A water quality monitoring network design methodology for the selection of critical sampling points: Part II

In order to resolve the spatial component of the design of a water quality monitoring network, a methodology has been developed to identify the critical sampling locations within a watershed. This methodology, called Critical Sampling Points (CSP), focuses on the contaminant total phosphorus (TP), and is applicable to small, predominantly agricultural-forested watersheds. The CSP methodology was translated into a model, called Water Quality Monitoring Station Analysis (WQMSA). It incorporates a geographic information system (GIS) for spatial analysis and data manipulation purposes, a hydrologic/water quality simulation model for estimating TP loads, and an artificial intelligence technology for improved input data representation. The model input data include a number of hydrologic, topographic, soils, vegetative, and land use factors. The model also includes an economic and logistics component. The validity of the CSP methodology was tested on a small experimental Pennsylvanian watershed, for which TP data from a number of single storm events were available for various sampling points within the watershed. A comparison of the ratios of observed to predicted TP loads between sampling points revealed that the model's results were promising.     

Reducing the environmental impact of road and rail vehicles

Methods have been developed to measure in situ the dynamic impact of both road and rail vehicles on the infrastructure and the environment. The resulting data sets have been analysed to quantify the environmental impacts in a transparent manner across both modes. A primary concern is that a small number of vehicles are being operated outside safe or regulatory limits which can have a disproportionate large impact. The analysis enables the various impacts to be ranked across both modes so enabling one to discern the benefits of intermodal transport. The impact of various policy options is considered and how to identify vehicles which can be classified as environmentally friendly. This would require European agreement as many heavy goods vehicle operate across country borders.     

Characterizing the generation and spatial patterns of carbon emissions from urban express delivery service in China

Express delivery services, as an indispensable part of our daily life, have grown rapidly because of the booming e-commerce and logistics industries. Accordingly, there is increasing concern about the environmental load from delivering letters and parcels, such as road freight transportation emissions and packaging waste, which have not been seriously considered in previous work. In this study, a spatially based dynamic model has been created to quantify the impacts (measured in carbon emissions, CO₂eq.) from the express delivery sector in China. Specifically, intracity (urban) express delivery services—delivery and pick-up services located within the same city—was chosen for analysis. The results indicated that the carbon emissions from the transportation phase of the express delivery sector in Chinese cities varied from 20 t to 4000 t in 2017, of which 18% was attributable to the weight of extra packaging materials. Carbon emission intensities for all cities showed a close relationship with their socioeconomic status. For example, the spatial pattern of intracity express delivery volumes and associated carbon emissions showed a significant clustering property: high-value cities were clustered in eastern China and low-value cities in western China. Furthermore, the carbon hotspots were mainly located in the Yangtze River Delta and Pearl River Delta urban agglomerations. Overall, our research method and preliminary findings could be helpful for the green development of the booming express delivery sector in China and beyond.     

An expert-based approach to forest road network planning by combining Delphi and spatial multi-criteria evaluation

Changes in forest landscapes resulting from road construction have increased remarkably in the last few years. On the other hand, the sustainable management of forest resources can only be achieved through a well-organized road network. In order to minimize the environmental impacts of forest roads, forest road managers must design the road network efficiently and environmentally as well. Efficient planning methodologies can assist forest road managers in considering the technical, economic, and environmental factors that affect forest road planning. This paper describes a three-stage methodology using the Delphi method for selecting the important criteria, the Analytic Hierarchy Process for obtaining the relative importance of the criteria, and finally, a spatial multi-criteria evaluation in a geographic information system (GIS) environment for identifying the lowest-impact road network alternative. Results of the Delphi method revealed that ground slope, lithology, distance from stream network, distance from faults, landslide susceptibility, erosion susceptibility, geology, and soil texture are the most important criteria for forest road planning in the study area. The suitability map for road planning was then obtained by combining the fuzzy map layers of these criteria with respect to their weights. Nine road network alternatives were designed using PEGGER, an ArcView GIS extension, and finally, their values were extracted from the suitability map. Results showed that the methodology was useful for identifying road that met environmental and cost considerations. Based on this work, we suggest future work in forest road planning using multi-criteria evaluation and decision making be considered in other regions and that the road planning criteria identified in this study may be useful.     

A GIS-based Study for Optimizing the Total Emission Control Strategy in Lanzhou City

A geographic information system (GIS)-based approach with spatial analysis advantages was developed to optimize the total emission control scheme on air pollution in Lanzhou, combined with Models-3 modeling system and a linear programming model. GIS system is mainly used for establishing a multifactor assessment model to quantitatively divide environmental functional zone, and also used for selecting control sites in linear programming model. The results show that most of the urban area belongs to the second type of function, which is 122.8 km² occupying about 76.5% and the third type of about 32.9 km² occupying 20.5%. To reach the air quality up to the national standard in the entire control area, some large-emission factories need to cut emissions from 19% to 27%. For small but low-emission height sources, the cut may be as high 40%. The improvement of the ecological environment is urgently needed for controlling the background particle pollution in Lanzhou city.     

Road Traffic Noise Prediction Model under Interrupted Traffic Flow Condition

The objective of this study is to develop an empirical traffic noise prediction model under interrupted traffic flow conditions using two analytical the approaches, the first being the acceleration lane approach and second being the deceleration approach. The urban road network of Bangalore city has been selected as the study area. Sixteen locations are chosen in major traffic junctions of the study area. The traffic noise data collected from the study locations were analyzed separately for both acceleration and deceleration lanes when vehicles leave an intersection on a green traffic light and come to a stop on red traffic light. Based on the study, a regression noise prediction model has been developed for both acceleration and deceleration lanes.     

Interval-Parameter Conditional Value-at-Risk Two-Stage Stochastic Programming Model for Management of End-of-Life Vehicles

The management of end-of-life vehicles conserves natural resources, provides economic benefits, and reduces water, air, and soil pollution. Sound management of end-of-life vehicles is vitally important worldwide thus requiring sophisticated decision-making tools for optimizing its efficiency and reducing system risk. This paper proposes an interval-parameter conditional value-at-risk two-stage stochastic programming model for management of end-of-life vehicles. A case study is conducted in order to demonstrate the usefulness of the developed model. The model is able to provide the trade-offs between the expected profit and system risk. It can effectively control risk at extremely disadvantageous availability levels of end-of-life vehicles. The formulated model can produce optimal solutions under predetermined decision-making risk preferences and confidence levels. It can simultaneously determine the optimal long-term allocation targets of end-of-life vehicles and reusable parts as well as capital investment, production planning, and logistics management decisions within a multi-period planning horizon. The proposed model can efficiently handle uncertainties expressed as interval values and probability distributions. It is able to provide valuable insights into the effects of uncertainties. Compared to the available models, the resulting solutions are far more robust.

     

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.     

Site location optimization of regional air quality monitoring network in China: methodology and case study

Regional air quality monitoring networks (RAQMN) are urgently needed in China due to increasing regional air pollution in city clusters, arising from rapid economic development in recent decades. This paper proposes a methodological framework for site location optimization in designing a RAQMN adapting to air quality management practice in China. The framework utilizes synthetic assessment concentrations developed from simulated data from a regional air quality model in order to simplify the optimal process and to reduce costs. On the basis of analyzing various constraints such as cost and budget, terrain conditions, administrative district, population density and spatial coverage, the framework takes the maximum approximate degree as an optimization objective to achieve site location optimization of a RAQMN. An expert judgment approach was incorporated into the framework to help adjust initial optimization results in order to make the network more practical and representative. A case study was used to demonstrate the application of the framework, indicating that it is feasible to conduct site optimization for a RAQMN design in China. The effects of different combinations of primary and secondary pollutants on site location optimization were investigated. It is suggested that the network design considering both primary and secondary pollutants could better represent regional pollution characteristics and more extensively reflect temporal and spatial variations of regional air quality. The work shown in this study can be used as a reference to guide site location optimization of a RAQMN design in China or other regions of the world.     

Decision-Tree-based data mining and rule induction for predicting and mapping soil bacterial diversity

Soilmicrobial ecology plays a significant role in global ecosystems. Nevertheless, methods of model prediction and mapping have yet to be established for soil microbial ecology. The present study was undertaken to develop an artificial-intelligence- and geographical information system (GIS)-integrated framework for predicting and mapping soil bacterial diversity using pre-existing environmental geospatial database information, and to further evaluate the applicability of soil bacterial diversity mapping for planning construction of eco-friendly roads. Using a stratified random sampling, soil bacterial diversity was measured in 196 soil samples in a forest area where construction of an eco-friendly road was planned. Model accuracy, coherence analyses, and tree analysis were systematically performed, and four-class discretized decision tree (DT) with ordinary pair-wise partitioning (OPP) was selected as the optimal model among tested five DT model variants. GIS-based simulations of the optimal DT model with varying weights assigned to soil ecological quality showed that the inclusion of soil ecology in environmental components, which are considered in environmental impact assessment, significantly affects the spatial distributions of overall environmental quality values as well as the determination of an environmentally optimized road route. This work suggests a guideline to use systematic accuracy, coherence, and tree analyses in selecting an optimal DT model from multiple candidate model variants, and demonstrates the applicability of the OPP-improved DT integrated with GIS in rule induction for mapping bacterial diversity. These findings also provide implication on the significance of soil microbial ecology in environmental impact assessment and eco-friendly construction planning.     

Chlorophyll derivatives for pest and disease control: Are they safe?

Chlorophyll derivatives are getting widespread acceptance among the researchers as natural photosensitizers for photodynamic control of pests and disease vectors; however, rare attention has been given to evaluation of their toxicity to non-target organisms in the environment. This perspective article highlights that chlorophyll derivatives may not be as safe as believed and can possibly pose risk to non-target organisms in the environment. We invite the attention of environmental biologists, particularly ecotoxicologists, to contribute their role in making the application of chlorophyll derivatives more environmentally friendly and publicly acceptable.     

上海市机动车污染实时排放预警系统设计与应用

研究上海市机动车污染的动态排放测算和网格化动态排放清单构建,在实时的交通数据和交通环境监测数据的基础上,结合交通模型、机动车排放清单模型等业务模型和算法,依托大数据存储、可视化和GIS等技术,开发了上海市机动车污染物实时排放预警系统,实现了上海市全市道路的机动车动态排放测算、交通环境政策实施情景模拟和网格化排放清单,更新频率为每30 min一次,包含PM、NOx、CO、SO2、VOCs等污染物和9种车型。系统建成后直接服务于首届中国国际进口博览会,为大气污染排放实时总量跟踪评估、污染源管控措施分析及监测成因分析等提供了有力的实时数据和技术支撑。     

Spatial analysis and land use regression of VOCs and NO2 in Dallas, Texas during two seasons

Passive air sampling for nitrogen dioxide (NO(2)) and select volatile organic compounds (VOCs) was conducted at 24 fire stations and a compliance monitoring site in Dallas, Texas, USA during summer 2006 and winter 2008. This ambient air monitoring network was established to assess intra-urban gradients of air pollutants to evaluate the impact of traffic and urban emissions on air quality. Ambient air monitoring and GIS data from spatially representative fire station sites were collected to assess spatial variability. Pairwise comparisons were conducted on the ambient data from the selected sites based on city section. These weeklong samples yielded NO(2) and benzene levels that were generally higher during the winter than the summer. With respect to the location within the city, the central section of Dallas was generally higher for NO(2) and benzene than north and south. Land use regression (LUR) results revealed spatial gradients in NO(2) and selected VOCs in the central and some northern areas. The process used to select spatially representative sites for air sampling and the results of analyses of coarse- and fine-scale spatial variability of air pollutants on a seasonal basis provide insights to guide future ambient air exposure studies in assessing intra-urban gradients and traffic impacts.     

环境应急监测最短路径分析系统的开发与实现

阐述了开发环境应急监测最短路径分析系统的目的.在ArcGIS Server的体系结构和开发方式基础上,利用城市道路交通网络模型,对.NET环境下GIS服务端进行扩展开发,实现了对环境应急监测中最短路径分析的功能,并通过南通市网络化环境污染事故区域预警系统的应用介绍了实现过程.     

Composite use of numerical groundwater flow modeling and geoinformatics techniques for monitoring Indus Basin aquifer, Pakistan

The integration of the Geographic Information System (GIS) with groundwater modeling and satellite remote sensing capabilities has provided an efficient way of analyzing and monitoring groundwater behavior and its associated land conditions. A 3-dimensional finite element model (Feflow) has been used for regional groundwater flow modeling of Upper Chaj Doab in Indus Basin, Pakistan. The approach of using GIS techniques that partially fulfill the data requirements and define the parameters of existing hydrologic models was adopted. The numerical groundwater flow model is developed to configure the groundwater equipotential surface, hydraulic head gradient, and estimation of the groundwater budget of the aquifer. GIS is used for spatial database development, integration with a remote sensing, and numerical groundwater flow modeling capabilities. The thematic layers of soils, land use, hydrology, infrastructure, and climate were developed using GIS. The Arcview GIS software is used as additive tool to develop supportive data for numerical groundwater flow modeling and integration and presentation of image processing and modeling results. The groundwater flow model was calibrated to simulate future changes in piezometric heads from the period 2006 to 2020. Different scenarios were developed to study the impact of extreme climatic conditions (drought/flood) and variable groundwater abstraction on the regional groundwater system. The model results indicated a significant response in watertable due to external influential factors. The developed model provides an effective tool for evaluating better management options for monitoring future groundwater development in the study area.     

Integrated studies for automobile wastes management in developing countries; in the concept of environmentally friendly mechanic village

More cities in developing countries now consider mechanic village (MV) as superior to the city wide auto-workshop practice following the increasing influx of used or waste automobile from industrialized nations. This is because of the numerous advantages of the mechanic village concept as a capacity building, and in poverty alleviation. Nevertheless, mechanic villages are poorly developed with no waste management plan. They are now identified with severe to excessive heavy metal soil pollution, causing ecological and public health hazards. This paper has a wider explanation of what it takes for a mechanic village to be environmentally friendly based on spectroscopic analysis and physical measurements conducted in three MVs. Heavy metal concentrations (mg kg(?-1)) above background levels in the upper 100 cm soil profiles of the Okigwe, the Orji, and the Nekede MVs in the Imo River basin collectively range 748-70,606 for Fe; 99-1,090 for Pb; 186-600 for Mn; 102-1,001 for Cu; 8-23 for Cd; 4-27 for Cr; and 3-10 for Ni. The most abundant metals of environmental concerns are Pb, Mn, and Cu, in the order of Pb > Mn > Cu. Three-phase storm water treatment, emission testing, minimum safe farming distance (350 m), extended producer responsibility for disposal or recycling of used motor oil, phyto-remediation using local plants, groundwater monitoring wells, and continuous education of mechanics are recommended. Exporters of waste automobiles to developing countries and the United Nations may assist developing countries in establishing environmentally friendly MVs.     

Austal 2000应用于国内“烟塔合一”类项目大气影响评价

简述了德国"烟塔合一"类大气污染扩散模式,以及相关模式Austal 2000的应用方法,修正了气象参数以适合本地化应用。以天津某电厂为实例,将Austal 2000模式"烟塔合一"和烟囱排烟方式的计算结果进行了对比分析。结果表明,在进行本地化修改后,Austal 2000模式适用于国内有关项目大气预测评价,但从环境影响角度考虑,"烟塔合一"相对于高烟囱排放方式没有明显优势,应用时需慎重。     

基于遥感和GIS的四川省草地动态变化分析

利用地理信息系统技术,在空间数据库平台的支持下,对四川省20世纪90年代中期到2000年间的草地动态变化特征、草地动态变化的背景特征及其空间分布特征进行了分析。研究表明,净增草地部分主要来源于耕地,净减草地部分的主要去向是林地。总体上,净增草地面积3812公顷,净增草地部分主要是在轻度土壤侵蚀区、中度土壤侵蚀区、剧烈土壤侵蚀区和强度土壤侵蚀区,坡度等级5、6和1的区域,环境等级5、6、4和1的区域;净减草地部分主要是在微度土壤侵蚀区和极强土壤侵蚀区,坡度等级3、2和4的区域,环境质量等级7和8的区域。净增草地的区域为川西北高原、丘陵和川西南山区,净增草地面积的前四个地州市是遂宁市、泸州市、巴中地区和广安市,净减少草地的区域为盆周山地和平原,净减少草地面积的前四个地州市是广元市、绵阳市、达川市和宜宾市。