The burning of crop residues emits large quantities of atmospheric aerosols.Published studies have developed inventories of emissions from crop residue burning based on statistical data.In contrast,this study used sat...The burning of crop residues emits large quantities of atmospheric aerosols.Published studies have developed inventories of emissions from crop residue burning based on statistical data.In contrast,this study used satellite-retrieved land-cover data(1 km×1 km)as activity data to compile an inventory of atmospheric pollutants emitted from the burning of crop residues in China in 2015.The emissions of PM10,PM2.5,VOCs,NOx,SO2,CO,and NH3 from burning crop straw on nonirrigated farmland in China in 2015 were 610.5,598.4,584.4,230.6,35.4,3329.3,and 36.1 Gg(1 Gg=109 g),respectively;the corresponding emissions from burning paddy rice residues were 234.1,229.7,342.3,57.5,57.5,1122.1,and 21.5 Gg,respectively.The emissions from crop residue burning showed large spatial and temporal variations.The emissions of particulate matter and gaseous pollutants from crop residue burning in nonirrigated farmland were highest in east China,particularly in Shandong,Henan,Anhui,and Sichuan provinces.Emissions from burning paddy rice residue were highest in east and central China,with particularly high levels in Shandong,Jiangsu,Zhejiang,and Hunan provinces.The monthly variations in atmospheric pollutant emissions were similar among different regions,with the highest levels observed in October in north,northeast,northwest,east,and southwest China and in June and July in central and south China.The developed inventory of emissions from crop residue burning is expected to help improve air quality models by providing high-resolution spatial and temporal data.展开更多
The authors evaluated and compared the behavior of PM2.5 with respect to NOx and NH3 emission changes in high(the year 2013)and low(the year 2018)SO2 emission cases.Two groups of simulations were conducted based on an...The authors evaluated and compared the behavior of PM2.5 with respect to NOx and NH3 emission changes in high(the year 2013)and low(the year 2018)SO2 emission cases.Two groups of simulations were conducted based on anthropogenic emissions from China in 2013 and 2018,respectively.In each group of simulations,a respective 25%reduction in NOx and NH3 emissions were assumed.A sensitivity factor(β)was defined as the relative change in PM2.5 concentration due to 1%change in NOx or NH3 emissions.In the high SO2 emissions case,PM2.5 was more sensitive to NH3(0.31)emissions change than NOx(0.21).Due to the significant decrease in SO2 emissions from the high to low SO2 emissions case,the sensitivity of PM2.5 to NOx increased to 0.33,while its sensitivity to NH3 decreased to 0.22.The result implies that now and in the future,PM2.5 is/will be less sensitive to NH3 emissions change,while NOx emissions control is more effective in reducing the surface PM2.5 concentration.Seasonally,in the low SO2 emissions case,the sensitivities of PM2.5 to NOx and NH3 in winter were higher than those in summer,indicating that to dealwith severewinter hazemore attention should be paid to the emissions control of inorganic PM2.5 precursors,especially NOx.展开更多
Particle emission during manufacturing processes, whether chemical, physical or mechanical can represent a serious danger for environment and for occupational safety. Especially machining processes, particle emission ...Particle emission during manufacturing processes, whether chemical, physical or mechanical can represent a serious danger for environment and for occupational safety. Especially machining processes, particle emission could have an important impact on shop floor air quality and might jeopardise workers’ health. It is therefore important to find ways of reducing the particle emission at the source of manufacturing processes. To do so, there is a need to know the size, the quantity and the distribution of particles produced by processes currently used in industry. In this study, investigations are done to compare the particle emission (PM2.5) when polishing two granites (black and white). The black granite contained low Si concentration (about 10% Si) and the white granite contained high Si concentration (about 50% Si). Particle emission was monitored using the DustTrak II equipment with 2.5 μm impactor. The particle grain size was evaluated using X-ray diffraction techniques. Machining conditions leading to the generation of finer particles were identified.展开更多
鉴于烟台市本地化源成分谱研究缺乏的现状,以及颗粒物精细化来源解析及环境管理的需求,采用NK-ZXF颗粒物再悬浮采样器,对6家烟台市典型工业下载灰源样品进行再悬浮采样,构建6类〔燃煤电厂、供热锅炉、生物质锅炉、钢铁(烧结)行业、玻璃...鉴于烟台市本地化源成分谱研究缺乏的现状,以及颗粒物精细化来源解析及环境管理的需求,采用NK-ZXF颗粒物再悬浮采样器,对6家烟台市典型工业下载灰源样品进行再悬浮采样,构建6类〔燃煤电厂、供热锅炉、生物质锅炉、钢铁(烧结)行业、玻璃行业和垃圾处理行业〕PM2.5源成分谱,并对PM2.5源成分谱特征及其排放颗粒物携带重金属特征进行评估.结果表明:①燃煤电厂PM2.5源成分谱的标识组分包括Si、Cl^-和SO4^2-,其质量分数分别为15.2%、9.3%和7.8%;与燃煤电厂相比,供热锅炉排放的PM2.5中w(OC)偏高、w(SO4^2-)偏低;生物质锅炉排放的主要组分有K、Cl^-和OC等,其质量分数分别为7.4%、13.3%和8.6%;钢铁(烧结)行业PM2.5源成分谱中w(Ca)、w(Fe)和w(Cl^-)较高;SO4^2-和Ca为玻璃行业PM2.5源成分谱的主要组分,其质量分数分别为20.6%、8.2%;垃圾处理行业重金属质量分数最高,其主要组分为Cl^-和SO4^2-.②CD (coefficient of divergence,分歧系数)计算结果表明,各源成分谱有一定相异性(CD范围为0.53~0.70),其中生物质锅炉与垃圾处理行业PM2.5源成分谱差异(CD为0.70)最大.③各典型工业排放PM2.5所携带重金属特征显示,垃圾处理行业排放PM2.5中的重金属质量分数(2.3%)最高,燃煤电厂、供热锅炉、生物质锅炉和玻璃行业排放的重金属中Cr、Ni和Cu相对质量分数较高,钢铁行业和垃圾处理行业排放的重金属中Pb相对质量分数较高.研究显示,所构建的烟台市各典型工业排放PM2.5源成分谱特征鲜明,能够反映各行业PM2.5排放特征.展开更多
To achieve the goals of national sustainable development, the peaking control of CO2 emissions is pivotal, as well as other pollutants. In this paper, we build a Chinese inter-regional CGE model and simulate 13 polici...To achieve the goals of national sustainable development, the peaking control of CO2 emissions is pivotal, as well as other pollutants. In this paper, we build a Chinese inter-regional CGE model and simulate 13 policies and their combinations. By analyzing the energy consumptions, coal consumptions, relating emissions and their impacts on GDP, we found that with the structure adjustment policy, the proportion of coal in primary fossil fuels in 2030 will decrease from 53% to 48% and CO2 emissions will decrease by 11.3%-22.8% compared to the baseline scenario. With the energy intensity reduction policy, CO2 emissions will decrease by 33.3% in 2030 and 47.8% in 2050 than baseline scenario. Other pollutants will also be controlled as synergetic effects. In this study we also find that although the earlier the peaking time the better for emission amounts control, the economic costs can not be ignored. The GDP will decrease by 2.96%-8.23% under different scenarios. Therefore, integrated policy solutions are needed for realizing the peaks package and more targeted measures are required to achieve the peaks of other pollutants earlier.展开更多
The source apportionment of PM2.5 is essential for pollution prevention.In view of the weaknesses of individual models,we proposed an integrated chemical mass balancesource emission inventory(CMB-SEI)model to acquire ...The source apportionment of PM2.5 is essential for pollution prevention.In view of the weaknesses of individual models,we proposed an integrated chemical mass balancesource emission inventory(CMB-SEI)model to acquire more accurate results.First,the SEI of secondary component precursors(SO2,NOx,NH3,and VOCs)was compiled to acquire the emission ratios of these sources for the precursors.Then,a regular CMB simulation was executed to obtain the contributions of primary particle sources and secondary components(SO4^2-,NO3^-3,NH4^+,and SOC).Afterwards,the contributions of secondary components were apportioned into primary sources according to the source emission ratios.The final source apportionment results combined the contributions of primary sources by CMB and SEI.This integrated approach was carried out via a case study of three coastal cities(Zhoushan,Taizhou,and Wenzhou;abbreviated WZ,TZ,and ZS)in Zhejiang Province,China.The regular CMB simulation results showed that PM2.5 pollution was mainly affected by secondary components and mobile sources.The SEI results indicated that electricity,industrial production and mobile sources were the largest contributors to the emission of PM2.5 gaseous precursors.The simulation results of the CMB-SEI model showed that PM2.5 pollution in the coastal areas of Zhejiang Province presented complex pollution characteristics dominated by mobile sources,electricity production sources and industrial production sources.Compared to the results of the CMB and SEI models alone,the CMB-SEI model completely apportioned PM2.5 to primary sources and simultaneously made the results more accurate and reliable in accordance with local industrial characteristics.展开更多
基金Under the auspices of National Key R&D Program of China(No.2017YFC0212303,2017YFC0212304)Key Research Program of Frontier Sciences,Chinese Academy of Sciences(No.QYZDB-SSW-DQC045)+1 种基金National Natural Science Foundation of China(No.41775116)Youth Innovation Promotion Association of Chinese Academy of Sciences(No.2017275).
文摘The burning of crop residues emits large quantities of atmospheric aerosols.Published studies have developed inventories of emissions from crop residue burning based on statistical data.In contrast,this study used satellite-retrieved land-cover data(1 km×1 km)as activity data to compile an inventory of atmospheric pollutants emitted from the burning of crop residues in China in 2015.The emissions of PM10,PM2.5,VOCs,NOx,SO2,CO,and NH3 from burning crop straw on nonirrigated farmland in China in 2015 were 610.5,598.4,584.4,230.6,35.4,3329.3,and 36.1 Gg(1 Gg=109 g),respectively;the corresponding emissions from burning paddy rice residues were 234.1,229.7,342.3,57.5,57.5,1122.1,and 21.5 Gg,respectively.The emissions from crop residue burning showed large spatial and temporal variations.The emissions of particulate matter and gaseous pollutants from crop residue burning in nonirrigated farmland were highest in east China,particularly in Shandong,Henan,Anhui,and Sichuan provinces.Emissions from burning paddy rice residue were highest in east and central China,with particularly high levels in Shandong,Jiangsu,Zhejiang,and Hunan provinces.The monthly variations in atmospheric pollutant emissions were similar among different regions,with the highest levels observed in October in north,northeast,northwest,east,and southwest China and in June and July in central and south China.The developed inventory of emissions from crop residue burning is expected to help improve air quality models by providing high-resolution spatial and temporal data.
基金This work was supported by the National Natural Science Foundation of China[grant number 41805098].
文摘The authors evaluated and compared the behavior of PM2.5 with respect to NOx and NH3 emission changes in high(the year 2013)and low(the year 2018)SO2 emission cases.Two groups of simulations were conducted based on anthropogenic emissions from China in 2013 and 2018,respectively.In each group of simulations,a respective 25%reduction in NOx and NH3 emissions were assumed.A sensitivity factor(β)was defined as the relative change in PM2.5 concentration due to 1%change in NOx or NH3 emissions.In the high SO2 emissions case,PM2.5 was more sensitive to NH3(0.31)emissions change than NOx(0.21).Due to the significant decrease in SO2 emissions from the high to low SO2 emissions case,the sensitivity of PM2.5 to NOx increased to 0.33,while its sensitivity to NH3 decreased to 0.22.The result implies that now and in the future,PM2.5 is/will be less sensitive to NH3 emissions change,while NOx emissions control is more effective in reducing the surface PM2.5 concentration.Seasonally,in the low SO2 emissions case,the sensitivities of PM2.5 to NOx and NH3 in winter were higher than those in summer,indicating that to dealwith severewinter hazemore attention should be paid to the emissions control of inorganic PM2.5 precursors,especially NOx.
文摘Particle emission during manufacturing processes, whether chemical, physical or mechanical can represent a serious danger for environment and for occupational safety. Especially machining processes, particle emission could have an important impact on shop floor air quality and might jeopardise workers’ health. It is therefore important to find ways of reducing the particle emission at the source of manufacturing processes. To do so, there is a need to know the size, the quantity and the distribution of particles produced by processes currently used in industry. In this study, investigations are done to compare the particle emission (PM2.5) when polishing two granites (black and white). The black granite contained low Si concentration (about 10% Si) and the white granite contained high Si concentration (about 50% Si). Particle emission was monitored using the DustTrak II equipment with 2.5 μm impactor. The particle grain size was evaluated using X-ray diffraction techniques. Machining conditions leading to the generation of finer particles were identified.
文摘鉴于烟台市本地化源成分谱研究缺乏的现状,以及颗粒物精细化来源解析及环境管理的需求,采用NK-ZXF颗粒物再悬浮采样器,对6家烟台市典型工业下载灰源样品进行再悬浮采样,构建6类〔燃煤电厂、供热锅炉、生物质锅炉、钢铁(烧结)行业、玻璃行业和垃圾处理行业〕PM2.5源成分谱,并对PM2.5源成分谱特征及其排放颗粒物携带重金属特征进行评估.结果表明:①燃煤电厂PM2.5源成分谱的标识组分包括Si、Cl^-和SO4^2-,其质量分数分别为15.2%、9.3%和7.8%;与燃煤电厂相比,供热锅炉排放的PM2.5中w(OC)偏高、w(SO4^2-)偏低;生物质锅炉排放的主要组分有K、Cl^-和OC等,其质量分数分别为7.4%、13.3%和8.6%;钢铁(烧结)行业PM2.5源成分谱中w(Ca)、w(Fe)和w(Cl^-)较高;SO4^2-和Ca为玻璃行业PM2.5源成分谱的主要组分,其质量分数分别为20.6%、8.2%;垃圾处理行业重金属质量分数最高,其主要组分为Cl^-和SO4^2-.②CD (coefficient of divergence,分歧系数)计算结果表明,各源成分谱有一定相异性(CD范围为0.53~0.70),其中生物质锅炉与垃圾处理行业PM2.5源成分谱差异(CD为0.70)最大.③各典型工业排放PM2.5所携带重金属特征显示,垃圾处理行业排放PM2.5中的重金属质量分数(2.3%)最高,燃煤电厂、供热锅炉、生物质锅炉和玻璃行业排放的重金属中Cr、Ni和Cu相对质量分数较高,钢铁行业和垃圾处理行业排放的重金属中Pb相对质量分数较高.研究显示,所构建的烟台市各典型工业排放PM2.5源成分谱特征鲜明,能够反映各行业PM2.5排放特征.
基金funded by the National Natural Fund of China(71173206)the Strategic Priority Research ProgramdClimate Change:Carbon Budget and Related Issues of the Chinese Academy of Sciences(XDA05150300)
文摘To achieve the goals of national sustainable development, the peaking control of CO2 emissions is pivotal, as well as other pollutants. In this paper, we build a Chinese inter-regional CGE model and simulate 13 policies and their combinations. By analyzing the energy consumptions, coal consumptions, relating emissions and their impacts on GDP, we found that with the structure adjustment policy, the proportion of coal in primary fossil fuels in 2030 will decrease from 53% to 48% and CO2 emissions will decrease by 11.3%-22.8% compared to the baseline scenario. With the energy intensity reduction policy, CO2 emissions will decrease by 33.3% in 2030 and 47.8% in 2050 than baseline scenario. Other pollutants will also be controlled as synergetic effects. In this study we also find that although the earlier the peaking time the better for emission amounts control, the economic costs can not be ignored. The GDP will decrease by 2.96%-8.23% under different scenarios. Therefore, integrated policy solutions are needed for realizing the peaks package and more targeted measures are required to achieve the peaks of other pollutants earlier.
基金supported by the National Key Research and Development Program of China(No.2018YFC0214102)。
文摘The source apportionment of PM2.5 is essential for pollution prevention.In view of the weaknesses of individual models,we proposed an integrated chemical mass balancesource emission inventory(CMB-SEI)model to acquire more accurate results.First,the SEI of secondary component precursors(SO2,NOx,NH3,and VOCs)was compiled to acquire the emission ratios of these sources for the precursors.Then,a regular CMB simulation was executed to obtain the contributions of primary particle sources and secondary components(SO4^2-,NO3^-3,NH4^+,and SOC).Afterwards,the contributions of secondary components were apportioned into primary sources according to the source emission ratios.The final source apportionment results combined the contributions of primary sources by CMB and SEI.This integrated approach was carried out via a case study of three coastal cities(Zhoushan,Taizhou,and Wenzhou;abbreviated WZ,TZ,and ZS)in Zhejiang Province,China.The regular CMB simulation results showed that PM2.5 pollution was mainly affected by secondary components and mobile sources.The SEI results indicated that electricity,industrial production and mobile sources were the largest contributors to the emission of PM2.5 gaseous precursors.The simulation results of the CMB-SEI model showed that PM2.5 pollution in the coastal areas of Zhejiang Province presented complex pollution characteristics dominated by mobile sources,electricity production sources and industrial production sources.Compared to the results of the CMB and SEI models alone,the CMB-SEI model completely apportioned PM2.5 to primary sources and simultaneously made the results more accurate and reliable in accordance with local industrial characteristics.
