Differentiated emission control strategy based on comprehensive evaluation of multi-media pollution: Case of mercury emission control

In order to comprehensively evaluate the environmental impact of multi-media mercury pollution under differentiated emission control strategies in China, a literature review and case studies were carried out. Increased human exposure to methylmercury was assessed through the dietary intake of residents in areas surrounding a typical coal-fired power plant and a zinc(Zn) smelter, located either on acid soil with paddy growth in southern China, or on alkaline soil with wheat growth in northern Chi...     

南北向街谷内热不稳定流场日变化规律的模拟研究

城市街谷内热不稳定流动是促进污染物扩散的重要影响因素之一.本文基于街谷内热平衡分析,结合大涡模拟方法,研究了一个南北走向的城市街谷内温度、风场的日变化特征,并分析了壁面对流换热及长波辐射对街谷内环境的影响.结果显示:壁面对流换热是影响街谷内温度、风场的主要因素,而长波辐射的影响非常小,长波辐射引起街谷内空气温度升高不足对流换热影响的10％,而其对平均风速和脉动量的影响更是在2％和1％以内;街谷内空气温度从早上开始逐渐增加,到15:00的时候达到最大,可达311 K(38℃);上午时段,迎风面壁面热浮力减弱街谷内风速,街谷底部和迎风墙侧的脉动量根均方值较大,而下午时段街谷顶部的脉动量根均方值达到最大.街谷内不同位置和不同时段内,通过建筑材料选择和表面结构设计,适当调控建筑壁面的温度,可以促进街谷内温度分布和空气流通改善.     

安徽省O3浓度时空分异及其驱动因素研究

基于2017—2018年安徽省132个空气质量监测站点的O₃浓度观测数据及各月份的气象与前体物排放数据, 采用空间自相关分析、地理探测器等方法分析安徽O₃浓度的时空分异及其驱动因素. 结果表明:安徽O₃浓度的峰值出现在5月和6月, 超标率分别为31.4%和42.8%. O₃浓度整体呈空间集聚特征, 高值区主要出现在安徽东北部的蚌埠、宿州、淮南和滁州4市, 低值主要分布在皖南山区. 气象要素是安徽省O₃浓度格局形成的主控因素, 其中6月的边界层高度(q=0.644)、近地面太阳辐射(q=0.597)和风速(q=0.571)的影响最大, 且呈正向影响, 风速的增大和边界层高度的增加可能使得输入性污染增加. 降雨量(q=-0.532)和相对湿度(q=-0.559)呈负向影响, 且降雨带的移动是影响安徽夏季O₃分布格局的一项关键因素. 本地前体物排放对安徽O₃浓度的影响受到气象要素的驱动, 在夏季呈正向, 而冬季呈反向, 其中CO的影响相对较大. 6月气象要素与本地前体物排放的双因子交互驱动对O₃浓度的空间分异具有增强作用. 边界层高度和近地面太阳辐射与本地前体物的组合解释力均大于0.7, 在不利的气象条件下, 应进一步加强对本地前体物排放的管控.     

城市间PM2.5源的碳成分谱比较

为了解我国不同城市PM_2.5源的碳成分谱特征和地域差异,采集沈阳市、十堰市和乌鲁木齐市的燃煤源、柴油车尾气源、汽油车尾气源和餐饮源样品,使用热光透射法分析PM_2.5中的总碳（TC）、有机碳（OC）和元素碳（EC）,以及细分的8种碳组分（OC1,OC2,OC3,OC4,EC1,EC2,EC3和OPC_T）,构建各类污染源碳成分谱.结果表明：3个城市4类源TC/PM_2.5从高到低分别为：餐饮源（65.1%±8.4%）、柴油车尾气源（46.2%±9.5%）、汽油车尾气源（37.7%±3.5%）和燃煤源（17.3%±8.0%）;OC/TC在餐饮源中最高（98.0%±0.5%）,EC/TC在柴油车尾气源中最高（38.6%±8.5%）.3个城市同类源的碳组分含量受污染源细分后的不同类型影响有一定差异,但归一化处理后总体仍表现为燃煤源中OC2（14%~30%）和OC3（13%~23%）含量最高,柴油车尾气源中EC2（22%~56%）含量最高,汽油车尾气源中OC2（24%~41%）、OC1（16%~42%）和OC3（12%~26%）含量最高,餐饮源中OC2（21%~43%）和OC3（23%~49%）含量最高.不同污染源的OC/EC值为燃煤源在0.4~7.6之间,柴油车尾气源在0.2~5.6之间,汽油车尾气源在1.1~38.5之间,餐饮源在6.4~170.2之间.分歧系数结果显示3个城市不同源的碳成分谱具有差异性,同类源的碳成分谱具有相似性.将3个城市同类源碳成分谱合并后利用化学质量平衡灵敏度矩阵得到OC2,OC3,OC4,EC1和OPC_T可共同作为燃煤源的标识组分;EC2是柴油车尾气源的标识组分;OC1,OC2和OC3可共同作为汽油车尾气源的标识组分;OC2和OC3可共同作为餐饮源的标识组分.沈阳市、十堰市和乌鲁木齐市相同污染源相似的碳成分谱和一致的标识碳组分可为国内其他城市相关研究提供数据参考.     

Drivers of microbial beta-diversity in wastewater treatment plants in China

As one of the most well-documented biogeographic patterns, the distance-decay relationship provides insights into the underlying mechanisms driving biodiversity distribution. Although wastewater treatment plants (WWTPs) are well-controlled engineered ecosystems, this pattern has been seen among microbial communities in activated sludge (AS). However, little is known about the relative importance of environmental heterogeneity and dispersal limitation in shaping AS microbial community across China; especially they are related to spatial scale and organism types. Here, we assessed the distance-decay relationship based on different spatial scales and microbial phylogenetic groups by analyzing 132 activated sludge (AS) samples across China comprising 3,379,200 16S rRNA sequences. Our results indicated that the drivers of distance-decay pattern in China were scale-dependent. Microbial biogeographic patterns in WWTPs were mainly driven by dispersal limitation at both local and national scales. In contrast, conductivity, SRT, and pH played dominant roles in shaping AS microbial community compositions at the regional scale. Turnover rates and the drivers of beta-diversity also varied with microorganism populations. Moreover, a quantitative relationship between dispersal limitation ratio and AS microbial turnover rate was generated. Collectively, these results highlighted the importance of considering multiple spatial scales and micro-organism types for understanding microbial biogeography in WWTPs and provided new insights into predicting variations in AS community structure in response to environmental disturbance.     

Estimation of Avian Influenza Viruses in Water Environments of Live Poultry Markets in Changsha,China, 2014 to 2018

Food and Environmental Virology - In routine surveillance for avian influenza viruses (AIVs) in the environments of live poultry markets (LPMs), certain samples were positive for AIVs type A while...     

Spatial and Seasonal Variation of Dissolved Organic Carbon (DOC) Concentrations in Irish Streams: Importance of Soil and Topography Characteristics

Dissolved organic carbon (DOC) concentrations have increased in many sites in Europe and North America in recent decades. High DOC concentrations can damage the structure and functions of aquatic ecosystems by influencing water chemistry. This study investigated the spatial and seasonal variation of DOC concentrations in Irish streams across 55 sites at seven time occasions over 1 year (2006/2007). The DOC concentrations ranged from 0.9 to 25.9 mg/L with a mean value of 6.8 and a median value of 5.7 mg/L and varied significantly over the course of the year. The DOC concentrations from late winter (February: 5.2 ± 3.0 mg/L across 55 sites) and early spring (April: 4.5 ± 3.5 mg/L) had significantly lower DOC concentrations than autumn (October: mean 8.3 ± 5.6 mg/L) and early winter (December: 8.3 ± 5.1 mg/L). The DOC production sources (e.g., litterfall) or the accumulation of DOC over dry periods might be the driving factor of seasonal change in Irish stream DOC concentrations. Analysis of data using stepwise multiple linear regression techniques identified the topographic index (TI, an indication of saturation-excess runoff potential) and soil conditions (organic carbon content and soil drainage characteristics) as key factors in controlling DOC spatial variation in different seasons. The TI and soil carbon content (e.g., soil organic carbon; peat occurrence) are positively related to DOC concentrations, while well-drained soils are negatively related to DOC concentrations. The knowledge of spatial and seasonal variation of DOC concentrations in streams and their drivers are essential for optimum riverine water resources management.     

Occurrence and distribution of antibiotic resistance genes in the sediments of the East China Sea bays

The coastal area of the East China Sea has experienced rapid urbanization and industrialization in China since 1980 s, resulting in severe pollution of its environments.Antibiotic resistance genes(ARGs) are regarded as a kind of emerging pollutant with potential high risk. The sediment samples were collected from Hangzhou Bay(HB),Xiangshan Bay(XB), and Taizhou Bay(TB) to investigate the spatial occurrence and distribution of 27 ARGs and class I integron–integrase gene(intI1) in the coastal area of the East China Sea. The PCR results showed the frequent presence of 11 ARGs and intI1 in the sediments of the three bays. The qPCR results further showed that sulfonamide resistance was the most prevalent ARG type and antibiotic target replacement and protection were the most important resistance mechanisms in the sediments. Regarding the subtype of ARGs, sulI, tetW, and dfrA13 were the most abundant ARGs, in which sulI was higher in TB(based on both the absolute and relative abundances) and dfrA13 was higher in HB(based on the relative abundances). The network analysis revealed that intI1 had significant correlations with tetC, sulI, sulII, and blaPSE-1. Oil was the key connected factor, which had positive connections with sulI, sulII, and blaPSE-1. In addition, the joint effect of heavy metals and nutrients organic pollutants might be crucial for the fate of ARGs in the coastal sediments.     

武清地区冬季一次重污染过程垂直分布特征

为研究京津冀地区重污染过程大气污染物的垂直分布特征,于2016年12月13日重污染前（11:49-12:18）和12月18日重污染期间（11:00-11:16）在北京市、天津市、河北省交界处的武清地区利用系留气球开展1 000 m以下的大气观测,探究污染物的垂直分布特征及对流边界层、覆盖逆温层和混合层等要素对重污染形成的影响.结果表明:①在重污染前,大气层结不稳定,ρ（PM_2.5）、ρ（NO_x）与ρ（O₃）随高度变化不明显,存在明显的垂直对流运动,有利于大气污染物的扩散;PM_2.5/PM₁₀[ρ（PM_2.5）/ρ（PM₁₀）]在800 m以下为0.60~0.80,在800~1 000 m以上大于0.90.②重污染期间,近地面大气层分为对流边界层（距地面0~150 m）、覆盖逆温层（150~370 m）、混合层（370~500 m）和自由大气（500 m以上）4个层次.③NO_x主要在对流边界层内聚积;高空O₃在向近地面扩散时受强混合层阻挡,在混合层出现一个小峰值;PM_2.5不仅在近地面聚积,而且在覆盖逆温层内聚积,ρ（PM_2.5）在覆盖逆温层内呈双峰（峰值分别出现在150和370 m）分布,其粒径集中在0.5~1.0 μm,属于积聚态气溶胶.研究显示,在不利扩散条件下,汽车排放、村镇居民供暖排放的污染物聚积及二次颗粒物的生成是重污染形成的重要因素.      

天津市典型区域PM2.5中水溶性离子污染特征

为了解天津市不同区域PM_2.5中水溶性离子污染特征,于2015年7月、10月及2016年1月、4月,在天津市南开区（简称“市区”）及武清区采集PM_2.5样品,结合气象因素、气态污染物研究,分析了样品中水溶性离子污染特征及来源.结果表明:①天津市市区及武清区PM_2.5中水溶性离子组分主要为二次离子（SO₄2-、NO₃-、NH₄+）;不同区域PM_2.5中二次离子各季节占比略有不同,市区为夏季（54.0%）>秋季（42.5%）>春季（41.3%）>冬季（40.7%）,武清区为夏季（53.0%）>春季（44.6%）>秋季（43.4%）>冬季（33.2%）.②冬季市区、武清区PM_2.5中水溶性离子组成差异较大,其他季节水溶性离子组成相似;夏季市区及武清区颗粒物呈酸性,其他季节均呈碱性,冬季武清区颗粒物碱性强于市区.③不同季节市区及武清区PM_2.5中SO₄2-均以（NH₄）₂SO₄形式存在,NO₃-冬季以NH₄NO₃形式存在,其他季节NO₃-主要以NH₄NO₃和HNO₃形式共存;市区Cl-主要以NH₄Cl、KCl和NaCl形式存在,武清区Cl-主要以NH₄Cl、KCl形式存在.④对市区及武清区来说,均相反应和非均相反应是SO₄2-重要生成途径,均相反应是生成NO₃-的主要途径.研究显示,代表一次排放的机动车源、燃煤源和二次无机粒子混合源对天津市PM_2.5中水溶性离子贡献率最高,工业源和扬尘源对市区的影响较大,农业源对武清区的影响较大.