Nitrogenous and carbonaceous aerosols in PM2.5 and TSP during pre-monsoon: Characteristics and sources in the highly polluted mountain valley

This study reports for the first time a comprehensive analysis of nitrogenous and carbonaceous aerosols in simultaneously collected PM_2.5 and TSP during pre-monsoon (March–May 2018) from a highly polluted urban Kathmandu Valley (KV) of the Himalayan foothills. The mean mass concentration of PM_2.5 (129.8 µg/m³) was only ~25% of TSP mass (558.7 µg/ m³) indicating the dominance of coarser mode aerosols. However, the mean concentration as well as fractional contributions of water-soluble total nitrogen (WSTN) and carbonaceous species reveal their predominance in find-mode aerosols. The mean mass concentration of WSTN was 17.43±4.70 µg/m³ (14%) in PM_2.5 and 24.64±8.07 µg/m³ (5%) in TSP. Moreover, the fractional contribution of total carbonaceous aerosols (TCA) is much higher in PM_2.5 (~34%) than that in TSP (~20%). The relatively low OC/EC ratio in PM_2.5 (3.03 ± 1.47) and TSP (4.64 ± 1.73) suggests fossil fuel combustion as the major sources of carbonaceous aerosols with contributions from secondary organic aerosols. Five-day air mass back trajectories simulated with the HYSPLIT model, together with MODIS fire counts indicate the influence of local emissions as well as transported pollutants from the Indo-Gangetic Plain region to the south of the Himalayan foothills. Principal component analysis (PCA) also suggests a mixed contribution from other local anthropogenic, biomass burning, and crustal sources. Our results highlight that it is necessary to control local emissions as well as regional transport while designing mitigation measures to reduce the KV's air pollution.     

基于无人机垂直观测塔克拉玛干沙漠一次沙尘污染过程研究

利用多旋翼无人机于2021年7月30—31日对塔克拉玛干沙漠的塔中（飞行高度0~2000 m）、民丰地区（飞行高度0~1000 m）不同粒径 颗粒物浓度、气温、相对湿度和风速进行垂直观测,结合多地面站点、再分析资料、后向轨迹模型和卫星遥感数据,对沙尘污染过程中的影响 因素、颗粒物垂直分布特征及污染成因进行了分析.结果表明：①近地面低气温、高相对湿度、高风速的气象条件有利于沙尘污染事件的发生,通过无人机探测数据发现高相对湿度有利于颗粒物吸湿增长,气温和风速的上升能够加强大气对流运动,有利于污染物的输送.②在沙尘污染期间,塔中地区PM₁、PM_2.5和PM₁₀的浓度分别为0.8~45.7、1.0~267.0和1.0~588.7 μg·m^-3;民丰地区PM₁、PM_2.5和PM₁₀的浓度分别为21.5~126.9、39.6~263.6和48.5~520.6 μg·m^-3.③在沙尘污染期间,塔克拉玛干沙漠腹地颗粒物组成以粗颗粒物为主,南缘则以细颗粒物为主.民丰地区PM₁/PM_2.5比值（0.48~0.55）和PM_2.5/PM₁₀比值（0.55~0.83）在同时刻均高于塔中地区（PM₁/PM_2.5为0.18~0.33, PM_2.5/PM₁₀为0.33~0.51）.④天气形势和后向轨迹表明,此次污染主要由西风环流导致,气团分别从北面翻越天山和东面绕道进入塔克拉玛干沙漠,携带了塔克拉玛干沙漠东部地区沙尘颗粒和新疆北部人为污染物.⑤CALIPSO卫星数据表明,此次污染中气溶胶存在于海拔1~8 km之间,主要集中在低层（消光系数在 海拔1.0~2.2 km左右最大）.气溶胶类型为沙尘气溶胶、污染沙尘气溶胶和烟雾气溶胶,其中,沙尘气溶胶占主要部分.     

基于排放清单和实地测试的工业VOCs排放特征:以郑州市高新区为例

基于本地污染源调查,同时对重点工业行业进行实地采样测试,建立了郑州市高新区工业VOCs排放清单及组分清单,并评估了 VOCs各组分的臭氧生成潜势(OFP)和二次有机气溶胶生成潜势(SOAp).结果表明,2017年郑州市高新区工业源VOCs排放总量为4 566.0 t,橡胶和塑料制品业、设备制造业和有色金属业是排放量最大的3个行业,排放量分别为1 924.2、1 396.3和813.4 t;各VOCs组分中,烷烃占比最大(40.9％),其次是含氧VOCs(32.2％)和芳香烃(20.3％);异丙醇、正十二烷、甲苯、甲基环己烷和丙酮是排放量最大的5种物质;OFP总量为8 753.8 t,最大贡献源和VOCs种类分别为设备制造业和芳香烃;SOAp总量为643.0 t,贡献较大的排放源为设备制造业和铝箔制造业,烷烃和芳香烃是两种主要贡献组分.     

不同浓度臭氧对单颗粒气溶胶化学组成的影响

为探讨高浓度臭氧(O_3)对气溶胶生成与老化过程的影响,本研究利用单颗粒气溶胶质谱仪(SPAMS)于2018年10月在广东省鹤山大气环境超级监测站进行观测.观测期间根据O_3浓度的高低,定义了高臭氧浓度(P_H)时段和低臭氧浓度(P_L)时段,其中P_H时段O_3平均浓度为117μg·m~(-3),P_L时段平均浓度为25μg·m~(-3).依据化学组成的不同,观测期间单颗粒主要包含老化元素碳颗粒(EC-aged)、二次颗粒(Sec)和老化有机碳颗粒(OC-aged).P_H时段单颗粒总数(348 085)高于P_L时段(224 797),且P_H时段Sec颗粒(37.1%)的占比显著高于P_L时段(27.8%),而EC-aged颗粒(32.1%)则低于P_L时段(44.1%),OC-aged颗粒(13.5%)略高于P_L时段(10.4%).含硝酸盐(nitrate)和硫酸盐(sulfate)的颗粒数浓度在P_H时段有显著的昼夜变化,而在P_L时段无昼夜变化,Sec颗粒和EC-aged颗粒中硝酸盐和硫酸盐的峰面积P_H时段高于P_L时段,表明在P_H时段通过二次反应过程生成硝酸盐和硫酸盐的量多于P_L时段.此外,Sec颗粒中硝酸盐和硫酸盐的峰面积显著高于EC-aged颗粒,表明Sec颗粒的老化程度更深.本研究选取了乙酸根(~(59)CH_3CO~-_2)和乙二醛(~(73)C_2HO~-_3)来代表醛酮化合物在单颗粒气溶胶中的变化特征.P_H时段Sec和OC-aged颗粒中~(59)CH_3CO~-_2和~(73)C_2HO~-_3的数浓度与峰面积显著高于P_L时段,且在P_H时段呈现显著的日变化特征,峰值出现在O_3浓度高峰后2 h,在P_L时段峰值显著降低,该变化趋势与Sec和OC-aged颗粒的数浓度变化特征相同,表明高浓度O_3有利于VOCs氧化生成~(59)CH_3CO~-_2和~(73)C_2HO~-_3.综上,高臭氧浓度时段光化学反应较强,二次气溶胶组分的含量显著增加,光化学反应增强是P_H时段臭氧浓度升高和单颗粒中二次组分增加的主要原因.     

基于工艺过程的金属包装业VOCs污染特征

识别金属包装业挥发性有机化合物(volatile organic compounds,VOCs)产生和排放节点,定量分析不同类型生产工艺所排放VOCs的物种及含量,结合最大增量反应活性法和修正的气溶胶生成系数法对行业二次污染进行核算.结果表明,金属包装业排放的VOCs主要为苯系物、醇类、酮类和酯类,苯系物和醇类在不同类型工序和排污节点中贡献较大,酮类和酯类贡献相对较少,单物种浓度最高的VOCs为正丁醇,浓度达269.08mg·m~(-3);生产线与相应的排气筒之间VOCs物种浓度相关性较好,但物种种类存在差异;行业的O_3和二次有机气溶胶(secondary organic aerosol, SOA)生成潜势(以O_3/VOCs和SOA/VOCs计)分别为(3.09±0.94)g·g~(-1)和(2.58±1.99)g·g~(-1),苯系物和内全涂烘干工序为O_3和SOA的主要前体物和首要生成节点.     

北京冬季PM2.5中有机气溶胶的化学特征和来源解析

为探讨北京冬季大气细颗粒物（PM_2.5）中有机气溶胶的浓度水平、分布特征和来源变化,对2016年11月10日~12月10日采集的北京大气PM_2.5样品进行气相色谱-质谱测定,定量了129种颗粒有机物（POM）,约占有机物总量的（9.3±1.2）%.其中含量最高的是糖类,仅左旋葡聚糖即可占到定量有机物的18%,其次是正构烷酸、正构烷烃、二元羧酸和多环芳烃.根据POM示踪物的变化特征,分析了供暖和生物质燃烧传输对北京冬季有机气溶胶的影响.相比于非供暖期间,供暖期间化石燃料示踪物藿烷的质量浓度及在有机物中的占比都明显升高,各组分间的分布也更加趋向于燃煤排放的特征.正构烷烃主峰碳数和奇偶分布的变化,反映了化石燃料贡献增强的影响.生物质燃烧示踪物左旋葡聚糖的浓度权重轨迹（CWT）模型结果表明,北京周围区域的秸秆燃烧污染会通过传输影响北京的有机气溶胶组成.利用分子示踪-化学质量平衡（MM-CMB）模型对2016年北京冬季有机碳（OC）进行了来源解析,并与2006年的结果进行比较,以定量10年间各污染来源贡献发生的变化.2016年与2006年相比,机动车对有机气溶胶贡献明显增加,燃煤和木材燃烧的贡献则大幅度降低,餐饮排放的贡献也不容忽视.因此,控制机动车和餐饮源的排放对改善北京冬季PM_2.5污染问题至关重要.     

Microbial aerosol particles in four seasons of sanitary landfill site: Molecular approaches, traceability and risk assessment

Landfill sites are regarded as prominent sources of bioaerosols for the surrounding atmosphere. The present study focused on the emission of airborne bacteria and fungi in four seasons of a sanitary landfill site. The main species found in bioaerosols were assayed using high-throughput sequencing. The SourceTracker method was utilized to identify the sources of the bioaerosols present at the boundary of the landfill site. Furthermore, the health consequences of the exposure to bioaerosols were evaluated based on the average daily dose rates. Results showed that the concentrations of airborne bacteria in the operation area (OPA) and the leakage treatment area (LTA) were in the range of (4684 ± 477)–(10883 ± 1395) CFU/m³ and (3179 ± 453)–(9051 ± 738) CFU/m³, respectively. The average emission levels of fungal aerosols were 4026 CFU/m³ for OPA and 1295 CFU/m³ for LTA. The landfill site received the maximum bioaerosol load during summer and the minimum during winter. Approximately 41.39%– 86.24% of the airborne bacteria had a particle size of 1.1 to 4.7 µm, whereas 48.27%– 66.45% of the airborne fungi had a particle size of more than 4.7 µm. Bacillus sp., Brevibacillus sp., and Paenibacillus sp. were abundant in the bacterial population, whereas Penicillium sp. and Aspergillus sp. dominated the fungal population. Bioaerosols released from the working area and treatment of leachate were the two main sources that emerged in the surrounding air of the landfill site boundary. The exposure risks during summer and autumn were higher than those in spring and winter.     

Control of exhaled SARS-CoV-2-laden aerosols in the interpersonal breathing microenvironment in a ventilated room with limited space air stability

The Coronavirus Disease 2019 (COVID-19) highlights the importance of understanding and controlling the spread of the coronavirus between persons. We experimentally and numerically investigated an advanced engineering and environmental method on controlling the transmission of airborne SARS-CoV-2-laden aerosols in the breathing microenvironment between two persons during interactive breathing process by combining the limited space air stability and a ventilation method. Experiments were carried out in a full-scale ventilated room with different limited space air stability conditions, i.e., stable condition, neutral condition and unstable condition. Two real humans were involved to conducted normal breathing process in the room and the exhaled carbon dioxide was used as the surrogate of infectious airborne SARS-CoV-2-laden aerosols from respiratory activities. A correspondent numerical model was established to visualize the temperature field and contaminated field in the test room. Results show that the performance of a ventilation system on removing infectious airborne SARS-CoV-2-laden aerosols from the interpersonal breathing microenvironment is dependent on the limited space air stability conditions. Appropriate ventilation method should be implemented based on an evaluation of the air condition. It is recommended that total volume ventilation methods are suitable for unstable and neutral conditions and local ventilation methods are preferable for stable conditions. This study provides an insight into the transmission of airborne SARS-CoV-2-laden aerosols between persons in ventilated rooms with different limited space air stability conditions. Useful guidance has been provided to cope with COVID-19 in limited spaces.     

广州PM2.5化学组分特征及其与气象因子的关系

于2012年12月—2013年12月在广州城区(市站)和东部郊区(九龙)开展为期一年的PM2.5样品采集,并同步收集气象因子和气态污染物质量浓度等数据.结果表明,PM2.5中主要化学组分为有机质(OM)和硫酸盐(SO2-4),分别占市站和九龙PM2.5质量浓度的49.4%和15.2%及57.0%和17.3%.碳质气溶胶(OM和EC)贡献接近50%,二次无机气溶胶(SO2-4、NO-3和NH+4总和,SIA)贡献超过30%.由于以机动车尾气为代表的移动污染源在城市区域贡献较大,市站[NO-3]/[SO2-4]比值显著高于九龙.两个站点[NH+4]/[SO2-4]摩尔质量比均高于1.5,表明观测期间广州市干季大气处于富铵状态.市站和九龙站硫氧化率(SOR)和氮氧化率(NOR)的时空变化趋势与O3类似,表明大气光化学过程是影响广州市SOR和NOR的重要因素.相对湿度低于65%时,SOR和NOR均较高;温度对SOR和NOR的影响有显著的城郊差异.降雨对PM2.5及各化学组分浓度有显著去除作用.     

Secondary organic aerosols in Jinan, an urban site in North China: Significant anthropogenic contributions to heavy pollution

Secondary organic aerosols(SOAs) are an important component of particulates, but whether biogenic SOAs(BSOAs) or anthropogenic SOAs(ASOAs) are the dominant contributors to haze pollution remains poorly characterized. In this study, particulate samples were collected from September 2014 to August 2015 at an urban site in Jinan, which is the capital of Shandong Province and a typical city in the North China Plain. The PM2.5 samples were analyzed for BSOA(isoprene(SOAI) and monoterpenes(SOAM)) and ASOA(aromatic(SOAA)) tracers. The concentrations of the SOAAtracer(1.1 ± 1.0 ng/m3) were lowest, and those of SOAItracers(41.8 ± 86.2 ng/m3) were highest, with the concentrations of SOAMtracers(19.4 ± 9.9 ng/m3) being intermediate. The SOAItracers were more abundant in the summer and less abundant in the winter. Both SOAIand SOAMincreased with increasing ozone level but decreased with increasing NOx level. Correlation analysis revealed a good correlation between 2,3-dihydroxy-4-oxopentanoic acid and levoglucosan levels in three seasons. These results suggested that biomass burning activities occurring in the NCP can enhance the emissions of aromatics and should be controlled, especially in the autumn and winter. SOA tracers were classified according to pollution degree, and the results showed that as pollution increases, the contributions of SOAAincrease. These results indicate that reducing anthropogenic emissions is necessary to prevent SOA pollution, especially during heavy pollution episodes.