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Abstract
As urban areas expand globally, human activities are leading to a sustained increase in non-methane volatile organic compound (NMVOC) emissions, escalating both environmental and health-related concerns. Given their diverse origins, estimating anthropogenic NMVOC emissions levels from global urban areas remains challenging. Here, we integrate TROPOspheric Monitoring Instrument (TROPOMI) formaldehyde (HCHO) column data, Visible Infrared Imaging Radiometer Suite (VIIRS) nighttime light (NTL) radiance data, and the Emission Database for Global Atmospheric Research (EDGAR) to develop a method for estimating global anthropogenic NMVOC emissions. Furthermore, we construct a linear model to analyze the relationship between urbanization and anthropogenic NMVOC emissions. Our research reveals that meticulously filtered TROPOMI HCHO columns have a high Pearson correlation coefficient (r = 0.91) with anthropogenic NMVOC emissions, indicating its reliability as an indicator reflecting the levels of anthropogenic NMVOC emissions. We establish linear models at various scales, including global, continental, and national, linking HCHO columns (as indicators of anthropogenic NMVOC emissions) and NTL radiance (as an indicator of urbanization). The global-scale linear model exhibits an r of 0.81, with a slope of 0.42 × 1015 molec. cm−2 nanoWatts−1 cm2 sr and an intercept of 9.26 × 1015 molec. cm−2. This linear model reflects a positive correlation between urbanization and anthropogenic NMVOC emissions, also serving as a tool for estimating the levels of anthropogenic NMVOC emissions in urban areas. This study offers valuable insights for real-time monitoring of extensive anthropogenic NMVOC emissions.
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1 Harbin Institute of Technology, School of Environment, Harbin, China (GRID:grid.19373.3f) (ISNI:0000 0001 0193 3564); Southern University of Science and Technology, School of Environmental Science and Engineering, Shenzhen, China (GRID:grid.263817.9) (ISNI:0000 0004 1773 1790)
2 Southern University of Science and Technology, School of Environmental Science and Engineering, Shenzhen, China (GRID:grid.263817.9) (ISNI:0000 0004 1773 1790); Guangdong Provincial Observation and Research Station for Coastal Atmosphere and Climate of the Greater Bay Area, Shenzhen, China (GRID:grid.263817.9); Southern University of Science and Technology, Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks, School of Environmental Science and Engineering, Shenzhen, China (GRID:grid.263817.9) (ISNI:0000 0004 1773 1790)
3 Royal Belgian Institute for Space Aeronomy (BIRA-IASB), Uccle, Belgium (GRID:grid.8654.f) (ISNI:0000 0001 2289 3389)
4 Southern University of Science and Technology, School of Environmental Science and Engineering, Shenzhen, China (GRID:grid.263817.9) (ISNI:0000 0004 1773 1790); Fujian Normal University, Fuzhou, School of Geographical Sciences, Fujian, China (GRID:grid.411503.2) (ISNI:0000 0000 9271 2478)
5 Southern University of Science and Technology, School of Environmental Science and Engineering, Shenzhen, China (GRID:grid.263817.9) (ISNI:0000 0004 1773 1790); Guangzhou University, School of Geography and Remote Sensing, Guangzhou, China (GRID:grid.411863.9) (ISNI:0000 0001 0067 3588)
6 Southern University of Science and Technology, School of Environmental Science and Engineering, Shenzhen, China (GRID:grid.263817.9) (ISNI:0000 0004 1773 1790)