Nonlinear and lagged effects of VOCs on SOA and O3 and multi-model validated control strategy for VOC sources

Abstract

VOCs, as the common precursor of PM2.5 and O3 pollution, has not been paid enough attention in the previous phase. How to implement scientific and effective emission reduction on VOC sources is the focus of the next step in improving the atmospheric environmental quality in China. In this study, based on observations of VOC species, PM1 components and O3, the distributed lag nonlinear model (DLNM) was used to investigate the nonlinear and lagged effects of key VOC categories on secondary organic aerosol (SOA) and O3. The control priorities of sources were determined by combining the VOC source profiles, which were afterwards verified using the source reactivity method and Weather Research and Forecasting Model-Community Multi-scale Air Quality Model (WRF-CMAQ). Finally, the optimized control strategy of VOC source was proposed. The results showed that SOA was more sensitive to benzene and toluene, and single-chain aromatics, while O3 was more sensitive to dialkenes, C2–C4 alkenes, and trimethylbenzenes. The optimized control strategy based on the total response increments (TRI) of VOC sources suggests that passenger cars, industrial protective coatings, trucks, coking, and steel making should be considered as the key sources for continuous emission reduction throughout the year in the Beijing-Tianjin-Hebei region (BTH). Non-road, oil refining, glass manufacturing and catering sources should be strengthened in summer, while biomass burning, pharmaceutical manufacturing, oil storage and transportation, and synthetic resin need more emphasis in other seasons. The multi-model validated result can provide scientific guidance for more accurate and efficient VOCs reduction.