[A-AS05] [EE] Contributions of local and long-range transport to air pollutants in mega-cities

[AAS05-06] Development of a high-resolution emission inventory and its evaluation and application through air quality modeling for Jiangsu China

★Invited papers

*Yu Zhao¹, Yaduan Zhou¹, Jie Zhang², Yang Yang¹ (1.School of the Environment, Nanjing University, 2.Jiangsu Provincial Academy of Environmental Science)

Keywords:emission inventory, air quality modeling, China

Improved emission inventories combining detailed source information are crucial for better understanding the atmospheric chemistry and effectively making emission control policies using air quality simulation, particularly at regional or local scales. With the downscaled inventories directly applied, chemical transport model might not be able to reproduce the authentic evolution of atmospheric pollution processes at small spatial scales. Using the bottom-up approach, a high-resolution emission inventory was developed for Jiangsu China, including SO₂, NOx, CO, NH₃, volatile organic compounds (VOCs), total suspended particulates (TSP), PM₁₀, PM_2.5, black carbon (BC), organic carbon (OC), and CO₂. The key parameters relevant to emission estimation for over 6000 industrial sources were investigated, compiled and revised at plant level based on various data sources and on-site survey. As a result, the emission fractions of point sources were significantly elevated for most species. The improvement of this provincial inventory was evaluated through comparisons with other inventories at larger spatial scales, using satellite observation and air quality modeling. Compared to the downscaled Multi-resolution Emission Inventory for China (MEIC), the spatial distribution of NO_X emissions in our provincial inventory was more consistent with summer tropospheric NO₂ VCDs observed from OMI, particularly for the grids with moderate emission levels, implying the improved emission estimation for small and medium industrial plants by this work. Three inventories (national, regional, and provincial by this work) were applied in the Models-3/Community Multi-scale Air Quality (CMAQ) system for southern Jiangsu October 2012, to evaluate the model performances with different emission inputs. The best agreement between available ground observation and simulation was found when the provincial inventory was applied, indicated by the smallest normalized mean bias (NMB) and normalized mean errors (NME) for all the concerned species SO₂, NO₂, O₃ and PM_2.5. The result thus implied the advantage of improved emission inventory at local scale for high resolution air quality modeling. Under the unfavorable meteorology in which horizontal and vertical movement of atmosphere was limited, the simulated SO₂ concentrations at downtown Nanjing (the capital city of Jiangsu) using the regional or national inventories were much higher than observation, implying the overestimated urban emissions when economy or population densities were applied to downscale or allocate the emissions. This case also stressed the importance of city-scale emission inventory when local sources dominated the pollution for mega cities. With more accurate spatial distribution of emissions at city level, the simulated concentrations using the provincial inventory were much closer to observation. Sensitivity analysis of PM_2.5 and O₃ formation was conducted using the improved provincial inventory through the Brute Force method. Iron & steel and cement plants were identified as important contributors to the PM_2.5 concentrations in Nanjing. The O₃ formation was VOCs-limited in southern Jiangsu, and the concentrations were negatively correlated with NO_X emissions in urban areas owing to the accumulated NOx from transportation. The sensitivity analysis also indicated that regional transport might contribute significantly to suburban O₃ levels. More evaluations are further suggested for the impacts of speciation and temporal and vertical distribution of emissions on air quality modeling at regional or local scales in China.