Understanding the atmospheric new particle formation (NPF) process within the global range is important for revealing the budget of atmospheric aerosols and their impacts. We investigated the seasonal characteristics of NPF in the urban environment of Beijing. Aerosol size distributions down to ∼1∼1 nm and H 2 SO 4 concentration were measured during 2018-2019.2018-2019. The observed formation rate of 1.5 nm particles (J 1.5 ) is significantly higher than those in the clean environment, e.g., Hyytiala;Hyytiala, whereas the growth rate is relatively lower. Both J 1.5 and NPF frequency in urban Beijing showed a clear seasonal variation with maxima in winter and minima in summer, while the observed growth rates were generally within the same range around the year. We show that ambient temperature is a governing factor driving the seasonal variation of J 1.5 . In contrast, the condensation sink showed no significant seasonal variation during the NPF periods and the daily maximum H 2 SO 4 concentration was slightly higher in summer than that in winter. In all four seasons, condensation of H 2 SO 4 and (H 2 SO 4 ) nn (amine) nn clusters contributes significantly to the growth rates in the sub-3 nm size range, whereas it is less important for the observed growth rates of particles above 3 nm. Therefore, other species are always needed for the growth of larger particles.

Abstract. Biomass burning injects many different gases and aerosols into the atmosphere that could have a harmful effect on air quality, climate, and human health. In this study, a comprehensive biomass burning emission inventory including domestic and in-field straw burning, firewood burning, livestock excrement burning, and forest and grassland fires is presented, which was developed for mainland China in 2012 based on county-level activity data, satellite data, and updated source-specific emission factors (EFs). The emission inventory within a 1  ×  1 km2 grid was generated using geographical information system (GIS) technology according to source-based spatial surrogates. A range of key information related to emission estimation (e.g. province-specific proportion of domestic and in-field straw burning, detailed firewood burning quantities, uneven temporal distribution coefficient) was obtained from field investigation, systematic combing of the latest research, and regression analysis of statistical data. The established emission inventory includes the major precursors of complex pollution, greenhouse gases, and heavy metal released from biomass burning. The results show that the emissions of SO2, NOx, PM10, PM2.5, NMVOC, NH3, CO, EC, OC, CO2, CH4, and Hg in 2012 are 336.8 Gg, 990.7 Gg, 3728.3 Gg, 3526.7 Gg, 3474.2 Gg, 401.2 Gg, 34 380.4 Gg, 369.7 Gg, 1189.5 Gg, 675 299.0 Gg, 2092.4 Gg, and 4.12 Mg, respectively. Domestic straw burning, in-field straw burning, and firewood burning are identified as the dominant biomass burning sources. The largest contributing source is different for various pollutants. Domestic straw burning is the largest source of biomass burning emissions for all the pollutants considered, except for NH3, EC (firewood), and NOx (in-field straw). Corn, rice, and wheat represent the major crop straws. The combined emission of these three straw types accounts for 80 % of the total straw-burned emissions for each specific pollutant mentioned in this study. As for the straw burning emission of various crops, corn straw burning has the largest contribution to all of the pollutants considered, except for CH4; rice straw burning has highest contribution to CH4 and the second largest contribution to other pollutants, except for SO2, OC, and Hg; wheat straw burning is the second largest contributor to SO2, OC, and Hg and the third largest contributor to other pollutants. Heilongjiang, Shandong, and Henan provinces located in the north-eastern and central-southern regions of China have higher emissions compared to other provinces in China. Gridded emissions, which were obtained through spatial allocation based on the gridded rural population and fire point data from emission inventories at county resolution, could better represent the actual situation. High biomass burning emissions are concentrated in the areas with more agricultural and rural activity. The months of April, May, June, and October account for 65 % of emissions from in-field crop residue burning, while, regarding EC, the emissions in January, February, October, November, and December are relatively higher than other months due to biomass domestic burning in heating season. There are regional differences in the monthly variations of emissions due to the diversity of main planted crops and climatic conditions. Furthermore, PM2.5 component results showed that OC, Cl−, EC, K+, NH4+, elemental K, and SO42− are the main PM2.5 species, accounting for 80 % of the total emissions. The species with relatively high contribution to NMVOC emission include ethylene, propylene, toluene, mp-xylene, and ethyl benzene, which are key species for the formation of secondary air pollution. The detailed biomass burning emission inventory developed by this study could provide useful information for air-quality modelling and could support the development of appropriate pollution-control strategies.

No abstract

Trade among regions or countries not only allows the exchange of goods and services but also leads to the transfer of pollution. The unequal exchange of goods and services and associated value added and pollution may be subject to environmental inequality in China given that Chinese provinces are in different development stages. By using the latest multiregional input-output tables and the sectoral air pollutant emission inventory in 2012, we traced emissions and value added along China's domestic supply chains. Here, we show that 62%-76% of the consumption-based air-pollutant emissions of richer regions (Beijing-Tianjin, East Coast and South Coast) were outsourced to other regions; however, approximately 70% of the value added triggered by these region's final consumption was retained within the region. Some provinces in western China, such as Guizhou, Ningxia, and Yunnan, not only incurred net pollution inflows but also suffered a negative balance of value added when trading with rich provinces. Addressing such inequalities could provide not only a basis for determining each province's responsibility for pollution control but also a model for other emerging economies.

No abstract