Evaluating efforts to build sustainable WEEE reverse logistics network design: comparison of regulatory and non-regulatory approaches

Many developing countries such as Turkey are still making an effort on building an infrastructure for waste of electrical and electronic equipment (WEEE) reverse logistic network design (RLND) processes. It is obvious that policies/laws/regulations related to WEEE management provide a sustainable framework for implementation in the RLND. The question is here: Does the implementation of WEEE directives make sense in terms of reducing the total cost of the network in the long term? This study aims to compare regulatory and non-regulatory situations of WEEE RLND in developing countries by formulating two models named as ‘regulatory’ and ‘non-regulatory’. Model 1 is considered as sustainable with economic, environmental and social goals, and the quotas imposed by the environmental directive are taken into consideration as the data of product return amount. In Model 2, only economic goal is considered, and product return amount is forecasted using Artificial Neural Network (ANN). A case study is conducted in a recycling company in order to evaluate performance of the proposed models. This study contributes to the relevant literature by (1) comparing the regulatory and non-regulatory situations RL models explicitly and (2) proposing ANN model to forecast EEE product return or WEEE quantity for non-regulatory situation.     

Addressing challenges for future strategic‐level emergency management: reframing,networking, and capacity‐building

The mounting frequency and intensity of natural hazards, alongside growing interdependencies between social‐technical and ecological systems, are placing increased pressure on emergency management. This is particularly true at the strategic level of emergency management, which involves planning for and managing non‐routine, high‐consequence events. Drawing on the literature, a survey, and interviews and workshops with Australia's senior emergency managers, this paper presents an analysis of five core challenges that these pressures are creating for strategic‐level emergency management. It argues that emphasising ‘emergency management’ as a primary adaptation strategy is a retrograde step that ignores the importance of addressing socio‐political drivers of vulnerabilities. Three key suggestions are presented that could assist the country's strategic‐level emergency management in tackling these challenges: (i) reframe emergency management as a component of disaster risk reduction rather than them being one and the same; (ii) adopt a network governance approach; and (iii) further develop the capacities of strategic‐level emergency managers.     

Non-linear autoregressive neural network approach for inside air temperature prediction of a pillar cooler

The volcanic plate made pillar cooler system is designed for outdoor spaces as a heat exchanging medium and reduces the outcoming air temperature which flows through the exhaust port. This paper proposes the use of artificial neural networks (ANNs) to predict inside air temperature of a pillar cooler. For this purpose, at first, three statistically significant factors (outside temperature, airing and watering) influencing the inside air temperature of the pillar cooler are identified as input parameters for predicting the output (inside air temperature) and then an ANN was employed to predict the output. In addition, 70%, 15% and 15% data was chosen from a previously obtained data set during the field trial of the pillar cooler for training, testing and validation, respectively, and then an ANN was employed to predict inside air temperature. The training (0.99918), testing (0.99799) and validation errors (0.99432) obtained from the model indicate that the artificial neural network model (NARX) may be used to predict inside air temperature of pillar cooler. This study reveals that, an ANN approach can be used successfully for predicting the performance of pillar cooler.     

Optimization of thermal performance of the parabolic trough solar collector systems based on GA-BP neural network model

The aim of this paper is to optimize the thermal performance (system output energy, thermal efficiency, and heat loss of cavity absorber) of parabolic trough solar collector (PTC) systems in order to improve its thermal performance, based on the genetic algorithm-back propagation (GA-BP) neural network model. There are a number of undefined problems, fuzzy or incomplete information and a complex thermal performance of the PTC systems. Therefore, the thermal performance prediction of the PTC systems based on GA-BP neural network model was developed. Subsequently, the metrics performances have been adopted to comprehensively understand the algorithm and evaluate the prediction accuracy. Results revealed that the GA-BP neural network model can be successfully used to predict the complex nonlinear relationship between the input variables and thermal performance of the PTC systems. The cosine effect has a great influence on the thermal performance; thereby the geometrical structure of the PTC systems was optimized. It was found that the optimized geometrical structure was beneficial to improve the thermal performance of the PTC system. In conclusion, the GA-BP neural network model has higher prediction accuracy than the other algorithm and it can be feasible and reliable.     

京津冀协同发展的生态环境保护战略研究

随着中共中央在2014年将京津冀协同发展上升为国家战略,京津冀区域再次成为我国北方重要的经济增长极。然而,京津冀地区当前环境形势仍十分严峻,是全国水资源最短缺,大气污染、水污染最严重的区域,生态环境是京津冀协同发展需要尽快补齐的突出短板。本文深刻分析了京津冀区域当前大气、水、生态三个领域存在的突出问题以及内在的体制机制不协调。在此基础上,明确了解决京津冀生态环保总体思路,并分别从环境功能区划、生态保护红线、大气联防联控、跨界水环境治理、环境监管联动以及体制政策创新等方面提出针对性解决措施,为国家开展京津冀生态环境协同治理提供参考借鉴。     

黄河流域区域发展优势与经济带生成可能

基于进化经济学和进化经济地理学的理论,文章重点讨论了黄河流域的区域发展优势和建成黄河流域经济带的可能性。研究从黄河流域发展的历史出发,论证了黄河流域经济发展的区域地理学本性(nature)条件和现实可能性:第一,黄河流域经济发展的区域地理学本性条件是,该区域已经完成了农业经济建设,出现了遍在性的工业化和经济区人口聚集,特别是经过长期聚集,黄河流域已经形成了中国的人口密集带,形成了具有区域发展优势的中原城市群。第二,在分析黄河流域区域发展优势基础上,提出建成“大中原-黄河经济带”的可能性及其发展途径,即在生态保护的前提下,坚持地理环境的鲁棒性建设,坚持城市创新发展,坚持发展新型产业。第三,地区发展政策重点应该关注中原城市群的工业化-城市化发育和一体化产业链的形成,根据新经济地理学理论,提倡城市产业专业化方向,打破省界限制,发挥经济区的地缘结构优势,在空间上与环渤海经济带融合,完成黄河流域经济带高质量发展的战略构想。     

用微生物群落评价水系的自组织人工神经网络方法

利用原生物群落在PFU上群集过程中的变化,可以评价水质和监测水污染,运用T．Kohonen自组织人工神经网络模型,根据NacArthur－Wilson平衡模型提出了3个功能参数和另外2个结构参数,对常德市16个站四季的水质进行了分析,建立了水质污染程度预测的计算机智能专家系统,预测成功率达100％。     

非点源污染的管理及控制

非点源污染是指溶解的或固体污染物从非特定的地域,在降水和径流冲刷作用下,通过径流过程而汇入受纳水体引起的水体污染,主要起源于土壤侵蚀,农药与化肥的施用,农村家畜粪便与垃圾,农田污水灌溉,城镇地表径流,林区地表径流和大气干湿沉降等污染源。     

水利水电工程环境影响综合评价的人工神经网络专家系统

在分级加权评价模型层次结构体系基础上,以三峡工程为背景,应用人工神经网络技术,建立了一个水利水电工程环境影响综合评价的人工神经网络专家系统,该专家系统的知识获取和存贮方式与普通专家系统不同,具有较高的推理效率,较强的容错、自适应和自我更新能力。      

Water quality indices appraisal and health risk assessment of nitrate,mercury and lead in water distribution network: A case study of Robat Karim in Tehran,Iran

Groundwater is a basic source of drinking water supply for urban and rural areas. This is especially the case for communities located in arid and semi-arid regions that rely on groundwater for drinking purposes. The present study set out to assess the potential health impacts of water impurities and to investigate the qualitative status of drinking water in Robat Karim rural areas, located in southwest Tehran, Iran. A total of 66 samples were collected from the water distribution network of 11 villages (33 sampling points, on two occasions) during September 2020 and were tested in terms of the most common quality parameters such as pH, mercury (Hg), lead (Pb), copper (Cu), zinc (Zn), chloride (Cl^–), chlorate (ClO₃^–), nitrite (NO₂^–), nitrate (NO₃^–), and flouride (F^–). Multiple methods and indexes including water quality index (WQI), hazard quotient (HQ), and hazard index (HI), were worked out to assess the quality of water and health risk assessment of NO₃^– Pb²⁺ and Hg²⁺. The results revealed that 33% and 90% of sampling sites have significantly high nitrate and total hardness (TH) concentrations, exceeding the maximum permissible limits set by World Health Organization (WHO; 50 and 200 mg/L, respectively). Furthermore, five sampling points exhibited poor WQIs mainly related to NO₃^– and TH. HQ values higher than 1 for nitrate were noticed in most sampling locations. Except for one sampling point, the HQ obtained for Pb²⁺ and Hg²⁺ were below 1 indicating no obvious health hazard. This study represents that children and infants are at higher risk of chronic toxicity by excess NO₃^– intake. The health hazard that is yet imposed on the community by NO₃^– necessitates regular monitoring of drinking water, the use of advanced technologies to purify water or otherwise alternative resources should be proposed.