Evaluation of the influence of El Niño–Southern Oscillation on air quality in southern China from long-term historical observations

•Strong ENSO influence on AOD is found in southern China region. •Low AOD occurs in El Niño but high AOD occurs in La Niña events in southern China. •Angstrom exponent anomalies reveals the circulation pattern during each ENSO phase. •ENSO exerts large influence (70.5%) on annual variations of AOD during 2002–2020. •Change of anthropogenic emissions is the dominant driver for AOD trend (2002–2020). Previous studies demonstrated that the El Niño–Southern Oscillation (ENSO) could modulate regional climate thus influencing air quality in the low-middle latitude regions like southern China. However, such influence has not been well evaluated at a long-term historical scale. To filling the gap, this study investigated two-decade (2002 to 2020) aerosol concentration and particle size in southern China during the whole dynamic development of ENSO phases. Results suggest strong positive correlations between aerosol optical depth (AOD) and ENSO phases, as low AOD occurred during El Niño while high AOD occurred during La Niña event. Such correlations are mainly attributed to the variation of atmospheric circulation and precipitation during corresponding ENSO phase. Analysis of the angstrom exponent (AE) anomalies further confirmed the circulation pattern, as negative AE anomalies is pronounced in El Niño indicating the enhanced transport of sea salt aerosols from the South China Sea, while the La Niña event exhibits positive AE anomalies which can be attributed to the enhanced import of northern fine anthropogenic aerosols. This study further quantified the AOD variation attributed to changes in ENSO phases and anthropogenic emissions. Results suggest that the long-term AOD variation from 2002 to 2020 in southern China is mostly driven (by 64.2%) by the change of anthropogenic emissions from 2002 to 2020. However, the ENSO presents dominant influence (70.5%) on year-to-year variations of AOD during 2002–2020, implying the importance of ENSO on varying aerosol concentration in a short-term period.     

Particle-bound polycyclic aromatic hydrocarbons in typical urban of Yunnan-Guizhou Plateau: Characterization,sources and risk assessment

• The sampling was conducted in city on the Yunnan-Guizhou Plateau for one year. • The groups of PAHs revealed their different environmental fates and migration paths. • Seasonal biomass burning could affect the concentration by long-distance transport. • Industrial sources and traffic emissions were the main contributor of PAHs. • Living in industrial areas or winter had higher health risk by exposure PAHs in PM_2.5. Monthly particle-phase ambient samples collected at six sampling locations in Yuxi, a high-altitude city on the edge of Southeast Asia, were measured for particle-associated PAHs. As trace substances, polycyclic aromatic hydrocarbons (PAHs) are susceptible to the influences of meteorological conditions, emissions, and gas-particulate partitioning and it is challenging job to precise quantify the source and define the transmission path. The daily concentrations of total PM_2.5-bound PAHs ranged from 0.65 to 80.76 ng/m³, with an annual mean of 11.94 ng/m³. Here, we found that the concentration of PM_2.5-bound PAHs in winter was significantly higher than that in summer, which was mainly due to source and meteorology influence. The increase of fossil combustion and biomass burning in cold season became the main contributors of PAHs, while precipitation and low temperature exacerbated this difference. According to the concentration variation trend of PM_2.5-bound PAHs and their relationship with meteorological conditions, a new grouping of PAHs is applied, which suggested that PAHs have different environmental fates and migration paths. A combination of source analysis and trajectory model supported local sources from combustion of fossil fuel and vehicle exhaust contributed to the major portion on PAHs in particle, but on the Indochina Peninsula the large number of pollutants emitted by biomass burning during the fire season would affect the composition of PAHs through long-range transporting. Risk assessment in spatial and temporal variability suggested that citizens living in industrial areas were higher health risk caused by exposure the PM_2.5-bound PAHs than that in other regions, and the risk in winter was three times than in summer.     

大清河水系河流表层沉积物重金属污染特征

沉积物中重金属污染是影响河流水生态系统健康的重要因素.本文采集大清河水系河流表层沉积物,分析了沉积物粒径分布、沉积物中有机质及6种重金属的含量,并采用富集系数法和生态危害指数法进行了重金属的来源解析和风险评价.结果表明:大清河水系河流表层沉积物粒径分布以粉砂为主,占51.27%,砂、黏土所占比例较低,分别为38.56%和10.17%;沉积物中有机质平均含量达到3.94%,且平原/滨海段含量较高;6种重金属Cd、Cr、Cu、Ni、Pb和Zn的含量均值分别为0.68、110.28、73.91、34.74、32.01和227.88 mg·kg-1,均超出背景值.Cd、Cu和Zn的富集系数分别为5.90、2.69和2.15,以人为来源为主;潜在生态危害指数大小顺序为Cd(217.38)Cu(16.05)Pb(7.45)Ni(5.64)Cr(3.23)Zn(2.91),其中Cd呈很强生态危害;重金属综合潜在生态危害表明,大清河水系河流表层沉积物整体处于中度生态危害(RI=253.56).此外,随沉积物中有机质含量增加,Cu和Zn含量增加;随沉积物粒径中值增大,Cd含量增加.     

黄河口湿地表层沉积物中磷赋存形态的分析

于2009年4月在黄河口湿地采集表层沉积物,利用改进后的SEDEX方法对沉积物样品进行了磷形态的分析.结果表明,表层沉积物中总磷含量变化范围为12.12~25.37μmol·g-1,平均值为20.70μmol·g-1,其中自生磷灰石磷和碎屑磷灰石磷为表层沉积物中磷的主要赋存形式.中值粒径与各形态磷含量密切相关,弱吸附态磷、自生磷灰石磷、活性有机磷含量与中值粒径呈显著负相关关系;碎屑磷灰石磷含量与中值粒径呈显著正相关关系.有机质含量影响各形态磷在沉积物中含量,弱吸附态磷、活性有机磷、自生磷灰石磷含量均随TOC含量增加而升高.包括弱吸附态磷、活性有机磷和铁结合态磷在内的生物可利用磷含量变化为1.15~6.74μmol·g-1,平均值为4.27μmol·g-1,占总磷的摩尔分数为6.35%~30.4%.     

不同粒径零价铁活化过硫酸钠氧化降解酸性橙7的影响及动力学研究

以偶氮染料酸性橙7(AO7)为目标污染物,研究了不同粒径零价铁(包括1 mm-ZVI、150μm-ZVI、50 nm-ZVI)对活化过硫酸钠(PS)氧化降解AO7的影响,并探讨了这3种不同粒径的零价铁活化体系中AO7的降解动力学及中间产物.结果表明,3种粒径零价铁均可以高效活化PS氧化降解AO7,反应90 min后,1 mm-ZVI、150μm-ZVI和50 nm-ZVI活化体系对AO7的去除率分别为43%、97%和100%.AO7动力学方程拟合结果表明,1 mm-ZVI和150μm-ZVI活化PS降解AO7是一级反应,50 nm-ZVI活化体系中AO7的降解是二级反应,这3种粒径零价铁活化PS降解AO7的速率常数大小顺序为50 nm-ZVI>150μm-ZVI>1 mm-ZVI.反应过程中1 mm-ZVI反应后主要生成α-Fe2O3和少量Fe3O4,150μm-ZVI表面的腐蚀产物主要是Fe3O4,而50 nm-ZVI的主要氧化物为α-Fe2O3和α-FeOOH.GC/MS检测出AO7降解中间产物有2-萘酚、邻甲酚、3-甲基-4-乙基苯酚、邻苯二甲酰亚胺、邻苯二甲酸等,AO7溶液吸收光谱的变化特征及GC/MS检测结果表明3种粒径零价铁活化PS氧化降解AO7的途径可能存在差异.     

高炉炼铁工艺细颗粒物PM2.5排放特性分析

采用静电低压撞击器(electrical low pressure impactor,ELPI)对高炉出铁场、矿槽除尘后细微颗粒物(PM2.5)的粒径及质量浓度分布进行在线分析.结果表明,出铁场除尘后PM2.5粒数浓度在105~106cm-3数量级范围内,主要为粒径小于0.1μm的颗粒物,而矿槽除尘后PM2.5粒数浓度在104~105cm-3数量级范围内,主要为粒径1.0μm以下的颗粒物,质量浓度呈单峰分布;PM2.5化学组成分析表明水溶性离子SO2-4、K+、Ca2+含量较高,分别为10.32%~28.55%、10.36%~12.15%、3.97%~15.4%;主量元素主要为Fe、Si、Al,含量分别为16.8%~31.62%、2.24%~8.76%、1.24%~5.89%;含碳组分OC和EC在PM2.5中的含量也较为丰富,分别为2.7%~4.6%和0.8%~1.3%.PM2.5单体颗粒形态主要为球状颗粒和不规则颗粒.高炉出铁场、矿槽除尘后PM2.5的排放因子分别为0.045~0.085 kg·t-1、0.042~0.071 kg·t-1.     

北京市常见落叶树种叶片滞纳空气颗粒物功能

为了探求北京市常见落叶乔木树种滞纳空气颗粒物的功能,选取了6种典型落叶乔木树种(杨树、刺槐、栾树、垂柳、元宝枫、银杏),利用空气气溶胶再发生器(QRJZFSQ-I)测定了不同树种单位面积叶片对空气总悬浮颗粒物(TSP)、粗颗粒物和细颗粒物的滞纳量.结果表明:16个树种的叶片对不同粒径空气颗粒物均能起到一定的滞纳作用,且不同树种滞纳量表现出较大差异,栾树和刺槐单位面积叶片对不同粒径颗粒物的滞纳量最高,杨树的滞纳量最小;2不同树种单位面积叶片对不同粒径颗粒物的滞纳量并不完全随着取样时间的延长而增加,在雨后8 d和雨后5 d,不同树种单位面积叶片对TSP和粗颗粒物的滞纳量差异较大,但不同树种单位面积叶片对细颗粒物的滞纳量在不同取样时间下没有明显差异.在北京以空气污染的生态治理为目标选择落叶树种时,与银杏、垂柳、元宝枫、杨树相比,应优先选择栾树,其次为刺槐.     

空气净化器去除细粒子性能实验研究

对空气净化器去除细粒子的性能进行实验研究。结果表明,不同粒径区间颗粒物的洁净空气量(CADR)相差很大;降低空气净化器的运行风量,0.3~0.5μm颗粒物一次通过效率减小,0.5~3μm颗粒物一次通过效率不变;延长测试时间会对不同粒径区间颗粒物洁净空气量的测量结果产生不同影响。     

我国部分城市大气颗粒物中多环芳烃的分布特征

主要研究中国大气颗粒物中多环芳烃污染状况,对多环芳烃的浓度水平、时间和空间分布、组成及在不同粒径颗粒物上的分布特征进行了综述.北方城市大气颗粒物中多环芳烃的浓度普遍高于南方城市.大气颗粒物中多环芳烃以4～6环为主,占多环芳烃总量的60％～ 80％.大多数多环芳烃分布于细粒子中,且多环芳烃在PM2.5中的分布占在PM1o中分布的70％以上.多环芳烃质量浓度有明显的季节变化特征,多数研究中多环芳烃浓度从高到低的季节变化规律为冬季、秋季、春季、夏季.不同功能区大气颗粒物中多环芳烃污染,城区高于郊区,交通区和工业区高于商业区、居住区和文化区.     

Characterizations of organic compounds in diesel exhaust particulates

To characterize how the speed and load of a medium-duty diesel engine affected the organic compounds in diesel particle matter (PM) below 1 μm, four driving conditions were examined. At all four driving conditions, concentration of identifiable organic compounds in PM ultrafine (34–94 nm) and accumulation (94–1000 nm) modes ranged from 2.9 to 5.7 μg/m³ and 9.5 to 16.4 μg/m³, respectively. As a function of driving conditions, the non-oxygen-containing organics exhibited a reversed concentration trend to the oxygen-containing organics. The identified organic compounds were classified into eleven classes: alkanes, alkenes, alkynes, aromatic hydrocarbons, carboxylic acids, esters, ketones, alcohols, ethers, nitrogen-containing compounds, and sulfur-containing compounds. At all driving conditions, alkane class consistently showed the highest concentration (8.3 to 18.0 μg/m³) followed by carboxylic acid, esters, ketones and alcohols. Twelve polycyclic aromatic hydrocarbons (PAHs) were identified with a total concentration ranging from 37.9 to 174.8 ng/m³. In addition, nine nitrogen-containing polycyclic aromatic compounds (NPACs) were identified with a total concentration ranging from 7.0 to 10.3 ng/m³. The most abundant PAH (phenanthrene) and NPACs (7,8-benzoquinoline and 3-nitrophenanthrene) comprise a similar molecular (3 aromatic-ring) structure under the highest engine speed and engine load.