Environmetrical interpretation of analytical data of marine organisms from the black sea

The environmetrical analysis of the benthic organisms data set from a Black sea region has revealed new information concerning the chemical content and the bioindicating abilities of polychaeta (Melina palmata), Crustacea (Aspendopsis ostroumovi) and molluscs (Mytilus gallo‐provincialis). The application of various multivariate statistical approaches like cluster and principal component analysis, linear regression and partial least square modeling, source apportioning makes it possible to understand in a better way the properties of the benthic organism as collectors of pollutants in a total and a more specific mode. It is shown that heavily polluted coastal zones are indicated in the same way by all benthic species but some specificity could be detected when moderately polluted zones are considered. In this case polychaeta accumulated preferably Co, Cr, Cu and Pb Crustacea ‐ As, Cd and Ni and molluscs ‐ Zn to a limited extent.

PCA identified three latent factors (“anthropogenic flotation”;, “anthropogenic galvanic”; and “naturally occurring") which explain about 65% of the total variance of the system and determine the data set structure. The source apportioning on the absolute principal component scores proved that none of the metals is quantitatively linked with only one anthropogenic or natural source.

The linear regression and PLS models have indicated that a reliable prognosis of the pollution on some naturally occurring chemical components (e.g. linear regression on Zn for Cr and Ni) or combination of them (PLS modeling on Mn/Zn or on Mn/Zn/Fe for the rest of the pollutants) could be achieved.     

Using structural equation modeling to investigate relationships among ecological variables

Structural equation modeling is an advanced multivariate statistical process with which a researcher can construct theoretical concepts, test their measurement reliability, hypothesize and test a theory about their relationships, take into account measurement errors, and consider both direct and indirect effects of variables on one another. Latent variables are theoretical concepts that unite phenomena under a single term, e.g., ecosystem health, environmental condition, and pollution (Bollen, 1989). Latent variables are not measured directly but can be expressed in terms of one or more directly measurable variables called indicators. For some researchers, defining, constructing, and examining the validity of latent variables may be the end task of itself. For others, testing hypothesized relationships of latent variables may be of interest. We analyzed the correlation matrix of eleven environmental variables from the U.S. Environmental Protection Agency's (USEPA) Environmental Monitoring and Assessment Program for Estuaries (EMAP-E) using methods of structural equation modeling. We hypothesized and tested a conceptual model to characterize the interdependencies between four latent variables-sediment contamination, natural variability, biodiversity, and growth potential. In particular, we were interested in measuring the direct, indirect, and total effects of sediment contamination and natural variability on biodiversity and growth potential. The model fit the data well and accounted for 81% of the variability in biodiversity and 69% of the variability in growth potential. It revealed a positive total effect of natural variability on growth potential that otherwise would have been judged negative had we not considered indirect effects. That is, natural variability had a negative direct effect on growth potential of magnitude –0.3251 and a positive indirect effect mediated through biodiversity of magnitude 0.4509, yielding a net positive total effect of 0.1258. Natural variability had a positive direct effect on biodiversity of magnitude 0.5347 and a negative indirect effect mediated through growth potential of magnitude –0.1105 yielding a positive total effects of magnitude 0.4242. Sediment contamination had a negative direct effect on biodiversity of magnitude –0.1956 and a negative indirect effect on growth potential via biodiversity of magnitude –0.067. Biodiversity had a positive effect on growth potential of magnitude 0.8432, and growth potential had a positive effect on biodiversity of magnitude 0.3398. The correlation between biodiversity and growth potential was estimated at 0.7658 and that between sediment contamination and natural variability at –0.3769.     

珠江广州河段底泥中汞铜铅的污染及其与有机质硫化物积累的关系

珠江广州河段底泥中有机质、硫化物和重金属汞、铜、铅的污染监测结果表明：各种污染物的含量范围分别为有机质２０．８—７４．４ｇ／ｋｇ，硫化物２８．７—５３８ｍｇ／ｋｇ，汞０．０７－０．７４ｍｇ／ｋｇ，铜２０．９—１０１ｍｇ／ｋｇ，铅１４．２—９１７ｍｇ／ｋｇ；它们在沿程各断面的分布表现为上游往中游递增，而中游向下游递减，基本上以猎德、广纸和黄沙三个断面的污染最严重；各种污染物的污染程度顺序是硫化物＞汞＞铜＞铅。相关分析表明：汞、铜与有机质和硫化物的相关关系均达到极显著水平。说明随着底泥中有机质和硫化物积累的增加，汞、铜的富集量相应增加，污染加重。     

河南省大气污染的气候分类

分析确定了影响大气污染的主要气候因子。根据省内各气象站的常规测资料，采用模糊聚类和纳污指数的方法将该省分成５个气候类型区。结果表明，纳污能力以中部地区为最强，占全省面积３／５的南、东、北邻近省界地区较强，豫西山区最弱。     

珠三角工业城市污染物入河量空间特征分析

以东莞市第一次全国污染源普查成果为数据基础,调查估算2010年东莞市33个镇街和25个水功能区的COD、氨氮入河量,并应用GIS技术及相关分析法分析污染物入河量空间分布特征及其影响因素。研究发现：①东莞市各镇街及水功能区的污染物入河量呈明显不均匀分布,人口、GDP是影响污染物入河量空间分布的主要因素。②河网区、非河网区镇街的工业污染物入河量与GDP均呈较好的正相关关系,但非河网区单位污染物入河量GDP产出拟合曲线斜率是河网区的31倍,显示河网区镇街每增长单位污染物入河量所产生的GDP远远小于非河网区,河网区镇街往往付出巨大的污染代价而经济增长却非常有限。     

Critical ranges of pollution indices: a tool for predicting soil metal pollution under long-term wastewater reuse

A greenhouse experiment was conducted in pots, for two years (2015–2016), in Amaliada, Greece, using a randomized block design, including six treatments with mixtures composed of Zn, Mn, Cd, Co, Cu, Cr, Ni, and Pb, each metal taking part in the mixture at concentrations of 0, 10, 20, 30 40, and 50 mg/kg soil in four replicates each. Beta vulgaris (beet) was used as a test plant. The aim of the experiment was to calibrate the following pollution indices: “pollution load index,” “elemental pollution index,” “heavy metal load,” and “total concentration factor,” in order to determine the level of soil pollution under variable levels (low to very high) of metal mixtures. The irrigation of the plants was conducted with treated municipal wastewater based on field capacity and percent wilting point. The above pollution indices were classified into four soil pollution classes, i.e., “optimum,” “low,” “high” and “very high” on the basis of percent dry matter plant losses.     

A factor analysis study: Air pollution,meteorology, and hospital admissions for respiratory diseases

It is well known that air pollution exerts adverse effects on health and environment. Bal?kesir located in the Marmara region (Turkey) has serious air pollution problems produced by heating in the months of winter. In this study, the effect of exposure to air pollution on hospital admission for respiratory illnesses among children and adults was examined. Epidemiological data from records of hospitals, air pollutants and meteorological data were used. During July 2005–July 2007 period, there was a total of 280,426 hospital admissions for respiratory diseases. In a population-based analysis, 9 children were admitted for asthma, 17 children for acute bronchitis, and 20 children for lower respiratory diseases out of 100 children. There was a significant increase in the hospital admissions for respiratory diseases and air pollutants from October to March. It was concluded that children living in the city suffer from respiratory diseases such as asthma, pneumonia, and lower respiratory diseases. Three factors that account for approximately 90% of total variance of hospital admissions, air pollution, and meteorology were identified by means of principal component factor analysis.     

渭河水中有机物在几种土壤中的吸附特性

通过批量实验研究了渭河水中有机物在几种土壤中的吸附行为，测得吸附常数，给出吸附等温线。对吸附等温线进行分析，发现已经吸附的有机物分子会影响土壤的吸附性质。同时数据的拟合表明，有机物在不同土样中的吸附行为均可用Freundlich方程描述。吸附常数和固相一水分配系数表明4种土样中河沙的吸附能力最强，进一步的实验发现这是由于河沙中已经吸附的有机物最少，吸附位相对多，造成吸附能力强。     

土壤污染物来源及前沿问题

人类活动对土壤系统的影响日趋严重。土壤污染物主要来自污染的大气沉降，废水和污水灌溉，工业废渣和城市垃圾，以及农药施用等。土壤污染对环境和人体健康造成极大的危害。文章通过计算得出了大气汞沉降和酸沉降在中国的累积沉降量，并通过调查分析中国各项污染物来源的最新资料，详细论述了各主要污染因素对土壤系统的影响。文章阐述了污染物在土壤系统中主要的物理化学行为，主要包括污染物在土壤生态系统中的吸附、迁移和扩散、酸沉降对土壤系统的影响等三个方面。最后回顾了该领域的研究现状和主要的前沿问题，并对进一步的深入研究提出了建议。     

土壤中有机污染物-重金属复合污染的交互作用

有机污染物-重金属复合污染是一种普遍存在的环境污染形式,对其进行研究具有重要的理论意义和实践价值。本文主要讨论了有机污染物和重金属在土壤中的吸附过程、化学作用过程以及生物学过程等的交互作用方式及其机理。     

Total phosphorus accident pollution and emergency response study based on geographic information system in Three Gorges Reservoir area

• A new algorithm of two-dimensional water quantity and the quality model was built. • The migration and diffusion of TP was simulated. • The emergency measures for sudden water pollution accidents was proposed. In recent years, sudden water pollution accidents in China’s rivers have become more frequent, resulting in considerable effects on environmental safety. Therefore, it is necessary to simulate and predict pollution accidents. Simulation and prediction provide strong support for emergency disposal and disaster reduction. This paper describes a new two-dimensional water quantity and the quality model that incorporates a digital elevation model into the geographic information system. The model is used to simulate sudden water pollution accidents in the main stream of the Yangtze River and Jialing River in the Chongqing section of the Three Gorges Reservoir area. The sectional velocity distribution and concentration change of total phosphorus are then analyzed under four hydrological situations. The results show that the proposed model accurately simulates and predicts the concentration change and migration process of total phosphorus under sudden water pollution accidents. The speed of migration and diffusion of pollutants is found to be greatest in the flood season, followed by the water storage period, drawdown season, and dry season, in that order. The selection of an appropriate water scheduling scheme can reduce the peak concentration of river pollutants. This study enables the impact of pollutants on the ecological environment of river water to be alleviated, and provides a scientific basis for the emergency response to sudden water pollution accidents in the Three Gorges Reservoir area.     

A GIS-based approach to spatio-temporal analysis of environmental pollution in urban areas: A case study of Prague's environment extended by LIDAR data

Environmental pollution of urban areas is one of key factors that state authorities and local agencies have to consider in the decision-making process. To find a compromise among many criteria, spatial analysis extended by geostatistical methods and dynamic models has to be carried out. In this case, spatial analysis includes processing of a wide range of air, water and soil pollution data and possibly noise assessment and waste management data. Other spatial inputs consist of data from remote sensing and GPS field measurements. Integration and spatial data management are carried out within the framework of a geographic information system (GIS). From a modeling point of view, GIS is used mainly for the preprocessing and postprocessing of data to be displayed in digital map layers and visualized in 3D scenes. Moreover, for preprocessing and postprocessing, deterministic and geostatistical methods (IDW, ordinary kriging) are used for spatial interpolation; geoprocessing and raster algebra are used in multi-criteria evaluation and risk assessment methods. GIS is also used as a platform for spatio-temporal analyses or for building relationships between the GIS database and stand-alone modeling tools. A case study is presented illustrating the application of spatial analysis to the urban areas of Prague. This involved incorporating environmental data from monitoring networks and field measurements into digital map layers. Extra data inputs were used to represent the 3D concentration fields of air pollutants (ozone, NO₂) measured by differential absorption LIDAR. ArcGIS was used to provide spatial data management and analysis, extended by modeling tools developed internally in the ArcObjects environment and external modules developed with MapObjects. Ordinary kriging methods were employed to predict ozone concentrations in selected 3D locations together with estimates of variability. Higher ozone concentrations were found above crossroads with their heavy traffic than above the surrounding areas. Ozone concentrations also varied with height above the digital elevation model. Processed data, spatial analysis and models are integrated within the framework of the GIS project, providing an approach that state and local authorities can use to address environmental protection issues.     

城市路面降雨径流污染特征及源解析的研究进展

城市路面径流是城市地表径流的重要组成部分,因其污染强度大、对地表水体的影响严重而被予以格外的关注。通过对国内外关于路面径流水质的研究进行总结发现：我国城市道路径流中COD、TP、TN和Pb的平均质量浓度分别为239.59、0.46、6.29和0.14 mg·L-1,超过了国家地表水环境质量Ⅴ类标准,TSS的质量浓度高达552.86 mg·L-1。因此,COD、TP、TN、Pb和TSS是我国路面径流的主要污染物。高速路径流污染物Pb、Cu和Zn的浓度明显高于普通道路,而普通道路径流污染物中COD和TSS要高于高速路。与其他国家相比,我国城市道路雨水径流污染物浓度偏高。多数研究表明：污染物的质量浓度与降雨量呈负相关关系,路面坡度增加了车辆与路面的摩擦力和燃料的消耗,进而导致路面径流污染物的浓度较高,路面清扫或许对污染物的浓度有不利的影响,主要由于道路清扫将路面中部分大颗粒破碎,释放出了细小的颗粒物（粒径〈43μm）并且不能将其清除的缘故。但是,降雨强度、干期、降雨历时和车流量对径流水质的影响存在一定的争议。通过对现有的研究总结发现：车流量≥30000的路面径流中COD、TSS、Pb和Cu的浓度是车流量〈30000的路面径流中的2.5、4.3、1.4和5.1倍;路面径流中的重金属主要来源于车辆的交通损耗,有机污染物来源于车辆的交通活动和路面材质,营养污染物来源于大气干湿沉降。今后应从以下几方面开展研究：将多环芳烃、大肠杆菌等水质指标列入研究计划;深入分析影响降雨径流水质的因素及各影响因子间的交互作用;运用同位素溯源技术识别道路径流污染物来源。     

Bewertungsverfahren Verfahren zur Bewertung von immissionsbedingten Stoffanreicherungen in standardisierten Graskulturen

Standardized grass cultures are routinely used to evaluate the accumulation of air pollutants. For the assessment of air pollutant accumulation in grass cultures, it is particularly important to distinguish between “normal” concentrations and the significantly increased accumulation caused by air pollution. This article presents a method to determine “normal” element concentrations (background levels) and define threshold values for the significantly elevated accumulation of pollutants for individual series of grass cultures. By applying the same method for the data from six regional air quality measuring programs, it was possible to derive universally applicable “normal” concentrations and threshold values for grass cultures. The described method is not limited to the evaluation of data from grass cultures but is also suitable for other biological or ecological data. It allows to distinguish between “normal” element concentrations and unusually high or low concentrations.     

嘉善冬季PM2.5化学组分特征及来源分析

为研究嘉兴地区嘉善冬季污染时段和清洁时段PM_2.5化学组分特征,结合气象数据对2019年1月嘉兴市嘉善县善西超级站在线自动监测PM_2.5及化学组分数据、气态污染物(NO₂和SO₂)进行了分析.结果表明,2019年1月嘉善善西超级站污染时段PM_2.5浓度(97.18μg·m^-3)为清洁时段(36.77μg·m^-3)的2.6倍.污染时段水溶性离子浓度(41.58μg·m^-3)较清洁时段(19.82μg·m^-3)高21.76μg·m^-3,但占比有所降低,含碳组分比例增加.OC;EC比值为3.93,可能受到燃煤及机动车排放的共同影响.低风速及高湿有利于NO₂和SO₂等气态污染物进行二次转化,污染时段硫转化率和氮转化率均比清洁时段高,分别增高7.93%和54.11%,说明NOx向硝酸盐二次转化较为明显,导致颗粒物浓度升高.聚类分析结果显示67.34%气流来自北方,且相应的气流轨迹上污染物浓度比周边高,说明污染物存在一定的长距离输送.结合风玫瑰图可以看出,污染主要为本地及其周边的输送,污染物的长距离输送在短时会使污染浓度突增.因此,在重点关注本地及周边污染的同时,偏北气流下的污染物区域输送不可忽视.     

沣河水系脱氮微生物群落结构研究

河流水体氮素的超负荷不仅破坏了水体生态环境,也严重威胁着人类的生存和发展.水体中有机氮、无机氮（氨氮、亚硝氮、硝氮）和分子氮之间的转化（氮循环）有赖于水体中大量的氮循环微生物（固氮细菌、硝化细菌和反硝化细菌）,然而这些氮循环微生物的生长繁殖也受到包括氮素的形态和浓度在内的多种环境因子的影响,这些因素也通过影响氮循环微生物的生长繁殖进而使得水体中氮素的转化速率发生变化,对水体氮污染的防治有不可忽视的作用.本研究通过在沣河设置不同的研究断面,采集水体样品,进行水质分析,并通过现代分子生物学技术（PCR-DGGE）方法对研究断面水体中氮循环微生物（固氮细菌、硝化细菌和反硝化细菌）的群落结构进行分析.再通过统计学软件对所得分子生物学信息与水质环境因子的相关性进行统计学分析,发现沣河水体中氮循环微生物群落结构受到多种环境因子共同影响,且在枯水期和丰水期表现出不同的特征.在丰水期沣河水体中,硝化细菌群落在中游表现出较高的多样性和丰富性,这与沣河中上游农业COD（化学需氧量）、BOD（生化需氧量）氨氮及有机氮污染物排放量较大,沣河水体DO（溶解氧）高有关.水体中的氨氮、亚硝氮、温度的增加是促进水体中硝化细菌的均匀性和丰富度的增高的主要因子,而pH 值的升高,使得水体中硝化细菌的均匀性和丰富度降低.反硝化微生物在中游和下游的多样性和丰富度较高,与有机物及硝酸盐含量相关.水体中的BOD、COD、TP（总磷）、硝氮的增加是促进水体中反硝化细菌的均匀性和丰富度的增高主要相关因子,而DO 的增多则会对部分反硝化细菌产生不利影响,使得水体中反硝化细菌的均匀性和丰富度降低.本研究结果为沣河以及其他河流的污染控制以及基于微生物的生态修复提供了科?     

Planning for the monitoring of pollutants from non‐stationary combustion sources†

The most important constituents of traffic exhaust are carbon monoxide, nitrogen oxides, volatile organic compounds, polycyclic hydrocarbons and lead. Satisfactory analytical methods are available for measuring these compounds, but the required expenditure in their application to air pollution studies is quite different. Due to correlations between the concentrations of several exhaust components in road air conclusions regarding the expected level of some substances can be drawn by measurement of another emitted compound. But the selection of indicator compounds must be made under the aspect of the source‐specific relationship of emitted substances. The temporal and spatial distribution of air pollutants in street air is affected by traffic emissions more than by meteorological conditions. “Fingerprints”; of typical organic gaseous components of traffic exhaust also were found in residential areas.     

1985年以来我国重大水体突发污染事件及在线生物监测的必要性分析

通过查阅和检索公开报道的期刊、报纸和网络,统计分析我国1985以来水体突发污染事件。1985—2015年间,我国水体突发污染事件年均发生数量总体变化呈现先动态增长后逐渐下降的趋势,其中2006年为水体突发性污染事件发生频次的转折点。导致水体突发性污染的主要原因包括企业违规排放、企业事故性泄漏、交通事故、自然因素和人为投毒等,污染方式多样。水体突发性污染的污染物种类包括化学品、污水(工业废水和生活污水)、油类、农药、重金属、生物污染物和其他不明污染物。鉴于水体突发性污染事件污染方式的多样性和污染物的复杂性,采用在线生物监测技术可实现对水体突发性污染事件在线监测与分析预警,已成为当前监测和评价水体突发污染事件有效手段。     

广州市空气污染物和气象要素的主成分与典型相关分析

用主成分和典型相关分析方法分析广州市近4a(2001—2004年)的空气污染物与气象要素之间的关系,按夏半年、冬半年和全年3个时间尺度分别进行。结果表明:污染物数据所得到的主成分分别代表机动车污染源(汽油燃烧和扬尘)和工业污染源(工业燃煤和燃油),气象数据的主成分分析表明空气的温度、湿度及对流速度对空气污染作用明显,而污染物和气象要素的主成分分析表明气温高低和空气干湿程度对大气污染的影响较大。污染物与气象要素两组数据之间的典型相关分析表明污染物与气象要素之间存在显著的相关关系,其中温度和风速对气态污染物有显著影响。     

大气化学污染的植物净化研究进展

大气污染是人类面临的严重环境问题之一,植物除了可以监测大气的化学污染外,在近地表大气污染物的清除中起着重要作用。利用植物净化大气化学污染是一种经济、有效、非破坏型的环境污染修复方式,植物净化污染大气的思想及其技术对城市园林绿化、环境规划和生态环境建设等具有直接的指导意义和应用价值。文章简要介绍了大气化学污染植物净化的机理,综述了近年来利用植物净化大气无机污染物和有机污染物的研究成果,并展望了今后需要进一步研究的领域。植物净化化学性大气污染的主要过程是持留和去除:持留过程涉及植物截获、吸附和滞留等,去除过程包括植物吸收、降解、转化、同化和超同化等。利用生物学、化学、农学、土壤科学和环境科学等多学科交叉,筛选高效的净化植物、研究污染物在植物体内的转化机理和影响净化效果的因素、开发联合修复技术、培育转基因净化植物等是未来研究的主要方向。