Identifying Potential Impact of Lead Contamination Using a Geographic Information System

/ The main objective of this research was to identify the potential hazards associated with lead contami-nation from fixed sources in the city of Tijuana. An exploratory model is presented that describes the potential polluting sources as well as the exposed universe. The results of the analysis provide a clear picture of the geographic distribution of hazards areas for potential lead pollution in Tijuana. The findings are indicative of the dramatic consequences of rapid industrialization and urbanization in a city where there have not been significant planning efforts to mitigate the negative effects of this growth. The approach followed helps to narrow the universe of potential pollution sources, which can help to direct attention, research priorities, and resources to the most critical areas.KEY WORDS: Lead contamination; Industrial hazards; GIS; Tijuana; Mexico     

Landform Classification for Land Use Planning in Developed Areas: An Example in Segovia Province (Central Spain)

Landform-based physiographic maps, also called land systems inventories, have been widely and successfully used in undeveloped/rural areas in several locations, such as Australia, the western United States, Canada, and the British ex-colonies. This paper presents a case study of their application in a developed semi-urban/suburban area (Segovia, Spain) for land use planning purposes. The paper focuses in the information transfer process, showing how land use decision-makers, such as governments, planners, town managers, etc., can use the information developed from these maps to assist them. The paper also addresses several issues important to the development and use of this information, such as the goals of modern physiography, the types of landform-based mapping products, the problem of data management in developed areas, and the distinctions among data, interpretations, and decisions.     

Classification and spatial mapping of riparian habitat with applications toward management of streams impacted by nonpoint source pollution

Management of riparian habitats has been recognized for its importance in reducing instream effects of agricultural nonpoint source pollution. By serving as a buffer, well structured riparian habitats can reduce nonpoint source impacts by filtering surface runoff from field to stream. A system has been developed where key characteristics of riparian habitat, vegetation type, height, width, riparian and shoreline bank slope, and land use are classified as discrete categorical units. This classification system recognizes seven riparian vegetation types, which are determined by dominant plant type. Riparian and shoreline bank slope, in addition to riparian width and height, each consist of five categories. Classification by discrete units allows for ready digitizing of information for production of spatial maps using a geographic information system (GIS). The classification system was tested for field efficiency on Tom Beall Creek watershed, an agriculturally impacted third-order stream in the Clearwater River drainage, Nez Perce County, Idaho, USA. The classification system was simple to use during field applications and provided a good inventory of riparian habitat. After successful field tests, spatial maps were produced for each component using the Professional Map Analysis Package (pMAP), a GIS program. With pMAP, a map describing general riparian habitat condition was produced by combining the maps of components of riparian habitat, and the condition map was integrated with a map of soil erosion potential in order to determine areas along the stream that are susceptible to nonpoint source pollution inputs. Integration of spatial maps of riparian classification and watershed characteristics has great potential as a tool for aiding in making management decisions for mitigating off-site impacts of agricultural nonpoint source pollution.     

AN INTERACTWE MODELING ENVIRONMENT FOR NON-POINT SOURCE POLLUTION CONTROL1

ABSTRACT: Non-point source pollution cuntinues to be an important environmental and water quality management problem. For the moat part, analysis of non-point source pollution in watersheds has depended on the use of distributed models to identify potential problem areas and to assess the effectiveness of alternative management practices. To effectively use these models for watershed water quality management, users depend on integrated geographic information systems (GIS)-based interfaces for input/output data management. However, existing interfaces are ad-hoc and the utility of GIS is limited to organization of input data and display of output data. A highly interactive water quality modeling interface that utilizes the functional components and analytical capability of GIS is highly desirable. This paper describes the tight coupling of the Agricultural Non-point Source (AGNPS) water quality model and ARC/INFO GIS software to provide an interactive hybrid modeling environment for evaluation of non-point source pollution in a watershed. The modeling environment is designed to generate AGNPS input parameters from user-specified GIS coverages, create AGNPS input data files, control AGNPS model simulations, and extract and organize AGNPS model output data for display. An example application involving the estimation of pesticide loading in a southern Iowa agricultural watershed demonstrates the capability of the modeling environment. Compared with traditional methods of watershed water quality modeling using the AGNPS model or other ad-hoc interfaces between a distributed model and GIS, the interactive modeling environment system is efficient and significantly reduces the task of watershed analysis using tightly coupled GIS databases and distributed models.     

Combining GIS with fuzzy multicriteria decision-making for landfill siting in a fast-growing urban region

Landfill siting is a difficult, complex, tedious, and protracted process requiring evaluation of many different criteria. This paper presents a fuzzy multicriteria decision analysis alongside with a geospatial analysis for the selection of landfill sites. It employs a two-stage analysis synergistically to form a spatial decision support system (SDSS) for waste management in a fast-growing urban region, south Texas. The first-stage analysis makes use of the thematic maps in Geographical information system (GIS) in conjunction with environmental, biophysical, ecological, and socioeconomic variables leading to support the second-stage analysis using the fuzzy multicriteria decision-making (FMCDM) as a tool. It differs from the conventional methods of integrating GIS with MCDM for landfill selection because the approach follows two sequential steps rather than a full-integrated scheme. The case study was made for the city of Harlingen in south Texas, which is rapidly evolving into a large urban area due to its vantage position near the US-Mexico borderlands. The purpose of GIS was to perform an initial screening process to eliminate unsuitable land followed by utilization of FMCDM method to identify the most suitable site using the information provided by the regional experts with reference to five chosen criteria. Research findings show that the proposed SDSS may aid in recognizing the pros and cons of potential areas for the localization of landfill sites in any study region. Based on initial GIS screening and final FMCDM assessment, "site 1" was selected as the most suitable site for the new landfill in the suburban area of the City of Harlingen. Sensitivity analysis was performed using Monte Carlo simulation where the decision weights associated with all criteria were varied to investigate their relative impacts on the rank ordering of the potential sites in the second stage. Despite variations of the decision weights within a range of 20%, it shows that "site 1" remains its comparative advantage in the final site selection process.     

ESTIMATING NONPOINT SOURCE POLLUTION LOADS WITH A GIS SCREENING MODEL1

ABSTRACT: The St. Johns River Water Management District (SJR-WMD) is using a Geographic Information System (GIS) screening model to estimate annual nonpoint source pollution loads to surface waters and determine nonpoint source pollution problem areas within the SJRWMD. The model is a significant improvement over current practice because it is contained entirely within the district's GIS software, resulting in greater flexibility and efficiency, and useful visualization capabilities. Model inputs consist of five spatial data layers, runoff coefficients, mean runoff concentrations, and stormwater treatment efficiencies. The spatial data layers are: existing land use, future land use, soils, rainfall, and hydrologic boundaries. These data layers are processed using the analytical capabilities of a cell-based GIS. Model output consists of seven spatial data layers: runoff, total nitrogen, total phosphorous, suspended solids, biochemical oxygen demand, lead, and zinc. Model output can be examined visually or summarized numerically by drainage basin. Results are reported for only one of the SJRWMD's ten major drainage basins, the lower St. Johns River basin. The model was created to serve a major planning effort at the SJRWMD; results are being actively used to address nonpoint source pollution problems.     

Assessment of tropical suburban surface soils contamination from Jengka,Malaysia

Heavy metals in suburban soils pose both indirect and direct health risks. This study assessed the concentrations of Cr, Zn, Pb, and Cd in Jengka (Malaysia) suburban soil and estimated the human health risk. Health risk assessment (HRA) was utilized to assess non-cancer and cancer risks. The concentrations of heavy metals increased in the following order: Cd < Zn < Cr < Pb. The heavy metals were found to be divided into two components using principal component analysis (PCA), with PC1 comprising Pb and Cd and PC2 containing Zn and Cr. PC1 originates from anthropogenic sources, while PC2 is often from mixed anthropogenic and natural sources. Despite having the lowest mean concentration, Cd was enriched based on the geo-accumulation index (Igeo) and enrichment factor (EF). Average hazard index values were below the acceptable threshold (HI < 1) for dermal and inhalation pathways suggesting a low non-cancer risk. Jengka suburban soil had total lifetime cancer risk values slightly higher than the acceptable threshold (1 × 10⁻⁵). Skin contact was the most prominent contributing exposure pathway for both non-carcinogenic and carcinogenic risks. This study suggests that heavy metal bioactivity levels be used to make a plausible HRA of heavy metal pollution in suburban soils.     

Detection and mapping of water pollution variation in the Nile Delta using multivariate clustering and GIS techniques

The limited water resources of Egypt lead to widespread water-stress. Consequently, the use of marginal water sources, such as agricultural drainage waters, provides one of the national feasible solutions to the problem. However, the marginal quality of the drainage waters may restrict their use.The objective of this research is to develop a tool for planning and managing the reuse of agricultural drainage water for irrigation in the Nile Delta. This is achieved by classifying the pollution levels of drainage water into several categories using a statistical clustering approach that may ensure simple but accurate information about the pollution levels and water characteristics at any point within the drainage system.The derived clusters are then visualized by using a Geographical Information System (GIS) to draw thematic maps based on the entire Nile Delta, thus making GIS as a decision support system. The obtained maps may assist the decision makers in managing and controlling pollution in the Nile Delta regions. The clustering process also provides an effective overview of those spots in the Nile Delta where intensified monitoring activities are required. Consequently, the obtained results make a major contribution to the assessment and redesign of the Egyptian national water quality monitoring network.     

Decision-tree and rule-induction approach to integration of remotely sensed and GIS data in mapping vegetation in disturbed or hilly environments

The integration of Landsat TM and environmental GIS data sets using artificial intelligence rule-induction and decision-tree analysis is shown to facilitate the production of vegetation maps with both floristic and structural information. This technique is particularly suited to vegetation mapping in disturbed or hilly environments that are unsuited to either conventional remote sensing methods or GIS modeling using environmental data bases.     

A procedure for incorporating spatial variability in ecological risk assessment of Dutch river floodplains

Floodplain soils along the river Rhine in the Netherlands show a large spatial variability in pollutant concentrations. For an accurate ecological risk characterization of the river floodplains, this heterogeneity has to be included into the ecological risk assessment. In this paper a procedure is presented that incorporates spatial components of exposure into the risk assessment by linking geographical information systems (GIS) with models that estimate exposure for the most sensitive species of a floodplain. The procedure uses readily available site-specific data and is applicable to a wide range of locations and floodplain management scenarios. The procedure is applied to estimate exposure risks to metals for a typical foodweb in the Afferdensche and Deestsche Waarden floodplain along the river Waal, the main branch of the Rhine in the Netherlands. Spatial variability of pollutants is quantified by overlaying appropriate topographic and soil maps resulting in the definition of homogeneous pollution units. Next to that, GIS is used to include foraging behavior of the exposed terrestrial organisms. Risk estimates from a probabilistic exposure model were used to construct site-specific risk maps for the floodplain. Based on these maps, recommendations for future management of the floodplain can be made that aim at both ecological rehabilitation and an optimal flood defense.     

区域污染源统计分析系统的设计与应用

区域污染源的管理和治理既涉及到广域的地理空间实体又涉及到众多相关的环境因素。改善区域环境质量需要高效适用的空间分析技术,统计分析与GIS平台有效集成是解决区域环境各类问题的突破口和发展趋势。本论文及其工作构建了基于GIS的区域污染源统计分析系统,并在平台基础上以北京市某区域的环境污染分析为例,对该区域的主要污染因子与相关变量进行了尝试性的分析评价。为区域环境管理及环境质量改善打造了高效的数字化管理平台与可借鉴的管理技术。     

南充市农家乐发展的SWOT分析及其思考

南充市作为川东北地区的区域中心城市，目前已经成为该地区的经济文化中心、医疗卫生中心、科技教育中心以及信息和交通枢纽。近年来，随着城市化进程的加快，城市郊区农家乐发展迅速。农家乐旅游在调整农村产业结构、改善农村环境、改变人们思想观念、加强城乡交流、促进农村地区的发展、缩小城乡差距、解决“三农”问题以及构建城郊和谐社区中发挥着越来越重要的作用。通过对南充市城市郊区农家乐现状的调查，运用SWOT分析法对农家乐发展的内部条件和外部环境进行分析，提出了该市农家乐持续发展的对策。     

实现保定市大气污染防治目标的对策及建议

摘 要:目前,京津冀及周边地区已成为国内大气污染最严重的区域,引起了社会广泛关注。文章在对保定市大气污染现状详细梳理的基础上,分析了保定市在生产、生活过程中造成大气污染的原因,探讨和提出了解决保定市大气污染的对策及实施建议。     

Developing the interaction matrix technique as a tool assessing the impact of traffic on air quality

This paper develops a technique which can be used as a preliminary tool for assessing air quality related to urban traffic. It combines a Geographic Information System (GIS) with an interaction matrix-type methodology based on a system analysis approach. The matrix identifies and quantifies interactions between all selected variables involved in a system as well as their interaction with the system as a whole. This matrix is used to determine the weightings to apply to spatial datasets within a GIS to develop a pollution vulnerability map. The focus of the paper is to introduce and assess a more versatile coding of the interaction matrix with respect to previously used coding. A case study is presented in which the modified interaction methodology is applied to data for a busy urban location. The resulting vulnerability map, in terms of pollution vulnerable hot spots, was compared to a pollution map derived from an advanced dispersion model. The interaction matrix technique with GIS can be used as a tool complementary to sophisticated numerical modelling and has potential as an analytical tool to evaluate multidisciplinary systems.     

GIS噪声环境监测与管理

环境噪声是评价城市环境质量的一个重要指标,但噪声污染与水污染、大气污染不同,不能通过"资源化"、"化害为利"等方式来治理,因而要解决噪声污染就必须准确地获取环境噪声信息,并对其影响进行科学评价,以及时进行噪声治理决策规划和管理。本文探讨了GIS在噪声环境监测与管理中的应用。     

The Fat of the Land: Linking American Food Overconsumption, Obesity, and Biodiversity Loss

Americans’ excessive consumption of food harms their health and quality of life and also causes direct and indirect environmental degradation, through habitat loss and increased pollution from agricultural fertilizers and pesticides. We show here that reducing food consumption (and eating less meat) could improve Americans’ health and well-being while facilitating environmental benefits ranging from establishing new national parks and protected areas to allowing more earth-friendly farming and ranching techniques. We conclude by considering various public policy initiatives to lower per capita caloric intake and excessive meat consumption, and to translate this temperate behavior into substantial environmental protection.     

城市河流治理技术研究进展

城市河流水体具有生态系统复杂、污染类型齐全、污染源数量多、危害极为严重的特点。本文结合国内外最新研究成果和积累的宝贵经验，介绍了河道曝气技术、生态混凝土技术、阿科蔓复合生态技术、接触氧化技术、生态疏浚、化学强化一级处理、光催化技术等比较先进技术的研究进展，并对今后保护城市河流提出了建议。     

Assessing Watershed-Scale, Long-Term Hydrologic Impacts of Land-Use Change Using a GIS-NPS Model

Land-use change, dominated by an increase in urban/impervious areas, has a significant impact on water resources. This includes impacts on nonpoint source (NPS) pollution, which is the leading cause of degraded water quality in the United States. Traditional hydrologic models focus on estimating peak discharges and NPS pollution from high-magnitude, episodic storms and successfully address short-term, local-scale surface water management issues. However, runoff from small, low-frequency storms dominates long-term hydrologic impacts, and existing hydrologic models are usually of limited use in assessing the long-term impacts of land-use change. A long-term hydrologic impact assessment (L-THIA) model has been developed using the curve number (CN) method. Long-term climatic records are used in combination with soils and land-use information to calculate average annual runoff and NPS pollution at a watershed scale. The model is linked to a geographic information system (GIS) for convenient generation and management of model input and output data, and advanced visualization of model results. The L-THIA/NPS GIS model was applied to the Little Eagle Creek (LEC) watershed near Indianapolis, Indiana, USA. Historical land-use scenarios for 1973, 1984, and 1991 were analyzed to track land-use change in the watershed and to assess impacts on annual average runoff and NPS pollution from the watershed and its five subbasins. For the entire watershed between 1973 and 1991, an 18% increase in urban or impervious areas resulted in an estimated 80% increase in annual average runoff volume and estimated increases of more than 50% in annual average loads for lead, copper, and zinc. Estimated nutrient (nitrogen and phosphorus) loads decreased by 15% mainly because of loss of agricultural areas. The L-THIA/NPS GIS model is a powerful tool for identifying environmentally sensitive areas in terms of NPS pollution potential and for evaluating alternative land use scenarios for NPS pollution management.     

IDENTIFICATION OF CRITICAL NONPOINT POLLUTION SOURCE AREAS USING GEOGRAPHIC INFORMATION SYSTEMS AND WATER QUALITY MODELING1

n integrated approach coupling water quality computer simulation modeling with a geographic information system (GIS) was used to delineate critical areas of nonpoint source (NPS) pollution at the watershed level. Two simplified pollutant export models were integrated with the Virginia Geographic Information System (VirGIS) to estimate soil erosion, sediment yield, and phosphorus (P) loading from the Nomini Creek watershed located in Westmoreland County, Virginia. On the basis of selected criteria for soil erosion rate, sediment yield, and P loading, model outputs were used to identily watershed areas which exhibit three categories (low, medium, high) of non-point source pollution potentials. The percentage of the watershed area in each category, and the land area with critical pollution problems were also identified. For the 1505-ha Nomini Creek watershed, about 15, 16, and 21 percent of the watershed area were delineated as sources of critical soil erosion, sediment, and phosphorus pollution problems, respectively. In general, the study demonstrated the usefulness of integrating GIS with simulation modeling for nonpoint source pollution control and planning. Such techniques can facilitate making priorities and targeting nonpoint source pollution control programs.     

人工增雨指挥系统构建与研究

为增加有效降水,降低干旱和雾霾等环境污染的影响,保护生态环境安全,研制了以提高开发空中水资源能力为主要目的、基于GIS技术的人工增雨作业决策指挥系统,依托新一代多普勒天气雷达、Micaps数据资料和自动站数据库,应用Microsoft C#语言开发了增雨作业预警和指挥功能、指挥信息和作业信息收集互传功能、增雨效果评估功能、常规业务管理功能,构建了功能较为完善的业务系统。