地理3G系统应用于城市固体废物管理的新模式

基于GPS、GPRS、GIS地理3G综合技术,设计城市固体废物综合监管系统,实现对固体废物从收集到再利用全过程的监督管理。该系统由申报信息系统、地面控制系统、处置保障系统、综合分析系统、应急指挥系统和线上“淘宝”系统组成,在固体废物收集站点采集的数据上传至综合分析系统,经分析与匹配后相关信息发布在线上“淘宝”交易平台,平台为买卖双方提供资源配置方案,也为管理部门的宏观调控提供数据支撑。     

Long-Term Planning of Waste Management System in the City of Regina – an Integrated Inexact Optimization Approach

In this study, an integrated solid waste management system based on inexact fuzzy-stochastic mixed integer linear programming (IFSMILP) has been applied to the long-term planning of waste management activities in the City of Regina. The model can effectively reflect dynamic, interactive, and uncertain characteristics of the solid waste management system in the city. The results have provided useful answers for the following questions: “What waste reduction goals are desired if the existing landfill's life is prolonged for 15 years?”, “What should be the waste flow allocation pattern in the city?”, “What should be done if the waste generation rate increases rapidly, while the relevant handling capacity is limited?”, and “What level of reliability will we have given the suggested waste management plan?”     

Microeconomic measurement of the social costs of environmental regulation

This paper provides a coherent microeconomic framework for defining and measuring the social costs of environmental regulations. A fundamental identity between two alternative means of measuring social costs is established and used to illustrate how erroneous methodologies have crept into the impact assessment literature. Several interesting cases of “ripple effects” including those related to the siting of hazardous waste disposal facilities are considered using this identity.     

Online rumor propagation of social media on NIMBY conflict: Temporal patterns,frameworks and rumor-mongers

The rapid development of social media has accelerated the online rumor propagation, making social conflicts more intense during the development of NIMBY facilities. The “fake news” issue is not new, as the consequences will be amplified when the fakery spreads on social media as online rumors. However, few studies have been undertaken on the online public opinion, especially the rumor propagation on NIMBYism. This study collects data related to the anti-PX demonstration in Maoming city in 2014 on the Weibo platform. To form the rumor text library, qualitative research method is adopted to encode the collected data. Based on the social amplification of risk framework, three sub-frameworks are proposed in this study and statistical method is used to analyze the topics of rumors. Meanwhile, the textual content analysis and impact factor analysis is employed to examine the semantic features of rumor texts and the key role of rumor-mongers respectively. The results show that there are three main propagation lifecycles of rumors while the topics of rumors vary according to the cycle. Rumors belonging to each framework have diverse trend and the assessment framework is dominant throughout the process. “Individuals” and “Elites” are the main force of rumor spreading, and “Media practitioners” are the opinion leaders. These findings are useful for governments to establish a rumor detection system so that official information can be released and rumors can be refuted without delay. Meanwhile, the cooperation with the opinion leaders in online rumor propagation should be strengthened. In addition, a scientific popularization and timely notification of project progress is recommended prior to the development of NIMBY facility.     

IOWLAD-based MCDM model for the site assessment of a household waste processing plant under a Pythagorean fuzzy environment

Household waste pollution is the main restrictive factor for urban development that leads to an increase in calorific value and decrease in disposal capacity. To deal with the demand derived from household waste, the development of a new household waste processing plant is necessary, with site assessment being an issue of primary consideration. In this study, to evaluate alternatives, we proposed a multiple-criteria decision-making framework based on the Pythagorean fuzzy induced ordered weighted logarithmic averaging distance (PFIOWLAD) operator. For this purpose, during the decision-making process, we extend the induced ordered weighted logarithmic averaging distance (IOWLAD) operator to the Pythagorean fuzzy set (PFS), which can deal with uncertain information. Then, an illustrative case including five criteria, namely, construction cost, impact on the cost of retrofitting existing household waste processing plants, traffic efficiency, impact on surrounding residents, and refuse processing capacity equilibrium, along with five alternatives in Shanghai is investigated. The robustness and effectiveness of the proposed framework are verified by comparing the results with those determined using the previous approaches.     

Application of data envelopment analysis in environmental impact assessment of a coal washing plant: A new sustainable approach

The main problem of traditional methods of environmental impact assessment (EIA) is that in most of the existing algorithms and methods, such as Leopold, Folchi and RIAM, the main attention is to the destructive effects of the proposed plan, and the advantages of the industrial project are less noticeable. This has led to a permanent challenge between environmental organizations and industrial stakeholders. Data envelopment analysis (DEA) is a new approach of assessing the industrial units. Besides, it considers the positive economic and social impacts of the project and provides a comprehensive assessment of the industrial unit. With this approach, the environmental impacts of an industrial unit have been considered as “inputs” and its positive economic and social impacts considered as the “outputs” of the DEA models. Therefore, the problem of impact assessment changes into a DEA model. In the present study, the Alborz Sharghi Coal washing plant in northern Iran has been considered as a case study for implementing the DEA-EIA approach, and 19 plant activities and 11 environmental components have been used to evaluate the environmental effects of the plant. To solve the EIA problem, two commonly used DEA approaches, called CRS (constant returns to scale) and VRS (variable returns to scale), have been used. The DEA results identified the critical environmental components of the plant that should be considered seriously. Also, drawing the “potential improvement” diagram in the DEA method is an effective tool for determining the high risk activities of the factory and applying them in development plans. Besides, using the VRS model with maximize-output approach showed that some of the plant activities had the most differences with optimal mode and these components should be considered in future development plans. Finally, it can be concluded that, assessing the environmental impacts of the mineral industries with VRS maximize-output approach, is closer to the concept of sustainable development and cost-benefit analysis.     

Assessment of groundwater quality: a fusion of geochemical and geophysical information via Bayesian neural networks

Deplorable quality of groundwater arising from saltwater intrusion, natural leaching and anthropogenic activities is one of the major concerns for the society. Assessment of groundwater quality is, therefore, a primary objective of scientific research. Here, we propose an artificial neural network-based method set in a Bayesian neural network (BNN) framework and employ it to assess groundwater quality. The approach is based on analyzing 36 water samples and inverting up to 85 Schlumberger vertical electrical sounding data. We constructed a priori model by suitably parameterizing geochemical and geophysical data collected from the western part of India. The posterior model (post-inversion) was estimated using the BNN learning procedure and global hybrid Monte Carlo/Markov Chain Monte Carlo optimization scheme. By suitable parameterization of geochemical and geophysical parameters, we simulated 1,500 training samples, out of which 50 % samples were used for training and remaining 50 % were used for validation and testing. We show that the trained model is able to classify validation and test samples with 85 % and 80 % accuracy respectively. Based on cross-correlation analysis and Gibb’s diagram of geochemical attributes, the groundwater qualities of the study area were classified into following three categories: “Very good”, “Good”, and “Unsuitable”. The BNN model-based results suggest that groundwater quality falls mostly in the range of “Good” to “Very good” except for some places near the Arabian Sea. The new modeling results powered by uncertainty and statistical analyses would provide useful constrain, which could be utilized in monitoring and assessment of the groundwater quality.     

Dynamical Allocation Method of Emission Rights of Pollutants by Viability Constraints Under Tychastic Uncertainty

This study proposes a method of dynamic decentralization by constraints and its associated software. It can be used to allocate pollutant emissions rights among the different polluters such that they achieve both given global and local emission thresholds not to be transgressed. Knowing the maximum growth rates of polluting emissions of each polluter in the worst case, this method provides the rule of a dynamic allocation of pollutant emissions rights as well as the required initial emissions of each polluters assuring that, whatever the growth rates of the emissions below the maximum growth rates, the resulting emissions will be, both globally and locally, under their thresholds. These guaranteed initial emissions supply each polluter with a measure of risk insurance. This problem, formulated as a “tychastic” regulated system with viability constraints, is solved with mathematical and algorithmic tools of viability theory and numerical results obtained by a dedicated software are presented.     

A framework to assess food security in regional strategic environmental assessment

Today, food security is central to global social policy and sustainable development agendas; yet food security considerations have not yet widely penetrated environmental impact assessment (IA) practice. This paper investigates criteria and approaches to food security assessment that align with Regional Strategic Environment Assessment (RSEA); a form of IA commonly used to influence natural resource development programmes. The research is based on interviews with seven international food security experts about how food security assessment can be performed at a regional scale, responsive to the impacts of natural resource developments. Analysis of data reveals essential components, key considerations, and procedural requirements for food security assessment within RSEA processes. Based on the evidence, we conclude that food security assessment in RSEA cannot be approached in a piecemeal fashion. To be successful: it must include holistic and comprehensive consideration of all four food security dimensions; communities should be profiled in early stages of the assessment to characterize the regional food system and define its importance to food security; vulnerable populations should be prioritized in the assessment; and it is critical to incorporate meaningful and influential opportunities for public participation. Finally, the recommended approach to analyze food security in RSEA is ‘system analysis’ which includes examination of food system pathways. A conceptual and methodological framework to assess food security in RSEA is presented, intended as a guide for practitioners wishing to incorporate food security into RSEA and RSEA-like initiatives.     

An evaluation of the social dimensions in public participation in rural domestic waste source-separated collection in Guilin,China

A comprehensive evaluation of public participation in rural domestic waste (RDW) source-separated collection in China was carried out within a social-dimension framework, specifically in terms of public perception, awareness, attitude, and willingness to pay for RDW management. The evaluation was based on a case study conducted in Guilin, Guangxi Zhuang Autonomous Region, China, which is a representative of most inland areas of the country with a GDP around the national average. It was found that unlike urban residents, rural residents maintained a high rate of recycling, but in a spontaneous manner; they paid more attention to issues closely related to their daily lives, but less attention to those at the general level; their awareness of RDW source-separated collection was low and different age groups showed significantly different preferences regarding the sources of knowledge acquirement. Among potential information sources, village committees played a very important role in knowledge dissemination; for the respondents’ pro-environmental attitudes, the influencing factor of “lack of legislation/policy” was considered to be significant; mandatory charges for waste collection and disposal had a high rate of acceptance among rural residents; and high monthly incomes had a positive correlation with both public pro-environmental attitudes and public willingness to pay for extra charges levied by RDW management. These observations imply that, for decision-makers in the short term, implementing mandatory RDW source-separated collection programs with enforced guidelines and economic compensation is more effective, while in the long run, promoting pro-environmental education to rural residents is more important.     

Comprehensive River Water Quality Management by Simulation and Optimization Models

In this paper, the performance of water quality modeling is investigated in the analysis of the natural assimilative capacity (NAC) of a river system. The new data available, along with the appropriate integrated model, allow for the analysis of the NAC of the entire river. The integrated model developed here emphasized the implementation of the QUAL2E simulation model and the appropriate allocation of waste loads (optimization model) in a subtropical area. Simulations are calibrated and validated according to the data from the Water Quality and Flow Rate Monitoring Project using the QUAL2E model. On the basis of the optimal allocation model, the results of the NAC and allowable pollution loading in the Putzu River basin are discussed. The study provides a framework of the integrated model that can be used as a guideline to determine the NAC of subtropical rivers.     

IFTCIP: An Integrated Optimization Model for Environmental Management under Uncertainty

In this study, an interval-fuzzy two-stage chance-constrained integer programming (IFTCIP) method is developed for supporting environmental management under uncertainty. The IFTCIP improves upon the existing interval, fuzzy, and two-stage programming approaches by allowing uncertainties expressed as probability distributions, fuzzy sets, and discrete intervals to be directly incorporated within a general mixed integer linear programming framework. It has advantages in uncertainty reflection, policy investigation, risk assessment, and capacity-expansion analysis in comparison to the other optimization methods. Moreover, it can help examine the risk of violating system constraints and the associated consequences. The developed method is applied to the planning for facility expansion and waste-flow allocation within a municipal solid waste management system. Violations of capacity constraints are allowed under a range of significance levels, which reflects tradeoffs between the system cost and the constraint-violation risk. The results indicate that reasonable solutions for both binary and continuous variables have been generated under different risk levels. They are useful for generating desired decision alternatives with minimized system cost and constraint-violation risk under various environmental, economic, and system-reliability conditions. Generally, willingness to take a higher risk of constraint violation will guarantee a lower system cost; a strong desire to acquire a lower risk will run into a higher system cost.     

Water and waste load allocation in rivers with emphasis on agricultural return flows: application of fractional factorial analysis

In this paper, a new methodology is developed to handle parameter and input uncertainties in water and waste load allocation (WWLA) in rivers by using factorial interval optimization and the Soil, Water, Atmosphere, and Plant (SWAP) simulation model. A fractional factorial analysis is utilized to provide detailed effects of uncertain parameters and their interaction on the optimization model outputs. The number of required optimizations in a fractional factorial analysis can be much less than a complete sensitivity analysis. The most important uncertain inputs and parameters can be also selected using a fractional factorial analysis. The uncertainty of the selected inputs and parameters should be incorporated real time water and waste load allocation. The proposed methodology utilizes the SWAP simulation model to estimate the quantity and quality of each agricultural return flow based on the allocated water quantity and quality. In order to control the pollution loads of agricultural dischargers, it is assumed that a part of their return flows can be diverted to evaporation ponds. Results of applying the methodology to the Dez River system in the southwestern part of Iran show its effectiveness and applicability for simultaneous water and waste load allocation in rivers. It is shown that in our case study, the number of required optimizations in the fractional factorial analysis can be reduced from 64 to 16. Analysis of the interactive effects of uncertainties indicates that in a low flow condition, the upstream water quality would have a significant effect on the total benefit of the system.     

Accounting embodied economic potential of healthcare waste recycling—a case study from Pakistan

Proper management of healthcare wastes is a key concern across resource-constrained countries in South Asia. Existing scientific research on this topic usually involves epidemiological and behavioral studies. Similarly, environmental impact assessment of healthcare wastes is mainly conducted from an end-user or anthropocentric point of view. In this study, we took a novel approach by analyzing healthcare wastes using an ecocentric position. Here, we utilize a case study of a general public hospital in a major city of Pakistan to analyze the embodied energy of its waste fractions by category. We used Emergy analysis to assess the true economic potential of recycling these waste items. While doing so, we compared the economic potential of current waste recycling practices with the scenario of 100% recycling of useful waste fractions. We discovered that the latent embodied energy of different recyclable waste fractions made them far more valuable than their existing market prices indicate. This value increased further if the useful waste fractions were completely recycled. In conclusion, this study used empirical evidence to argue in favor of source-segregation and recycling of healthcare wastes so that the higher costs associated with natural resource extraction and processing can be avoided. Future studies considering hazardous healthcare wastes can use the approach taken in this paper to analyze the impact of other practical waste treatment procedures.     

Geospatial strategy for sustainable management of municipal solid waste for growing urban environment

This paper presents the implementation of a Geospatial approach for improving the Municipal Solid Waste (MSW) disposal suitability site assessment in growing urban environment. The increasing trend of population growth and the absolute amounts of waste disposed of worldwide have increased substantially reflecting changes in consumption patterns, consequently worldwide. MSW is now a bigger problem than ever. Despite an increase in alternative techniques for disposing of waste, land-filling remains the primary means. In this context, the pressures and requirements placed on decision makers dealing with land-filling by government and society have increased, as they now have to make decisions taking into considerations environmental safety and economic practicality. The waste disposed by the municipal corporation in the Bhagalpur City (India) is thought to be different from the landfill waste where clearly scientific criterion for locating suitable disposal sites does not seem to exist. The location of disposal sites of Bhagalpur City represents the unconsciousness about the environmental and public health hazards arising from disposing of waste in improper location. Concerning about urban environment and health aspects of people, a good method of waste management and appropriate technologies needed for urban area of Bhagalpur city to improve this trend using Multi Criteria Geographical Information System and Remote Sensing for selection of suitable disposal sites. The purpose of GIS was to perform process to part restricted to highly suitable land followed by using chosen criteria. GIS modeling with overlay operation has been used to find the suitability site for MSW.     

A new method for environmental site assessment of urban solid waste landfills

Regarding various types of pollutant, waste management requires high attention. Environmental site selection study, prior to landfill operation, and subsequently, monitoring and maintaining of the location, are of foremost points in landfill site selection process. By means of these studies, it is possible to control the undesirable impacts caused by landfills. Study ahead aims at examination of effectiveness of a new method called Monavari 95–2 in landfill site assessment. For this purpose, two landfills Rasht and Andisheh, which are, respectively, located on humid and arid areas, were selected as case studies. Then, the results obtained from both sites were compared with each other to find out the weaknesses and strengths of each site. Compared with others similar methods, much more criteria (53 parameters) can be considered within this method, so the results will be more calculable. According to this method, Rasht landfill (site H) is classified as unacceptable landfill site i.e. there is an urgent need for a new suitable site for landfill, while Andishe Landfill (site D) is ranked as acceptable landfill site but needs environmental management program to handle the existing weaknesses.     

First Step for an Ecological Risk Assessment to Evaluate the Impact of Diffuse Pollution in Lake Vela (Portugal)

Lake Vela, located in the Portuguese littoral-centre, is a temperate shallow lake exhibiting a high trophic status. This aquatic ecosystem has been potentially exposed to contamination generated by agricultural and livestock activities held in their drainage basin, which seriously compromise their health. This work summarizes some background information and presents the problem formulation step of the ERA. Therefore, it evaluates the characteristics of the stressor(s), describes the ecological system and receptors and suggests a conceptual model, which predicts the potential exposure pathways, relating suspected sources to the defined endpoints. This introductory step also described an analysis plan on the entire study, which includes a delineation of the assessment design, data needs, measures, and methods for conducting the analysis phase of the risk assessment process.     

Application of FT-IR for assessment of the biological stability of landfilled municipal solid waste (MSW) during in situ aeration

Disposal of untreated municipal solid waste leads to gaseous emissions as well as liquid degradation products. In situ aeration is an emerging means for remediation of abandoned landfills. It aims at an accelerated mineralization and stabilization of waste organic matter and thus reduces significantly the emission potential of the site. In order to prove the success of the technique, evaluation of the biological stability of the aerated material has been suggested. Fourier Transform Infrared Spectroscopy (FT-IR) provides comprehensive information on the chemical composition of solid waste samples. Different stages of organic matter degradation are reflected by changes in the infrared spectral pattern. In the present study the feasibility of applying FT-IR for assessment of the stability of waste material derived from abandoned landfills and for in situ aeration process control was investigated. Waste samples derived in the course of pilot-scale and lab-scale aeration experiments were characterized by FT-IR (4000-400 cm(-1), KBr-technique, transmission mode) and a set of conventional parameters describing biological stability. The occurrence of distinct indicator bands was correlated with chemical and biological waste properties using 206 solid waste samples. Visual spectra interpretation was found to be appropriate in proving a reduced emission potential of initially rather reactive waste (respiration activity over 4 days (RA(4)) > 7 mg O(2) g(-1) DM) during aeration. Furthermore, cluster analysis was applied successfully to differentiate between original and aerated waste samples, even for rather stable material (RA(4) < 7 mg O(2) g(-1) DM), when visual spectra interpretation was limited.     

A framework for adaptive monitoring of the cumulative effects of human footprint on biodiversity

Effective ecological monitoring is imperative in a human-dominated world, as our ability to manage functioning ecosystems will depend on understanding biodiversity responses to anthropogenic impacts. Yet, most monitoring efforts have either been narrowly focused on particular sites, species and stressors — thus inadequately considering the cumulative effects of multiple, interacting impacts at scales of management relevance — or too unfocused to provide specific guidance. We propose a cumulative effects monitoring framework that integrates multi-scaled surveillance of trends in biodiversity and land cover with targeted evaluation of hypothesized drivers of change. The framework is grounded in a flexible conceptual model and uses monitoring to generate and test empirical models that relate the status of diverse taxonomic groups to the nature and extent of human “footprint” and other landscape attributes. An adaptive cycle of standardized sampling, model development, and model evaluation provides a means to learn about the system and guide management. Additional benefits of the framework include standardized data on status and trend for a wide variety of biodiversity elements, spatially explicit models for regional planning and scenario evaluation, and identification of knowledge gaps for complementary research. We describe efforts to implement the framework in Alberta, Canada, through the Alberta Biodiversity Monitoring Institute, and identify key challenges to be addressed.