燃煤锅炉湿法脱硫烟气中颗粒物排放特征

选择北京市典型燃煤锅炉进行研究,结果表明:烟气中可凝结颗粒物在总颗粒物中占有较高比例,供热燃煤锅炉总颗粒物排放水平明显高于电厂燃煤锅炉;颗粒物中水溶性离子含量较高,供热燃煤锅炉硫酸根比例尤其显著;烟气总颗粒物中存在大量不稳定的易被氧化的组分;同为燃煤源,不同的烟气净化工艺排放的PM2.5组分特征差异明显;现有标准和技术规范存在不足,无法满足全面、准确监测污染源排放总颗粒物的实际需要。建议建立总颗粒物、可凝结颗粒物的监测技术规范,全面测算燃煤锅炉硫、氮化合物排放情况,科学评估脱硫及脱硝效率。     

基于颗粒物光量子雷达的颗粒物排放实时溯源及应用

在大气污染治理中,传统探测方式在局地大气颗粒物排放源的精准定位和实时溯源方面还有所不足。自主研发的1 550 nm波长颗粒物光量子雷达,具备探测效率高、人眼安全等特点,360°水平扫描一周仅需8.5 min。基于该雷达水平扫描监测,结合迭代拼接法和新发展的颗粒物示踪系数及污染源定位方法,可准确识别并定位出当地的污染排放源位置。对于部分污染排放定位溯源案例,结合多图展现并分析了颗粒物排放、扩散、传输、消散过程中的烟羽变化,并结合卫星图像确认了相应工业生产和建筑扬尘等典型颗粒物排放源。地面监测数据分析了部分污染源对监测站点颗粒物浓度的影响。该雷达通过低仰角、可重复性的快速扫描,结合符合颗粒物扩散规律的分析过程,在颗粒物污染实时溯源定位方面展现了极高的准确性。     

Verifying emission factors and national POPs emission inventories for the UK using measurements and modelling at two rural locations

Different approaches are used to verify the adequacy of emission factors (EFs) and their use in emission inventories of persistent organic pollutants (POPs). The applicability of EFs was tested using atmospheric dispersion modelling to predict atmospheric concentrations of polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), dibenzo-p-dioxins (PCDDs) and dibenzofurans (PCDFs) and resulting toxic equivalents (SigmaTEQ) and particulate matter <10 microm (PM(10)) in two rural locations in northern England (UK). The modelling was based on general assumptions of fuel composition, consumption and heating needs to simulate emissions of POPs from the domestic burning of coal and wood where ambient measurements were made in the winter of 1998. The model was used to derive the local contribution to ambient air concentrations, which were estimated independently based on comparative air measurements. The results support the hypothesis that in both villages, the majority of PAHs and the lower chlorinated PCDFs were locally released. The situation for PCBs and polychlorinated naphthalenes (PCNs) was different. While the EFs show the release of both compound groups from the domestic burning of coal and wood, the ambient levels of these "legacy POPs" in the villages were still clearly dominated by other sources. Rural areas relying mainly on fossil fuels can exceed the proposed UK ambient air quality standard for benzo[a]pyrene during winter. The measured EFs were then used to estimate the importance of the domestic burning of coal and wood to national emission inventories for these compound classes. Extrapolations to the UK suggest that the domestic burning of pure wood and coal were minor emitters for chlorinated POPs but contributed strongly to PAH and PM(10) levels in 2000. Finally, the UK's national POPs emission inventories based on source inventories and EF, as used here, were compared to estimates derived using the increase in atmospheric concentration of selected POPs.     

质谱直接测量法解析盐城市大气细颗粒物来源

为全面了解盐城市大气颗粒物的组成,摸清以PM2.5为首要污染物的来源,说清其化学组分和源贡献率,于2014年12月16日00:00—2014年12月21日09:00,利用在线单颗粒气溶胶质谱仪,对盐城市细颗粒物进行实时在线源解析。结果表明,盐城首要污染物为燃煤,占比为23.7%,其次是机动车尾气,占比为18.3%,第三位是扬尘,占总颗粒数的15.7%,生物质燃烧占比为14.8%位列第四,工业工艺源、二次无机源和其他源贡献率相对较小。     

克拉玛依市中心城区颗粒物中多环芳烃污染特征

在克拉玛依市中心城区布设4个采样点,在供暖期和非供暖期分别同步采集4个点位大气中不同粒径的颗粒物,采用HPLC进行分析并计算2个采样期内PM_(10)和PM_(2.5)中多环芳烃(PAHs)的浓度和种类。结果表明:中心城区供暖期PM_(10)中PAHs浓度为56.19 ng/m3,PM_(2.5)中PAHs浓度为48.85 ng/m3;中心城区非供暖期PM_(10)中PAHs浓度为18.86 ng/m~3,PM_(2.5)中PAHs浓度为14.53 ng/m~3。不同采样期PM_(10)和PM_(2.5)中PAHs浓度变化趋势相同,均为供暖期明显大于非供暖期。中心城区供暖期大气颗粒物吸附的PAHs以4环以下的组份为主,非供暖期则是5~6环的高环数组份偏多。分析结果表明克拉玛依市中心城区供暖期颗粒物中PAHs来源于燃煤排放叠加机动车排放,与中心城区集中供热锅炉关系密切;非供暖期则是以机动车排放污染为主。     

基于环境库兹涅茨曲线特征的桂林市大气环境状况研究

根据2006年-2012年桂林市经济发展主要指标和大气环境污染指标的统计资料，分析了该市人均 GDP 与SO2、NO x、烟（粉）尘排放量及 PM10质量浓度和 API优良率等大气环境指标的相关关系，建立了经济发展与大气环境指标之间的模拟曲线。模拟结果表明，桂林市处于工业时期，随着人均GDP增加，SO2和烟（粉）尘排放得到了一定程度的缓解，而NO x 和 PM10排放从长期看还处于上升趋势。建议改善能源结构，调整产业结构和工业布局，制定财税激励政策，开展环境综合整治，加大机动车排污防治力度，进一步控制大气污染。     

不同木柴在两种条件下燃烧生成的颗粒物中多环芳烃的排放特性研究

将马尾松、赤桉、甜叶桉树和锦熟黄杨四种木柴,使用普通家用木柴燃烧加热炉在两种条件下进行燃烧,采集燃烧所排放的颗粒物样品并分析,获得了颗粒物中多环芳烃(Polycyclic Aromatic Hydrocarbons简写为PAHs)的排放因子及单个多环芳烃化合物的分布规律。结果显示:在颗粒物中检测出的多环芳烃化合物主要是分子量较大并被称为基因致毒性类的多环芳烃化合物,实验还发现:在四种木柴中,马尾松具有最高的多环芳烃化合物的排放因子,其次是赤桉和锦熟黄杨,最低的是甜叶桉树。两种不同的燃烧条件相比,慢燃烧比快燃烧所产生的总多环芳烃化合物和基因致毒性多环芳烃化合物的量都要高。     

太原市大气颗粒物中重金属的污染特征及来源解析

为了解太原市采暖期大气颗粒物不同粒径中重金属的污染特征及其来源,于2012年10月—2013年2月对环境空气中颗粒物采样,用原子吸收分光光度法测定样品中Fe、Pb、Cu、Ni、Cr、Cd、Mn、Zn等8种元素的含量。结果表明,太原市采暖期重金属浓度从高到低依次为FePbMnZnCrCuNiCd。重金属Pb、Mn、Zn、Ni、Cd主要富集在PM2.5中;Cr主要富集在PM10中;Cu主要富集在PM5中;Fe主要在粒径大于2.5μm的粗粒子中富集。除Zn外,其他7种元素浓度均表现为灰霾期采暖期采暖前。通过主因子分析表明,太原市大气颗粒物中重金属主要来源于冶金、有机合成工业、燃煤、汽车尾气、土壤尘等。     

Characterization of PM10-bound polycyclic aromatic hydrocarbons in the ambient air of Spanish urban and rural areas

Urban areas constitute major pollution sources due to anthropogenic activities located in these areas. Among the legislated air pollutants, the particulate matter with an aerodynamic diameter less than or equal to 10 microns (PM10) and polycyclic aromatic hydrocarbons (PAH) are controlled under Directive 2008/50/EC and Directive 2004/107/EC, respectively due to their adverse health effects. A study was carried out at four urban and rural Spanish areas during the warm and cold seasons in 2008-2009 to quantify 19 PAH associated with the atmospheric PM10 by gas chromatography-mass spectrometry-mass spectrometry detection (GC-MS-MS) with the internal standard method. The particle-bound composition of the analysed PAH was 5 and 10 times greater in industrial and urban areas, respectively when compared to those measured in rural areas. The highest PAH concentrations during the cold period were possibly due to the additional contribution of domestic heating sources and meteorological conditions such as low temperature and solar irradiation. The use of molecular diagnostic ratios indicated that the possible, major PAH pollution sources in the most polluted areas were pyrogenic sources, mainly attributed to petroleum combustion sources (motor vehicle emissions and crude oil combustion). Petrogenic sources related to evaporative emissions also seemed to contribute in the most polluted area during the warm period. Those dates with high carcinogenic character according to the benzo(a)pyrene equivalent (BaP-eq) were also possibly attributed to petroleum combustion sources.     

Emission Inventory for an Industrial Area of India

The paper presents an emission inventory for Cochin, which is a highly industrialized area situated in the southern part of India. A proper emission inventory is very important for planning pollution control programmes, particularly in coastal sites like Cochin, where environmental situations are of growing concern owing to their typical meterorological conditions. In a systematic way the sources are broadly classified as point, line and area sources. The data on emissions from industries, fuel consumption for vehicular and domestic activities along with the respective emission factors are used for estimating the emissions. The study reveals that industrial sources are mainly responsible for emissions of particulate matter, oxides of sulphur and ammonia in the region. Automobiles are the prime sources of hydrocarbons, oxides of nitrogen and carbon monoxide emitting 95%, 77% and 70% respectively of their total emissions, while the contribution from domestic sources is not very significant.     

Receptor modeling for source apportionment of polycyclic aromatic hydrocarbons in urban atmosphere

This study reports source apportionment of polycyclic aromatic hydrocarbons (PAHs) in particulate depositions on vegetation foliages near highway in the urban environment of Lucknow city (India) using the principal components analysis/absolute principal components scores (PCA/APCS) receptor modeling approach. The multivariate method enables identification of major PAHs sources along with their quantitative contributions with respect to individual PAH. The PCA identified three major sources of PAHs viz. combustion, vehicular emissions, and diesel based activities. The PCA/APCS receptor modeling approach revealed that the combustion sources (natural gas, wood, coal/coke, biomass) contributed 19–97% of various PAHs, vehicular emissions 0–70%, diesel based sources 0–81% and other miscellaneous sources 0–20% of different PAHs. The contributions of major pyrolytic and petrogenic sources to the total PAHs were 56 and 42%, respectively. Further, the combustion related sources contribute major fraction of the carcinogenic PAHs in the study area. High correlation coefficient (R ² > 0.75 for most PAHs) between the measured and predicted concentrations of PAHs suggests for the applicability of the PCA/APCS receptor modeling approach for estimation of source contribution to the PAHs in particulates.     

大气颗粒物手工比对监测体系滤膜称量质控技术探讨

健全大气颗粒物手工比对监测体系是"十三五"环境空气自动监测质量管理的一项重点任务,其中颗粒物滤膜的称量直接影响手工监测数据质量。研究调研了国内各级环保部门所属环境监测机构颗粒物滤膜称量工作情况,结合国内外方法标准、技术规范等,重点探讨了称量实验室环境、称量设备、称量影响因素等滤膜称量质控要点,并针对环境管理与监测需求对大气颗粒物手工比对监测滤膜称量质控提出建议。     

乌鲁木齐市冬季大气颗粒物PM_(10) 和PM_(2.5)污染水平及相关性研究

为研究乌鲁木齐市冬季采暖期间大气颗粒物污染特征,通过采样和在线监测二种手段分析了2015年1~2月大气颗粒物样品,采用重量法分析颗粒物质量浓度,并对其相关性进行分析。结果表明:依据《环境空气质量标准》(GB 3095-2012),采样期间乌鲁木齐市大气PM_(10) 和PM_(2.5)的日均质量浓度均超过了国家二级标准,颗粒物污染严重;PM_(10) 和PM_(2.5)存在显著相关性,PM_(2.5)和PM_(10) 浓度的比值均大于0.5,采暖期PM2.5对乌鲁木齐市大气颗粒物贡献显著。     

上海市浦东新区大气细颗粒物中重金属污染特征及来源解析

于2017年对浦东城区和郊区大气PM2.5中的重金属特征和来源进行了分析。结果表明,K、Fe、Na、Ca、Mg、Al等矿物元素为浦东新区PM2.5中含量最高的金属元素,其中K的年均值为297.3 ng/m^3。浦东城区的不同元素在季节变化上呈现较为不同的变化规律,郊区的金属元素值大部分呈现春季先逐月下降,在夏、秋季有起伏波动,在10月之后逐渐上升;沙尘+道路源+建筑扬尘、煤燃烧、工业排放、金属冶炼、船舶排放、海盐+垃圾焚烧+生物质燃烧为浦东城区PM2.5中重金属元素的6大类主要来源。其中沙尘+道路源+建筑扬尘对Ca的贡献率为82.7%,煤燃烧对As的贡献率为86.6%,工业排放对SO4^2-的贡献率达到65.9%,金属冶炼对Cr的贡献率为75.7%,船舶排放对V的贡献率为97.5%、海盐+垃圾焚烧+生物质燃烧对Cl^-的贡献率为93.0%。煤燃烧和金属冶炼主要来自于西部方向。船舶排放分布在长江口及其延伸带。浦东新区PM2.5中重金属元素的质量浓度与本地源排放强度、外界传输和大气扩散条件均有密切关系。     

Variations in wood burning organic marker concentrations in the atmospheres of four European cities

The particulate emissions from biomass burning are a growing concern due to the recent evidence of their ubiquitous and important contribution to the ambient aerosol load. A possible strategy to apportion the biomass burning share of particulate matter is the use of organic molecular tracers. Anhydrosugars (levoglucosan, mannosan and galactosan), together with two organic acids (dehydroabietic and pimaric acids), were previously reported as organic markers for particulate wood burning emissions. These five compounds were studied in four European cities (Helsinki, Copenhagen, Birmingham and Oporto), at both a Roadside and an Urban Background station, during a summer and a winter campaign in the fine (PM(2.5)) and the coarse (PM(10-2.5)) size-fractions of the ambient aerosol. Levoglucosan concentrations were highest in the city of Oporto. In winter, levoglucosan was more present in the fine fraction but in summer, concentrations were similar in both size fractions. Levoglucosan concentrations in the fine size fraction were higher in winter, but no seasonal differences were observed for the coarse size fraction. The lack of difference between the Roadside and Urban Background levoglucosan concentrations points towards a regional nature of this type of pollution. Wood burning was estimated to contribute to about 3.1% of the winter PM(10) mass in Oporto, and to 3.7% in Copenhagen. Mannosan followed the trends exhibited by levoglucosan. The ratio between the levoglucosan and mannosan concentrations allowed determination of a preference for softwood over hardwood in all four cities. Galactosan, pimaric acid and dehydroabietic acid were found to be minor compounds.     

Investigation into presence of atmospheric particulate matter in Marikana, mining area in Rustenburg Town, South Africa

An investigation to find out presence of particulate matter in Marikana, a mining area in Rustenburg town, South Africa, was carried out in the months of August and November of 2008. Samples were collected for measurements of particulate matter (PM) of particle diameters of PM10, PM2.5, and PM1. After gravimetric analysis of daily measurements, it was found that PM10 concentration values ranged between 3 and 9 ??g/m³, PM2.5 concentration values ranged between 16 and 26 ??g/m³, and PM1 concentration values ranged between 14 and 18 ??g/m³ for the month of August 2008. For the month of November, it was found that PM10 concentration values ranged between 2 and 8 ??g/m³, PM2.5 concentration values ranged between 0 and 5 ??g/m³, and PM1 concentration values ranged between 4 and 15 ??g/m³. This study was undertaken as preliminary work having in mind that mining activities could be emitting high levels of particulate matter in the atmosphere which might be degrading the quality of the air. It was observed, however, that the daily particulate matter especially of PM10 emitted were quite low when compared to laid down International Air Quality Standards. The standards did not give guidelines for particulate matter of diameter 2.5 ??m. It was concluded that particulate matter came from three major sources: platinum mining, domestic biomass burning, and traffic emissions due to fuel burning.     

乌鲁木齐采暖期TSP、PM10、PM5、PM2.5中重金属污染水平评价

采用石墨炉原子吸收分光光度法、双道原子荧光光谱法研究乌鲁木齐市采暖期前期与后期不同粒径大气颗粒物(TSP、PM_(10)、PM_5、PM_(2.5))中Hg、As、Zn、Pb、Ni等5种重金属元素的质量浓度,并对重金属污染水平进行评价。Hg质量浓度为0.3~5.7 ng/m3;As质量浓度为15.3~122.5 ng/m~3;Zn质量浓度为298.0~1 686.5 ng/m~3;Pb质量浓度为0.5~88.8 ng/m~3;Ni质量浓度为10.4~25.5 ng/m~3。Igeo计算得出采暖期后期的TSP、PM_(10)、PM_5、PM_(2.5)中各重金属Igeo值均高于采暖期前期,其中Hg元素为严重污染;富集因子分析得出Hg、Zn元素的EFi值大于10,说明这些元素是人为源贡献。通过研究乌鲁木齐市不同时期、不同粒径大气颗粒物中各种重金属污染状况,为乌鲁木齐大气污染治理提供科学支持。     

基于新空气质量标准的全国大气环境承载力评价

随着中国环境问题特别是大气环境问题的凸显,环境承载能力研究成为国内各界关注的热点。采用大气污染物年均质量浓度与新的空气质量标准比较的方法即超标倍数法,对全国330个地级城市进行大气环境承载力评价。评价结果表明,有70%的城市大气环境超载,大气环境承载形势严峻。超载最严重地区为京津冀及周边区域,长三角地区、中部大部分地区。PM2.5为大多数重点城市超载的首要污染物。通过对比大气环境承载指数与污染物排放总量、污染排放强度、人口、第二产业、地形、气象等因素的相关关系发现,不同地区主要影响因素不同,应该采取分区域、季节等差别化手段控制污染物排放,提高环境承载能力。     

A new indicator of fireworks emissions in Rochester, New York

In ambient particle source apportionment studies, data for holidays such as July 4 (US Independence Day) are normally removed because of the high concentrations of chemical species and unusually high particle mass concentrations that are due to fireworks. Many cultures celebrate events with fireworks. A near real-time measurement that could indicate fireworks would be useful in indicating their impact on air quality. Commonly monitored ambient pollutants include PM_2.5, CO, SO₂, O₃, 10–500-nm particle number, and black carbon (BC). Using a two-wavelength aethalometer, another parameter, delta-C (UVBC_370?nm–BC_880?nm, aethalometer), can be calculated. These variables were continuously monitored during July 1–7, 2005–2010, in Rochester, New York. High delta-C values are normally associated with biomass combustion particles. However, statistically higher delta-C values were observed on Independence Day compared to the other period. Back trajectory analysis showed transport of local fireworks smoke to the sampling site on the night of July 4. An enhanced correlation between delta-C and BC during the fireworks episodes suggests changes from the usual BC sources. Fireworks emissions changed the ambient carbonaceous particulate species during these intervals. The delta-C value was found to be a readily measured indicator of fireworks emissions during periods when wood combustion was not likely to be present and provides a tool for monitoring such emissions where they might be more common such as amusement parks.     

The use of semipermeable membrane devices as passive samplers to determine persistent organic compounds in indoor air

In the study reported here semipermeable membrane devices (SPMDs) were used to sample 28 PAHs and 19 PCBs in the gas phase in 15 single-family houses located in an area where domestic wood burning is widespread. Eight of the households used wood burning appliances whereas the others used other systems for residential heating. Most of the studied compounds were found in the houses: the PAHs at levels that were similar to or slightly higher than published SPMD-sampled levels for background or urban sites in Sweden, and the PCBs at levels that were somewhat lower than those recently found in both indoor and outdoor urban locations. A principal component analysis revealed that wood-burning heating systems may contribute to PAHs in indoor air. The sources may be emissions indoors or penetration from outdoors. The convenience of SPMD technology facilitates its use for semi-quantitative screening and monitoring of various persistent organic compounds indoors in dwellings and working environments.