Sources of humic-like substances (HULIS) in PM2.5 in Beijing: Receptor modeling approach.

Recent work has identified the presence of humic-like substances (HULIS) in ambient fine particulate matter (PM2.5) in Beijing, China and that residential coal combustion as well as biomass burning are significant contributors to its presence. These results were based on the characterization of emissions from representative stoves and modeling of the aerosol with the Community Multiscale Air Quality (CMAQ) chemical transport model. The CMAQ source apportionment estimated that residential coal and biofuel burning and secondary aerosol formation were important annual sources of ambient HULIS, contributing 47.1%, 15.1%, and 38.9%, respectively. In this study, chemical composition data including concentrations of water-soluble organic carbon and HULIS across four seasons during 2012-2013 were analyzed with positive matrix factorization (PMF) to provide a complementary source apportionment. The PMF results indicate that the identified sources were Traffic, Biomass Burning, Nitrate/Sulfate, Incineration, Sulfate, Coal Combustion/Ammonium Chloride, Residential Coal/Biofuel Combustion, and Road Dust/Soil with mass contributions (fractions) to PM2.5 of 12.35 (10.4%), 8.70 (8.9%), 24.51 (22.4%), 5.64 (7.2%), 25.14 (24.5%), 7.10 (6.2%), 14.18 (15.4%), and 5.33 µg/m3 (5.0%), respectively. The contributions to the observed HULIS concentrations were 0.63 (10.9%), 0.38 (6.4%), 0.07 (1.7%), 0.00 (0%), 1.12 (28.8%), 0.00 (0%), 1.50 (52.2%), and 0.01 µg/m3 (0.3%), respectively. These PMF modeling results were in reasonable agreement with the CMAQ values supporting the attribution of significant amounts of primary HULIS to residential coal and biofuel combustion. Currently, efforts are underway in China to replace solid fuel combustion for heating and cooking with natural gas and electricity by 2020. Thus, future studies should be able to see substantial reductions in both PM2.5 and HULIS in the near term future.

[Vehicle Exhaust Emission Characteristics and Their Contributions in Jiangsu Province].

An hourly vehicular emission inventory with 1 km×1 km resolution was developed for Jiangsu Province in 2015, using the COPERT model and ArcGIS technology. The improved "standard road length" method, as well as road network information and monthly, weekly, and daily variations of the congestion delay index were used to increase temporal-spatial resolution. The contributions of different vehicle types, emission standards, and road types to total vehicular emissions were analyzed. Results showed that vehicular emissions of NOx, HC, CO, PM2.5, SO2, OM, and BC were 490.9, 166.3, 1614.8, 16.9, 1.9, 3.6, and 6.7 thousand tons, respectively. On average, Suzhou and Xuzhou contributed 34%-45% of the total. Evaporative emissions of HC were 20.2 thousand tons, accounting for 12% of total HC emissions. Small passenger cars and motorcycles were the major HC and CO contributors, accounting for over 30% of total emissions. Heavy-duty diesel trucks contributed 36%-54% to NOx, PM2.5, SO2, OM, and BC emissions, representing much higher emissions than other vehicles. Heavy-duty and medium-duty diesel trucks in Suzhou and Xuzhou are the main sources of NOx and PM2.5emissions. China Ⅲ diesel vehicles account for the largest share (42%-55%) of NOx, PM2.5, SO2, and BC emissions. China Ⅲ heavy-duty diesel trucks and China 0 medium-duty diesel trucks are the primary and secondary contributors of NOx, PM2.5, OM, and BC emissions, with a total share of 40%-56%. China 0 motorcycles contributed about 16% to total HC and CO.