典型旅游城市河流水体及污水厂出水中全氟烷基酸类化合物的空间分布及其前体物的转化

全氟烷基酸类化合物(perfluoroalkyl Acids,PFAAs)在各环境介质中被普遍检出,对生态环境和人体健康具有潜在风险.为探明旅游型城市不同水体PFAAs污染特征及其前体物对污染的贡献,以典型旅游型城市——日照市为例,基于超高效液相色谱-串联质谱,结合WAX固相萃取及羟基自由基氧化等方法,系统分析了日照市主要河流水体和污水厂出水中15种PFAAs及其3种前体物的含量水平和空间分布特征,探讨PFAAs前体物的转化潜力及其对污染的贡献.结果表明,在上述水体中15种PFAAs普遍被检出,前体物中只有全氟辛基磺酰胺(perfluorooctane sulfoneamide,FOSA)被检出;在河流水体和污水厂出水中总质量浓度(ΣPFAAs)分别为3. 79~45. 58 ng·L~(-1)和54. 04~105. 64 ng·L~(-1),其中质量浓度较高的污染物是全氟辛烷磺酸(perfluorooctanesulfonic acid,PFOS)、全氟己烷磺酸(perfluorohexanesulfonic acid,PFHx S)、全氟辛酸(perfluorooctanoic acid,PFOA)和全氟壬酸(perfluorononanoic acid,PFNA).河流水体ΣPFAAs明显低于污水厂出水,河流下游水体高于上游.运用羟基自由基氧化法对样品进行氧化处理后,所有样品PFAAs的质量浓度都明显升高;相对于河流水体,污水厂出水中碳原子数为4~12的全氟羧酸类化合物(perfluorinated carboxylic acids,PFCAs)浓度增加值(ΣΔPFCAC4~C12)更高,这可能是由于PFAAs前体物在污水处理过程中降解所致.研究成果可为旅游城市新型污染物环境污染防治提供数据支撑和技术借鉴.     

东平湖CDOM吸收光谱特性及其来源解析

为分析东平湖有色可溶性有机物（CDOM）吸收特性、来源和空间分布的季节变化,分别于2013年8、12月以及2014年3月采集了35个表层水样,分析了各基本水质参数、CDOM吸收系数[a（440）]、比吸收系数[a^*（440）]和相对分子量参数M值的分布规律及CDOM吸收系数与水质参数之间的相关关系.结果表明：东平湖CDOM吸收系数a（440）呈现出枯水期 > 丰水期 > 平水期的规律,空间分布与CDOM比吸收系数[a^*（440）]相似.M值呈现出丰水期 < 平水期 < 枯水期的变化趋势.丰水期CDOM吸收系数与叶绿素a（Chla）具有显著相关关系;丰、平水期两季CDOM吸收系数与DOC存在显著相关关系.丰水期CDOM同时受外源和内源输入的影响,但以内源输入为主,主要来源于浮游植物降解产物;老湖镇湖区外源特征明显.平水期CDOM亦受内源和外源输入的双重影响,但浮游植物的腐烂降解不是CDOM的主要来源;北部湖区以外源输入为主.枯水期CDOM整体表现出较强的自生源特征,但相关分析显示,浮游植物降解并不是CDOM的主要来源,自生源特征可能与挖沙活动导致的悬浮物浓度增高有关;东南湖区因大汶河输入的影响呈现出较强的外源特征.利用东平湖丰、平水期两季CDOM浓度反演DOC浓度具有可行性.     

长春市餐饮源PM2.5和VOCS排放清单

采用自下而上的四种不同清单编制方法（以人口、就餐次数、用油量和灶头为核算基准）,评估了长春市辖区2014年不同餐饮活动（家庭餐饮、社会餐饮和食堂餐饮）的大气污染物PM_2.5和VOC_S的排放量,编制了餐饮源大气污染物PM_2.5和挥发性有机物（VOC_S）排放清单,并分析了餐饮源排放的时空分布特征.结果表明：2014年长春市辖区餐饮源PM_2.5总排放量183~770t,VOC_S总排放量9~586t;长春市辖区餐饮源PM_2.5和VOC_S的最大排放源是家庭餐饮,其贡献率分别为74%~81%和28%~78%,食堂餐饮的贡献率分别为8%~22%和3%~26%,社会餐饮的贡献率分别为2%~17%和2%~69%;排放强度空间分布表明,长春市辖区餐饮源污染物在排放区域上：朝阳区 > 南关区 > 绿园区 > 二道区 > 宽城区 > 双阳区;时间变化特征显示,日变化峰值为07：00~08：00,11：30~12：30,18：00~20：00;周变化中周三、周六和周日排放量较大;季节变化中,冬季排放强度高于其他季节,其中十二月份贡献率最大（9.98%）;不同方法计算的大气污染物排放清单中,以人口为基准的不确定性最大,VOC_S的不确定性为302%,以用油量为基准的不确定性最小,PM_2.5和VOC_S的不确定性分别为31%和61%,可以作为区域餐饮源大气污染物清单推荐方法.未来的工作将侧重于典型餐饮源本地排放因子的测定,从而有效减少排放清单的不确定性.     

太湖流域农田生产-畜禽养殖系统氮素流动特征

为应对太湖严峻的水体富营养化现状,从源头上降低面源污染负荷,基于物质流分析法与质量守恒原理,研究了常熟市辛庄镇农田生产-畜禽养殖系统的氮素流动通量、流动效率及环境负荷,并用实测值进行了参数校正. 结果表明:2000—2012年,辛庄镇农田生产子系统的单位面积氮素流动通量呈下降趋势,而畜禽养殖子系统的单位面积氮素流动通量则在42.5~50.9 kg/hm2范围内持续波动. 氮素利用率与氮素循环利用率均较低,氮素环境损失率较高,系统损失的氮素中有54.5%进入周围水体. 2000年以来,作物种植与畜禽养殖对辛庄镇环境氮负荷的贡献率分别在38.8%~50.2%与25.4%~35.8%之间波动. 辛庄镇农田施氮量为310.8 kg/hm2,人畜排泄氮量为61.1 kg/hm2,分别远高于全国平均值(197.2和18.6 kg/hm2). 过量施用化学氮肥与畜禽粪便的大量排放是辛庄镇环境氮负荷加重的主要原因. 辛庄镇高投入高产出的农业生产方式加大了太湖水环境修复的难度. 建议调整作物种植与畜禽养殖结构,推广科学施肥与生态养殖,将农田生产与畜禽养殖结合形成产业链,以此减轻氮素环境负荷.      

阳澄湖表层沉积物中氮磷及重金属的空间分布特征及污染评价

为了解阳澄湖表层沉积物中氮磷及重金属的空间分布和污染特征,对全湖开展了大范围调查,基于综合污染指数、地积累指数法和潜在生态风险指数法对沉积物污染风险进行评价.结果表明:阳澄湖表层沉积物中w(TN)、w(TP)平均值分别为3 433、379 mg/kg,湖区氮磷污染严重且空间差异明显,w(TN)高值区位于阳澄东湖,w(TP)高值区位于阳澄西湖;综合污染指数评价结果显示,整个阳澄湖TN均为重度污染状态,TP除阳澄西湖外大部分区域处于轻度污染状态.阳澄湖表层沉积物中w(Cu)、w(Zn)、w(Pb)、w(Cr)、w(Cd)、w(As)、w(Hg)、w(Ni)的平均值分别为35.0、141、12.6、62.6、0.36、27.5、0.145、47.6 mg/kg,分别是江苏省土壤重金属环境背景值的1.50、2.17、0.57、0.83、4.22、2.93、5.78、1.45倍,阳澄西湖的重金属含量要高于阳澄中湖和阳澄东湖.地积累指数法和潜在生态风险指数法评价结果均表明,Hg和Cd是主要的生态风险贡献因子,二者生态风险指数平均值分别为231.23、126.63.相关分析结果表明,阳澄湖表层沉积物中Cu、Zn、Pb、Cr、Cd、Hg和Ni的质量分数显著相关,说明其具有相似的来源,结合水系结构和周边企业分布,推测其主要来自于相城区和常熟市的工业企业.      

Estimating changes in flood risks and benefits of non-structural adaptation strategies - a case study from Tyrol,Austria

Flood damage has increased significantly and is expected to rise further in many parts of the world. For assessing potential changes in flood risk, this paper presents an integrated model chain quantifying flood hazards and losses while considering climate and land use changes. In the case study region, risk estimates for the present and the near future illustrate that changes in flood risk by 2030 are relatively low compared to historic periods. While the impact of climate change on the flood hazard and risk by 2030 is slight or negligible, strong urbanisation associated with economic growth contributes to a remarkable increase in flood risk. Therefore, it is recommended to frequently consider land use scenarios and economic developments when assessing future flood risks. Further, an adapted and sustainable risk management is necessary to encounter rising flood losses, in which non-structural measures are becoming more and more important. The case study demonstrates that adaptation by non-structural measures such as stricter land use regulations or enhancement of private precaution is capable of reducing flood risk by around 30 %. Ignoring flood risks, in contrast, always leads to further increasing losses—with our assumptions by 17 %. These findings underline that private precaution and land use regulation could be taken into account as low cost adaptation strategies to global climate change in many flood prone areas. Since such measures reduce flood risk regardless of climate or land use changes, they can also be recommended as no-regret measures.     

闽江福州段与城市内河表层沉积物重金属污染特征研究

为了探讨城市内河对闽江福州段重金属污染的影响特征,本文对闽江福州段和福州城市主要内河表层沉积物中的Cr、Ni、Cu、Zn、As和Pb 6种重金属元素进行了系统的分析,并采用地累积指数法和潜在生态风险评价法进行污染情况和潜在危险评估.研究结果表明,表层沉积物中重金属Cr、Ni、Cu、Zn、As和Pb含量范围分别为:5.55~131.35、0.74~138.82、2.45~95.84、24.24~609.72、2.82~95.90、13.91~108.45mg·kg~(-1),各重金属含量平均值明显高于福建省土壤环境背景值,但低于国家土壤环境质量Ⅱ类标准值(除As略高于Ⅱ类标准).地累积指数法评价结果表明,表层沉积物中重金属大多为无污染或中污染程度,受人类活动影响强烈.潜在生态风险评价法表明,表层沉积物中重金属Cr、Ni、Cu、Pb和Zn存在轻微潜在风险,As以中等潜在风险为主,总体存在轻微潜在风险.重金属污染物的空间分布与福州市的发展格局相适应,人类活动集中的老城区和工业密集区,是闽江与内河重金属污染物含量相对较高的区域.城市内河汇入闽江后,携带的大量重金属污染物加剧了闽江重金属污染.建议加强对闽江重金属含量较高的晋安河段、光明港段-磨溪河段的污水排放监控.     

Vegetation Placement for Summer Built Surface Temperature Moderation in an Urban Microclimate

Urban vegetation can mitigate increases in summer air temperature by reducing the solar gain received by buildings. To quantify the temperature-moderating influence of city trees and vine-covered buildings, a total of 13 pairs of temperature loggers were installed on the surfaces of eight buildings in downtown Toronto, Canada, for 6 months during the summer of 2008. One logger in each pair was shaded by vegetation while the other measured built surface temperature in full sunlight. We investigated the temperature-moderating benefits of solitary mature trees, clusters of trees, and perennial vines using a linear-mixed model and a multiple regression analysis of degree hour difference. We then assessed the temperature-moderating effect of leaf area, plant size and proximity to building, and plant location relative to solar path. During a period of high solar intensity, we measured an average temperature differential of 11.7 °C, with as many as 10–12 h of sustained cooler built surface temperatures. Vegetation on the west-facing aspect of built structures provided the greatest temperature moderation, with maximum benefit (peak temperature difference) occurring late in the afternoon. Large mature trees growing within 5 m of buildings showed the greatest ability to moderate built surface temperature, with those growing in clusters delivering limited additional benefit compared with isolated trees. Perennial vines proved as effective as trees at moderating rise in built surface temperature to the south and west sides of buildings, providing an attractive alternative to shade trees where soil volume and space are limited.     

Improved space–time forecasting of next day ozone concentrations in the eastern US

There is an urgent need to provide accurate air quality information and forecasts to the general public and environmental health decision-makers. This paper develops a hierarchical space–time model for daily 8-h maximum ozone concentration (O₃) data covering much of the eastern United States. The model combines observed data and forecast output from a computer simulation model known as the Eta Community Multi-scale Air Quality (CMAQ) forecast model in a very flexible, yet computationally fast way, so that the next day forecasts can be computed in real-time operational mode. The model adjusts for spatio-temporal biases in the Eta CMAQ forecasts and avoids a change of support problem often encountered in data fusion settings where real data have been observed at point level monitoring sites, but the forecasts from the computer model are provided at grid cell levels. The model is validated with a large amount of set-aside data and is shown to provide much improved forecasts of daily O₃ concentrations in the eastern United States.     

Modeling Pareto efficient PM10 control policies in Northern Italy to reduce health effects

High PM10 concentrations can cause human health problems, both related to short-term and long-term exposure to particles. In this work the impact of efficient PM10 control problems in Northern Italy is assessed by means of a two-stage methodology. In the first stage a multi-objective optimization approach is applied. The multi-objective problem defines two control objectives (the emission reduction costs and the air quality index) to be minimized varying the decision variables (precursor emission reductions). The solution of the multi-objective problem is the Pareto efficient PM10 control policies. In the second stage, the ExternE methodology is applied to estimate health impacts and external costs for the efficient emission reduction scenarios computed in the first stage. The methodology has been applied over Lombardia region, one of the most polluted areas in Europe.