Doctor of Philosophy (PhD)
Department of Civil and Environmental Engineering
Air pollution is a worldwide threat to human health and ecosystems, especially in developing countries. After being emitted to the atmosphere, air pollutant concentrations are determined by chemical and physical processes including transport, transformation, and deposition, which are largely affected by meteorological variations. In turn, pollutants such as fine particulate matter (PM2.5) affect meteorology by impacting solar radiation and cloud condensation processes. Thus, it is important and necessary to understand the interactions between air pollutants and meteorology for better designing effective air pollution control strategies and forecasting weather. In this study, two chemical transport models (CTMs) are applied to understand the interactions between air pollutants and meteorology in different areas. One model is the Community Multi-scale Air Quality (CMAQ) model and the other is the Weather Research and Forecasting model with Chemistry (WRF/Chem). Four cases are studied, the first case studies the responses of ozone (O3) and PM2.5 concentrations to variations in meteorology in China from 2013 to 2015. It is found that emission reductions in 2014 and 2015 effectively reduced PM2.5 concentrations by 23.9 and 43.5 µg/m3, respectively, but was partially counteracted by unfavorable meteorology. Reduction of primary PM and gaseous precursors led to 13.4 and 16.5 ppb increase of daily maximum 8 h average (MDA8) concentrations in the summertime in 2014 and 2015 in comparison to 2013, which was likely caused by the increase of solar actinic flux due to PM reduction. The other case understands the uncertainties caused by meteorology in simulating summertime O3 from 2016 to 2018 over the Southeast United States. WRF/Chem showed good performance in O3 simulation over Southeast US, especially along the coastal areas. The O3 simulation is sensitive to the meteorology uncertainties. The ensemble was more reliable than any individual run in this simulation. The last two cases simulate the feedbacks of air pollutants on meteorological conditions and related changes in pollutant concentrations in the Sichuan Basin (SCB), China and Africa, respectively. Aerosol radiation decreased surface temperature by 1-2 ℃, wind speed (WS) by ~ 0.3 m/s, planetary boundary layer (PBL) height by 10-20 %, solar radiation (SR) by ~ 30 %, and precipitation by 0.02-0.2 mm, while increased relative humidity (RH) by up to 2-4 % in January, which resulted in up to 10 µg/m3 increase of PM2.5 in January and 2 ppb decrease of O3 in July in SCB. In the simulation of Africa, PM2.5 concentration was higher in January and lower in August while O3 showed no significant seasonal and distribution variance. Aerosol radiative effects reduced solar radiation at the ground by as much as 20 w/m2 in January and 40 w/m2 in August, lowering the temperature by 1 °C in January and 0.5 °C in August on average, decreased WS by ∼0.1 m/s, and reduced PBL height by up to 120 m in both months, while slightly increased RH (2-4%).
Wang, Pengfei, "Understanding Air Pollutants and Meteorology Interactions Using Chemical Transport Models" (2020). LSU Doctoral Dissertations. 5267.
Available for download on Tuesday, May 18, 2021