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The pulp and paper industry accounts for approximately 5% of total industrial energy consumption and contributes 2% of direct carbon dioxide (CO 2 ) emissions from industries. World paper and paperboard demand and production are increasing significantly, leading to an increase in this sector's energy use and CO 2 emissions. Although current studies identify a wide range of energy-efficiency technologies that have already been commercialized for the pulp and paper industry, information is limited or scattered regarding new energy-efficiency technologies that are not yet fully commercialized. Development of emerging or advanced energy-efficiency technologies and their deployment in the market will be crucial for this industry's mid- and long-term energy saving and climate change mitigation strategies. This paper compiles available information on energy savings, environmental and other benefits, costs, and commercialization status for 25 emerging technologies to reduce the energy use and CO 2 emissions. The purpose is to provide a well-structured comprehensive review on these emerging energy-efficiency technologies for engineers, researchers, investors, policy makers, pulp and/or paper companies, and other interested parties. [ABSTRACT FROM AUTHOR]

The increasing presence of e-books (electronic books) has become a major focus in countries around the world. In the United States, e-books represented 28% of the total book sales for 2012. In Japan, the conversion from paper books to e-books is expected to accelerate by the prevalent use of smartphones and tablet PCs. It is therefore important to quantitatively evaluate the environmental load of paper books and e-books for a sustainable society. In this study, paper books are compared to e-books read on different electronic devices (e-ink tablets, tablets, cell phones, smartphones, laptop computers, desktop computers and portable music players) through a case study on a 224-page book. The study is based on key primary data such as use time and reading speed for each device and aims to minimize assumptions made in other studies. GHG emissions for paper books are 1.24 kg-CO 2 e/book, and are reduced to 1.11 kg-CO 2 e/book when the effect of paper recycling is taken into consideration. The results for e-books under average use-time conditions range from 0.25 to 0.91 kg-CO 2 e/book with the e-ink tablet having the lowest emissions. When the average use time of each e-book device is applied, the paper book has a higher impact than all the e-books. However, sensitivity analysis shows that the impact of paper books can be lower than that of e-books for larger screen devices such as tablets, laptops and desktops when the reuse of books is considered or the e-book reading device is hardly used during its life cycle. [ABSTRACT FROM AUTHOR]

A simple framework to estimate the potential of solar industrial process heating (SIPH) and corresponding CO 2 emissions mitigation in paper industry in India is presented. Geographical locations with clusters of paper mills have been identified and the annual process heating requirement for paper production (based on raw material use) at each cluster has been estimated. The total process heating potential for the paper industry in India has been estimated at 25.2 PJ/annum. Using the estimated performance of a commercially available parabolic trough based SIPH system with collector area requirement of 1.11 million m 2 annual solar fraction in the range of 0.25–0.30 have been estimated. Annual energy delivery of SIPH systems estimated at 4.34 PJ per annum. Finally at 8 main locations with clusters of paper mills in India considered in this study, adoption of SIPH without storage is expected to mitigate 0.34 million tonnes of CO 2 emissions annually. [ABSTRACT FROM AUTHOR]

Compared to cast-in-situ construction, prefabricated construction reduces the generation of construction waste; however, construction waste cannot be entirely eliminated through prefabrication and can be generated at each stage of its life cycle. This paper generates a system dynamics model, comprising two causal-loop diagrams and one stock-flow diagram, to simulate the effectiveness of policies on decarbonizing prefabricated concrete building waste. The model can predict the annual and total construction waste, along with the associated carbon emissions, under different policy scenarios in China by 2030. This paper focuses on prefabricated concrete buildings in China, with specific attention to the wastage of concrete, bricks, mortar, and metal. In single-factor scenario simulations, increasing landfilling fee is the most effective policy for waste decarbonization, potentially reducing carbon emissions by 31%. Increasing prefabrication rate and enhancing regulation degree at the design phase of prefabrication can directly reduce prefabricated building waste generation, subsequently resulting in an 18% and 7% carbon emissions reduction. Multi-factor scenario simulations demonstrate that the simultaneous application of all four policies is most effective, achieving a 44% reduction in carbon emissions. This research establishes a theoretical framework for prefabricated concrete building waste management and provides the Chinese government with practical insights on optimizing policies for waste decarbonization in the dynamic landscape of prefabrication. • This paper develops the prefabricated building waste generation and disposal systems. • The model predicts the construction waste and associated carbon emissions by 2030. • Raising landfill fee is an effective policy for decarbonizing construction waste by 31.06%. • Prefabrication rate reaching 100% can reduce 18.04% of carbon emissions from waste. • Applying all policies is most effective, achieving a 44.34% carbon emissions reduction. [ABSTRACT FROM AUTHOR]

This paper investigates the potential benefits of integrating rooftop greenhouses (RTGs) with buildings to reduce energy and CO 2 costs, contributing to urban decarbonization efforts. This integration not only advances sustainable urban agriculture but also aligns with the United Nations Sustainable Development Goal 7 (SDG7) - Affordable and Clean Energy, and Sustainable Development Goal 11 (SDG11) - Sustainable Cities and Communities, through its energy-efficient, low-carbon approach. We hypothesize that this integration can significantly lower energy use in integrated RTGs (i-RTGs) and set out to validate this through dynamic models for both building and i-RTG climates, focusing on CO 2 concentration, humidity, and temperature. Central to our approach is the implementation of a nonlinear model predictive control (NMPC) framework, which utilizes these dynamic models to make control decisions aimed at minimizing total control costs. This framework operates in a receding horizon procedure, regulating climate factors within the i-RTG and building using various actuators. We validate our approach by simulating an i-RTG atop a building in eleven different cities, demonstrating interactions such as energy, moisture, and CO 2 exchange. Significantly, our study reveals that integrating i-RTG with buildings under the NMPC framework leads to a 15.2% reduction in control costs. Additionally, we find that the i-RTG model is adaptable to different climates, with colder regions showing greater cost reduction potential. Our study underscores the viability and advantages of integrating i-RTGs with buildings, offering a sustainable, decarbonizing solution for urban agriculture and building management that contributes to the fulfillment of SDG7 and SDG11. • Nonlinear model predictive control framework for integrated rooftop greenhouse. • Energy transfer between rooftop greenhouse and host building minimizes energy costs. • A case study on a building-integrated rooftop greenhouse in eleven different cities. • Proposed control framework lowers costs and ensure safety for crops and occupants. [ABSTRACT FROM AUTHOR]

The chemical industry is one of the fundamental industries of economic development. Coordinating the relationship between economic growth and carbon emissions (EGCE) is crucial in realizing the carbon neutrality target. The Tapio model and decomposition models are used to assess the degree of decoupling within the Chinese chemical industry and identify pivotal factors impeding progress. The energy efficiency decomposition model explores the crux of failure to achieve strong decoupling. This framework further decomposed the energy intensity to uncover how technical efficiency, technological progress, and input substitution changes affect energy intensity and CO 2 emission. The paper found that the EGCE of the chemical industry were stable in a weak decoupling mode from 2009 to 2019. The reliance on technological progress to reduce energy intensity and emissions is insufficient (accounting for only 18.2%), far below the cumulative contribution from economic growth (accounting for 57.76%), which has become the crux of the strong decoupling failure. Technological advancements drive energy substitution for labour, resulting in 244.41 Mt of cumulative carbon emissions. The improper factor input allocation hinders the desired reduction in energy intensity and carbon emissions. A series of policy implications are proposed based on the insights derived from the decomposition analysis to foster sustainable practices in the chemical industry. [Display omitted] • This study focuses on the decoupling in chemical industry. • The decoupling between economic growth and carbon emissions (EGCE) is explored. • The reasons for the failure of strong decoupling from technical perspective are tested. • The decoupling between EGCE of chemical industry was in a weak decoupling mode. • Technological progress accelerated the substitution of energy for labour. [ABSTRACT FROM AUTHOR]

This paper proposes a directionality framework that highlights goal, sector and solution as key dimensions of transformative policy missions. The framework is used to investigate the directionality of process industry decarbonization in Sweden, by analyzing the orientation of projects supported by the major national funding program the 'Industry Leap' between 2017 and 2022. The results show that innovation activities (i) mainly aim to reduce fossil emissions rather than produce negative emissions, (ii) focus on the steel and chemicals industries, and (iii) engage mostly with carbon capture, electrification and hydrogen. This indicates that innovation activities are somewhat narrow and imbalanced, which suggests that policymakers should promote broader experimentation. The theoretical and empirical contribution of this paper supports academics, policymakers and other actors in understanding, evaluating and shaping the directionality of transformative policy missions. [Display omitted] • Transformative policy missions unfold in goal, sector and solution dimensions. • The directionality of process industry decarbonization in Sweden is analyzed. • Innovation activities focus on decarbonizing steel and chemicals production. • Carbon capture, electrification and hydrogen are the main solution pathways. • Swedish policymakers should promote broader experimentation. [ABSTRACT FROM AUTHOR]

As a significant source of carbon emissions, road logistics operators are under increasing pressure from governments and customers to find ways to decarbonize as part of broader global efforts to reach net zero. Decarbonization of road logistics relies on the widespread diffusion of existing and emerging technological transport solutions. These include alternative fuel vehicles, battery technologies, renewable energy and charging solutions. All promise to reduce carbon emissions, but their implementation remains challenging, expensive, and risky. As early adopters of alternative fuel vehicles have reported, transitioning from fossil fuels poses challenges that must be prepared for and understood to minimize the obstacles to genuine emissions reductions in road logistics. A considerable volume of academic research has been published advocating emission reduction solutions and providing detailed analyses of their potential positive environmental impacts. However, to our knowledge, no frameworks integrate these analyses with practical insights into current and anticipated challenges for road logistics operators transitioning from fossil fuels to a decarbonized future. This paper analyses contemporary evidence and insights on current and future issues and presents an integrated framework for road freight logistics decarbonization challenges. The framework primarily focuses on decarbonization through alternative fuels and analyses three categories of challenges from socio-technical, economic, and environmental perspectives. The three categories of challenges relate to alternative fuel vehicles and fleets, alternative fuel distribution infrastructure and renewable energy generation. The underlying principle of the framework is to provide a practical tool that supports a more informed view of both the advantages and challenges of transitioning to alternative fuels. This research contributes to the body of knowledge by providing a framework to help direct future research into tackling these logistics decarbonization challenges. The insights presented in this paper may also inform practitioners by sensitizing them to potential roadblocks in the transition away from fossil fuels. • Framework integrating road freight logistics decarbonization challenges. • Analyse alternative fuels, alternative fuel distribution and renewable energy. • Three perspectives on decarbonization: socio-technical, economic, and environmental. • Highlight logistics services provider strategies to minimize risk and uncertainty. [ABSTRACT FROM AUTHOR]

Innovative emission reduction technologies combined with optimized processes can effectively reduce the environmental pressure in the iron and steel industry (ISI). Identifying and comparatively analyzing the carbon emissions (CE) from steel productions is conducive to achieving China's ambitious carbon reduction targets. In this paper, we investigated two innovative routes: the shaft furnace-induction furnace-basic oxygen furnace route (SF-IF-BOF) and shaft furnace-electric smelting furnace-basic oxygen furnace route (SF-ESF-BOF), alongside two traditional routes: the blast furnace-BOF route (BF-BOF) and SF-electric arc furnace route (SF-ESF). The analysis was based on a functional unit of 1000 kg of crude steel (CS). By establishing the mass and energy balance models and decision criteria, 12 typical smelting scenarios for these routes were analyzed and compared in terms of materials consumption and CE. The results showed that increasing the proportion of scrap was beneficial for reducing CE. Under the condition of a 50% scrap ratio, the CE of the SF-IF-BOF, SF-ESF-BOF, BF-BOF, and SF-EAF routes were 768, 823, 946, and 870 kg, respectively. The SF-IF-BOF route displayed the most significant advantage of CE reduction. In addition, by using 100% zero-carbon electricity substitution, the SF-EAF route exhibited the greatest CE reduction effect of 41% (from 870 to 510 kg/t). While deploying 100% biomass fuels to replace coal, the CE of the BF-BOF route reduced by 80%. Finally, after introducing biomass fuels and zero-carbon electricity, the CE of the SF-IF-BOF route was minimized to a significantly low 13 kg/t (from 768), nearing zero CE. This research is expected to provide a novel solution for further CE reduction in the future of ISI, contributing to environmental sustainability and carbon reduction goals. • Suggestions for solutions to reduce CO2 emissions in the steel industry are provided. • Emissions of the SF-IF-BOF and SF-ESF-BOF compared to the BF-BOF and DRI-EAF routes. • DRI is considered to be generated using COG zero reforming process. • Using zero-C electricity and biomass can reduce CO2 emissions for the steel industry. [ABSTRACT FROM AUTHOR]

The power sector significantly contributes to global greenhouse gas emissions, making its transition to low-carbon energy crucial for achieving carbon neutrality. Zhengzhou, recognized as one of the China's "National Central Cities", has a high energy demand. Its power sector, which is primarily reliant on coal, is responsible for half of the city's CO 2 emissions. The low emissions analysis platform (LEAP) model serves as an effective tool for exploring the power sector's transition to low-carbon sources. However, studies on the combined reduction in air pollutants and CO 2 at the city level are scarce. This study focuses on Zhengzhou's power sector, examining the power composition, coal usage, CO 2 and air pollutant emissions, social costs, and employment effects across five scenarios using LEAP. The five scenarios are the business-as-usual scenario, the reference scenario, the carbon neutrality scenario, and two optimization scenarios with different carbon peak and carbon neutrality time. CO 2 emissions will peak in 2030 at 34.6 Mt in the reference scenario, and in 2022 at 32.4 Mt in the carbon neutrality scenario. Emissions in the reference and carbon neutrality scenarios will decrease by 64.8% and 75.2%, respectively, from those in the business-as-usual scenario due to emission reduction strategies. In the carbon neutrality scenario, coal power reformation is the most significant measure, accounting for 45.7% of the total CO 2 reduction compared to that in the business-as-usual scenario, followed by the integration of external electricity (17.8%) and solar energy (13.6%). This scenario also demonstrated a strong synergistic effect on reducing air pollutants and CO 2 emissions. Although the carbon neutrality scenario incurs costs 60.4 billion yuan higher than those of the reference scenario, its CO 2 mitigation cost is 66.1 yuan/t lower. This indicated that more rapid CO 2 reduction, despite higher economic inputs, is justified by ambitious CO 2 reduction goals and environmental benefits. Enhancing the use of renewable energy technologies for research and development to lower costs could increase the economic feasibility of the carbon neutrality scenario. In the two optimization scenarios, complete elimination of CO 2 and air pollutant emissions is achieved by 2060, with all the electricity generated from renewable sources, although issues of uncertainty and stability need to be addressed. The study also highlights that renewable energy development will significantly boost employment, with an estimated 1.19 million jobs in 2060 in the carbon neutrality scenario. Finally, the paper concludes with a sensitivity analysis and offers policy recommendations for the power sector's low-carbon transition. [Display omitted] • Low-carbon transition paths of Zhengzhou power sector are investigated by scenario analysis. • Coal power reformation and external electricity are effective measures for CO 2 reduction. • Synergistic reduction of air pollutants and CO 2 is achieved in the CAN scenario. • The CAN scenario has a good cost-effectiveness of CO 2 mitigation. • Policy recommendations for Zhengzhou power sector are proposed. [ABSTRACT FROM AUTHOR]

The quest for sustainability and reduction of human impact on the planet has led to discussions about environmental efficiency in the manufacture and use of automotive vehicles. The advancement of environmental and government laws has encouraged the automotive industry to seek constant improvements in safety, fuel economy and reduction of greenhouse gas emissions. To achieve these goals, reducing the weight of vehicles has been considered a relevant strategy, with several research and development efforts in search of high-tech materials and innovative design. The assessment of the life cycle of vehicles, from the extraction of raw materials to the end of their useful life, is essential for estimating environmental impacts. In this context, this paper focuses on the life cycle analysis of vehicles with new generation steel structures (Body in White Solution) compared to current steels (Body in White Baseline), aiming at reducing greenhouse gas emissions by reducing of the thickness of the steel plates, maintaining the mechanical properties necessary to guarantee the safety of the vehicle. The methodology of this study was divided into the evaluation of Body in White (BIW) mass in current steels (Baseline) and in advanced high resistance steels (Solution); detailing the vehicular life cycle from the extraction of materials to its end of life; in the estimation of greenhouse gas emissions through simulation and in the comparison of vehicle emissions with BIW in current steels and in advanced high resistance steels. As a result, it was possible to observe that, in the comparison of the CO 2 footprint, modeled in the Eco Audit, there is a 15% reduction in emissions in the CO 2 footprint for the BIW solution, as well as a 7% reduction in the C eq total , in the on-site test and a saving of 260.40 L in fuel consumption, that is, the reduction in vehicle weight plays a significant role in reducing CO 2 emissions, providing a mitigation factor for global warming. [Display omitted] • There is a 15% reduction in emissions in the CO2 footprint for the BIW solution. • There is a 7% reduction in the Ceq total, in the on-site test. • Reduction in vehicle weight plays a significant role in reducing CO2 emissions. • Providing a mitigation factor for global warming. • There is a fuel economy of 260.4 L over the vehicle's life cycle. [ABSTRACT FROM AUTHOR]

Mitigating greenhouse gas emissions is a significant global challenge, and precise prediction of carbon emissions holds the utmost importance for China to attain its dual carbon goal. To overcome the limitations of existing studies using a single forecasting method, based on quadratic exponential smoothing, multiple linear regression, and Gaussian process regression models, this paper constructs a carbon emission combination forecasting model with the generalized induced ordered weighted average (GIOWA) operator and analyzes carbon emission reduction performance. Empirical testing utilizing China's carbon emission data from 1980 to 2020 reveals the following findings: (1) The GIOWA combination forecasting model significantly enhances the accuracy of carbon emission forecasts, with an average accuracy exceeding 99.5% over the sample period, surpassing various single forecasting methods. (2) The carbon emission reduction target can be achieved under three different scenarios of low, average, and high GDP growth rates. Specifically, under the low growth rate scenario, China can achieve a 60% reduction in carbon intensity by 2025 and a 65% reduction by 2030. This study offers valuable decision support for the development of effective carbon reduction policies. [ABSTRACT FROM AUTHOR]

Abstract China is under great pressure to reduce CO 2 emissions (CEs). Meanwhile, China's economy is more reliant on domestic consumption (particularly household consumption) than on exports. So, to achieve large-scale CEs' reduction for China, there is urgent need to study the CO 2 emissions from household consumption (CEs HC). Based on the environmentally extended Multiregional Input-Output model, this paper not only calculates both the direct CO 2 emissions from household consumption (DCEs-CH) and the indirect CO 2 emissions from household consumption （ICEs CH）at the provincial level in China, but also splits ICEs CH into domestic and foreign CEs. The findings of this paper are as follows: (1) between 2002 and 2012, CEs HC in China increased significantly, by 2.27 times, from 1306.17 Mt in 2002 to 2971.01 Mt in 2012. The CO 2 emissions from urban household consumption (CEs UHC) in China accounted for 75% of the total CEs HC in 2012. (2) The per capita CEs HC in China increased from 1.02 t/person in 2002 to 2.19 t/person in 2012. There was a prominent disparity in the total CEs and per capital CEs HC among the provinces in China. The per capita CEs HC were larger in provinces with a higher level of urbanization and higher per capita income. (3) The large-scale interprovincial transfer of ICEs caused by household consumption mainly occurred either within the Yangtze River Delta, the Pearl River Delta, and the Jing-Jin-Ji region or among these three regions. In addition, to service the household consumption, the energy-abundant provinces transferred a considerable amount of CEs to eastern coastal provinces. To achieve CEs' reduction, consumption-based strategies, such as lifestyle changes, should be required in parallel with strategies to reduce emission intensities on the producer side in China. Urban households should take more responsibility for the reduction of CEs in China. The interprovincial "Carbon leakage" should be taken into account when making policies for CEs' reduction in China. [ABSTRACT FROM AUTHOR]

Abstract With the development of China's economy, the use of fossil energy has become more and more, resulting in increasing carbon emissions. CO 2 emissions have caused global warming, threatening humans and creatures on Earth. In order to effectively suppress the growth of carbon emissions, it is necessary to analyze the influencing factors of carbon emissions and apply them to predict carbon emissions. This paper presents sixteen potential influencing factors and uses grey relational analysis to identify the factors that have a strong correlation with carbon emissions. The principal component analysis (PCA) is used to extract the four principal components, which reduce the redundancy of the input data. The long short-term memory (LSTM) method is established to predict carbon emissions in China. We use back propagation neural network (BPNN) and Gaussian process regression (GPR) to compare LSTM method. The simulation results show that the prediction accuracy of carbon emissions based on LSTM is better than that of BPNN and GPR, indicating the effectiveness of PCA and LSTM in prediction of carbon emissions. Finally, this paper provides the theoretical basis for China to reduce carbon emissions by studying prediction of carbon emissions. Highlights • Grey correlation analysis is applied to identify factors associated with carbon emissions. • Principal components analysis is used to simplify input variables and obtain the main factors affecting carbon emissions. • The long short-term memory model is used for the first time to predict carbon emissions. • The direction of reducing carbon emissions in China is given by analyzing the prediction results. [ABSTRACT FROM AUTHOR]

Abstract Cities do play significant roles in tackling global environmental changes. Decoupling economic growth from environmental pressures is critical for global sustainable development, however, few studies pay attention to the decoupling analysis at city level. This paper conducts a comparative study of the decoupling performance of economic output from CO 2 emissions between Beijing and Shanghai, the top two cities in China. In this paper, the decoupling trends and the decoupling effects are explored from a sectoral perspective, by combining the Tapio decoupling elasticity and the logarithmic mean Divisia index (LMDI) model. The results show that Beijing and Shanghai both experienced weak decoupling in construction, expansive negative decoupling in transport, expansive coupling in trade, and weak decoupling in others over the period 2000–2015. Moreover, agriculture appeared strong decoupling in Beijing, and recessive decoupling in Shanghai; industry showed strong decoupling in Beijing, and weak decoupling in Shanghai. The decoupling effects showed different magnitudes and patterns in industrial sectors between Beijing and Shanghai. Overall, per-capita GDP and population growth inhibited the decoupling, while energy intensity, industrial share, energy mix accelerated the decoupling process. Highlights • The decoupling of sectoral economic output from carbon emissions in Beijing and Shanghai are investigated. • Beijing's industry enjoyed better decoupling performance than Shanghai's industry. • Transport should be put more emphasis in further decoupling efforts. • Energy intensity is crucial effect accelerating the decoupling process. [ABSTRACT FROM AUTHOR]

Abstract Local governments have provided the subsidy policy to help enterprises for their efforts in reducing the emission of carbon dioxide. The current paper discusses the policy decision-making process of a local government on how to determine the best subsidy rate under the consideration of achieving the best comprehensive effect. The policy-making framework introduced to determine the optimal subsidy rate takes three steps. First, a market of distinct products is set up to describe the competitive situation between traditional high-emission product and low-emission green product. Then, the subsidy policy provided by the local government stimulates and supports the companies producing green products and reducing the emissions. Once the subsidy rate is determined, three indicators including government revenue, employment level and pollution emissions used to analyze the influences of the policy upon the government. At last, the selection problem regarded as a multicriteria decision-making (MCDM) problem is solved by Data Envelopment Analysis (DEA) technique. A numerical example is presented to illustrate how our method works. Highlights • The paper proposes a new decision-making framework to determine the best subsidy policy. • The paper chooses three indicators to analyze the influences of the subsidy policy upon the government. • The estimation on the values of the indicators for any given subsidy policy rate could be calculated. • The proposed model solves the problem that the units used to measure the indicators are different. [ABSTRACT FROM AUTHOR]

Abstract The construction industry is a large contributor to global emissions, though it is becoming more aligned with sustainability practices. Historically, the industry has focused on cost, production and time, but now adds emissions to this list. Industry attitudes to emissions have been the subject of a number of surveys, but these necessarily only give qualitative information. This paper takes a quite different tack and establishes, for the first time, quantitative measures of industry attitude. Both the qualitative and quantitative approaches have a perception basis. The paper's approach is through the medium of utility and utility functions. The paper takes a number of industry scenarios and establishes the attitude of industry personnel to lower-emissions production. Generally, it is found that construction personnel are risk aversive to emissions, but to differing degrees. Here, risk is used in the sense of the magnitude and likelihood of an outcome involving emissions. The implications of this are demonstrated through an earthmoving operation, where the emissions-production results for differing degrees of risk aversion are highlighted. The paper is original in terms of offering a different view of emissions, and unique in its approach. By analysing the utility functions obtained, industry's attitude toward carbon emissions can be better understood. And flowing from this, more effective and efficient methods for reducing carbon emissions can be created. Graphical abstract Image 1 Highlights • Utility is advanced as a measure of attitudes to cleaner production. • Construction personnel are found to be risk averse to emissions. • The paper gives an original and unique view of attitudes to cleaner production. • A utility measure provides understanding of industry emissions attitudes. • Effective and efficient methods for reducing emissions can follow. [ABSTRACT FROM AUTHOR]

Quantifying the use of resources in food production and its environmental impact is key to identifying distinctive measures which can be used to develop pathways towards low-carbon food systems. In this paper, a first-principle modelling approach is developed, referred to as gThermaR (Glasshouse-Thermal Requirements). gThermaR is a generic tool that focuses on the energy requirements of protected heated production, by integrating holistic energy, carbon, and cost modelling, food production, data analytics and visualization. The gThermaR tool employs historic data from weather stations, growing schedules and requirements specific to grower and product needs (e.g. set-point temperatures, heating periods, etc.) in order to quantify the heating and cooling requirements of glasshouse food production. In the present paper, a case study is reported that employs a database compiled for the UK. Another relevant feature of the tool is that it can quantify the effects that spatial and annual weather trends can have on these heating and cooling requirements. The main contribution of this work, therefore, concerns the development a tool that can provide a simple integrated approach for performing a wide range of analyses relevant to the thermal requirements of heated glasshouses. The tool is validated through collaborations with industrial partners and showcased in a case study of a heated glasshouse in the UK, offering the capacity to benchmark and compare different glasshouse types and food growth processes. Results from the case study indicate that a significant reduction in the heating requirement and, therefore, carbon footprint, of the facility can be achieved by improving key design and operational parameters. Results indicate savings in the peak daily and annual heating requirements of 44–50% and 51–57% respectively, depending on the region where the glasshouse is located. This improvement is also reflected in the carbon emissions and operating costs for the different energy sources considered. Furthermore, the temporal variability/uncertainty of the annual energy requirements and of the peak daily energy requirements are found to be considerably lowered through improvements to the glasshouse attributes. Overall, gThermaR proves its value in quantifying and identifying key factors that have a significant impact on energy requirements of heated glasshouses. Such valuable outputs are invaluable for stakeholders in the food industry that have an interest in mapping the sustainability and mitigating the carbon footprint of their supply chain processes. [ABSTRACT FROM AUTHOR]

The textile industry is a significant source of global greenhouse gas emissions; therefore, it is crucial to implement decarbonization measures throughout the supply chain (SC) to reduce carbon emissions and achieve sustainable development. However, there exists a lack of systematic review regarding decarbonization in textile SCs. The objective of this review is to identify themes related to decarbonization in textile SCs, address research gaps, and propose an integrated framework. To do this, we conducted a systematic literature review of 68 identified papers discussing decarbonization in textile SCs. Based on descriptive and thematic findings, we have developed a comprehensive conceptual framework that synthesizes antecedents, decarbonization practices, influential factors, and outcomes within the context of textile SCs. Furthermore, our review highlights current research gaps and recommends future directions for studying decarbonization in textile SCs. By providing the first comprehensive framework for addressing decarbonization across all stages of the textile SC process, this review contributes significantly to the existing literature. [ABSTRACT FROM AUTHOR]

The significant carbon emissions generated by China's sludge treatment industry cannot be ignored. However, with only a few recent well-executed studies on carbon emission reduction in the sludge treatment field, the literature awaits a more comprehensive assessment and prediction whether the sludge treatment industry can achieve the dual-carbon target. This article aims to fill this gap, holistically examining the carbon emission reduction potential in the industry. Using the moving average method and IPCC method, the projected carbon emission value of sludge treatment in China from 2021 to 2030 indicates a total net carbon emission of 0.3 million tons by 2030. This suggests that the sludge treatment industry is on track to meet the carbon peak target, leaving surplus carbon quotas or credits available to assist other industries for carbon emissions reductions. The study also finds that only incineration and composting demonstrate the potential to be able to partially offset carbon emissions through resource utilization in certain stages or processes. Therefore, the current sludge treatment methods do not yield comprehensive emission reduction effects and cannot provide sufficient contribution to China's dual carbon goals. To address this issue, the paper explores a new scheme that focuses on improving the sludge treatment process. The scheme comparative analysis reveals that, even with all sludge treatment methods optimized, the total net carbon emissions of the industry could only be reduced to 0.058 million tons. This reduction falls short of significantly mitigating carbon emissions to achieve the carbon neutrality goal. Therefore, industries unable to achieve substantial net carbon reduction may need to explore alternative measures, such as carbon sinks, to ultimately attain carbon neutrality. [ABSTRACT FROM AUTHOR]

Towards the target of carbon neutrality, the need for deep decarbonization in iron and steel industry is increasingly recognized. Existing studies rarely mention the effects of collaboration with its source industries for carbon emission reduction in ISI. Furthermore, the fundamental laws of CO 2 emission reduction capacity with cost change of source substitutions for various steel production routes under market economics are unclear. To avoid the blind substitution of clean sources for meeting the urgent requirements for decarbonization in China's steel industry, which may result in increased carbon emissions and uneconomical carbon reduction from a lifecycle perspective. This paper integrates the production and utilization processes of source resources into the steel production process, establishes coupling models of carbon and value flows for four main types of steel production routes, and aims to quantitatively analyze the specific CO 2 emission reduction potential and costs. Three economic market development scenarios from 2021 to 2060 are set, and the marginal carbon prices of various source substitutions are determined. Subsequently, decarbonization pathways with the goal of minimizing production costs are developed. Finally. The future resource demand and the carbon emission reduction contributions of source industries collaborated are predicted. The results show that (1) about 81.7–89.9 % of CO 2 emissions could be reduced in the scenarios; (2) the demands of electric power and hydrogen energy will reach 54.48–511.90 BkWh and 7.47–10.31 Gt in 2060, respectively; and (3) collaboration with source industries could make 18.3–18.3% of CO 2 emission reduction contributions. All in all, this study could provide scientific support for the low-carbon transformation of China's steel industry. • Carbon and value flows of BF-BOF, Scrap-EAF, DRI-EAF, MOE-EAF routes are analyzed. • CO 2 emission reduction potential with marginal carbon price is determined. • Decarbonization paths during 2021–2060 for China's steel industry are developed. • Quantify the contribution of collaborative carbon reduction with source industries. [ABSTRACT FROM AUTHOR]

Forecasting the future emission trajectories and the relating sensitive driving factors of emissions for cities is of great significance to formulate realizable CO 2 mitigation policies. To proceed the forecasting, studies on peak prediction and quantification of reduction potential at the city level are essential. However, the studies in the area are very limited. Selecting the Beijing-Tianjin-Hebei urban agglomeration (BTH) as the study region, this paper aims to contribute to the research area and provides implications for other cities or urban agglomerations. The Kaya identity and multi-scenario simulation were employed to predict the dynamic evolution pathways of CO 2 emissions from 2021 to 2035 and explore the differential CO 2 peak time, peak value, and reduction potential for 13 cities in BTH. Monte Carlo simulation, Mann-Kendall trend test and Sen's slope estimation method are jointly used to reduce uncertainties in estimation. The Monte Carlo simulation results show that most cities in BTH have already reached their CO 2 emissions peak, while Tianjin, Langfang, Cangzhou and Tangshan are expected to reach their peaks between 2025 and 2030. Among them, 5 and 8 cities have the risk of not reaching their peak before 2035 in the high consumption scenario (HCS) and extensive development scenario (EDS) respectively. Comparative analysis reveals that low-carbon scenario (LCS) and sustainable development scenario (SDS) have significant effects on emissions reductions. The top three cities in terms of accumulative emission reduction in 2021–2035 are Tianjin, Tangshan and Cangzhou, estimated as 117.82–250.75 Mt CO 2 in LCS and 217.77–454.10 Mt CO 2 in SDS, respectively. The results of sensitivity analysis reveal that the most critical driver of CO 2 emissions in Beijing is population, while that is GDP per capita for Tianjin. Langfang and Hengshui showed the highest sensitivity to energy intensity. Accordingly, these cities have differentiated concerns and priorities to achieve their carbon peak goal as scheduled. • Kaya identity and scenario simulation are combined to predict future CO 2 emissions. • The BTH would reach CO 2 emission peak by 2025, but the time varies on city-level. • Tangshan, Langfang, and Cangzhou are at greater risk of not reaching the peak by 2030. • Tianjin, Tangshan and Cangzhou have the greatest potential to reduce emissions. • Differentiated priorities are suggested for specific city's CO 2 mitigation targets. [ABSTRACT FROM AUTHOR]

This paper analyses businesses' initiatives to influence consumption carbon emissions in home laundering, principally by persuading consumers to wash clothes at lower temperatures. A number of voluntary business initiatives have sought to change consumer practices, coming from detergent manufacturers, their industry association and retailers. This paper analyses their impact at system level, by assessing the coevolutionary interactions between ‘Supply’, from consumer-facing firms, whose principle business is to sell products to consumers, both manufacturing and retailing, and ‘Demand’ from consumers, whose interactions with the businesses arise from shopping, using and receiving consumer messages from the firms. The research analyses the interactions between the business case drivers for presentation of consumer messages to reduce laundry emissions and the drivers of changes in consumer laundry practices. This enables inductive inference of the causal relationships over time between businesses’ strategies to communicate with consumers and changes in users’ laundry temperatures. The paper concludes that, in spite of considerable efforts and resources, these business initiatives have not resulted in the intended level of change in consumer practice that would deliver significant emissions reductions. Consumption emissions from households are a result of interdependent systems of provision, technologies and infrastructure, so stronger actions by business to influence consumer practices as well as further regulatory drivers are likely to be needed to deliver stricter emission reduction targets. This research contributes to the field of sustainable consumption through bringing together a coevolutionary framework with theories of business model innovation and social practices, in order to analyse whole systems of competing businesses’ strategies in context with technologies, institutions and ecosystems. [ABSTRACT FROM AUTHOR]

The five major power generation corporations dominate the power industry in China, and play vital roles in China's carbon trading scheme. Under this circumstance, this paper studies the allocation of carbon emission quotas to China's five major power generation corporations based on the fairness and efficiency principles, which proves the primary prerequisite for setting up the national carbon market. Specifically, a bi-level programming model is developed to optimally allocate carbon emission quotas to the corporations, and then a zero sum gains data envelopment analysis (ZSG-DEA) model is adopted to evaluate the efficiency of the allocation so as to adjust towards the optimal solution. The results indicate that power generation has significantly positive influence on the allocation of carbon emission quotas. Moreover, the difference between the sum of optimal carbon emissions and the sum of carbon quotas allocated is 1.431 billion tons, which implies that the emission reduction potential of the five major power generation corporations is tremendous. Finally, the bi-level model in this paper can well capture the context of China's power industry and provide effective results for the allocation of carbon quotas. [ABSTRACT FROM AUTHOR]

As agriculture is an important contributor to greenhouse gas emissions, carbon labelling aiming at climate protection will play an increasing role in the future. An important example is the development of guidelines and standards for climate-neutral agricultural products and their respective certification. Carbon neutral certifications are, however, affected by criticism and mistrust as there were cases of doubtful claims to carbon neutrality in the past. Against this background, this paper analyses a rather promising case of certification for carbon neutrality: the pioneer case of the Costa Rican coffee cooperative Coopedota, which is the first organization worldwide that achieved certification for carbon neutrality in coffee using a renowned international standard. Coopedota's carbon neutral coffee is certified according to the Publicly Available Specification (PAS) 2060, which is based on a Life Cycle Assessment (LCA). The paper analyses how the cooperative came to apply this certification, which challenges it faced and how the cooperative solved them. Furthermore, the paper examines the social, political and institutional factors that fostered this innovation. To analyse the success factors that were relevant in this case, a Social Network Analysis approach was used. An innovative tool called ‘Process Net-Map’ was applied to visualize the social networks that enabled the actors to pursue the certification scheme. Process Net-Map also made it possible to identify the role and importance of different types of actors. The analysis shows that the certification created awareness on emission hot-spots along the coffee value chain. Reliable farm data from producers were identified as crucial because emissions at the farm level account for 60% of total emissions. It was also found that by avoiding pure offsetting, PAS 2060 supports emission reduction; however, PAS 2060 does not account for on-site carbon sequestration, for which coffee cultivation has high potential. Overall, the study found that the most important success factors include a combination of (i) past achievements in Coopedota's sustainability policy, which was incentivised by national and international trends and (ii) strong, visionary actors who performed the necessary network functions. The analysis also showed that the network of relevant actors is highly centralized, (indicated by a degree centrality of 86%), which may jeopardize the sustainability of the innovation project. Moreover, the network analysis revealed the importance of ‘double linkages’ between actors, which points to the role that combined services, such as funding and advice, played for the introduction of the certification scheme. General implications are derived from this case for future efforts to promote carbon neutral certification schemes for agri-food products. [ABSTRACT FROM AUTHOR]

To achieve the Chinese government's CO 2 emissions reduction target and build a carbon trading market in the Pearl River Delta (PRD) region, an initial allocation of CO 2 emissions quotas among cities in this region is fundamental. Different from the previous CO 2 emissions quotas allocation methods, this paper uses the maximum deviation method (MDM) to allocate CO 2 emissions quotas in the PRD region by taking the imbalanced development of different cities into consideration. Three principles including equality (represented by a population indicator), efficiency (represented by a GDP indicator) and feasibility (represented by a historical CO 2 emissions indicator) are considered in the method. The results reveal that the allocations derived by the MDM are more balanced than those derived using either single indicator approach or the information entropy method, and more closer to the development targets of Guangdong province. The more balanced allocations will be conducive to stimulating the development of under-developed cities and narrowing the gap between developed and under-developed cities, thus help to achieve the sustainable development in the PRD region. This paper helps to enrich the emissions quotas allocation methods and provides a new equitable method for policy makers to allocate emissions quotas under imbalanced development circumstances. [ABSTRACT FROM AUTHOR]

The metallurgy industry plays a very important role in China's economic growth. Due to its energy concentration, the energy consumption of the industry accounts for a large proportion of China's total energy consumption, and thus contributes to carbon emissions. Whether the metallurgy industry can successfully reduce emissions is related to the future of China's carbon emissions targets. In this paper, the logarithmic mean Divisia index model is used to analyze the change in China's carbon dioxide emissions from 1991 to 2014. The empirical results show that there are three main factors affecting the carbon dioxide emissions of China's metallurgy industry. The three factors are labor productivity, energy intensity and industry size. In addition, we further analyzed the deep motivation of carbon dioxide emissions in the industry, and calculated the future emission reduction potentials. Lastly, according to the empirical results, the paper proposes policy recommendations for the future emission reduction of China's metallurgy industry. [ABSTRACT FROM AUTHOR]

Ecological sustainability of the Chinese economy is vital for China as well as for the world. By integrating environmental input-output analysis, emergy theory, and a complex network model into one framework, this paper explores Chinese sectoral ecological sustainability with the most recent 2012 input-output table. The results show that there are significant differences in emergy intensities among sectors. The non-metal mining sector is the most emergy-intensive sector at 6.06E+17 sej/10000 Yuan, followed by the metal mining sector. Additionally, output connections have a positive impact on the emergy yield ratio, input connections exert a negative impact on the emergy yield ratio, and PageRank centrality has a positive effect on the environmental loading ratio. This paper updates the Chinese sectoral emergy assessment, identifies key sectors in the Chinese ecological network, and analyzes the impact of network indicators on sectoral emergy performance. These analyses will be useful in updating the guide for adjusting industrial structure in China. [ABSTRACT FROM AUTHOR]

Low carbon urban transition experiments are emerging across cities globally. These experiments are socio-technical innovations with a high potential to contribute to a low carbon. Through the Global Intelligence Corps knowledge of these experiments is being disseminated across a variety of spatial contexts. Foreign cities are keen to replicate these examples of best practice; whilst technical experts, technology providers and governments are keen to export their expertise and technologies. However, the factors influencing the successful translation - movement, transformation and adaptation - of these experiments across spatial contexts requires deeper investigation. This paper explores the process using a mobile transitions conceptualisation. In this paper we develop a theoretical conceptualisation of the mobile transition process and test it using two low carbon experiments - Hammarby Sjostad (Stockholm) and BedZed (London). We identify the type of knowledge that is translatable (in the global form), and how this is modified both by the global and local assemblages throughout the process. The implication of our findings is that greater clarity is needed throughout the translation process if outcomes are to improve. Firstly, in order to determine the potential for an urban experiment to translate into a new spatial context the practitioner must understand the context from which it emerged and the context into which it will be translated. Secondly practitioners need to clearly define the translatable global form emerging from an experiment. It must be possible to decontextualise and re-contextualise the global form if it is to translate successfully. In some cases it may be impossible to decontextualise the global form without undermining the fundamental principles underlying the experiment. Thirdly, practitioners need to be aware of how the global form can be manipulated and re-represented by the global and local assemblages during the translation process. The global form is not fixed. Finally practitioners should be aware that new socio-technical systems (adopting the fundamental principles developed in the experiment) will emerge from the translation process. [ABSTRACT FROM AUTHOR]

The allocation of carbon emission quotas is recognized as a fundamental and critical step towards the establishment of an effective nationwide carbon emissions trading (CET) market in China. This paper aims to examine the quota allocation pertaining to China's east coastal areas. These regions are pioneers in reformation and the domestic heavy emitters. In this paper, a multi-criteria decision analysis model is proposed. This model is based on the principles of efficiency and equity. In order to reflect the true efficiency of carbon emissions, a weighted Russell direction distance model is employed. Three criteria, namely capacity, responsibility and potential, are used to evaluate the degrees of equity. Furthermore, different situations are set to evaluate the related indicators. The results indicate the following: (1) Industrial provinces have less carbon emission quota increments. (2) The Yangtze River Delta Economic Zone has notably improved energy efficiency, and future quota increments correspond with the zone's current carbon emissions. (3) Circum-Bohai Sea Economic Zone will be a major buyer of carbon emission quotas, while Pan-Pearl River Delta Economic Zone currently receives surplus quota. (4) The overall allocation of quotas converts from uneven to even as a result of GDP growth. These results provide a reference for collaborative regional reductions in carbon emissions and for the construction of a CET market. [ABSTRACT FROM AUTHOR]

This paper first estimates the energy-related carbon dioxide (CO 2 ) emissions and carbon intensity of China's 30 provinces from 2000 to 2015. By constructing a 4-variable Panel Vector Auto-regression (PVAR) model, the paper quantitatively analyzes the dynamic relationship among urbanization, industrial structure, energy and carbon intensity in China during urbanization and industrialization stage. The results show that urbanization process and the advancement of industrial structure are consistent with the optimization goals of energy and carbon intensity. In the long term, energy and carbon intensity will decline with the development of urbanization and the advancement of industrial structure. But urbanization process has an inverted U-shaped effect on energy and carbon intensity, while the influence of industrial structure advancement on energy and carbon intensity increases over time. In contrast, the positive impact of energy intensity on carbon intensity is mainly reflected in the short term. This paper confirms the importance of urbanization and upgrading of industrial structure in the goal of energy saving and emissions reduction. Thus, this paper suggests that each province should adopt the upgrading of industrial structure as one of the policy goals, and constantly promote new urbanization process, following their own development characteristics. [ABSTRACT FROM AUTHOR]

One-third of global energy demand as well as CO 2 emissions is accounted to industrial processes. In particular, over 30% of total industrial energy consumption is attributed to the iron and steel, cement and refining industry. The aim of the present paper is to review crosscutting technologies and measures adopted to improve energy efficiency in the main Italian industrial sectors regulated by the recent EU legislation on integrated pollution prevention and control (IPPC-IED). In fact, 2010/75/EU Directive on industrial emissions, a general improvement on the entire environmental performance of the industrial installations is pursued by taking into account relevant environmental issues, such as emissions into water, air, soil as well as energy efficiency, waste production, recovering and recycling, restoration of the site upon definitive cessation of activities. Moreover, according to 2010/75/EU Directive, IPPC permits should be based on Best Available Techniques (BAT) aimed to reach an adequate level of environmental protection and should establish all the necessary measures including operating conditions, emission limit values for relevant polluting substances as well as monitoring requirements. Thus, in the present paper an assessment of Best Available Techniques (BAT) related to energy efficiency in the main Italian industrial installations is carried out on the base of the analysis on the IPPC permits released by the Italian Ministry for the Environment, Land and Sea, and made available on its web site. As a result a significant improvement in energy efficiency was assessed. In fact, many process units were upgraded, by major revamping or even by replacing the process completely with one showing better performances. Finally, since energy efficiency is at its best at the beginning of the life cycle of the plant, operators, whenever necessary, periodically monitor and measure the actual energy performance of their own installations for process control and maintenance purposes. [ABSTRACT FROM AUTHOR]

Cities are the main carbon dioxide (CO 2 ) emitters in China, and it is important to explore both the characteristics and reduction potential of their CO 2 emissions. This paper calculates the industrial energy-related CO 2 emissions (IECEs) of 17 cities in China's Yangtze River Delta (YRD) region from 2005 to 2014 and analyses the driving factors of CO 2 emissions using the Logarithmic Mean Divisia Index (LMDI). In addition, this paper predicts the CO 2 reduction potential of this group of cities for the period from 2015 to 2020. The results show that (1) during the sample period, industrial CO 2 emissions in the studied cities increased by a factor of 1.61. Economic output is the greatest contributor, followed by population size. Energy intensity and energy structure are the two main emission mitigation factors; (2) the driving factors of CO 2 emissions in the group of cities exhibit distinct spatial characteristics, indicating that future analyses of cities in this area should have distinctly different foci; and (3) the forecasting results show that under moderate and aggressive scenarios, CO 2 emissions in the studied cities can be reduced by 281.59 Mt and 711.90 Mt, respectively, by 2020. [ABSTRACT FROM AUTHOR]

Decarbonisation of stationary energy supply, particularly electricity grids, is the current focus of climate change mitigation policy. However, studies have suggested that this narrow policy focus is insufficient to achieve meaningful global emissions reductions. Using Iceland as a case study, this paper demonstrates that significant emissions arise from transport and imported products, which are often not fully captured in territorial GHG inventories. This results in high greenhouse gas emissions per capita regardless of the nation's domestic energy supply. The result is a low carbon illusion in which rich economies believe they are reducing their GHG responsibility whilst global emissions continue to grow. This paper presents the first consumption-based carbon footprint (CBCF) analysis for Iceland, a nation where the stationary energy supply is 99% renewable, and could be viewed as a decarbonisation ‘future case’ for rich nations globally. The study combines Icelandic household expenditure data with the Multi-Regional Input-Output database Eora to calculate the CBCF of Icelandic households. The average annual CBCF of Icelandic households was 10.4 tCO 2 eq/capita, similar in magnitude to other EU nations despite Iceland's unique energy supply. GHG emissions from transport, food and goods dominated the household CBCF. The national CBCF was higher than most European nations and 55% higher than the territorial emissions inventory. Approximately 71% of household emissions were attributed to imported goods, which were mapped globally revealing that the GHG emissions burden of Icelandic consumption falls primarily on developing nations. The findings suggest that a broader GHG accounting framework and resulting policy focus is required, both in Iceland and globally, that incorporates both supply and demand-based GHG reduction strategies. [ABSTRACT FROM AUTHOR]

The paper examines the types and role of carbon management control systems by analysing in-depth interviews undertaken with 38 individuals from 30 organizations that use carbon management control systems. The paper identifies the different types of carbon controls, and the internal and external uses and objectives of controls. Carbon controls can be used to achieve compliance or improve performance, and organizations can focus on different objectives at different times. The findings suggest that emissions reductions do not occur without absolute (as opposed to intensity) reduction targets, management support, and resource allocation for carbon management. The findings further suggest that firms that want to improve performance or manage compliance costs effectively will require the integration of carbon controls into operational and strategic processes. A framework is developed that managers and researchers can use as an implementation guide or a research framework. The framework highlights three elements that were found to be critical to ensure control effectiveness, namely managerial communication, quality of information, and employee perceptions. The evidence suggests that communication of carbon information through appropriate channels and language, as well as high quality of carbon information are essential to ensure positive employee perceptions and buy-in, which will contribute to effective carbon reduction. [ABSTRACT FROM AUTHOR]

As an important part of smart grid optimizations, optimal dispatch of microgrid is of great significance to reduce energy consumption, environmental pollution and user's electricity costs. The development objective of microgrid is not only to meet the basic demand of power supply, but also to improve its economic efficiency and environmental protection. In this regard, this paper proposes a multi-objective optimal dispatch model for microgrid under grid-connected mode, which comprehensively considers the operation cost and the environmental protective cost of the microgrid system. Distribution generators in the microgrid system include photovoltaic array, wind turbine, diesel engine, micro turbine and electric vehicle. The batteries of the accessed electric vehicles are treated as a kind of mobile distributed energy storage device in the model. In order to solve the proposed model effectively, according to the configuration and characteristics of the model, this paper proposes an improved particle swarm optimization algorithm to solve the optimization model. Two different operation scheduling scenarios under grid-connected mode are researched, and the dispatch results of different optimization goals are discussed in this paper. The simulation results show that the effectiveness and superiority of the proposed model, which can effectively reduce the user's electricity costs and environmental pollution, promote the optimal operation of microgrid and achieve the economic management of the batteries of electric vehicles. [ABSTRACT FROM AUTHOR]

The commercial sector is one of the key sectors in China’s economic transformation and carbon emissions control. This paper applies VAR and STIRPAT models to investigate the major influencing factors of CO 2 emissions in China’s commercial sector over the period 1980–2014. According to the empirical results, per capita GDP, urbanization and energy structure have positive effects on CO 2 emissions while energy intensity has negative effect on CO 2 emissions in the long term. Besides, per capita GDP ranks as the most important driving factors of CO 2 in China’s commercial sector, followed by urbanization, energy structure and energy intensity in that order. This paper argues that reducing energy intensity and improving energy structure are the means to realize CO 2 emission reductions in the commercial sector in the short and long term, respectively. Besides, this paper forecasts that CO 2 emissions in China’s commercial sector will be 1942 Mt by 2030, which is huge and about half of the CO 2 emissions of the European Union in 2014. The findings have important implications for policy-makers to enact CO 2 emission reduction policies. [ABSTRACT FROM AUTHOR]

With the increase of the concern from the public for environmental pollution and waste of resources, the value recovery through reuse, repair, remanufacturing and recycling from the end-of-use (EOU) and end-of-life (EOL) products have become increasingly important. Reverse logistics is the process for capturing the remaining value from the EOU and EOL products and also for the proper disposal of the non-reusable and non-recyclable parts. A well-designed reverse logistics system will yield both economic and environmental benefits, so the development of an advanced decision-making tool for reverse logistics system design is of significant importance. The paper presents a novel multi-product multi-echelon stochastic programming model with carbon constraint for sustainable reverse logistics design under uncertainty. Compared with the previous stochastic optimization models in reverse logistics system design, which mainly focuses on the expectation of the optimal value, this paper, however, emphasizes on both optimal value expectation and its reliability in decision-making. Due to this reason, a multi-criteria scenario-based risk-averse solution method is developed based on a latest research in order to obtain the optimal solution with high level of confidence. Later in this paper, the application of the model and the augmented solution method is illustrated and the managerial implications are discussed through the numerical experiment and sensitivity analysis. The result of the study shows that the model can be used for providing decision-makers with a deep insight into the relationship between profit and carbon emission requirement, understanding and resolution of the infeasibility caused by capacity limitation, the use of flexible manufacturing system in reverse logistics, and proper use of the government subsidy as a leverage in reverse logistics design. [ABSTRACT FROM AUTHOR]

This paper shows the differences between the design of a reinforced concrete structure considering two objectives to minimize; economic cost and CO 2 emissions. Both objectives depend on the amount of two high carbon intensive materials: cement in the concrete and steel; therefore, these objectives are related. As the balance between steel and cement per m 3 of concrete depends on several factors such as the type of structure, this study focuses on buttressed earth-retaining walls. Another factor that determines the balance between steel and concrete is the height of the wall. Thus, the methodology considers a parametric study for optimal designs of buttressed earth-retaining walls, where one of the parameters is the wall height. One of the objectives is to show the variation in cost when CO 2 is minimized, respectful of minimizing the economic cost. The findings show that wall elements under bending-compressive strains (i.e. the stem of the buttressed retaining wall) perform differently depending on the target function. On one hand, the study reveals an upward trend of steel per unit volume of concrete in emission-optimized earth-retaining buttressed walls, compared to the cost-optimized. On the other hand, it is checked that unlike the cost-optimized walls, emission-optimized walls opt for a higher concrete class than the minimum class available. These findings indicate that emission-optimized walls penalize not only concrete volume, but also the cement content, to the extent that a higher concrete class outperforms in reduced emissions. Additionally, the paper outlines how and to what extent the design of this typology varies for the two analyzed objectives in terms of geometry and amount of materials. Some relevant differences influencing the geometry of design strategies are found. [ABSTRACT FROM AUTHOR]

A carbon reduction labelling scheme is an effective policy tool for motivating enterprises or organizations to reduce their life-cycle-based carbon emissions to benefit the environment. This paper uses system dynamics to model enterprises' compliance with a combined government policy instrument for a carbon reduction labelling scheme, that is, government subsidies and economic sanctions. A case study of paper enterprises in China is provided to demonstrate the application of the proposed model in which two optional technological plans to reduce the enterprises' carbon emissions are examined. The technological plans are categorized as a low-cost and high-cost plan. The simulation results show that both the technological plans are vulnerable to the combined policy making, and the high-cost plan shows superior environmental performance for carbon emissions reduction. However, the enterprises are more inclined to choose the low-cost plan because of superior economic performance. The study offers insights to help enterprises select optimal actions on carbon emissions reduction and to inform government of possible sustainable policy design to promote low-carbon development. The model limitations are discussed as a basis for further improvements in low-carbon development. [ABSTRACT FROM AUTHOR]

Evaluating innovative process technologies has become highly important within the last decades. As standard tools different Life Cycle Assessment methods have been established, which are continuously improved. While those are designed for evaluating single processes they run into difficulties when it comes to assessing environmental impacts of process innovations at macroeconomic level. In this paper we develop a multi-step evaluation framework building on multi regional input–output data that allows estimating macroeconomic impacts of new process technologies, considering the network characteristics of the global economy. Our procedure is as follows: i) we measure differences in material usage of process alternatives, ii) we identify where the standard processes are located within economic networks and virtually replace those by innovative process technologies, iii) we account for changes within economic systems and evaluate impacts on emissions. Within this paper we exemplarily apply the methodology to two recently developed innovative technologies: longitudinal large diameter steel pipe welding and turning of high-temperature resistant materials. While we find the macroeconomic impacts of very specific process innovations to be small, its conclusions can significantly differ from traditional process based approaches. Furthermore, information gained from the methodology provides relevant additional insights for decision makers extending the picture gained from traditional process life cycle assessment. [ABSTRACT FROM AUTHOR]

E-commerce has emerged through digital platforms and Internet construction as an important way to achieve low-carbon development in China. To evaluate the mitigation effect of e-commerce, this paper conducts a quasi-natural experiment in terms of the pilot policy of national e-commerce demonstration cities (NEDC) to explore the changes in CO 2 emissions of 270 cities from 2004 to 2017 in China. We also check the asymmetry, mechanism effects and heterogeneity. The results show that the treated cities reduce CO 2 emissions by 4.1% due to the NEDC pilot policy compared to the untreated cities. The estimated results pass the parallel trend test, robustness tests, and the Goodman-Bacon decomposition. Moreover, the NEDC pilot policy increases the CO 2 emissions of treated cities by promoting economic growth (scale effect), and decreases the carbon emissions of treated cities by upgrading the industrial structure (structural effect) and increasing the technological innovation level (technical effect). Furthermore, the CO 2 mitigation effects of the NEDC pilot policy are significantly concentrated in the higher quantiles. Finally, the NEDC pilot policy has significantly negative effects on CO 2 emissions in "postage-free regions," southern China, and cities with large e-commerce sales. The results of this paper provide theoretical and practical references for China to achieve low-carbon development. • Evaluating the impact of pilot policies of national e-commerce demonstration cities (NEDC) on carbon emissions in China. • The NEDC pilot policy reduces carbon emissions of treated cities by 4.1%. • The NEDC pilot policy reduces carbon emissions through structural and technical effects. • The emission-reduction effects are significant at the higher quantiles. • The impact of the NEDC pilot policy on carbon emissions is obviously heterogeneous. [ABSTRACT FROM AUTHOR]

Carbon dioxide emissions pricing is employed as an approach to mitigate climate change. To analyze the impact of carbon prices on the metal mining industry, this paper presents a new block-based carbon dioxide emissions estimation model to assess the carbon dioxide emissions and carbon intensity in varying carbon prices, by employing the engineering-based inputs from life cycle of mineral production. Such engineering-based data of an iron case is provided to test the impact of carbon prices on mining projects. The results indicate that the negative impact of carbon prices on the profit of mining projects is more sensitive in low minerals prices, especially for underground method. On the other hand, carbon price rising facilitates the mitigation of carbon dioxide emissions, by lowering the ratio of excavated waste rocks to mined-out raw ore, which varies linearly with the emissions. The carbon dioxide emissions in the studied case decrease from 39.92 kg carbon dioxide eq per ton to 21.50 kg carbon dioxide eq per ton, and from 51.02 kg carbon dioxide eq per ton to 42.80 kg carbon dioxide eq per ton, for surface and underground method, respectively. The results of carbon intensity show that it keeps increasing due to carbon price rising, until the mining boundaries are optimized based on the increased carbon price. Image 1089 • Block-based carbon dioxide emissions estimation model is introduced for metal mines. • The projects' profit is more sensitive to carbon prices in low minerals prices. • Carbon dioxide emissions vary linearly with the ratio of excavated rocks to raw ore. • Rising carbon price increases carbon intensity before mining boundary is optimized. [ABSTRACT FROM AUTHOR]

The Republic of Serbia has a significant potential for the electricity production from solar energy, namely the floating photovoltaic (PV) systems, which are not exploited enough. Although there is a large interest in floating photovoltaic systems (FPVS) worldwide, studies related to the assessment of FPVS potential in this part of Europe have not been performed yet. This paper investigates, for the first time, the possibility of implementation of the FPVS on the six largest Serbian lakes and demonstrates the impact of geographical location on the energy output of the FPVS for the selected locations. The possibility of implementation is studied by simulating the energy output of FPVS using "PVGIS" tool. Energy production from the proposed FPVS, for selected locations, is discussed on a monthly and yearly basis. Installment of the FPVS on these water bodies can produce up to 8959 kWh of energy, while saves 164 · 10 6 m 3 / y e a r of water from evaporation at the same time. In addition, the annual reduction of carbon dioxide emissions was analyzed and found to be up to 6.34 tons per year, which further implies with carbon credit potential of up to 9741 € in 20 years period. Drawn conclusions provides better understanding of FPVS and their applicability in the Republic of Serbia to ensure a sustainable, ecological friendly, secure and reliable supply of green energy, and further the used approach can be easily applied in other countries with similar geographical characteristics. • Methodology for the application of floating PV systems on water bodies. • FPVS on six largest lakes in Serbia are able to produce up to 8959 kWh of energy. • FPVS could mitigate up to 126.8 tons of carbon dioxide in 20 years. • The Government of Serbia could earn total carbon credit per year from 381 to 487 €. • FPVS could save 3280 million cubic meters of water from evaporation. [ABSTRACT FROM AUTHOR]

Based on semi-structured interviews with key stakeholders in Nanhai, this paper adopts an analytical framework to examine how a combination of infrastructure-pull, supply-push and demand-pull initiatives implemented by a small district government in southern China were able to facilitate socio-technical transitions to the public transport decarbonization through the establishment of hydrogen refuelling infrastructures, the adoption of fuel cell electric vehicles (FCEVs), and the development of production network on FCEVs. With neither massive investment from the central government nor captive linkage with global automakers, Nanhai out-performs other automotive powerhouses in China by accounting for 9.85 percent of FCEVs and 4.59 percent of all operating hydrogen refuelling stations in China, despite its land area only accounting for 0.01 percent of the country. The provision of hydrogen infrastructures and other pro-active local government initiatives (including financial incentives) facilitate the development of a competitive regionalized production network of about 90 (privately-owned) fuel cell electric buses makers and parts suppliers around the Xianhu Hydrogen Valley in Nanhai. This finding enhances our understanding on effects of (local) state policies on the socio-technical transitions to public transport decarbonization and the long-term development of hydrogen economies in other countries. [ABSTRACT FROM AUTHOR]

• The thermodynamics and reaction stoichiometry of the proposed design. • The mass balance for the system proposed in the paper. • The heat and fuel needs implicit in the proposed system. • The feasibility of the proposed gas separations and of using the BCNF double perovskite for decomposition of CO 2 at a realistic scale. [ABSTRACT FROM AUTHOR]

In July 2021, the European Union (EU) published a package of measures for the decarbonization of maritime transport: Market Based Measures (MBM) and Goal Based Measures (GBM) that will gradually be phased in over 2023. The measures derive from an EU decision taken independently of the International Maritime Organization. This fragmentation of maritime transport governance leads to new working scenarios in the EU that have given rise to concern in the shipping industry. This paper analyzes the monetary consequences of EU decarbonization regulation on Short Sea Shipping (SSS) by introducing a mathematical model to meet this aim. From the application of this model to SSS container vessel operating between the Canary Islands and the Iberian Peninsula, it is found that, although MBM accurately reflect the pollutant impact of SSS vessels in the aftermath of the 2020 Global Sulphur Cap, only GBM along with non-compliance deterrents can redirect the vessels' investments towards more sustainable solutions in the medium-term. • Mathematical model to quantify the EU measures for shipping's decarbonization. • Market Based Measures accurately reflect the pollutant impact of Short Sea Shipping. • Market Based Measures are insufficient to boost more sustainable investment decisions. • Goal Based Measures are really able to modify mitigation strategies in vessels. • Deterrent fines by Goal Based Measures non-compliance are needed for decarbonization. [ABSTRACT FROM AUTHOR]

The increasing energy demand in harbour areas, coupled with the need to reduce pollutant emissions, has led to the development of renewable energy-based polygeneration systems to face the carbon footprint of ports and ships at berth. In this way, in the coming years, ports can be converted into modern energy hubs. From this point of view, this paper presents a new dynamic simulation model for assessing and optimizing the energy and economic impact of ports. Here, energy systems and renewable sources can be designed to be connected to national electricity and natural gas grids and can include also alternative fuels (hydrogen, biomethane, etc.) and thermal energy networks, as well as different biomass fluxes (to be exploited for energy aims). Energy availability/demands of near towns and port buildings/infrastructures, as well as on-shore power supply are also included in the dynamic assessments. Hourly weather data and different prices for all the considered energy carriers are taken into account hour by hour. A multi-objective optimization approach is also implemented in the model considering energy and economic indexes to be optimized. The whole model is implemented in a computer tool written in MATLAB. For showing the capability of the developed model, a novel case study referred to the port of Naples (South-Italy) is presented. Here, several renewable energy sources are considered, including an anaerobic biodigester for producing biogas from the organic waste of docked cruise ships. A combined heat and power system (fed by biogas) is implemented in the port energy hub also for supplying absorption chillers. PV panels, and marine power generators are also included. In the conducted analysis, optimization targets are the maximization of system self-consumption and self-sufficiency as well as the minimum simple payback period. The proposed system can effectively contribute to the decarbonization of the port energy demand and reduce harmful pollutant emissions. Results showed that very high rate of renewable energy produced on-site can be exploited (up to 84%) by the considered port facilities, ensuring increasing independency from utility power grid (self-sufficiency index up to 40%). By the obtained results and through the developed simulation/optimization tool, novel design and operating criteria can be achieved for future port energy hubs featured by renewables and bi-directional energy exchange between ships and port. [ABSTRACT FROM AUTHOR]

To comply with the European Green Deal, decarbonization of transportation is decisive, especially a shift towards more sustainable transportation services is essential. Due to the tripartite nature of sustainability (society, environment and economy), multiple interrelated criteria are part of the sustainability assessment of transportation services. Discovering these interrelations between criteria to anticipate conflicts and integrate them appropriately into multi-criteria analysis is important for ranking urban transportation services. This paper presents a novel, two-folded methodology for assessing the sustainability of different urban transportation services. First, integrative structural modeling with polarity (ISM-P) is used for universally identifying sustainability criteria interrelationships and weighting them. Second, the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) method is applied to a sustainability assessment of five specific urban transportation services (public and sharing). In conclusion, applying the methodology to the example of urban transportation services in the Ruhr region, the importance of public transportation as the most sustainable alternative is proven. • A holistic method for sustainability appraisal with dependent criteria is presented. • Urban transportation sustainability is assessed using 12 multi-dimensional criteria. • Demand and operating cost, as well as occupancy and operating cost diverge. • Combining multiple services increases overall transportation sustainability. [ABSTRACT FROM AUTHOR]

Sustained increase in Chinese household income has exerted positive impact on the consumption of goods and services. This paper aims to analyze the unequal impacts of household consumption across different income households on the whole CO 2 emissions, by utilizing a semi-closed input-output model and hypothetical extraction method. The semi-closed input-output model moves household consumption activities into the intermediate use along with dividing urban and rural households to several groups by their income levels, and the hypothetical extraction method (HEM) is used to estimate the reductions of CO 2 emissions relative to total emissions after extracting the consumption of each household group. The results show that: (1) the impact on CO 2 emissions generated by urban households’ consumption are 1.8 times as much as that of rural ones; (2) excluding consumption of higher-income households from the economy would cause greater CO 2 emission reductions than lower ones. Specifically, urban highest-income households have the most relative reductions of CO 2 emissions, which are −12.2% in 2007 and -13.8% in 2012, while for rural highest-income households are −5.1% in 2007 and -5.1% in 2012. And urban and rural highest-income households are respectively 3.8 and 1.8 times on the relative reductions of the lowest-income ones; (3) the relative reductions of household CO 2 emissions from food sectors is the most, while from residence sectors is the least. Based on the above conclusions, this paper puts forward consumption-based policy implications. [ABSTRACT FROM AUTHOR]