大气污染物排放源清单不确定性定量分析方法及案例研究

大气污染物排放源清单由于在数据收集过程中存在的不可避免的监测误差、随机误差、关键数据缺乏以及数据代表性不足等因素而具有不确定性,而排放源清单的不确定性指的是人们对排放清单的真实值缺乏认识和了解.介绍了目前大气排放源清单定量不确定性方法框架,并使用电厂NO_x在线监测数据,通过实际案例量化排放源清单中的不确定性.结果表明:即使对被认为具有较高准确性的火电厂点源排放清单,案例中NO_x的排放源清单来自随机误差的不确定性在±15%左右.对排放源清单的不确定性量化有助于决策者确定污染物排放削减目标的可达性和科学制定大气污染物控制策略,指导排放源清单的改进和数据收集工作.同时,对我国排放源清单开发中不确定性分析提出建议.      

Analysis of differences between national inventories and an Emissions Database for Global Atmospheric Research (EDGAR)

A comparison is made of national greenhouse gas inventories for the Climate Convention, (including US country study results) and an emissions database for global atmospheric research (EDGAR). The comparison pointed to some gaps in reporting and some large differences within sectors. In most cases the differences can be traced down to the use of different emission factors or the use of national statistics that differed from the internationally available ones. Comparison of inventories may stimulate the scientific exchange of data and increase the consensus on emissions. This comparison of semi-independent databases may therefore reduce uncertainties in emissions estimates. The exercise illustrated the usefulness of standard reporting formats and the availability of background information other than the official National Communications to the Climate Convention. The comparison may lead to major revisions of officially reported methane emissions in several countries.     

Recent advances and perspectives towards emission inventories of mobile sources: Compilation approaches, data acquisition methods, and case studies

In recent years, great efforts have been devoted to reducing emissions from mobile sources with the dramatic growth of motor vehicle and nonroad mobile source populations. Compilation of a mobile source emission inventory is conducive to the analysis of pollution emission characteristics and the formulation of emission reduction policies. This study summarizes the latest compilation approaches and data acquisition methods for mobile source emission inventories. For motor vehicles, a high-resolution emission inventory can be developed based on a bottom-up approach with a refined traffic flow model and real-world speed-coupled emission factors. The top-down approach has advantages when dealing with macroscale vehicle emission estimation without substantial traffic flow infrastructure. For nonroad mobile sources, nonroad machinery, inland river ships, locomotives, and civil aviation aircraft, a top-down approach based on fuel consumption or power is adopted. For ocean-going ships, a bottom-up approach based on automatic identification system (AIS) data is adopted. Three typical cases are studied, including emission reduction potential, a cost-benefit model, and marine shipping emission control. Outlooks and suggestions are given on future research directions for emission inventories for mobile sources: building localized emission models and factor databases, improving the dynamic updating capability of emission inventories, establishing a database of emission factors of unconventional pollutants and greenhouse gas from mobile sources, and establishing an urban high temporal-spatial resolution volatile organic compound (VOC) evaporation emission inventory.     

中国平板玻璃行业大气污染物排放特征研究

基于中国2013~2015年27个省（区、市）平板玻璃企业的逐生产线基础信息、活动水平及污染物控制技术等数据,建立了平板玻璃主要大气污染物SO₂、NO_x排放量计算方法和排放清单,使用蒙特卡洛法进行了不确定性分析.统计了平板玻璃产量、燃料使用量、燃料结构以及污染物控制技术,分析了排放特征与空间差异.结果表明：中国平板玻璃行业以天然气/煤气为主要燃料,平均单位产品能源消耗量为13.2kg标煤/重量箱,山西、内蒙古等省份较高;37%和42%的生产线分别安装了脱硫、脱硝设施,技术以烟气循环流化床、双碱法、SCR为主;SO₂排放量先升后降,2014年达到16.84万t,2015年下降至13.67万t,湖北、浙江、河北、广东排放量较大;NO_x排放量持续下降,从2013年的37.47万t下降至2015年的28.38万t,河北、湖北、山东、广东排放量较大;SO₂排放强度西南部地区高于其他地区,且有上升趋势,其他地区SO₂排放强度整体下降;NO_x排放强度中西部地区较高.应加强高能耗、高排放以及高强度地区的污染控制力度.     

Development of a high-resolution spatial inventory of greenhouse gas emissions for Poland from stationary and mobile sources

Greenhouse gas (GHG) inventories at national or provincial levels include the total emissions as well as the emissions for many categories of human activity, but there is a need for spatially explicit GHG emission inventories. Hence, the aim of this research was to outline a methodology for producing a high-resolution spatially explicit emission inventory, demonstrated for Poland. GHG emission sources were classified into point, line, and area types and then combined to calculate the total emissions. We created vector maps of all sources for all categories of economic activity covered by the IPCC guidelines, using official information about companies, the administrative maps, Corine Land Cover, and other available data. We created the algorithms for the disaggregation of these data to the level of elementary objects such as emission sources. The algorithms used depend on the categories of economic activity under investigation. We calculated the emissions of carbon, nitrogen sulfure and other GHG compounds (e.g., CO₂, CH₄, N₂O, SO₂, NMVOC) as well as total emissions in the CO₂-equivalent. Gridded data were only created in the final stage to present the summarized emissions of very diverse sources from all categories. In our approach, information on the administrative assignment of corresponding emission sources is retained, which makes it possible to aggregate the final results to different administrative levels including municipalities, which is not possible using a traditional gridded emission approach. We demonstrate that any grid size can be chosen to match the aim of the spatial inventory, but not less than 100 m in this example, which corresponds to the coarsest resolution of the input datasets. We then considered the uncertainties in the statistical data, the calorific values, and the emission factors, with symmetric and asymmetric (lognormal) distributions. Using the Monte Carlo method, uncertainties, expressed using 95% confidence intervals, were estimated for high point-type emission sources, the provinces, and the subsectors. Such an approach is flexible, provided the data are available, and can be applied to other countries.

     

京津冀城市群大气污染传输规律研究——两组排放清单的比较分析

利用WRF/CALPUFF耦合模型,在同样重污染气象条件下,选择了当下模拟应用最广的两组排放清单对4种主要污染物（NO_x,SO₂,PM_2.5和PM₁₀）进行京津冀城市间区域传输贡献比较分析.其中一组排放清单来自政府的环境统计（以下称：环统排放清单）,另一组排放清单是来自中国多尺度排放清单（以下称：MEIC排放清单）.污染物的浓度空间分布表明,两种排放清单下污染物浓度均呈现北部以唐山中心,南部以石家庄-邯郸为中心的分布特征,均是由两个浓度最高的中心向外逐渐降低.但是环统排放清单下模拟的污染物浓度高值区范围更大,更接近实际监测数据.基于不同的清单输入,一些城市的传输角色存在一些差异.例如,对于4种污染物,两种排放清单模拟出的沧州与周边城市的净传输方向完全相反,在MEIC排放清单中,沧州以向外净传输为主,即为源;而在环统排放清单中,沧州则变成了净输入城市,即为汇.这些结论将影响大气联防联控中各城市源汇责任的认定,在实际环境管理中应注重多源数据的选择、验证和比较.     

基于测点环境浓度影响的点源应急强化减排分析

基于预报气象条件、广州及周边城市的重点企业排放清单,采用CALPUFF模型模拟2010年亚运会开幕式期间重点企业对广州市内空气质量监测点的相对环境浓度影响,据此筛选得出预报不利气象条件下工业点源应急强化减排名单,并利用GIS可视化技术分析点源强化减排效果,为空气质量保障的专家会商提供依据.广州亚运会期间点源应急强化减排实施效果表明,有针对性地对测点环境浓度影响大的企业实施强化减排措施,可有效缓解个别点位的一定范围内超标问题.本文提出的研究方法和配套的GIS软件可为不利气象条件下工业点源的应急强化减排提供辅助决策服务和数据支持.     

Comparison of CH4 emission inventory data and emission estimates from atmospheric transport models and concentration measurements

CH₄ emissions from two sources of emission inventory data i.e. the National Communications and the EDGAR/GEIA database, are compared with emission estimates from six global and two regional atmospheric transport models. The emission inventories were compiled using emission process parameters to establish emission factors and statistical data to derive activity data. The emission estimates were derived from an evaluation of atmospheric transport modelling results and measured concentrations of CH₄. The comparison of emission inventories and the emissions derived from atmospheric transport models shows the largest differences on the global scale to occur in biogenic CH₄ emissions, i.e. by wetlands and biomass burning. Anthropogenic CH₄ emissions due to oil and gas production and distribution, also appear rather uncertain, especially with respect to the spatial distribution of the sources. A comparison of CH₄ emissions on a smaller scale (NW Europe) showed a fair amount of agreement between National Communications, EDGAR data and results of inverse atmospheric modelling. Because most of the CH₄ emissions in this area come from reasonably well-known CH₄ emission sources like ruminants and landfills, this is a good argument. CH₄ emission from some areas in the North Sea was underestimated by inventories. This could be due to CH₄ emissions of oil production platforms in the North Sea.     

Biogenic VOCs emission inventory development of temperate grassland vegetation in Xilin River basin, Inner Mongolia, China

Given the key role of biogenic volatile organic compounds(VOCs) to tropospheric chemistry and regional air quality, it is important to generate accurateVOCs emission inventories. However, only a less fraction of plant species, in temperate grassland of Inner Mongolia, has been characterized by quantitative measurements. A taxonomic methodology, which assigns VOCs measurements to unmeasured species, is an applicable and inexpensive alternation for extensive VOCs emission survey, although data are needed for additional plant families and genera to further validate the taxonomic approach in grassland vegetation. In this experiment, VOCs emission rates of 178 plant species were measured with a portable photoionization detector( PID). The results showed the most of genera and some families have consistent feature of their VOCs emission, especially for isoprene, and provide the basic premise of taxonomic methodology to develop VOCs emission inventories for temperate grassland. Then, the taxonomic methodology was introduced into assigning emission rate to other 96 species, which no measured emission rates available here. A systematical emission inventory of temperate grassland vegetation in Inner Mongolia was provided and further evidence that taxonomy relationship can serve as a useful guide for generalizing the emissions behavior of many, but not all, plant families and genera to grassland vegetation.     

基于CSGD的排放清单处理工具研究

CSGD（crowd sourcing geographic data,众源地理数据）是通过互联网向大众或相关机构提供的一种开放地理空间数据,具有易获取、时效性好、准确性高等特点,在排放清单时空分配方面具有应用潜力.然而,现有排放清单处理工具不支持CSGD数据直接输入且难以满足排放清单空间分配和空气质量模式所需清单格式,因此,亟待开发一套可以拓展该类数据在排放清单领域应用的工具.以CSGD中的POI（城市设施兴趣点）数据为主要研究对象,基于QGIS平台、C++语言及Python语言,开发了在Windows系统下的ISAT（inventory spatial allocate tool,排放清单空间分配工具）工具及在Windows或Linux系统下的ISAT.M工具.结果表明:ISAT工具以POI数据为基础制作出的空间分配结果与排放源排放强度的空间分布特征的一致性较好;ISAT.M工具输出的inline清单可以作为CMAQ空气质量模式及其DDM敏感性分析模块的输入文件并开展模拟,通过与SMOKE模型的关闭源法模拟结果对比发现,二者在数据及空间分布上呈较好的一致性.研究显示,CSGD数据应用于排放清单空间分配可较好地反映排放源空间分布特征,同时由于此类数据存在信息冗杂、近郊区数据缺失等问题,在应用过程中应注意数据清洗及数据种类的选取工作.      

基于精细化年均行驶里程建立机动车排放清单

基于环保检测数据，提出“里程-车龄”曲线用以获取满足“车辆类型-燃料种类-排放标准”三级分类的精细化年均行驶里程.使用《道路机动车大气污染物排放清单编制技术指南（试行）》推荐值、车辆类型均值、“里程-车龄”曲线3种方式获取年均行驶里程并分别建立排放清单，发现年均行驶里程的本地化与精细化可以极大降低行驶里程不确定性对排放清单准确性的影响.采用精细化年均行驶里程，计算得到青岛市2017年机动车CO、VOCs、NO_x、PM₁₀、NH₃和SO₂的排放量分别为7.07，1.14，2.84，0.10，0.08和0.08万t.分析排放构成可知，老旧车淘汰在当前仍可作为青岛市机动车排放治理的有效举措.结合路网信息与交通数据，得到0.01°×0.01°高时空分辨率网格化排放清单.结果表明，青岛市机动车排放分布在不同时段变化明显.以NO_x为例，排放的早晚高峰分别出现在8：00与17：00，占到了全天总排放的8.17%和7.53%.同时，排放分布存在着空间异质性，排放从城市中心至边缘呈逐渐降低趋势，沿高速路呈明显带状分布.     

基于交通流量和路网的区域机动车污染物排放量空间分配方法

针对传统的机动车污染物排放空间分配方法精度不高的问题,提出了一种基于交通流量与道路系统的机动车污染物排放"标准道路长度"空间分配的新方法.该方法以实际道路网络作为机动车污染物排放的分配基底,根据不同等级道路交通流量的差异引入"标准道路长度"转换体系,并利用GIS技术完成机动车污染物排放的空间分配过程.将该方法应用于珠三角地区,建立了2004年珠三角地区的机动车污染物空间分配清单.研究结果表明,珠三角地区机动车高污染物排放集中在车辆保有量大、路网密集、交通流量大的城市和地区,且高污染物排放空问分布情况与主干路网的分布一致,呈现出明显的路状分布;结果显示,该方法能有效降低传统方法空问分配的偏差,尤其当路网分辨率提高时.分配结果精度更高,更切合实际排放情况.     

四川省2008-2014年水泥行业大气污染物排放清单及时空分布特征

根据收集的四川省水泥行业活动水平数据及排放因子,建立了四川省2008-2014年水泥行业大气污染物排放清单,分析其年际变化趋势,识别时间分布特征,并利用GIS建立了高分辨率的网格化清单.此外,对水泥行业污染物排放的不确定性范围进行了定量估算.结果表明,2008-2014年水泥行业SO₂和NO_x排放显著增长,而PM₁₀和PM_2.5排放呈下降趋势;成都及周边地区以及川东北地区是水泥污染排放的主要贡献地区,大部分城市的污染变化与全省的情况基本一致;新型干法水泥产量比重由2008年的41%增长至2014年的88%,随之各污染物排放占比也显著增长,2014年约达到90%;水泥NO_x排放对空气NO₂质量浓度有一定影响,变化趋势较为一致,相比而言,PM₁₀质量浓度受水泥排放影响较小;水泥产量月变化特征不明显,年初1、2月份产量较低,下半年产量高于上半年;在空间分布上,污染物排放主要集中在德阳-绵阳、眉山-乐山及内江-自贡等地;水泥行业排放清单的不确定性主要来源于污染物去除效率及排放因子的选取,其中,PM_2.5不确定性范围较大,约为-64%~103%,SO₂的不确定性范围较小,为-45%~45%.     

东北地区农业源一次颗粒物排放清单研究

采用自下而上的清单编制方法,搜集各农业环节(秸秆燃烧、整地、收割、谷物处理、化肥施用、农机排放、风蚀)排放因子、作物面积和耕作方式等信息,编制了2010年东北地区县级尺度的农业一次颗粒物(PM₁₀和PM_2.5)排放清单,并分析了农业源颗粒物排放的时空分布特征.结果表明:1)2010年东北地区农业源一次颗粒物PM₁₀总排放量54.6万t,PM_2.5总排放量35.6万t;2)东北地区农业源一次颗粒物PM₁₀排放量最大的农业活动环节是秸秆燃烧,占农业源总排放量的比例为60%,秸秆燃烧排放PM_2.5占PM_2.5农业源排放量的87%,整地环节是一次颗粒物排放的第2大农业排放源,对农业源排放PM₁₀和PM_2.5总量的贡献率分别是27%和6%; 3)PM₁₀和PM_2.5的排放强度空间分布表明,东北地区农业源颗粒物排放区域集中在黑龙江省东北部和中部地区,吉林省中部和辽宁省中部地区; 4)PM₁₀和PM_2.5排放的时间变化特征显示,PM₁₀农业源排放年变化曲线中,5月份和9、10月份是农业源排放一次颗粒物PM₁₀较多的月份,PM_2.5排放集中在9、10月份;5)本研究估算的污染物排放清单的不确定性为184.3%.未来的工作将侧重于典型农业区本土排放因子测定,从而有效减小排放清单的不确定性.     

2000～2020年天津市机动车全过程VOCs排放特征及演变

机动车排放已成为城市地区人为源挥发性有机物(VOCs)的重要来源,排放清单是量化其环境影响的重要手段.针对已有研究中存在的过程区分不清、排放因子测试不全和气象参数考虑不细等问题,基于文献调研与实验测试完善了排放因子库,在月尺度上提出了涵盖尾气排放和蒸发排放(包括运行损失、昼间排放、热浸排放和加油排放)的机动车全过程VOCs逐月排放清单构建方法,并应用此方法建立了2000～2020年天津市机动车全过程VOCs排放清单.研究期内,天津市机动车VOCs排放总量呈现出先缓慢上升后逐步下降的趋势,2020年排放总量为2.14万t,小型客车是对排放总量贡献最大的车型,贡献率达75.00%.排放标准升级对不同过程VOCs排放的影响存在差异.与尾气排放量的持续下降不同,蒸发排放量呈现出先升后降的倒U型走势,且对总排放量的贡献逐年上升,2020年时贡献率为31.69%.机动车排放的月度变化受活动水平与排放因子的双重影响.VOCs排放量呈现出秋冬季高和春夏季低的特点,2020年新冠疫情期间,封控措施限制了机动车活动水平,使得VOCs排放量显著低于往年同期.计算方法和数据结论可为大气污染防治工作提供技术参考...     

基于热异常探测的北京水泥厂大气污染排放评估

为对水泥行业实现大气污染排放动态监测,反映污染排放的时空分布特征,提出基于热异常点探测数据的新型干法水泥气态污染物排放量测算方法.利用VIIRS热异常点的FRP(fire radiation power,辐射功率)参数结合水泥产业结构特点,建立FRP与污染物排放之间的定量估算关系.利用2013—2017年北京市水泥生产统计信息和热异常点探测数据进行了大气污染排放评估,结果显示:①利用热异常产品的FRP参数估算北京市水泥厂的污染排放水平,利用NO_x和SO₂排放量的统计数据对排放估算值进行相关性验证,二者统计值与估算值之间的相关性系数分别为0.65和0.63.②2013—2017年北京市所有水泥厂的热异常点数据与环境统计数据中水泥总产量、熟料总产量、煤炭总产量以及NO_x、SO₂和烟(粉)尘排放量的相关性均较好,相关性系数均在0.7左右.③自2013年以来,北京市金隅琉水环保科技有限公司和北京金隅北水环保科技有限公司的热异常点数均呈下降趋势.由于采取了减排措施,水泥总产量和污染排放量也均呈逐年减少的趋势.研究显示,基于热异常点探测数据的新型干法水泥气态污染物排放量测算方法可快速获取水泥厂的位置信息、热释放规模,结合污染排放因子可间接评估水泥厂NO_x和SO₂等主要污染物的排放情况.      

自上而下的城市能源消耗碳排放估算方法

快速的城镇化进程带来城市碳排放的快速增长,准确的城市水平碳排放数据对于制定科学合理的碳减排政策极为关键,明确碳排放源的关键类别可以做到有的放矢和精准管控.但是目前中国碳排放数据的研究主要集中在国家、地区和省级层面,城市水平由于所需基础数据的不透明和不准确,长久以来缺乏完整的碳排放清单.为解决该问题,在以前相关研究的基础上,通过省级能源平衡表,尝试利用合理的分配指标从省级碳排放数据估算出下属城市的碳排放,构建了一套自上而下的城市能源消耗碳排放估算方法.通过与现有可获得的城市水平数据进行对比,发现估算差距均在10%以内,证明了该方法的可行性和准确性,并尝试在时间尺度进行了扩展.为获取在时间和空间上均连续的中国城市能源消耗碳排放数据提供了科学的方法和合理的思路,也能为各城市分配减排任务和城市间进行减排协商提供可靠的数据支撑.     

Influence of agricultural activities, forest fires and agro-industries on air quality in Thailand

Annual and monthly-based emission inventories in northern, central and north-eastern provinces in Thailand, where agriculture and related agro-industries are very intensive, were estimated to evaluate the contribution of agricultural activity, including crop residue burning, forest fires and related agro-industries on air quality monitored in corresponding provinces. The monthly-based emission inventories of air pollutants, or, particulate matter (PM), NOx and SO₂, for various agricultural crops were estimated based on information on the level of production of typical crops: rice, corn, sugarcane, cassava, soybeans and potatoes using emission factors and other parameters related to country-specific values taking into account crop type and the local residue burning period. The estimated monthly emission inventory was compared with air monitoring data obtained at monitoring stations operated by the Pollution Control Department, Thailand (PCD) for validating the estimated emission inventory. The agro-industry that has the greatest impact on the regions being evaluated, is the sugar processing industry, which uses sugarcane as a raw material and its residue as fuel for the boiler. The backward trajectory analysis of the air mass arriving at the PCD station was calculated to confirm this influence. For the provinces being evaluated which are located in the upper northern, lower northern and northeast in Thailand, agricultural activities and forest fires were shown to be closely correlated to the ambient PM concentration while their contribution to the production of gaseous pollutants is much less.     

A comparison of five high-resolution spatially-explicit,fossil-fuel,carbon dioxide emission inventories for the United States

The quantification of fossil-fuel-related emissions of carbon dioxide to the atmosphere is necessary in order to accurately represent carbon cycle fluxes and to understand and project the details of the global carbon cycle. In addition, the monitoring, reporting, and verification (MRV) of carbon dioxide emissions is necessary for the success of international agreements to reduce emissions. However, existing fossil-fuel carbon dioxide (FFCO₂) emissions inventories vary in terms of the data and methods used to estimate and distribute FFCO₂. This paper compares how the approaches used to create spatially explicit FFCO₂ emissions inventories affect the spatial distribution of emissions estimates and the magnitude of emissions estimates in specific locales. Five spatially explicit FFCO₂ emission inventories were compared: Carbon Dioxide Information and Analysis Center (CDIAC), Emission Database for Global Atmospheric Research (EDGAR), Fossil Fuel Data Assimilation System (FFDAS), Open-source Data Inventory for Anthropogenic CO₂ (ODIAC), and Vulcan. The effects of using specific data and approaches in the creation of spatially explicit FFCO₂ emissions inventories, and the effect of resolution on data representation are analyzed using graphical, numerical, and cartographic approaches. We examined the effect of using top-down versus bottom-up approaches, nightlights versus population proxies, and the inclusion of large point sources. The results indicate that the approach used to distribute emissions in space creates distinct patterns in the distribution of emissions estimates and hence in the estimates of emissions in specific locations. The different datasets serve different purposes but collectively show the key role of large point sources and urban centers and the strong relationship between scale and uncertainty.