工业源重点调查单位分界点的确定

讨论了工业源重点调查单位分界点确定的思路和方法,并基于污染源普查更新调查中河南省的数据(数据时点为2010年)进行了实证研究,研究结果表明,所有污染物产排指标都呈现出高度右偏分布,适宜采用目录抽样法,将工业源区分为重点污染源和非重点污染源,对重点污染源进行全面调查,对非重点污染源进行抽样调查,分界点可以下调到80%。     

上海市环境监测质量管理规划探讨

针对上海市环境监测行业质量管理工作在宏观管理和微观控制两个方面存在的问题,制定了上海市环境监测质量管理近期和中期规划。建立质量管理信息共享平台和QC指标评定体系,组建质量与技术管理委员会,建立环境质量和污染源连续自动监测系统的QA/QC体系。在全市环境监测行业内建立质量管理考核评价体系和法制保障体系,推进LIMS建设并实现与上海市环境监测中心LIMS的无缝链接,探索构建"上海市水环境监测质量控制平台"。     

Air pollution sources of PM10 in Buenos Aires City

To elucidate the sources of PM(10) air pollution from the experimental information collected in a local air quality monitoring campaign we have applied two methods, effective variance and genetic algorithms, in the solution of the chemical mass balance. The comparison of these two mathematical approaches show that the identification of the possible sources and the evaluation of its contributions are quite independent of them. The role of possible different sources for major and trace elements and the significance of standardizing available data is also addressed. We also present a simple method for identifying the number of candidate sources, a key element defining the dimension of the search space.     

Air Pollution Estimates in Guadalajara City

A method for estimating the impact of industrial emissions is suggested and applied to the Guadalajara City Metropolitan Area (GCMA). The method is based on solutions to the pollution transport model and its adjoint. Two equivalent direct and adjoint mean pollution concentration estimates are considered for ecologically important zones of the GCMA. The dependence of these estimates on the number, positions and emission rates of industrial plants, as well as on the wind and initial pollution distribution in the GCMA is qualitatively and quantitatively examined. It is shown that the adjoint model solutions serve as the influence functions providing valuable information on the role of each of the industrial plants in polluting different zones within the GCMA. These solutions have been calculated with a balanced and absolutely stable second-order finite-difference scheme based on the splitting method. A method for an optimal allocation of a new industrial plant is considered.     

Optimization of fertirrigation efficiency in strawberry crops by application of fuzzy logic techniques

A high level of price support has favoured intensive agriculture and an increasing use of fertilisers and pesticides. This has resulted in the pollution of water and soils and damage to certain eco-systems. The target relationship that must be established between agriculture and environment can be called "sustainable agriculture". In this work we aim at relating strawberry total yield with nitrate concentration in water at different soil depths. To achieve this objective, we have used the Predictive Fuzzy Rules Generator (PreFuRGe) tool, based on fuzzy logic and data mining, by means of which the dose that allows a balance between yield and environmental damage minimization can be determined. This determination is quite simple and is done directly from the obtained charts. This technique can be used in other types of crops permitting one to determine in a precise way at which depth the appropriate dose of nitrate fertilizer must be correctly applied, on the one hand providing the maximum yield but, on the other hand, with the minimum loss of nitrates that leachate through the saturated zone polluting aquifers.     

Groundwater contamination and its effect on health in Turkey

The sources of groundwater pollution in Turkey are identified, and pathways of contaminants to groundwater are first described. Then, the effects of groundwater quality on health in Turkey are evaluated. In general, sources of groundwater contamination fall into two main categories: natural and anthropogenic sources. Important sources of natural groundwater pollution in Turkey include geological formations, seawater intrusion, and geothermal fluid(s). The major sources of anthropogenic groundwater contamination are agricultural activities, mining waste, industrial waste, on-site septic tank systems, and pollution from imperfect well constructions. The analysis results revealed that natural contamination due to salt and gypsum are mostly found in Central and Mediterranean regions and arsenic in Aegean region. Geothermal fluids which contain fluoride poses a danger for skeleton, dental, and bone problems, especially in the areas of Denizli, Isparta, and Ayd?n. Discharges from surface water bodies contaminate groundwater by infiltration. Evidence of such contamination is found in Upper K?z?l?rmak basin, Gediz basin, and Büyük Melen river basin and some drinking water reservoirs in ?stanbul. Additionally, seawater intrusion causes groundwater quality problems in coastal regions, especially in the Aegean coast. Industrial wastes are also polluting surface and groundwater in industrialized regions of Turkey. Deterioration of water quality as a result of fertilizers and pesticides is another major problem especially in the regions of Mediterranean, Aegean, Central Anatolia, and Marmara. Abandoned mercury mines in the western regions of Turkey, especially in ?anakkale, ?zmir, Mu?la, Kütahya, and Bal?kesir, cause serious groundwater quality problems.     

Domestic Water Contamination in Rapidly Growing Megacities of Asia: Case of Karachi, Pakistan

The development of essential services including water and sanitation in many megacities of the economically developing countries of Asia cannot keep pace with their rapidly growing population and accompanying urban and industrial development. The inadequate water supply and poor sanitation services lead to contamination of their water supply. It also leads to the input of sewage water into the groundwater. The problem is seriously acute in Karachi, the largest city in Pakistan with a population of over 12 million and growing at 6 percent. This paper examines the problem of water contamination in Karachi. The paper presents the data on water quality from various sources, mainly municipal water supply, vendors and well water; the three major sources of water for domestic use in Karachi. Except municipal water from some areas and during certain periods, water from most other sources contain coliform bacteria, and in many cases faecal coliform, in amounts several magnitudes higher than any standards permit. Many samples have also been found to contain heavy metals including Chromium, Lead, Nickel and Arsenic in amounts excessive of permitted standards. The probable sources of contaminants for the various types of water (piped, vendors, wells) indicate that groundwater may be the main contributor. The very source of this groundwater is predominantly from sewage. The health hazards from consuming such contaminated water are obvious. The paper also evaluates the solutions that are being practiced, proposed or may be feasible, as well as those that are evolving.     

Uncertain spatial reasoning of environmental risks in GIS using genetic learning algorithms

Modeling the impact of air pollution is one of the most important approaches for managing damages to the ecosystem. This problem can be solved by sensing and modeling uncertain spatial behaviors, defining topological rules, and using inference and learning capabilities in a spatial reasoning system. Reasoning, which is the main component of such complex systems, requires that proper rules be defined through expert judgments in the knowledge-based part. Use of genetic fuzzy capabilities enables the algorithm to learn and be tuned to proper rules in a flexible manner and increases the preciseness and robustness of operations. The main objective of this paper was to design and evaluate a spatial genetic fuzzy system, with the goal of assessing environmental risks of air pollution due to oil well fires during the Persian Gulf War. Dynamic areas were extracted and monitored through images from NOAA, and the data were stored in an efficient spatial database. Initial spatial knowledge was determined by expert consideration of the application characteristics, and the inference engine was performed with genetic learning (GL) algorithms. Finally, GL (0.7 and 0.03), GL (0.7 and 0.08), GL (0.98 and 0.03), GL (0.98 and 0.08), and Cordon learning methods were evaluated with test and training data related to samples extracted from Landsat thematic mapper satellite images. Results of the implementation showed that GL (0.98, 0.03) was more precise than the other methods for learning and tuning rules in the concerned application.     

Application of Microwave Plasma Atomic Emission Spectrometry (MP-AES) for environmental monitoring of industrially contaminated sites in Hyderabad City

Recently introduced microwave plasma-atomic emission spectroscopy (MP-AES) represents yet another and very important addition to the existing array of modern instrumental analytical techniques. In this study, an attempt is made to summarize the performance characteristics of MP-AES and its potential as an analytical tool for environmental studies with some practical examples from Patancheru and Uppal industrial sectors of Hyderabad city. A range of soil, sediment, water reference materials, particulate matter, and real-life samples were chosen to evaluate the performance of this new analytical technique. Analytical wavelengths were selected considering the interference effects of other concomitant elements present in different sample solutions. The detection limits for several elements were found to be in the range from 0.05 to 5 ng/g. The trace metals analyzed in both the sectors followed the topography with more pollution in the low-lying sites. The metal contents were found to be more in ground waters than surface waters. Since a decade, the pollutants are transfered from Patancheru industrial area to Musi River. After polluting Nakkavagu and turning huge tracts of agricultural lands barren besides making people residing along the rivulet impotent and sick, industrialists of Patancheru are shifting the effluents to downstream of Musi River through an 18-km pipeline from Patancheru. Since the effluent undergoes primary treatment at Common Effluent Treatment Plant (CETP) at Patanchru and travels through pipeline and mixes with sewage, the organic effluents will be diluted. But the inorganic pollutants such as heavy and toxic metals tend to accumulate in the environmental segments near and downstreams of Musi River. The data generated by MP-AES of toxic metals like Zn, Cu, and Cr in the ground and surface waters can only be attributed to pollution from Patancheru since no other sources are available to Musi River.     

An Inexact Fuzzy-robust Two-stage Programming Model for Managing Sulfur Dioxide Abatement Under Uncertainty

In this study, an inexact fuzzy-robust two-stage programming (IFRTSP) method is developed for tackling multiple forms of uncertainties that can be expressed as discrete intervals, probabilistic distributions and/or fuzzy membership functions. The model can reflect economic penalties of corrective measures against any infeasibilities arising due to a particular realization of system uncertainties. Moreover, the fuzzy decision space can be delimited into a more robust one with the uncertainties being specified through dimensional enlargement of the original fuzzy constraints. A management problem in terms of regional air pollution control has been studied to illustrate the applicability of the proposed approach. Results indicate that useful solutions for planning the air quality management practices have been generated. They can help decision makers identify desired pollution-abatement strategy with minimized system cost and maximized environmental efficiency.     

Fuzzy clustering analysis in environmental impact assessment — A complement tool to environmental quality index

In spite of rapid progress achieved in the methodological research underlying environmental impact assessment (EIA), the problem of weighting various parameters has not yet been solved. This paper presents a new approach, fuzzy clustering analysis, which is illustrated with an EIA case study on Baoshan-Wusong District in Shanghai, China. Fuzzy clustering analysis may be used whenever a composite classification of environmental quality/impact incorporates multiple parameters. In such cases the technique may be used as a complement or an alternative to comprehensive assessment. In fuzzy clustering analysis, the classification is determined by a fuzzy relation. After a fuzzy similarity matrix has been established and the fuzzy relation stabilized, a dynamic clustering chart can be developed. Given a suitable threshold, the appropriate classification can be accomplished. The methodology is relatively simple and the results can be interpreted to provide valuable information to support decision making and improve management of the environment.     

Analysis of Key Features of Non-Linear Behaviour Using Recurrence Quantification. Case Study: Urban Airborne Pollution at Mexico City

The use of recurrence plots have been extensively used in various fields. In this work, recurrence plots investigate the changes in the non-linear behaviour of urban air pollution using large datasets of raw data (hourly). This analysis has not been used before to extract information from large datasets for this type of non-linear problem. Two different approaches have been used to tackle this problem. The first approach is to show results according to monitoring network. The second approach is to show the results by particle type. This analysis shows the feasibility of using recurrence analysis for pollution monitoring and control.     

The contribution of sensor-based equipment to life cycle assessment through improvement of data collection in the industry

Within the paradigm of “Industry 4.0”, data collection and management acquire new relevance. In this context, the introduction of the Internet of Things (IoT) in the manufacturing field allows to develop information systems able to offer the possibility of using a large amount of data collected from heterogeneous sources in real time. The information thus obtained is functional not only to the attainment of an industrial development but also for evaluation and improvement of its sustainability. For example, the benefit obtainable for the life cycle assessment (LCA) methodology from the new digital configuration is represented by a greater specificity of data that wireless sensors networks (WSN) measure and transmit in a continuous way.This paper explores the benefit of using a sensor for the evaluation of the environmental impact, in particular for LCA, in an Italian company producing chemical formulations. The machinery electric consumption directly measured data is compared with the same data estimated with mathematical models. It highlights how much different approach of data measurement and calculation can affect the LCA results. The detection of the energy variable related to a single machine for a particular process, which has been described in the paper, represents a first step towards the implementation of a WSN, proposed by Scatol8 srl, to be used to produce in a more sustainable way.     

地下水环境质量评价方法

分析了ＧＢ／Ｔ１４８４８－９３《地下水质量标准》提出的评价方法和使用范围的局限性，根据建设项目环境影响评价实际，提出采用模糊综合评判结合单因子污染指数法描述污控因子，评价地下水环境质量的方法，给出模糊综合评判方法步骤，并以实例说明其应用情况。     

Assessment of water quality monitoring for the optimal sensor placement in lake Yahuarcocha using pattern recognition techniques and geographical information systems

Pollution and the eutrophication process are increasing in lake Yahuarcocha and constant water quality monitoring is essential for a better understanding of the patterns occurring in this ecosystem. In this study, key sensor locations were determined using spatial and temporal analyses combined with geographical information systems (GIS) to assess the influence of weather features, anthropogenic activities, and other non-point pollution sources. A water quality monitoring network was established to obtain data on 14 physicochemical and microbiological parameters at each of seven sample sites over a period of 13 months. A spatial and temporal statistical approach using pattern recognition techniques, such as cluster analysis (CA) and discriminant analysis (DA), was employed to classify and identify the most important water quality parameters in the lake. The original monitoring network was reduced to four optimal sensor locations based on a fuzzy overlay of the interpolations of concentration variations of the most important parameters.     

Receptor modeling for analyzing PCDD/F and dioxin-like PCB sources in Hong Kong

A total of 96 ambient air samples were collected from January 2004 to December 2004 for the investigation of dioxins (polychlorinated dibenzo-para-dioxins and polychlorinated dibenzofurans [PCDD/Fs]) and dioxin-like profile for polychlorinated biphenyls (PCBs) in the atmosphere of Hong Kong. Two-day back-trajectories were obtained using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model from National Oceanic and Atmospheric Administration (NOAA) Air Resources Laboratory. Receptor models – potential source contribution function (PSCF) and concentration-weighted trajectory (CWT) – were built based on the measured PCDD/Fs and dioxin-like PCBs total toxic equivalent (TEQ) concentrations. Both models were modified in this study so as to integrate the information obtained from three sampling sites in Hong Kong. The PSCF modeling resolved two main PCDD/F and dioxin-like PCB polluting paths from Mainland China. In line with previous studies, the northerly path around the Pearl River Delta might be one of the pollution sources of Hong Kong air. On the other hand, the receptor models also indicated another potential northeasterly source from Yangtze River Delta, which was seldom mentioned as the source region of Hong Kong air. Results from the CWT modeling suggested that the most toxic air mass affecting Hong Kong is probably attributable to the northeast path rather than the north path.     

Fecal indicator bacteria (FIB) levels during dry weather from Southern California reference streams

High levels of fecal indicator bacteria (FIB) in surface waters is a common problem in urban areas that often leads to impairment of beneficial uses such as swimming. Once impaired, common management and regulatory solutions include development of total maximum daily loads (TMDLs) and other water quality management plans. A critical element of these plans is establishment of a "reference" level of exceedances against which to assess management goals and TMDL compliance. The goal of this study was to provide information on indicator bacteria contributions from natural streams in undeveloped catchments throughout southern California during dry weather, non-storm conditions. To help establish a regional reference data set, bacteria levels [i.e. Escherichia coli (E. coli), enterococci and total coliforms] were measured from 15 unimpaired streams in 11 southern California watersheds weekly for one full year. Concentrations measured from reference areas were typically between one to two orders of magnitude lower than levels found in developed watersheds. Nearly 82% of the time, samples did not exceed daily and monthly bacterial indicator thresholds. E. coli had the lowest daily percent exceedance (1.5%). A total of 13.7% of enterococci exceeded daily thresholds. Indicator bacteria levels fluctuated seasonally with an average of 79% of both enterococci and total coliforms exceedances occurring during summer months (June to August). Temperature, at all sites, explained about one-half the variation in total coliforms density suggesting that stream temperatures regulated bacterial populations. Accounting for natural background levels will allow for management targets that are more reflective of the contributions from natural sources.     

淄博化工园区大气有机污染应急监测与管理对策

针对工业聚集区内多种恶臭混杂的情况,以淄博化工园区为例,研究了大气有机污染突发事件中有机物的应急监测方法,并提出了治理对策。利用便携式气相色谱-质谱联用仪,对重点企业事先监测,掌握各企业特征污染物,作为应急监测查找污染源头的依据;现场分析受污染空气中的化合物组成及浓度,通过查询、比对各企业特征污染物,确认责任排污企业。提出了末端监测处罚治理与对重点污染企业推行清洁生产相结合,应急监测与有机污染物在线监测相结合,建立企业污染源特征组分数据库,加强企业无组织排放监测与监管等治理大气有机污染的建议。     

Fire risk evaluation using multicriteria analysis—a case study

Forest fires are one of the major causes of ecological disturbance and environmental concerns in tropical deciduous forests of south India. In this study, we use fuzzy set theory integrated with decision-making algorithm in a Geographic Information Systems (GIS) framework to map forest fire risk. Fuzzy set theory implements classes or groupings of data with boundaries that are not sharply defined (i.e., fuzzy) and consists of a rule base, membership functions, and an inference procedure. We used satellite remote sensing datasets in conjunction with topographic, vegetation, climate, and socioeconomic datasets to infer the causative factors of fires. Spatial-level data on these biophysical and socioeconomic parameters have been aggregated at the district level and have been organized in a GIS framework. A participatory multicriteria decision-making approach involving Analytical Hierarchy Process has been designed to arrive at a decision matrix that identified the important causative factors of fires. These expert judgments were then integrated using spatial fuzzy decision-making algorithm to map the forest fire risk. Results from this study were quite useful in identifying potential “hotspots” of fire risk, where forest fire protection measures can be taken in advance. Further, this study also demonstrates the potential of multicriteria analysis integrated with GIS as an effective tool in assessing “where and when” forest fires will most likely occur.     

Microbial source tracking: a forensic technique for microbial source identification?

As the requirements of the Water Framework Directive (WFD) and the US Clean Water Act (USCWA) for the maintenance of microbiological water quality in 'protected areas' highlight, there is a growing recognition that integrated management of point and diffuse sources of microbial pollution is essential. New information on catchment microbial dynamics and, in particular, the sources of faecal indicator bacteria found in bathing and shellfish harvesting waters is a pre-requisite for the design of any 'programme of measures' at the drainage basin scale to secure and maintain compliance with existing and new health-based microbiological standards. This paper reports on a catchment-scale microbial source tracking (MST) study in the Leven Estuary drainage basin, northwest England, an area for which quantitative faecal indicator source apportionment empirical data and land use information were also collected. Since previous MST studies have been based on laboratory trials using 'manufactured' samples or analyses of spot environmental samples without the contextual microbial flux data (under high and low flow conditions) and source information, such background data are needed to evaluate the utility of MST in USCWA total maximum daily load (TMDL) assessments or WFD 'Programmes of Measures'. Thus, the operational utility of MST remains in some doubt. The results of this investigation, using genotyping of Bacteroidetes using polymerase chain reaction (PCR) and male-specific ribonucleic acid coliphage (F + RNA coliphage) using hybridisation, suggest some discrimination is possible between livestock- and human-derived faecal indicator concentrations but, in inter-grade areas, the degree to which the tracer picture reflected the land use pattern and probable faecal indicator loading were less distinct. Interestingly, the MST data was more reliable on high flow samples when much of the faecal indicator flux from catchment systems occurs. Whilst a useful supplementary tool, the MST information did not provide quantitative source apportionment for the study catchment. Thus, it could not replace detailed empirical measurement of microbial flux at key catchment outlets to underpin faecal indicator source apportionment. Therefore, the MST techniques reported herein currently may not meet the standards required to be a useful forensic tool, although continued development of the methods and further catchment scale studies could increase confidence in such methods for future application.