Rivers are considered the most important channel for microplastics traveling to the ocean from inland. The Yellow River is one of a main microplastics source for the Bohai Sea. As hydropower station operations—especially the artificial flood pulse—could significantly affect the transportation processes of microplastics, it is necessary to investigate the transportation regulation of microplastics from the Yellow River to the estuary. In this study, the distribution of microplastics (across 10 sections of the river from Xiaolangdi to the estuary) was detected at three stages (the pre-, inter-, and post-artificial flooding season). The result showed that the microplastic concentrations in the Yellow River ranged from 0.105 to 1.17 items m-2. The main microplastic shapes found were foam and film, and the main components were expanded polystyrene and polyethylene. The average particle sizes were 1101.54, 484.93, and 509.46 μm at the three stages, respectively. The artificial flood accelerated the transport of microplastics from inland to the estuary and ocean; it also unified the overall particle size of microplastics along the river. The microplastics in the surface water of the study area likely originate mostly upstream of the Xiaolangdi Hydropower Station. The artificial flooding generated from water and sediment regulation transports a large amount of microplastics in the reservoirs and river channels to the estuary and offshore areas in a short time period via artificial flooding.

This paper examines the process through which a construction project’s implementation of green practices in its site processes influences its economic performance by meeting environmental performance standards. The uniqueness of this study stems from its focus on practices carried out on the construction sites, and the consideration of project economic performance as against corporate level performance. A conceptual model is proposed and tested using a sample of 168 construction projects completed by class A contractors in Nigeria. The data were analysed through the Partial Least Squares Structural Equation Modelling (PLS-SEM) technique. Results obtained showed that the model satisfied all the criteria for both the measurement model and structural model for formative constructs. The study results indicate that environmental performance only partially mediates the relationship between green construction site practices and economic performance. The results imply that, it is not in all occasions that a project meeting environmental performance standard will result in the construction project been economically profitable, as adopting green construction site practices could lead to economic performance without necessarily performing environmentally. It is recommended that contractors should exhibit some level of flexibility while adopting green practices on site in order to achieve a balance between green practices, environmental performance and economic performance.

The textile industry has a high share in the total energy consumption of the manufacturing industry, especially in global textile supplier countries. Energy consumption and air emissions can be reduced at the source with detailed cleaner production and energy efficiency applications in textile production processes. In this study, energy efficiency studies were carried out in an integrated woolen textile facility. In this context, energy consumptions were analyzed based on the main production and other preparatory processes by detailed onsite investigations. Specific electricity, thermal energy, and air emissions were calculated based on the production processes of the facility. In addition, specific energy consumption values were compared with similar textile facilities to evaluate energy saving potentials and opportunities. A list consisting of 85 energy efficiency techniques was prepared to reduce energy consumption and air emissions in the facility. These techniques were evaluated and prioritized in terms of techno-economic feasibility, potential savings, and environmental benefits using a systematic decision-making model. Ultimately, it was decided to apply the following priority energy efficiency techniques (a total of 13): process optimization, the establishment of a process-based energy monitoring and control system, the recovery of waste heat, the optimization of steam boilers, the modification of radio frequency (RF) dryers, the modification of fan motors in the ventilation-humidification system, the proper positioning of compressors, the installation of a compressor monitoring system, and an air emission treatment system. It was found that with the application of such techniques, electricity, thermal energy, and air emissions could be reduced by 8–27%, 12–28%, and 23–45%, respectively. Based on the financial analysis, the payback periods of the priority energy efficiency techniques were found to be generally less than 36 months.

The implementation of Integrated Management Systems (IMS) has become a prerequisite for any organization looking to transform itself into a competitive and more sustainable enterprise. However, these efforts are not successful for some organizations, and there is an opportunity to explore what it takes to have an effective IMS implementation. Prior studies attribute several barriers to implementation. Yet, little is known about the degree to which these barriers impede implementation. To fill this gap in the literature, we have developed a systematic framework to prioritize barriers. We first identify and classify barriers using a literature review and modified Delphi method providing twenty-six barriers categorized under six main categories. These included Resources and Management, People, Implementation, Economic, Social & Legal and Cultural. Next, we used Analytical Hierarchical Process (AHP) to calculate weights and rankings of barriers and sub-barriers. We then take this process a step further by using a Grey preference by similarity to ideal solution (GTOPSIS) methodology to further prioritize alternatives. The results reveal the implementation and social & legal barrier categories ranked highest among major categories. Overall rankings showed that the economic and implementation sub-barrier is more important than the other twenty-four sub-barriers within different categories. The contributions of this study provide new insights regarding levels of integration and employee motivation as important to overcoming barriers to implementation. Finally, a sensitivity analysis checked the robustness of the proposed research framework that could be implemented to overcome the IMS barriers. This study is the first of its kind to organize barriers of IMS in this way. The outcomes of this study will assist organizations and policymakers in their decision making regarding IMS implementation while simultaneously improving sustainability practices. Researchers will find new IMS implementation insights and constructs for further empirical investigation.

The background for this paper was a wish to extend the understanding of how sustainable transitions in sociotechnical systems come about, especially the characteristics of processes and the role of actors. The empirical context was the case of developing biogas production and improving transport in the Trondheim region in Norway. The case consisted of two connected units; establishment of a biogas plant (production side) and development of a sustainable public transport system (use side). As a template for the analysis, the Multilevel Perspective (MLP) on sociotechnical transitions was applied. The core in this perspective is the (sociotechnical) regime level, where changes have to occur in order for sustainable transitions to take place. Central at the regime level is the interaction between actors, technologies and institutions. Transitions can take place if actors experience threats from the external world and have access to niche innovations. Analysis of the case showed that the development first went through a transformation phase (ca. 1990-2009) where R&D actors developed basic technical innovations. In the next phase (2009-2019) there was a reconfiguration process were politicians and market actors engaged. Over the years, this process resulted in significant sustainability outcomes (increased production of biogas and exchange of fossil for biofuels in transport). Three major lessons can be drawn: 1) the crucial role of leadership when it comes to interpreting external changes, timing of actions and coordination of resources, 2) the necessity of new technological innovations and their adoption on regime level, and 3) differentiated state support can develop demand for renewable products and is necessary for compensating extra costs for niche actors.

In recent decades, conventional intensive agricultural practices have led to serious non-point-source pollution in China and have imposed serious ecological threats to agroecosystems, especially in ecologically sensitive areas. The Middle Line of the South-to-North Water Diversion project, which covers one of the largest ecologically sensitive areas in China, began in December 2014. In the study area around the Danjiangkou Reservoir belonging to the Middle Line of the South-to-North Water Diversion project, organic farming has been encouraged instead of conventional farming. This study aimed to measure the difference in ecological safety between conventional and organic farming based on the ecological footprint combined with life cycle assessment, which integrated the assessments of carbon footprint (CF), water footprint (WF) and nitrogen footprint (NF). This paper hypothesized that the EF of organic farming in the target area would be lower than that of conventional farming because of the reduced chemical inputs. The results showed that, as expected, first, organic farming had a lower footprint with a higher ecological remainder than conventional farming in 2015, indicating that organic farming practices made greater contributions to regional ecological safety in the study area. Second, in conventional farming, the total grey water footprint (nitrogen, phosphorus pentoxide and potassium oxide) was much higher than that of the farms in which only nitrogen fertilizer were used, indicating that both phosphorus pentoxide and potassium oxide also play indispensable roles in water footprint evaluation. Third, the energy-related nitrogen footprint was greatest in organic farming, caused by higher diesel oil consumption due to greater farm size for mechanical operation. Finally, the methods of calculating the amount of ecological compensation were improved. According to reduced ecological footprints, an extra payment (CF = 115.17 CNY ha−1; WF = 0.09 CNY ha−1; NF = 102.20 CNY ha−1) for organic farming should be seriously considered by different stakeholders, due to its benefit to greater ecological safety. From the perspective of ecological footprints, ecological compensation policies for organic farming might effectively promote ecological safety in the South-to-North Water Diversion watershed in the future. Footprint, as an accounting tool, offers great potential in assessment of ecological safety and ecological compensation worldwide and needs to be further explored in more dimensions such as phosphorus footprint, biodiversity footprint and so on.

Pilot and industrial scale tests for the preparation of permeable bricks were carried out in a refractory plant. The permeable bricks were firstly prepared using 82wt.% ceramic waste large aggregate by pilot test. The permeability, flexural strength and apparent porosity of the obtained permeable bricks can reach 3.2×10-2 cm/s, 6.8 MPa and 28%, respectively, and the relationships between these properties were studied. Moreover, industrial scale test was performed based on the best conditions of the pilot test, and 100 permeable bricks having a size of 140 mm × 280 mm × 80 mm were successfully produced using 600 kg of raw materials. The produced permeable brick has a high permeability of 3.0×10-2 cm/s, flexural strength of 6.3 MPa, as well as a relatively high apparent porosity of 26%, which exceed Chinese national standard GB/T 25993-2010. It has been found that a large number of through holes are homogeneously distributed within the permeable brick, which ensures the high permeability. Meanwhile, the binders make the aggregates interconnect with each other, guaranteeing sufficient mechanical strength. In addition, the energy consumption for whole producing process of permeable bricks is relatively low, about 1.4 MJ/kg. Hence, it is completely feasible to achieve industrial production of permeable bricks with good performance by using solid waste, which not only contributes to the construction of the sponge city, but also meets the requirements of cleaner production and brings obvious ecological and economic benefits.

Eco-Industrial Parks (EIPs), network of industries that collaborate by utilizing each other's byproducts and wastes, are highly desirable for both the industries themselves, their environment, and governments due to their economic, environmental, and social advantages. Previous work has shown that EIPs are not as successful as they could be in terms of mimicking the behavior of biological ecosystems, highlighting that more work needs to be done for EIPs to truly mimic their biological-counterparts. The Kalundborg EIP, located in Kalundborg, Denmark, is a well documented example of an EIP with long-term success. Using the water network within the Kalundborg EIP as a case study, two bio-inspired networks are selected from an optimization based on the ecosystem metric robustness. The bio-inspired solutions are compared with a traditionally cost-minimized solution to understand what bio-inspired design can offer when a network is disturbed. Disturbances such as connection breakages and industry shutdowns are tested, showing that the bio-inspired designs require minimal recovery costs – in stark contrast to the traditional network solution. The results show that the bio-inspired designs reduce the network's dependence on a scarce import (freshwater) and have higher overall network resilience in the event of disturbances. The three network solutions are discussed from a ecological perspective, explaining differences from the standpoint of ecosystem characteristics. The analysis highlights the benefits of using ecology to understand the nature of and improve the design of industrial networks.

Respiratory dust and dust fall from the mechanized excavation faces of coal mines are crucial issues that require immediate attention. The dust fall technique for two-phase gas–water spraying is effective in solving these issues. We designed a spray dust fall simulated experimental system to test the dust fall efficiency for six grain sizes of water mist: D50 = 9.00 μm, 18.75 μm, 29.87 μm, 49.85 μm, 75.85 μm, and 116.47 μm, respectively. The results demonstrate that the smaller the D50 of the water mist particles, the better is the trapping effect of the respiratory dust. The main dust catching stage of water mist of different particle sizes is different. The main dust catching stage of water mist of small particle size is the initial contact stage of mist particles and respirable dust, while the main dust catching stage of water mist of large particle size appears later. The research findings will lay a theoretical groundwork for the application of new-type nozzle in the coal mines and provide technical support to the clean production of the coal mines.

The industrial energy recovery network has a large energy-saving potential. The retrofit of the original heat exchanger network (HEN) plays an important role in reducing energy consumption in existing process industries. However, a single economic or energy target is no longer sufficient to meet the retrofit needs of existing process industries. Therefore, an improved retrofit method that comprehensively considers many-objective is worthy of exploration. In this study, a many-objective optimization model with energy, economic, environmental and engineering quantity (4E) indexes for heat exchanger network retrofit is proposed, which avoids the one-sided analysis brought by single-objective optimization. The non-dominated sorting genetic algorithm based on reference point (NSGA-III) is applied to solve the proposed retrofit model. Three typical cases are used to verify and analyze the effectiveness and superiority of the proposed method. The case results show that the many-objective optimization method provides diverse retrofit options and flexibility to decision makers. Retrofit schemes with comparative energy, economic or environmental performance may take on notable difference in engineering quantity. Compared with the original networks, the retrofitted networks in the case studies can achieve a decrease in energy consumption up to 49.6%, a decrease in the total annual cost up to 22.2%, and a decrease in environmental impact up to 32.8%. Compared with the literature, the proposed method obtains optimization solutions with less energy consumption, capital cost, environmental impact and payback period.

The main objective of this paper is to propose a loan approval evaluation framework of public-private partnership project (PPP) of battery storage power station (BSPS) for the commercial bank to evaluate and select the optimal project to provide the loan and then promote the development of BSPS-PPP. In order to achieve this goal, this study proposed a loan approval evaluation index system which consist of 5 attributes, 14 criteria and 45 sub-criteria. The novelty of this loan evaluation index system is that it reflects the basic requirement of loan approval of the commercial bank based on the characteristics of BSPS and PPP project, the commercial banks can better prepare for possible risks of BSPS-PPP. The proposed decision model was established based on the interval-valued intuitionistic fuzzy value (IVIFV) and interval number. Its novelty is that ①The model not only satisfies the experts’ expression habit of uncertainty, but also can be handled the uncertainty in the performance evaluation value and the criteria’s weights properly;②the proposed weight determining method based on the deviation maximization principle can not only maintain the will of decision makers as much as possible, but also decrease the uncertainty of weights. Finally, the effectiveness of loan approval evaluation framework was verified based on a case study of China. According to the application effect of the evaluation index system and the proposed model, 3 managerial implication are put forward.

Although large firms have already begun addressing energy efficiency issues and adopting “cleaner” types of energy, companies with fewer resources, such as small and medium-sized enterprises, are more reluctant to implement these measures. Given that strategies leading to energy sustainability have become a key aspect of business competitiveness, decision makers in small and medium-sized enterprises could clearly benefit from a new approach that provides a better understanding of energy-change impacts on their business activities. The present study combined fuzzy cognitive mapping and the system dynamics approach to develop an informed, transparent model for use in analyses of energy-change effects on the sustainability of small and medium-sized enterprises. This dual methodology facilitated an examination of cause-and-effect relationships between decision criteria and the clarification of dynamic interactions between variables from a holistic, real-world perspective, thereby enriching the extant literature. The results of the proposed decision-support system were validated by two senior staff members of the Directorate for Energy Sustainability Services of Portugal’s Directorate General for Energy and Geology. The advantages, limitations, and implications of our constructivist, process-oriented framework for research and practice are also discussed.

Three kinds of turbines (Vestas V-47:660kW, Enercon E-40:600kW, Vestas V-66:1.75MW) were installed on three selected sites (Mailiao, Jhongtun, Chunfong) as wind power plants for electricity generation on an island. However, such power plants including turbines in establishment and operation during entire life cycle are bound to consume energy and produce carbon emission, causing environmental problems. Therefore, the purpose of the present study is to evaluate the effects of three wind power plants on the environment during their entire life cycle. This paper made the calculations of carbon emissions of three wind power plants, and compared and discussed the occupied shares of each primary energy input in manufacture, construction, operation and disposal phases using the methods of mathematics and materials input-output life cycle assessment. The results show that the CO2 emission factor of three systems was on average 3.9 g/kWh for the whole life cycle. The average CO2 emission intensity of all raw materials was 1.35 kg/kg. The occupied share of CO2 emissions in manufacturing, construction, and decommissioning phases was 44%, 16%, and 40% respectively. The primary energy input intensity was on average 0.0625 MJ/kWh of three systems for whole life cycle. The average energy input intensity of three systems was 21.48 MJ/kg. The combined CO2 emission intensity of all steel materials was 1.98 kg/kg. The demands for materials and energy inputs, and carbon emissions are positively related to the rated power value of a wind turbine. Wind power has a priority to produce clean energy, and can significantly decrease CO2 emissions.

The shortage of resources and environmental pollution have become the social issues of world concern, they have seriously affected the sustainable development. Remanufacturing has been recognized as an effective technology helps to improve the energy and materials utilization, and reduce environmental emissions with a low cost. we performed a comprehensive literature review of assessing energy, environment, and economy in remanufacturing based on life cycle assessment method to summarize the development of remanufacturing technologies, conclude new progress of remanufacturing in energy, environment and economy and review the remanufacturing trend. Firstly, we reviewed the life cycle assessment (LCA) method and its application in remanufacturing assessment. Some remanufacturing assessment methods based on LCA were analyzed here. Secondly, a framework of assessing energy, environment, and economy in remanufacturing based on LCA was built. Corresponding assessment methods in remanufacturing were studied and summarized in dimensions of energy, environment and economy respectively. Then following the integrated studies of energy-environment-economic assessment in remanufacturing was also described. In this paper, the remanufacturing and assessment about energy, environment, economy based on LCA were described systematically, so as to better understand and apply LCA and promote remanufacturing. Finally, the limitations of the LCA method were discussed, furthermore, in order to catch up with the trend of the manufacturing industry, the integration of remanufacturing and emerging technologies was proposed at the end of the paper, which will be conducive to the continuous innovation of remanufacturing.

Supported by preferential policies and government funding, the technological innovation of China's photovoltaic industry has been improved greatly. As a capital-intensive practice, will innovation activities in China's photovoltaic industry be affected by the continuous decline of government subsidies in recent years? Therefore, it is essential to study the relationship between government subsidies and innovation performance of Chinese photovoltaic industry. However, there is less empirical research on this topic. In this context, this study aims to supplement existing studies by proposing a micro-level perspective to measure the innovation performance based on the data of Chinese listed photovoltaic companies from 2012 to 2016. Moreover, we assess the effects of government subsidies and other influencing factors on innovation performance. The findings reveal that, firstly, the average innovation efficiency of Chinese listed photovoltaic companies is over 0.9, which is relatively high. Secondly, government subsidies make a positive influence on innovation performance. Thirdly, financial leverage and ownership concentration have significant positive impacts, while firm size has a significant negative effect on the innovation efficiency of China's photovoltaic industry. The findings will serve as a reference for policy-making to promote further technological progress and sustainable development of China's photovoltaic industry.

Current Account (CA) imbalances reveal the unequal Trade and Foreign Direct Investment (T&FDI) flows between various countries. This paper investigates the performance of the CA component of the Balance of Payments (BoP) of major advanced economies following the recent global financial and economic crisis (2013–2017) using a Data Envelopment Analysis (DEA) second-stage approach. Slack-based inefficiency (SBI) DEA models are proposed, using both a conventional perspective and a sustainability perspective that consider greenhouse gas (GHG) emissions as an undesirable output. The efficiency assessment aims to identify output slacks (i.e. exports and income inflows shortfalls) as well as input slacks (i.e. import and income outflows excesses). In the second stage, explanatory factors of the observed CA inefficiencies have been investigated, using regression models under frequentist and Bayesian frameworks. Although some differences exist between the Conventional and Sustainability scenarios regarding the negative effects of trade diversification and external debt and energy dependency on CA inefficiency, in both scenarios the results indicate links between CA inefficiency and geographical regions, socio-economic development and the burden of customs procedures.

In many inventory deterioration problems of real world, deterioration rate of some items may be affected by other adjacent items. Accordingly, the effect of deteriorated items on other items could be declined by removing them through inspection. In this sense, an inventory model for deteriorating items is introduced in this paper, considering the effect of inspection times during the replenishment period on average deterioration rate. Also, supplier is considered to impose some prepayments to the retailer. In the proposed model, the average deterioration rate is related to the number of inspections at each period. Likewise, to illustrate the uniqueness of the solution, the convexity of the model is proved. Moreover, the proposed model is validated by discussing and analyzing a case study in Iran through which noticeable results are achieved. The findings indicate that compared to previous models, the proposed model is superior in cost management.

Southern China is susceptible to urban heat island (UHI) effect due to the rapid urbanization and subtropical climate. However, comprehensively assessing long-term UHI and its driving factors across southern China remains elusive. In this study, we investigate the UHI effect and its relationship with several critical factors in the urban agglomerations of southern China from 2003 to 2015 using remotely sensed derived products and land surface Noah model outputs. Results indicate that (1) the UHI intensity (UHII) in southern China is 1.49 K with an increasing trend of 0.011 ± 0.004 K per year. This relates to the land cover changes caused by the urbanization, which explains ∼40% of UHII trend variance; (2) Resided in the subtropical maritime climate, UHII across southern China is closely related to two climate factors: solar radiation and precipitation. Specifically, the adverse impact of precipitation on UHII is significant across southern China, where sufficient rainfall can modify soil moisture condition and improve the thermal regulation of watershed; (3) Diurnal temperature range and surface net radiation that describes surface property cannot fully explain UHII across southern China. Nevertheless, variations of sensible flux and latent flux correlate better with UHII. The sensible flux (associated with aerodynamic roughness) is responsible for 32% of UHII while the latent flux (attributed to evaporation cooling) is responsible for 13% of UHII. This result underscores the substantial contribution of sensible flux on UHI. In addition, our study suggests the effect of anthropogenic intervention may could explain the inconsistent performances of heat fluxes in responding to UHI. Our findings highlight the significance of land-atmosphere controlling factors on UHI, which have practical implications for researching urban climate.

The underground disposal of drill cuttings waste is a common practice for the gas/oil industry to achieve zero-discharge sustainable development. In this study, a numerical modeling approach was developed to simulate the slurry flow for underground disposal of drill cuttings waste. The modeling approach was coupled with and implemented in the well-known general purpose subsurface multiphase flow simulator, TOUGH2. The new modeling approach treats the slurry flow behavior in subsurface systems as Bingham plastic liquid, with a linear relationship representing the yield stress and the concentration of the gelatinizer in the slurry. In addition, the precipitation-dissolution process was taken into account for solid-aqueous phase changes of the water-slurry mixture under and over the threshold pressure. The model has been verified by the analytical solution of a transient flow of single-phase Bingham fluid, and has further been tested by modeling field-scale injection of drill cutting wastes into a multi-layered geological formation in Texas. A hypothetical model has also been used to conduct sensitivity analysis of the impact of slurry density, injection depth and injection pattern on the storage formation performance. The results revealed that the effect of injection volume is greater than the mass on pressure buildup. In addition, a short period of intermittent reinjection can lead to an earlier formation breakdown due to particle sedimentation and reduce the storage capacity. The developed model can be used to evaluate the prediction of slurry transport, storage capacity, pressure distribution, and the formation breakdown time in a drill cuttings waste disposal project.

China is facing severe environmental problems, the total municipal solid waste (MSW) generation has dramatically increased and presented great challenges all over the country. Cities have different characteristics in MSW components, generation quantity, influencing factors and disposal ways. Beijing, Guangzhou and Lhasa of Beijing-Tianjin-Hebei economic circle, Pearl River Delta economic zone, and Qinghai-Tibet plateau regions were selected as representative cities, to compare and analyze the features, influencing factors to the MSW generation quantities, and its components by grey correlation analysis. Predictions of MSW generation quantities for Beijing, Guangzhou and Lhasa in 2025 would be 1251.22, 704.71 and 71.040 million tons, respectively, made by BP (back propagation) nerve work using MATLAB software. Results showed that the main indicators of influencing factors to MSW in three cities were all of economic development levels, population and investments of government input. Based on the analysis of internal relationship and characteristics of MSW, some barriers of MSW management were analyzed, and recommendations were given. Our study analyzed the influencing factors and forecasted quantities of MSW generation in representative cities in China, providing valuable evidences for the severe MSW disposal situation of different economic zones in China.

Environmental policy tools are an important means of improving environmental pollution and promoting regional green development. Working from a heterogeneous perspective, this study constructed a model using several different types of environmental policy tools and green innovation. Data from China's 30 provinces, spanning the period 1997 to 2014, was selected as the sample, and a multiple regression analysis and difference-in-differences model was used to analyze the data. The results showed that command-and-control type environmental policy tools had the most positive effect on innovations relating to end-of-pipe treatment and green products. By contrast, their effect on clean production technology lacked significance. Pollution charges played a positive role in promoting green process innovation, but a negative role in green product innovation. In addition, the overall effect of the emission trading mechanism was not significant. Despite this, the emission trading system that was independently implemented within some provinces was more successful than the system used within trial provinces that were identified and approved by the central government.

Pervious concrete using Steel Slag Aggregate (SSA) is a promising Low Impact Development (LID) and sustainable pavement material solution. This study investigated the enhancing mechanism using SSA instead of limestone in pervious concrete from the perspective of microscopic characterizations. Nanoindentation, Backscatter Electrons - Scanning Electron Microscope (BSE-SEM), and Energy Dispersive Spectroscopy (EDS) tests were conducted to obtain the micro-mechanical, micro-morphological and element composition of the interfacial transition zone (ITZ) and adjacent cement paste. The nanoindentation tests showed that the modulus and hardness of the ITZ in SSA pervious concrete were 44% and 68% higher than those of limestone concrete, and the contour plots showed that ITZ thickness of SSA pervious concrete was around 18 μm, narrower than the 25 μm thickness of limestone samples. The BSE-SEM tests showed that the ITZ of SSA pervious concrete had more hydration products and were more compacted. Specifically, denser flower-shape polyhedral crystals were observed, which was coalesced hydration products including calcium silica hydrates (CSH), calcium hydroxide (CH) and ettringite. The EDS results showed that not only were the contents of silicon and calcium in ITZ of SSA pervious concrete were higher, the silicon and calcium (S/C) ratio of SSA pervious concrete was also 42% higher, indicating that more CSH gel was formed. Based on the change of element composition, the estimated width of the ITZ in SSA pervious concrete was also smaller than that of the limestone sample. In all, the ITZ enhancing mechanism of using SSA includes improved strength, reduced width and densified structure.

Alkali activated geopolymer is an attractive solution to limit the adverse consequences of cement manufacturing. In this paper, an evaluation of environmental impacts of geopolymer containing fly ash and silica fume is conducted. Life cycle assessment is performed by benchmarking the environmental impacts of three geopolymer concrete mixes against the conventional cement concrete, namely: fly ash geopolymer (with hydroxide and silicate of sodium); fly ash–silica fume blend geopolymer (with hydroxide and silicate of sodium); and fly ash–silica fume blend geopolymer (with sodium hydroxide). Impact analysis is performed by using ReCiPe midpoint and endpoint methods in life cycle assessment software UMBERTO NXT using database of Ecoinvent 3.0. Sensitivity analysis is performed to determine the effect of transportation. One mix design for each concrete of equal water to binder ratio and 28-days compressive strength of more than 35 MPa is analyzed. Results of life cycle assessment indicate that alkaline activators and cement are the major sources of negative environmental impacts for geopolymer and cement concrete, respectively. Global warming potential of geopolymer concretes is lower than conventional cement concrete. Fly ash–silica fume geopolymer concrete activated without sodium silicate has lowest environmental impacts. Transportation of raw materials is found to increase the overall negative of all four concrete mixes. Cost reduction of 10.87% to 17.77% per unit volume is achieved with the use of fly ash – silica fume based geopolymer concrete. Sustainability in terms of cost and environmental benefits of geopolymer concrete can be further increased by using silica fume. It can be concluded that the use of fly ash – silica fume blended geopolymer in the construction industry has huge possibility to improve its sustainability. Furthermore, waste management can be effectively done by utilization of industrial by-products in concrete.

The supply of public charging infrastructure is insufficient to meet the charging demand of a large number of electric vehicles (EVs). Private charging pile sharing is an emerging solution to alleviate this imbalance. However, a reasonable price for charging pile sharing has not yet been determined. This study employs a non-cooperative game model to determine a charging pile sharing price considering EV consumers’ charging behaviors. First, a multi-logit model is constructed to measure the probability of EV consumers’ charging behavior choices. Then, a two-matrix game model is established between the private charging pile sharing and public charging mode. Using Beijing as a sample, the sharing rate and price strategies of private and public charging piles are calculated based on the proposed game model. The results show that the optimal sharing rate is 20.01% private charging pile sharing with 1.14 yuan/kWh and 79.99% public charging with 1.7946 yuan/kWh. Sensitivity analysis shows that economics is the most sensitive factor affecting the charging price of private charging pile sharing. Finally, policy recommendations are outlined to improve the private charging pile sharing rate and service efficiency, to broaden the charging options for EV consumers, reduce the construction of public charging piles, and save the government subsidy.

To recover diisopropyl ether (DIPE) and isopropyl alcohol (IPA) from industrial wastewater through extractive distillation (ED), the most suitable extrainer 1-ethyl-3-methylimidazolium acetate ([EMIM][OAc]) was screened out by comparing the selectivity of DIPE to IPA and IPA to water in ionic liquids (ILs) composed of 9 common cations and 12 common anions. Theoretical insight at the molecular level based on surface charge-density (σ-profiles) and excess enthalpy (HE) was provided to analyze the hydrogen bonding and separation mechanism between IL and the azeotrope. Isobaric vapor-liquid equilibrium (VLE) experiment of DIPE + IPA + [EMIM][OAc] and IPA + water + [EMIM][OAc] further validated the predicted results. After inputting the binary interaction parameters, the ternary ED configuration with [EMIM][OAc] as entrainer was simulated, and the thermal integration scheme was further explored. Comprehensive evaluation demonstrated that when compared to ethylene glycol (EG), the energy-integrated ED scheme with [EMIM][OAc] as entrainer saves energy consumption and the total annual cost (TAC) of 27.71% and 12.29%, respectively. This separation method provides a more energy-efficient and environmentally friendly choice for clean production of IPA.

The emergence of new sites for wind energy exploration in South Africa requires an accurate prediction of the potential power output of a typical utility-scale wind turbine in such areas. However, careful selection of data clustering technique is very essential as it has a significant impact on the accuracy of the prediction. Adaptive neurofuzzy inference system (ANFIS), both in its standalone and hybrid form has been applied in offline and online forecast in wind energy studies, though the effect of clustering techniques has not been reported despite its significance. Therefore, this study investigates the effect of the choice of clustering algorithm on the performance of a standalone ANFIS and ANFIS optimized with particle swarm optimization (PSO) technique using a synthetic wind turbine power output data of a potential site in the Eastern Cape, South Africa. In this study a wind resource map for the Eastern Cape province was developed. Also, autoregressive ANFIS models and their hybrids with PSO were developed. Each model was evaluated based on three clustering techniques (grid partitioning (GP), subtractive clustering (SC), and fuzzy c-means (FCM)). The gross wind power of the model wind turbine was estimated from the wind speed data collected from the potential site at 10minutes data resolution using Windographer software. The standalone and hybrid models were trained and tested with 70 % and 30 % of the dataset respectively. The performance of each clustering technique was compared for both standalone and PSO-ANFIS models using known statistical metrics. From our findings, ANFIS standalone model clustered with SC performed best among the standalone models with a root mean square error (RMSE) of 0.132, mean absolute percentage error (MAPE) of 30.94, a mean absolute deviation (MAD) of 0.077, relative mean bias error (rMBE) of 0.190 and variance accounted for (VAF) of 94.307. Also, PSO-ANFIS model clustered with SC technique performed the best among the three hybrid models with RMSE of 0.127, MAPE of 28.11, MAD of 0.078, rMBE of 0.190 and VAF of 94.311. The ANFIS-SC model recorded the lowest computational time of 30.23secs among the standalone models. However, the PSO-ANFIS-SC model recorded a computational time of 47.21secs. Based on our findings, a hybrid ANFIS model gives better forecast accuracy compared to the standalone model, though with a trade-off in the computational time. Since, the choice of clustering technique was observed to plays a vital role in the forecast accuracy of standalone and hybrid models, this study recommends SC technique for ANFIS modeling at both standalone and hybrid models.

The current energy and environmental target is the completely integration of the energy produced from different sources taking into account the renewables. The traditional power grids or thermal-cooling and heating conversion systems converge to the use of smart grids and to the planning of intelligent local organizations through energy integration techniques. This cannot be assessed as an isolated problem but an integrated one. The right construction of smart society is to match different challenges achieving sustainable energy systems not only from the point of view of energy consumption in different sectors (civil, industrial, agriculture, transport) and of the related of pollutants emissions, but considering simultaneously the relation with the socio-economic impact. The aim of this paper is firstly to examine the theories-approach to smart energy systems at the community level, the scientific literature of the smart energy community, the benefits of their potential applications in the smart energy municipalities. Finally, it manages the aspects related to smart energy community adoption with a multidisciplinary approach linking the technical conditions to the socio-economic systems of territorial planning. The main finding is that the concept of the intelligent energy community is strictly related to a coherent and intersectoral approach searching the best control strategy to satisfy all energy requirements. Moreover, the road leading to the smart energy community is essential to build the more sustainable renewable energy systems, to collect storage synergies between energy sub-sectors through the energy sharing and finally to exploit economically efficient sources.

Water quality management remains a challenge due to the complex interactions between multiple influencing factors. Although the influences of land use/cover types on water quality have received extensive attention, few researchers have attempted to elucidate the correlation between water body characteristics and water quality, and the interactions between water bodies and other land use/cover types on water quality have been relatively less studied. In this study, the southern Jiangsu Plain, eastern China, was taken as a study area, and the influence of water body area on water quality was investigated. The results revealed that all land use/cover types exhibited correlations with water quality, but their correlative directions and significance levels exhibited larger differences. The influences of different water body types on water quality were discrepant, and these influences all had spatial non-stationarity. The interactions between urban and dry lands and water bodies on water quality were bidirectionally weakened, and there was an inverted U-shaped relationship between water body area and water quality. The water body area could predict whether the water quality reached the standard of Class Ⅲ, and the appropriate cut-off values of the water body, rivers, and lakes were 10.65%, 9.33%, and 2.38%, respectively. These results suggested that water body area had a positive influence on water quality, and the loss of water bodies caused by the expansion of urban and dry lands created a double whammy on water quality; finally, water body area could effectively predict whether water quality reached a certain standard. Thus, maintaining a reasonable water body area contributes to managing water quality, and the proportion of water bodies can be a useful index for water quality management in downstream regions with dense river networks.

A consumer purchasing a car can benefit the environment by choosing a vehicle with lower emissions and higher fuel efficiency. In addition to emissions of CO2, Nitrogen oxide (NOx) emissions have serious implications for the environment and public health. Working with a national environmental protection agency, we conducted a consumer choice experiment with a representative sample (N = 95) of consumers. We tested whether choices were altered by (i) the introduction and presentation of a NOx tax and (ii) the presentation of fuel efficiency information. The results show that a NOx tax has the potential to shift consumer choices towards lower NOx-emitting vehicles, particularly if the tax is made salient. We extend previous research on partitioned prices by finding an effect of partitioning environmental taxes, although the largest impact on choices occurred when the amount of pollutant was made explicit. Consumers were more likely to choose fuel efficient cars when running costs were communicated as travel units per fixed cost of fuel than as cost of fuel per fixed unit of travel, though a manipulation of unit size had no effect. Overall, these findings imply that financial incentives and subtle presentational changes can alter consumer choices, with the potential to promote sustainable consumption.

During shutdown operations of chemical plants, significant amounts of raw materials, intermediates, and products may be flared leading to economic losses and emissions such as carbon dioxide, nitrogen oxides, and volatile organic compounds. Thus, flare minimization during plant shutdown is a desirable goal towards economic benefit and environmental sustainability. In this paper, a systematic flare minimization methodology for an olefin plant shutdown operation has been developed. It includes three iterative stages: (i) steady-state modeling and validation to build the foundation of the dynamic modeling; (ii) dynamic modeling and validation to enable plant-wide simulations under designated plant control strategies; and (iii) plant shutdown simulation and optimization to iteratively examine, validate, quantify various flare minimization opportunities so as to identify the improved shutdown strategy. Particularly, dynamic performances of the critical equipment (e.g., the cracked gas compressor) has been thoroughly investigated to ensure the operating safety associated with the developed new shutdown strategy. Compared with the conventional plant shutdown strategy, the case study has shown that the new development can significantly reduce flared raw materials and emissions by 90.23%, which result in estimated economic savings by 91.03% and the social cost of carbon saving by 90.37%.

In this study, the effects of metakaolin (MK), as a replacement for the Portland cement, in the ratios of 0%, 10% and 20% by cement weight and steel fiber (SF) dosages of 0%, 0.25%, 0.5%, and 1% by concrete volume were investigated on the microstructure, mechanical properties, durability and global warming potential (GWP) of concrete containing 25% volume percentage of crumb rubber replaced with natural fine aggregates at elevated temperatures. Several specimens were exposed to the high temperatures of 150, 300, 450 and 600 °C for an hour, and were then compared in terms of mass loss, compressive strength, ultrasonic pulse velocity (UPV), splitting tensile strength (STS), and impact resistance at the ambient temperature. The role of MK and SF on the concrete microstructure at high temperatures was investigated by scanning electron microscopy (SEM) and X-ray diffraction (XRD) analyses. The results show that not only does the combination of MK and SF improve the mechanical properties and durability of rubberized concrete at high temperatures, but it can also introduce more environmentally friendly mixes by reducing CO2 emissions, compared to a plain concrete mix.

Consumers play an important role in the market penetration of environmentally-friendly food packaging because it is they who decide whether or not to buy a particular product. The objective of this paper is to analyse the state of the art regarding consumers’ response to environmentally-friendly food packaging in order to identify existing barriers to purchase and potential measures to overcome these barriers. The paper is based on a systematic synthesis of 46 scientific journal articles on consumer studies related to environmentally-friendly packaging. The literature review applies a conceptual framework regarding the ways consumers respond to product stimuli and the psychological processes involved. Three important barriers to purchasing environmentally-friendly packaging are identified. First, consumers need guidance in recognizing environmentally-friendly packaging; for while consumers primarily consider the packaging material itself and any eco-labels, they also consider other packaging design elements such as colours and pictures of ‘nature’ that can be misleading. Second, it became obvious that consumers lack knowledge, in particular about new packaging materials like bio-based packaging. Third, many of the studies reviewed provide evidence that other product attributes such as price and product quality are more important to consumers than environmentally-friendly packaging. Nevertheless, some studies recorded a significantly higher willingness on the part of consumers to buy and pay for environmentally-friendly packaging and products with reduced packaging compared to products with standard packaging, signalling an overall positive attitude. The literature review revealed many research gaps. For example, it became obvious that consumers’ response to environmentally-friendly food packaging is not yet well understood, in particular with regards to purchasing behaviour (in the real world as opposed to in a survey setting) and measures for overcoming existing barriers.

In this work, a new model of air to air heat pump (AAHP) using industrial continuous heat treatment furnace (ICHTF) that runs by wind generation and solar Stirling engine are presented. The suggested approach for making fire includes an internal and an external airflow fans, extension valve, compressor, condenser, and evaporator to provide energy with temperature higher than 1000 K for thermal demands. While the combustion reactions is happening, AAHP does not provide thermal energy; it is moved from the environment to furnace section. Accordingly, application of wind, solar and AAHP not only decreases the emission and ozone depleting substances, but also significantly rises the saving rate in electricity and petroleum products consumptions. The paper presents a mathematical approach, that utilizes energy and exergy, which is used for modeling the suggested ICHTF in presence of green energy, e.g. solar, wind and air. The proposed method is compared with different optimization algorithms. In addition, a robust periodic optimization technique for economic issues is presented for minimization of the overall energy supplement costs utilizing the predicted wind velocity as the problem input and considering the higher and lower bounds of wind energy for simulating wind volatility. Obtained results proof the validity of proposed model.

Food waste is a problem for which solutions are recognised but not readily put into practice. What should be the primary objective, reducing or eliminating surplus food production, requires great change within social, cultural and economic structures. The secondary approach of redistributing surplus food to areas of deficit (in terms of socio-economic groups and/or geographic regions) involves a significant logistical burden, and suffers the same issues as with the elimination of waste. The least desirable, but perhaps most practicable approach, is the use of food waste as a feedstock for Anaerobic Digestion (AD). The strategic adoption of AD can therefore be seen as an important step towards mitigating food waste, but the implementation of efficient AD systems on a large (county/region) scale involves significant complexity. The optimal number, size and location of AD plants, and whether they are centralised versus decentralised, may be determined by considering factors such as supply and proximity to feedstock, transport links, emission hazards and social impact. Reaching balanced and objective decisions when faced with such disparate criteria is inevitably very difficult. To address this problem we prototype and evaluate a decision support tool for county-scale AD planning. Our approach is a hybridised Agent Based Model (ABM) with a Multi Objective Optimisation. We capture the spatio-temporal dependencies that exist in the water, energy and food systems associated with energy derived from food waste using Agent Based Modelling (ABM). The use of Interactive Multi Criteria Analysis as visual analytics offers a means to communicate the co-benefits and trade-offs that may emerge, as well as prioritise the AD strategies, based on the weighting of criteria. Specifically, the method supports exploration of the social, environmental and economic impact of different AD strategies and decisions, linked to current issues, namely AD scale and adoption. The results highlight a trade-off between transport costs and social acceptability for the AD centralised versus decentralised strategies. When low carbon options are weighted higher then slow, steady and aggressive decentralised strategies are the best strategic adoption of AD. Conversely, when Energy production is considered with a greater weighting, then aggressive scaling up in a centralised approach is best with slow and steady approaches being further from the ideal. The framework has demonstrated that it permits a space for dialogue and transparent prioritization of AD strategies based on WEF nexus impacts.

In the frame of the water circular economy, the reuse of the treated sewage sludge supposes a good action. Nevertheless, the reuse might suppose a human health risk because of the presence of pathogen germs, concentrated in the generated sludge during urban wastewater treatment. For this reason, sludge treatments, conventional or advanced, should be focused on the reduction of fermentation capacity and microorganisms presence. This research assess the microbiological quality of the treated sludge, based on the use of faecal pollution indicators such as total coliforms, Escherichia coli, Enterococcus sp., Pseudomonas sp.¸ Staphylococcus aureus and total mesophilic bacteria, after the application of different digestion treatments, and their final aptitude to be reused. Three different pilot scale plants were used: two anaerobic digestion plants with a volume of 2.75 m3 working in mesophilic (35-37 °C) and thermophilic (55-57 °C) conditions, and hydraulic retention times (HRT) ranging from 5 to 20 days; and a autothermal thermophilic aerobic digestion plant (ATAD) with a volume of treatment of 3.9 m3 working at 55-57 °C for an HRT of 5–15 days. The raw sludge to be treated came from a full-operative WWTP located in the region of Navarra (Spain), laid within Ebro River Basin. It was concluded that both treatments studied obeyed the current European legislation in therms of E. coli concentration and absence of Salmonella spp., being available for agricultural purposes. Considering other microbiological parameters, the anaerobic thermophilic treatment had the best conditions to reduce the Enterococcus sp. concentrations and the aerobic thermophilic treatment was the best one reducing E. coli, being non-significant the influence of HRT to microbial reduction. For this reason, it is strongly recommended the use of both faecal indicators to assess the microbial quality of the treated sludge.

There is currently no consensus on the relationship between environmental regulation and enterprise innovation. Moreover, empirical studies on this topic have generally been based on government indirect environmental regulation data. To examine this relationship further, this study uses government direct environmental regulation (GDER) data. Here, enterprise innovation is measured by innovation investment. Additionally, innovation investment is divided into two stages, a research stage and a development stage, to explore the effect of GDER on heterogeneous innovation investment. Furthermore, this study examines the impact of executive compensation on GDER and innovation investment, specifically looking at the two stages of innovation investment. The results indicate that GDER has a negative impact on heterogeneous innovation investment and executive compensation has different moderating effects: strengthening the negative relationship between GDER and research investment, while weakening the negative relationship between GDER and development investment. This study offers new insights into the relationship between environmental regulation and enterprise innovation considering the impact of executive compensation.

In this paper, the Multi-Layer Perceptron (MLP) neural network is optimized with two metaheuristic algorithms, namely Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) for estimating the heating load (HL) and cooling load (CL) of the energy efficient buildings with the residential use. To achieve this, a dataset composed of eight independent factors namely, relative compactness, surface area, wall area, roof area, overall height, orientation, glazing area, glazing area distribution, along with the two dependent variables of HL and CL is provided. Out of 768 samples, 80:20 ratio is considered to select the training and testing datasets randomly. Through a trial and error process, the optimal parameters of the MLP, ABC-MLP and PSO-MLP networks are determined. Three well-known criteria including coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE) are utilized to measure the accuracy of the used models. The results reveal that applying the ABC and PSO algorithms, helps the MLP to perform more efficiently. In this sense, the increase of R2 from 0.8933 to 0.9349 and 0.9370 for the HL, and from 0.8872 to 0.8969 and 0.8997 for the CL prediction show that the outputs of the ensemble models (i.e., ABC-MLP and PSO-MLP) are more correlated with the actual data. Also, the MAE decreases as 22.32% and 24.28% for the HL, and 10.36% and 12.00% for the CL respectively by applying the ABC and PSO. Besides, the RSME decreases as 22.48% and 23.86% for the HL, and 6.06% and 7.56% for the CL modeling respectively with using the ABC and PSO. It is also deduced that the PSO outperforms the ABC in the performance enhancement of the MLP.

To address the environmental problems caused by solid waste while promoting the sustainable development of mines, gangue and fly ash can be used as underground backfill materials to achieve the comprehensive utilisation of solid waste mining resources. We measured the compressive deformation characteristics of samples with different ratios of gangue to fly ash and analysed their stress-strain relationship and associated changes in their porosities using a YAS-5000 servo testing machine and a homemade compression apparatus. Moreover, we revealed the mechanisms of deformation resistance of gangue and fly ash from both a macro and meso perspective and determined that the optimal ratio of gangue to fly ash is 0.35. In addition, taking the backfill face in Coal Mine as an example, mixed materials of gangue and fly ash at a ratio of 1:0.35 were backfilled into a goaf. After mining of the working face, the surface only sank by 170 mm approximately. This method not only effectively disposes of solid wastes, i.e., gangue and fly ash, on a large scale but also controls surface subsidence to protect adjacent buildings and structures. Therefore, the coordinated development of coal resource mining and environmental protection are realised.

Green development competitiveness plays an active role inthe construction of ecological civilization. This researchbuilds a green development competitiveness index system, and measures the competitiveness level of 30 sample provinces in Chinafrom 2003 to 2016 before testing the convergence tendency. It is found that the comprehensive competitiveness of green development in China developed steadily from 2003 to 2016, with the eastern region valuedthe highest, followed by the northeastern, central and western region. The five aspects of evaluation index system for green development competitiveness showed different development tendencies:the competitiveness of green high-quality growth and that of resource conservation and emission reduction sawa steady increase; the competitiveness of urban ecological environment quality and that of green lifestyle remained relatively stable, while the competitiveness of green investment declined slightly. Analysis of regional difference showed that the varying degree of western China was larger than that of eastern, central and northeastern China in order. Besides, the varying degree is becoming larger in eastern and northeastern regions while becoming lower in central and western regions. Convergence analysis showed that from 2003 to 2016, competitiveness level differed from region to region and there were no obvious signs of stochastic convergence at the national level. At the regional level, it can be found that the evaluation values of the eastern region saw stochastic dispersion from the national average. Only four provinces of Henan, Hubei, Guizhou, and Yunnan had possibilities of stochastic convergence to the regional average.

With large-scale urbanization and dramatic economic development, the deterioration of urban ecological pollution and excessive consumption of resources in Chinese cities have turned into serious challenges. Due to the lack of resources and environment protection, natural assets are become increasingly scarce. In order to achieve sustainable urbanization, it is important to improve the well-being of urban residents within the restricted ecological resources. Ecological well-being performance (EWP) reflects the trends in well-being level and ecological consumption. In order to evaluate urban EWP, an index system is established in the perspective of input-output. After that, a case study of 30 provincial capital cities in China from 2011 to 2016 is presented, in which the Super-slack-based measure model (Super-SBM) is utilized. The results show that (1) the average EWP value of 30 provincial capital cities was low with the value of 0.89, but it has an overall improvement during 2011-2016; (2) the average EWP of Haikou was the highest, followed by Changsha and Beijing, while the bottom three EWP performers were Urumqi, Lanzhou and Xining; (3) spatially, capital cities in east and central regional provinces of China ranked first and second, while the capital cities in the northeast and west regions were ranked third and fourth according to the EWPs, respectively. In order to improve the EWP for 30 provincial capital cities, policy suggestions are proposed to make urban well-being improvement more ecologically efficient. The results from this study will provide valuable guidance to urban managers for designing and taking effective steps, allowing the Chinese cities to progress towards sustainable urban development.

Bike-sharing systems have rapidly expanded around the world. Previous studies found that docked and dockless bike-sharing systems are different in terms of user demand and travel characteristics. However, their usage regularity and its determinants have not been fully understood. This research aims to fill this gap by exploring smart card data of a docked bike-sharing scheme and GPS trajectory data of a dockless bike-sharing scheme in Nanjing, China, over the same period. Both docked and dockless bike-sharing users can be classified into regular users and occasional users according to their usage frequency. Two systems are cross-compared regarding their travel characteristics. Then, binary logistic models are applied to reveal the impacts of travel characteristics and built environment factors on the regularity of bike-sharing usage. Results show that for both bike-sharing systems, regular users and occasional users share similar riding time and distance, while significant differences in the spatio-temporal distribution between docked and dockless bike-sharing systems are observed. The regression model results show that the “Trips during morning and afternoon peak hours” are positively associated with the regularity of both docked and dockless bike-sharing usage. However, the “Riding distance” variable is negatively associated with the usage regularity of both systems. Built environment factors including working point of interest (POI), residential POI, and transit POI promote the usage regularity of both bike-sharing systems. Finally, policy implications are proposed, such as increasing the density of docking stations in suburban areas and developing high-quality parking area for dockless bike-sharing around public transport stations. This study can help operators or governments to launch or improve the service of bike-sharing systems.

The integration of a large number of wind farms poses big challenges to the secure and economical operation of power systems, and ultra-short-term wind power forecasting is an effective solution. However, traditional approaches can only predict an individual wind farm power at a time and ignore the spatio-temporal correlation of wind farms. In this paper, a novel ultra-short-term forecasting framework based on spatio-temporal (ST) analysis, multi-output support vector machine (MSVM) and grey wolf optimizer (GWO) which defined ST-GWO-MSVM model is proposed to predict the output wind power from multiple wind farms; the ST-GWO-MSVM model includes data analysis stage, parameters optimization stage, and modeling stage. In the data analysis stage, the person correlation coefficient and partial autocorrelation function are used to analyze the spatio-temporal correlation of wind power. In the parameters optimization stage, to avoid obtaining the unreliable forecasting results due to the parameters are chosen empirically, the GWO algorithm is used to optimize the kernel function parameters of the MSVM model. In the modeling stage, an innovative forecasting model with optimal parameter of MSVM is proposed to predict the output wind power of 15 wind farms. Results show that the performance of ST-GWO-MSVM is better than other benchmark models in terms of multiple-error metrics including fractional bias, direction accuracy, and improvement percentages.

An important concern in the mining industry is to reduce greenhouse gas (GHG) emissions across all their processes in the supply chain (SC). A good supply chain network design (SCND) involving environmental strategic challenges allows dealing with this problem. Since the literature about SCND in the mining industry is scarce, in this paper we address a multi-echelon, multi-period and multi-product environmental mining SCND with the objective to reduce GHG emissions under Emissions Trading Scheme (ETS), along with minimizing investment, transportation, operating costs and carbon credits costs resulting by ETS. To solve this problem, we propose a mixed integer linear programming model that considers the location of capacitated facilities in the SC, addressing specific mining problems related to the ore grade available in mining fronts and the customer demand satisfaction in terms of quality and quantity, through additional processes such as blending and beneficiation that occurs along the several echelons of the mining SC. Our model integrates, for the first time the environmental impacts of ore grade on the mining SCND. Taking a base case inspired in a iron ore mining real-world scenario, several instances were generated to validate the proposed model. The results suggested that when the ore grade is included in the SC design, different configurations with direct effects on costs and emissions of equivalent carbon dioxide are obtained; in addition, the ETS showed to be a valid option for reducing both costs and the environmental impact along the SC. Finally, we analyze the environmental and economic impact in front of ore grade and carbon credit price variations to find managerial insights that can help decision-makers in this sector.

Concentrations of building mass and insufficient greenery in cities are identified to contribute significantly to extended heat stress in the built environment, commonly known as the urban heat island (UHI) effect. This paper presents a scenario-based modelling based on climate change projections and potential changes in urban greenery in 2030 and 2090 in Adelaide. The model is based on regional climate change scenarios, potential urban surface cover alternatives and resulted urban microclimate variations in Adelaide, South Australia. Projected energy demand variations and corresponding carbon emission are calculated in each scenario. Results indicate that an ideal urban landscape transformation scenario with 30% tree canopy can effectively decrease the surface temperature by 1°C in winter and 3°C in summer by 2090. It is estimated that having greener and more heat resilient public spaces could save a total carbon emission of 140,000 tone CO2e in Adelaide annually compared to a business-as-usual scenario. Urban greenery may be used as a mean of increased urban life resilience to climate change by reducing surface temperature, increasing urban resilience and decreasing the energy demand during summer.