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.     

Increasing utilisation efficiency of ferric chloride etchant in industrial photochemical machining

The environmental effects of photochemical machining (PCM) can be appreciable in view of the nature of the industry whereby various chemicals are used in the preparation and cleaning of metal surfaces, photographic processing of phototooling, coating and selective removal (development) of photoresists, etching through apertures in the resist stencils and stripping of resist after etching. This paper concerns the environmental impact of ferric chloride, the most commonly used etchant in PCM, and is believed to be the first quantitative analysis for the PCM industry. The findings showed that more than half of the PCM companies used regeneration of ferric chloride etchant and 76.3% of companies were prepared to use a more environment-friendly regeneration system at a higher overall cost. Regarding ferric chloride consumption, it was found that the performance of companies varies greatly: companies using regeneration were, on average, nearly seven times (340.8% compared with 51.1%) more efficient than those that do not regenerate, and the most efficient company used 135 times less etchant than the least efficient company. The findings of this study and the analysis carried out can be used by PCM companies as a benchmark in assessing their environmental performance with respect to etchant consumption efficiency.     

Fuzzy Possibilistic Modeling for Closed Loop Recycling Collection Networks

Nowadays, in the competitive market, commercial companies due to their economic problems and also restrictions imposed by international organizations to comply with environmental regulations are making noticeable efforts to reduce the level of their wastes in their manufacturing systems and consequently the level of waste in consumers’ products. In harmony with this issue, one of the most effective ways which has successfully been used and proven to be economically profitable is to take products lifecycles into consideration. Consideration of products lifecycle has made supply chain practitioners to investigate the reverse logistics activities in addition to forward logistics activities. Hence, corporations, in order to reduce their cost on the one hand and boosting their efficiency on the other hand, were obligated to employ closed loop supply chain models to concurrently benefit from its economical and environmental advantages. Therefore, in this paper, a mixed nonlinear facility location–allocation model is proposed for recycling collection centers. The considered closed loop logistics model consists of multiple echelons, multiple suppliers, multiple collection centers, multiple time period and also multiple facilities. In real-life problems parameters like demand, cost, capacity, distances, and quantities of returned products are always uncertain. Therefore, in order to solve a realistic problem, foregoing parameters are considered as fuzzy in our proposed model. Subsequently, to solve fuzzy mixed nonlinear programming model, one of the most effective technique in the literature is used. Additionally, in order to demonstrate the behavior of the parameters employed in the model, a comprehensive sensitivity analysis is conducted. Computational results demonstrate that the proposed model can show favorable efficiency in solving supply chain problems.     

Developing a fuzzy neural network-based support vector regression (FNN-SVR) for regionalizing nitrate concentration in groundwater

The aim of this study is to develop a fuzzy neural network-based support vector regression model (FNN-SVR) for mapping crisp-input and fuzzy-output variables. In this model, an artificial neural network (ANN) estimator based on multilayer perceptron (MLP) is considered as the kernel function of the SVR, whereas asymmetric triangular fuzzy H-level sets are assumed for model parameters including weight and biases of the ANN model. A genetic algorithm (GA) with real coding is implemented to optimize the model parameters during the training phase. To evaluate the efficiency and applicability of the proposed model, it is applied for simulating and regionalizing nitrate concentration in Karaj Aquifer in Iran. The goodness-of-fit criteria indicate a better performance of the FNN-SVR compared to some benchmark models such as geostatistic techniques as well as traditional SVR models with linear, quadratic, polynomial, and Gaussian kernel functions for modeling nitrate concentrations in groundwater.     

An improved stochastic life-cycle cost analysis model for examining the impact of environmental policy instruments on construction equipment replacement

Both contractors and governments are eager for a model that can assist them to examine the impact of environmental policy instruments (EPIs) on construction equipment replacement from a stochastic perspective. Therefore, this study introduces an improved stochastic life cycle cost (LCC) analysis model and designs eight scenarios in which different EPIs are considered for such examination. The limitation of the traditional LCC analysis model has been examined. The effectiveness of the improved LCC analysis model is demonstrated with its application in a 2002 Sterling LT9500 dump truck in the US market. The results show that: (1) The traditional LCC analysis model is not robust due to failing to consider costs incurred by EPIs and a lack of stochastic perspective. (2) Mandatory administration policy instruments (EPI_A) can promote earlier replacement of construction equipment, but EPI_A can put a heavy financial burden on contractors. (3) When economic incentive policy instruments such as grants or subsidies programs (EPI_BGS) and tax credits programs (EPI_BT) are not lucrative enough, it is very hard to involve contractors in these programs, which will hardly motivate them to replace their construction equipment earlier. (4) A combination of EPI_A, EPI_BGS and EPI_BT can work better, which can motive contractors to earlier replace existing equipment, and reduce the financial burden of contractors to some extent.     

Environmental assessment and investment strategies of provincial industrial sector in China — Analysis based on DEA model

As an energy-intensive industry, the industrial sector consumes 70% of energy consumption and causes serious environmental pollution in China. Also, the government emphasized the promotion of R&D investment in the industrial sector in China's National Plan on Climate Change (2014–2020). It is meaningful and contributes to assessing energy and environmental performance, as well as R&D and industrial pollution control (IPC) investment strategies of China's industrial sector. A non-radial DEA model, as with natural and managerial disposability, was adopted to evaluate this from provincial and regional perspectives during the 2008–2012 period. Energy and environmental performance was evaluated by unified efficiency under natural disposability (UEN), unified efficiency under managerial disposability (UEM), and unified efficiency under natural and managerial disposability (UENM). The empirical results indicated that Shandong and Hainan were efficient under natural and managerial disposability, while other provinces had the potential to improve their energy and environmental performance. The number of provinces that was fit for investments of R&D and IPC increased from 2008 to 2010, then decreased in 2011 and 2012. In spite of this, many provincial industrial sectors should make efforts to reduce pollution by investment on technology. Tianjin, Heilongjiang, Jiangxi and Henan were especially the best investment objects because investments of R&D and IPC turned to be effective for them during the whole study period. Moreover, western China had the highest average UENM, followed by eastern China and central China. Eastern China and central China were rewarding to expand investments. Coal consumption was the main factor to negatively affect unified efficiency whereas the increase in economic development level was primarily responsible for the improvement of unified efficiency. According to the results, differentiated suggestions to further improve energy and environmental performance were proposed.     

An Indicator for the Economic Performance and Ecological Sustainability of Nations

This document proposes a new indicator to assess countries’ sustainability. The indicator synthetises measures of economic and ecological efficiency. In other words, we assess the ability of countries to use resources to produce the maximum possible amounts of goods and services while keeping production activities’ impact on the environment as low as possible. The measure of ecological efficiency is the ecological reserve/deficit (ERD), which is based on the concept of ecological footprint. The new indicator is computed using the data envelopment analysis (DEA) model, a well-known non-parametric technique that delivers measures of productive efficiency by comparing outputs to inputs used in production. We modify the standard DEA model in two ways. Firstly, we allow for negative input and output data. Secondly, to increase DEA discriminating power of countries, we compute anti-efficiency measures. This allows us to obtain a ranking of countries based on the best and worst performances. Results show that the new efficiency indicator is valid and that high ERD positively influences the ranking of countries. Introducing anti-efficiency provides more plausible results and a more accurate ranking, for example high-polluting countries like China previously economically efficient are now ranked as low efficient when sustainability is taken into account.

     

Developing an automated BIM-based life cycle assessment approach for modularly designed high-rise buildings

Modular construction has attracted increasing attention due to its energy and environmental benefits. Digital technologies such as building information modelling (BIM) have also been explored to generate and manage data through the lifecycle of buildings. Although research has been performed in the area of integrating BIM and modular construction, BIM-based automated lifecycle assessment (LCA) of prefabricated buildings remains unexplored. This study therefore aims to develop a BIM-based LCA method for prefabricated buildings incorporating different assessment levels with unique system boundaries and functional units. The developed approach can support automated assessments through all lifecycle phases of a prefabricated building. It is achieved through an automated process of creating parameters to merge LCA data into the building model, systematic zoning, model setup and impact estimation. This approach is applied to evaluate the energy and environmental performances of a case building in Hong Kong. The case study validated the efficiency of the developed BIM-based LCA method in providing a systematic and detailed assessment of modularly designed buildings. This study extends the knowledge in automated BIM-based LCA by addressing specific characteristics of prefabrication and promotes the incorporation of comprehensive and detailed LCA data into BIM models for improved design robustness and holistic performances of buildings. This validated approach will enhance the willingness of designers to apply LCA during the design stages for minimizing the energy and environmental impacts of both new and renovated buildings with prefabrication.     

A Rapid Method for Assessing the Environmental Performance of Commercial Farms in the Pampas of Argentina

The generation of reliable updated information is critical to support the harmonization of socio-economic and environmental issues in a context of sustainable development. The agro-environmental assessment and management of agricultural systems often relies on indicators that are necessary to make sound decisions. This work aims to provide an approach to (a) assess the environmental performance of commercial farms in the Pampas of Argentina, and (b) propose a methodological framework to calculate environmental indicators that can rapidly be applied to practical farming. 120 commercial farms scattered across the Pampas were analyzed in this study during 2002 and 2003. Eleven basic indicators were identified and calculation methods described. Such indicators were fossil energy (FE) use, FE use efficiency, nitrogen (N) balance, phosphorus (P) balance, N contamination risk, P contamination risk, pesticide contamination risk, soil erosion risk, habitat intervention, changes in soil carbon stock, and balance of greenhouse gases. A model named Agro-Eco-Index was developed on a Microsoft-Excel support to incorporate on-farm collected data and facilitate the calculation of indicators by users. Different procedures were applied to validate the model and present the results to the users. Regression models (based on linear and non-linear models) were used to validate the comparative performance of the study farms across the Pampas. An environmental dashboard was provided to represent in a graphical way the behavior of farms. The method provides a tool to discriminate environmentally friendly farms from those that do not pay enough attention to environmental issues. Our procedure might be useful for implementing an ecological certification system to reward a good environmental behavior in society (e.g., through tax benefits) and generate a commercial advantage (e.g., through the allocation of green labels) for committed farmers.     

A strategic management model for evaluation of health,safety and environmental performance

Strategic health, safety, and environmental management system (HSE-MS) involves systematic and cooperative planning in each phase of the lifecycle of a project to ensure that interaction among the industry group, client, contractor, stakeholder, and host community exists with the highest level of health, safety, and environmental standard performances. Therefore, it seems necessary to assess the HSE-MS performance of contractor(s) by a comparative strategic management model with the aim of continuous improvement. The present Strategic Management Model (SMM) has been illustrated by a case study and the results show that the model is a suitable management tool for decision making in a contract environment, especially in oil and gas fields and based on accepted international standards within the framework of management deming cycle. To develop this model, a data bank has been created, which includes the statistical data calculated by converting the HSE performance qualitative data into quantitative values. Based on this fact, the structure of the model has been formed by defining HSE performance indicators according to the HSE-MS model. Therefore, 178 indicators have been selected which have been grouped into four attributes. Model output provides quantitative measures of HSE-MS performance as a percentage of an ideal level with maximum possible score for each attribute. Defining the strengths and weaknesses of the contractor(s) is another capability of this model. On the other hand, this model provides a ranking that could be used as the basis for decision making at the contractors’ pre-qualification phase or during the execution of the project.     

Investigation of impact of environmental changes on precipitation pattern of Pakistan

In this paper, variability in precipitation pattern of Pakistan due to environmental and climatic changes has been studied. Maps have been generated to depict global precipitation variation. Precipitation data of 25 stations of Pakistan have been used. These data were taken from Meteorological Department, Islamabad, Pakistan. The results of two global climate models, namely Australia’s Commonwealth Scientific and Industrial Research’s third generation general circulation model and National Center for Atmospheric Research’s first generation precipitation circulation model for A2 scenario have been applied to investigate the changes. It is observed that precipitation pattern will change significantly in the future. The occurrence of precipitation in all seasons for Pakistan is expected to increase with almost uniform distribution across a season. Average annual precipitation of the country will undergo an increase in the range of +57 to +71 % as compared to average of the base period.     

An Evaluation of Microscopic Emission Models for Traffic Pollution Simulation Using On-board Measurement

As a result of the continuously increasing numbers of motor vehicles in metropolitan areas worldwide, road traffic emission levels have been recognized as a challenge during the planning and management of transportation. Experiments were conducted to collect on-road emission data using portable emission measurement systems in two Chinese cities in order to estimate real traffic emissions and energy consumption levels and to build computational models for operational transport environment projects. In total, dynamic pollutant emissions and fuel consumption levels from dozens of light duty vehicles, primarily from four different vehicle classes, were measured at a second-by-second level. Using the collected data, several microscopic emission models including CMEM, VT-Micro, EMIT, and POLY were evaluated and compared through calibration and validation procedures. Non-linear optimization methods are applied for the calibration of the CMEM and EMIT models. Numerical results show that the models can realize performance levels close to the CMEM model in most cases. The VT-Micro model shows advantages in its unanimous performance and ability to describe low emission profiles while the EMIT model has a clear physics basis and a simple model structure. Both of them can be applied when extensive emission computation is required in estimating environmental impacts resulting from dynamic road traffic.     

A performance evaluation of strategic environmental assessment (SEA) processes within the South African context

SEA has been described as being more about process than about product. Yet very little research has been conducted to gain a better understanding of how SEA processes perform within developing country contexts. To address this gap in knowledge the research underlying this paper aimed to evaluate the quality of SEA processes within the South African context against specifically designed key performance indicators. Comparison of the different data patterns revealed general SEA process features as well as three broad models, namely the ‘stand alone’, ‘central to decision making’ and ‘integrated’ models. The research results suggest a particularly poor performance in terms of process quality for the SEA case studies investigated. Moreover, it shows that there is no one understanding of SEA process within the South African context. The main limitations related to a weak understanding of the decision making processes SEA aimed to inform, as well as an inability to incorporate flexibility into process design. To take the debate forward it is proposed that SEA follow-up and effectiveness research be explored to determine which of these models (if any) ultimately contributed to influencing decision making and promote sustainability.     

Does the air pollution joint prevention and control policy possess the Porter effect in China -evidence from two perspectives

In order to fundamentally get rid of the plight of air pollution, China has introduced and implemented a series of joint prevention and control (AJPC) policies on air pollution. The Porter hypothesis emphasizes that environmental policies can create both environmental and economic dividends, building a win-win prospect for energy efficiency and economic growth, that is the Porter effect. However, the Porter effect of AJPC has not received the attention it deserves. Therefore, we empirically studied the short- term and long-term Porter effect of AJPC. Firstly, using the data of 283 prefecture-level cities, we studied the short-term Porter effect of AJPC by applying Propensity Score Matching Difference-in-Difference model (PSM-DID). Then, Data Envelopment Analysis (DEA) was used to estimate the potential Porter effect of AJPC, that is, the potential economic and environmental dividends of AJPC. In addition, we also calculated regional Global Malmquist Luenberger (GML) to observe variations in total factor productivity to observe the technology change caused by AJPC. Results showed that, AJPC policy has not realized Porter effect from the short-term perspective. In the long run, AJPC has environmental dividends but no economic dividends. In other words, there is no long-term Porter effect with AJPC. The implementation of AJPC policies can increase regional total factor productivity, in which technical efficiency is improved but technological progress remains unchanged.     

An Optimization Model for Integrated Coastal Management: Development and a Case Study Using Italy’s Comacchio Municipality

In this paper, I develop an optimization model for integrated coastal management in which decisions arise from an area-based algorithm that minimizes predicted damage caused by beach erosion and inshore flooding, while accounting for economic, social, and environmental losses. The model favors the involvement of stakeholders in coastal management, but does not use complicated assessment procedures for non-economic indicators or relative weights to combine economic, social, and environmental indicators. Instead, the integration between economic activities or properties and the environmental status and landscape is represented objectively and non-linearly by referring to initial and sustainability conditions, combined with budgetary and environmental constraints. The model successfully accounted for both human and environmental dynamics by depicting delayed effects, neighborhood externalities, and feedback effects. It calculated a single optimal value for each integrated coastal management strategy, which permitted the support of future decisions and the evaluation of past decisions. The model’s insights were based on reliable estimates, with reliability determined by calculating the confidence level. The model was successfully applied to Italy’s Comacchio coastal municipality, where it revealed the priorities for optimal beach nourishment, dune fixation, and residential and holiday housing development based on budget constraints, beach losses, flood damage, pollution impacts, and land-use constraints.     

The effect of collaboration and IT competency on reverse logistics competency - Evidence from Brazilian supply chain executives

Business models have being designed, worldwide, to create sustainability competencies and in particular to incorporate reverse logistics, but Brazilian executives have not yet fully adhered to Law 12,305 on solid waste and reverse logistics. What would be the Brazilian executives' perception about reverse logistics competency and the support provided by a collaborative and IT competency? The objective of the paper is to investigate the effects of collaboration and IT competency in developing reverse logistics competency, as a strategy, and its consequences in economic and environmental performance. A survey was performed with 320 Brazilian supply chain executives and analyzed using Structural Equation Modeling. The models demonstrated that collaboration has a direct positive influence on the development of reverse logistics competency, by executives' point of view. The moderation effect between collaboration and IT competency for reverse logistics was not confirmed, since it was adopted a strategic view of reverse logistics. Therefore, despite there was not a moderation effect, IT presented a lower direct effect on reverse logistics competency. Results reinforce that organizations that develop reverse logistics competency tend to improve their economic and environmental performances.     

How does trade development affect environmental performance? New assessment from partially linear additive panel analysis

Assessing the linkage between trade development and environmental quality has recently attracted increasing attention because of the rapid advancement of trade globalization along with the severe degradation of the environment. However, neglecting the possible nonlinear relationship between the variables, the existing studies mainly use linear models to explore the trade-environment linkage. To fill this gap, this paper introduces a novel partially linear additive panel model that highlights nonlinear and heterogeneous features to investigate the direct and indirect influences of trade development on environmental performance over the period 2005–2017 in China. The results show that trade has an inverse “U-shaped” direct effect on the environment. In contrast, trade development can indirectly improve environmental quality through economic growth. Nonlinear marginal analysis demonstrates that such an impact not only presents individual differences but also embodies the trait of temporal dynamics. Empirical results further reveal the importance of our model, which can automatically identify the variable nexus and thus reduce the setting error of the parametric models. Model evaluation also confirms the superiority of the used model over existing parametric and nonparametric models. The partially linear additive panel model provides a new evaluation method for environmental impact regarding trade development, and can be applied to other fields where an assessment of the effect of socio-economic factors on the environment is needed.     

The spatial convergence and drivers of environmental efficiency under haze constraints - Evidence from China

Haze has seriously threatened the ecological environment and public health, so researching environmental efficiency under haze constraints is significant in managing pollution and evaluating the balance between economic development and environmental health. Based on the panel data of China's 99 cities during 2005–2017, this paper uses α-convergence and β-convergence models to analyze the spatial convergence of environmental efficiency under haze constraints and its drivers in China,specifically in Eastern China, Central China, and Western China.The main results are as follows: (1) The trend of environmental efficiency under haze constraints in these regions evidently follows a dumbbell curve. In recent years, it has been growing slowly in Eastern China, Central China, and Western China, and the environmental efficiency in the Eastern China is the highest, the Central China is the second, and the Western China is the lowest; (2) it demonstrates both α-convergence and β-convergence in Central China, Western China, and Eastern China, and the speed of convergence is the fastest in the Central China, the second in the Western China and the slowest in the Eastern China; there is a “catch-up effect” in cities from less environmentally efficient regions to more efficient regions; and (3) Industrial structure and degree of trade dependence have a significantly negative correlation; characteristics of the region and dependence on foreign investment have significantly positive correlations with the environmental efficiency of Eastern China and Central China; environmental regulations and economic scale limit the improvement of environmental efficiency of Central China and Western China; and technological innovation significantly impacts Eastern China only. Although the paper refers to the specific evidence of China, with haze as a new indicator in the comprehensive evaluation of environmental efficiency can be extended to other developing countries as well as to other pollutants such as land pollution and waste water. The understanding of drivers of environmental efficiency under haze constraints in China provides international policy-makers with valuable reference for formulating effective measures to balance the dilemma between economic development and environmental health.     

有机污染物环境逸度模型构建及软件化

目前研究人员已经可以通过建立模型来评估有机物的环境风险并研究其在多介质环境中的迁移与转化。针对多介质逸度模型中的参数繁多,不利于研究人员模拟有机污染物的归趋状况的问题,现基于Ⅲ级多介质环境逸度模型,采用Python编程语言进行软件设计,完成有机物在环境各介质中的分布模拟功能,并在此基础上集成参数灵敏度和模型不确定度分析功能,且对用户提供了友好的图形界面。以北京地区地表水环境中的药物和个人护理品（PPCPs）为例,研究结果表明该软件得到的模拟值与实测值有较好的吻合度,可为有机物的区域环境污染和风险评估提供参考。     

Critical appraisal of available thermodynamic data for the complexation of antimony(III) and antimony(V) by low molecular mass organic ligands

Antimony is an element of increasing environmental significance but one whose chemical speciation has received little attention and, until recently, one which had not been modelled in any comprehensive way. This paper reports thermodynamic data for computer speciation models of antimony in aqueous, multicomponent solutions of environmental and biological interest involving low molecular mass organic ligands. The available data have been critically evaluated and entered into a thermodynamic database. The JESS suite of computer programs has been used to develop the thermodynamically-consistent mass balance equations used for modelling purposes. No data could be found for Sb(V) complexes and only a few of the existing data for Sb(III) complexes can be considered as being reliably described.