Carbonyl emissions from heavy-duty diesel vehicle exhaust in China and the contribution to ozone formation potential

Fifteen heavy-duty diesel vehicles were tested on chassis dynamometer by using typical heavy duty driving cycle and fuel economy cycle. The air from the exhaust was sampled by 2,4- dinitrophenyhydrazine cartridge and 23 carbonyl compounds were analyzed by high performance liquid chromatography. The average emission factor of carbonyls was 97.2 mg/km, higher than that of light-duty diesel vehicles and gasoline-powered vehicles. Formaldehyde, acetaldehyde, acetone and propionaidehyde were the species with the highest emission factors. Main influencing factors for carbonyl emissions were vehicle type, average speed and regulated emission standard, and the impact of vehicle loading was not evident in this study. National emission of carbonyls from diesel vehicles exhaust was calculated for China, 2011, based on both vehicle miles traveled and fuel consumption. Carbonyl emission of diesel vehicle was estimated to be 45.8 Gg, and was comparable to gasolinepowered vehicles （58.4 Gg）. The emissions of formaldehyde, acetaldehyde and acetone were 12.6, 6.9, 3.8 Gg, respectively. The ozone formation potential of carbonyls from diesel vehicles exhaust was 537 mg O3/km, higher than 497 mg O3/km of none-methane hydrocarbons emitted from diesel vehicles.     

Development of database of real-world diesel vehicle emission factors for China

A database of real-world diesel vehicle emission factors, based on type and technology, has been developed following tests on more than 300 diesel vehicles in China using a portable emission measurement system. The database provides better understanding of diesel vehicle emissions under actual driving conditions. We found that although new regulations have reduced real-world emission levels of diesel trucks and buses significantly for most pollutants in China,NO_x emissions have been inadequately controlled by the current standards, especially for diesel buses, because of bad driving conditions in the real world. We also compared the emission factors in the database with those calculated by emission factor models and used in inventory studies. The emission factors derived from COPERT (Computer Programmer to calculate Emissions from Road Transport) and MOBILE may both underestimate real emission factors, whereas the updated COPERT and PART5 (Highway Vehicle Particulate Emission Modeling Software) models may overestimate emission factors in China. Real-world measurement results and emission factors used in recent emission inventory studies are inconsistent, which has led to inaccurate estimates of emissions from diesel trucks and buses over recent years. This suggests that emission factors derived from European or US-basedmodels will not truly represent real-world emissions in China. Therefore, it is useful and necessary to conduct systematic real-world measurements of vehicle emissions in China in order to obtain the optimum inputs for emission inventory models.     

Do vehicular emissions dominate the source of C6–C8 aromatics in the megacity Shanghai of eastern China?

The characteristic ratios of volatile organic compounds(VOCs) to i-pentane, the indicator of vehicular emissions, were employed to apportion the vehicular and non-vehicular contributions to reactive species in urban Shanghai. Two kinds of tunnel experiments, one tunnel with more than 90% light duty gasoline vehicles and the other with more than 60% light duty diesel vehicles, were carried out to study the characteristic ratios of vehicle-related emissions from December 2009 to January 2010. Based on the experiments, the characteristic ratios of C6–C8aromatics to i-pentane of vehicular emissions were 0.53 ± 0.08(benzene), 0.70 ± 0.12(toluene),0.41 ± 0.09(m,p-xylenes), 0.16 ± 0.04(o-xylene), 0.023 ± 0.011(styrene), and 0.15 ± 0.02(ethylbenzene), respectively. The source apportionment results showed that around 23.3% of C6–C8 aromatics in urban Shanghai were from vehicular emissions, which meant that the non-vehicular emissions had more importance. These findings suggested that emission control of non-vehicular sources, i.e. industrial emissions, should also receive attention in addition to the control of vehicle-related emissions in Shanghai. The chemical removal of VOCs during the transport from emissions to the receptor site had a large impact on the apportionment results. Generally, the overestimation of vehicular contributions would occur when the VOC reaction rate constant with OH radicals(k OH) was larger than that of the vehicular indicator, while for species with smaller k OH than the vehicular indicator, the vehicular contribution would be underestimated by the method of characteristic ratios.     

Dovehicular emissions dominate the source of C6-C8aromatics in the megacity Shanghai of eastern China?

The characteristic ratios of volatile organic compounds (VOCs) to i-pentane, the indicator of vehicular emissions, were employed to apportion the vehicular and non-vehicular contributions to reactive species in urban Shanghai. Two kinds of tunnel experiments, one tunnelwith more than 90% light duty gasoline vehicles and the otherwithmore than 60% light duty diesel vehicles, were carried out to study the characteristic ratios of vehicle-related emissions from December 2009 to January 2010. Based on the experiments, the characteristic ratios of C6-C8 aromatics to i-pentane of vehicular emissions were 0.53 ± 0.08 (benzene), 0.70 ± 0.12 (toluene), 0.41 ± 0.09 (m,p-xylenes), 0.16 ± 0.04 (o-xylene), 0.023 ± 0.011 (styrene), and 0.15 ± 0.02 (ethylbenzene), respectively. The source apportionment results showed that around 23.3% of C6-C8 aromatics in urban Shanghai were from vehicular emissions, which meant that the non-vehicular emissions had more importance. These findings suggested that emission control of non-vehicular sources, i.e. industrial emissions, should also receive attention in addition to the control of vehicle-related emissions in Shanghai. The chemical removal of VOCs during the transport from emissions to the receptor site had a large impact on the apportionment results. Generally, the overestimation of vehicular contributions would occur when the VOC reaction rate constant with OH radicals (k_OH) was larger than that of the vehicular indicator, while for species with smaller kOH than the vehicular indicator, the vehicular contribution would be underestimated by the method of characteristic ratios.     

Regulated emission characteristics of in-use LNG and diesel semi-trailer towing vehicles under real driving conditions using PEMS

On-road driving emissions of six liquefied natural gas(LNG) and diesel semi-trailer towing vehicles(STTVs) which met China Emission Standard IV and V were tested using Portable Emission Measurement System(PEMS) in northern China.Emission characteristics of these vehicles under real driving conditions were analyzed and proved that on-road emissions of heavy-duty vehicles(HDVs) were underestimated in the past.There were large differences among LNG and diesel vehicles, which also existed between China V vehicles and China IV vehicles.Emission factors showed the highest level under real driving conditions, which probably be caused by frequent acceleration, deceleration, and start-stop.NOx emission factors ranged from 2.855 to 20.939 g/km based on distance-traveled and 6.719–90.557 g/kg based on fuel consumption during whole tests, which were much higher than previous researches on chassis dynamometer.It was inferred from tests that the fuel consumption rate of the test vehicles had a strong correlation with NOx emission, and the exhaust temperature also affected the efficiency of Selected Catalytic Reduction(SCR) aftertreatment system, thus changing the NOx emission greatly.THC emission factors of LNG vehicles were 2.012–10.636 g/km, which were much higher than that of diesel vehicles(0.029–0.185 g/km).Unburned CH_4 may be an important reason for this phenomenon.Further on-road emission tests, especially CH_4 emission test should be carried out in subsequent research.In addition, the Particulate Number(PN) emission factors of diesel vehicles were at a very high level during whole tests, and Diesel Particulate Filter(DPF)should be installed to reduce PN emission.     

On-road emissions of CO, CO2 and NOX from four wheeler and emission estimates for Delhi

This study presents the emission factor of gaseous pollutants(CO, CO_2, and NO X) from on-road tailpipe measurement of 14 passenger cars of different types of fuel and vintage. The trolley equipped with stainless steel duct, vane probe velocity meter, flue gas analyzer, Nondispersive infra red(NDIR) CO_2 analyzer, temperature, and relative humidity(RH) sensors was connected to the vehicle using a towing system. Lower CO and higher NO X emissions were observed from new diesel cars(post 2010) compared to old cars(post 2005), which implied that new technological advancement in diesel fueled passenger cars to reduce CO emission is a successful venture,however, the use of turbo charger in diesel cars to achieve high temperature combustion might have resulted in increased NO X emissions. Based on the measured emission factors(g/kg), and fuel consumption(kg), the average and 95% confidence interval(CI) bound estimates of CO, CO_2,and NO X from four wheeler(4W) in Delhi for the year 2012 were 15.7(1.4–37.1), 6234(386–12,252),and 30.4(0.0–103) Gg/year, respectively. The contribution of diesel, gasoline and compressed natural gas(CNG) to total CO, CO_2 and NO X emissions were 7:84:9, 50:48:2 and 58:41:1respectively. The present work indicated that the age and the maintenance of vehicle both are important factors in emission assessment therefore, more systematic repetitive measurements covering wide range of vehicles of different age groups, engine capacity, and maintenance level is needed for refining the emission factors with CI.     

Dynamics of major air pollutants from crop residue burning in mainland China, 2000–2014

Based on satellite image data and China's Statistical Yearbooks(2000 to 2014), we estimated the total mass of crop residue burned, and the proportion of residue burned in the field vs.indoors as domestic fuel. The total emissions of various pollutants from the burning of crop residue were estimated for 2000-2014 using the emission factor method. The results indicate that the total amount of crop residue and average burned mass were 8690.9 Tg and4914.6 Tg, respectively. The total amount of emitted pollutants including CO_2, CO, NOx,VOCs, PM_(2.5), OC(organic carbon), EC(element carbon) and TC(total carbon) were 4212.4–8440.9 Tg, 192.8–579.4 Tg, 4.8–19.4 Tg, 18.6–61.3 Tg, 18.8–49.7 Tg, 6.7–31.3 Tg, 2.3–4.7 Tg, and8.5–34.1 Tg, respectively. The emissions of pollutants released from crop residue burning were found to be spatially variable, with the burning of crop residue mainly occurring in Northeast, North and South China. In addition, pollutant emissions per unit area(10 km ×10 km) were mostly concentrated in the central and eastern regions of China. Emissions of CO_2, NOx, VOCs, OC and TC were mainly from rice straw burning, while burning of corn and wheat residues contributed most to emissions of CO, PM_(2.5) and EC. The increased ratio of PM_(2.5) emissions from crop residue burning to the total emitted from industry during the study period is attributed to the implementation of strict emissions management policies in Chinese industry. This study also provides baseline data for assessment of the regional atmospheric environment.     

Evaluation of the International Vehicle Emission （IVE） model with on-road remote sensing measurements

Intemational Vehicle Emissions （IVE） model funded by U.S. Environmental Protection Agency （USEPA） is designed to estimate emissions from motor vehicles in developing countries. In this study, the IVE model was evaluated by utilizing a dataset available from the remote sensing measurements on a large number of vehicles at five different sites in Hangzhou, China, in 2004 and 2005. Average fuel-based emission factors derived from the remote sensing measurements were compared with corresponding emission factors derived from IVE calculations for urban, hot stabilized condition. The results show a good agreement between the two methods for gasoline passenger cars＇ HC emission for all 1VE subsectors and technology classes. In the case of CO emissions, the modeled results were reasonably good, although systematically underestimate the emissions by almost 12%-50% for different technology classes. However, the model totally overestimated NOx emissions. The IVE NOx emission factors were 1.5-3.5 times of the remote sensing measured ones. The IVE model was also evaluated for light duty gasoline truck, heavy duty gasoline vehicles and motor cycles. A notable result was observed that the decrease in emissions from technology class State II to State I were overestimated by the IVE model compared to remote sensing measurements for all the three pollutants. Finally, in order to improve emission estimation, the adjusted base emission factors from local studies are strongly recommended to be used in the IVE model.     

Recent development of a refined multiple air pollutant emission inventory of vehicles in the Central Plains of China

Central Plains region of China,represented by Henan Province,is facing serious air pollution problems.Vehicular exhaust emissions had adverse impacts on the atmospheric environment.The first comprehensive and novel vehicle emission inventory for Henan Province using vehicle kilometers traveled,localized emission factors,and activity data at city-level was developed.Furthermore,3 km×3 km gridded emission and temporal variations were determined by using localized information.Results show that the total emissions of sulfur dioxide(SO_2),nitrogen oxides(NOx),carbon monoxide(CO),particular matter with aerodynamic diameter10μm(PM_(10)),aerodynamic diameter2.5μm(PM_(2.5)),volatile organic compounds(VOCs),VOCs-evaporation and ammonia in 2015 were 9.1,533.4,1190.7,23.7,21.6,150.8,31.5 and 10.4 Gg,respectively,and the emission intensities of the above pollutants were 0.05,2.7,6.0,0.1,0.1,0.8,0.2 and 0.05 g/km,respectively.Vehicles meeting the Primary China 1,China 3 and China 4 contributed 89.1%,82.7%,75.3%,75.5%,75.5%,68.2%,68.4%and 82.3%for SO_2,NO_x,CO,PM_(10),PM_(2.5),VOCs,VOCs-evaporation and ammonia emissions,respectively.Zhengzhou,Zhoukou,Nanyang,Luoyang,Shangqiu and Xinyang showed relatively higher emissions and contributed more than 50%of each pollutant.The spatial distribution indicated obvious characteristics of the road network,and high-level emission was concentrated in the downtown areas.Additionally,the ozone formation potential(OFP)based on the estimated speciated VOC emissions was 569.6 Gg in Henan Province.Aliphatic and aromatic hydrocarbons were the main species of VOCs,whereas olefins contributed the largest proportion of OFP,with 42.2%.     

Local PM10 and PM2.5 emission inventories from agricultural tillage and harvest in northeastern China

Mineral particles or particulate matters(PMs) emitted during agricultural activities are major recurring sources of atmospheric aerosol loading.However,precise PM inventory from agricultural tillage and harvest in agricultural regions is challenged by infrequent local emission factor(EF) measurements.To understand PM emissions from these practices in northeastern China,we measured EFs of PM_(10) and PM_(2.5) from three field operations(i.e.,tilling,planting and harvesting) in major crop production(i.e.,corn and soybean),using portable real-time PM analyzers and weather station data.County-level PM_(10) and PM_(2.5) emissions from agricultural tillage and harvest were estimated,based on local EFs,crop areas and crop calendars.The EFs averaged(107 ± 27),(17 ± 5) and 26 mg/m~2 for field tilling,planting and harvesting under relatively dry conditions(i.e.,soil moisture 15%),respectively.The EFs of PM from field tillage and planting operations were negatively affected by topsoil moisture.The magnitude of PM_(10) and PM_(2.5) emissions from these three activities were estimated to be 35.1 and 9.8 kilotons/yr in northeastern China,respectively,of which Heilongjiang Province accounted for approximately45%.Spatiotemporal distribution showed that most PM_(10) emission occurred in April,May and October and were concentrated in the central regions of the northeastern plain,which is dominated by dryland crops.Further work is needed to estimate the contribution of agricultural dust emissions to regional air quality in northeastern China.     

成都市道路移动源排放清单与空间分布特征

以成都市为例开展了路网、交通流、道路行驶工况和机动车保有量等数据的收集工作,运用自下而上的方法,基于实测校正和本地化的IVE模型计算了不同区域机动车在高速路、主干道、次干道和支路的排放因子,应用GIS技术建立了1 km×1 km的成都市高时空分辨率道路移动源排放清单.结果表明,2016年成都市道路移动源CO、VOCs、NO_x、SO_2、PM_(10)和NH_3排放量分别为4.2×10~5、4.5×10~4、7.2×10~4、0.4×10~3、1.1×10~4和6.2×10~3t.CO排放主要贡献车型为小型客车、中型客车和大型客车,VOCs排放主要源于小型客车和摩托车,NOx和SO2排放主要产生于小型客车和重型货车,PM10排放主要贡献车型为重型货车,NH3排放主要由小型客车贡献.污染物排放量空间分布呈现出由城市中心向卫星城市、远郊区递减趋势,中心城区和二圈层区域路网密集,排放呈片状分布,三圈层则呈带状分布.排放清单机动车技术分布数据可靠性较高,而交通流数据和排放因子存在一定不确定性.     

河南省2016~2019年机动车大气污染物排放清单及特征

基于城市机动车保有量和高速公路交通流量,结合行驶里程和VOCs源谱,采用排放因子法建立了河南省2016~2019年城市和2016年高速公路机动车高分辨率大气污染物排放清单.结果表明,2016年小型客车和普通摩托车等汽油车是CO、VOCs和NH₃的主要贡献源,SO₂、NO_x和PM主要来自重型和轻型柴油货车,国1、国3和国4标准车对污染物排放贡献突出,郑州、周口和南阳的排放量较大;高速公路8~10月的车流量较高,11月最低,城市主干道周变化和日变化分别呈现出明显的周末效应和双峰特征;排放高值区集中在交通网密集、交通流量大的城市中心及市区附近向外辐射的道路上,连霍高速和京港澳高速是高排放道路;轻型汽油车对臭氧生成潜势（OFP）贡献最大,乙烯和丙烯等5个物种对VOCs排放量和OFP贡献均较大;2016~2019年机动车保有量年均增长率为5.7%;与2016年相比,2019年VOCs排放增加2.8%,SO₂、PM_2.5、PM₁₀、NH₃、CO和NO_x的降幅分别为76.3%、51.7%、50.3%、43.1%、16.7%和5.9%;2019年各污染物在控制政策下的实际排放量相对基准情景的减排比例在15.6%~82.4%之间.     

基于交通流的成都市高分辨率机动车排放清单建立

提出一种基于交通流监测数据的道路机动车高分辨率排放清单建立方法,对成都市道路交通流特征进行分析并建立了成都市机动车尾气高分辨率排放清单.结果表明,成都市道路车流量及排放均呈现明显的"双峰"分布,早晚高峰时段机动车通行量占全天的39.85%,车队结构中排放标准以国Ⅳ车为主,车辆类型以小型车为主,燃料类型以汽油车为主;道路机动车SO_2、NO_x、CO、PM_(10)、PM_(2.5)、BC、OC和VOCs(不含驻车蒸发)日排放量分别为3.89、 162.08、 324.11、 4.79、 4.36、 1.89、 0.78和44.37 t,空间分布整体呈现从城市中心到外围排放强度逐渐降低趋势,时间分布基本呈现"双峰"分布,颗粒物相关指标受货车流量影响较大; NO_x、PM_(10)、PM_(2.5)、BC和OC主要来源为大型柴油车,CO主要来源为小型汽油车,其中大型车对NO_x的贡献率达80%;基于保有量的计算方法对成都市道路机动车污染物排放存在一定高估,高估比例在1%～30%.     

中国国道和省道机动车尾气排放特征

近年来,随着我国机动车保有量的持续增长,机动车排放已成为我国重要的大气污染物来源之一.现有的机动车排放研究多关注城市内的机动车大气污染物排放,针对城市间的大气污染物排放研究较少.我国城市间交通道路主要包括国道和省道,截止至2015年我国国道里程18.53万km、省道里程32.97万km,约占全国等级公路总里程的13%,因此开展我国国道和省道机动车大气污染物排放研究十分重要.本研究基于全国国道和省道交通监测站的年均监测数据,采用环境保护部发布的《道路机动车大气污染物排放清单编制技术指南(试行)》中的指导方法,计算了2015年我国国道和省道机动车的大气污染物排放清单,分析了污染物排放的时空分布特征.结果表明,我国国道和省道公路机动车排放的一氧化碳(CO)、氮氧化物(NO_x)、颗粒物(PM)和碳氢化合物(HC)排放量分别占全国机动车污染物总排放量的4.5%、27.9%、14.4%和7.7%;不同车型对国道和省道机动车大气污染物排放的分担率不同,其中大货车是NO_x、PM_(10)、PM_(2.5)的主要来源,摩托车是CO和HC的主要来源;不同道路类型中各车型的大气污染物排放分担率也不同,如高速路上大货车是NO_x、PM_(10)和PM_(2.5)的主要来源,普通道路上大客车和大货车是NO_x、PM_(10)和PM_(2.5)的主要来源.     

海峡西岸地区人为源大气污染物排放特征研究

采用以"自下而上"为主的方法建立了2007年海峡西岸地区的人为源大气污染物排放清单.计算结果显示,海西地区人为源SO2、NOx、CO、PM10、PM2.5、VOCs和NH3排放总量分别为69.5×104、96.1×104、413.1×104、93.9×104、40.6×104、85.0×104和28.5×104t.电厂和工业燃烧设施分别占SO2排放的48%和39%,以及NOx排放的51%和25%.水泥、砖瓦等制造过程贡献了约51%的PM10排放和36%的PM2.5排放.秸秆燃烧、加油站和涂料等VOCs面源分别占到其排放总量的27%、15%和4%.NH3的主要排放源为畜禽养殖和氮肥施用等农业部门,占到总排放量的89%.海西地区的单位面积大气污染物排放量仅相当于长三角地区的25%左右,略高于全国平均水平.该地区人为源和天然源VOCs排放比重分别占56%和44%,人为源VOCs排放比重低于全国大部分地区.海西大气污染高排放地区主要集中在沿海一带,以泉州、潮汕、福州和温州等地区为主,建议"十二五"发展过程中,重点关注上述高排放地区,限制重点排放源的发展,开发低耗能、低污染的发展模式.     

长沙市人为源大气污染物排放清单及特征研究

根据收集的长沙市人为源活动水平数据,建立了该地区2014年1 km×1 km人为源大气污染物排放清单.结果显示,2014年长沙市SO_2、NO_x、CO、PM_(10)、PM_(2.5)、BC、OC、VOCs和NH_3排放总量分别为53.5×10~3、78.3×10~3、284.6×10~3、102.3×10~3、42.1×10~3、4.0×10~3、7.2×10~3、64.2×10~3、27.1×10~3t.化石燃料固定燃烧源为最大的SO_2排放贡献源,道路移动源是主要的NO_x贡献源,CO排放主要来自化石燃料固定燃烧源和道路移动源,长沙市VOCs的最大贡献源是溶剂使用源,PM_(10)、PM_(2.5)最主要的排放源是扬尘源,BC最大的排放贡献源为化石燃料固定燃烧源,生物质燃烧源是最大的OC贡献源,NH_3排放主要来源于畜禽养殖和农业施肥.空间分布结果显示,长沙市NH_3的排放在宁乡县、望城区、长沙县、浏阳市分布较多,主要呈现片状分布.其他污染物排放高值区则主要分布在中心城区、工业区及道路分布区域.     

City-specific vehicle emission control strategies to achieve stringent emission reduction targets in China''s Yangtze River Delta region

The Yangtze River Delta (YRD) region is one of the most prosperous and densely populated regions in China and is facing tremendous pressure to mitigate vehicle emissions and improve air quality. Our assessment has revealed that mitigating vehicle emissions of NOx would be more difficult than reducing the emissions of other major vehicular pollutants (e.g., CO, HC and PM_2.5) in the YRD region. Even in Shanghai, where the emission control implemented are more stringent than in Jiangsu and Zhejiang, we observed little to no reduction in NOx emissions from 2000 to 2010. Emission–reduction targets for HC, NOx and PM_2.5 are determined using a response surface modeling tool for better air quality. We design city-specific emission control strategies for three vehicle-populated cities in the YRD region: Shanghai and Nanjing and Wuxi in Jiangsu. Our results indicate that even if stringent emission control consisting of the Euro 6/VI standards, the limitation of vehicle population and usage, and the scrappage of older vehicles is applied, Nanjing and Wuxi will not be able to meet the NOx emissions target by 2020. Therefore, additional control measures are proposed for Nanjing and Wuxi to further mitigate NOx emissions from heavy-duty diesel vehicles.     

珠江三角洲机动车挥发性有机物排放化学成分谱研究

根据珠三角地区机动车挥发性有机物排放(VOCs)贡献特征,选取在用轻型汽油车、轻型柴油车、液化石油气(LPG)出租车和摩托车,采用底盘测功机及实际道路测试,获取了以上车型尾气排放的VOCs化学成分(59种非甲烷碳氢化合物)特征谱.轻型汽油车以及摩托车的尾气组成中芳香烃含量最高,其次为烷烃;苯系物、异戊烷以及乙烯占轻型汽油车尾气VOCs组成的54.5%;苯系物、异戊烷以及乙炔占摩托车尾气组成的54.6%.轻型柴油车的尾气组成中烷烃比例最高,其次是芳香烃和烯炔烃.除了苯和甲苯,正十一烷、正十二烷、正癸烷、乙烯、丙烯、1-丁烯亦在柴油车尾气中占有重要比例(41.2%).LPG出租车尾气组成以丙烷、正丁烷、异丁烷为主,并伴有较高比例的1,2,4-三甲基苯、1,2,3-三甲基苯和甲苯.与类似研究比较结果表明:由于在油品、排放标准及采样与分析方法等方面的差异,机动车排放源成分谱相关研究结果仍存在一定的差异性,建议对机动车成分谱研究在尾气采样与分析方法等方面进行规范化和标准化.     

西宁市生物质燃烧源大气污染物排放清单

本研究根据调查的西宁市生物质燃烧源活动水平数据,采用排放因子方法,建立了 2018年西宁市生物质燃烧源9种大气污染物的排放清单,并分析了清单的时空分布特征和不确定性.结果表明,西宁市2018年生物质燃烧源CO、NOx、SO2、NH3、VOCs、PM2.5、PM10、BC 和OC 的排放量分别为 11 718.34、604.41、167.80、209.72、1 617.97、2 054.04、2 135.04、281.07和 1 224.78 t.秸秆露天焚烧 CO、NOx、VOCs、PM2.5、PM10、BC 和OC 的排放对生物质燃烧源的排放贡献率最高;其中,秸秆露天焚烧NOx、VOCs和CO的贡献率分别为72.35％、63.94％和53.18％.户用生物质炉NH3和SO2的排放对生物质燃烧源的贡献率最大,分别为41.49％和42.05％.生物质燃烧源大气污染物排放地区分布不均衡,主要集中于大通县和湟中区.生物质燃烧源9项污染物的排放量在1、2、3、10、11和12月较大,占比在5％～33％.蒙特卡罗模拟结果表明,在95％置信区间下,不确定度最高的是森林和草原火灾的PM2.5排放,不确定度为-26.71％～29.78％.