区域大气细颗粒物化学组分及来源年变化趋势

利用单颗粒气溶胶质谱仪(SPAMS)于2018年1月1日—2019年12月31日对上海市浦东新区环境空气PM_2.5开展高时间分辨化学成分监测。结果表明，2019年监测点空气质量总体优于2018年，AQI达标率由74.8%升高至86.6%。通过对PM_2.5成分分类，最终确定了8类颗粒物，相较于2018年，2019年富钾颗粒物升幅较为明显，左旋葡聚糖、重金属和元素碳有小幅增加，其余各组分相对减少。对PM_2.5排放源分类分析显示，机动车尾气源占比>25%，其中2018年3月、2018年7月、2019年2和3月贡献超过40%；二次无机源和燃煤源呈现一定的季节变化特点，整体秋冬季高于春夏季，2019年燃煤源占比较2018年下降了41%；工业排放源2018年5和10月、2019年1和5月占比相对较高，其余各月份占比相对较为稳定。     

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。     

广州市空气可吸入性颗粒物的污染水平

报告了中美合作“广州市大气污染对儿童肺功能影响研究”课题可吸入性颗粒物的两年监测结果。用安德森双道采样器、Ｔｅｆｌｏｎ膜采集细颗粒物（＜２５μｍ,ＰＭ２５）和粗颗粒物（２５≤＜１０μｍ,ＰＭ２５１０）,两者之和为ＰＭ１０,每季度采１５天,每天采一个２４小时样品。结果表明,广州市城区大气可吸入性颗粒物的污染相当严重,尤其是细颗粒物（ＰＭ２５）的污染,应引起公众和政府有关部门的重视。     

Particle emission from heavy-duty engine fuelled with blended diesel and biodiesel

In this study, particulate matter (PM) were characterized from a place impacted by heavy-duty vehicles (Bus Station) fuelled with diesel/biodiesel fuel blend (B3) in the city of Londrina, Brazil. Sixteen priority polycyclic aromatic hydrocarbons (PAH) concentrations were analyzed in the samples by their association with atmospheric PM, mass size distributions and major ions (fluorite, chloride, bromide, nitrate, phosphate, sulfate, nitrite, oxalate; fumarate, formate, succinate and acetate; lithium, sodium, potassium, magnesium, calcium and ammonium). Results indicate that major ions represented 21.2% particulate matter mass. Nitrate, sulfate, and ammonium, respectively, presented the highest concentration levels, indicating that biodiesel may also be a significant source for these ions, especially nitrate. Dibenzo[a,h]anthracene and indeno[1,2,3,-cd]pyrene were the main PAH found, and a higher fraction of PAH particles was found in diameters lower than 0.25 μm in Londrina bus station. The fine and ultrafine particles were dominant among the PM evaluated, suggesting that biodiesel decreases the total PAH emission. However, it does also increase the fraction of fine and ultrafine particles when compared to diesel.     

Characteristic, composition, and sources of TSP investigated by HRTEM/EDS and ESEM/EDS

Total suspended particle (TSP) collected at the fifth floor of House Dust in Hunan University, China, was analyzed in terms of microscopic morphology and chemical composition. The fine particles (50?nm-2?μm) in the TSP were analyzed by a high-resolution transmission electron microscope equipped with an energy-dispersive X-ray analyzer (HRTEM/EDS). Results showed that the particles were in shapes of plate, irregular and agglomerate. Based on EDS results, these fine particulate matter was primarily composed of Fe-rich (35.82-61.29%), Ca-rich (30.18-36.77%) and Si-rich (18.95-32.28%) particles. Other elements mainly including Mg (0.47-4.97%), Al (0.45-14.57%), S (0.45-4.73%), K (1.13-2.13%) and Zn (0.67-3.85%) were also observed. The sources analysis indicated that the HRTEM particles mainly originated from coal combustion, traffic emission, vehicles exhaust emission and fugitive soil or cement particulate matter. The coarse particles (4-50?μm) were detected by environmental scanning electron microscopy coupled with energy-dispersive X-ray detector (ESEM/EDS). Based on a simple algorithm, ESEM particles were categorized into five groups: C-bearing (46.15%, 67% and 86.98%), Si + Ca-bearing (21.48?+?11.80%, 16.51?+?10.81% and 16.32?+?10.62%), Si + Al-bearing (20.06?+?12.40%, 20.16?+?11.22% and 15.31?+?11.25%), Si-bearing (34.40%, 26.92% and 27.15%) particles and aggregates, most of which exhibit obvious crystalline structure, and these ESEM particles mainly derived from vehicles exhaust emission, coal combustion, soil, and biomass burning, while the aggregates are indicative of atmospheric reaction progress. HRTEM/EDS and ESEM/EDS are mutual complementary in analyzing the characteristic and determining the sources of TSP.     

Characterisation of PM10, PM2.5 and Benzene Soluble Organic Fraction of Particulate Matter in an Urban Area of Kolkata, India

In this study, the relationship between inhalable particulate (PM₁₀), fine particulate (PM_2.5), coarse particles (PM_{2.5 – 10}) and meteorological parameters such as temperature, relative humidity, solar radiation, wind speed were statistically analyzed and modelled for urban area of Kolkata during winter months of 2003–2004. Ambient air quality was monitored with a sampling frequency of twenty-four hours at three monitoring sites located near traffic intersections and in an industrial area. The monitoring sites were located 3–5 m above ground near highly trafficked and congested areas. The 24 h average PM₁₀ and PM_2.5 samples were collected using Thermo-Andersen high volume samplers and exposed filter papers were extracted and analysed for benzene soluble organic fraction. The ratios between PM_2.5 and PM₁₀ were found to be in the range of 0.6 to 0.92 and the highest ratio was found in the most polluted urban site. Statistical analysis has shown a strong positive correlation between PM₁₀ and PM_2.5 and inverse correlation was observed between particulate matter (PM₁₀ and PM_2.5) and wind speed. Statistical analysis of air quality data shows that PM₁₀ and PM_2.5 are showing poor correlation with temperature, relative humidity and solar radiation. Regression equations for PM₁₀ and PM_2.5 and meteorological parameters were developed. The organic fraction of particulate matter soluble in benzene is an indication of poly aromatic hydrocarbon (PAH) concentration present in particulate matter. The relationship between the benzene soluble organic fraction (BSOF) of inhalable particulate (PM₁₀) and fine particulate (PM_2.5) were analysed for urban area of Kolkata. Significant positive correlation was observed between benzene soluble organic fraction of PM₁₀ (BSM10) and benzene soluble organic fraction of PM_2.5 (BSM2.5). Regression equations for BSM10 and BSM2.5 were developed.     

沈阳市冬季环境空气质量统计预报模型建立及应用

利用沈阳市2013年1—2月大气自动监测数据和同期气象资料,选取19项预报因子,采用逐步回归方法建立了沈阳市冬季环境空气质量统计预报模型,预报项目包括细颗粒物(PM2.5)、可吸入颗粒物(PM10)、二氧化硫(SO2)、二氧化氮(NO2)、一氧化碳(CO)日均浓度及臭氧(O3)日最大8 h平均浓度。2013年11月至2014年1月,应用该模型并结合人为经验修订,开展了沈阳市环境空气质量预报工作,预报结果与实测结果的对比验证结果表明,环境空气预测结果级别准确率达到79.1%,首要污染物准确率为73.6%。     

Possible markers of traffic-related emissions

Looking for robust indicators of motor vehicle emissions it has been found that brake wear and linings are significant contributors of Cu, Mo and Sb to air particulate matter. These trace elements, whose mutual ratios in airborne particulate matter resulted quite different from those in crustal material, appear to be available fingerprinting tools to identify the contribution of on-road vehicles to traffic-derived particulate matter. In this study, the results of analytical determinations of Cu, Mo and Sb on PM(10), PM(2.5), vegetation and brake dust samples, together with gas (CO, NOx) concentrations, are discussed. Highly significant correlations among Cu, Sb and Mo were observed in particulate matter from Palermo and between Cu-Sb and Cu-Mo at Catania. Further significant positive correlations have been found in pine needles from Palermo, Gela and in platanus leaves from Catania.     

Cycling of rare earth elements in the atmosphere in central Tokyo

Concentrations of 14 rare earth elements (REEs) in six size classes of airborne particulate matter (APM) (<0.43, 0.43-0.65, 0.65-1.1, 1.1-2.1, 2.1-11, and >11 μm) and in two different phases (suspended particulate and dissolved) in rainwater were determined by inductively coupled plasma mass spectrometry (ICP-MS). Positive Eu and Tb anomalies were observed in size-classified APM. These anomalies may be due to large emissions of Eu and Tb to the atmosphere resulting from the recent change in Japan from the use of cathode-ray tubes to plasma displays in television sets (Eu and Tb) and from the widespread use of magneto-optical disks (Tb). The light REEs were enriched in fine APM particles (diameter < 1.1 μm). Because compositions of La/Ce/Sm in fine APM (diameter < 1.1 μm) were similar to those in automobile catalyst, the light REE enrichment was attributed to automobile emissions. In contrast, the REE distribution pattern in the suspended particulate phase in rainwater was similar to that in coarse APM (diameter > 2.1 μm), and a positive Tb anomaly was observed, suggesting that coarse particles easily become trapped in rain droplets. A negative Eu anomaly was observed in the dissolved phase in rainwater, but not in APM or in the suspended particulate phase in rainwater. Unlike other REEs, Eu can exist as both bivalent and trivalent ions in nature, and Eu-selective dissolution from or adsorption onto the trapped particles of Eu might account for the negative anomaly. These results show that atmospheric REE cycling is affected by the physico-chemical properties of APM.     

喀什市2022年环境空气质量特征分析

为摸清喀什市环境空气质量变化特征,为管理部门进行污染精准管控提供科学参考,基于喀什市2022年环境空气自动监测数据开展分析研究。结果表明:2022年喀什市二氧化硫、二氧化氮、臭氧、一氧化碳年均质量浓度均优于国家二级标准。超标污染物主要为可吸入颗粒物和细颗粒物。喀什市细颗粒物、可吸入颗粒物浓度呈春、秋、冬季高,夏季低的季节特征。     

兰州市气溶胶中金属与非金属元素的污染规律

通过对兰州市空气飘尘中粗、细颗粒物上化学元素的分布规律与特征的分析 ,指出了细颗粒物 (PM2 .5 )是一些有毒有害元素的主要携带者。这是可以在肺泡沉积 ,并能直接进入血液循环 ,对人体产生危害的重要部分     

Source identification and apportionment of PM2.5 and PM2.5−10 in iron and steel scrap smelting factory environment using PMF,PCFA and UNMIX receptor models

To identify the potential sources responsible for the particulate matter emission from secondary iron and steel smelting factory environment, PM_2.5 and PM_2.5?10 particles were collected using the low-volume air samplers twice a week for a year. The samples were analyzed for the elemental and black carbon content using x-ray fluorescence spectrometer and optical transmissometer, respectively. The average mass concentrations were 216.26, 151.68, and 138. 62 μg/m³ for PM_2.5 and 331.36, 190.01, and 184.60 μg/m³ for PM_2.5?10 for the production, outside M1 and outside M2 sites, respectively. The same size resolved data set were used as input for the positive matrix factorization (PMF), principal component factor analysis (PCFA), and Unmix (UNMIX) receptor modeling in order to identify the possible sources of particulate matter and their contribution. The PMF resolved four sources with their respective contributions were metal processing (33 %), e-waste (33 %), diesel emission (22 %) and soil (12 %) for PM_2.5, and coking (50 %), soil (29 %), metal processing (16 %) and diesel combustion (5 %) for PM_2.5?10. PCFA identified soil, metal processing, Pb source, and diesel combustion contributing 45, 41, 9, and 5 %, respectively to PM_2.5 while metal processing, soil, coal combustion and open burning contributed 43, 38, 12, and 7 %, respectively to the PM_2.5?10. Also, UNMIX identified metal processing, soil, and diesel emission with 43, 42 and 15 % contributions, respectively for the fine fraction, and metal processing (71 %), soil (21 %) and unidentified source (1 %) for the coarse fraction. The study concluded that metal processing and e-waste are the major sources contributing to the fine fraction while coking and soil contributed to the coarse fraction within the factory environment. The application of PMF, PCFA and UNMIX receptor models improved the source identification and apportionment of particulate matter drive in the study area.     

Genotoxicity at Low Level Dose of Inspirable Urban Ambient Air Particulate in a Semiarid Regime

Samples of inspirable air particulate(inhalable + ingestable) were obtained at two urbanlocations in southern Argentina which differ in theirexposure to pollution by class B2 polynuclear aromatichydrocarbons (PAHs). Sample extracts were tested in vitro for induction of chromosomal aberrations incultured rat hepatocytes. The average induced amountof chromosomal aberrations did not vary amonggeographic locations, but significant differences wereidentified in samples near known emitting sources. Thedifferences were analyzed in the frame of a model ofthe emissions and their subsequent distribution andre-suspension from the soil and other surfaces. Theresults show that the rat hepatocyte test is sensitiveto genotoxic activity of the urban air particulate inthe low dose range of the tested fractions. Adequatemodels of human exposure to these materials shouldconsider emissions and re-suspension of pollutants bywind. The implications of these results on theformulation of policies of emission reduction, urbansoil management and the design of cancer epidemiologystudies are discussed.     

2020年江苏省机动车排放污染分布特征及与大气质量耦合性研究

依据生态环境部2021年6月发布的《排放源统计调查产排污核算方法和系数手册》,结合本地实测数据,在对汽油车颗粒物(PM)排放系数进行测算的基础上,核算了2020年江苏省机动车PM、氮氧化物(NO_(X))、挥发性有机物(VOC_(S))的排放总量,分析了机动车排放污染分布特征及与大气质量的耦合关系。结果表明:2020年江苏省机动车PM、NO_(X)、VOC_(S)排放量分别为0.5×10^(4),3.71×10^(5),1.17×10^(5) t。从区域分布来看,苏州、南京、无锡3市的3项污染物排放总量及NO_(X)、VOC_(S)排放量均位列前3位,PM排放量位列前3位的是苏州、徐州、无锡。从车型、燃料类型和排放阶段来看,国Ⅳ及以下排放标准的汽油小型客车是机动车VOC_(S)排放控制的重点,国Ⅲ排放标准的重型柴油货车是机动车PM和NO_(X)排放控制的重点。分析区域机动车PM排放量与大气中PM_(2.5)来源解析结果的耦合关系,其间存在不同程度的正相关性,控制机动车污染对改善大气环境会产生积极成效,南京、徐州和盐城3市的成效会尤为明显。     

Ecotoxicity and genotoxicity assessment of exhaust particulates from diesel-powered buses

Diesel exhaust is one of the major sources of fine and ultra-fine particulate matter in urban air. Toxicity of diesel-powered engine emissions has been quite widely assessed; however, much less information is available on their ecotoxicity. In our study, the kinetic version of the Vibrio fischeri bioluminescence inhibition bioassay based on the ISO 21338:2010 standard was used to characterise the ecotoxicity of diesel-powered buses. It is a direct contact test in which solid samples are tested in suspension and test organisms are in direct contact with toxic particles. The age of the selected buses fell into a wide range; the oldest one was produced in 1987. Diesel engines of different emission standards (Euro0–Euro4) were included. Measured EC₅₀ values of Euro0–Euro1 engine emissions fell into the same range, 1.24–0.96 μg ml^?1, respectively. On the contrary, emission of Euro4 vehicle proved to be non-toxic. Genotoxic potential of the samples was also estimated, using the colorimetric SOS-chromotest?. Genotoxicity was detected also for Euro0 and Euro1 buses, showing correlation with the ecotoxic potential. The fact that the particulates from Euro4 vehicles did not show ecotoxic/genotoxic effect implies that replacing old Euro1 and Euro2 buses can be a highly effective solution for reducing environmental hazard of automotive emissions. The whole-aerosol testing method is a cheap alternative that can be used in engine developments and emission control.     

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。     

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.     

Development of Spatial and Temporal Emission Inventory for Crop Residue Field Burning

Accurate emission inventory (EI) is the foremost requirement for air quality management. Specifically, air quality modeling requires EI with adequate spatial and temporal distributions. The development of such EI is always challenging, especially for sporadic emission sources such as biomass open burning. The country of Thailand produces a large amount of various crops annually, of which rough (unmilled) rice alone accounted for over 30 million tonnes in 2007. The crop residues are normally burned in the field that generates large emissions of air pollutants and climate forcers. We present here an attempt at a multipollutant EI for crop residue field burning in Thailand. Available country-specific and regional primary data were thoroughly scrutinized to select the most realistic values for the best, low and high emission estimates. In the base year of 2007, the best emission estimates in Gigagrams were as follows: particulate matter as PM_2.5, 128; particulate matter as PM₁₀, 143; sulfur dioxide (SO₂), 4; carbon dioxide (CO₂), 21,400; carbon monoxide (CO), 1,453; oxides of nitrogen (NO_x), 42; ammonia (NH₃), 59; methane (CH₄), 132; non-methane volatile organic compounds (NMVOC), 108; elemental carbon (EC), 10; and organic carbon (OC), 54. Rice straw burning was by far the largest contributor to the total emissions, especially during the dry season and in the central part of the country. Only a limited number of EIs for crop residue open burning were reported for Thailand but with significant discrepancies. Our best estimates were comparable but generally higher than other studies. Analysis for emission uncertainty, taking into account possible variations in activity data and emission factors, shows considerable gaps between low and high estimates. The difference between the low and high EI estimates for particulate matter and for particulate EC and OC varied between −80% and +80% while those for CO₂ and CO varied between −60% and +230%. Further, the crop production data of Thailand were used as a proxy to disaggregate the emissions to obtain spatial (76 provinces) and temporal (monthly) distribution. The provincial emissions were also disaggregated on a 0.1° × 0.1° grid net and to hourly profiles that can be directly used for dispersion modeling.     

The organic composition of diesel particulate matter, diesel fuel and engine oil of a non-road diesel generator

Diesel-powered equipment is known to emit significant quantities of fine particulate matter to the atmosphere. Numerous organic compounds can be adsorbed onto the surfaces of these inhalable particles, among which polycyclic aromatic hydrocarbons (PAHs) are considered potential occupational carcinogens. Guidelines have been established by various agencies regarding diesel emissions and various control technologies are under development. The purpose of this study is to identify, quantify and compare the organic compounds in diesel particulate matter (DPM) with the diesel fuel and engine oil used in a non-road diesel generator. Approximately 90 organic compounds were quantified (with molecular weight ranging from 120 to 350), which include alkanes, PAHs, alkylated PAHs, alkylbenzenes and alkanoic acids. The low sulfur diesel fuel contains 61% alkanes and 7.1% of PAHs. The identifiable portion of the engine oil contains mainly the alkanoic and benzoic acids. The composition of DPM suggests that they may be originated from unburned diesel fuel, engine oil evaporation and combustion generated products. Compared with diesel fuel, DPM contains fewer fractions of alkanes and more PAH compounds, with the shift toward higher molecular weight ones. The enrichment of compounds with higher molecular weight in DPM may be combustion related (pyrogenic).     

Submicron particle characteristics of atmospheres in a long highway tunnel

This study used a scanning mobility particle sizer (SMPS) to measure and categorize submicron atmospheric particles in the 14–737-nm size range for ambient and urban roadside air and for air in the Hsuehshan Tunnel (12.9 km), Taiwan. Principal component analysis, traffic flow, and particle size distributions were used to identify the emission characteristics of light-duty vehicles (LDV) with the SMPS data. In the Hsuehshan Tunnel, the particle size from the majority of emissions discharged by LDV is approximately 20–60 nm, and the maximum particle number can reach up to 2.5?×?10⁵. In contrast, submicron particle size distribution for urban roadsides is mostly 14–200 nm, and the maximum particle number is approximately 4?×?10⁴ with the particle number for most particle sizes being below 1,200. The submicron particle size distribution at the ambient air station was unimodal with a mode sizes at 30–50 nm with the maximum particle number of 3,000.