核算间接冷却水污染当量数的研讨

针对间接冷却水的特点和核算其污染当量数过程中存在的问题，阐述了间接冷却水的界定，水源水的采样监测技术，本底值的扣除以及超标排放的判别等环节的技术要求和注意事项，并就与之密切相关的几个问题展开了讨论,为核算间接冷却水当量数提供了一定的参考依据，建议增加水湿排放指标，以切实控制间接冷却水造成的主要污染－热污染。     

深圳大气PM2.5中水溶性有机物的来源特征

对2017年9月~2018年8月深圳市北部大气PM_2.5中水溶性有机物（WSOM）的质量浓度、质谱及来源结构进行测量和分析.结果表明：PM_2.5的质量浓度为（32.3±18.4）μg/m³,WSOM的质量浓度为（9.4±5.7）μg/m³,占颗粒物总有机物的（77.6%±14.0%）.质谱分析显示,WSOM的氧碳比（O/C）平均值达到（0.57±0.09）,属于二次有机物的O/C值范围,且生物质燃烧排放的离子碎片C₂H₄O₂⁺的丰度显著,说明WSOM的来源中有显著的生物质燃烧排放的有机气溶胶.为了明确WSOM的来源结构,利用正矩阵因子分解法（PMF）模型进行来源解析,发现3个合理因子：高氧化态有机气溶胶（MO-OOA）,低氧化态有机气溶胶（LO-OOA）和生物质燃烧（BBOA）,贡献比例分别为51.7%,31.8%和16.5%.MO-OOA和BBOA贡献浓度均呈现秋冬高、春夏低的季节变化特征,反向轨迹分析显示其与内陆污染传输关系密切.LO-OOA的变化相对稳定,本地源的贡献较大.结合¹⁴C同位素示踪法对秋冬季WSOM样品分析,发现机动车等化石源二次有机物是WSOM的主要来源,贡献比例达到53.9%,需继续加强对化石燃料控制来降低WSOM污染.     

加入SOA示踪的深圳大气PM2.5受体模型源解析

为厘清包括二次有机气溶胶（SOA）在内的深圳市区PM_2.5各种一次和二次来源贡献,本文于2017年9月2日~2018年8月29日在深圳市大学城点位开展PM_2.5样品采集,并进行化学组分和水溶性有机物（WSOM）质谱测量,共获得162组有效数据.观测期间深圳市大气PM_2.5平均质量浓度为26μg/m³,在传统PMF源解析的基础上加入羧基离子碎片（CO₂⁺）作为SOA的示踪物,加入水溶性有机氧（WSOO）用于计算各因子O/C,验证有机物解析效果.结果表明,SOA可以被独立解析出,其O/C明显高于其他一次污染源中有机物;机动车、二次硫酸盐、二次硝酸盐、SOA为最主要的4个源,对PM_2.5质量浓度的贡献分别为25%、23%、17%和10%,船舶、地面扬尘、老化海盐、建筑尘、生物质燃烧、燃煤和工业贡献均在5%以内.各个源的变化特征表明,机动车、二次硫酸盐、二次硝酸盐、SOA等源贡献呈现冬高夏低的季节特征,与冬季季风条件下源自内陆的污染传输密切相关.污染天气时,二次硝酸盐和SOA的贡献增加相对最显著,因此NOx和挥发性有机物是减排的关键.     

Using Multiple Antibiotic Resistance and land use characteristics to determine sources of fecal coliform bacterial pollution

Multiple Antibiotic Resistance (MAR) analysis and regression modeling techniques were used to identify surface water areas impacted by fecal pollution from human sources, and to determine the effects of land use on fecal pollution in Murrells Inlet, a small, urbanized, high-salinity estuary located between Myrtle Beach and Georgetown, South Carolina. MAR analysis was performed to identify areas in the estuary that are impacted by human-source fecal pollution. Additionally, regression analysis was performed to determine if an association exists between land use and fecal coliform densities over the ten-year period from 1989 to 1998. Land-use variables were derived using Geographic Information System (GIS) techniques and were used in the regression analysis.MAR analyses were conducted by comparing the frequency and patterns of antibiotic resistance found in Escherichia coli isolates derived from surface water samples and from sewage sources in the Murrells Inlet sewage collection system. The MAR results suggest that the majority of the fecal pollution detected in the Murrells Inlet estuary may be from non-human sources, including fecal coliforms isolated from areas in close proximity to high densities of active septic tanks.A MAR Index, which measures the frequency of antibiotic resistance, was calculated for each of twenty-three water samples and nine sewage samples. The antibiotic resistance pattern comparisons were performed using cluster analysis. Although the MAR indices indicated that several surface water sites had potential human-source contamination, the cluster analysis suggests that only one sampling site had MAR patterns that were similar to those found in the sewage samples. This site was in close proximity to several large pleasure boats as well as a sewage collection system lift station, but was not near areas with active septic tanks. The results of the regression analysis also suggest that sewage sources and rainfall runoff from urbanized areas may contribute to fecal pollution in the estuary.     

大气可吸入颗粒物研究进展

简述了国内外有关大气颗粒物中的可吸入颗粒物 (空气动力学直径小于或等于 10 μm)的研究进展 ,主要围绕可吸入颗粒物的基本特性、可吸入颗粒物与健康的关系、可吸入颗粒物的源解析 ,对其研究动向进行阐述。     

Characteristics and source apportionment of PM2.5 under the dual influence of the Spring Festival and the COVID-19 pandemic in Yuncheng city

Based on the online and membrane sampling data of Yuncheng from January 1st to February 12th, 2020, the formation mechanism of haze under the dual influence of Spring Festival and COVID-19 (Corona Virus Disease) was analyzed. Atmospheric capacity, chemical composition, secondary transformation, source apportionment, backward trajectory, pollution space and enterprise distribution were studied. Low wind speed, high humidity and small atmospheric capacity inhibited the diffusion of air pollutants. Four severe pollution processes occurred during the period, and the pollution degree was the highest around the Spring Festival. In light, medium and heavy pollution periods, the proportion of SNA (SO₄²⁻, NO₃⁻ and NH₄⁺) was 59.6%, 56.0% and 54.9%, respectively, which was the largest components of PM_2.5; the [NO₃⁻]/[SO₄²⁻] ratio was 2.1, 1.5 and 1.7, respectively, indicating that coal source had a great influence; the changes of NOR (nitrogen oxidation ratio, 0.44, 0.45, 0.61) and SOR (sulphur oxidation ratio, 0.40, 0.49, 0.65) indicated the accumulation of secondary aerosols with increasing pollution. The coal combustion, motor vehicle, secondary inorganic sources and industrial sources contributed 36.8%, 26.59%, 11.84% and 8.02% to PM_2.5 masses, respectively. Backward trajectory showed that the influence from the east was greater during the Spring Festival, and the pollutants from the eastern air mass were higher, which would aggravate the pollution. Meteorological and Spring Festival had a great impact on heavy pollution weather. Although some work could not operate due to the impact of the COVID-19 epidemic, the emission of pollutants did not reduce much.     

氯气和光气爆燃事故源强估算

在建立化学品泄漏的气体排放、液体排放、两相排放模式和爆炸燃烧的火球和气爆，蒸气云爆炸及绝热扩散和池蒸发扩展等模式的基础上，估计分析了氯气和光气爆燃事故源强，即爆炸能量及碎片抛射、冲击波、热辐射和毒云等后果影响     

南京北郊黑碳气溶胶的来源解析

利用七波段黑碳仪对2015年1~12月南京北郊地区黑碳(black carbon,BC)气溶胶实时监测,并结合黑碳仪模型对该期间内BC进行来源解析,探讨化石燃料排放产生BC(BCff)与生物质燃烧产生BC(BCbb)各自的贡献大小.结果表明,观测期间BC的吸收波长指数(α)和生物质燃烧对BC的贡献百分比(BB)的变化范围都较大但趋势较为一致;冬季α值偏高而夏季α值较低,表明不同季节时间BC来源和强度的差异性.BCff在各季节BC总浓度中占比略有不同但均高于75%;BC、BCff和BCbb的日变化趋势均呈双峰特征,在07:00~09:00和18:00~21:00左右浓度有最大值;全天中,BCff对BC贡献最大,浓度值约为BCbb的3~5倍;夜晚BC浓度普遍高于白天,其平均浓度值是白天的1.2倍.由浓度权重轨迹分析的结果可知,影响南京北郊地区高浓度BC的源区主要集中在浙江、安徽以及江西和福建等地区.     

泉州市大气PM2.5镧系元素组成特征及来源解析

2014年3月、4月和7月分别采集了泉州市5个采样点共49个PM_(2.5)样品,采用电感耦合等离子体质谱(ICP-MS)测定样品镧系元素(Loid)及其他微量金属元素浓度水平.分析了PM_(2.5)镧系元素组成特征和配分模式,利用La-Ce-V三元图和化学质量平衡(CMB)受体模型解析了泉州市大气PM_(2.5)污染来源.结果表明:(1)泉州市大气PM_(2.5)总镧系元素(Σ Loid)浓度为2.490~5.708 ng·m~(-3)(含量65.682~126.529μg·g~(-1)),轻重镧系元素比值(L/H)为12.086~14.319;(2)PM_(2.5)镧系元素配分模式与福建土壤相似,PM_(2.5)中Ce元素表现为正异常,而Eu元素表现为负异常;(3)城市扬尘、燃煤尘、汽车尾气尘和垃圾焚烧飞灰是泉州市大气PM_(2.5)的主要来源,贡献率分别为18.9%、10.9%、30.6%和30.2%.     

夏季太湖CDOM光学特性空间差异及其来源解析

为进一步探究夏季太湖CDOM（有色溶解性有机质）光学特性在空间分布上的差异性与其来源的关系,对其紫外-可见吸收及三维荧光光谱特性进行了分析研究,在此基础上进一步分析了CDOM吸尘系数及其荧光组分（C1、C2、C3、C4）强度和各水质参数间的相关性.结合主成分分析法探讨了CDOM的来源以及与各参数指标[ρ（DOC）除外]之间的来源关系.结果表明:CDOM吸收系数α（355）、S值（光谱斜率）变化范围分别为3.27~8.27 m-1和0.011~0.021 nm-1;太湖西部、北部及南部湖区CDOM丰度较大,S值较低,受陆源输入的影响较为明显.CDOM的三维荧光光谱揭示其中含有两种类蛋白质组分C1和C2以及类腐殖质组分C3和C4,并且以类蛋白质组分为主.此外,大部分采样点的荧光指数（FI）为1.70~2.01,自生源指数（BIX）大于1,腐殖化指数（HIX）小于0.6,r_（T/C）（荧光峰T与荧光峰C荧光强度比值）小于2,表明夏季太湖CDOM内源特性相对强烈.研究显示,除ρ（DOC）外,CDOM与其他水质参数在第一主成分上（贡献率为90.8%）均存在显著相关关系,说明各水质参数的来源存在相似性,并且受生物自生源影响更为显著.