npj Climate and Atmospheric Science (Jun 2024)

Integrated satellite observations unravel the relationship between urbanization and anthropogenic non-methane volatile organic compound emissions globally

  • Dongchuan Pu,
  • Lei Zhu,
  • Huizhong Shen,
  • Isabelle De Smedt,
  • Jianhuai Ye,
  • Juan Li,
  • Lei Shu,
  • Dakang Wang,
  • Xicheng Li,
  • Xiaoxing Zuo,
  • Xin Yang,
  • Tzung-May Fu

DOI
https://doi.org/10.1038/s41612-024-00683-5
Journal volume & issue
Vol. 7, no. 1
pp. 1 – 9

Abstract

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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.