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Product service systems (PSS) are an example of a novel business model billed as having the potential to significantly reduce the environmental burdens of production and consumption processes. However, despite widespread interest in PSS, consensus regarding their actual environmental impacts, particularly with regard to salient issues such as global warming, is lacking. Hence this paper explores existing research to investigate the state of the art regarding the climatic impacts of PSS, alongside the set of factors that influence climatic impacts. The paper comprises a systematic review of peer-reviewed academic literature, quantifying the extent to which different types of PSS have the capacity to reduce greenhouse gas emissions across multiple product categories. Our study shows that significant reductions in climatic emissions are possible, but PSS are in many cases associated with more modest reductions and, in some cases, increased emissions. Further, we observe no clear differences in climatic impacts according to the type of PSS model that is deployed. Rather, differences in climatic impact are influenced by factors such as production and design alongside use-phase impacts and contextual factors such as transportation and the energy mix. The study argues that further research is needed to establish a more robust baseline upon which to draw conclusions regarding the sources of climatic impacts, and outlines fruitful ways for companies to tackle the complexities of climatic emissions that are beyond their control. • In some cases, product service systems can reduce climatic impacts by up to 80%. • In other cases, climatic impacts increase compared to traditional product sales. • Climatic impacts are influenced by use intensity, transportation and production. • Other contextual factors such as the energy mix play a role. • More quantitative assessments are needed with less reliance on estimations. [ABSTRACT FROM AUTHOR]

In recent years, there has been a notable surge in focus on the mitigation of carbon emissions, mostly motivated by the urgent concern about global warming and its adverse impacts on the Earth's climate. Power-to-gas (PtG) systems have emerged as a promising technological solution in the pursuit of mitigating carbon emissions. This paper presents a mathematical modeling framework that aims to accurately represent the power-to-gas system integrated with wind power plants while taking into account the technological constraints of the system in practical scenarios. To analyze the proposed system under the stresses, worst situations caused by existing uncertain parameters, especially wind power, is modeled using a risk modeling technique called downside risk constraints (DRC). The DRC endeavors to mitigate the likelihood of situations resulting in significant stresses by incorporating an expected downside risk into the proposed framework. This paper will provide a number of conservative tactics to be employed in the decision-making process under the realizations of uncertainties. These tactics, including strategic operational control strategies, provide a structured approach for decision-making under uncertain conditions. By incorporating downside risk constraints, the framework enables conservative decision-making that prioritizes mitigating potential losses and minimizing the operational risk within scheduling horizon of proposed PtG facility. The findings demonstrate that the implementation of PtG technology has the potential to yield a substantial reduction in external energy consumption, namely by 39.1 %. Additionally, it has been seen that PtG may effectively mitigate carbon emissions, resulting in a decrease of 38.9 %. The utilization of PtG technology and gas storage will result in a substantial reduction in wind curtailment, ultimately leading to a near elimination of curtailment. Further study is conducted on the model in order to explore the benefits of carbon and methane storage, as supported by the results obtained. [ABSTRACT FROM AUTHOR]

Food, energy, and water, as the basic resources supporting human survival, are fundamental to the sustainable development of humanity. Urban space plays an influential role in promoting the sustainable development of the three resources. As environmental problems such as global warming, ecological destruction, and resource shortages become increasingly severe, there is also a growing recognition of the importance of community as the fundamental component of urban space in sustainable development. In order to systematically understand the impact between food–energy–water nexus and community spatial planning, this paper provides a comprehensive literature review to bridge the current gaps in this area. This paper uses the nexus approach to summarize the trends and results of the food–energy–water nexus research in the community space field from the following five aspects: spatial scale, spatial interface, interactions, synergistic effects, and research methods. The results show that food–energy–water systems in community space are closely related to each other. However, the existing studies mostly focus on resource interaction and environmental impact, and lack of discussion on how food–energy–water nexus affects community spatial planning and its optimization. Finally, based on the current results, this paper proposes a conceptual research framework of the food–energy–water nexus in community space including influential mechanisms, space utilization, disciplinary integration, new technology application, data and methods. Therefore, the major findings of this review highlight the importance of the impact between food–energy–water nexus and community spatial planning and develop a conceptual framework for research. • This paper reviewed the FEW nexus research in the community space field. • It shows that FEW systems in community space are closely related to each other. • Researchers mainly focus on interactions of the FEW but rarely on other constraints. • It summarized new FEW system integration approaches to promote synergistic effects. • A conceptual research framework for the FEW nexus in community space is proposed. [ABSTRACT FROM AUTHOR]

The battery electric vehicle (BEV) industry, commanding over half of the global market share in China, has garnered significant attention in response to escalating concerns about climate change. NCM (LiNi x Co y Mn z O 2) batteries, prized for their high energy density, are pivotal in this industry. However, their production relies on critical metals, posing environmental challenges. Recycling processes aim to address this issue by recovering critical metals from end-of-life batteries. The industry is updating from NCM 111 to NCM 811 batteries to enhance energy density and reduce costs, but the key factors influencing the material flows and environmental impacts remain uncertain. This paper aims to identify the key factors contributing to the potential differences in material flows and environmental impacts introduced by the NCM battery upgrading in China. Following the new energy vehicle sales projections in China until 2035, a dynamic material flow analysis was employed to calculate material demands, recovered amounts, and substitution rates for various upgrading scenarios. The study reveals that the majority of retired batteries until 2035 were sold between 2022 and 2029. Material substitution rates prove to be more sensitive to the upgrading scenario than the lifetime and growth rate of BEVs. Faster NCM 811 penetration results in over 2.5 times more saved cobalt demand compared to additional nickel demand. A life cycle assessment of NCM batteries reveals a 39% lower global warming impact for NCM 811 compared to NCM 111, highlighting environmental benefits from increased energy density and reduced cobalt consumption. The energy density improvement contributed 85%, while the alteration in material composition contributed 15% to the global warming reduction in NCM 811. Recycling emerges as a crucial strategy in mitigating environmental impacts across all categories, particularly addressing eutrophication, previously deemed challenging due to the difficulty in recovering Li 2 CO 3. [ABSTRACT FROM AUTHOR]

Two economic activities have been integrated in southern Brazil: olive cultivation and sheep farming. The favorable edaphoclimatic conditions in the southern region for cultivating olive trees and cultural preferences for the consumption of sheep meat make this integration a valuable strategy. Considering that every activity causes environmental impact and the exploitation of natural resources, new systems that promote sustainable development and the efficient use of these resources become necessary. This paper presents the first study of the carbon footprint of the life cycle of integrating of sheep and olive farming, with the objective to build an inventory based on primary data collected on olive and sheep farms in Brazil, determine the carbon footprint of the conventional and integrated system and estimate the potential for mitigating GHG emissions. The evaluation was performed using the life cycle assessment (LCA) methodology. The study focuses on the detailed analysis of the processes and activities that are responsible for GHG emissions, including enteric methane emissions, methane emissions from manure management, emissions from nitrogen fertilizer use and limestone application and energy consumption. For this, two major scenarios were considered, the first centered around on the traditional olive cultivation and sheep farming systems individually, and the second involved their synergistic integration. The findings indicate that the conventional system is associated with a global warming impact of 6.8 kg CO 2 eq per liter olive oil and kg live weight. In contrast, the integrated system demonstrates a significant mitigation potential of 27.7%, resulting in a reduced global warming impact of 4.92 kg CO 2 eq. This advantage is a consequence of the synergy between the systems, as they now occupy the same area, which allows the sharing of agricultural activities and agrochemical inputs, in addition to optimizing nutrient recycling and complementing each other. Additionally, the results of a sensitivity analysis showed that enteric methane from sheep and the application of limestone to the soil are the most influential parameters on the carbon footprint, indicating that they are key parameters for the development of GHG mitigation strategies, some of which were discussed in the article. • First life cycle assessment of integration between olive and sheep farming in Brazil. • The inventory was constructed with primary data collected in situ. • The study assesses the carbon footprint of the olive and sheep farming system. • The results show environmental advantages of the integration of olive and sheep farming systems. [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]

Pavement life cycle assessments (LCAs) enable decision-makers to evaluate the environmental impact of alternative maintenance, rehabilitation, and reconstruction strategies. This paper explores the viability of deep reinforcement learning (DRL), a framework that enables agents to learn optimal actions within a given situation, to identify environmentally benign pavement management strategies. More specifically, this study utilizes proximal-policy optimization (PPO), a subtype of DRL algorithms, to identify a management strategy that minimizes the expected global warming impact of a pavement facility over its lifecycle. Through an urban Interstate case study, this paper shows that the proposed PPO algorithm identifies management strategies that are anticipated to reduce the expected global warming impact of a pavement facility over its planning horizon by 16 percent relative to traditional practice. Furthermore, the PPO algorithm is able to identify this management strategy in only 25 learning iterations, which is in stark comparison to Q -learning, a common reinforcement learning algorithm, that requires 70,000 learning iterations. The results of this work highlight the viability of DRL to integrate within complex LCA models to determine environmentally sustainable pavement management strategies. • Deep reinforcement learning (DRL) supports the identification of environmentally benign pavement management strategies. • Probabilistic LCA integrates DRL to minimize a pavement's global warming impact. • Proximal policy optimization (PPO) converges to a near-optimal management strategy. • PPO identifies a management strategy where expected GWP is 16% lower than traditional practice. [ABSTRACT FROM AUTHOR]

Climate warming is a common concern around the world. Achieving carbon reduction within the warehouse is a problem that needs to be addressed in the layout of the green warehouse. This paper builds a soft path model to study the impact of the improved systematic layout planning method on carbon reduction in warehouses from a low carbon economy perspective. This paper considers two main warehouse layout factors: logistic and nonlogistic factors. A dual-objective warehouse optimization model is designed by quantifying the relationship between logistic and nonlogistic factors, and the heuristic algorithm is used for simulation optimization. Finally, the functional warehouse area is comprehensively evaluated using fuzzy constraint theory. The results show that the established soft path solution optimizes and improves logistics activities such as internal warehouse layout, material handling strategy, and warehouse management by comparing with the traditional layout method. The efficiency of warehouse operation, warehouse space utilization, and energy are improved. The goal of reducing carbon footprints from the warehouse is thus achieved. It is demonstrated that the soft path solution can minimize warehouse carbon emissions and generate positive synergy in terms of environmental impact. This study enriches green warehouse layout design procedures and provides a facility optimization technique with the potential to minimize warehouse carbon emissions, which can help planners combine other green warehouse management tools to optimize operations and reduce carbon in daily practice. [ABSTRACT FROM AUTHOR]

The construction sector is one of the main contributors to carbon dioxide (CO 2) emission and causes of global warming. CO 2 mitigation solutions are vital. New technologies can facilitate and improve these efforts. Thus, the paper reviews how new technologies of artificial intelligence and machine learning have contributed to CO 2 emissions reduction in construction and what techniques have been applied in the literature to provide significant information that will be beneficial for the construction sector design and management. The paper provides the results of a content review, including their contributions and gaps. A total of 78 papers were identified to develop the dataset. The method was a combination of systematic reviews, including co-occurrence analytical map development of the main keywords, co-authorship network analyses, publication source analyses, and content analysis, including theme identification and review of the selected papers, which were divided into five conceptual clusters based on their scopes: (1) sustainable materials and components design/production, (2) on-site vehicles and equipment, (3) energy and life cycle assessment, (4) optimization, decision-making and solution-based platforms, and (5) real-world monitoring. The content of each cluster of papers was also reviewed, and the potential gaps were identified and discussed. A set of directions for future research investigations were presented that can be a valuable source for researchers in their future research. This paper contributes to the current knowledge base by presenting insights into intelligent techniques in the construction industry to mitigate CO 2 emissions. [ABSTRACT FROM AUTHOR]

Decarbonization is a process that transforms economies to lower greenhouse gas (GHG) emissions per unit of economic output, aiming towards net-zero GHG emissions. This process could also reduce short-lived climate pollutant (SLCP) emissions, including black carbon and methane. They have relatively short atmospheric lifetimes but have large radiative forcing and impact human health. Therefore, reducing SLCPs can improve air pollution and help mitigate climate change. Costa Rica was one of the first countries to have a decarbonization plan, and many others have stated their goal to reach net-zero emissions by around mid-century. However, reducing SLCP emissions as an economy decarbonizes is not guaranteed, and few examples in the literature have assessed how decarbonization impacts SLCPs. This paper estimates the SLCP emission reductions from Costa Rica's decarbonization plan. Through a value chain analysis and the identification of implementation barriers, the paper also evaluates which policy instruments can advance SLCP mitigation in multiple sectors, creating implementation synergy. We find that mitigation measures, by 2050, in the transport, agricultural, solid waste, and industrial sectors avoid 25.2 kt of black carbon emissions (23 times the 2018 emissions) and 2167 kt of methane (15 times the 2018 emissions). However, the country faces financial and governance challenges in each sector that will need overcoming to implement the intended mitigation measures. We identify a comprehensive environmental tax reform, the overhauling of urban regulatory plans, the strengthening of institutional capabilities, and low-carbon investment with favorable financing as crucial cross-sectoral policy synergies that will advance the implementation of SLCP mitigation. • Decarbonizing can reduce and avoid short-lived climate pollutant (SLCP) emissions. • Black carbon and methane (two SLCPs) cause global warming and poor air quality. • Some policy instruments can reduce SLCPs in multiple sectors, causing synergy. • Improved urban planning can favor the mitigation in transport and waste sectors. • Institutional strength and favorable financing are needed to advance mitigation. [ABSTRACT FROM AUTHOR]

Although the carbon reduction role of green finance has been highlighted in the context of global warming, discussions on green finance have primarily focused on size rather than structure. Based on Chinese panel data from 2008 to 2019, this paper distinguishes itself by investigating the relationship between green financial structures and carbon emission intensity from a structural matching perspective using the two-way fixed effect model, system generalized method of moments model, quantile regression, and the mediating effect model. Our findings indicate that a green financial structure can lower overall carbon emission intensity and that an inverted U-shaped carbon emission mitigation effect results from a green financial structure. Additionally, green financial structures alleviate carbon emission intensity by facilitating the development of energy technology. Furthermore, greater degrees of finance-technology matching effectively lower carbon emission intensity. These findings provide lessons for countries striving to construct comprehensive and reasonable green financial systems to address climate change. [ABSTRACT FROM AUTHOR]

The increasing contribution of refrigeration systems to global warming has led to widespread demand for low global warming potential (GWP) refrigerants as alternatives. This paper proposed a comprehensive environmental assessment method for evaluating the carbon footprint of units charged with low-GWP refrigeration. Experimental and numerical studies were used to investigate the carbon footprint impact of using alternative refrigerants at different ambient temperatures in China. Initially, the model was validated through experimental case studies on the use stage of cold storage units. Subsequently, a comparison was made between the cooling capacity (CC) and energy efficiency ratio (EER) of cold storage units charged with different refrigerants. Additionally, the impact of alternative refrigerants in the use stage was analyzed by numerical calculations, and the adaptability of the cold storage unit to the ambient temperature and the national energy structure was also studied. The results indicate that among the four stages of the cold storage unit, the use stage is the hotspot of carbon footprint due to the large amount of energy consumption and the existence of refrigerant leakage and other behaviors. Utilizing low-GWP alternative refrigerants could significantly reduce the carbon footprint of the cold storage units' use stage by 10.56%–16.39%, thereby lowering the whole stage carbon footprint. Furthermore, the ambient temperature and national energy structure could also effectively reduce the carbon footprint of cold storage units' whole stage by 1%–27.17%. Furthermore, after adopting low GWP refrigerants, the life-cycle cost (LCC) of the units have also decreased by 6.1%–12%. Taking into account both environmental impact and economic considerations, it is recommended to directly replace R404A with R448A in the units in regions where the average ambient temperature is above 15 °C. • A carbon footprint evaluation model for the units was established. • Influencing factors of carbon footprint are studied numerically and experimentally. • By GHG assessments, the optimal refrigerant and external conditions were determined. • Alternative refrigerants reduce carbon emissions for cold storage units by 8.8%–24.92%. [ABSTRACT FROM AUTHOR]

The efficient and effective new energy vehicles (NEVs) power batteries recycling (PBR) plays a critical role in reusing scared metal resources, decarbonizing the transport sector and climate warming mitigation. The policy consistency from up to down in a big country lays a solid foundation for sustainable recycling. However, quantitative comparison or evaluation of power batteries recycling policies (PBRPs) from various levels of government is insufficient in the existing literature. In this paper, text mining technology and the Policy Modelling Consistency Index (PMC-Index) model are used to evaluate the longitudinal and horizontal consistency level of China's 13 central PBRPs as well as 25 local PBRPs from 2016 to 2022. The findings demonstrated that: (1) Longitudinally, the local governments present a high consistency level with the central government in the objective and content of PBRPs via comparison analysis of high-frequency words, which embodies the local governments firmly advocating the national strategy for retired battery recycling. (2) Horizontally, the number of central PBRPs with excellent and good consistency is five and seven, respectively, while the number of local PBRPs with excellent and good consistency is six and seven, respectively. One central and twelve local PBRPs are of acceptable consistency, indicating significant disparity in local governments' policymaking ability. (3)The drawbacks of those acceptable policies attribute to the policy tendency of traceability management, policy timeliness, policy content in terms of incentives and business recycling model. Finally, management implications were summarized to optimize China's PBRPs system and PBR performance based on the empirical result, an overview of PBRPs and recycling practices in developed countries. [Display omitted] • We evaluate the China's central and local power batteries recycling policies. • The PMC-Index model is used to quantitative analysis of policy consistency. • The longitudinal and horizontal consistency of battery recycling policies is good. • We outline the power battery recycling policies and practice in the EU and the U.S. • Carbon footprint requirements should be added in China's battery recycling polices. [ABSTRACT FROM AUTHOR]

Soil respiration is the process of decomposition of organic matter in soil and microbial metabolism to produce carbon dioxide. In the context of climate warming and degradation of agricultural soil fertility, it becomes crucial to explore the mechanisms of soil respiration to increase carbon sequestration. In this paper, five biochar applications (0, 3.79, 7.58, 11.36, 15.15 t/ha) and two tillage methods (shallow ploughing, deep ploughing) were set up to explore the mechanism of soil respiration and its temperature sensitivity by studying the effects of tillage methods and different amounts of biochar application on soil properties, soil enzyme activities, soil respiration and its temperature sensitivity during the growing season of soybeans in the black soil area. The results showed that soil respiration rate increased with biochar application in the low biochar application range; the opposite trend was observed for high biochar application beyond the threshold (11.36 t/ha). The application of 11.36 t/ha of biochar amount had the strongest promotion effect on soil respiration, reaching 2.42 μmol m−2·s−1 in the shallow ploughing treatment and increasing 0.32 μmol m−2·s−1 in the deep ploughing compared to the shallow ploughing. The application of biochar significantly increased the activity of nitrogen and phosphorus enzymes and had an inhibitory effect on carbon cycle enzymes; the increased activity of nitrogen and phosphorus cycle enzymes provided sufficient substrate for microbial respiration and thus increased soil respiration, and the decrease in the enzymatic reaction of carbon cycle enzymes led to a decrease in temperature sensitivity. The temperature sensitivity of deep ploughing (2.18–2.59) got a more substantial reduction than that of shallow ploughing (2.34–3.53), which indicates that deep ploughing treatments can better reduce the mineralization of organic carbon than shallow tillage. Meanwhile, the temperature sensitivity of soil respiration reached a minimum with the application of 7.58 t/ha of biochar, which was reduced by 16% under deep ploughing treatment compared to the control, 33% under shallow ploughing treatment compared to the control, and also reduced by 27.27% under deep ploughing compared to shallow ploughing, which suggests that the addition of biochar reduces the loss of carbon to a certain extent. This study is important for assessing the effects of tillage practices and biochar combinations on carbon sequestration in agricultural soils in black soil areas. Note: Upward arrows indicate an increase, downward arrows indicate a decrease, and the thickness of the line characterizes the degree of strength; SP and DP represent shallow and deep ploughing treatments. [Display omitted] • DP applied 7.58 t/ha of biochar reduced Q 10 by 16% compared to the control. • The Q 10 of DP is reduced by 36.29% relative to SP without the application of biochar. • Soil enzyme activity enhances soil respiration but reduces temperature sensitivity. [ABSTRACT FROM AUTHOR]

As countries pay more attention to the issue of global warming, the solution of carbon emission reduction has important practical value. Most of the existing literature studied the driving factors of embodied carbon emissions. This paper creatively focuses on the impact of technological progress on embodied carbon emissions and on the embodied carbon emissions of different technology-intensive manufacturing industries, and aims to find out the important role of technological progress on embodied carbon emissions. This paper constructs a multi-regional input-output model based on the world input-output table, and analyzes and compares the changes in carbon emission intensity and export-implied carbon emissions of G7 countries from 2000 to 2014. This paper introduces the SDA model to investigate the impact of technology effects on the embodied carbon emissions of G7 countries' exports, and decomposes the technology effects into carbon emission technology effects and intermediate production technology effects. This study divides the manufacturing industries into low-tech, medium-low-tech, medium-high-tech and high-tech industries, and aims to examine the impact of technological progress effect on manufacturing with different levels of technology intensity. The empirical results reveal that, first, the carbon emission technical effect and the technical effect of intermediate production together constitute the technical effect. The carbon emission technology effect has a significant effect on suppressing the embodied carbon emissions of exports, while the impact of the intermediate production technology effect is relatively small, and the direction of action is uncertain. Second, the overall technological effect reduces the embodied carbon emissions of G7 countries' exports, and offsets the embodied carbon emissions brought about by the scale effect to a certain extent. That is, technological progress can effectively reduce the embodied carbon emissions of exports. Third, technological effect has the most significant effect on the low- and medium-tech industries, and the low- and medium-tech industries are also the manufacturing industries with the most embodied carbon exports in G7 countries. Relevant policy recommendations for global carbon emission reduction are put forward at the end of this paper. [ABSTRACT FROM AUTHOR]

Global warming is a global and critical challenge and car manufacturers pledge to reduce their carbon footprint. It is mandatory to assess the carbon footprint of current and upcoming vehicles to achieve these self-set and quantified targets. Life Cycle Assessment (LCA) is a standardized and scientifically acknowledged method to quantify a product's or company's environmental impact. Due to the complexity of a vehicle's cradle-to-gate phase, automation of LCAs is a suitable simplification strategy by importing product information and automatically assign them to pre-defined life cycle inventory (LCI) models. The data acquisition is a recognized issue, but the LCI modelling is hardly discussed in the literature for automated LCAs even though it has a significant influence on their accuracy. This paper presents an approach to elaborate an LCI model construct that enables consistent and efficient automated LCA while maintaining defined accuracy and applicability in commercial LCA software. Such an LCI model construct and its derivation are presented in this paper for automotive aluminium components considering sheet components, casting components and extrusion profiles. It is mandatory for a precise calculation to take the most influencing parameters into consideration. Grid points for each of these parameters are elaborated dependent on the characteristic if the parameter is continuously or discretely variable. The resulting LCI model construct makes this most influencing parameters customizable in an automated LCA. A generic method for the design of such an LCI model construct based on the findings of the use case was derived in this paper. The application of this methodology is not limited for vehicle's LCAs and carbon footprint, but other complex products and impact categories to enable efficient, consistent, and accurate LCA results for complex products. [ABSTRACT FROM AUTHOR]

Global warming caused by the excessive combustion of fossil fuels has become the focus of the international community. China's carbon emission reduction policy plays a vital role in international climate change, carbon emission neutrality and domestic environmental pollution control. This paper summarises the progress of China's Emission Trading Scheme (ETS) pilots from 2011 to 2021, including trading volume, carbon emissions price, and the effect of carbon emission abatement. By calculating the carbon emissions intensity decrease rate of China's ETS pilot and non-pilot regions, the ETS and carbon emissions tax are compared in terms of emission reduction effectiveness, emission reduction cost and implementation resistance to provide theoretical support for the Chinese government to select and develop carbon emission reduction tools. The development of the Clean Development Mechanism in China is also compared with China Certified Emission Reduction (CCER), and the offsetting rules of CCER are summarised. After the whole analysis and assessment, the results show that from 2013 to 2018, the average carbon emissions intensity decline rate in the ETS pilots was 7.3% and that in non-pilots was 4.29%. Some problems of China's carbon emissions trading market are also concluded. The trading volume is small (only 43.4 × 106 t in 2020) and is discrepant greatly in the different ETS pilots. The carbon emissions price is low (only 33.45 Yuan/t in 2020), with high volatility and large price differences among the ETS pilots. Based on the existing problems, this paper proposes some suggestions for improving China's emission trading market and provides theoretical and decision-making support for promoting carbon emission reduction and neutralisation for China. [Display omitted] [ABSTRACT FROM AUTHOR]

Tourism places pressures on the environment through the services provided (accommodation, food, leisure activities, and transport), meanwhile it is particularly vulnerable to global warming as climate is a crucial component of destinations' attractiveness. As a result, research focusing on the impacts of tourism has increased significantly. Practitioners consult a plethora of frameworks and publications to environmentally assess tourism but none of the existing guidelines provides specific recommendations making difficult to obtain reliable results that can be properly replicated and compared. This paper discusses the use of Footprint family indicators in tourism through a review of studies that measure the Water, Carbon, and Ecological Footprint of tourists. Results show a lack of specific data, and an absence of consensus about the system boundaries and methodologies used for calculation. Food production and transportation are the main drivers of environmental burdens. The Footprint indicators help to understand the trade-offs between environmental effects which can be used to prioritize sustainability efforts in the tourism industry. Additionally, this study presents a critical analysis of the influence on the trip's Footprint of the services provided to different rated tourism experiences (high, medium, and low rated) and offers a reflective comparison on the pressure exerted by visitors and the local population. • Tourism Footprint studies lack trustworthy datasets due to gaps in specific data. • Lack of consensus on boundaries in tourism Footprint studies hinders result comparison. • Tourism Footprint studies generally ignore end-of-life environmental impacts. • High-rated vacations impose the highest environmental burdens. • Tourists exert more pressure on natural resources and ecosystems than residents. [ABSTRACT FROM AUTHOR]

Cement industry is one of the largest contributors to greenhouse gas emissions accounting for about 7% of global CO 2 emission. As global cement demand continues to rise exponentially, the industry is taking numerous effective steps to meet net-zero emission targets by limiting global warming to 1.5 °C by the end of the century and improve the ecological system. Worldwide, about 2.9 billion tons of CO 2 were emitted in 2021 from cement production and the industries are expected to achieve the net-zero target by 2050. The reduction of CO 2 emission remains a major challenge for the cement industry as the manufacturing processes and the current infrastructure allow little margin for the reduction in CO 2 emission, considering the age-old and conventional Portland cement chemistry. To achieve a net-zero emission target, several effective measures are being explored to mitigate CO 2 emissions from cement industries, viz., use of alternative fuels, reducing clinker-to-cement ratio, improving energy efficiency, carbon capture, utilization, and storage (CCUS) techniques etc. Apart from these, production of low-carbon cement different from Portland clinker chemistry has the potential to make a big difference in mitigating CO 2 emission. Carbonatable calcium silicate-based cement, is found to be a promising alternative to OPC and reduces about 70% of total CO 2 emission from cement production. This paper thoroughly reviews the different low-carbon emission approaches (both direct and indirect) such as reducing clinker factor, lowering the clinkerization temperature by using fluxes and mineralizers (such as CaF 2 , BaO, SnO 2 , P 2 O 5 , Na 2 O, NiO, ZnO etc), producing low temperature clinker, use of supplementary cementitious materials (SCMs) in concrete and capturing the emitted CO 2 through mineral carbonation, direct air capture (DAC) etc for future alternative low-carbon cements. Various commercialized technologies for reducing CO 2 emissions (CarbonCure, Solidia, Heidelberg, Novacem, Carbicrete and CO 2 -SUICOM) with their technology readiness levels (TRLs) are also discussed. [Display omitted] • Focus on reviewing major strategies to mitigate the carbon footprint of cement industry. • The CO 2 reduction potential of various low-carbon cements are discussed. • The status of various commercialized CO 2 utilization technologies are further discussed. [ABSTRACT FROM AUTHOR]

Global warming may cause the average atmospheric temperature to exceed 2 °C by the end of this century, instigating climate change and adversely affecting human lives. Emissions of carbon dioxide (CO 2) should be reduced to overcome the problems of global warming and climate change. The applications of negative emission technologies (NETs) are proposed to reduce terrestrial CO 2 and are identified as one of the prominent options for the energy system transition. Most negative emission technologies require energy to function, which has to be produced from additional energy sources. Understanding the interdependence of the energy sources and NETs for planning the carbon-constrained energy sector is essential. A novel graphical approach, founded on the concepts of Pinch Analysis, to decarbonize the energy sector is purported in this paper. The proposed method determines the minimum integration of negative emission technologies required to attain the allowed CO 2 emission limit while satisfying the energy demand. Four different examples are used to show the applicability of the suggested approach with different NETs: carbon capture and sequestration (CCS), bioenergy with carbon capture and storage (BECCS), and direct air capture (DAC). In these examples, renewable-based energy sources, fossil-based energy sources, as well as energy-producing negative emission technologies are used as compensatory energy sources. The proposed graphical approach has the potential to be used as a planning tool to decarbonize the energy sector involving interdependent energy sources and NETs. [Display omitted] • Negative emission technologies help decarbonize the energy sector. • Identified dependence between the energy sector and negative emission technologies. • A graphical method is proposed to integrate negative emissions technologies. • Determined minimum compensatory energy for adopting negative emission technologies. • The proposed graphical approach provides insight into the overall systems planning. [ABSTRACT FROM AUTHOR]

Global warming can be solved with carbon trading. When carbon emissions become a commodity, it can be a powerful motivator for companies to optimize production capacity and innovate technologically. The goal of this paper is to examine the way in which China's carbon emissions trading policy (CET) influences firm technological innovation in seven pilot regions, using a sample of firms in eight high-carbon industries. We employ difference-in-difference (DID) as well as DID-based propensity score matching (PSM-DID) models to investigate the influence of China's carbon emission policy on firms' technological innovation by using 4745 observations of 749 A-share listed firms in eight high-carbon industries in mainland China from 2007 to 2021. According to the findings, China's CET policy significantly boosts firms' technological innovation, and this beneficial effect persists even after a series of robustness tests that change the policy's implementation year and the technological innovation measure. Further analysis shows that this positive effect is heterogeneous across high-carbon industries and firms with different ownership. In addition, based on the external governance perspective, we find that CET policy performs better in firms in high-carbon industries with a sizable portion of ownership held by institutional investors. This study suggests the effectiveness of CET policy in promoting firms' technological innovation, confirms empirical evidence for Porter's hypothesis, and provides a basis for Chinese firms to achieve their emission reduction targets by improving technological innovation. [ABSTRACT FROM AUTHOR]

Climate models and decarbonization scenarios use carbon budgets to distribute emission allowances and derive reduction targets for sectoral developments to limit global warming. These requirements are often not aligned with corporate climate targets due to missing targeting approaches for sectors and scopes as well as differences between absolute and intensity targets. Therefore, the aim of this paper is the development of an allocation scheme by combining frameworks for CO 2eq accounting like the ISO 14040, the Greenhouse Gas Protocol and the IPCC Guidelines for inventory accounting to link sectoral carbon budgets to stages of product life cycles and vice versa. To calculate carbon budgets and reduction targets, a case study for the automotive industry is conducted. Consequently, average data sets of emission reporting, studies and LCAs for material compositions, forecasts on vehicles sales and the shares of electrified products are used. Depending on the applied decarbonization scenarios, different reduction trajectories aligned with pathways to limit global warming well below 2 °C and respectively to 1.5 °C are determined. As a result, the company has to reduce their absolute emissions from 2019 to 2030 by −25% to −46% equal to an intensity target of −32% to −51%. • Corporate climate targets need to be aligned with carbon budgets based on climate scenarios. • Combining life cycle management and reporting frameworks enables a method to derive sectoral decarbonization pathways. • For the automotive industry, a case study aligned to different decarbonization scenarios from IEA and IRENA is conducted. • Efforts to reduce GHG emissions by −25% to −46% from 2019 to 2030 on absolute level are required. [ABSTRACT FROM AUTHOR]

Global warming, climate change, and resource depletion have forced us to reconsider energy usage and efficiencies over the last few decades. Residential and commercial buildings are both large energy consumers, so improving energy and material usage efficiency in this sector is a common research topic. According to a recent study, the Building Sector (BS) accounts for 40% of greenhouse gas emissions. The primary objective of this paper is to examine and assess the potential of Renewable Energy Systems (RES) and their combinations for enhancing energy efficiency in the BS. Specifically, the focus will be on converting low energy-efficient buildings into highly efficient ones. The potential of the RES and their combinations for the BS is evaluated based on payback durations, energy generation, and reduction of CO 2 emissions. The optimization flow charts for the RES, feasibility studies, commercialization road maps of energy storage systems and the necessity of control mechanisms for enhancing RES efficiency were discussed. Additionally, the technology drawbacks are discussed, along with various innovative techniques recommended to direct future study in this area. Finally, this article assists the audience clear idea in the selection of the right combination of potential RES based on different conditions to achieve deep decarbonization in BSs. • Buildings sector (BS) responsible for 40% of GHG emissions. • Study assesses potential of Renewable Energy System (RES) in BS. • RES evaluated on payback, energy generation, and CO 2 reduction. • Optimization, feasibility and commercialization studies were discussed. • Article recommends right RES combinations for deep decarbonization in BS. [ABSTRACT FROM AUTHOR]

With the confluence of rapidly continuing economic development and increasing greenhouse gas emissions, the frequency and severity of natural disasters caused by global warming have increased in recent years. The international Financial Stability Board established the Task Force on Climate-Related Financial Disclosures (TCFD) to provide recommendations for collecting and disclosing climate-related information that is helpful for decision-making such that investors, decision-makers and supervision units can understand and more accurately assess climate-related risks as well as opportunities. However, the TCFD recommendations only provide a general framework of risks and opportunities from which companies cannot derive specific disaster-related data for regional climate disclosures. For stakeholders in different continents and regions, there is a need to develop a disaster data-driven model that can precisely disclose regional risks. Our study develops a regional climate framework for TCFD based on natural language processing that can process and analyze data from historical local news. The paper aims to offer suitable climate recommendations for different regions and suggest possible preventive measures and responses to emergencies caused by various disasters. The contributions of this research contain: (1) using unsupervised learning to present climate change in a quantitative way; (2) helping enterprises adjust sustainable strategies according to conditions in different regions; (3) extending involvement from a small area to a large area, quantifying climate data so that investors can make decisions based on factual results; (4) combining artificial intelligence with climate change in the field of TCFD. [Display omitted] • We develop a data-driven regional climate framework for TCFD based on deep learning. • This framework can help enterprises minimize risks along with costs and can be applied to other industries. • This research supplements quantitative information in TCFD and provides a scientific climate risk management method. • The first study that applies artificial intelligence to climate change in the field of TCFD. [ABSTRACT FROM AUTHOR]

Metallized textiles are novel materials that can be used in high value added functional goods, such as Assistive Technologies (AT) products. Potential issue with innovative metallization of textiles is the toxicity and environmental impact of the substances used in the process. To investigate this issue, this paper utilizes an original methodology of linking the analysis of toxicity of chemicals used in the textile metallization with Life Cycle Assessment (LCA) of the metallization process itself. This is done from the perspective of three relevant impact categories: global warming, toxicity and water use, for which, three methods were selected: IPCC et al., 2013 GWP 100a; USEtox 2 and Available WAter Remaining (AWARE). The LCA uses a mix of primary and secondary data and three cradle-to-gate scenarios were chosen for calculating results - first presenting just the metallization process itself, second taking into account alternative impregnation process and third including metallized surfaces - woven cotton and polyester. While the most toxic chemical identified was formaldehyde, the results of the LCA shows top processes contributing to global warming is the electricity consumption, the use of polyurethane with 0.996 kg CO 2 eq. and EDTA with a result of 0.816 kg CO 2 eq. The greatest impact on human toxicity and freshwater ecotoxicity comes from copper (II) chloride mostly used in the plating phase. Moreover polyurethane used in the impregnation phase leaves the largest water footprint of 0.984 m3. When taking into account the metallized surface scenario, the impact of cotton was high for global warming and water use and the impact of polyester was relatively low for all impact categories. The main conclusions of the research relate to the identification of cleaner production methods that could reduce the environmental footprint of the metallization of textiles. They include, among others: development of technology that can significantly increase resource productivity through selective metallization of conductive tracks; use of alternative formaldehyde-free and polyurethane-free chemicals; use of a closed loop system for water remaining in the technological process. [ABSTRACT FROM AUTHOR]

Sustainability is one of the major issues faced by the concrete industry due to the high CO 2 emissions caused by cement production. Although most of the conventional mix-design approaches account for requirements in the fresh and hardened states, along with durability criteria, sustainability is a new key parameter that must be evaluated in concrete production. This paper focuses on disseminating the environmental concerns related to cement, highlighting the importance of using alternative materials as cement partial replacement. Moreover, advanced mix-design techniques must be used to further enhance concrete eco-efficiency; hence, an overview of the different types of particle packing models (PPMs) is presented. Combining PPM with limestone fillers as an alternative ready-to-apply method to produce eco-efficient mixtures is then proposed enabling concrete future competitiveness as a sustainable material. Finally, a brief discussion on the fresh and hardened performance of sustainable concrete along with its global warming impact is conducted. • Producing eco-efficient concrete mixtures. • Advanced mix-design methods to improve concrete sustainability. • Alternative Materials to produce sustainable concrete. • Use of Particle Packing Models to manufacture concrete. • Evaluation of concrete Global Warming Potential. [ABSTRACT FROM AUTHOR]

Global warming is a serious problem presently faced by human society, and CO 2 is a major concern as a greenhouse gas (GHG), especially as the amount of atmospheric CO 2 has been steadily increasing in recent years. Multi-depot model of vehicle routing has sparked widespread interest among researchers as an effective means of reducing cost comprising carbon emissions, fuel consumption, vehicles rental, and driver salaries. In this paper, we developed an improved adaptive large neighborhood search (ALNS) algorithm to efficiently solve large-scale instances of the multi-depot green vehicle routing problem with time windows (MDGVRPTW), based on the characteristics of the multi-depot model, and the formulation of carbon emissions from customers. For the destroy operation, three problem-specific destroy operators that took advantage of the structure of the multi-depot model and the calculation formula of carbon emissions, were deliberately tailored for the MDGVRPTW. The operators could rapidly remove customers causing significant carbon emissions, which enabled these customers to be better positioned in future repair operations. For the repair operation, a noise-greedy repair operator was proposed to enhance the diversification capabilities of the ALNS. Additionally, two methods for speeding up the repair process were proposed to improve computational time. Computational experiments revealed that the proposed ALNS algorithm exhibited a significant improvement in calculation speed and accuracy compared with existing algorithms. • Multi-depot green VRPTW (MDGVRPTW) to reduce emissions and economic cost is studied. • Improved adaptive large neighborhood search (ALNS) is devised for larger-scale MDGVRPTW. • Three novel destroy operators and two speeding-up repair methods are developed. • Accuracy is improved by 17.94% on average compared to classic ALNS. [ABSTRACT FROM AUTHOR]

While concrete mix design has typically focused on the development of low-cost concretes that achieve a particular set of material characteristics, it is now becoming increasingly important to consider environmental impact. This is a challenging problem because concrete mix design, particularly when involving waste materials, is impacted not only by the concrete mix performance but also on material availability and local variation in chemical composition. This variation impacts material performance, financial cost and environmental sustainability. This paper presents a generic framework for mix design optimisation based on a material design and profiling tool coupled with an optimisation algorithm. The framework is then demonstrated for geopolymer concrete (GPC) using a new data-driven mix design tool based on an artificial neutral network to predict mechanical properties (compressive strength and slump) coupled with life-cycle assessment and financial models to quantify mix performance. Together these inputs are used as the basis for single and multi-objective optimisation using a genetic algorithm as part of set of scenarios examining the impact of regional scale transportation scenarios and the chemical composition of binders on the resultant mix properties. The framework's implementation for GPC enabled up to a 50% reduction in CO 2-eq emissions compared to equivalent strength experimental mixes, and demonstrated that for a given strength, slump and transportation case the overall CO 2-eq emissions can increase by up to 30% where multi-objective optimisation is used (financial and CO 2-eq emissions minimization) when compared to minimization of CO 2-eq emissions alone. • A mix optimisation framework is shown considering environmental and financial impact. • The framework is demonstrated for geopolymer concrete using demonstration scenarios. • Trade-offs are shown between environmental and financial objectives. • Results show the importance of material chemical composition and transport distance. • Implementation of the framework yields significant reduction in emissions. [ABSTRACT FROM AUTHOR]

Droughts resulting from global warming severely hamper the healthy development of terrestrial vegetation ecosystems. This paper defines a terrestrial vegetation ecological drought index, i.e., the Standardized Water Supply–Demand Index (SSDI), based on the water balance method using the same calculation model as the SPEI. The theory of run is used to analyze the spatial and temporal distribution of the drought characteristics in the Yangtze River Basin (YRB). The results show that (1) the drought events monitored by the SSDI were in good agreement with historical drought events, and the correlation coefficient between SSDI and NDVI (0.94) was significantly higher than that between SPEI and NDVI (0.88). (2) About 55.4% of the regions in the YRB experienced more than 13 droughts, and about 41.4% of the regions had an average drought duration of more than 3.1 months. In the northern part of the YRB, droughts tend to develop in a short-term high frequency, while in the southern part of the YRB, there is a long-term low-frequency development trend. Nearly 24.5% of the regions have an average drought intensity of more than 1.4, and most of them are located in the lower reaches of the Yangtze River. (3) Over the last 18 years, about 79.5% of the regions in the YRB showed an increasing trend in SSDI, of which 36.8% showed an increasing trend of more than 0.04/yr. In addition, 40.4% of the regions showed a significant upward trend. Precisely analyzing the spatiotemporal variation of drought characteristics in the YRB is critical for drought risk assessment and sustainable development of water resources and could provide a theoretical basis for effective water resource allocation and drought relief. • A new drought monitoring index, i.e., the Standardized Water Supply–Demand Index (SSDI) was defined. • SSDI can effectively monitor drought events. • SSDI is more suitable for monitoring ecological drought. • Drought of vegetation ecosystem in the Yangtze River Basin was assessed and analyzed with the SSDI. • It provides a theoretical basis for drought management and water allocation in the Yangtze River Basin. [ABSTRACT FROM AUTHOR]

Global-level warming largely influences drought dynamics. Therefore, a robust drought projection is critical to support sustainable development under a future warming climate, especially at the regional level (i.e., South Asia). Encouraged by the Paris Agreement, this study investigates the changes in the intensity, area, and duration of future droughts under 1.5 °C, 2.0 °C, 3.0 °C, and 4.0 °C global warming levels over South Asia. In this regard, seven global climate model outputs under seven newly designed climate change scenarios (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0, and SSP5-8.5) from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) are used. The standardized precipitation evapotranspiration index (SPEI), self-calibrating Palmer drought severity index (scPDSI), and intensity-area-duration (IAD) method are adopted to characterize drought. Drought events are identified considering an area coverage greater than 50,000 km2 for predefined drought durations of 3- (short-term), 6- (medium-term), and 12-month (long-term). A significant drying trend is seen and tested against the two-sample t -test. Notably, to represent the more concrete picture of changes in drought characteristics, the results based on two indices (SPEI and scPDSI) are combined (average) in this paper. The results reveal that droughts with higher-intensity, and long-term duration will increase with continued warming. As drought features, the number of long-term droughts will increase by 21.5% (highest), and the leading area coverage is also estimated (>7%) for long-term drought at higher warming (i.e.4.0 °C) than the reference period (1995–2014). Furthermore, drought events with large-area (>3 × 105 km2) coverage are projected to become more frequent. For drought severity, extreme drought events and associated area coverage are more likely to unfold over the region. However, overall drought conditions are inclined to worsen under higher warming, especially 4.0 °C warming. Importantly, for global warming targets set by the Paris Agreement (1.5 °C and 2.0 °C), drought conditions will be more acute at 2.0 °C than at 1.5 °C. Spatially, a significant drying trend is mainly observed in the western part of South Asia (Southwest-Northwest) according to both drought metrics (SPEI and scPDSI). Notably, NW will experience acute droughts under all warming levels. Droughts in this region will be mainly influenced by the combined effect of decreasing precipitation and escalated evapotranspiration. As global warming increases, a significant increase in PET and temperature is found over South Asia. In addition, the model evaluation shows that the CMIP6-Global climate models (GCMs) are capable of satisfactorily reproducing climate variables and drought events in South Asia. However, our study's findings strongly support the execution of the Paris Agreement target and provide a scientific basis for articulating drought adaptation measures at the regional scale, especially in South Asia. • Intensity-Area-Duration approach is used to analyze future drought over South Asia for 1.5oC - 4.0oC warming. • The modified Penman-Monteith method (considering CO 2) are adopted to estimate PET. • Overall drought conditions will worsen under 4.0oC warming. • The Northwest of South Asia is inclined to be affected by intense drought in the future. [ABSTRACT FROM AUTHOR]

Given the severe global warming situation, it is very important to explore the factors influencing carbon emission intensity and accurately analyze the trends in the development of carbon emission intensity to achieve the goal of reducing carbon emissions. In contrast with the existing research, this paper starts from the perspective of carbon emission efficiency, applies stochastic frontier analysis to screen the factors influencing carbon intensity, and constructs a model for predicting carbon emission intensity based on factor analysis and an extreme learning machine. The results suggest that, first, there is a high correlation between carbon emission efficiency and carbon emission intensity. Second, the level of economic development, industrial structure, urbanization level, and government intervention all promote a reduction in carbon emission intensity. The structure of energy consumption and dependence on foreign trade restrain reductions in carbon emission intensity. Finally, the proposed model accurately predicts carbon emission intensity. The research results provide theoretical support for the development of technologies to reduce carbon emissions. This idea can be applied to predict carbon emission intensity in different regions and has practical significance. [Display omitted] • Carbon efficiency is related to carbon intensity. • Indicators of carbon efficiency work in reverse on carbon intensity. • Energy consumption and foreign trade restrain the reduction of carbon intensity. • Economic, industrial, urbanization and government promote the reduction. [ABSTRACT FROM AUTHOR]

This paper estimated the environmental performance and primary energy consumption of a newly installed large-scale solar photovoltaic system of 37.57 MW dc in Bidor, Malaysia using the process-based life-cycle assessment approach. The mid-point and end-point impact categories were evaluated, and seven relevant indicators related to energy and global warming were determined. The global warming impact and energy payback time obtained were 30.95 g CO 2 -eq/kWh and 3.43 years, respectively. Furthermore, the global warming impact mitigation potential attained was 811 kilo metric tonne (ktonne) CO 2 -eq throughout the system lifetime. Analyses of contribution, sensitivity and uncertainty were performed to i) identify photovoltaic system components that substantially consumed primary energy and impacted the environment, ii) evaluate the effect of four key parameters, namely irradiation, performance ratio, system lifetime and electricity mix on the energy and global warming-related indicators, and iii) estimate the uncertainty range of the evaluated indicators. The results highlighted that the main contributor to the indicators is the photovoltaic module. Other significant contributors are the civil work and operational and maintenance but the contribution from these components is much lower than the photovoltaic module. Besides that, the cumulative energy demand, energy return on investment, global warming impact and global warming impact mitigation potential showed an improvement when extending system lifetime from 15 to 40 years, i.e. from 0.8136 to 0.3677 MJ, 4.61 to 11.25, 55.37 to 24.99 g CO 2 -eq/kWh and 407.36 to 1055.78 g CO 2 -eq respectively, except for energy payback time and global warming payback time, i.e. from 3.26 to 3.55 years and 1.42 to 1.71 years respectively. • A life-cycle assessment of a real large-scale solar photovoltaic system is performed. • Extending lifetime of the system marginally increases the energy payback time. • The GW impact is about 19 times smaller than the Malaysian grid emission factor. • PV module is the major contributor to total primary energy consumption and GW impact. • BOS and O&M have a moderate share for primary energy consumption and GW impact. [ABSTRACT FROM AUTHOR]

Wood pallets play a critical role in the movement and storage of goods worldwide. They are an important component in the complex global supply chain and used by almost every industry. It is therefore important to assess the environmental implications of the wood pallet supply chain and identify optimization strategies that can be implemented. In this paper, primary 2018 annual production data collected from U.S. pallet manufacturers were used to develop the first industry-average life-cycle inventory (LCI). A new functional unit was proposed to perform a more refined and accurate environmental life-cycle assessment of the wood pallet supply chain. Using the LCI data developed, a cradle-to-grave industry-average life-cycle impact assessment was performed. This novel approach quantifies environmental impacts of a generic multi-use pallet, including repair and remanufacturing. The total global warming impact was 10.4 kg CO 2 e per 45.4 t of pallet loads of product delivered using wood pallets. The manufacturing stage contributed the most, about 35%, followed by the raw material supply stage. About 41% of total primary energy consumption was from renewable sources, with most sourced from biomass. Fossil fuels comprised about 52% of the total (225 MJ per functional unit) primary energy consumption. Total environmental impact was significantly affected by two main parameters: reference service life and load-bearing capacity. Pallet repair was also found to be an important component of the wood pallet supply chain, which has a low environmental footprint compared with the overall impact of a pallet and enables mitigation of overall impact by extending the reference service life. At end-of-life, common industry practices demonstrated substantial potential environmental benefits that can minimize overall environmental impact. The first industry-average wooden pallet life-cycle assessment based on a novel primary dataset. A unique functional unit developed based on pallet characteristics and load-carrying capacity. Global warming impact was 10.4 kg CO 2 e per functional unit. Raw material supply and manufacturing stages dominated the environmental impacts. Scenarios analyses showed the importance of repair and end-of-life pathways. [ABSTRACT FROM AUTHOR]

Concrete is responsible for a significant share of global GHG emissions, which can be mainly ascribed to the production of clinker. Alkali-activated concretes have been investigated in literature as a possible alternative, but the sustainability still appears reduced by the high embodied energy of chemicals typically used for the activation step. This paper investigates concrete belonging to strength classes 35, 50 and 70 MPa and produced with a silicate activator derived from waste glass (AABR). Through a Life Cycle Assessment (LCA), the investigation aims to compare the AABR to Ordinary Portland Cement (OPC) concrete and alkali-activated concrete produced with commercially available chemicals (AABC). The effects produced by the variations of some key parameters (impact allocation of precursors, energy mix, amount of activator in the concrete, distance of procurement of raw materials) over the total impact of the AABR are also investigated. Results show that the adoption of alkali-activated concretes instead of OPC concrete allows a significant reduction in environmental categories of global warming (averagely 64% reduction for AABC and 70% for AABR), acidification potential (averagely 23% for AABC and 35% for AABR), and terrestrial eutrophication (averagely 53% for AABC and 60% for AABR). In addition, the study evidenced that the use of waste glass-based activator allows a significant reduction in every environmental category when compared to the use of commercially available chemicals. • LCA was carried out on alkali activated concrete with waste-derived activator. • Comparisons to OPC and AAC with commercial activators were performed. • AAC with waste activator allows 70% reduction of global warming. • Waste derived activator has lower impacts than commercially available chemicals. • Impacts of key parameters from the use of waste-derived activator were assessed. [ABSTRACT FROM AUTHOR]

Cyanobacterial blooms under global warming are increasing worldwide, producing emerging contaminants, which threaten the health of human beings and aquatic ecosystems. The health burdens warrant the development of a useful risk-assessment tool and a holistic preventive-control scheme to prevent cyanobacterial blooms. This paper aims to integrate cyanobacterial risk assessment and risk preventive control by investigating the relationships amongst cyanobacterial blooms and multi-dimensional influencing variables. Two challenges hinder such a task. First, the time-series variations in cyanobacteria and influencing variables are uncertain and nonlinear. Second, there rarely exists an explicit modelling framework for integrating cyanobacterial risk assessment and risk preventive control. This study builds an extended Bayesian network model and proposes an integrated framework with functions of assessment, inference, preventive control, and visualisation of the risk of cyanobacterial blooms. Field data from a tropical lake are used to evaluate the model and framework. The proposed model achieves better performance than the seven models in comparison. The cyanobacterial risk is anticipated to increase by 38.5% under global warming. On the contrary, guided by the model and framework, the risk could be reduced by about 60% by taking the identified risk preventive control scheme. The cyanobacterial risk prevention would reduce aquatic emerging contaminants in drinking and recreational water sources. [Display omitted] • The cyanobacterial multivariate system was modelled by an extended Bayesian network. • The risk assessment and preventive control of cyanobacterial blooms were integrated. • The proposed model achieved better performance than the seven models in comparison. • The cyanobacterial risk was anticipated to increase by 38.5% under global warming. • The risk was reduced by about 60% if taking the proposed preventive-control scheme. [ABSTRACT FROM AUTHOR]