Top-down estimate of black carbon emissions for city clusters using ground observations: A case study in southern Jiangsu, China

Date: 

Thursday, October 25, 2018, 3:30pm to 4:45pm

Location: 

Pierce Hall 100F, 29 Oxford St., Cambridge, MA

Speaker: ZHAO Yu

ZHAO Yu, Professor, School of the Environment, Nanjing University; Postdoctoral Fellow Alumnus and Collaborator, Harvard-China Project

Abstract: 

Black carbon (BC) is an important component of atmospheric particulate matter and is emitted directly into the atmosphere from incomplete combustion associated with anthropogenic activities and biomass burning. BC has adverse effects on public health by absorbing harmful volatile organic compounds, and contributes to global warming by intercepting and absorbing sunlight. Due to lack of sufficient understanding of major emission sources, the impact of BC on regional climate has not been fully quantified by models. We combined a chemistry transport model (CTM), a multiple regression model and available ground observations, to derive top-down estimates of BC emissions and to reduce deviations between simulations and observations for a southern Jiangsu city cluster, a typical developed and polluted region in eastern China. The effects of number and spatial representativeness of observation sites on top-down estimate were further quantified. Sensitivity analysis proved the rationality of near linearity assumption between emissions and concentrations, and the impact of wet deposition on the multiple regression model was demonstrated to be moderate through data screening based on simulated wet deposition and satellite-derived precipitation.

Sponsored by China Project, Harvard Paulson School of Engineering and Applied Sciences.