典型城市机动车非常规污染物排放清单

以2007年为目标年,利用IVE模型计算并建立北京市、上海市和深圳市3个典型城市的机动车1,3-丁二烯、甲醛、乙醛、NH3、苯、CO2、N2O和CH4等非常规污染物的排放清单.结果表明,在北京市,对8种非常规污染物的排放贡献率最大的均为轻型客车,排放贡献率均在50%以上;其次主要为中重型客车,排放贡献率为5%～26%....     

成都市餐饮源大气污染物排放清单研究

为全面、准确地获得成都市餐饮源大气污染物排放清单,针对成都市社会餐饮、家庭餐饮和食堂餐饮分别选择监测对象进行细颗粒物(PM2.5)、非甲烷总烃(NMHCs)、油烟、氮氧化物(NOx)、SO2和CO 6种大气污染物排放浓度监测.分别按照用油量、就餐人次和灶头风量3种核算依据计算了6种大气污染物的排放因子,并计算成都市餐饮...     

嘉兴市人为源大气污染物排放清单研究

建立了2017年嘉兴市人为源大气污染物排放清单。结果发现,SO_2、NO_x、CO、挥发性有机物(VOCs)、NH_3、总悬浮颗粒物(TSP)、PM_(10)、PM_(2.5)、黑碳(BC)和有机碳(OC)排放总量分别为15 224、60 663、102 600、93 256、26 266、118 923、70 367、19 024、941、1 622t。SO_2的最大排放源是化石燃料固定燃烧源中的电力供热;NO_x的最大排放源是移动源中的柴油车;CO的最大排放源是移动源中的汽油车;VOCs的最大排放源是工艺过程源中的石油化工;NH_3的最大排放源是农业源中的氮肥施用;TSP的最大排放源是扬尘源中的道路扬尘;PM_(10)和PM_(2.5)的最大排放源是工艺过程源中的水泥生产;BC的最大排放源是移动源中的柴油车;OC的最大排放源是餐饮油烟源中的餐饮油烟。对于大气污染中普遍关注的6种污染物,SO_2、NO_x、PM_(10)、PM_(2.5)和VOCs排放的重点源主要集中在各县(市、区)的工业园区或工业集聚区,而NH_3的排放空间分布相对比较分散。     

天津市民用散煤燃烧大气污染物排放清单

为了研究天津市民用散煤燃烧大气污染物的排放情况,采用排放因子法,结合散煤燃烧活动水平,建立了2019、2020年天津市民用散煤燃烧大气污染物排放清单,并根据排放清单对污染物空间分布特征进行了分析。结果表明：2020年民用散煤燃烧量相比2019年减少约61万t,细颗粒物(PM_2.5)、CO、SO₂、氮氧化物(NO_x)分别减排1 010.33、38 070.69、904.16、824.68 t。其中,污染物排放贡献最大的区为蓟州区。各区显示出明显的污染物排放空间差异,未来应推进清洁能源的使用,加快清洁能源政策的推广,以减少民用散煤燃烧的污染物排放。     

乌昌石区域的非金属矿物制品业大气污染物排放清单研究

建立了乌昌石区域非金属矿物制品业CO、NO_x、SO_2、PM_(2.5)和PM_(10) 5种大气污染物的排放清单,并进行了时空分布特征分析,初步探究了估算的不确定性。结果显示,乌昌石区域非金属矿物制品业CO、NO_x、SO_2、PM_(2.5)和PM_(10)总排放量分别为3.71×10~4、2.76×10~4、3.10×10~4、3.04×10~4、1.29×10~5 t。熟石膏行业是CO的主要排放源;水泥(干法)行业是NO_x、SO_2、PM_(2.5)和PM_(10)的主要排放源。乌鲁木齐市是CO、NO_x和SO_2排放量的最大贡献源;石河子市是PM_(2.5)和PM_(10)排放量的最大贡献源。乌昌石区域5月至9月是一年中污染物排放的高峰期,11:00至20:00是一天中污染物排放的高峰期。空间上,乌昌石区域的污染物排放主要分布在乌鲁木齐市中部、西南部以及石河子市。     

东北长春民用散煤燃烧大气污染物排放清单研究

民用散煤燃烧是大气污染的重要来源,由于民用散煤活动水平获取难度较大,目前有关民用散煤燃烧大气污染物排放量的研究较少。计算了2016年长春6个城区内民用散煤燃烧产生的CO、SO2、NOx、PM2.5、PM10、挥发性有机化合物(VOCs)的排放量,编制了民用散煤燃烧大气污染物排放清单,并分析了大气污染物排放的时空分布特征。结果表明:长春城区燃煤棚户区共计287处,总面积26.64km2,棚户区户均燃煤量约为2.1t/户,住户燃煤比在0.6～0.8;2016年长春城区民用散煤CO、SO2、NOx、PM2.5、PM10、VOCs的排放量分别为12 462、329、142、961、1 201、356t,CO为长春地区民用散煤燃烧主要污染物,占民用散煤燃烧污染物总排放量的80.7%;长春各城区民用散煤燃烧总排放量为绿园区宽城区朝阳区双阳区二道区南关区;大气污染物排放日变化峰值在6:00—7:00、12:00、19:00;民用散煤燃烧污染物排放的周变化差异不大,周末排放量较工作日稍高;采暖期大气污染物排放的月变化与气温的变化同步,排放量呈现1月12月2月11月3月10月4月的变化规律。     

西安市机动车污染物排放清单与空间分布特征

基于机动车排放因子(MOVES)模型和地理信息系统(ArcGIS)技术,建立了西安市2017年分辨率为1km×1km的机动车污染物排放清单。结果显示:2017年西安市机动车污染物PM_(2.5)、PM_(10)、NO_x(NO+NO_2)、NO、NO_2、N_2O和挥发性有机物(VOCs)的年排放总量分别为126.1×10~4、138.2×10~4、2 884.2×10~4、2 577.8×10~4、306.4×10~4、27.9×10~4、1 281.2×10~4 kg;柴油车是PM_(2.5)、PM_(10)和NO_x排放的主要来源,贡献率分别为80.2%、79.5%和75.8%;VOCs和N_2O则主要来自汽油车,贡献率分别为74.2%、89.7%;总体看来,研究区域内不同污染物的空间分布规律相似,这与西安市公路分布有关,PM_(2.5)和NO_x的排放主要集中在主城区及周边县区的高速路和国道,而VOCs的排放主要集中在主城区二环及环内。     

乌鲁木齐市固定燃烧点源大气污染物排放清单

通过现场调研结合物料衡算法、排放因子法,建立了2015年乌鲁木齐市固定燃烧点源大气污染物CO、NO_x、SO_2和PM_(2.5)排放清单。结果表明,2015年乌鲁木齐市CO、NO_x、SO_2、PM_(2.5)的排放量分别为4.41×10~4、6.20×10~4、4.61×10~4、1.57×10~4t;从排放污染物的行业来看,采矿与制造业对4种污染物排放的贡献最大,其对CO、NO_x、SO_2、PM_(2.5)排放的贡献率分别为49.02%、42.17%、48.40%、78.55%。从地区分布来看,米东区污染物排放量最大,其对CO、NO_x、SO_2、PM_(2.5)排放的贡献率分别为46.99%、45.90%、51.69%、29.68%。从排放时间来看,供暖季污染物的排放量明显高于非供暖季,白天的污染物排放量高于夜晚。采用蒙特卡罗统计法分析预测的污染物排放量与排放清单计算结果较为接近。     

关中地区机动车颗粒物排放清单

利用本地化修正的MOVES模型模拟确定了关中地区不同类型车辆的颗粒物排放因子,结合实地调研的保有量和行驶里程数据测算了该地区的机动车颗粒物年排放总量,并从季节、城市、车型和燃油等多个角度详细分析了颗粒物的排放分担率。结果表明：关中地区2012年的机动车颗粒物排放总量分别为PM2.5 4.06×103 t,PM10 5.52×103 t;关中五市一区中西安市的颗粒物排放量最高,PM2.5和PM10排放分别占到该地区的46.53%和48.39%;不同类型车辆中,重型货车的排放分担率最高,其次为中型货车,二者之和占到颗粒物总排放的50%以上;不同燃油车辆中,柴油车的排放分担率远远高于汽油车,是颗粒物的主要贡献者;因此中型和重型柴油货车是关中地区控制颗粒物排放污染的重点车型。     

Quality considerations of European PM emission inventories

This paper reviews information on emission inventories of particulate matter (PM) in Europe. A large body of scientific literature is available to cover many different aspects. Studies focus on specific sources or source sectors (road transport as well as off-road machinery, domestic heating, industry, agriculture, and natural sources), among which especially road transport emissions are clearly best established. Emission inventories comprising all sources are available for specific European regions, often pointing out regional differences, but also for the entire continent. Still these inventories often are not able to satisfy the needs. Due to PM specific circumstances such as the large number of sources, very different release pathways and differences of the individual particles in terms of chemical composition or size, it is very difficult to appropriately handle measurement conditions to arrive at adequate emission factors, especially when emission points cannot be defined clearly. Information on fugitive emissions (caused by wind shear, material transfer processes or other mechanical forces from non-point sources) is sparse, except for road traffic emissions where recent data seems to converge. The problem of data gaps concerns activities in industry (quarries), agriculture, but also natural particles like sea salt and wind-blown dust. Comparing complete inventories to independent efforts in assessing emissions, e.g. atmospheric measurements combined with source apportionment, allows to better understand and quantify the reliability of inventory data. Methodological improvements and harmonization currently under way in Europe will focus efforts and allow for more reliable PM inventories in the near future.     

Spatial surrogates for the disaggregation of CORINAIR emission inventories

CORINAIR atmospheric emission inventories are frequently used input data for air quality models with a domain situated in Europe. In CORINAIR emission inventories, sources are broken down over 11 major source categories. This paper presents spatial surrogates for the disaggregation of CORINAIR atmospheric emission inventories for input of air pollutants and particulate matter to grid or polygon based air quality model domains inside Europe. The basis for the disaggregation model was the CLC2000 land cover data to which statistical weights were added. Weights were population census data for residential emissions, employment statistics for agricultural and industrial area emissions, livestock statistics for ammonia emissions and annual aircraft movements for emissions realized by air transport. Additional road and off-road network information was used to disaggregate emissions realized by traffic. A comparison of top down produced emission estimates with spatially resolved national emission data for The Netherlands and the United Kingdom gave confidence in the present spatial surrogates as a tool for the top down production of atmospheric emission maps. Explained variance at a spatial resolution of 5 km was >70% for CO, NMVOC and NO_x, >60% for PM10 and almost 50% for SO₂.     

The impact of the establishment of carbon emission trade exchange on carbon emission efficiency

Environmental Science and Pollution Research - The China government focuses on changes in carbon emission efficiency with establishing carbon emission trade exchange (CETE). It is meaningful to...     

The role of bio-mechanical treatments of waste in the dioxin emission inventories

PCDD/Fs are one of the most studied molecules in the world because of their toxicity. In the last years the toxicity of these compounds has been analyzed in details. For years PCDD/F inventories have pointed out the significant role of municipal solid waste (MSW) incinerators in the overall balance. Recently, thanks to new regulations on PCDD/F emissions, in a few countries this scenario is changing: it can be demonstrated that modern MSW incinerators can play a secondary role even if the percentage of MSW sent to combustion has increased. In the latest inventories an unconventional source of PCDD/F has appeared: in nineties some biogas characterizations have demonstrated that there is a release of PCDD/F from MSW sanitary landfills. In addition, the combustion of collected biogas can generate not negligible amounts of PCDD/F. A new question can be put: does the MSW contribute with other management options to the overall balance of PCDD/F? The present work points out that a detailed inventory should take into account also the PCDD/F release from bio-mechanical treatment plants (both composting and bio-drying/bio-stabilization plants). However the contribution from this option is secondary when it is compared with the one from old MSW incinerators.     

Estimation of vehicular emission inventories in China from 1980 to 2005

Multi-year inventories of vehicular emissions at a high spatial resolution of 40 km×40 km were established in China using the GIS methodology for the period 1980–2005, based on provincial statistical data from yearbooks regarding vehicles and roads, and on the emission factors for each vehicle category in each province calculated by COPERT III program. Results showed that the emissions of CH₄, CO, CO₂, NMVOC, NO_x, PM₁₀, and SO₂ increased from 5, 1066, 19 893, 169, 174, 26, and 16 thousand tons in 1980 to 377, 36 197, 674 629, 5911, 4539, 983, and 484 thousand tons in 2005 at an annual average rate of 19%, 15%, 15%, 15%, 14%, 16%, and 15%, respectively. Statistical analysis of vehicular emissions and GDP showed that they were well positively correlated, which revealed that increase of pollutant emissions has been accompanying the growth of GDP. Spatial distribution of pollutant emissions was rather unbalanced: over three-quarters of the total emissions concentrated in developed regions of China's southeastern, northern and central areas covering only 35.2% of China's territory, while the remaining emissions were distributed over the southwestern, northwestern and northeastern regions covering as much as 64.8% of the territory. In 2005, the Beijing–Tianjin–Hebei region, the Yangtze River Delta, and the Pearl River Delta covering only 2.3%, 2.2%, and 1.9%, respectively, of the territory, generated about 10%, 19%, and 12%, respectively, of the total emissions. Since 1990, motorcycles have been the major contributors to the CH₄, CO, NMVOC, and PM₁₀ emissions, due to the large population. Heavy-duty vans were the major contributors to the NO_x and SO₂ emissions because of high emission factors. Passenger cars contributed about one third of the emissions of each pollutant. Contributions of vehicle categories to emissions varied from province to province, due to the diversity of vehicle compositions among provinces.     

Air emission inventories in North America: a critical assessment

Although emission inventories are the foundation of air quality management and have supported substantial improvements in North American air quality, they have a number of shortcomings that can potentially lead to ineffective air quality management strategies. Major reductions in the largest emissions sources have made accurate inventories of previously minor sources much more important to the understanding and improvement of local air quality. Changes in manufacturing processes, industry types, vehicle technologies, and metropolitan infrastructure are occurring at an increasingly rapid pace, emphasizing the importance of inventories that reflect current conditions. New technologies for measuring source emissions and ambient pollutant concentrations, both at the point of emissions and from remote platforms, are providing novel approaches to collecting data for inventory developers. Advances in information technologies are allowing data to be shared more quickly, more easily, and processed and compared in novel ways that can speed the development of emission inventories. Approaches to improving quantitative measures of inventory uncertainty allow air quality management decisions to take into account the uncertainties associated with emissions estimates, providing more accurate projections of how well alternative strategies may work. This paper discusses applications of these technologies and techniques to improve the accuracy, timeliness, and completeness of emission inventories across North America and outlines a series of eight recommendations aimed at inventory developers and air quality management decision-makers to improve emission inventories and enable them to support effective air quality management decisions for the foreseeable future.     

Primary sources of selected POPs: regional and global scale emission inventories

During the last decade, a number of studies have been devoted to the sources and emissions of Persistent Organic Pollutants (POPs) at regional and global scales. While significant improvements in knowledge have been achieved for some pesticides, the quantitative understanding of the emission processes and emission patterns for "non-pesticide" POPs are still considered limited. The key issues remaining for the non-pesticide POPs are in part determined by their general source classification. For industrial chemicals, such as the polychlorinated biphenyls (PCBs), there is considerable uncertainty with respect to the relative importance of atmospheric emissions from various source categories. For PCBs, temperature is discussed as a potential key factor influencing atmospheric emission levels and patterns. When it comes to the unintentional by-products of combustion and industrial processes (PCDD/Fs), there is still a large uncertainty with respect to the relative contribution of emissions from unregulated sources such as backyard barrel burning that requires further consideration and characterisation. For hexachlorobenzene (HCB), the relative importance of primary and secondary atmospheric emissions in controlling current atmospheric concentrations remains one of the key uncertainties. While these and other issues may remain unresolved, knowledge concerning the emissions of POPs is a prerequisite for any attempt to understand and predict the distribution and fate of these chemicals on a regional and global scale as well as to efficiently minimise future environmental burdens.     

机动车污染排放模型研究综述

过去几十年,为了掌握机动车污染排放的规律和特征,向决策者提供科学有效的机动车污染控制措施,研究者们致力于研究机动车污染物排放的物化原理和影响机动车污染的主要因素,并据此建立多种尺度的机动车排放模型,以模拟城市区域或者街道的污染物排放.为了分析机动车的瞬态排放特征,目前的机动车排放模型研究正逐渐从宏观向微观发展,排放测试方法注重获取逐秒的排放数据,排放模型模拟的时间尺度和空间尺度逐步趋向微观.此外,机动车模型研究正趋向与交通模型进行耦合,从而揭示机动车在实际道路交通流中的排放特征.从机动车排放的主要影响因素、机动车排放测试、机动车排放因子模型及机动车排放清单等4个方面综述了国内外机动车排放研究现状和发展动向,对比并评价各种机动车排放模型方法的优缺点和适用范围,对我国的机动车排放模型发展方向进行了展望.