Designing a mixed performance measurement system for environmental supply chain management using evolutionary game theory and balanced scorecard: A case study of an auto industry supply chain

This paper proposes a mixed performance measurement system using a combination of evolutionary game theory and the balanced scorecard (BSC) in environmental supply chain management (ESCM) that measures and evaluates business operations using the four different perspectives of finance, customer, internal business process, and learning and growth. ESCM plays an important role in the supply chain which leads to the reduction, reuse and recycling of resources involved in both upstream and downstream activities. This paper presents guidance for practical managers in evaluating and measuring ESCM by developing a knowledge-based BSC and evolutionary game theory. The primary purpose of this paper is to apply the proposed method in a case study to one of Iran's biggest auto industry supply chain SAIPA Company. The results of this study indicate that the adoption of ESCM, in the absence of regulatory pressures and cost-saving measures is triggered by public pressures and its implementation is limited by organizational factors and strategic myopia.     

Ecosystem states: Creating a data-derived, ecosystem-scale ecological response model that is explicit in space and time

Increasing difficulties associated with balancing consumptive demands for water and achieving ecological benefits in aquatic ecosystems provide opportunities for new ecosystem-scale ecological response models to assist managers. Using an Australian estuary as a case study, we developed a novel approach to create a data-derived state-and-transition model. The model identifies suites of co-occurring birds, fish, benthic invertebrates and aquatic macrophytes (as ‘states’) and the changing physico-chemical conditions that are associated with each (‘transitions’). The approach first used cluster analysis to identify sets of co-occurring biota. Differences in the physico-chemical data associated with each state were identified using classification trees, with the biotic distinctness of the resultant statistical model tested using analysis of similarities. The predictive capacity of the model was tested using new cases. Two models were created using different time-steps (annual and quarterly) and then combined to capture both longer-term trends and more-recent declines in ecological condition. We identified eight ecosystem states that were differentiated by a mix of water-quantity and water-quality variables. Each ecosystem state represented a distinct biotic assemblage under well-defined physico-chemical conditions. Two ‘basins of attraction’ were identified, with four tidally-influenced states, and another four independent of tidal influence. Within each basin, states described a continuum of relative health, manifest through declining taxonomic diversity and abundances. The main threshold determining relative health was whether freshwater flows had occurred in the region during the previous 339 days. Canonical analyses of principal coordinates tested the predictive capacity of the model and demonstrated that the variance in the environmental data set was well captured (87%) with 52% of the variance in the biological data set also captured. The latter increased to >80% when long- and short-term biological data were analysed separately, indicating that the model described the available data for the Coorong well. This approach thus created a data-derived, multivariate model, where neither states nor transitions were determined a priori. The approach did not over-fit the data, was robust to patchy or missing data, the choice of initial clustering technique and random errors in the biological data set, and was well-received by local natural resource managers. However, the model did not capture causal relationships and requires additional testing, particularly during future episodes of ecological recovery. The approach shows significant promise for simplifying management definitions of ecological condition and, via scenario analyses, can be used to assist in manager decision-making of large, complex aquatic ecosystems in the future.     

Development of a coupled reservoir operation and water diversion model: Balancing human and environmental flow requirements

Maintaining a natural flow regime helps preserve the health of riverine ecosystems. Conventional studies on reservoir operations have focused mainly on identifying optimal operational schemes for satisfying human water demands. To systematically reflect the ecological effects of both natural and human-induced hydrologic alterations, water diversions downstream of the reservoirs should be considered as well. This research focused on a coupled reservoir operation and water diversion (CROWD) model, created through the integration of a reservoir operation model and a water diversion model. The proposed model considers both human and environmental flow requirements, and represents a compromise that balances ecological protection (preservation of the natural flow regime of a river) and human needs (reduced water shortages). In the reservoir operation model, the reservoir space is divided into three zones and different operating rules are developed for directing reservoir operation when water levels are in different zones; in the water diversion model, different water users are assigned different supply priorities with the instream flows no more than the minimum environmental flows having the highest priority; and the two models are coupled by the water mass balance between the two hydraulic facilities. The non-dominated-sorting genetic algorithm II (NSGA-II) was used to determine the parameters of the developed CROWD model and the model was applied to support the joint operational management of the Tanghe Reservoir and the Liaoyang Diversion in the Tang river basin, China. The resulting reservoir operation and water diversion schemes indicate that the CROWD model is useful for optimizing the operation of reservoirs and water diversion schemes. Moreover, it helps to analyze tradeoffs between human and environmental water needs, resulting in solutions that reduce the risk of water shortages and minimize ecological integrity disturbances.     

Incorporating low-resolution historic species location data decreases performance of distribution models

Developing robust species distribution models is important as model outputs are increasingly being incorporated into conservation policy and management decisions. A largely overlooked component of model assessment and refinement is whether to include historic species occurrence data in distribution models to increase the data sample size. Data of different temporal provenance often differ in spatial accuracy and precision. We test the effect of inclusion of historic coarse-resolution occurrence data on distribution model outputs for 187 species of birds in Australian tropical savannas. Models using only recent (after 1990), fine-resolution data had significantly higher model performance scores measured with area under the receiver operating characteristic curve (AUC) than models incorporating both fine- and coarse-resolution data. The drop in AUC score is positively correlated with the total area predicted to be suitable for the species (R² = 0.163-0.187, depending on the environmental predictors in the model), as coarser data generally leads to greater predicted areas. The remaining unexplained variation is likely to be due to the covariate errors resulting from resolution mismatch between species records and environmental predictors. We conclude that decisions regarding data use in species distribution models must be conscious of the variation in predictions that mixed-scale datasets might cause.     

Regulatory attitudes and environmental innovation in a model combining internal and external R&D

The extent to which environmental regulatory institutions are either ‘green’ or ‘brown’ impacts not just the intensity of regulation at any moment, but also the incentives for the development of new pollution-control technologies. We set up a strategic model of R&D in which a polluter can deploy technologies developed in-house, or license technologies developed by specialist outsiders (an ‘eco-industry’). Polluters exert R&D effort and may even develop redundant technologies to improve the terms on which they procure technology from outside. We find that, while regulatory bias has an ambiguous impact on the best-available technology, strategic delegation to systematically biased regulators can improve social welfare.     

宝钢环境信息化系统建设探索

系统介绍了宝钢环境信息化系统建设架构、功能、特点,以及对污染减排、环境自动监测及信息化技术进行有效融合后的应用实践,并对该信息化系统在提高环境监控能力,完善系统建设上提出扩展监控范围、提升功能等构想.     

基于重要抽样法的耐压球壳可靠性计算方法研究

目的 解决耐压球壳极小失效概率的可靠性计算问题。方法 在自适应Kriging的基础上,结合重要抽样法提出耐压球壳可靠性计算方法。该方法在较大失效概率下构建的Kriging模型基础上获得重要方向,在重要方向上计算得到较低失效概率下的设计点,以设计点为中心,构建小失效概率的Kriging模型,并通过此模型采用重要抽样法开展可靠性计算。结果 分别使用提出的重要抽样法和蒙特卡洛法计算了2个算例的失效概率,计算结果表明,该方法具有较高的精度和效率。使用该方法对某耐压球壳工作载荷下的失效概率进行了计算,计算得到该球壳失效概率为4.094×10^–96。结论 研究结果可为无失效方程下极低失效概率的可靠性计算问题提供参考。     

Comprehensive and high-resolution emission inventory of atmospheric pollutants for the northernmost cities agglomeration of Harbin-Changchun, China: Implications for local atmospheric environment management

Using a bottom-up estimation method, a comprehensive, high-resolution emission inventory of gaseous and particulate atmospheric pollutants for multiple anthropogenic sectors with typical local sources has been developed for the Harbin-Changchun city agglomeration (HCA). The annual emissions for CO, NOx, SO₂, NH₃, VOC_S, PM_2.5, PM₁₀, BC and OC during 2017 in the HCA were estimated to be 5.82 Tg, 0.70 Tg, 0.34 Tg, 0.75 Tg, 0.81Tg, 0.67 Tg, 1.59 Tg, 0.12 Tg and 0.26 Tg, respectively. For PM₁₀ and SO₂, the emissions from industry processes were the dominant contributors representing 54.7% and 49.5%, respectively, of the total emissions, while 95.3% and 44.5% of the total NH₃ and NOx emissions, respectively, were from or associated with agricultural activities and transportation. Spatiotemporal distributions showed that most emissions (except NH₃) occurred in November to March and were concentrated in the central cities of Changchun and Harbin and the surrounding cities. Open burning of straw made an important contribution to PM_2.5 in the central regions of the northeastern plain during autumn and spring, while domestic coal combustion for heating purposes was significant with respect to SO₂ and PM_2.5 emissions during autumn and winter. Furthermore, based on Principal Component Analysis and Multivariable Linear Regression model, air temperature, relative humidity, electricity and energy consumption, and the urban and rural population were optimized to be representative indicators for rapidly assessing the magnitude of regional atmospheric pollutants in the HCA. Such indicators and equations were demonstrated to be useful for local atmospheric environment management.     

生态市建设的战略环境影响评价初探——以淮南市为例

生态市建设是一项系统工程，是实现可持续发展的必然途径。通过对战略环境影响评价理论、方法的探讨，开发出了针对生态市建设的战略环境影响评价技术框架，并以淮南市为例，构建了一套完整的战略环境影响评价指标体系。最后分析了淮南生态市建设SEIA的主要内容：土地利用规划、产业政策结构调整以及各项战略的环境影响评价，为生态市建设SEIA提供方法和技术支持。     

Developing sustainable products and services

In light of increasing pressures to adopt a more sustainable approach to product design and manufacture, the requirement to develop sustainable products is one of the key challenges facing industry in the 21st century. Hence, the concept of developing sustainable products as well as services is evolving as a key element of Cleaner Production. Sustainable product development initiatives (mainly through eco-design) have been evolving for some time to support companies develop more sustainable products. Ireland has been running the highly successful Environmentally Superior Products (ESP) initiative that supports industrial companies to incorporate a more sustainable approach to the development of products and/or services. The lessons learned from the ESP and other global Sustainable Product and Service Developments in industry and research, are being used to develop a method for effective sustainable product and/or service development (SPSD) in industry. The method is designed to provide pragmatic guidance to business and industry for developing sustainable products and services as well as incorporating this approach within existing corporate strategy, cleaner production and product development systems. This method is being developed by the authors at the Environmental Policy and Management Group (EPMG), Department of Environmental Science and Technology, Imperial College London, UK in conjunction with industry and practitioners. The method provides a framework for implementing SPSD throughout the entire lifecycle of a product and/or service. It can be used to identify, assess and implement the options for optimum sustainability in the design and development of a product and/or service. This paper describes the key features of this method.