

Bai, J., & Yu, X. (2021). Export trade and smog pollution: Empirical evidence from China. Growth and Change, 52(1), 224-242. doi:10.1111/grow.12463
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Bai, K., Ma, M., Chang, N.-B., & Gao, W. (2019). Spatiotemporal trend analysis for fine particulate matter concentrations in China using high-resolution satellite-derived and ground-measured PM2.5 data. Journal of Environmental Management, 233, 530-542. doi:10.1016/j.jenvman.2018.12.071
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Baniasad, M., Mofrad, M. G., Bahmanabadi, B., & Jamshidi, S. (2021). COVID-19 in Asia: Transmission factors, re-opening policies, and vaccination simulation. Environmental Research, 202, 111657. doi:10.1016/j.envres.2021.111657
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Banks, A., Kooperman, G. J., & Xu, Y. (2022). Meteorological influences on anthropogenic PM2.5 in future climates: Species level analysis in the Community Earth System Model v2. Earth's Future, 10(2), e2021EF002298. doi:10.1029/2021EF002298
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1) - 10.7927/H4ZK5DQS

Banzhaf, E., Bulley, H. N., Inkoom, J. N., & Elze, S. (2022). Mapping open data and big data to address climate resilience of urban informal settlements in Sub-Saharan Africa. Climate, 10(12), 186. doi:10.3390/cli10120186
Gridded Population of the World (GPW) v4.11 (population count)
Gridded Population of the World (GPW) v4.11 (population density)
Satellite-Derived Environmental Indicators (Global Urban Heat Island (UHI) Data Set, v1)

Bao, H., Shan, L., Wang, Y., Jiang, Y., Lee, C., & Cui, X. (2021). How does local real estate investment influence neighborhood PM2.5 concentrations? A spatial econometric analysis. Land, 10(5), 518. doi:10.3390/land10050518
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Bergs, R., & Budde, R. (2022). The potential of small-scale spatial data in regional science. Review of Regional Research, 42(2), 97-110. doi:10.1007/s10037-022-00172-3
Satellite-Derived Environmental Indicators (Global High Resolution Daily Extreme Urban Heat Exposure (UHE-Daily), v1)

Berry, L. (2020). Explore Air Quality with New Layers and Maps in ArcGIS Living Atlas.  Retrieved from https://www.esri.com/arcgis-blog/products/arcgis-living-atlas/analytics/explore-air-quality/
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Bombardini, M., & Li, B. (2020). Trade, pollution and mortality in China. Journal of International Economics, 125, 103321. doi:10.1016/j.jinteco.2020.103321
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v1)

Bowe, B., Xie, Y., Li, T., Yan, Y., Xian, H., & Al-Aly, Z. (2018). The 2016 global and national burden of diabetes mellitus attributable to PM2·5 air pollution. The Lancet Planetary Health, 2(7), e301-e312. doi:10.1016/S2542-5196(18)30140-2
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v1)

Bowe, B., Xie, Y., Li, T., Yan, Y., Xian, H., & Al-Aly, Z. (2018). Particulate matter air pollution and the risk of incident CKD and progression to ESRD. Journal of the American Society of Nephrology, 29(1), 218-230. doi:10.1681/asn.2017030253
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v1)

Bowe, B., Xie, Y., Li, T., Yan, Y., Xian, H., & Al-Aly, Z. (2019). Estimates of the 2016 global burden of kidney disease attributable to ambient fine particulate matter air pollution. BMJ Open, 9(5), e022450. doi:10.1136/bmjopen-2018-022450
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v1)

Bowe, B., Xie, Y., Yan, Y., Xian, H., & Al-Aly, Z. (2020). Diabetes minimally mediated the association between PM2.5 air pollution and kidney outcomes. Scientific Reports, 10(1), 4586. doi:10.1038/s41598-020-61115-x
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Boyd, D. S., Perrat, B., Li, X., Jackson, B., Landman, T., Ling, F., . . . Foody, G. M. (2021). Informing action for United Nations SDG target 8.7 and interdependent SDGs: Examining modern slavery from space. Humanities and Social Sciences Communications, 8(1), 111. doi:10.1057/s41599-021-00792-z
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)
NASA REMOTE SENSING (MODIS - MCD12Q2)
REMOTE SENSING (Airbus Pléiades)
REMOTE SENSING (DMSP-OLS)
REMOTE SENSING (Landsat)

Browning, M. H. E. M., Lee, K., & Wolf, K. (2019). Tree cover shows an inverse relationship with depressive symptoms in elderly residents living in U.S. nursing homes. Urban Forestry & Urban Greening, 41, 23-32. doi:10.1016/j.ufug.2019.03.002
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Cao, J., Ho, M. S., Ma, R., & Teng, F. (2021). When carbon emission trading meets a regulated industry: Evidence from the electricity sector of China. Journal of Public Economics, 200, 104470. doi:10.1016/j.jpubeco.2021.104470
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)
NASA REMOTE SENSING (OMI NO2)

Cao, L., Gao, J., & Xia, Y. (2021). The effects of household solid fuel use on self-reported and performance-based physical functioning in middle-aged and older Chinese populations: A cross-sectional study. Ecotoxicology and Environmental Safety, 213, 112053. doi:10.1016/j.ecoenv.2021.112053
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Cao, Q., Liang, Y., & Niu, X. (2017). China’s air quality and respiratory disease mortality based on the spatial panel model. International Journal of Environmental Research and Public Health, 14(9), 15pp. doi:10.3390/ijerph14091081
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v1)

Cao, Q., Rui, G., & Liang, Y. (2018). Study on PM2.5 pollution and the mortality due to lung cancer in China based on geographic weighted regression model. BMC Public Health, 18(1), 925. doi:10.1186/s12889-018-5844-4
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v1)

Cárdenas, M., Bonilla, J. P., & Brusa, F. (2021). Climate Policies in Latin America and the Caribbean: Success Stories and Challenges in the Fight against Climate Change. Retrieved from https://doi.org/10.18235/0003239
National Aggregates of Geospatial Data Collection (NAGDC) (Population, Landscape, And Climate Estimates (PLACE), v3) - 10.7927/H4F769GP
Satellite-Derived Environmental Indicators (Trends in Global Freshwater Availability from the Gravity Recovery and Climate Experiment (GRACE), v1)

Carrasco-Escobar, G., Schwalb, A., Tello-Lizarraga, K., Vega-Guerovich, P., & Ugarte-Gil, C. (2020). Spatio-temporal co-occurrence of hotspots of tuberculosis, poverty and air pollution in Lima, Peru. Infectious Diseases of Poverty, 9(1), 32. doi:10.1186/s40249-020-00647-w
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Carrasco-Escobar, G., Schwarz, L., Miranda, J. J., & Benmarhnia, T. (2020). Revealing the air pollution burden associated with internal Migration in Peru. Scientific Reports, 10(1), 7147. doi:10.1038/s41598-020-64043-y
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Chai, J., Hao, Y., Wu, H., & Yang, Y. (2021). Do constraints created by economic growth targets benefit sustainable development? Evidence from China. Business Strategy and the Environment, 30(8), 4188-4205. doi:10.1002/bse.2864
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Chang, Z., Deng, C., Long, F., & Zheng, L. (2021). High-speed rail, firm agglomeration, and PM2.5: Evidence from China. Transportation Research Part D: Transport and Environment, 96, 102886. doi:10.1016/j.trd.2021.102886
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1) - 10.7927/H4ZK5DQS

Chen, F., & Chen, Z. (2020). Air pollution and avoidance behavior: A perspective from the demand for medical insurance. Journal of Cleaner Production, 259, 120970. doi:10.1016/j.jclepro.2020.120970
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Chen, F., Zhang, X., & Chen, Z. (2023). Air pollution and mental health: Evidence from China Health and Nutrition Survey. Journal of Asian Economics, 86, 101611. doi:10.1016/j.asieco.2023.101611
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Chen, J., Wang, B., Huang, S., & Song, M. (2020). The influence of increased population density in China on air pollution. Science of The Total Environment, 735, 139456. doi:10.1016/j.scitotenv.2020.139456
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Chen, M., Guo, S., Hu, M., & Zhang, X. (2020). The spatiotemporal evolution of population exposure to PM2.5 within the Beijing-Tianjin-Hebei urban agglomeration, China. Journal of Cleaner Production, 265, 121708. doi:10.1016/j.jclepro.2020.121708
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Chen, S., Zhang, Y., Zhang, Y., & Liu, Z. (2019). The relationship between industrial restructuring and China's regional haze pollution: A spatial spillover perspective. Journal of Cleaner Production, 239, 115808. doi:10.1016/j.jclepro.2019.02.078
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Chen, S., Zhao, X., & Zhou, L. (2023). Which works better? Comparing the environmental outcomes of different forms of intergovernmental collaboration in China's air pollution control. Journal of Environmental Policy & Planning, 25(1), 16-28. doi:10.1080/1523908X.2021.2000379
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Chen, Y., Dou, S., & Xu, D. (2021). The effectiveness of eco-compensation in environmental protection -A hybrid of the government and market. Journal of Environmental Management, 280, 111840. doi:10.1016/j.jenvman.2020.111840
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1) - 10.7927/H4ZK5DQS

Cheng, Y., Ma, B., & Sun, Y. (2023). Does central ecological transfer payment enhance local environmental performance? Quasi-experimental evidence from China. Ecological Economics, 212, 107920. doi:10.1016/j.ecolecon.2023.107920
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Cheng, Z., Li, L., & Liu, J. (2017). Identifying the spatial effects and driving factors of urban PM2.5 pollution in China. Ecological Indicators, 82, 61-75. doi:10.1016/j.ecolind.2017.06.043
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v1)

Cheng, Z., Li, L., & Liu, J. (2020). The impact of foreign direct investment on urban PM2.5 pollution in China. Journal of Environmental Management, 265, 110532. doi:10.1016/j.jenvman.2020.110532
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Cheval, S., Micu, D., Dumitrescu, A., Irimescu, A., Frighenciu, M., Iojă, C., . . . Antonescu, B. (2020). Meteorological and Ancillary Data Resources for Climate Research in Urban Areas. Climate, 8(3), 37. doi:10.3390/cli8030037
Satellite-Derived Environmental Indicators (Global Urban Heat Island (UHI) Data Set, v1)
Global High Resolution Urban Data from Landsat (Cities from Space)
Global High Resolution Urban Data from Landsat (GMIS)
Global High Resolution Urban Data from Landsat (HBASE)
NASA REMOTE SENSING (MODIS)
REMOTE SENSING (Landsat)

Christensen, P., & Timmins, C. (2018). Sorting or Steering: Experimental Evidence on the Economic Effects of Housing Discrimination. Retrieved from Cambridge, MA: https://doi.org/10.3386/w24826
Superfund Site Footprints (collection)
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v1)

Chuai, X., Lu, Y., Xie, F., Yang, F., Zhao, R., & Pang, B. (2021). A new approach to evaluate regional inequity determined by PM2.5 emissions and concentrations. Journal of Environmental Management, 277, 111335. doi:10.1016/j.jenvman.2020.111335
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Chung, S.-h. (2020). The impact of regional environmental amenity on skill aggregation across regions in developing countries: evidence from air pollution in China. Asia-Pacific Journal of Regional Science, 4, 27-53. doi:10.1007/s41685-019-00125-8
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v1) - 10.7927/H4028PFS

Coffel, E. D., de Sherbinin, A. M., Horton, R. M., Lane, K., Kienberger, S., & Wilhelmi, O. (2018). Chapter 7 - The Science of Adaptation to Extreme Heat. In K. Alverson (Ed.), Resilience (pp. 89-103): Elsevier.
Satellite-Derived Environmental Indicators (Global Urban Heat Island (UHI) Data Set, v1)

Coker, E. S., Cavalli, L., Fabrizi, E., Guastella, G., Lippo, E., Parisi, M. L., . . . Vergalli, S. (2020). The effects of air pollution on COVID-19 related mortality in Northern Italy. Environmental and Resource Economics, 76, 611-634. doi:10.1007/s10640-020-00486-1
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1) - 10.7927/H4ZK5DQS

Creutzig, F., Lohrey, S., Bai, X., Baklanov, A., Dawson, R., Dhakal, S., . . . Walsh, B. (2019). Upscaling urban data science for global climate solutions. Global Sustainability, 2, e2. doi:10.1017/sus.2018.16
Global Rural-Urban Mapping Project (GRUMP) v1.01 (urban extent) - 10.7927/H4Z31WKF
Global Roads (Global Roads Open Access Data Set (gROADS), v1) - 10.7927/H4VD6WCT
Satellite-Derived Environmental Indicators (Global Urban Heat Island (UHI) Data Set, v1)- 10.7927/H4H70CRF
NASA REMOTE SENSING (OCO)

Creutzig, F., Lohrey, S., Bai, X., Dawson, R., Dhakal, S., Lamb, W., . . . Walsh, B. (2018). Upscaling urban data science for global climate solutions. Paper presented at the CitiesIPCC Cities and Climate Change Science Conference, Edmonton. https://citiesipcc.org/wp-content/uploads/2018/03/Upscaling-urban-data-science-for-global-climate-solutions-v28_clean.pdf
Global Rural-Urban Mapping Project (GRUMP) v1.01 (urban extent) - 10.7927/H4Z31WKF
Global Roads (Global Roads Open Access Data Set (gROADS), v1) - 10.7927/H4VD6WCT
Satellite-Derived Environmental Indicators (Global Urban Heat Island (UHI) Data Set, v1)- 10.7927/H4H70CRF
NASA REMOTE SENSING (OCO)

Cuesta, J., Cai, L., Madrigal, L., & Pecorari, N. (2023). Exposure to climatic risks and social sustainability in Vietnam. Sustainability, 15(4), 3260. doi:10.3390/su15043260
Natural Disaster Hotspots (earthquake hazard frequency and distribution)
Satellite-Derived Environmental Indicators (Global (GL) Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v4.03)

Dance, S., Kommenda, N., & Ducroquet, S. (2022). The surprising reasons parts of Earth are warming more slowly.  Retrieved from https://www.washingtonpost.com/climate-environment/interactive/2022/global-cool-spots-least-warming/
Satellite-Derived Environmental Indicators (Global (GL) Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v4.03)

Dasadhikari, K., Eastham, S. D., Allroggen, F., Speth, R. L., & Barrett, S. R. H. (2019). Evolution of sectoral emissions and contributions to mortality from particulate matter exposure in the Asia-Pacific region between 2010 and 2015. Atmospheric Environment, 216, 116916. doi:10.1016/j.atmosenv.2019.116916
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1) - 10.7927/H4ZK5DQS

de Manuel, B. F., Méndez-Fernández, L., Peña, L., & Ametzaga-Arregi, I. (2021). A new indicator of the effectiveness of urban green infrastructure based on ecosystem services assessment. Basic and Applied Ecology, 53, 12-25. doi:10.1016/j.baae.2021.02.012
Satellite-Derived Environmental Indicators (Global Summer Land Surface Temperature (LST) Grids, v1)

De Pauw, K., Depauw, L., Calders, K., Caluwaerts, S., Cousins, S. A. O., De Lombaerde, E., . . . De Frenne, P. (2023). Urban forest microclimates across temperate Europe are shaped by deep edge effects and forest structure. Agricultural and Forest Meteorology, 341, 109632. doi:10.1016/j.agrformet.2023.109632
Satellite-Derived Environmental Indicators (Global Urban Heat Island (UHI) Data Set, v1)

de Sherbinin, A. M. (2015, 26-31 July 2015). Integration of remote sensing and population data: Lessons from the NASA Socioeconomic data and applications center. Paper presented at the 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).
Gridded Population of the World (GPW) v3 (collection)
Global Rural-Urban Mapping Project (GRUMP) v1 (collection)
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Deng, Z., Qin, M., & Song, S. (2020). Re-study on Chinese city size and policy formation. China Economic Review, 60, 101390. doi:10.1016/j.chieco.2019.101390
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v1)

Dilawar, A., Chen, B., Ul-Haq, Z., Amir, M., Arshad, A., Hassan, M., . . . Zhang, H. (2023). Investigating the potential climatic effects of atmospheric pollution across China under the National Clean Air Action Plan. Remote Sensing, 15(8), 2084. doi:10.3390/rs15082084
Satellite-Derived Environmental Indicators (Global (GL) Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v4.03)
NASA REMOTE SENSING (OMI)

Ding, F., Fu, J., Jiang, D., Hao, M., & Lin, G. (2018). Mapping the spatial distribution of Aedes aegypti and Aedes albopictus. Acta Tropica, 178, 155-162. doi:10.1016/j.actatropica.2017.11.020
Gridded Population of the World (GPW) v4 (population density UN WPP-adjusted)
Satellite-Derived Environmental Indicators (Global Summer Land Surface Temperature (LST) Grids, v1)
REMOTE SENSING (DMSP-OLS)

Ding, Y., Zhang, M., Chen, S., Wang, W., & Nie, R. (2019). The environmental Kuznets curve for PM2.5 pollution in Beijing-Tianjin-Hebei region of China: A spatial panel data approach. Journal of Cleaner Production, 220, 984-994. doi:10.1016/j.jclepro.2019.02.229
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Ding, Y., Zhang, M., Qian, X., Li, C., Chen, S., & Wang, W. (2019). Using the geographical detector technique to explore the impact of socioeconomic factors on PM2.5 concentrations in China. Journal of Cleaner Production, 211, 1480-1490. doi:10.1016/j.jclepro.2018.11.159
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Dong, F., Yu, B., Pan, Y., & Hua, Y. (2020). What contributes to the regional inequality of haze pollution in China? Evidence from quantile regression and Shapley value decomposition. Environmental Science and Pollution Research, 27, 17093-17108. doi:10.1007/s11356-020-07929-8
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1) - 10.7927/H4ZK5DQS

Dong, F., Zhang, S., Li, Y., Li, J., Xie, S., & Zhang, J. (2020). Examining environmental regulation efficiency of haze control and driving mechanism: evidence from China. Environmental Science and Pollution Research, 27, 29171-29190. doi:10.1007/s11356-020-09100-9
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Dong, Z., Xia, C., Fang, K., & Zhang, W. (2022). Effect of the carbon emissions trading policy on the co-benefits of carbon emissions reduction and air pollution control. Energy Policy, 165, 112998. doi:10.1016/j.enpol.2022.112998
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1) - 10.7927/H4ZK5DQS

Duncan, B. N., Malings, C. A., Knowland, K. E., Anderson, D. C., Prados, A. I., Keller, C. A., . . . Ensz, H. (2021). Augmenting the standard operating procedures of health and air quality stakeholders with NASA resources. GeoHealth, 5(9), e2021GH000451. doi:10.1029/2021GH000451
Satellite-Derived Environmental Indicators (collection)

Faisal, A.-A., Kafy, A. A., Abdul Fattah, M., Amir Jahir, D. M., Al Rakib, A., Rahaman, Z. A., . . . Huang, X. (2022). Assessment of temporal shifting of PM2.5, lockdown effect, and influences of seasonal meteorological factors over the fastest-growing megacity, Dhaka. Spatial Information Research, 30, 441-453. doi:10.1007/s41324-022-00441-w
Gridded Population of the World (GPW) v3 (population count) - 10.​7927/​H4639MPP
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v1) - 10.7927/H4028PFS

Faisal, A.-A., Rahman, M. M., & Haque, S. (2022). Retrieving spatial variation of aerosol level over urban mixed land surfaces using Landsat imageries: Degree of air pollution in Dhaka Metropolitan Area. Physics and Chemistry of the Earth, Parts A/B/C, 126, 103074. doi:10.1016/j.pce.2021.103074
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)
REMOTE SENSING (Landsat)

Fan, B., Wang, T., Wang, W., Zhang, S., Gong, M., Li, W., . . . Guo, L. (2019). Long-term exposure to ambient fine particulate pollution, sleep disturbance and their interaction effects on suicide attempts among Chinese adolescents. Journal of Affective Disorders, 258, 89-95. doi:10.1016/j.jad.2019.08.004
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Fan, Q., Goetz, S. J., & Liang, J. (2016). The interactive effects of human capital and quality of life on economic growth. Applied Economics, 48(53), 5186-5200. doi:10.1080/00036846.2016.1173180
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Fan, Q., Klaiber, H. A., & Fisher-Vanden, K. (2016). Does extreme weather drive interregional brain drain in the U.S.? Evidence from a sorting model. Land Economics, 92(2), 363-388. doi:10.3368/le.92.2.363
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Fang, J. (2021). Impacts of high-speed rail on urban smog pollution in China: A spatial difference-in-difference approach. Science of The Total Environment, 777, 146153. doi:10.1016/j.scitotenv.2021.146153
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Feldman, L., Gao, C., Zhu, J., Simatovic, J., & To, T. (2014). Impact of air pollution on physician office visits for common childhood conditions in Ontario, Canada. Allergy, Asthma & Clinical Immunology, 10(Suppl 2), A54. doi:10.1186/1710-1492-10-S2-A54
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Feng, T., Du, H., Lin, Z., & Zuo, J. (2020). Spatial spillover effects of environmental regulations on air pollution: Evidence from urban agglomerations in China. Journal of Environmental Management, 272, 110998. doi:10.1016/j.jenvman.2020.110998
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Feng, Y., Cheng, J., Shen, J., & Sun, H. (2019). Spatial effects of air pollution on public health in China. Environmental and Resource Economics, 73(1), 229-250. doi:10.1007/s10640-018-0258-4
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Feng, Y., Jones, M. R., Ahn, J. B., Garonzik-Wang, J. M., Segev, D. L., & McAdams-DeMarco, M. (2021). Ambient air pollution and posttransplant outcomes among kidney transplant recipients. American Journal of Transplantation, 21(10), 3333-3345. doi:10.1111/ajt.16605
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Feng, Y., Jones, M. R., Chu, N. M., Segev, D. L., & McAdams-DeMarco, M. (2021). Ambient air pollution and mortality among older patients initiating maintenance dialysis. American Journal of Nephrology, 52, 217-227. doi:10.1159/000514233
Gridded Population of the World (GPW) v4.11 (population count) - 10.7927/H4JW8BX5
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1) - 10.7927/H4ZK5DQS

Feng, Y., & Wang, X. (2020). Effects of urban sprawl on haze pollution in China based on dynamic spatial Durbin model during 2003-2016. Journal of Cleaner Production, 242, 118368. doi:10.1016/j.jclepro.2019.118368
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Fletcher, D. H., Likongwe, P. J., Chiotha, S., Nduwayezu, G., Mallick, D., Uddin Md, N., . . . Jones, L. (2021). Using demand mapping to assess the benefits of urban green and blue space in cities from four continents. Science of The Total Environment, 785, 147238. doi:10.1016/j.scitotenv.2021.147238
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1) - 10.7927/H4ZK5DQS
REMOTE SENSING (Landsat)

Florczyk, A. J., Melchiorri, M., Corbane, C., Schiavina, M., Maffenini, M., Pesaresi, M., . . . Zanchetta, L. (2019). Description of the GHS Urban Centre Database 2015,  Public Release 2019, Version 1.0. Retrieved from https://doi.org/10.2760/037310
Global Rural-Urban Mapping Project (GRUMP) v1 (settlement points) - 10.7927/H4M906KR
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1) - 10.7927/H4ZK5DQS
REMOTE SENSING (ALOS Global Digital Surface Model - ALOS World 3D - 30m (AW3D30))
REMOTE SENSING (Landsat)

Fu, J., Jiang, D., Lin, G., Liu, K., & Wang, Q. (2015). An ecological analysis of PM2.5 concentrations and lung cancer mortality rates in China. BMJ Open, 5(11), e009452. doi:10.1136/bmjopen-2015-009452
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1) - 10.7927/H4H41PB4

Gan, T., Liang, W., Yang, H., & Liao, X. (2020). The effect of Economic Development on haze pollution (PM2.5) based on a spatial perspective: Urbanization as a mediating variable. Journal of Cleaner Production, 266, 121880. doi:10.1016/j.jclepro.2020.121880
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Gao, H., He, J., & Li, Y. (2022). Media spotlight, corporate sustainability and the cost of debt. Applied Economics, 54(34), 3989-4005. doi:10.1080/00036846.2021.2020710
Satellite-Derived Environmental Indicators (unspecified PM.25 data set)

Ghanbari, S., & Mansouri Daneshvar, M. R. (2021). Urban and rural contribution to the GHG emissions in the MECA countries. Environment, Development and Sustainability, 23, 6418-6452. doi:10.1007/s10668-020-00879-8
Satellite-Derived Environmental Indicators (Global Urban Heat Island (UHI) Data Set, v1)
NASA REMOTE SENSING (GIOVANNI)

Gong, C., Zhang, J., & Liu, H. (2021). Do industrial pollution activities in China respond to ecological fiscal transfers? Evidence from payments to national key ecological function zones. Journal of Environmental Planning and Management, 64(7), 1184-1203. doi:10.1080/09640568.2020.1813695
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1) - 10.7927/H4ZK5DQS

Gong, Y., Li, S., Sanders, N. J., & Shi, G. (2023). The mortality impact of fine particulate matter in China: Evidence from trade shocks. Journal of Environmental Economics and Management, 117, 102759. doi:10.1016/j.jeem.2022.102759
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v1)

Guo, H., Chang, Z., Wu, J., & Li, W. (2019). Air pollution and lung cancer incidence in China: Who are faced with a greater effect? Environment International, 132, 105077. doi:10.1016/j.envint.2019.105077
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1) - 10.7927/H4ZK5DQS

Guo, H., Li, W., & Wu, J. (2020). Ambient PM2.5 and annual lung cancer incidence: A nationwide study in 295 Chinese counties. International Journal of Environmental Research and Public Health, 17(5), 1481. doi:10.3390/ijerph17051481
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Guo, L., Cheng, Z., Tani, M., & Cook, S. (2023). ZA DP No. 16320: Environmental Policy and Gender Health Gap Retrieved from https://www.iza.org/publications/dp/16320/environmental-policy-and-gender-health-gap
Satellite-Derived Environmental Indicators (Global (GL) Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v4.03) - 10.7927/fx80-4n39
NASA REMOTE SENSING (MODIS)

Guo, Q., Wei, Y., & Wan, R. (2023). Leading officials’ accountability audit of natural resources and haze pollution: evidence from China. Environmental Science and Pollution Research, 30, 17612-17628. doi:10.1007/s11356-022-23340-x
Satellite-Derived Environmental Indicators (Global (GL) Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v4.03)

Guo, S., Tao, X., & Liang, L. (2023). Exploring natural and anthropogenic drivers of PM2.5 concentrations based on random forest model: Beijing-Tianjin-Hebei urban agglomeration, China. Atmosphere, 14(2), 381. doi:10.3390/atmos14020381
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Guo, Y., Zeng, H., Zheng, R., Li, S., Pereira, G., Liu, Q., . . . Huxley, R. (2017). The burden of lung cancer mortality attributable to fine particles in China. Science of The Total Environment, 579, 1460-1466. doi:10.1016/j.scitotenv.2016.11.147
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Han, B., Jin, X., Sun, R., Li, H., Liang, X., & Zhou, Y. (2023). Understanding land-use sustainability with a systematical framework: An evaluation case of China. Land Use Policy, 132, 106767. doi:10.1016/j.landusepol.2023.106767
Global Roads (Global Roads Open Access Data Set (gROADS), v1)
Satellite-Derived Environmental Indicators (Global (GL) Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v4.03)
NASA REMOTE SENSING (MODIS - MOD17A3)
REMOTE SENSING (DMSP-OLS)

Han, L., & Jia, J. (2022). Alcohol consumption, poor lifestyle choices, and air pollution worsen cognitive function in seniors: a cohort study in China. Environmental Science and Pollution Research, 29(18), 26877-26888. doi:10.1007/s11356-021-17891-8
Satellite-Derived Environmental Indicators (Annual PM2.5 Concentrations for Countries and Urban Areas, v1)

Han, L., Zhou, W., Li, W., & Qian, Y. (2017). Global population exposed to fine particulate pollution by population increase and pollution expansion. Air Quality, Atmosphere & Health, 10(10), 1221-1226. doi:10.1007/s11869-017-0506-8
Gridded Population of the World (GPW) v3 (population density) - 10.7927/H4XK8CG2
Gridded Population of the World (GPW) v3 (population count future estimates) - 10.7927/H42B8VZZ
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v1) - 10.7927/H4028PFS

Han, S., Miao, C., & Zhang, B. (2023). Impact of density on the COVID-19 pandemic: Evidence from Chinese cities. Cities, 142, 104534. doi:10.1016/j.cities.2023.104534
Satellite-Derived Environmental Indicators (Global (GL) Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v4.03)

Han, S., & Sun, B. (2019). Impact of population density on PM2.5 concentrations: A case study in Shanghai, China. Sustainability, 11(7), 1968. doi:10.3390/su11071968
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Han, W., Tong, L., & Wen, J. (2020). Long-term spatiotemporal trend analysis (1998–2016) of PM2.5 in China using satellite product. Paper presented at the IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium.
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Hao, Y., Gai, Z., Yan, G., Wu, H., & Irfan, M. (2021). The spatial spillover effect and nonlinear relationship analysis between environmental decentralization, government corruption and air pollution: Evidence from China. Science of The Total Environment, 763, 144183. doi:10.1016/j.scitotenv.2020.144183
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Hasan, I., Noth, F., & Tonzer, L. (2020). Cultural Norms and Corporate Fraud: Evidence from the Volkswagen Scandal. Retrieved from Halle (Saale), Germany: http://hdl.handle.net/10419/226484
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Hassan, M. S., Bhuiyan, M. A. H., & Rahman, M. T. (2023). Sources, pattern, and possible health impacts of PM2.5 in the central region of Bangladesh using PMF, SOM, and machine learning techniques. Case Studies in Chemical and Environmental Engineering, 8, 100366. Retrieved from https://doi.org/10.1016/j.cscee.2023.100366
Satellite-Derived Environmental Indicators (unspecified PM.25 data set)

He, L., Zhang, X., & Yan, Y. (2021). Heterogeneity of the Environmental Kuznets Curve across Chinese cities: How to dance with ‘shackles’? Ecological Indicators, 130, 108128. doi:10.1016/j.ecolind.2021.108128
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v1)

He, Q., Rao, Y., Dai, J., Dai, D., & Ou, G. (2022). Effect of urban structure on PM2.5 in China: A multiscale landscape analysis of 362 cities. Journal of Urban Planning and Development, 148(2), 05022010. doi:10.1061/(ASCE)UP.1943-5444.0000831
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)
NASA REMOTE SENSING (MODIS - MOD11A1)

He, Y., Lin, K., Liao, N., Chen, Z., & Rao, J. (2022). Exploring the spatial effects and influencing factors of PM2.5 concentration in the Yangtze River Delta Urban Agglomerations of China. Atmospheric Environment, 268, 118805. doi:10.1016/j.atmosenv.2021.118805
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Hu, J., Chen, J., Ying, Q., & Zhang, H. (2016). One-year simulation of ozone and particulate matter in China using WRF/CMAQ modeling system. Atmospheric Chemistry and Physics, 16, 10333-10350. doi:10.5194/acp-2016-148
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Hu, Z. (2018). City-level adult stroke prevalence in relation to remote sensing derived PM2.5 adjusting for  unhealthy behaviors and medical risk factors. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-3, 579-582. doi:10.5194/isprs-archives-XLII-3-579-2018
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v1) - 10.7927/H4028PFS

Hu, Z., & Baker, E. (2017). Geographical analysis of lung cancer mortality rate and PM2.5 using Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth. Journal of Geoscience and Environment Protection, 5(6), 183-197. doi:10.4236/gep.2017.56017
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Hu, Z., Zhang, Y., Cao, J., & Zhou, K. (2022). Longing for the Blue Sky: Urban air quality and the individual decision to immigrate. Journal of Asian Economics, 79, 101437. doi:10.1016/j.asieco.2021.101437
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Huang, B., Liu, Y., Feng, Z., Pearce, J. R., Wang, R., Zhang, Y., & Chen, J. (2019). Residential exposure to natural outdoor environments and general health among older adults in Shanghai, China. International Journal for Equity in Health, 18(1), 178. doi:10.1186/s12939-019-1081-4
Satellite-Derived Environmental Indicators (Global 3-Year Running Mean Ground-Level NO2 Grids from GOME, SCIAMACHY and GOME-2, v1)
REMOTE SENSING (Landsat)
REMOTE SENSING (HJ-1)

Huang, D., Tian, M., & Yuan, L. (2023). Do objective and subjective traffic-related pollution, physical activity and nature exposure affect mental wellbeing? Evidence from Shenzhen, China. Science of The Total Environment, 869, 161819. doi:10.1016/j.scitotenv.2023.161819
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Huang, Q., Xu, C., Jiang, W., Yue, W., Rong, Q., Gu, Z., & Su, M. (2021). Urban compactness and patch complexity influence PM2.5 concentrations in contrasting ways: Evidence from the Guangdong-Hong Kong-Macao Greater Bay Area of China. Ecological Indicators, 133, 108407. doi:10.1016/j.ecolind.2021.108407
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Huang, Q., Zhang, Y. Y., Chen, Q., & Ning, M. (2021). Does air pollution decrease labor supply of the rural middle-aged and elderly? Sustainability, 13(5), 2906. doi:10.3390/su13052906
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Huang, S., Ding, Y., & Failler, P. (2022). Does the government's environmental attention affect ambient pollution? Empirical research on Chinese cities. Sustainability, 14(6), 3242. doi:10.3390/su14063242
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Huang, Y., & Zhu, S. (2020). Regional industrial dynamics under the environmental pressures in China. Journal of Cleaner Production, 265, 121917. doi:10.1016/j.jclepro.2020.121917
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Jain, M. (2022). Increasing Atmospheric Extreme Events and Role of Disaster Risk Management: Dimensions and Approaches. In P. Saxena, A. Shukla, & A. K. Gupta (Eds.), Extremes in Atmospheric Processes and Phenomenon: Assessment, Impacts and Mitigation (pp. 303-328). Singapore: Springer Nature Singapore.
Gridded Population of the World (GPW) v4.11 (population density) - 10.7927/H49C6VHW
Satellite-Derived Environmental Indicators (Global Fire Emissions Indicators, Grids, v1) - 10.7927/H400002V
NASA REMOTE SENSING (MODIS)
NASA REMOTE SENSING (TRMM)

Ji, X., Yao, Y., & Long, X. (2018). What causes PM2.5 pollution? Cross-economy empirical analysis from socioeconomic perspective. Energy Policy, 119, 458-472. doi:10.1016/j.enpol.2018.04.040
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Jia, A., Liang, S., Wang, D., Jiang, B., & Zhang, X. (2020). Air pollution slows down surface warming over the Tibetan Plateau. Atmospheric Chemistry and Physics, 20, 881-899. doi:10.5194/acp-20-881-2020
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v1) - 10.7927/H4028PFS
NASA REMOTE SENSING (ASTER GDEM)
NASA REMOTE SENSING (CERES EBAF)
NASA REMOTE SENSING (MODIS - MOD/MYD08)
NASA REMOTE SENSING (OMI)
NASA REMOTE SENSING (SeaWiFS)
NASA REMOTE SENSING (TOMS)

Jiang, D., Hao, M., Ding, F., Fu, J., & Li, M. (2018). Mapping the transmission risk of Zika virus using machine learning models. Acta Tropica, 185, 391-399. doi:10.1016/j.actatropica.2018.06.021
Satellite-Derived Environmental Indicators (Global Urban Heat Island (UHI) Data Set, v1)
NASA REMOTE SENSING (Surface meteorology and Solar Energy (SSE))
REMOTE SENSING (AVHRR GIMMS NDVI)
REMOTE SENSING (DMSP-OLS)

Jiang, D., Li, W., Shen, Y., & Zhang, Y. (2022). Does air quality affect firms’ investment efficiency? Evidence from China. International Review of Economics & Finance, 79, 1-17. doi:10.1016/j.iref.2022.01.001
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Jiang, Y., Wang, X., Li, M., Liang, Y., Liu, Z., Chen, J., . . . Wang, W. (2024). Comprehensive understanding on sources of high levels of fine particulate nitro-aromatic compounds at a coastal rural area in northern China. Journal of Environmental Sciences, 135, 483-494. doi:10.1016/j.jes.2022.09.033
Satellite-Derived Environmental Indicators (Global (GL) Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v4.03)

Jin, P., Wang, S., Yin, D., & Zhang, H. (2023). Environmental institutional supply that shapes a green economy: Evidence from Chinese cities. Technological Forecasting and Social Change, 187, 122214. doi:10.1016/j.techfore.2022.122214
Satellite-Derived Environmental Indicators (Global (GL) Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v4.03)

Jones, B. (2020). Modeling Climate Change-Induced Migration in Central America & Mexico Methodological Report. Retrieved from New York: https://assets-c3.propublica.org/Climate-Migration-Modeling-Methodology.pdf
Digital Elevation Data Collection (DEDC) (Altimeter Corrected Elevations (ACE2), v2)
Gridded Population of the World (GPW) v4 (population count) - 10.7927/H4X63JVC
Gridded Population of the World (GPW) v4.10 (basic demographic characteristics) - 10.7927/H45H7D7F
Satellite-Derived Environmental Indicators (Trends in Global Freshwater Availability from the Gravity Recovery and Climate Experiment (GRACE), v1)

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Keles, D., Pfaff, A., & Mascia, M. (2023). Does the selective erasure of protected areas raise deforestation in the Brazilian Amazon? Journal of the Association of Environmental and Resource Economists, 10(4), 1121-1147. doi:10.1086/723543
Gridded Population of the World (GPW) v4 (admin unit center points with population estimates)
Global Roads (Global Roads Open Access Data Set (gROADS), v1)
Satellite-Derived Environmental Indicators (Global Fire Emissions Indicators, Grids, v1)
NASA REMOTE SENSING (SRTM)
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Li, B., Gui, T., Chen, G., & Cheng, S. (2023). The effect of environmental regulation on population migration: Evidence from China's new ambient air quality standards. Journal of Cleaner Production, 415, 137786. doi:10.1016/j.jclepro.2023.137786
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Li, G., Li, L., Liu, D., Qin, J., & Zhu, H. (2021). Effect of PM2.5 pollution on perinatal mortality in China. Scientific Reports, 11(1), 7596. doi:10.1038/s41598-021-87218-7
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Li, H., Shahbaz, M., Jiang, H., & Dong, K. (2021). Is natural gas consumption mitigating air pollution? Fresh evidence from national and regional analysis in China. Sustainable Production and Consumption, 27, 325-336. doi:10.1016/j.spc.2020.11.010
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Li, H., Zhang, M., Li, C., & Li, M. (2019). Study on the spatial correlation structure and synergistic governance development of the haze emission in China. Environmental Science and Pollution Research, 26(12), 12136-12149. doi:10.1007/s11356-019-04682-5
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Li, L., Feng, X. D., & Chen, T. (2019). Satellite-derived air pollutants and their correlations with urban form in Guangdong, China. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-3/W9, 109-112. doi:10.5194/isprs-archives-XLII-3-W9-109-2019
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Li, M., Zhang, M., Du, C., & Chen, Y. (2020). Study on the spatial spillover effects of cement production on air pollution in China. Science of The Total Environment, 748, 141421. doi:10.1016/j.scitotenv.2020.141421
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Li, Q., Zheng, D., Wang, Y., Li, R., Wu, H., Xu, S., . . . Qiao, J. (2021). Association between exposure to airborne particulate matter less than 2.5 μm and human fecundity in China. Environment International, 146, 106231. doi:10.1016/j.envint.2020.106231
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Li, W., Ali, E., Abou El-Magd, I., Mourad, M. M., & El-Askary, H. (2019). Studying the impact on urban health over the Greater Delta Region in Egypt due to aerosol variability using optical characteristics from satellite observations and ground-based AERONET measurements. Remote Sensing, 11(17), 1998. doi:10.3390/rs11171998
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NASA REMOTE SENSING (CALIPSO)
NASA REMOTE SENSING (MISR)
NASA REMOTE SENSING (MODIS)
NASA REMOTE SENSING (OMI)
REMOTE SENSING (POLDER)

Li, W., Sun, B., Zhang, T., & Zhang, Z. (2022). Panacea, placebo or pathogen? An evaluation of the integrated performance of polycentric urban structures in the Chinese prefectural city-regions. Cities, 125, 103624. doi:10.1016/j.cities.2022.103624
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Li, X., Li, S., Tian, S., Guan, Y., & Liu, H. (2021). Air quality and the spatial-temporal differentiation of mechanisms underlying Chinese urban human settlements. Land, 10(11), 1207. doi:10.3390/land10111207
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)
REMOTE SENSING (DMSP-OLS)

Li, X., & Nam, K.-M. (2022). Environmental regulations as industrial policy: Vehicle emission standards and automotive industry performance. Environmental Science & Policy, 131, 68-83. doi:10.1016/j.envsci.2022.01.015
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Li, X., Xu, Y., & Yao, X. (2021). Effects of industrial agglomeration on haze pollution: A Chinese city-level study. Energy Policy, 148, 111928. doi:10.1016/j.enpol.2020.111928
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Li, X.-X., Ren, Z.-P., Wang, L.-X., Zhang, H., Jiang, S.-W., Chen, J.-X., . . . Zhou, X.-N. (2016). Co-endemicity of pulmonary tuberculosis and intestinal helminth infection in the People’s Republic of China. PLoS Neglected Tropical Diseases, 10(4), e0004580. doi:10.1371/journal.pntd.0004580
Global Rural-Urban Mapping Project (GRUMP) v1 (urban extent)
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Li, Z., & Lin, B. (2022). Analyzing the impact of environmental regulation on labor demand: A quasi-experiment from Clean Air Action in China. Environmental Impact Assessment Review, 93, 106721. doi:10.1016/j.eiar.2021.106721
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Liang, C., & Wang, Q. (2023). The relationship between total factor productivity and environmental quality: A sustainable future with innovation input. Technological Forecasting and Social Change, 191, 122521. doi:10.1016/j.techfore.2023.122521
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Liang, L. (2021). Calibrating low-cost sensors for ambient air monitoring: Techniques, trends, and challenges. Environmental Research, 197, 111163. doi:10.1016/j.envres.2021.111163
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Liang, Z., Huang, J., Wang, Y., Wei, F., Wu, S., Jiang, H., . . . Li, S. (2021). The mediating effect of air pollution in the impacts of urban form on nighttime urban heat island intensity. Sustainable Cities and Society, 74, 102985. doi:10.1016/j.scs.2021.102985
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Liang, Z., Wang, W., Wang, Y., Ma, L., Liang, C., Li, P., . . . Zhang, L. (2021). Urbanization, ambient air pollution, and prevalence of chronic kidney disease: A nationwide cross-sectional study. Environment International, 156, 106752. doi:10.1016/j.envint.2021.106752
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Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Liang, Z., Wang, W., Yang, C., Wang, Y., Shen, J., Li, P., . . . Zhang, L. (2022). Residential greenness and prevalence of chronic kidney disease: Findings from the China National Survey of Chronic Kidney Disease. Science of The Total Environment, 806, 150628. doi:10.1016/j.scitotenv.2021.150628
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Lin, B., & Zhu, J. (2020). Policy effect of the Clean Air Action on green development in Chinese cities. Journal of Environmental Management, 258, 110036. doi:10.1016/j.jenvman.2019.110036
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Lin, G., Fu, J., Jiang, D., Hu, W., Dong, D., Huang, Y., & Zhao, M. (2013). Spatio-temporal variation of PM2.5 concentrations and their relationship with geographic and socioeconomic factors in China. International Journal of Environmental Research and Public Health, 11(1), 173-186. doi:10.3390/ijerph110100173
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NASA REMOTE SENSING (MISR)
NASA REMOTE SENSING (MODIS)

Lin, H., Guo, Y., Di, Q., Zheng, Y., Xian, H., Li, X., . . . Wu, F. (2018). Consumption of fruit and vegetables might mitigate the adverse effects of ambient PM2.5 on lung function among adults. Environmental Research, 160(Supplement C), 77-82. doi:10.1016/j.envres.2017.09.007
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Lin, L., Di, L., Yang, R., Zhang, C., Yu, E., Rahman, M. S., . . . Tang, J. (2018, 6-9 Aug. 2018). Using machine learning approach to evaluate the PM2.5 concentrations in China from 1998 to 2016. Paper presented at the 7th International Conference on Agro-geoinformatics.
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Lin, Y., Yang, X., Li, Y., & Yao, S. (2020). The effect of forest on PM2.5 concentrations: A spatial panel approach. Forest Policy and Economics, 118, 102261. doi:10.1016/j.forpol.2020.102261
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REMOTE SENSING (DMSP-OLS)

Liu, B., Wu, J., & Chan, K. C. (2021). Does air pollution change a firm's business strategy for employing capital and labor? Business Strategy and the Environment, 30(8), 3671-3685. doi:10.1002/bse.2833
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Liu, C., Shen, X., Gao, W., Liu, P., & Sun, Z. (2014). Evaluation of CALIPSO aerosol optical depth using AERONET and MODIS data over China.
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Liu, F., Zheng, M., & Wang, M. (2020). Does air pollution aggravate income inequality in China? An empirical analysis based on the view of health. Journal of Cleaner Production, 271, 122469. doi:10.1016/j.jclepro.2020.122469
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Liu, G., Dong, X., Kong, Z., & Dong, K. (2021). Does national air quality monitoring reduce local air pollution? The case of PM2.5 for China. Journal of Environmental Management, 296, 113232. doi:10.1016/j.jenvman.2021.113232
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Liu, G., Dong, X., Li, J., Jiang, Q., & Kong, Z. (2021). Does the pollutant charging system effectively reduce PM2.5 concentration? Evidence from 255 cities in China. IOP Conference Series: Earth and Environmental Science, 647, 012182. doi:10.1088/1755-1315/647/1/012182
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Liu, H., Gu, J., Huang, Z., Han, Z., Xin, J., Yuan, L., . . . Zhang, Z. (2022). Fine particulate matter induces METTL3-mediated m6A modification of BIRC5 mRNA in bladder cancer. Journal of Hazardous Materials, 437, 129310. doi:10.1016/j.jhazmat.2022.129310
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Liu, J., Pan, H., & Zheng, S. (2019). Tourism development, environment and policies: Differences between domestic and international tourists. Sustainability, 11(5), 1390. doi:10.3390/su11051390
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Liu, J.-Y., Woodward, R. T., & Zhang, Y.-J. (2021). Has carbon emissions trading reduced PM2.5 in China? Environmental Science & Technology, 55(10), 6631-6643. doi:10.1021/acs.est.1c00248
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Liu, L., Ding, D., & He, J. (2019). Fiscal decentralization, economic growth, and haze pollution decoupling effects: A simple model and evidence from China. Computational Economics, 54(4), 1423-1441. doi:10.1007/s10614-017-9700-x
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Liu, N., Sun, J., & Wang, Y. (2022). The influence of urban spatial structure on urban heat island effect is analyzed by means of Geographic Information System (GIS). Paper presented at the Advances in Urban Engineering and Management Science Volume 2: Proceedings of the 3rd International Conference on Urban Engineering and Management Science (ICUEMS 2022), Wuhan, China.
Satellite-Derived Environmental Indicators (Global Urban Heat Island (UHI) Data Set, v1)

Liu, S., Hou, P., Gao, Y., & Tan, Y. (2022). Innovation and green total factor productivity in China: a linear and nonlinear investigation. Environmental Science and Pollution Research, 29, 12810-12831. doi:10.1007/s11356-020-11436-1
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Liu, S., Xing, J., Wang, S., Ding, D., Chen, L., & Hao, J. (2020). Revealing the impacts of transboundary pollution on PM2.5-related deaths in China. Environment International, 134, 105323. doi:10.1016/j.envint.2019.105323
Gridded Population of the World (GPW) v4.10 (population count) - 10.7927/H4PG1PPM
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Long, F., Zheng, L., & Qian, H. (2023). Entrepreneurship in China’s peripheral regions. The Annals of Regional Science, 70, 287-313. doi:10.1007/s00168-022-01122-0
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Lövei, G. L., & Magura, T. (2022). Body size and the urban heat island effect modulate the temperature–size relationship in ground beetles. Journal of Biogeography, 49(9), 1618-1628. doi:10.1111/jbi.14458
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Lu, J., Chen, F., & Cai, S. (2023). Air pollution monitoring and avoidance behavior: Evidence from the health insurance market. Journal of Cleaner Production, 414, 137780. doi:10.1016/j.jclepro.2023.137780
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Lu, J., Li, B., Li, H., & Al-Barakani, A. (2021). Expansion of city scale, traffic modes, traffic congestion, and air pollution. Cities, 108, 102974. doi:10.1016/j.cities.2020.102974
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Luan, W., & Li, X. (2021). Rapid urbanization and its driving mechanism in the Pan-Third Pole region. Science of The Total Environment, 750, 141270. doi:10.1016/j.scitotenv.2020.141270
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NASA REMOTE SENSING (MODIS)

Luo, C., Ouyang, Y., Shi, S., Li, G., Zhao, Z., Luo, H., . . . Xie, J. (2022). Particulate matter of air pollution may increase risk of kidney failure in IgA nephropathy. Kidney International, 102(6), 1382-1391. doi:10.1016/j.kint.2022.08.020
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Luo, E., Kuffer, M., & Wang, J. (2022). Urban poverty maps - From characterising deprivation using geo-spatial data to capturing deprivation from space. Sustainable Cities and Society, 84, 104033. doi:10.1016/j.scs.2022.104033
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REMOTE SENSING (SPOT 7)

Luo, J., & Che, M. (2023). Spatio-temporal change pattern investigation of PM2.5 in Jiangsu Province with MODIS time series products. Atmosphere, 14(6), 943. doi:10.3390/atmos14060943
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NASA REMOTE SENSING (MODIS)

Luo, J., Du, P., Samat, A., Xia, J., Che, M., & Xue, Z. (2017). Spatiotemporal pattern of PM2.5 concentrations in mainland China and analysis of its influencing factors using geographically weighted regression. Scientific Reports, 7, 40607. doi:10.1038/srep40607
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Ma, D., He, F., Li, G., & Chen, L. (2018). Estimation and comparative analysis of environmental efficiency in China, with and without consideration of haze. Polish Journal of Environmental Studies, 27(1), 201-211. doi:10.15244/pjoes/74900
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Ma, Z., Hu, X., Huang, L., Bi, J., & Liu, Y. (2014). Estimating ground-level PM2.5 in China using satellite remote sensing. Environmental Science & Technology, 48(13), 7436-7444. doi:10.1021/es5009399
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NASA REMOTE SENSING (MODIS)
NASA REMOTE SENSING (MISR)

Machado-Silva, F., Libonati, R., Melo de Lima, T. F., Bittencourt Peixoto, R., de Almeida França, J. R., de Avelar Figueiredo Mafra Magalhães, M., . . . DaCamara, C. C. (2020). Drought and fires influence the respiratory diseases hospitalizations in the Amazon. Ecological Indicators, 109, 105817. doi:10.1016/j.ecolind.2019.105817
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

MacManus, K., Balk, D., Engin, H., McGranahan, G., & Inman, R. (2021). Estimating population and urban areas at risk of coastal hazards, 1990–2015: How data choices matter. Earth System Science Data, 13(12), 5747-5801. doi:10.5194/essd-13-5747-2021
Gridded Population of the World (GPW) v4.11 (national identifier grid) - 10.7927/H4TD9VDP
Global Rural-Urban Mapping Project (GRUMP) v1.02 (urban extent polygons) - 10.7927/np6p-qe61
Low Elevation Coastal Zone (LECZ) (Urban-Rural Population Estimates, v1) - 10.7927/H4TM782G
Low Elevation Coastal Zone (LECZ) (Urban-Rural Population and Land Area Estimates, v2) - 10.7927/H4MW2F2J
Low Elevation Coastal Zone (LECZ) (Urban-Rural Population and Land Area Estimates, v3) - 10.7927/d1x1-d702
Satellite-Derived Environmental Indicators (VIIRS Plus DMSP Change in Lights (VIIRS+DMSP dLIGHT), v1) - 10.7927/9ryj-6467
REMOTE SENSING (MERIT)

Magura, T., Ferrante, M., & Lövei, G. L. (2020). Only habitat specialists become smaller with advancing urbanization. Global Ecology and Biogeography, 29(11), 1978-1987. doi:10.1111/geb.13168
Satellite-Derived Environmental Indicators (Global Urban Heat Island (UHI) Data Set, v1)- 10.7927/H4H70CRF

Mai, X., Zhou, H., Li, Y., Huang, X., & Yang, T. (2022). Associations between ambient fine particulate (PM2.5) exposure and cardiovascular disease: findings from the China Health and Retirement Longitudinal Study (CHARLS). Environmental Science and Pollution Research, 29, 13114-13121. doi:10.1007/s11356-021-16541-3
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Manoli, G., Fatichi, S., Schläpfer, M., Yu, K., Crowther, T. W., Meili, N., . . . Bou-Zeid, E. (2019). Magnitude of urban heat islands largely explained by climate and population. Nature, 573(7772), 55-60. doi:10.1038/s41586-019-1512-9
Satellite-Derived Environmental Indicators (Global Urban Heat Island (UHI) Data Set, v1)- 10.7927/H4H70CRF
NASA REMOTE SENSING (MODIS - MCD43B3)
NASA REMOTE SENSING (MERRA)

Mao, Z. (2016). Turning Policy Promises into Blue Skies: Mixed-Method Assessment of China's Past and Future Air Pollution–Reduction Efforts. (Ph.D.). Santa Monica. Retrieved from https://doi.org/10.7249/RGSD385 (RGSD-385)
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v1) - 10.7927/H4028PFS

Marlier, M. E., Jina, A. S., Kinney, P. L., & DeFries, R. S. (2016). Extreme air pollution in global megacities. Current Climate Change Reports, 2(1), 15-27. doi:10.1007/s40641-016-0032-z
Global Rural-Urban Mapping Project (GRUMP) v1 (urban extent)
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v1) - 10.7927/H4028PFS
NASA REMOTE SENSING (MODIS)

McKeon, T. P., Hwang, W.-T., Ding, Z., Tam, V., Wileyto, P., Glanz, K., & Penning, T. M. (2021). Environmental exposomics and lung cancer risk assessment in the Philadelphia metropolitan area using ZIP code–level hazard indices. Environmental Science and Pollution Research, 28, 31758-31769. doi:10.1007/s11356-021-12884-z
Satellite-Derived Environmental Indicators (Global 3-Year Running Mean Ground-Level NO2 Grids from GOME, SCIAMACHY and GOME-2, v1)
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Meichang, W., & Bingbing, Z. (2020). Examining the impact of polycentric urban form on air pollution: evidence from China. Environmental Science and Pollution Research, 27, 43359–43371. doi:10.1007/s11356-020-10216-1
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)
REMOTE SENSING (DMSP-OLS)

Mentaschi, L., Duveiller, G., Zulian, G., Corbane, C., Pesaresi, M., Maes, J., . . . Feyen, L. (2022). Global long-term mapping of surface temperature shows intensified intra-city urban heat island extremes. Global Environmental Change, 72, 102441. doi:10.1016/j.gloenvcha.2021.102441
Satellite-Derived Environmental Indicators (Global Urban Heat Island (UHI) Data Set, v1)- 10.7927/H4H70CRF
NASA REMOTE SENSING (MODIS)

Meredith, W. J., Cardenas-Iniguez, C., Berman, M. G., & Rosenberg, M. D. (2022). Effects of the physical and social environment on youth cognitive performance. Developmental Psychobiology, 64(4), e22258. doi:10.1002/dev.22258
Satellite-Derived Environmental Indicators (Global 3-Year Running Mean Ground-Level NO2 Grids from GOME, SCIAMACHY and GOME-2, v1) - 10.7927/H4JW8BTT
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1) - 10.7927/H4ZK5DQS

Minaravesh, B., & Aydin, O. (2023). Environmental and demographic factors on childhood academic performance in Los Angeles county: A generalized linear elastic net regression model. Remote Sensing Applications: Society and Environment, 30, 100942. doi:10.1016/j.rsase.2023.100942
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1) - 10.7927/H4ZK5DQS

Misra, P., Avtar, R., & Takeuchi, W. (2018). Comparison of digital building height models extracted from AW3D, TanDEM-X, ASTER, and SRTM digital surface models over Yangon City. Remote Sensing, 10(12), 2008. doi:10.3390/rs10122008
Global Rural-Urban Mapping Project (GRUMP) v1 (urban extent)
Satellite-Derived Environmental Indicators (Global Urban Heat Island (UHI) Data Set, v1)
NASA REMOTE SENSING (ASTER GDEM)
NASA REMOTE SENSING (SRTM)
REMOTE SENSING (TanDEM-X)
REMOTE SENSING (ALOS Global Digital Surface Model - ALOS World 3D - 30m (AW3D30))

Moraga, P., Cramb, S. M., Mengersen, K. L., & Pagano, M. (2017). A geostatistical model for combined analysis of point-level and area-level data using INLA and SPDE. Spatial Statistics, 21, Part A, 27-41. doi:10.1016/j.spasta.2017.04.006
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v1) - 10.7927/H4028PFS

Mukherjee, A. D. (2018). Examining Aerosol Properties and Their Impacts to Visibility Utilizing Particulate Monitor and Sensor Measurements. (Ph.D. Ph.D.). Univeristy of Colorado Boulder, Retrieved from https://search.proquest.com/docview/2048322168?accountid=10226 
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1) - 10.7927/H4H41PB4

Munir, S., Gabr, S., Habeebullah, T. M., & Janajrah, M. A. (2016). Spatiotemporal analysis of fine particulate matter (PM2.5) in Saudi Arabia using remote sensing data. The Egyptian Journal of Remote Sensing and Space Science, 19(2), 195-205. doi:10.1016/j.ejrs.2016.06.001
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Narayan, T., Bhattacharya, T., Chakraborty, S., & Konar, S. (2022). Application of multiple linear regression and geographically weighted regression model for prediction of PM2.5. Proceedings of the National Academy of Sciences, India Section A: Physical Sciences, 92, 217-229. doi:10.1007/s40010-020-00718-5
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1) documentation

Nath, D., Sasikumar, K., Nath, R., & Chen, W. (2021). Factors affecting COVID-19 outbreaks across the globe: Role of extreme climate change. Sustainability, 13(6), 3029. doi:10.3390/su13063029
Gridded Population of the World (GPW) v3 (population count) - 10.​7927/​H4639MPP
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v1) - 10.7927/H4028PFS

Nguyen, H. D., Trieu, T., Cope, M., Azzi, M., & Morgan, G. (2020). Modelling hazardous reduction burnings and bushfire emission in air quality model and their impacts on health in the Greater Metropolitan Region of Sydney. Environmental Modeling & Assessment, 25, 705-730. doi:10.1007/s10666-020-09705-x
Satellite-Derived Environmental Indicators (Global Fire Emissions Indicators, Country-Level Tabular Data, v1) - 10.7927/H4V69GJ5
NASA REMOTE SENSING (MODIS)

Nguyen, K.-A., & Liou, Y.-A. (2019). Mapping global eco-environment vulnerability due to human and nature disturbances. MethodsX, 6, 862-875. doi:10.1016/j.mex.2019.03.023
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1) - 10.7927/H4ZK5DQS
NASA REMOTE SENSING (MODIS - MCD12Q1)
REMOTE SENSING (Soil Moisture and Ocean Salinity (SMOS))

Ning, G., Wang, S., Ma, M., Ni, C., Shang, Z., Wang, J., & Li, J. (2018). Characteristics of air pollution in different zones of Sichuan Basin, China. Science of The Total Environment, 612, 975-984. doi:10.1016/j.scitotenv.2017.08.205
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Ou, Y., Kim, E., Liu, X., & Nam, K.-M. (2023). Delineating functional regions from road networks: The case of South Korea. Environment and Planning B: Urban Analytics and City Science, 50(6), 1677-1694. doi:10.1177/23998083231172198
Satellite-Derived Environmental Indicators (Global (GL) Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v4.03) - 10.7927/fx80-4n39

Pang, J., Li, N., Mu, H., & Zhang, M. (2021). Empirical analysis of the interplay between shadow economy and pollution: With panel data across the provinces of China. Journal of Cleaner Production, 285, 124864. doi:10.1016/j.jclepro.2020.124864
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Pansini, R., & Fornacca, D. (2021). Early spread of COVID-19 in the air-polluted regions of eight severely affected countries. Atmosphere, 12(6), 795. doi:10.3390/atmos12060795
Satellite-Derived Environmental Indicators (Global 3-Year Running Mean Ground-Level NO2 Grids from GOME, SCIAMACHY and GOME-2, v1) - 10.7927/H4JW8BTT
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1) - 10.7927/H4ZK5DQS

Partnership for Resilience and Preparedness (PREP). (2018). PREPdata. Retrieved from https://www.prepdata.org/
Energy Infrastructure (Population Exposure Estimates in Proximity to Nuclear Power Plants, Locations)
Spatial Economic Data (Global Gridded Geographically Based Economic Data (G-Econ), v4)
Land Use and Land Cover (LULC) (Global Grid of Probabilities of Urban Expansion to 2030, v1)
Gridded Population of the World (GPW) v4 (population count UN WPP-adjusted)
Global Reservoir and Dam (GRanD) v1 (collection)
Global Roads (Global Roads Open Access Data Set (gROADS), v1)
Satellite-Derived Environmental Indicators (Global Urban Heat Island (UHI) Data Set, v1)

Paul, B., Mishra, M. K., & Das, A. K. (2022). Spatial heterogeneity and estimation of PM10 concentration over Brahmaputra Valley using geographic weighted regression model assimilating surface, MODIS, and ERA-interim reanalysis data. Air Quality, Atmosphere & Health, 15, 425-435. doi:10.1007/s11869-022-01160-9
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)
NASA REMOTE SENSING (MODIS)

Pezzulo, C., Tejedor-Garavito, N., Chan, H. M. T., Dreoni, I., Kerr, D., Ghosh, S., . . . Tatem, A. J. (2023). A subnational reproductive, maternal, newborn, child, and adolescent health and development atlas of India. Scientific Data, 10(1), 86. doi:10.1038/s41597-023-01961-2
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1) - 10.7927/H4ZK5DQS
REMOTE SENSING (VIIRS NTL)

Pricope, N. G., Daldegan, G. A., Zvoleff, A., Mwenda, K. M., Noon, M., & Lopez-Carr, D. (2023). Operationalizing an integrative socio-ecological framework in support of global monitoring of land degradation. Land Degradation & Development, 34(1), 109-124. doi:10.1002/ldr.4447
Anthropogenic Biomes of the World (collection)
Food Security (Food Insecurity Hotspots Data Set, v1)
Gridded Population of the World (GPW) v4 (collection)
Global Rural-Urban Mapping Project (GRUMP) v1 (collection)
Satellite-Derived Environmental Indicators (Trends in Global Freshwater Availability from the Gravity Recovery and Climate Experiment (GRACE), v1)
NASA REMOTE SENSING (AVHRR GIMMS)
NASA REMOTE SENSING (MODIS)

Qiang, W., Lee, H. F., Lin, Z., & Wong, D. W. H. (2020). Revisiting the impact of vehicle emissions and other contributors to air pollution in urban built-up areas: A dynamic spatial econometric analysis. Science of The Total Environment, 740, 140098. doi:10.1016/j.scitotenv.2020.140098
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Qiang, W., Lin, Z., Zhu, P., Wu, K., & Lee, H. F. (2021). Shrinking cities, urban expansion, and air pollution in China: A spatial econometric analysis. Journal of Cleaner Production, 324, 129308. doi:10.1016/j.jclepro.2021.129308
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Qiao, X., Jaffe, D., Tang, Y., Bresnahan, M., & Song, J. (2015). Evaluation of air quality in Chengdu, Sichuan Basin, China: are China’s air quality standards sufficient yet? Environmental Monitoring and Assessment, 187(5), 1-11. doi:10.1007/s10661-015-4500-z
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Qin, M., Liu, X., & Tong, Y. (2019). Does urban sprawl aggravate smog pollution? In D. He & C. Wang (Eds.), A New Era: China's Economy Globalizes (pp. 175-201). Singapore: Springer Singapore.
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)
REMOTE SENSING (DMSP-OLS)

Ren, T., Yu, X., & Yang, W. (2019). Do cognitive and non-cognitive abilities mediate the relationship between air pollution exposure and mental health? PLoS ONE, 14(10), e0223353. doi:10.1371/journal.pone.0223353
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1) - 10.7927/H4ZK5DQS

Rhew, S. H., Kravchenko, J., & Lyerly, H. K. (2021). Exposure to low-dose ambient fine particulate matter PM2.5 and Alzheimer’s disease, non-Alzheimer’s dementia, and Parkinson’s disease in North Carolina. PLoS ONE, 16(7), e0253253. doi:10.1371/journal.pone.0253253
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Ribeiro Rios, I. H. (2022). Mudança temporal da concentração de material particulado na região metropolitana de Salvador: comparação com padrões da CONAMA 491/2018 e OMS. Europub Journal of Health Research, 3(4), 891-896. Retrieved from https://ojs.europubpublications.com/ojs/index.php/ejhr/article/view/517
Satellite-Derived Environmental Indicators (Global (GL) Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v4.03)

Rizzati, M. C. P., Florenzio, N., Guastella, G., & Pareglio, S. (2023). Kuznets and the cities: Urban level EKC evidence from Europe. Ecological Indicators, 148, 110143. doi:10.1016/j.ecolind.2023.110143
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1) - 10.7927/H4ZK5DQS

Rohde, R. A., & Muller, R. A. (2015). Air pollution in China: Mapping of concentrations and sources. PLoS ONE, 10(8), e0135749. doi:10.1371/journal.pone.0135749
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1) - 10.7927/H4H41PB4

Rousseau, L. S. A., Kloostra, B., AzariJafari, H., Saxe, S., Gregory, J., & Hertwich, E. G. (2022). Material stock and embodied greenhouse gas emissions of global and urban road pavement. Environmental Science & Technology, 56(24), 18050-18059. doi:10.1021/acs.est.2c05255
Satellite-Derived Environmental Indicators (Global Urban Heat Island (UHI) Data Set, v1)

Sadik-Zada, E. R., & Gatto, A. (2022). Chapter 2 - Vulnerability to the urban heat islands effect in the Global North and the Global South: assessment of the drivers and mitigation strategies. In A. Khan, H. Akbari, F. Fiorito, S. Mithun, & D. Niyogi (Eds.), Global Urban Heat Island Mitigation (pp. 29-45): Elsevier.
Global Rural-Urban Mapping Project (GRUMP) v1.02 (urban extent polygons) - 10.7927/np6p-qe61
Satellite-Derived Environmental Indicators (Global Urban Heat Island (UHI) Data Set, v1)- 10.7927/H4H70CRF
Satellite-Derived Environmental Indicators (Global Summer Land Surface Temperature (LST) Grids, v1) - 10.7927/H408638T

Sarangi, C., Qian, Y., Leung, R., Zhang, Y., Zou, Y., & Wang, Y. (2023). Projected increases in wildfires may challenge regulatory curtailment of PM2.5 over the eastern US by 2050. Atmospheric Chemistry and Physics, 23(2), 1769-1783. doi:10.5194/acp-23-1769-2023
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1) - 10.7927/H4ZK5DQS

Sasikumar, K., Nath, D., Nath, R., & Chen, W. (2020). Impact of extreme hot climate on COVID-19 outbreak in India. GeoHealth, 4(12), e2020GH000305. doi:10.1029/2020GH000305
Gridded Population of the World (GPW) v4.11 (population density map)
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Schiavina, M., Melchiorri, M., & Freire, S. (2023). A smart and flexible approach for aggregation of adjacent polygons to meet a minimum target area or attribute value. Scientific Reports, 13(1), 4367. doi:10.1038/s41598-023-31253-z
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Shan, Y., Wang, X., Wang, Z., Liang, L., Li, J., & Sun, J. (2020). The pattern and mechanism of air pollution in developed coastal areas of China: From the perspective of urban agglomeration. PLoS ONE, 15(9), e0237863. doi:10.1371/journal.pone.0237863
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Shao, J., Ge, T., Liu, Y., Zhao, Z., & Xia, Y. (2021). Longitudinal associations between household solid fuel use and depression in middle-aged and older Chinese population: A cohort study. Ecotoxicology and Environmental Safety, 209, 111833. doi:10.1016/j.ecoenv.2020.111833
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Shao, S., Cheng, S., & Jia, R. (2023). Can low carbon policies achieve collaborative governance of air pollution? Evidence from China's carbon emissions trading scheme pilot policy. Environmental Impact Assessment Review, 103, 107286. doi:10.1016/j.eiar.2023.107286
Satellite-Derived Environmental Indicators (Global (GL) Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v4.03)

Shao, W.-C., & Chou, L.-C. (2023). Political influence and air pollution: Evidence from Chinese cities. Heliyon, 9(7), e17781. doi:10.1016/j.heliyon.2023.e17781
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Shi, Y., Bilal, M., Ho, H. C., & Omar, A. (2020). Urbanization and regional air pollution across South Asian developing countries – A nationwide land use regression for ambient PM2.5 assessment in Pakistan. Environmental Pollution, 266, 115145. doi:10.1016/j.envpol.2020.115145
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Shi, Z., Li, X., Hu, T., Yuan, B., Yin, P., & Jiang, D. (2023). Modeling the intensity of surface urban heat island based on the impervious surface area. Urban Climate, 49, 101529. doi:10.1016/j.uclim.2023.101529
Satellite-Derived Environmental Indicators (Global Urban Heat Island (UHI) Data Set, v1)- 10.7927/H4H70CRF

Singh, A., Avis, W., R., & Pope, F. (2020). Visibility as a proxy for air quality in East Africa. Environmental Research Letters, 15(8), 084002. doi:10.1088/1748-9326/ab8b12
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Singha, M., Dong, J., Ge, Q., Metternicht, G., Sarmah, S., Zhang, G., . . . Xiao, X. (2021). Satellite evidence on the trade-offs of the food-water–air quality nexus over the breadbasket of India. Global Environmental Change, 71, 102394. doi:10.1016/j.gloenvcha.2021.102394
Gridded Population of the World (GPW) v4 (population count)
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)
NASA REMOTE SENSING (GRACE)
NASA REMOTE SENSING (MODIS - MOD09A1)

Siregar, S., Idiawati, N., Pan, W.-C., & Yu, K.-P. (2022). Association between satellite-based estimates of long-term PM2.5 exposure and cardiovascular disease: evidence from the Indonesian Family Life Survey. Environmental Science and Pollution Research, 29, 21156-21165. doi:10.1007/s11356-021-17318-4
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Song, D., Zhang, Q., & Yang, L. (2020). Environmental effect of flattening administrative structure on local water quality: a county-level analysis of China’s County-Power-Expansion reform. Journal of Cleaner Production, 276, 123256. doi:10.1016/j.jclepro.2020.123256
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1) - 10.7927/H4ZK5DQS

Song, Y., Zhu, N., & Luo, F. (2022). City size and permanent settlement intention: Evidence from rural-urban migrants in China. International Journal of Environmental Research and Public Health, 19(2), 676. doi:10.3390/ijerph19020676
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Soo, J.-S. T. (2018). Valuing air quality in Indonesia using households' locational choices. Environmental and Resource Economics, 71(3), 755-776. doi:10.1007/s10640-017-0182-z
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)
REMOTE SENSING (WindSat)

Su, S., Liu, Z., Xu, Y., Li, J., Pi, J., & Weng, M. (2017). China’s megaregion policy: Performance evaluation framework, empirical findings and implications for spatial polycentric governance. Land Use Policy, 63, 1-19. doi:10.1016/j.landusepol.2017.01.014
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v1) - 10.7927/H4028PFS
REMOTE SENSING (Landsat)

Su, Z., Xu, Z., Lin, L., Chen, Y., Hu, H., Wei, S., & Luo, S. (2022). Exploration of the contribution of fire carbon emissions to PM2.5 and their influencing factors in Laotian tropical rainforests. Remote Sensing, 14(16), 4052. doi:10.3390/rs14164052
Satellite-Derived Environmental Indicators (Global (GL) Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v4.03)

Sun, J., Zhang, J.-H., Wang, C., Duan, X., & Wang, Y. (2019). Escape or stay? Effects of haze pollution on domestic travel: Comparative analysis of different regions in China. Science of The Total Environment, 690, 151-157. doi:10.1016/j.scitotenv.2019.06.415
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v1)

Sun, X., Zhang, R., & Wang, G. (2022). Spatial-temporal evolution of health impact and economic loss upon exposure to PM2.5 in China. International Journal of Environmental Research and Public Health, 19(4), 1922. doi:10.3390/ijerph19041922
Satellite-Derived Environmental Indicators (unspecified PM.25 data set)

Sun, Y., Hu, H., & Jin, G. (2022). Pollution or innovation? How enterprises react to air pollution under perfect information. Science of The Total Environment, 831, 154821. doi:10.1016/j.scitotenv.2022.154821
Satellite-Derived Environmental Indicators (Global (GL) Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v4.03) - 10.7927/fx80-4n39

Szabó, B., Korányi, D., Gallé, R., Lövei, G. L., Bakonyi, G., & Batáry, P. (2023). Urbanization decreases species richness, and increases abundance in dry climates whereas decreases in wet climates: A global meta-analysis. Science of The Total Environment, 859(Part 1), 160145. doi:10.1016/j.scitotenv.2022.160145
Satellite-Derived Environmental Indicators (Global Urban Heat Island (UHI) Data Set, v1)- 10.7927/H4H70CRF

Tayari, S., Taghikhah, F., Bharathy, G., & Voinov, A. (2023). Designing a conceptual framework for strategic selection of Bushfire mitigation approaches. Journal of Environmental Management, 344, 118486. doi:10.1016/j.jenvman.2023.118486
Satellite-Derived Environmental Indicators (Global Fire Emissions Indicators, Country-Level Tabular Data, v1) - 10.7927/H4V69GJ5

Taylor, J., Haines, A., Milner, J., Davies, M., & Wilkinson, P. (2018). A comparative analysis of global datasets and initiatives for urban health and sustainability. Sustainability, 10(10), 3636. doi:10.3390/su10103636
Satellite-Derived Environmental Indicators (Global Urban Heat Island (UHI) Data Set, v1)- 10.7927/H4H70CRF
NASA REMOTE SENSING (ASTER)

Tidwell, V., Gunda, T., Caballero, M., Xu, P., Xu, X., Bernknopf, R., . . . Jacobson, J. (2022). Produced Water-Economic, Socio, Environmental Simulation Model (PW-ESEim) Model: Proof-of-Concept for Southeastern New Mexico. Retrieved from https://doi.org/10.2172/1868149
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1) - 10.7927/H4ZK5DQS

Tippett, M. K., Lepore, C., Koshak, W. J., Chronis, T., & Vant-Hull, B. (2019). Performance of a simple reanalysis proxy for U.S. cloud-to-ground lightning. International Journal of Climatology, 39(10), 3932-3946. doi:10.1002/joc.6049
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v1) - 10.7927/H4028PFS

Tsurumi, T., & Managi, S. (2020). Health-related and non-health-related effects of PM2.5 on life satisfaction: Evidence from India, China and Japan. Economic Analysis and Policy, 67, 114-123. doi:10.1016/j.eap.2020.06.002
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Turner-Skoff, J. B., & Cavender, N. (2019). The benefits of trees for livable and sustainable communities. Plants, People, Planet, 1(4), 323-335. doi:10.1002/ppp3.39
Satellite-Derived Environmental Indicators (Global Urban Heat Island (UHI) Data Set, v1)- 10.7927/H4H70CRF

Unfried, K., Kis-Katos, K., & Poser, T. (2021). Water Scarcity and Social Conflict. Retrieved from Bonn: https://www.iza.org/publications/dp/14707/water-scarcity-and-social-conflict
Global Rural-Urban Mapping Project (GRUMP) v1 (urban extent)
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)
NASA REMOTE SENSING (GRACE)

Unfried, K., Kis-Katos, K., & Poser, T. (2022). Water scarcity and social conflict. Journal of Environmental Economics and Management, 113, 102633. doi:10.1016/j.jeem.2022.102633
Gridded Population of the World (GPW) v4 (admin unit center points with population estimates)
Global Rural-Urban Mapping Project (GRUMP) v1 (urban extent)
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)
NASA REMOTE SENSING (GRACE)

Unfried, K., & Wang, F. (2022). Importing Air Pollution? Evidence from China's Plastic Waste Imports Retrieved from https://www.iza.org/publications/dp/15218/importing-air-pollution-evidence-from-chinas-plastic-waste-imports#
Satellite-Derived Environmental Indicators (Annual PM2.5 Concentrations for Countries and Urban Areas, v1) - 10.7927/rja8-8h89
NASA REMOTE SENSING (FIRMS)

Wang, K., Yin, H., & Chen, Y. (2019). The effect of environmental regulation on air quality: A study of new ambient air quality standards in China. Journal of Cleaner Production, 215, 268-279. doi:10.1016/j.jclepro.2019.01.061
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Wang, K., Zhao, X., Peng, B., & Zeng, Y. (2021). Can energy efficiency progress reduce PM2.5 concentration in China’s cities? Evidence from 105 key environmental protection cities in China, 2004–2015. Journal of Cleaner Production, 288, 125684. doi:10.1016/j.jclepro.2020.125684
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Wang, L., Jiang, S., & Xu, H. (2021). Reexamining the impact of industrial structure on haze pollution based on the Yangtze River Delta. Atmosphere, 12(5), 613. doi:10.3390/atmos12050613
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Wang, L., Shi, T., & Chen, H. (2023). Air pollution and infant mortality: Evidence from China. Economics & Human Biology, 49, 101229. doi:10.1016/j.ehb.2023.101229
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Wang, L.-J., & Chen, M.-H. (2021). Nonlinear impact of air quality on tourist arrivals: New proposal and evidence. Journal of Travel Research, 60(2), 434-445. doi:10.1177/0047287519899993
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Wang, L.-J., Chen, M.-H., & Lu, L. (2022). Air quality effect on the hotel industry. Tourism Economics, 28(4), 942-950. doi:10.1177/1354816620970747
Satellite-Derived Environmental Indicators (unspecified PM.25 data set)

Wang, M., & Wang, H. (2021). Spatial distribution patterns and influencing factors of PM2.5 pollution in the Yangtze River Delta: Empirical analysis based on a GWR model. Asia-Pacific Journal of Atmospheric Sciences, 57, 63-75. doi:10.1007/s13143-019-00153-6
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Wang, N. N., Zhu, C. Y., Li, W., Qiu, M. Y., Wang, B. L., Li, X. Y., . . . Cheng, H. C. (2023). Air quality improvement assessment and exposure risk of Shandong Province in China during 2014 to 2020. International Journal of Environmental Science and Technology, 20, 9495-9504. doi:10.1007/s13762-022-04651-5
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1) via Earthdata

Wang, R., Feng, Z., Pearce, J., Liu, Y., & Dong, G. (2021). Are greenspace quantity and quality associated with mental health through different mechanisms in Guangzhou, China: A comparison study using street view data. Environmental Pollution, 290, 117976. doi:10.1016/j.envpol.2021.117976
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)
REMOTE SENSING (Landsat)

Wang, R., Feng, Z., Pearce, J., Zhou, S., Zhang, L., & Liu, Y. (2021). Dynamic greenspace exposure and residents’ mental health in Guangzhou, China: From over-head to eye-level perspective, from quantity to quality. Landscape and Urban Planning, 215, 104230. doi:10.1016/j.landurbplan.2021.104230
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)
REMOTE SENSING (Landsat)

Wang, R., Yang, B., Yao, Y., Bloom, M. S., Feng, Z., Yuan, Y., . . . Dong, G. (2020). Residential greenness, air pollution and psychological well-being among urban residents in Guangzhou, China. Science of The Total Environment, 711, 134843. doi:10.1016/j.scitotenv.2019.134843
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v1)

Wang, S., & Cai, Q. (2021). Are home buyers in Chinese cities concerned about air quality? Using panel data for 70 large and medium-sized cities from 2006 to 2016 as an example. Journal of Housing and the Built Environment, 36, 685-704. doi:10.1007/s10901-020-09771-3
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Wang, S., Ren, Z., Liu, X., & Yin, Q. (2022). Spatiotemporal trends of life expectancy, economic growth, and air pollution: A 134 countries investigation based on Bayesian modeling. Social Science & Medicine, 293, 114660. doi:10.1016/j.socscimed.2021.114660
Gridded Population of the World (GPW) v4 (unspecified)
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Wang, X., & Feng, Y. (2021). The effects of National High-tech Industrial Development Zones on economic development and environmental pollution in China during 2003–2018. Environmental Science and Pollution Research, 28, 1097-1107. doi:10.1007/s11356-020-10553-1
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Wang, Y., Chen, S., & Yao, J. (2019). Impacts of deregulation reform on PM2.5 concentrations: A case study of business registration reform in China. Journal of Cleaner Production, 235, 1138-1152. doi:10.1016/j.jclepro.2019.06.312
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v1)

Wang, Y., Chen, X., & Ren, S. (2019). Clean energy adoption and maternal health: Evidence from China. Energy Economics, 84, 104517. doi:10.1016/j.eneco.2019.104517
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Wang, Y., Gong, Y., Bai, C., Yan, H., & Yi, X. (2023). Exploring the convergence patterns of PM2.5 in Chinese cities. Environment, Development and Sustainability, 25, 708-733. doi:10.1007/s10668-021-02077-6
Satellite-Derived Environmental Indicators (Annual PM2.5 Concentrations for Countries and Urban Areas, v1) - 10.7927/rja8-8h89

Wang, Z., Hu, B., Huang, B., Ma, Z., Biswas, A., Jiang, Y., & Shi, Z. (2022). Predicting annual PM2.5 in mainland China from 2014 to 2020 using multi temporal satellite product: An improved deep learning approach with spatial generalization ability. ISPRS Journal of Photogrammetry and Remote Sensing, 187, 141-158. doi:10.1016/j.isprsjprs.2022.03.002
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)
NASA REMOTE SENSING (MODIS - MCD19A2)

Weber, S., Sadoff, N., Zell, E., & de Sherbinin, A. M. (2015). Policy-relevant indicators for mapping the vulnerability of urban populations to extreme heat events: A case study of Philadelphia. Applied Geography, 63, 231-243. doi:10.1016/j.apgeog.2015.07.006
Satellite-Derived Environmental Indicators (Global Urban Heat Island (UHI) Data Set, v1)- 10.7927/H4H70CRF
NASA REMOTE SENSING (MODIS)

Wei, L.-Y., & Liu, Z. (2022). Air pollution and innovation performance of Chinese cities: human capital and labour cost perspective. Environmental Science and Pollution Research, 29, 67997-68015. doi:10.1007/s11356-022-20628-w
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Wen, C., Huang, X., Feng, L., Chen, L., Hu, W., Lai, Y., & Hao, Y. (2021). High-resolution age-specific mapping of the two-week illness prevalence rate based on the National Health Services Survey and geostatistical analysis: a case study in Guangdong province, China. International Journal of Health Geographics, 20(1), 20. doi:10.1186/s12942-021-00273-1
Satellite-Derived Environmental Indicators (Global Fire Emissions Indicators, Grids, v1)
NASA REMOTE SENSING (MODIS)

Wen, J., Chuai, X., Gao, R., & Pang, B. (2022). Regional interaction of lung cancer incidence influenced by PM2.5 in China. Science of The Total Environment, 803, 149979. doi:10.1016/j.scitotenv.2021.149979
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Wu, W., Yao, M., Yang, X., Hopke, P. K., Choi, H., Qiao, X., . . . Zhang, J. (2021). Mortality burden attributable to long-term ambient PM2.5 exposure in China: Using novel exposure-response functions with multiple exposure windows. Atmospheric Environment, 246, 118098. doi:10.1016/j.atmosenv.2020.118098
Gridded Population of the World (GPW) v4.11 (population count UN WPP-adjusted)
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Wu, X., Chen, Y., Guo, J., & Gao, G. (2018). Inputs optimization to reduce the undesirable outputs by environmental hazards: a DEA model with data of PM2.5 in China. Natural Hazards, 90(1), 1-25. doi:10.1007/s11069-017-3105-y
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Wu, X., Chen, Y., Guo, J., Wang, G., & Gong, Y. (2017). Spatial concentration, impact factors and prevention-control measures of PM2.5 pollution in China. Natural Hazards, 86(1), 393-410. doi:10.1007/s11069-016-2697-y
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Wu, X., Chen, Y., Zhao, P., Guo, J., & Ma, Z. (2020). Study of haze emission efficiency based on new co-opetition data envelopment analysis. Expert Systems, 37(4), e12466. doi:10.1111/exsy.12466
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Wu, X., Deng, H., Huang, Y., & Guo, J. (2022). Air pollution, migration costs, and urban residents’ welfare: A spatial general equilibrium analysis from China. Structural Change and Economic Dynamics, 63, 396-340. doi:10.1016/j.strueco.2022.05.010
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1) - 10.7927/H4ZK5DQS

Wu, X., Deng, H., Li, H., & Guo, Y. (2021). Impact of energy structure adjustment and environmental regulation on air pollution in China: Simulation and measurement research by the dynamic general equilibrium model. Technological Forecasting and Social Change, 172, 121010. doi:10.1016/j.techfore.2021.121010
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1) - 10.7927/H4ZK5DQS

Wu, X., Guo, J., Wei, G., & Zou, Y. (2020). Economic losses and willingness to pay for haze: the data analysis based on 1123 residential families in Jiangsu province, China. Environmental Science and Pollution Research, 27, 17864-17877. doi:10.1007/s11356-020-08301-6
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Wu, X., Ji, Z., Gong, Y., Chen, Y., & Toloo, M. (2021). Haze emission efficiency assessment and governance for sustainable development based on an improved network data envelopment analysis method. Journal of Cleaner Production, 317, 128424. Retrieved from https://doi.org/10.1016/j.jclepro.2021.128424
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Wu, X., Tan, L., Guo, J., Wang, Y., Liu, H., & Zhu, W. (2016). A study of allocative efficiency of PM2.5 emission rights based on a zero sum gains data envelopment model. Journal of Cleaner Production, 113, 1024-1031. doi:10.1016/j.jclepro.2015.11.025
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Xiao, H., & Wang, K. (2020). Does environmental labeling exacerbate heavily polluting firms’ financial constraints? Evidence from China. China Journal of Accounting Research, 13(2), 147-174. doi:10.1016/j.cjar.2020.05.001
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Xie, W., Deng, H., & Chong, Z. (2019). The spatial and heterogeneity impacts of population urbanization on fine particulate (PM2.5) in the Yangtze River Economic Belt, China. International Journal of Environmental Research and Public Health, 16(6), 1058. doi:10.3390/ijerph16061058
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Xie, Z., Li, Y., & Qin, Y. (2020). Allocation of control targets for PM2.5 concentration: An empirical study from cities of atmospheric pollution transmission channel in the Beijing-Tianjin-Hebei district. Journal of Cleaner Production, 270, 122545. doi:10.1016/j.jclepro.2020.122545
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Xie, Z., Li, Y., Qin, Y., & Rong, P. (2019). Value assessment of health losses caused by PM2.5 pollution in cities of atmospheric pollution transmission channel in the Beijing–Tianjin–Hebei Region, China. International Journal of Environmental Research and Public Health, 16(6), 1012. doi:10.3390/ijerph16061012
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Xie, Z., Qin, Y., Zhang, L., & Zhang, R. (2018). Death effects assessment of PM2.5 pollution in China. Polish Journal of Environmental Studies, 27(4), 1813-1821. doi:10.15244/pjoes/77077
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v1)

Xing, G., Zhang, Y., & Guo, J. e. (2023). Environmental regulation in evolution and governance strategies. International Journal of Environmental Research and Public Health, 20(6), 4906. doi:10.3390/ijerph20064906
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Xiong, G., & Luo, Y. (2021). Smog, media attention, and corporate social responsibility—empirical evidence from Chinese polluting listed companies. Environmental Science and Pollution Research, 28, 46116-46129. doi:10.1007/s11356-020-11978-4
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Xu, B., & Lin, B. (2016). Regional differences of pollution emissions in China: contributing factors and mitigation strategies. Journal of Cleaner Production, 112(Part 2), 1454-1463. doi:10.1016/j.jclepro.2015.03.067
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Xu, B., & Lin, B. (2018). What cause large regional differences in PM2.5 pollutions in China? Evidence from quantile regression model. Journal of Cleaner Production, 174, 447-461. doi:10.1016/j.jclepro.2017.11.008
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Xu, B., Luo, L., & Lin, B. (2016). A dynamic analysis of air pollution emissions in China: Evidence from nonparametric additive regression models. Ecological Indicators, 63, 346-358. doi:10.1016/j.ecolind.2015.11.012
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Xu, C., Wang, S., Zhou, Y., Wang, L., & Liu, W. (2016). A comprehensive quantitative evaluation of new sustainable urbanization level in 20 Chinese urban agglomerations. Sustainability, 8(2), 19. doi:10.3390/su8020091
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Xu, S., & Wang, C. (2021). City image and eco-efficiency: evidence from China. Environmental Science and Pollution Research, 28, 52459-52474. doi:10.1007/s11356-021-14219-4
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1) - 10.7927/H4ZK5DQS

Xu, Y., Wu, J., & Han, Z. (2022). Evaluation and projection of surface PM2.5 and its exposure on population in Asia based on the CMIP6 GCMs. International Journal of Environmental Research and Public Health, 19(19), 12092. doi:10.3390/ijerph191912092
Satellite-Derived Environmental Indicators (Global (GL) Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v4.03)
NASA REMOTE SENSING (MERRA-2)

Yan, D., Ren, X., Kong, Y., Ye, B., & Liao, Z. (2020). The heterogeneous effects of socioeconomic determinants on PM2.5 concentrations using a two-step panel quantile regression. Applied Energy, 272, 115246. doi:10.1016/j.apenergy.2020.115246
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Yan, D., Ren, X., Zhang, W., Li, Y., & Miao, Y. (2022). Exploring the real contribution of socioeconomic variation to urban PM2.5 pollution: New evidence from spatial heteroscedasticity. Science of The Total Environment, 806(Part 4), 150929. doi:10.1016/j.scitotenv.2021.150929
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Yang, C., Wang, W., Liang, Z., Wang, Y., Chen, R., Liang, C., . . . Zhang, L. (2023). Regional urbanicity levels modify the association between ambient air pollution and prevalence of obesity: A nationwide cross-sectional survey. Environmental Pollution, 320, 121079. doi:10.1016/j.envpol.2023.121079
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Yang, C., Zhan, Q., Xiao, Y., & Liu, H. (2020). Identifying the driving factors of population exposure to fine particulate matter (PM2.5) in Wuhan, China. ISPRS Annals of the Photogrammetry, Remote Sensing, and Spatial Information Sciences, V-3-2020, 355-361. doi:10.5194/isprs-annals-V-3-2020-355-2020
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)
NASA REMOTE SENSING (MODIS - MOD11A1)
NASA REMOTE SENSING (SRTM)

Yang, D., Meng, F., Liu, Y., Dong, G., & Lu, D. (2022). Scale effects and regional disparities of land use in influencing PM2.5 concentrations: A case study in the Zhengzhou Metropolitan Area, China. Land, 11(9), 1538. doi:10.3390/land11091538
Satellite-Derived Environmental Indicators (Global (GL) Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v4.03)

Yang, F., Li, K., Jin, M., & Shi, W. (2021). Does financial deepening drive spatial heterogeneity of PM2.5 concentrations in China? New evidence from an eigenvector spatial filtering approach. Journal of Cleaner Production, 291, 125945. doi:10.1016/j.jclepro.2021.125945
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Yang, F., Xu, Q., Li, K., Yuen, K. F., & Shi, W. (2022). The inhibition effect of bank credits on PM2.5 concentrations: Spatial evidence from high-polluting firms in China. Environmental Pollution, 308, 119639. doi:10.1016/j.envpol.2022.119639
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Yang, J., & Xu, L. (2020). How does China's air pollution influence its labor wage distortions? Theoretical and empirical analysis from the perspective of spatial spillover effects. Science of The Total Environment, 745, 140843. doi:10.1016/j.scitotenv.2020.140843
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Yang, M., Xu, J., Yang, F., & Duan, H. (2021). Environmental regulation induces technological change and green transformation in Chinese cities. Regional Environmental Change, 21(2), 41. doi:10.1007/s10113-021-01759-1
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Yang, X., Wu, H., Ren, S., Ran, Q., & Zhang, J. (2021). Does the development of the internet contribute to air pollution control in China? Mechanism discussion and empirical test. Structural Change and Economic Dynamics, 56, 207-224. doi:10.1016/j.strueco.2020.12.001
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Yang, Y., Cao, L., Xia, Y., & Li, J. (2023). The effect of living environmental factors on cardiovascular diseases in Chinese adults: Results from a cross-sectional and longitudinal study. European Journal of Preventive Cardiology, 30(11), 1063-1073. doi:10.1093/eurjpc/zwac304
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Yang, Y., Lan, H., & Li, J. (2019). Spatial econometric analysis of the impact of socioeconomic factors on PM2.5 concentration in China’s inland cities: A case study from Chengdu Plain Economic Zone. International Journal of Environmental Research and Public Health, 17(1), 74. doi:10.3390/ijerph17010074
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Yang, Z., Song, Q., Li, J., Zhang, Y., Yuan, X.-C., Wang, W., & Yu, Q. (2021). Air pollution and mental health: The moderator effect of health behaviors. Environmental Research Letters, 16(4), 044005. doi:10.1088/1748-9326/abe88f
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1) - 10.7927/H4ZK5DQS

Yang, Z., Wang, Z., Yuan, X.-C., Qi, Y., Zhang, Y., Wang, W., . . . Li, J. (2022). Does income inequality aggravate the impacts of air pollution on physical health? Evidence from China. Environment, Development and Sustainability, 24, 2120-2144. doi:10.1007/s10668-021-01522-w
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1) - 10.7927/H4ZK5DQS

Yao, L., Sun, S., Wang, Y., Song, C., & Xu, Y. (2022). New insight into the urban PM2.5 pollution island effect enabled by the Gaussian surface fitting model: A case study in a mega urban agglomeration region of China. International Journal of Applied Earth Observation and Geoinformation, 113, 102982. doi:10.1016/j.jag.2022.102982
Satellite-Derived Environmental Indicators (Global (GL) Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v4.03)

Ye, C., Chen, R., Chen, M., & Ye, X. (2019). A new framework of regional collaborative governance for PM2.5. Stochastic Environmental Research and Risk Assessment, 33(4-6), 1109-1116. doi:10.1007/s00477-019-01688-w
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Yim, S. H. L., Gu, Y., Shapiro, M. A., & Stephens, B. (2019). Air quality and acid deposition impacts of local emissions and transboundary air pollution in Japan and South Korea. Atmospheric Chemistry and Physics, 19(20), 13309-13323. doi:10.5194/acp-19-13309-2019
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1) - 10.7927/H4ZK5DQS

Yin, C., Liu, J., & Sun, B. (2023). Effects of built and natural environments on leisure physical activity in residential and workplace neighborhoods. Health & Place, 81, 103018. doi:10.1016/j.healthplace.2023.103018
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Yu, K., Xing, Z., Huang, X., Deng, J., Andersson, A., Fang, W., . . . Du, K. (2018). Characterizing and sourcing ambient PM2.5 over key emission regions in China III: Carbon isotope based source apportionment of black carbon. Atmospheric Environment, 177, 12-17. doi:10.1016/j.atmosenv.2018.01.009
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v1) - 10.7927/H4028PFS

Yu, L., Ying, R., & Zhang, B. (2021). How air pollution lowers the domestic value-added ratio in exports: an empirical study of China. Environmental Science and Pollution Research, 28, 48123-48140. doi:10.1007/s11356-021-14120-0
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Yu, Y., Dai, C., Wei, Y., Ren, H., & Zhou, J. (2022). Air pollution prevention and control action plan substantially reduced PM2.5 concentration in China. Energy Economics, 113, 106206. doi:10.1016/j.eneco.2022.106206
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v1)

Yu, Z., Wei, F., Wu, M., Lin, H., Shui, L., Jin, M., . . . Chen, K. (2021). Association of long-term exposure to ambient air pollution with the incidence of sleep disorders: A cohort study in China. Ecotoxicology and Environmental Safety, 211, 111956. doi:10.1016/j.ecoenv.2021.111956
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Yun, G., Yang, C., & Ge, S. (2023). Understanding anthropogenic PM2.5 concentrations and their drivers in China during 1998-2016. International Journal of Environmental Research and Public Health, 20(1), 695. doi:10.3390/ijerph20010695
Satellite-Derived Environmental Indicators (Global (GL) Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v4.03)

Yun, G., & Zhao, S. (2022). The imprint of urbanization on PM2.5 concentrations in China: the urban-rural gradient study. Sustainable Cities and Society, 86, 104103. doi:10.1016/j.scs.2022.104103
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Zeng, Z., Xu, X., Wang, Q., Zhang, Z., Meng, P., & Huo, X. (2022). Maternal exposure to atmospheric PM2.5 and fetal brain development: Associations with BAI1 methylation and thyroid hormones. Environmental Pollution, 308, 119665. doi:10.1016/j.envpol.2022.119665
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Zhai, D., Cao, L., Zhou, Y., Liu, H., Shi, M., Wei, Y., & Xia, Y. (2022). The effect of water source on cognitive functioning in Chinese adults: A cross-sectional and follow-up study. Ecotoxicology and Environmental Safety, 230, 113156. doi:10.1016/j.ecoenv.2021.113156
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Zhang, G., Jia, Y., Su, B., & Xiu, J. (2021). Environmental regulation, economic development and air pollution in the cities of China: Spatial econometric analysis based on policy scoring and satellite data. Journal of Cleaner Production, 328, 129496. doi:10.1016/j.jclepro.2021.129496
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Zhang, H., Chen, J., & Wang, Z. (2021). Spatial heterogeneity in spillover effect of air pollution on housing prices: Evidence from China. Cities, 113, 103145. doi:10.1016/j.cities.2021.103145
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Zhang, H., Chen, J., Zhao, X., & Liu, J. (2020). Spatio-temporal variation of PM2.5 concentration in China from 1998 to 2016 and its response to economic development. Paper presented at the International Conference on Geomatics in the Big Data Era (ICGBD). https://doi.org/10.5194/isprs-archives-XLII-3-W10-49-2020
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Zhang, J., Wang, J., Yang, X., Ren, S., Ran, Q., & Hao, Y. (2021). Does local government competition aggravate haze pollution? A new perspective of factor market distortion. Socio-Economic Planning Sciences, 76, 100959. doi:10.1016/j.seps.2020.100959
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Zhang, L., Wilson, J. P., MacDonald, B., Zhang, W., & Yu, T. (2020). The changing PM2.5 dynamics of global megacities based on long-term remotely sensed observations. Environment International, 142, 105862. doi:10.1016/j.envint.2020.105862
Gridded Population of the World (GPW) v4 (collection)
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Zhang, L., Wilson, J. P., Zhao, N., Zhang, W., & Wu, Y. (2022). The dynamics of cardiovascular and respiratory deaths attributed to long-term PM2.5 exposures in global megacities. Science of The Total Environment, 842, 156951. doi:10.1016/j.scitotenv.2022.156951
Gridded Population of the World (GPW) v4.11 (population count)
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Zhang, M., & Chung, S.-h. (2020). Is air pollution detrimental to regional innovation? Evidence from Chinese cities. Growth and Change, 51(4), 1657-1689. doi:10.1111/grow.12445
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Zhang, M., Liu, X., Ding, Y., & Wang, W. (2019). How does environmental regulation affect haze pollution governance?—An empirical test based on Chinese provincial panel data. Science of The Total Environment, 695, 133905. doi:10.1016/j.scitotenv.2019.133905
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Zhang, M., Liu, X., Sun, X., & Wang, W. (2020). The influence of multiple environmental regulations on haze pollution: Evidence from China. Atmospheric Pollution Research, 11(6), 170-179. doi:10.1016/j.apr.2020.03.008
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Zhang, M., & Liu, Y. (2021). Does environmental pollution influence household asset allocation? Evidence from China. Environmental Science and Pollution Research, 28, 15406+15423. doi:10.1007/s11356-020-11710-2
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Zhang, N., Zhang, A., Wang, L., & Nie, P. (2021). Fine particulate matter and body weight status among older adults in China: Impacts and pathways. Health & Place, 69, 102571. doi:10.1016/j.healthplace.2021.102571
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Zhang, T., Sun, Y., Zhang, X., Yin, L., & Zhang, B. (2023). Potential heterogeneity of urban ecological resilience and urbanization in multiple urban agglomerations from a landscape perspective. Journal of Environmental Management, 342, 118129. doi:10.1016/j.jenvman.2023.118129
Satellite-Derived Environmental Indicators (unspecified PM.25 data set)
REMOTE SENSING (Landsat)

Zhang, X., Geng, Y., Shao, S., Song, X., Fan, M., Yang, L., & Song, J. (2020). Decoupling PM2.5 emissions and economic growth in China over 1998–2016: A regional investment perspective. Science of The Total Environment, 714, 136841. doi:10.1016/j.scitotenv.2020.136841
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Zhang, Y. (2020). Free trade and the environment – evidence from Chinese cities. Environment and Development Economics, 25(6), 561-582. doi:10.1017/S1355770X2000042X
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1) - 10.7927/H4H41PB4

Zhang, Y., Chen, X., Mao, Y., Shuai, C., Jiao, L., & Wu, Y. (2021). Analysis of resource allocation and PM2.5 pollution control efficiency: Evidence from 112 Chinese cities. Ecological Indicators, 127, 107705. doi:10.1016/j.ecolind.2021.107705
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Zhang, Y., Shi, T., Wang, A.-J., & Huang, Q. (2022). Air pollution, health shocks and labor mobility. International Journal of Environmental Research and Public Health, 19(3), 1382. doi:10.3390/ijerph19031382
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Zhang, Y., Wang, M., Shi, T., Huang, H., & Huang, Q. (2023). Health damage of air pollution, governance uncertainty and economic growth. International Journal of Environmental Research and Public Health, 20(4), 3036. doi:10.3390/ijerph20043036
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Zhao, C., Xie, R., Ma, C., & Han, F. (2022). Understanding the haze pollution effects of China's development zone program. Energy Economics, 111, 106078. doi:10.1016/j.eneco.2022.106078
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v1)

Zhao, J., & Dong, K. (2023). Is environmental regulation a powerful weapon to mitigate China’s PM2.5 emissions? The role of human capital. Journal of Asian Economics, 87, 101634. doi:10.1016/j.asieco.2023.101634
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), v1)

Zhao, J., Wang, X., Song, H., Du, Y., Cui, W., & Zhou, Y. (2019). Spatiotemporal trend analysis of PM2.5 concentration in China, 1999–2016. Atmosphere, 10(8), 461. doi:10.3390/atmos10080461
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Zhao, Y., Liang, C., & Zhang, X. (2021). Positive or negative externalities? Exploring the spatial spillover and industrial agglomeration threshold effects of environmental regulation on haze pollution in China. Environment, Development and Sustainability, 23, 11335-11356. doi:10.1007/s10668-020-01114-0
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1) - 10.7927/H4ZK5DQS

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Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Zheng, W., & Walsh, P. P. (2018). Air pollution and health - A provincial level analysis of China. Retrieved from Dublin: https://ideas.repec.org/p/ucd/wpaper/201819.html
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Zhou, J., Zhou, Y., & Bai, X. (2023). Can green-technology innovation reduce atmospheric environmental pollution? Toxics, 11(5), 403. doi:10.3390/toxics11050403
Satellite-Derived Environmental Indicators (unspecified PM.25 data set)

Zhou, L., Chen, X., & Tian, X. (2018). The impact of fine particulate matter (PM2.5) on China’s agricultural production from 2001 to 2010. Journal of Cleaner Production, 178, 133-141. doi:10.1016/j.jclepro.2017.12.204
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Zhou, L., Tian, X., & Zhou, Z. (2017). The effects of environmental provisions in RTAs on PM2.5 air pollution. Applied Economics, 49(27), 2630-2641. doi:10.1080/00036846.2016.1243218
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Zhou, Q., Zhong, S., Shi, T., & Zhang, X. (2021). Environmental regulation and haze pollution: Neighbor-companion or neighbor-beggar? Energy Policy, 151, 112183. doi:10.1016/j.enpol.2021.112183
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Zhu, F., Zhuang, D., Jin, S., Gao, L., & Chen, R. (2022). Effects of air pollution on regional innovation and the mediator role of health: Evidence from China. Growth and Change, 53(2), 628-650. doi:10.1111/grow.12600
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Zhu, L., Liao, H., & Burke, P. J. (2023). Household fuel transitions have substantially contributed to child mortality reductions in China. World Development, 164, 106174. doi:10.1016/j.worlddev.2022.106174
Satellite-Derived Environmental Indicators (Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, v1)

Zhu, W. (2020). The impact of economic growth on PM2.5 concentrations in China’s Yangtze River Delta Urban Agglomeration: Analysis based on Spatial Durbin Model. Journal of Physics: Conference Series, 1437, 012121. doi:10.1088/1742-6596/1437/1/012121
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)

Zhu, W., Wang, M., & Zhang, B. (2019). The effects of urbanization on PM2.5 concentrations in China's Yangtze River Economic Belt: New evidence from spatial econometric analysis. Journal of Cleaner Production, 239, 118065. doi:10.1016/j.jclepro.2019.118065
Satellite-Derived Environmental Indicators (Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD), v1)