The vehicular emission trend in China was tracked for the recent period 2006–2009 based on a database of dynamic emission factors of CO, nonmethane volatile organic compounds (NMVOC), NOx, PM10, CO2, CH4, and N2O for all categories of on-road motor vehicles in China, which was developed at the provincial level using the COPERT 4 model, to account for the effects of rapid advances in engine technologies, implementation of improved emission standards, emission deterioration due to mileage, and fuel quality improvement. Results show that growth rates of CO and NMVOC emissions slowed down, but NOx and PM10emissions continued rising rapidly for the period 2006–2009. Moreover, CO2, CH4, and N2O emissions in 2009 almost doubled compared to those in 2005. Characteristics of recent spatial distribution of emissions and emission contributions by vehicle category revealed that priority of vehicular emission control should be put on the eastern and southeastern coastal provinces and northern regions, and passenger cars and motorcycles require stricter control for the reduction of CO and NMVOC emissions, while effective reduction of NOx and PM10 emissions can be achieved by better control of heavy-duty vehicles, buses and coaches, and passenger cars. Explicit provincial-level Monte Carlo uncertainty analysis, which quantified for the first time the Chinese vehicular emission uncertainties associated with both COPERT-derived and domestically measured emission factors by vehicle technology, showed that CO, NMVOC, and NOx emissions for the period 2006–2009 were calculated with the least uncertainty, followed by PM10 and CO2, despite relatively larger uncertainties in N2O and CH4 emissions. The quantified low uncertainties of emissions revealed a necessity of applying vehicle technology- and vehicle age-specific dynamic emission factors for vehicular emission estimation, and these improved methodologies are applicable for routine update and forecast of China's on-road motor vehicle emissions.

Based on the official statistics, locally measured emission factors, and the vehicular emission factor model most suitable for China, we developed a black carbon (BC) emission inventory for 2008 in China and at a spatial resolution of 0.5°×0.5°. In 2008, the total BC emissions in China were 1604.94 Gg. Industry and the residential sector were the dominant contributors, estimated at 695.03 Gg and 636.02 Gg of BC, respectively. Together, these two source types contributed 82.9% of the total emissions. Emissions from transportation were 194.63 Gg, accounting for 12.1% of the total. Since emission contributions from different sectors showed significant spatial diversity among the 31 administrative districts, we divided the districts into four categories: industry contribution district, residential contribution district, industry and residential contribution district, and transportation contribution district. As for energy consumption, coal and biofuel contributed 51.0% and 32.2%, respectively, of the total emissions. Spatially, BC emissions in China were unevenly distributed, higher in the east and lower in the west, corresponding to regional economic development and rural population density. High emission districts, covering 5.7% of the territory, contributed 41.2% of the total emissions. Shanxi, Hebei, Shandong, Henan, and Sichuan were the largest contributors to national BC emissions.

Presence of atmospheric PAHs in urban and suburban region (Beijing, China) was studied in April and July 2011. Forty-four pairs of gas and particle (TSP) phase samples were collected every six day by high volume (Hi-Vol) air samplers at four sampling sites, and determined separately by GC/MS based on USEPA Method TO-13A. Average total concentration (gas + particles) of PAHs (T-PAHs) was 135.1±49.0 ng/m3 and 181.2±40.9 ng/m3 in April and July, respectively. Gas phase PAHs (G-PAHs) was the major fraction, comprising 63–92% of T-PAHs. Lighter (2-, 3-, 4-ring) and heavier (5-,6-ring) PAHs were found predominantly in gas and particle phase, respectively. 2- to 6- ring PAHs contributed 10%, 53%, 26%, 7% and 4% of T-PAHs, respectively. Five major PAHs, naphthalene (NAP), fluorene (FLU), PHE, fluoranthene (FLA), and pyrene (PYR) contributed 70 – 90% of T-PAHs. G-PAHs increased significantly while PAHs in particle phase (P-PAHs) decreased from April to July. Volatilization from soil and more emission from power generation increase might explain the increase of G-PAHs, and the washout of P-PAHs along with particles might explain the decrease of P-PAHs. Given particulate organic carbon (OC) and elemental carbon (EC) being well correlated, P-PAHs was moderately correlated with OC and EC, suggesting that there were other mechanisms contributing to P-PAHs different from those of OC/EC. Significant correlation between P-PAHs with SO2 and NO2 suggested coal combustion and automobile exhaust to be contamination contributors.

Aiming to reduce the large uncertainties of biogenic volatile organic compounds (BVOCs) emissions estimation, the emission inventory of BVOCs in China at a high spatial and temporal resolution of 36 km × 36 km and 1 h was established using MEGANv2.1 with MM5 providing high-resolution meteorological data, based on the most detailed and latest vegetation investigations. BVOC emissions from 82 plant functional types in China were computed firstly. More local species-specific emission rates were developed combining statistical analysis and category classification, and the leaf biomass was estimated based on vegetation volume and production with biomass-apportion models. The total annual BVOC emissions in 2003 were 42.5 Tg, including isoprene 23.4 Tg, monoterpene 5.6 Tg, sesquiterpene 1.0 Tg, and other VOCs (OVOCs) 12.5 Tg. Subtropical and tropical evergreen and deciduous broadleaf shrubs, Quercus, and bamboo contributed more than 45% to the total BVOC emissions. The highest biogenic emissions were found over northeastern, southeastern, and southwestern China. Strong seasonal pattern was observed with the highest BVOC emissions in July and the lowest in January and December, with daily emission peaked at approximately 13:00 or 14:00 local time.