Adverse effects of increasing drought on air quality via natural processes

• Main Authors: Y. Wang, Y. Xie, W. Dong, Y. Ming, J. Wang, L. Shen
• Format: Article
• Language: English
• Published: Copernicus Publications 2017-10-01
• Series: Atmospheric Chemistry and Physics
• Online Access: https://www.atmos-chem-phys.net/17/12827/2017/acp-17-12827-2017.pdf
• ISSN: 1680-7316; 1680-7324

Drought is a recurring extreme of the climate system with well-documented impacts on agriculture and water resources. The strong perturbation of drought to the land biosphere and atmospheric water cycle will affect atmospheric composition, the nature and extent of which are not well understood. Here we present observational evidence that US air quality is significantly correlated with drought severity. Severe droughts during the period of 1990–2014 were found associated with growth-season (March–October) mean enhancements in surface ozone and PM_2.5 of 3.5 ppbv (8 %) and 1.6 µg m⁻³ (17 %), respectively. The pollutant enhancements associated with droughts do not appear to be affected by the decreasing trend of US anthropogenic emissions, indicating natural processes as the primary cause. Elevated ozone and PM_2.5 are attributed to the combined effects of drought on deposition, natural emissions (wildfires, biogenic volatile organic compounds (BVOCs), and dust), and chemistry. Most climate–chemistry models are not able to reproduce the observed correlations of ozone and PM_2.5 to drought severity. The model deficiencies are partly attributed to the lack of drought-induced changes in land–atmosphere exchanges of reactive gases and particles and misrepresentation of cloud changes under drought conditions. By applying the observed relationships between drought and air pollutants to climate model projected drought occurrences, we estimate an increase of 1–6 % for ground-level O₃ and 1–16 % for PM_2.5 in the US by 2100 compared to the 2000s due to increasing drought alone. Drought thus poses an important aspect of climate change penalty on air quality, and a better prediction of such effects would require improvements in model processes.