Recent Development of the PKU-Fuel and PKU-Emission Inventory College of Urban and Environmental Sciences, Peking University, Beijing, China Speaker: Huizhong Shen

Introduction Emissions Transport RF Climate Implications Fuel Exposure Health

PKU-FUEL Fuel scale: 222 countries/regions period: 1960~2030 spatial resolution: country level temporal resolution: monthly source category: 64 scale: global period: 2002, 2007, 2008, 2011 spatial resolution: 0.1º×0.1º temporal resolution: monthly source category: 64

Global inventory of fuel combustion Spatially-resolved 0.1º×0.1º: sub-national fuel for 45 countries, especially large countries (2002, 2007, 2008, 2011) Country-level: 1960~2030 Reduce the spatial bias caused by uneven distribution of per-capita fuel consumption within countries The uneven distribution of per-capita fuel consumption within large countries confirms the spatial bias if we use simple population-based aggregation at national scale Provincial, county level, more than 8000 administrative units (Wang et al., ACP 2013)

Global inventory of fuel combustion Source information 64 source categories, 5 fuel types, 6 main sectors coal oil natural gas biomass waste Coal Oil Natural Gas Solid waste Biomass Power stations Industry Residential Agriculture Transportation Wildfires Sector Fuel 64 source categories

Global inventory of fuel combustion Temporally-resolved: monthly variation Residential sector Climate factors (Heating degree days, Cooling degree days) Socioeconomic indexes (Icap, UR, electricity price, housing unit)

Global inventory of fuel combustion Temporally-resolved: monthly variation Open fire (open straw burning, deforestation, wildfire) GFED database Transportation (in process) Other sectors (constant)

Rural residential energy consumption Fuel Rural residential energy consumption Energy structure in Chinese rural residence 50,000 questionnaires Urban Rural-Urban migrants Population flows in China Spatial reallocation of emissions Pollutants cluster at where population gather 1300 questionnaires

Small scale coke production in Shanxi Fuel Small scale coke production in Shanxi Satellite: Landsat-5 ( TM 751 )- short-wave length IR band, THERMO-SENSITIVE Data source: CEODE, USGS, CSDB, GLCF Year: 1987-2011

Small scale coking Fuel A higher resolution of beehive coking emission inventory (30m×30m) National scale

Development of emissions inventory bottom-up method Emission Activity Emission factor Technology divisions Time trends of technology divisions Time trends of EFPAHs Correlated with socioeconomic indexes Index-dependent regression models EFPAHs varied with indexes S-shaped regression model Regression

Development of emissions inventory Greenhouse gases and air pollutants CO2, PM (PM2.5, TSP, PM2.5), Black Carbon, CO, Organic Carbon, Hg, PAHs (naphthalene, acenaphthylene, acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene, pyrene, benz(a)anthracene, chrysene, benzo(b)fluoranthene, benzo(k)fluoranthen, benzo(a)pyrene, dibenz(a,h)anthracene, indeno(l,2,3-cd)pyrene, benzo(g,h,i)perylene), SO2, N2O, NH3 PKU-FUEL can be used to estimate emissions of green house gasses and air pollutants Desulfurization rate Sulfur Dioxide, Nitrous Oxide, ammonia

Development of emissions inventory Spatially resolved  2007 CO2 PM2.5 BC PAHs Hg

Development of emissions inventory Temporal trends Hg (Chen et al., EST 2014) BC (Wang et al., EST 2012) PAHs (Shen et al., EST 2013)

Thank You ! http://inventory.pku.edu.cn