Development a detailed inventory framework for estimating major pollutants emissions inventory for Yunnan Province, China

Tang, Xiaolong; Zhang, Yan; Yi, Honghong; Ma, Jieyun; Li, Pu

doi:10.1016/j.atmosenv.2012.04.018

Cited by 16 publications

(6 citation statements)

References 24 publications

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“…The point sources including power and industrial plants contributed 84%, 71%, 55%, 83%, 75%, 64%, 41%, 31%, 83%, 2% and 36%, to the total emissions of SO 2 , NOx, CO, TSP, PM 10 , PM 2.5 , BC, OC, CO 2 , NH 3 and VOCs, respectively. The emission fractions of point sources were notably larger than those in other regional inventories (Fu, 2009;Tang et al, 2012;B. Zhao et al, 2012), resulting mainly from the compiling and application of information on individual power and industrial plants from varied data sources.…”

Section: Emission Estimation and Sector Contributionmentioning

confidence: 82%

Development of a high-resolution emission inventory and its evaluation through air quality modeling for Jiangsu Province, China

Zhou

Zhao

Mao

et al. 2016

Preprint

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Abstract. 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 (CTM) might not be able to well reproduce the evolution of atmospheric pollution process 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, PM2.5, 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 NOx 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, 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 PM2.5. The result thus implied the advantage of improved emission inventory at local scale for high resolution air quality modeling. Under the unfavorable meteorology for pollution transport, in particular, much higher SO2 concentrations than observation were simulated for downtown Nanjing (the capital city of Jiangsu) using the regional or national inventories, implying the overestimation in urban emissions when the locations of large emitters were not fully considered, and the densities of economy or population were simply applied to downscale or allocate the emissions. 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 PM2.5 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 PM2.5 concentrations in Nanjing (the capital city of Jiangsu). The O3 formation was VOCs-limited in southern Jiangsu, and the concentrations were negatively correlated with NOx emissions in urban areas owing to the accumulated NOx from transportation. 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.

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Section: Emission Estimation and Sector Contributionmentioning

confidence: 82%

Development of a high-resolution emission inventory and its evaluation through air quality modeling for Jiangsu Province, China

Zhou

Zhao

Mao

et al. 2016

Preprint

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“…Unit capacity of coal-fired plants was 696 GW in 2011 with a growth ratio of 96% compared with 2005 (CEC, 2012b).Coal-fired power plants have been considered as one of the major emission sources of regional atmospheric haze and acid rain (Li et al, 2011;Nicks et al, 2003;Tang et al, 2012;Wang et al, 2005;Zheng et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

Unit-based emission inventory and uncertainty assessment of coal-fired power plants

Sun

Zhang

et al. 2014

Atmospheric Environment

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“…Some emission inventories of primary air pollutants for China treat the iron and steel industry as a part of the industrial sector, roughly estimating its emissions based on coal and oil consumption (Streets et al, 2003;Ohara et al, 2007). Some emission inventories estimate the emissions of the regional iron and steel industry (Zheng et al, 2009;Tang et al, 2012); some take processes into account, such as the Huabei region emission inventory (Zhao et al, 2012) and national key iron and steel plants emission inventory (Lei et al, 2008). Moreover, there have been many studies measuring or investigating the emissions of iron and steel equipment, including SO 2 , NO x , PM, VOCs, PCDD/Fs (Gong et al, 2008;Lei et al, 2008;Tsai et al, 2008;Lu et al, 2009;Ma et al, 2009;Zou et al, 2012;Yang et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Primary Air Pollutant Emissions and Future Prediction of Iron and Steel Industry in China

Zhao

Zhang

et al. 2015

Aerosol Air Qual. Res.

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China is the largest iron and steel producing and consuming country in the world, which leads to enormous quantities of emitted air pollutants. Direct emissions of air pollutants from the iron and steel industry in China were estimated by developing a process and technology-based methodology using information of the proportion of pig iron, crude steel, and rolled steel produced from different processes and technology. Emissions of sulfur dioxide (SO 2 ), nitrogen oxides (NO x ), particulate matter (PM), volatile organic compound (VOCs), and dioxin (PCDD/Fs) were estimated for the year 2012, and future emissions of major pollutants (SO 2 , NO x , TSP) were projected up to 2030 based on technology developing trends and emission control policies. According to the estimation, 2222 kt of SO 2 , 937 kt of NO x , 1886 kt of TSP, 555 kt of PM 2.5 , 254 kt of VOCs, 618 g I-TEQ of PCDD/Fs was produced in China in 2012. Sintering produced 72.4% of SO 2 , 49.4% of NO x , 22.5% of TSP, 24.0% of PM 2.5 , 69.6% of VOCs and 98.0% of PCDD/Fs, which is the main emission source. Through faithful implementation of closing down outdated production and emission control policies, approximately 77%, 49%, 67% and 64% of SO 2 , NO x , TSP and PCDD/Fs emissions, respectively, could be further reduced in 2012. Emissions in 2020 and 2030 of iron and steel sectors were predicted applying scenario analysis. The removal potential for SO 2 and TSP is larger than NO x by improvement of removal facilities, and southwest, northwest, and north China has the largest SO 2 , NO x , TSP and PCDD/Fs removal potential respectively.

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Development a detailed inventory framework for estimating major pollutants emissions inventory for Yunnan Province, China

Cited by 16 publications

References 24 publications

Development of a high-resolution emission inventory and its evaluation through air quality modeling for Jiangsu Province, China

Development of a high-resolution emission inventory and its evaluation through air quality modeling for Jiangsu Province, China

Unit-based emission inventory and uncertainty assessment of coal-fired power plants

Primary Air Pollutant Emissions and Future Prediction of Iron and Steel Industry in China

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