龙凤山大气气溶胶散射特性观测分析

利用2018年龙凤山区域大气本底站(简称龙凤山站)气溶胶散射系数、PM₁₀质量浓度及常规气象观测资料,研究了东北本底地区气溶胶散射系数的变化特征.结果表明,2018年龙凤山站3个波长下气溶胶散射系数的均值为(194.1±202.4)Mm^-1(450 nm)、(133.4±139.2)Mm^-1(550 nm)、(81.8±85.3)Mm^-1(700 nm).龙凤山地区散射系数具有明显的日变化特征,且不同季节的日变化特征具有较大区别.龙凤山地区地处相对洁净的背景地区,气溶胶散射系数水平相对较低,春季受局地及长距离风沙的影响散射系数均值较高,冬季东北地区采暖燃烧排放量比较大,大气层相对稳定,不利于气溶胶污染物的扩散,冬季气溶胶散射系数最高.夏秋季受湿沉降与植被条件的影响气溶胶散射系数最低.散射系数与PM₁₀质量浓度相关性较好,相关系数r为0.82.龙凤山PM₁₀的质量散射效率为3.6 m²·g^-1(550 nm).2018年龙凤山PM₁₀气溶胶的散射Angstrom指数(SAE)平均值为1.96±0.25,表明在观测期间气溶胶主要是以较小的粒子主导,夏季的SAE最大,秋季的SAE最低,春季和冬季居中.     

青藏高原东缘冬季PM2.5中碳组分特征和来源解析

于2017年冬季12月13—21日在青藏高原东缘理塘地区分昼夜采集PM_2.5样品,并用DRI2001A热光碳分析仪测定了有机碳(OC)和元素碳(EC)的质量浓度,研究青藏高原PM_2.5中碳组分的化学特征及主要来源,以期为理塘地区制定污染排放政策提供参考。结果表明,2017年冬季青藏高原东缘理塘地区PM_2.5平均质量浓度为44.34μg·m^?3,OC和EC的质量浓度为12.72μg·m^?3和3.85μg·m^?3,分别占PM_2.5质量浓度的29.61%和8.96%。通过经验公式,计算得到总碳气溶胶(TCA)质量浓度为24.20μg·m^?3,占PM_2.5的54.84%,说明碳质气溶胶对青藏高原东缘理塘地区PM_2.5有着十分重要的贡献。OC和EC在白天和夜间都有较高的相关性(相关系数分别为0.74和0.91),表明OC和EC的来源基本一致,受燃烧源影响较大。其中白天的相关系数低于夜间,说明青藏高原东缘理塘地区白天碳组分来源相对复杂。昼夜浓度对比显示,青藏高原东缘理塘地区PM_2.5白天和夜间的质量浓度分别为53.88μg·m^?3和33.44μg·m^?3,OC和EC浓度白天高于夜间,表明白天人为排放相对较高。冬季观测期间,PM_2.5中二次有机碳(SOC)昼夜浓度分别为1.11μg·m^?3和3.03μg·m^?3,分别占OC质量浓度的7.09%、26.59%,表明青藏高原东缘理塘城区白天碳组分主要为一次源。利用PMF 5.0软件对理塘城区碳组分进行进一步的解析,结果显示燃煤和生物质燃烧的混合源对总碳(TC)的贡献高达47.84%,占比最高;其次是汽车尾气和柴油车尾气源,贡献率分别为28.62%和23.54%。     

中国典型沿海城市冬季PM2.5中碳组分的污染特征及来源解析

为研究中国典型沿海城市冬季PM_2.5中碳组分的污染特征及来源,于2018年12月5日—2019年1月30日分别在天津(TJ)、上海(SH)和青岛(QD)同步采集PM_2.5样品。结果表明,天津、上海和青岛PM_2.5的平均浓度分别为(116.96±66.93)、(31.21±25.62)、(74.93±54.60)μg·m^-3,OC和EC的空间分布均为天津(18.69±7.95)μg·m^-3和(4.98±2.08)μg·m^-3>青岛(16.45±8.94)μg·m^-3和(2.01±1.04)μg·m^-3>上海(7.28±3.11)μg·m^-3和(1.05±1.25)μg·m^-3。3个站点的OC和EC均呈现较好的相关性,表明OC和EC具有相似的来源;OC/EC比值范围在2.37—7.53、5.47—46.41和4.77—13.36之间,证明各采样点均存在二次有机碳(SOC)的生成;采用最小R²法(MRS)估算SOC浓度,得到3个采样点SOC的平均质量浓度为(5.09±4.68)、(3.90±1.65)、(4.21±4.31)μg·m^-3,分别占OC总量的27.2%、55.8%和19.5%,其中上海的SOC在OC中的占比最大,说明上海二次有机碳污染较为严重,这主要归因于冬季严重污染源排放和有利的二次转化气象条件,而天津和青岛的碳组分主要来自污染源的直接排放。主成分分析(PCA)结果发现,天津PM_2.5中碳组分主要来源于道路尘、生物质燃烧和机动车尾气,上海PM_2.5中碳组分主要来源于生物质燃烧、道路扬尘和机动车尾气。青岛PM_2.5中碳组分主要来源于道路扬尘、机动车尾气。后向轨迹聚类分析表明,来自西北方向的气团对天津的影响较大,PM_2.5和碳组分的浓度值最大;而对上海而言,主要受北方气溶胶经过海面又传输回上海的气团的影响;青岛站点主要受华北地区污染物和本地排放源的影响。     

Mass concentrations and temporal profiles of PM10, PM2.5 and PM1 near major urban roads in Beijing

Mass concentrations of PM₁₀, PM_2.5 and PM₁ were measured near major roads in Beijing during six periods: summer and winter of 2001, winter of 2007, and periods before, during and after the 2008 Beijing Olympic Games. Since the control efforts for motor vehicles helped offset the increase of emissions from the rapid growth of vehicles, the averaged PM_2.5 concentrations at roadsides during the sampling period between 2001 and 2008 fluctuated over a relatively small range. With the implementation of temporary traffic control measures during the Olympics, a clear “V” shaped curve showing the concentrations of particulate matter and other gaseous air pollutants at roadsides over time was identified. The average concentrations of PM₁₀, PM_2.5, CO and NO decreased by 31.2%, 46.3%, 32.3% and 35.4%, respectively, from June to August; this was followed by a rebound of all air pollutants in December 2008. Daily PM₁₀ concentrations near major roads exceeded the National Ambient Air Quality Standard (Grade II) for 61.2% of the days in the non-Olympic periods, while only for 12.5% during the Olympics. The mean ratio of PM_2.5/PM₁₀ near major roads remained relatively stable at 0.55 (±0.108) on non-Olympic days. The ratio decreased to 0.48 (±0.099) during the Olympics due to a greater decline in fine particles than in coarse-mode PM. The ratios PM₁/PM_2.5 fluctuated over a wide range and were statistically different from each other during the sampling periods. The average ratios of PM₁/PM_2.5 on non-Olympic days were 0.71.     

天津城区秋冬季黑碳气溶胶观测与分析

利用天津大气边界层观测站2010年9月—2011年1月黑碳气溶胶、PM2.5质量浓度、大气能见度及常规气象观测数据,研究天津城区秋冬季黑碳气溶胶污染特征.结果表明,天津秋冬季黑碳气溶胶质量浓度均值7.24μg.m-3和6.46μg.m-3,分别占PM2.5质量的9.42%和7.98%,其吸收作用分别贡献大气消光的17.2%和17.6%;采用最大频数浓度法计算黑碳浓度本底值为2.50μg.m-3;黑碳浓度的日变化特征与天气过程有关,雾和霾天气下黑碳浓度较高,降水利于清除黑碳污染,秋季高浓度黑碳除局地源污染外,可能还与河北、山西、天津等地燃烧秸秆有关.     

辽宁西南典型城市冬季大气细颗粒物水溶性无机离子污染特征及来源解析

本研究于2018年12月3日-2019年1月1日在辽宁省西南典型城市葫芦岛市和朝阳市分别布设3个城区采样点,在区域传输点龙屯水库布设1个采样点,采集大气细颗粒物PM2.5样品(n=201).使用离子色谱检测样品中的Na+、Mg2+、Ca2+、K+、NH4+、SO42-、F-、Cl-和NO3-的质量浓度.观测期间PM2....     

天津市夏季PM2.5中碳组分时空变化特征及来源解析

为研究天津市夏季PM_2.5中碳组分的时空变化特征及来源,于2019年7—8月设立2个点位分昼夜采集天津市PM_2.5样品,并测定了其中有机碳(OC)和元素碳(EC)的含量。结果表明,城区PM_2.5、OC和EC浓度日均值分别为(53.4±20.8)μg·m^-3、(8.72±2.56)μg·m^-3和(1.67±0.90)μg·m^-3,郊区PM_2.5、OC和EC浓度日均值分别为(54.2±24.5)μg·m^-3、(7.54±2.50)μg·m^-3和(1.82±1.06)μg·m^-3;白天PM_2.5、OC、EC的平均浓度分别为(47.3±16.1)μg·m^-3、(8.7±2.1)μg·m^-3和(1.5±0.6)μg·m^-3,夜间PM_2.5、OC、EC的平均浓度分别为(60.2±26.2)μg·m^-3、(7.5±2.9)μg·m^-3和(2.0±1.2)μg·m^-3。OC浓度表现为城区高于郊区,白天高于夜间;EC及PM_2.5浓度表现为郊区高于城区,夜间高于白天。OC/EC比值分析得,城区(6.04)高于郊区(5.08);白天(6.58)高于夜间(4.54)。城区OC与EC相关性弱于郊区,白天OC与EC相关性弱于夜间。采用EC示踪法与MRS模型对SOC含量进行估算,得到白天与夜间SOC浓度分别为(5.71±1.35)μg·m^-3和(3.81±1.20)μg·m^-3,白天SOC污染比夜间严重。丰度分析与主成分分析的结果表明,天津市夏季城郊区PM_2.5中碳组分均主要来源于燃煤和机动车尾气排放。     

Enrichment and transfer of polycyclic aromatic hydrocarbons (PAHs) through dust aerosol generation from soil to the air

● Compositional patterns of PAHs in dust aerosol vary from soil during dust generation. ● The EF of PAH in dust aerosol is affected by soil texture and soil PAH concentration. ● The sizes of dust aerosol play an important role in the enrichment of HMW-PAHs. Polycyclic aromatic hydrocarbons (PAHs) are major organic pollutants in soil. It is known that they are released to the atmosphere by wind via dust aerosol generation. However, it remains unclear how these pollutants are transferred through the air/soil interface. In this study, dust aerosols were generated in the laboratory using soils (sandy loam and loam) with various physicochemical properties. The PAH concentrations of these soils and their generated dust aerosol were measured, showing that the enrichment factors (EFs) of PAHs were affected by soil texture, PAH contamination level, molecular weight of PAH species and aerosol sizes. The PAHs with higher EFs (6.24–123.35 in dust PM_2.5; 7.02–47.65 in dust PM₁₀) usually had high molecular weights with more than four aromatic rings. In addition, the positive correlation between EFs of PAHs and the total OC_aerosol content of dust aerosol in different particle sizes was also statistically significant (r = 0.440, P < 0.05). This work provides insights into the relationship between atmospheric PAHs and the contaminated soils and the transfer process of PAHs through the soil-air interface.     

How aerosol direct effects influence the source contributions to PM2.5 concentrations over Southern Hebei,China in severe winter haze episodes

The aerosol direct effects result in a 3%–9% increase in PM_2.5 concentrations over Southern Hebei. These impacts are substantially different under different PM_2.5 loadings. Industrial and domestic contributions will be underestimated if ignoring the feedbacks. Beijing-Tianjin-Hebei area is the most air polluted region in China and the three neighborhood southern Hebei cities, Shijiazhuang, Xingtai, and Handan, are listed in the top ten polluted cities with severe PM_2.5 pollution. The objective of this paper is to evaluate the impacts of aerosol direct effects on air quality over the southern Hebei cities, as well as the impacts when considering those effects on source apportionment using three dimensional air quality models. The WRF/Chem model was applied over the East Asia and northern China at 36 and 12 km horizontal grid resolutions, respectively, for the period of January 2013, with two sets of simulations with or without aerosol-meteorology feedbacks. The source contributions of power plants, industrial, domestic, transportation, and agriculture are evaluated using the Brute-Force Method (BFM) under the two simulation configurations. Our results indicate that, although the increases in PM_2.5 concentrations due to those effects over the three southern Hebei cities are only 3%–9% on montly average, they are much more significant under high PM_2.5 loadings (~50 μg·m⁻³ when PM_2.5 concentrations are higher than 400 μg m⁻³). When considering the aerosol feedbacks, the contributions of industrial and domestic sources assessed using the BFM will obviously increase (e.g., from 30%–34% to 32%–37% for industrial), especially under high PM_2.5 loadings (e.g., from 36%–44% to 43%–47% for domestic when PM_2.5>400 μg·m⁻³). Our results imply that the aerosol direct effects should not be ignored during severe pollution episodes, especially in short-term source apportionment using the BFM.     

南京秋季大气PM2.5中类腐殖质的光学性质与来源分析

类腐殖质(humic-like substances, HULIS)是水溶性有机碳(WSOC)中具有吸光特性的重要组分,对空气质量、气候变化和人体健康均有重要影响.尽管目前对HULIS的研究很多,但不同方法分离机理不同,对于HULIS的分离与测定仍然缺乏统一的标准,针对HULIS分离方法的研究很少.固相萃取法(solid phase extraction, SPE)因其操作简单、分离效果较好而被广泛应用,但对于低浓度样品仍存在检出限较高、回收率较低的问题,且很少有人关注提纯过程中流程空白所包含的含碳组分及其吸光能力.本研究通过调整活化溶液(0.01 mol·L^-1 HCl溶液+甲醇+2%NH₃H₂O/MeOH)与洗脱溶液(2%NH₃H₂O/MeOH)用量的比例对提纯方法进行优化.结果表明,应用优化后的方法对流程空白进行测量时,检出限(MDL)降低到0.035 mg·L^-1以下,精密度RSD <5.41%(n=20),标准品回收率达到95%,在保证回收率的情况下减少了流程空白,提高了样品的精密度,使测定浓度较低的HULIS含量成为可能.为了探究生物质燃烧期间含碳组分的光学特性和来源特征,本研究对2017年10月6日至11月9日南京北郊秋季大气气溶胶样品进行采集.采样期间PM_2.5的浓度为(87.9±43.7)μg·m^-3,WSOC和类腐殖质碳(HULIS-C)的浓度分别为(4.2±2.3)μg·m^-3和(3.6±2.0)μg·m^-3,HULIS-C占WSOC的比例为47.3%,是WSOC中的重要组成部分.本研究还对HULIS在330—400 nm波段的吸光进行测定,使用Angstrom指数(absorption angstrom exponent,AAE)进行表征,得到采样期间AAE的值为2—7,说明HULIS污染主要来自二次转化.后向轨迹结果表明,重污染期间污染物来源为本地生物质燃烧和区域或者长距离气团的输送.     

Effects of a diesel oxidation catalyst on gaseous pollutants and fine particles from an engine operating on diesel and biodiesel

The effects of a diesel oxidation catalytic (DOC) converter on diesel engine emissions were investigated on a diesel bench at various loads for two steady-state speeds using diesel fuel and B20. The DOC was very effective in hydrocarbon (HC) and CO oxidation. Approximately 90%–95% reduction in CO and 36%–70% reduction in HC were realized using the DOC. Special attention was focused on the effects of the DOC on elemental carbon (EC) and organic carbon (OC) fractions in fine particles (PM_2.5) emitted from the diesel engine. The carbonaceous compositions of PM_2.5 were analyzed by the method of thermal/optical reflectance (TOR). The results showed that total carbon (TC), OC and EC emissions for PM_2.5 from diesel fuel were generally reduced by the DOC. For diesel fuel, TC emissions decreased 22%–32% after the DOC depending on operating modes. The decrease in TC was attributed to 35%–97% decrease in OC and 3%–65% decrease in EC emissions. At low load, a significant increase in the OC/EC ratio of PM_2.5 was observed after the DOC. The effect of the DOC on the carbonaceous compositions in PM_2.5 from B20 showed different trends compared to diesel fuel. At low load, a slight increase in EC emissions and a significant decrease in OC/EC ratio of PM_2.5 after DOC were observed for B20.     

Physical and chemical processes of wintertime secondary nitrate aerosol formation

The UCD/CIT model was modified to include a process analysis (PA) scheme for gas and particulate matter (PM) to study the formation of secondary nitrate aerosol during a stagnant wintertime air pollution episode during the California Regional PM_2.5/PM₁₀ Air Quality Study (CRPAQS) where detailed measurements of PM components are available at a few sites. Secondary nitrate is formed in the urban areas from near the ground to a few hundred meters above the surface during the day with a maximum modeled net increase rate of 4 μg·m^-3·d^-1 during the study episode. The secondary nitrate formation rate in rural areas is lower due to lower NO₂. In the afternoon hours, near-surface temperature can be high enough to evaporate the particulate nitrate. In the nighttime hours, both the gas phase N₂O₅ reactions with water vapor and the N₂O₅ heterogeneous reactions with particle-bound water are important for secondary nitrate formation. The N₂O₅ reactions are most import near the surface to a few hundred meters above surface with a maximum modeled net secondary nitrate increase rate of 1 μg·m^-3·d^-1 and are more significant in the rural areas where the O₃ concentrations are high at night. In general, vertical transport during the day moves the nitrate formed near the surface to higher elevations. During the stagnant days, process analysis indicates that the nitrate concentration in the upper air builds up and leads to a net downward flux of nitrate through vertical diffusion and a rapid increase of surface nitrate concentration.     

Long-term trends of fine particulate matter and chemical composition in the Pearl River Delta Economic Zone (PRDEZ), China

Understanding the trends in PM_2.5 levels is essential for formulating clean air plans. This paper analyzes PM_2.5 data from various published sources for the years 2000 to 2010 in the Pearl River Delta Economic Zone (PRDEZ). The long-term variation in PM_2.5 mass concentration is analyzed. Results show that PM_2.5, organic carbon (OC), elemental carbon (EC), and SO42− show a similar trend, increasing before 2005 and then decreasing slightly. The annual average PM_2.5 concentration ranges from 49.1 μg·m⁻³ in 2000 to 64.3 μg·m⁻³ in 2010, with a peak of 84.1 μg·m⁻³ in 2004. None of these 11 years meets the new National Ambient Air Quality standard (NAAQS) for PM_2.5 (35 μg·m⁻³). Overall average concentrations of OC, EC, and SO42− are 13.0, 6.5, and 11.8 μg·m⁻³, respectively. NO3− and NH4+ respectively have concentrations of 1.5 μg·m⁻³ and 2.9 μg·m⁻³ in 2000 and 6.4 μg·m⁻³ and 5.3 μg·m⁻³ in 2010, with a statistically significant average annual trend of+ 0.2 μg·m⁻³·yr⁻¹ and+ 0.1 μg·m⁻³·yr⁻¹. In certain geographic regions, OC and EC contribute most of the PM_2.5, while in other regions secondary water-soluble ions are more important. In general, OC and SO42− are the dominant components of PM_2.5, contributing 20.6% and 18.6%, respectively. These results provide, for the first time, a better understanding of the long-term PM_2.5 characteristics and trends, on a species-by-species basis, in the PRDEZ. The results indicate that PM_2.5 abatement needs to prioritize secondary species.     

川南四座城市PM2.5化学组分污染特征及其源解析

为探究川南地区大气气溶胶中化学组分与来源特征,于2015年9月—2016年8月在四川盆地南部4个典型代表城市(泸州、内江、宜宾、自贡)采集了226个PM_2.5样品,对PM_2.5的质量浓度和主要化学组分(水溶性离子和碳质组分)进行测定,并利用颗粒物源解析受体模型对PM_2.5来源进行解析.结果表明:川南地区PM_2.5日均浓度为46.4—68.0μg·m^-3,均高于国家环境空气质量标准年均PM_2.5限值(35.0μg·m^-3).OC、EC和水溶性二次离子(SO₄^2-、NO₃-和NH₄+)分别占PM_2.5质量的15.7%—22.8%、4.2%—6.4%和28.6%—55.8%.PM_2.5及其主要化学组分浓度有显著的季节变化,即冬季浓度显著高于其他季节,夏季浓度最低.泸州除夏季外,其他季节SO₄2-、NO₃-同源性较好;其他城市在冬季,SO₄2-、NO₃-同源性较好.NH₄+主要存在形式为NH₄NO₃、(NH₄)2SO₄、NH₄HSO₄.OC、EC来源复杂,主要为机动车源、煤燃烧源和生物质燃烧源.川南地区PM_2.5的来源主要受8种因子影响,按总体贡献排序依次为:二次硫酸盐、生物质燃烧、工业源、二次硝酸盐、机动车源、煤燃烧、道路尘埃和建筑尘埃.此外,相比较而言,机动车源贡献在泸州市较凸显,煤燃烧源贡献在宜宾市较凸显.     

Relations between indoor and outdoor PM2.5 and constituent concentrations

Factors impacting indoor-outdoor relations are introduced. Sulfate seems a fine tracer for other non-volatile species. Particulate nitrate and ammonium desorb during outdoor-to-indoor transport. OC load increases during the transport due to sorption of indoor SVOCs. Outdoor PM_2.5 influences both the concentration and composition of indoor PM_2.5. People spend over 80% of their time indoors. Therefore, to assess possible health effects of PM_2.5 it is important to accurately characterize indoor PM_2.5 concentrations and composition. Controlling indoor PM_2.5 concentration is presently more feasible and economic than decreasing outdoor PM_2.5 concentration. This study reviews modeling and measurements that address relationships between indoor and outdoor PM_2.5 and the corresponding constituent concentrations. The key factors in the models are indoor-outdoor air exchange rate, particle penetration, and deposition. We compiled studies that report I/O ratios of PM_2.5 and typical constituents (sulfate (SO₄^2-), nitrate (NO₃^-), ammonium (NH₄⁺), elemental carbon (EC), and organic carbon (OC), iron (Fe), copper (Cu), and manganese (Mn)). From these studies we conclude that: 1) sulfate might be a reasonable tracer of non-volatile species (EC, Fe, Cu, and Mn) and PM_2.5 itself; 2) particulate nitrate and ammonium generally desorb to gaseous HNO₃ and NH₃ when they enter indoors, unless, as seldom happens, they have strong indoor sources; 3) indoor-originating semi-volatile organic compounds sorb on indoor PM_2.5, thereby increasing the PM_2.5 OC load. We suggest further studies on indoor-outdoor relationships of PM_2.5 and constituents so as to help develop standards for healthy buildings.     

Response of organic aerosol characteristics to emission reduction in Yangtze River Delta region

● The emission reduction causes significant change in organic aerosol composition. ● The atmospheric oxidizing capacity improved during emission reduction. ● The mixed oxygenated organic aerosol contributed higher during emission reduction. Organic aerosol (OA) is a major component of atmospheric particulate matter (PM) with complex composition and formation processes influenced by various factors. Emission reduction can alter both precursors and oxidants which further affects secondary OA formation. Here we provide an observational analysis of secondary OA (SOA) variation properties in Yangtze River Delta (YRD) of eastern China in response to large scale of emission reduction during Chinese New Year (CNY) holidays from 2015 to 2020, and the COVID-19 pandemic period from January to March, 2020. We found a 17% increase of SOA proportion during the COVID lockdown. The relative enrichment of SOA is also found during multi-year CNY holidays with dramatic reduction of anthropogenic emissions. Two types of oxygenated OA (OOA) influenced by mixed emissions and SOA formation were found to be the dominant components during the lockdown in YRD region. Our results highlight that these emission-reduction-induced changes in organic aerosol need to be considered in the future to optimize air pollution control measures.     

Identify the contribution of vehicle non-exhaust emissions: a single particle aerosol mass spectrometer test case at typical road environment

● A single particle observation was conducted in a high traffic flow road environment. ● Major particle types were vehicle exhausts, coal burning, and biomass burning. ● Contribution of non-exhaust emissions was calculated via PMF. ● Proportion of non-exhaust emissions can reach 10.1 % at road environment. A single particle aerosol mass spectrometer (SPAMS) was used to accurately quantify the contribution of vehicle non-exhaust emissions to particulate matter at typical road environment. The PM_2.5, black carbon, meteorological parameters and traffic flow were recorded during the test period. The daily trend for traffic flow and speed on TEDA Street showed obvious “M” and “W” characteristics. 6.3 million particles were captured via the SPAMS, including 1.3 million particles with positive and negative spectral map information. Heavy Metal, High molecular Organic Carbon, Organic Carbon, Mixed Carbon, Elemental Carbon, Rich Potassium, Levo-rotation Glucose, Rich Na, SiO₃ and other categories were analyzed. The particle number concentration measured by SPAMS showed a good linear correlation with the mass concentrations of PM_2.5 and BC, which indicates that the particulate matter captured by the SPAMS reflects the pollution level of fine particulate matter. EC, ECOC, OC, HM and crustal dust components were found to show high values from 7:00–9:00 AM, showing that these chemical components are directly or indirectly related to vehicle emissions. Based on the PMF model, 7 major factors are resolved. The relative contributions of each factor were determined: vehicle exhaust emission (44.8 %), coal-fired source (14.5 %), biomass combustion (12.2 %), crustal dust (9.4 %), ship emission (9.0 %), tires wear (6.6 %) and brake pads wear (3.5 %). The results show that the contribution of vehicle non-exhaust to particulate matter at roadside environment is approximately 10.1 %. Vehicle non-exhaust emissions are the focus of future research in the vehicle pollutant emission control field.     

PM2.5 concentration declining saves health expenditure in China

● Monthly hospitalization expenses are sensitive to increases in PM_2.5 exposure. ● The increased PM_2.5 causes patients with CHD and LRI to stay longer in the hospital. ● The impact of PM_2.5 on total expenses for stroke is greater in southern China. ● Males may be more sensitive to air pollution than females. Air pollution has been a severe issue in China. Exposure to PM_2.5 has adverse health effects and causes economic losses. This study investigated the economic impact of exposure to PM_2.5 pollution using monthly city-level data covering 88.5 million urban employees in 2016 and 2017. This study mainly focused on three expenditure indicators to measure the economic impact considering lower respiratory infections (LRIs), coronary heart disease (CHD), and stroke. The results show that a 10 µg/m³ increase in PM_2.5 would cause total monthly expenses of LRIs, CHD, and stroke to increase by 0.226%, 0.237%, and 0.374%, respectively. We also found that LRI, CHD, and stroke hospital admissions increased significantly by 10%, 8.42%, and 5.64%, respectively. Furthermore, the total hospital stays of LRIs, CHDs, and strokes increased by 2.49%, 2. 51%, and 1.64%, respectively. Our findings also suggest heterogeneous impacts of PM_2.5 exposures by sex and across regions, but no statistical evidence shows significant differences between the older and younger adult subgroups. Our results provide several policy implications for reducing unequal public health expenditures in overpolluted countries.     

天津市采暖季PM2.5组分消光特性及来源分析

为了解天津市采暖季细颗粒物组分对能见度的影响、明确消光组分来源,对天津市2017年采暖季大气PM_2.5样品进行了为期一月的连续采集,并测定水溶性离子、有机碳和元素碳的含量,通过修正IMPROVE方程研究了细颗粒物消光特性,并采用主成分分析—多元线性回归模型(PCA-MLR)对其来源进行解析,同时应用潜在源贡献因子(PSCF)和浓度权重轨迹(CWT)明确PM_2.5质量浓度的潜在污染源区域。结果表明,OC、EC以及SNA(NO3^?、NH₄⁺、SO₄^2?)的生成和积累对于能见度的下降具有重要影响,且能见度随SOR和NOR二次转化程度的升高而下降;2017年天津市采暖季日均消光系数为(294.56±262.89)Mm^?1,其中OM(34.86%)、硝酸盐(22.84%)、硫酸盐(11.59%)和EC(11.54%)为主要消光组分,硝酸盐和硫酸盐的增加对于能见度的下降起主要影响作用;根据PCA分析结果可知,天津市采暖季PM_2.5中的碳组分和水溶性离子主要来源于燃煤、生物质燃烧(68%),受扬尘(22%)和海盐(8%)的影响较小;区域传输分析结果表明天津市采暖季PM_2.5污染源潜在区域主要分布在河北中西部、河南北部、山西北部和内蒙古中部、西部。     

Observation of black carbon aerosol in Beijing, 2003

The objective of this study was to determine the black carbon concentration in Beijing in 2003. The aerosol properties were measured using an Aethalometer and a tapered element oscillating microbalance (TEOM) on the roof of the Physics Building of Peking University (39.99° N, 116.31° E) from July to August 2003 and from November 2003 to January 2004. The average black carbon (BC) concentrations in the summer and winter were 8.80 and 11.4 μg/m³, respectively. During winter, two different cyclone cut offs were installed at the inlet of an aethalometer. The BC mass concentration in TSP, PM₁₀, and PM_2.5 were obtained. The results indicated that in winter aerosol, 90% of BC exited in PM₁₀ and 82.6% of BC exited in PM_2.5. The BC in PM₁₀ accounted for 5.11% of the PM₁₀ mass.