成都双流国际机场大气污染物排放清单与时空分布特征

基于成都双流国际机场活动水平数据,采用排放因子法和计算模型等,编制了机场大气污染物排放清单,并完成了时空分配和不确定性分析,建立了高分辨率网格化排放清单。结果表明,成都双流国际机场标准起飞着陆(LTO)循环数为2.4×10~5次/a,CO、VOCs、NO_x、PM_(10)、PM_(2.5)、SO_2排放量分别为1.2×10~3、1.3×10~2、2.1×10~3、2.8×10、2.7×10、2.5×10~2t/a,且主要由飞机发动机排放;活动水平数据仅包括LTO循环数和地面保障设备两部分;污染物排放分布和跑道类型相关性较高;排放清单活动水平数据可靠性较高,而排放因子存在一定的不确定性。     

重庆市主城区大气水溶性离子在线观测分析

2015年12月—2016年3月期间,利用在线气体与气溶胶成分监测仪(IGAC)在重庆市大气超级站开展连续观测分析,并捕捉到2次持续时间较长的空气重污染过程。对PM_(2.5)中9种水溶性离子及5种气态前体物的观测结果分析表明:NO_3~-、NH_4~+和SO_4~(2-)是重庆市主城区PM_(2.5)中主要的水溶性离子成分,其浓度均表现出明显的日变化特征,主要以(NH4)_2SO_4和NH_4NO_3的形式存在。NH_3和SO_2是最主要的气态污染物。2次重污染过程的水溶性离子组分有明显差异,细颗粒物累积型污染的NH_4~+、SO_4~(2-)、NO_3~-浓度高,二次转化十分明显;春节期间烟花爆竹集中燃放,Cl~-、K~+浓度高,主要属于一次排放;污染期间主要离子组分的同源性特征显著。     

奎独乌区域大气降水离子来源分析

通过研究2010—2015年奎独乌区域大气降水化学特征和变化,分析降水中离子组成和来源。结果表明,2010—2015年奎独乌区域硫酸型大气污染较为明显,硫酸盐污染物对降水酸性影响略降,土壤扬尘带来的钙离子污染略降;降水中SO_4~(2-)、Cl~-、Ca~(2+)、Na~+、F~-、K~+主要来源于土壤扬尘,其中SO_4~(2-)、Cl-、Ca~(2+)还来源于人为源排放;NO-3主要来源于人为源排放。工业源SO_2、烟粉尘排放量变化是引起降水中SO_4~(2-)、Ca~(2+)当量浓度变化的主要因素,大风和扬尘天气的减少也是降水中Ca~(2+)当量浓度降低的重要因素;工业源和机动车NO_x排放量变化是引起降水中NO_3~-当量浓度变化的主要因素。     

常州市大气污染物排放清单及分布特征

以点源、流动源、面源分类,在研究工业企业、机动车、建筑工地、秸秆焚烧等20多类排放源的基础上,建立2011年常州市大气污染物排放清单。结果表明:2011年该市大气污染物PM、PM10、PM2.5、SO_2、NO_x、CO、NH_3和VOCs的排放总量分别为13.514万t、6.746万t、2.67万t、5.975万t、12.316万t、66.595万t、1.64万t、9.026 1万t。道路、工业、建筑工地、机动车是颗粒物的主要排放来源;SO_2、NO_x、CO排放主要来自工业和机动车;NH_3的主要排放源为农业氮肥使用和畜禽养殖;VOCs的排放主要来自机动车、涂料、植被和工业。各行政区中,武进、溧阳、新北和金坛大气污染物排放量较大。     

南充市大气PM10与PM2.5排放清单及特征

以四川省南充市为研究区域,通过实地调研、现场测试及结合统计年鉴等获得数据,采用排放因子法计算南充市2014年大气PM_(10)、PM_(2.5)排放量并建立排放清单。结果表明,南充市2014年扬尘源、移动源、生物质燃烧源、化石燃料固定燃烧源、工艺过程源排放总量PM_(10)分别为85 187、1 777、9 175、2 417、3 519 t,PM_(2.5)分别为16 093、1 619、7 322、914、1 585 t,PM_(10)贡献率分别为83.5%、1.7%、9.0%、2.4%、3.4%,PM_(2.5)贡献率分别为58.4%、5.9%、26.6%、3.3%、5.8%。城市区域扬尘源、生物质燃烧源、移动源、化石燃料固定燃烧源、工艺过程源对PM_(10)贡献分别为60.0%、12.5%、6.3%、8.6%、12.5%,对PM_(2.5)贡献分别为41.8%、21.6%、14.4%、8.1%、14.1%。南充市2014年大气PM_(10)、PM_(2.5)排放源总量和贡献率以及区域空间分布特征均存在差异。     

佛山市禅城区天然气公交车排气污染分析

以2015年佛山市禅城区的公交车为研究对象,利用COPERTⅣ模型计算本地化的排放因子,分析该区公交车污染排放现状,以及天然气公交车相对于柴油公交车的减排效果。结果表明,禅城区公交车污染物年排放量分别为CO180.73 t、VOCs 176.92 t、NO_x672.87 t、PM_(2.5)14.17 t,用天然气公交车替代柴油公交车,NO_x和PM_(2.5)分别减排53.39%和79.11%。通过遥感监测数据进一步分析禅城区天然气公交车的排气污染特点,表明其CO排放基本处于稳态,NO_x排放波动较大,并据此提出了相应的污染控制措施。     

北京市典型重污染过程中PM2.5载带水溶性无机离子污染特征分析

为研究北京地区冬季PM_(2.5)载带的水溶性无机离子组分污染特征,2013年1月在中国环境科学研究院内采用在线离子色谱(URG-9000B,AIM-IC)对PM_(2.5)中水溶性无机离子(SO_4~(2-)、NO_3~-、Cl~-、NH_4~+、Na~+、K~+、Mg~(2+)、Ca~(2+))进行监测与分析。结果表明,采样期间总水溶性无机离子(TWSI)浓度为61.0μg/m~3,其中二次无机离子SO_4~(2-)、NO_3~-、NH_4~+(SNA)占比达72.3%,在PM_(2.5)中占比为40.29%,表明北京市PM_(2.5)二次污染严重。重污染天[NO_3~-]/[SO_4~(2-)]表明,固定源污染较移动源更为显著。三元相图表明,在空气质量为优的情况下,NH_4~+(在SNA中占比为30.3%~65.5%,下同)主要以NH_4NO_3的形式存在,较少比例以(NH_4)_2SO_4存在;严重污染时,NH_4~+(47.3%~77.9%)主要以(NH_4)_2SO_4形式存在,其次以NH_4NO_3的形式存在,其余的NH_4~+以NH_4Cl的形式存在。[NO_3~-]/[SO_4~(2-)]日变化表明,早、晚机动车高峰影响北京重污染发生。     

衡阳城区冬季PM2.5中水溶性离子污染特征

为探究衡阳冬季PM_(2.5)和水溶性离子污染特征及其来源,于2019年1月在衡阳市城区采集大气PM_(2.5)样品,使用重量法和离子色谱法测得PM_(2.5)和水溶性离子组分质量浓度,并分析其浓度特征、酸碱度和来源等问题。结果表明:采样期间衡阳大气PM_(2.5)平均质量浓度为94.25μg/m~3,总水溶性离子质量浓度为52.94μg/m~3,占PM_(2.5)总质量浓度的56.43%;阴阳离子当量之比为1.12,PM_(2.5)呈酸性,其中SNA(SO_4~(2-)、NO_3~-和NH_4~+)占总水溶性离子质量浓度的95.06%。污染期间二次转化明显,SNA主要以(NH_4)_2SO_4和NH_4NO_3形式存在。源解析发现大气PM_(2.5)受化石燃料和生物质燃烧、垃圾焚烧、建筑扬尘、气态前体物二次转化、外来输送等多重因素影响,其中机动车尾气排放的NO_x在大气中二次转化形成的硝酸盐是衡阳重污染的最主要原因。     

北京地区冬季典型PM2.5重污染案例分析

对2013年1月10—14日发生的持续性PM2.5重污染过程从污染过程演变、气象条件影响、与气态污染物关系、区域污染背景、PM2.5浓度空间分布演变及其与地面风场的关系、PM2.5组分特征等多个方面进行全面的分析,较为完整地还原了该次重污染案例的形成原因以及主要影响因素。主要结论包括:该次重污染过程是稳定气象条件下导致的局地污染物积累,再叠加华北区域性污染的影响共同造成,其中10、12日北京地区PM2.5浓度的快速增长反映了周边污染传输的显著影响;逆温不但造成污染物难以扩散,且不同的逆温类型对PM2.5浓度水平有显著影响,同时还发现逆温的破坏导致近地面高浓度污染物向上扩散,造成百花山出现峰值高污染浓度现象;NO2与PM2.5浓度水平的高相关性反映交通污染二次转化对PM2.5浓度水平的影响,在较高湿度条件下,SO2浓度水平对湿度敏感且表现为负相关性;该次污染过程中OM、SO2-4、NO-3、NH+4等组分在PM2.5质量浓度中的占比超过70%,说明燃煤、机动车等仍是北京地区最主要的污染来源,同时SO2-4占比最高也说明区域污染传输对该次重污染的显著贡献。     

能源结构变化对兰州市大气质量的影响

将2001—2010年的主要能源材料消耗、主要污染物变化及主要行业分布进行了相关性分析,结果表明:兰州市大气4种主要污染物中除烟尘呈下降趋势外,废气总量、SO2、NOx仍呈上升趋势;主要污染源为燃煤,主要污染行业为电力、蒸汽热水产供业;废气和SO2排放总量与燃煤和燃气呈强正相关,而NOx排放只与燃气呈强正相关。建议发挥兰州地域优势,加大以水电供应为主的能源结构调整,对改善当地空气质量有重要价值。     

Monitoring of Criteria Air Pollutants in Bursa, Turkey

The concentrations of criteria air pollutants such as CO, NO_x (NO + NO₂), SO₂ and PM were measured in the period of May 2001 and April 2003 in the city of Bursa, Turkey. The average concentrations for this period were 1115±1600 μg/m³, 29±50 μg/m³, 51±24 μg/m³, 79±65 μg/m³, 40±35 μg/m³, 98±220 μg/m³, for CO, NO, NO₂, NO_x, SO₂ and PM, respectively. Temporal changes in concentrations were analyzed using meteorological factors. Correlations among pollutant concentrations and meteorological parameters showed weak relations nearly in all data. Lower concentrations were observed in the summer months while higher concentrations were measured in the winter months. The increase in winter concentrations was probably due to residential heating. Pollutants were associated with each other in order to have information about their origin. NO_x/SO₂ ratio was also examined to bring out the source origin contributing on air pollution (i.e., traffic or stationary).     

杭州市大气污染物排放清单及特征

以杭州市区为研究区域,通过调查整合多套污染源数据库及其他统计资料,研究文献报道及模型计算的各种污染源排放因子,获得杭州市区各行业PM10、PM2.5、SO2、NOx、CO、VOCs、NH3等污染物的排放量,建立了杭州市区2010年1 km×1 km大气污染物排放清单。结果表明,2010年杭州市区PM10、PM2.5、SO2、NOx、CO、VOCs和NH3的排放总量分别为7.96×104、4.02×104、7.23×104、8.98×104、73.90×104、39.56×104、3.32×104t。从排放源的行业分布来看,机动车尾气排放是杭州市区大气污染物最重要排放源之一,对PM10、PM2.5、NOx、CO和VOCs的贡献分别达到14.4%、27.1%、40.3%、21.4%、31.1%。道路扬尘、电厂锅炉、工业炉窑、植被、畜禽养殖对不同污染物分别有着重要贡献,道路扬尘对PM10和PM2.5的贡献分别为44.6%和20.0%、电厂锅炉对SO2和NOx的贡献分别为37.0%和25.7%、工业炉窑对CO的贡献为41.5%、植被排放对VOCs的贡献为27.1%、畜禽养殖对NH3的贡献为76.5%。从空间分布来看,萧山区和余杭区对SO2、NH3和植被排放BVOC的贡献要显著高于主城区;而主城区机动车对PM2.5、NOx和VOCs的贡献分别达到36.3%、56.0%和47.4%,较市区范围内显著增加,表明机动车尾气排放已成为杭州主城区大气污染最重要的来源之一。     

Extreme Nitrogen Oxide and Ozone Concentrations in Athens Atmosphere in Relation to Meteorological Conditions

In the present study, we investigate the variation of NO _x (NO + NO₂) and O₃ concentrations and the relation between the extreme events (episodes) of NO _x and O₃ concentrations and the relevant meteorological conditions in the urban atmosphere of the Athens basin. Hourly data of NO, NO₂ and O₃ concentrations from 10 representative monitoring sites located in the Athens basin were used, covering the 10-year time period from 1994 to 2003. The results of our analysis show that the concentrations of air pollutants differ significantly from one monitoring site to another, due to the location and proximity of each station to the emission sources. For each site, there are also significant differences in NO _x and O₃ concentrations from day to day, as well as from month to month and/or from season to season. The annual and seasonal variations show higher NO values in winter and lower in summer. On the contrary, NO₂ and O₃ values are higher in summer (photochemical production of O₃) and lower in winter. These differences are attributed, to a large extent, to the prevailing synoptic and meteorological conditions, the most important between them being the wind direction and speed as well as the atmospheric pressure. Our analysis of the identified 179 extreme NO _x air pollution events shows that most of them took place under anticyclonic conditions, associated with calm or weak winds (speed <2.5 ms⁻¹) of mostly southern to southwestern directions, as well as with low air temperatures and intense stable surface atmospheric conditions. There exists a significant decreasing tendency in NO _x air pollution episodic events over the 10-year study period, resulting in very few to none events in the period from 2000 to 2003. As far as it concerns the extreme O₃ concentrations, 34 air pollution events were identified, occurring under high air temperatures, variable weak winds and intense solar irradiation. The trends of O₃ concentrations are stronger in suburban sites than in urban ones.     

An Analysis of Secondary Pollutants in Buenos Aires City

Air pollutant concentrations from a monitoring campaign in Buenos Aires City, Argentina, are used to investigate the relationships between ambient levels of ozone (O₃), nitric oxide (NO) and nitrogen dioxide (NO₂) as a function of NO _x (=NO + NO₂). This campaign undertaken by the electricity sector was aimed at elucidating the apportionment of thermal power plants to air quality deterioration. Concentrations of carbon monoxide (CO) and sulphur dioxide (SO₂) were also registered. Photo stationary state (PSS) of the NO, NO₂, O₃ and peroxy radicals species has been analysed. The ‘oxidant’ level concept has been introduced, OX (=O₃ + NO₂), which varies with the level of NO _x . It is shown that this level is made up of NO _x -independent and NO _x -dependent contributions. The former is a regional contribution that equates the background O₃ level, whereas the latter is a local contribution that correlates with the level of primary pollution. Furthermore, the anticorrelation between NO₂ and O₃ levels, which is a characteristic of the atmospheric photo stationary cycle has been verified.The analysis of the concentration of the primary pollutants CO and NO strongly suggests that the vehicle traffic is the principal source of them. Levels of continuous measurements of SO₂ for Buenos Aires City are reported in this work as a complement of previously published results.     

Study of urban atmospheric pollution in Navarre (Northern Spain)

An ambient air quality study was undertaken in two cities (Pamplona and Alsasua) of the Province of Navarre in northern Spain from July 2001 to June 2004. The data were obtained from two urban monitoring sites. At both monitoring sites, ambient levels of ozone, NO_x, and SO₂ were measured. Simultaneously with levels of PM₁₀ measured at Alsasua (using a laser particle counter), PM₁₀ levels were also determined at Pamplona (using a beta attenuation monitor). Mean annual PM₁₀ concentrations in Pamplona and Alsasua reached 30 and 28 μg m⁻³, respectively. These concentrations are typical for urban background sites in Northern Spain. By using meteorological information and back trajectories, it was found that the number of exceedances of the daily PM₁₀ limit as well as the PM₁₀ temporal variation was highly influenced by air masses from North Africa. Although North African transport was observed on only 9% of the days, it contributed the highest observed PM₁₀ levels. Transport from the Atlantic Ocean was observed on 68% of the days; transport from Europe on 13%; low transport and local influences on 7%; and transport from the Mediterranean region on 3% of the days. The mean O₃ concentrations were 45 and 55 μg m⁻³ in Pamplona and Alsasua, respectively, which were above the values reported for the main Spanish cities. The mean NO and NO₂ levels were very similar in both sites (12 and 26 μg m⁻³, respectively). Mean SO₂ levels were 8 μg m⁻³ in Pamplona and 5 μg m⁻³ in Alsasua. Hourly levels of PM₁₀, NO and NO₂ showed similar variations with the typically two coincident maximums during traffic rush hours demonstrating a major anthropogenic origin of PM₁₀, in spite of the sporadic dust outbreaks.     

灰霾期间武汉城市区域大气污染物的理化特征

利用湖北省大气复合污染自动监测站2013年的全年监测数据,分析了灰霾期间武汉城市区域大气污染物的理化特征。霾日主要出现在春季、秋季和冬季。霾日与非霾日大气污染物质量浓度和气象参数的对比分析结果显示:高湿度、静风是武汉城市区域霾日的重要气象特征;PM1、PM_(2.5)、PM_(10)、NO_2、CO、NH3的质量浓度,SOR、NOR值以及PM_(2.5)中的二次无机离子(SO2-4、NO-3、NH+4)和部分元素(Pb、Se、Cd、Zn、K)的质量浓度均在霾日明显高于非霾日,而霾日SO2质量浓度仅在冬季略高于非霾日。选取2013年1月的连续灰霾日进行相关性分析,结果表明:污染组分主要来自当地排放(包括直接排放和二次形成),并受当地气象条件影响。此次灰霾过程中PM_(2.5)中的硫酸盐和硝酸盐主要来自气相反应,气态NO_2主要生成了气态HNO_3,而不是HNO_2。     

西宁市金属冶炼和压延加工业大气颗粒物排放清单

大气污染物排放清单是了解大气污染特征和控制对策的前提。根据排放因子方法,建立了2018年西宁市金属（包括黑色和有色金属）冶炼和压延加工业PM_2.5、PM₁₀大气污染物的排放清单,并对其时空分布特征和清单不确定性进行了分析。结果表明：西宁市黑色金属冶炼和压延加工业PM_2.5、PM₁₀的总排放量分别是4.88×10³、8.37×10³ t;该行业对PM_2.5、PM₁₀排放量贡献率最大的是城北区,分别为58.36%、49.61%。有色金属冶炼和压延加工业PM_2.5、PM₁₀的总排放量分别是1.85×10³、2.78×10³ t,该行业对PM_2.5、PM₁₀贡献率最大的是大通县,分别为53.51%、56.99%。黑色金属冶炼和压延加工业对PM_2.5、PM₁₀贡献率最大的产业是粗钢产业,贡献率分别是38.41%、30.28%。有色金属冶炼和压延加工业对PM_2.5、PM₁₀贡献率最大的是铝行业,贡献率分别是97.33%和98.01%。2个行业PM_2.5和PM₁₀的排放受月份影响较小,一天中09：00—18：00是排放高峰期。蒙特卡罗法模拟结果表明：黑色金属冶炼和压延加工业95%置信区间的不确定性较高,PM_2.5和PM₁₀的不确定性分别为-59.33%~58.55%和-47.51%~47.28%。     

Emissions of gaseous and particulate pollutants in a port and harbour region in India

Ports can generate large quantity of pollutants in the atmosphere due to various activities like loading and unloading,transportation, and construction operations. Determination of the character and quantity of emissions from individual sources is an essential step in any project to control and minimize the emissions.In this study a detailed emission inventory of total suspendedparticulate matter (TSP), particulate matter less than 10 m(PM₁₀), sulfur dioxide (SO₂) and nitrogen oxides (NO_x) for a port and harbour project near Mumbai is compiled. Results show that the total annual average contributions of TSP and PM₁₀ from all the port activitieswere 872 and 221 t yr^-1, respectively. Annual average emissions of gaseous pollutants SO₂ and NO_xwere 56 and 397 t yr^-1, respectively, calculatedby using emission factors for different port activities. The maximum TSP emission (419 t yr ^-1) was from paved roads, while the least (0.4 t yr^-1) was from bulk handling activity. The maximum PM₁₀ emission (123 t yr^-1) was from unpaved roads and minimum (0.2 t yr^-1) from bulk handling operations. Similarly the ratio of TSP and PM₁₀ emission was highest (5.18) from paved roads and least (2.17) from bulk handling operations. Regression relation was derivedfrom existing emission data of TSP and PM₁₀ from variousport activities. Good correlation was observed between TSP andPM₁₀ having regression coefficient >0.8.