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1.
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。 相似文献
2.
合成麝香是一类近十多年才引起人们关注的有机污染物.合成麝香广泛分布于环境中.难降解,易生物富集,对水生生物和人体均呈现一定的生物毒性.文章对某一化妆品厂生产车闯内、外及工厂外的上、下风向大气中多环麝香进行了定性定量分析,结果表明,除ATⅡ之外,大气中检测出了五种多环麝香,其中作为对照点的上风向多环麝香总浓度为5.43ng/m3,而工厂室内、外及下风向的多环麝香浓度范围为17.25~5543.4ng/m3;气固分配实验研究发现,超过68.43%的多环麝香分布于气相中. 相似文献
3.
Source characterization of ambient fine particles at multiple sites in the Seattle area 总被引:2,自引:0,他引:2
To identify major PM2.5 (particulate matter ≤2.5 μm in aerodynamic diameter) sources with a particular emphasis on the ship engine emissions from a major port, integrated 24 h PM2.5 speciation data collected between 2000 and 2005 at five United State Environmental Protection Agency's Speciation Trends Network monitoring sites in Seattle, WA were analyzed. Seven to ten PM2.5 sources were identified through the application of positive matrix factorization (PMF). Secondary particles (12–26% for secondary nitrate; 17–20% for secondary sulfate) and gasoline vehicle emissions (13–31%) made the largest contributions to the PM2.5 mass concentrations at all of the monitoring sites except for the residential Lake Forest site, where wood smoke contributed the most PM2.5 mass (31%). Other identified sources include diesel vehicle emissions, airborne soil, residual oil combustion, sea salt, aged sea salt, metal processing, and cement kiln. Residual oil combustion sources identified at multiple monitoring sites point clearly to the Port of Seattle suggesting ship emissions as the source of oil combustion particles. In addition, the relationship between sulfate concentrations and the oil combustion emissions indicated contributions of ship emissions to the local sulfate concentrations. The analysis of spatial variability of PM2.5 sources shows that the spatial distributions of several PM2.5 sources were heterogeneous within a given air shed. 相似文献
4.
Kelsey RH Scott GI Porter DE Thompson B Webster L 《Environmental monitoring and assessment》2003,81(1-3):337-348
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. 相似文献
5.
徐州城市表层土壤中重金属的富积、分布特征与环境风险 总被引:3,自引:0,他引:3
研究了徐州城市表层土壤的21个样品中30种元素的富集与分布特征。结果表明,与我国土壤元素的背景值(算术平均值)相比,表层土壤中Zn、Cd、As、Hg、Sb、Sn、Ag等元素富集大;Fe、Se、Sc、Ba、Bi、Pb、Cu、Ni、Cr、Mn、Mo、Be、Ti、Al、Ga、Li、Co等元素的富集较小。污染元素的空间分布特征显示了Zn、Cu、Pb、Cd等元素主要与交通运输等扩散污染源相关,而元素As、Sb的空间分布主要与工业污染源(点源)有关。环境风险指数的计算结果表明,表层土壤中重金属污染具有较大的环境风险,其中属于中等环境风险级别以上的样品占近40%,而且高风险区域主要集中在钢铁厂和化机厂等工业区范围内。 相似文献
6.
大气可吸入颗粒物研究进展 总被引:24,自引:0,他引:24
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。 相似文献
7.
8.
《环境科学学报(英文版)》2023,35(3):553-567
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 PM2.5; 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 PM2.5 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. 相似文献
9.
上海市大气颗粒物高浓度区污染物的源解析 总被引:37,自引:0,他引:37
应用受体模式的化学质量平衡法支9个监测点的大气颗粒物进行污染源的源解析,得出这9个监测点的各类污染源平均贡献率为建筑尘占32.1%,土壤尘占27.5%,钢铁尘占24.9%,燃煤尘占14.8%,汽车尘和燃油尘分别占0.2%和0.4%。 相似文献
10.