1. Multi-scale Emission Inventory of Toxic Heavy Metals (MEITHM) from Anthropogenic Activities --From Chinese City Clusters, Mainland China to the world 多尺度人为源有害重金属大气排放清单 -- 从城市群，中国大陆到全球 Hezhong Tian*, Chuanyong Zhu, and Junrui Zhou Center for Atmospheric Environment, Beijing Normal University, China *E-mail: hztian@bnu.edu.cnhztian@bnu.edu.cn Nov.18-20, 2015, Beijing 17 th GEIA Conference Influence of Urbanization on Emissions Worldwide School of Environment, Nov. 18-20, Beijing, China

2. The motivation and purposes Why should we develop and know about the emission inventory （ EI ） of  Toxic Heavy Metals （ HMs ）？ Domestic pollution control demand: Increased poisoning accidents related with heavy metals have happened in China; Arsenic （ As ） poisoning owing to coal-burning in Guizhou; Excessive Pb of Children blood nearby Lianzhou coal-fired power plant in Guangdong; Cadmium contaminated rice in Hunan province; etc. PM 2.5 health effects: mainly because toxic heavy metals are easily adsorbed on the fine PM 2.5 particles and inhaled into the depth of respiratory system. Source of Pb poisoning incident in Guangdong--- Excessive Pb of Children blood : Lianzhou Coal-fired power plants Pacyna et al., 2006 International Demand on Hg emission reduction : Minamata Convention on Mercury

3. Datasets of activity level by province and by sectors Activity level Population & Urbanization GDP and its composition Industry and Energy use Datasets of heavy metals CEFs for concerned sources Anthropogenic sources CEFs for Coal CEFs for industrial process CEFs for Other sources Proposal on control policies of heavy metals emission in China Gridded EI and Uncertainty Temporal and spatial distribution Appointment of key sources Emission inventory (EI) of 12 typical heavy metals in 1949- 2012 from anthropogenic sources in China Hg, Se, As, Cd, Pb, Cr, Sb, Ni, Mn, Co, Cu, Zn Roadmap for compiling EI of Heavy Metals in China Methodology and Data Sources

4. 4 Methodology and data source Anthropogenic activities category and classification Combustion Source Coal Combustion Power plant Industrial sector Residential sector Other sector Liquid Fuels Combustion Crude oil Fuel oil Gasoline Diesel Kerosene Biomass burning Crop residues Wood Municipal waste incineration Industrial Process Nonferrous metal smelting Copper smelting Lead smelting Zinc smelting Iron and steel manufacture Pig iron Steel Non-metallic minerals manufacturing Cement Glass Brick Phosphatic fertilizer production Lead-acid battery production, etc. Other Source Brake pad & Tire erosion

5. Methodology and Data Sources Overall: A Bottom-up emission factor methodology is used to estimate emissions of heavy metals where possible: Where ， E is the emissions of heavy metals ； A is the energy consumption and activity data of other sources ； EF is the comprehensive emission factor (CEF) ； i is the province (autonomous region or municipality) ； and j is different emission sources. Where ， E is the emissions from coal combustion ； C is the content of heavy metals in consumed raw coals of different province; A is coal consumption ； R is the release rate of different combustion devices; η PM, η SO2 and η NOx represent the averaged fraction of one heavy metal which is removed from flue gas by the conventional PM/SO 2 /NO X emission control devices, respectively; j is different emission sources; i is the province (autonomous region or municipality); k represents the type of coal as consumed. Where, EE is the emissions of heavy metals; M is MSW Incineration/Industrial production; CEF is the emission factors; EF a represents the emission level for process p in pre-1900; EF b is the best emission factor achieved in China for process p at present; s p is the shape parameter of the curve for process p; j is the emission sources; i is the province (autonomous region or municipality). Coal: Non-Coal:

6. Copper smelting for As Steel making for Zn Algorithm for determination of dynamic emission factors Determination of dynamic emission factors during the period of 1949-2012 Technological upgrade level Emission control level Economic development S shape curve equation

7. Page  7 Temporal trend of HM emissions by source categories, 1949-2012 Tian et al., ACP, 2015

8. Page  8 Hg Zn Cu Co Mn Sb Ni Cr Cd As Se Pb Geographical distribution of HMs emissions with 0.5º×0.5º gridded resolution, 2010 Tian, et al., 2012, ES&T.; Tian et al., ACP, 2015

9. Page  9 HM Emission Inventory of Chinese City Clusters -- three biggest metropolitan areas Spatial distribution of HM emissions in the City clusters regions with high resolution (9 km×9 km) Beijing-Tianjin-Hebei RegionYangtze River Delta Region Pearl River Delta Region Tian et al. Unpublished PM2.5 in 190 cities in China, 2014

10. Global Atmospheric Antimony(Sb) Emissions from Anthropogenic Activities ， 1995-2010 Tian et al., ES&T, 2014b Global Sb emissions in 2010

11. Fig. 5 Global Sb emissions by 2050 with 0.5º×0.5º gridded resolution Page  11 2010 2050 Zhou et al., Atmos. Environ., 2015 source categories continents (a) Current Legislations (CL); (b) Strengthened Control (SC); (c) Maximum Feasible Technological Reduction （ MFTR ）.

12. Page  12 Framework of Multi-scale Emission Inventory of Toxic Heavy Metals and Metalloids -----MEITHM Ongoing work : The specific online website of MEITHM database is in construction, and it will be available soon !