Search

Paper products are carbon-intensive and having a huge potential for carbon reduction due to their biomass-oriented characteristics. A uniform standard for total carbon footprint (CF) accounting is vital. However, the existing standards have not yet been unified. Inconsistencies between standards cause difficulties in their use and significantly weaken the credibility and comparability of the carbon footprint of a product (CFP). This work rethought the three most widely used standards (Publicly Available Specification 2050 (PAS2050), Product Life Cycle Accounting and Reporting Standard (GHG Protocol), and Product Life Cycle Accounting and Reporting Standard (ISO14067)) from the life-cycle perspective, and established a more appropriate and comprehensive CF accounting standard for paper products (CFASPP). Sanitary pads were selected as a case study to illustrate the discrepancies between PAS 2050, the GHG Protocol, ISO 14067, and CFASPP, for which the annual production CF results were 1424.60, 1481.08, 1453.57, and 1427.04 tons of carbon dioxide equivalent (CO 2 e) respectively. The main reasons for the different CF results were the cut-off criteria and the inclusion or exclusion of carbon storage, delayed emissions, and energy recovery. Each element increased or decreased 22.57 (carbon storage), 29.96 (cut-off criteria), 10.4 (delayed emissions), and 27.52 (incineration with energy recovery) tons of CO 2 e in the results. With increasing demand, these discrepancies will become increasingly significant and may lead to corporations shouldering more or less carbon emission responsibilities by selecting different standards, which will challenge the fairness of product carbon neutrality management. CFASPP covers all paper product life-cycle stages and places greater emphasis on the aspects of carbon storage, delayed emissions, and energy recovery in incineration, which cannot be ignored for the CF accounting of paper products and other biomass-oriented products. This study aims to provide a more applicable and comprehensive guide for corporations to evaluate the CF of paper products, and to provide a reference for the construction of a carbon-neutral evaluation system. [ABSTRACT FROM AUTHOR]

The urgent challenge of reducing industrial greenhouse gas emissions has created a growing demand for a more comprehensive understanding of how various technology options can contribute to achieving carbon neutrality. Energy efficiency has long been regarded as a key pathway in this context, but the volume and diversity of efficiency options has resulted in an unclear understanding of their combined impacts. In this study, we present a novel technology-explicit method to estimate the overall abatement potential associated with a comprehensive suite of 115 energy efficiency technologies spanning all relevant sector processes and energy types. By applying our flexible analysis framework to a case study of the Canadian pulp and paper sector, we demonstrate that energy efficiency could be the single largest contributor to achieving a carbon-neutral target for the sector. We find that efficiency can reduce emissions by 4.92 MtCO 2 e/yr (66%) relative to business-as-usual by 2050 at a weighted average abatement cost of -$162/tCO 2 e when accounting for capital, operating, maintenance, and energy costs. Abatement at the energy system-wide level is even larger, reaching 6.67 MtCO 2 e in 2050 when accounting for upstream effects. Adoption of the full suite of efficiency measures could materially improve the competitiveness of the sector by reducing energy and carbon costs. On the whole, our results suggest that proven energy efficiency technologies could be the primary element of a credible low-cost pathway towards achieving a target of carbon neutrality for the pulp and paper sector. [ABSTRACT FROM AUTHOR]

Carbon footprints (CFs) are the measure of extent of green house gases (GHGs) emitted from any organization or activity. Reporting of extent of CFs in terms of CO 2 e from educational campus may be considered as a first step towards sustainable educational practices. The present study employs a bottom up approach where CFs due to consumption of resources from each academic department is evaluated separately and net is obtained by adding contributions from individual departments. This method has the advantage of avoiding the potential overlaps in the calculation. Hence this approach to calculate carbon footprints can lead to their precise CF evaluation. In order to justify above hypothesis, CF evaluation was carried out at Shikshana Prasarak Mandali's Sir Parashurambhau College, Pune for three consecutive years starting from 2015 to 2016. The average carbon footprints over the study period were 3630.57 ± 296.79 tones CO 2 e per year with per capita emission of 0.81 ± 0.06 tones CO 2 e. The emission density determined from the average value was found to be 0.0361 ± 0.0029 tCO 2 e m−2 of the campus. It was observed that emission sources classified as scope-1, scope-2 and scope-3 contribute 28%, 48% and 25% respectively to total emission. Out of all the emission sources identified, apart from human contribution through respiration, electricity (35%), biodegradable and non-biodegradable waste, stationary paper, 7%, use of chemicals in the laboratories (5%), paper for official purpose (12%), LPG (3%) and transport (27%) were main contributors. As this is a multi faculty college, science faculty contributes almost 62%, commerce 9% and arts 11% of the total emission. • Present paper highlights carbon footprints from an Indian HEI using bottom up approach. • A questionnaire based survey was used to arrive at departmental and net footprints. • Carbon footprints of HEI in India are much less as compared to developed countries. • The carbon footprints of Indian HEIs are expected to grow at 5–6%. [ABSTRACT FROM AUTHOR]

China has committed to peak carbon emissions by 2030 and become carbon neutral by 2060. Hebei, as a major energy province in China, has more challenging carbon peaking and carbon neutrality targets. Based on the extended STIRPAT model, this paper evaluates the time to peak carbon and post-peak carbon trend changes in Hebei province under different scenarios from 2020 to 2060. Based on the support vector machine model with particle swarm optimization, this paper evaluates the carbon neutral pathways under different scenarios in Hebei province from 2020 to 2060 in terms of forests, croplands, wetlands, grasslands and Carbon Capture, Utilization and Storage (CCUS). The results show that a monotonically flat trend without inflection point, a single-inflection-point plateau-period trend and a multi-inflection-point inverted U-wave trend occur after carbon peaks. Hebei Province can achieve carbon neutrality by 2060 under the policy scenario and the enhanced scenario, and the enhanced scenario is better. Comparing with existing studies, the innovation of this paper is to design different trends of changes after carbon peak, combining carbon absorption and carbon emission, and providing more diversified development paths for carbon neutral strategies through a more integrated perspective and multi-scenario comprehensive analysis. Therefore, In the future, Hebei Province should establish a platform for carbon emissions monitoring and carbon footprint assessment, and set up an early warning and assessment mechanism for carbon peaking, so as to prevent a rebound trend in carbon emissions after peaking. At the same time, it should introduce and develop carbon capture and conversion technologies and promote the low-carbon transformation of the industrial and energy sectors, thereby forcing the early realization of peak carbon. Pay attention to the role of forestry resources in carbon neutrality, increase carbon sink resources such as forests and wetlands, promote the development of CCUS, and enhance the implementation of the policy. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of China's environmental regulations, with a focus on the green credit policy, on green innovation in pursuit of the "carbon peak and carbon neutrality" goal. Given the implementation of the 2012 Green Credit Guidelines, this paper employs the Difference-in-Difference Method (DID) and conducts a quasi-natural experiment to empirically examine the interactions among the central government, local governments, and high-pollution and high-emission enterprises by exploring the impact of green credit policies on green innovation of these enterprises. Relying on 4503 samples of 237 high-pollution and high-emission enterprises listed in the main board in China from 2003 to 2021, this study reveals that the green credit policy can improve green innovation of these enterprises. Specifically, this study explores the detailed mechanism through which the green credit policy enables these enterprises to increase their market concentration and then the monopoly profits, which in turn promotes their green innovative productivity. In addition, this paper also reveals how local governments' political and financial incentives may serve as positive and negative moderating factors, respectively, within the impact mechanism. This study has valuable implications for how to effectively formulate and implement environmental regulations by balancing the interests of the central government, local governments and enterprises. [ABSTRACT FROM AUTHOR]

This study delves into the nexus between the efficiency of carbon emission allocation and the efficiency of green development within the context of innovative city construction. Leveraging data from 283 prefecture-level cities and corresponding provincial-level panel data spanning the period from 2005 to 2019 in mainland China, the research employs the zero-sum gain DEA model to compute provincial carbon emission allocation efficiency and allocate allowances. Furthermore, it utilizes the all-factor non-radial directional distance function and the SBM-DEA model to gauge the green development efficiency of prefecture-level cities. The double-difference method is applied to evaluate the impact of innovative city construction on regional green development efficiency. The results indicate that an imbalance between carbon emission allocation efficiency and emission quotas detrimentally affects urban green development. However, technological progress, factor accumulation, and the institutional environment associated with innovative city building mitigate this negative impact. Heterogeneity analysis reveals a differentiated effect of innovative city building on regional green development efficiency. This paper not only explores the concept of achieving an equitable distribution of carbon emission allowances but also examines how innovative city building influences regional green development. By establishing connections between urban policies, the equitable distribution of carbon emission allowances, and regional green development, it introduces a new perspective for promoting high-quality development at the regional level. [ABSTRACT FROM AUTHOR]

Because transport in the port hinterlands heavily depends on roads with negative externalities, much social interest has been in modal shifts (MSs) to rail and shipping with lower environmental impact. Currently, leading industry sectors to ambitiously embrace technological innovations to decarbonize—consequently, in line with these changes, the significance of MSs should change; however, no previous studies have comprehensively presented the overall CO 2 emissions and transport mode shares for future regional cargo transport. This paper presents a scenario analysis of CO 2 emission reductions in the Japanese domestic hinterland of international maritime container transport based on future scenarios of technological innovation and change in shipper behavior. The simulation results using the global logistics intermodal network simulation model showed that up to 87% CO 2 reduction is possible, and the primary driver for this is technological innovation. Moreover, the significance of MSs fluctuates depending on the advancement of technological innovation, suggesting that MSs hold a degree of import as a decarbonization measure during the transitional phase toward carbon neutrality (CN) as technological innovation advances. The results of this study, which fluctuated considerably by scenario and timing, have policy implications with respect to the path to be followed toward CN, including whether to promote MSs. • Scenario analysis of CO 2 emission reductions in Japanese maritime transportation. • Up to 87% CO 2 reduction possible using technological innovation. • Significance of modal shifts fluctuated with the degree of technological innovation. • Policy implications suggesting that the path toward carbon neutrality is crucial. [ABSTRACT FROM AUTHOR]

China's climate and environmental problems remained prominent. Energy transition was the key to improve climate and pollution, and it was at a critical period. Previous studies mostly focused on the impact of climate policies on the reduction of air pollutants and the environmental health impacts of individual sector or pathway policies. Thus, focusing on the synergistic abatement of CO 2 and air pollutants and health effects of energy transition in carbon neutrality was significant for building beautiful and healthy China. LEAP-HEA model was constructed to project energy demand, CO 2 and air pollutants, and assess energy transition's environmental health effects from 2020 to 2060. LMDI model was adopted to decompose the abatement contribution. Synergistic assessment index was used to estimate the coordinated abatement effects. Cost-effectiveness of energy transition and regional heterogeneity of PM 2.5 toxicity were not considered. The results indicated: (1) energy demand would decrease and structure would be optimized significantly under deep energy transition scenario. (2) Deep energy transition could promote earlier realization of carbon neutrality. It would contribute significantly to CO 2 and air pollutants abatement with strong synergistic effects. (3) Energy transition would reduce health risks with large economic benefits. Recommendations were proposed based on the conclusions. The framework of LEAP-HEA model. [Display omitted] • The synergistic abatement and health effect of energy transition were explored. • The models of LEAP, LMDI, exposure-response and the data of 2020 were used. • Energy transition would have significant synergistic abatement and health effect. • The paper has significance for promoting carbon neutrality and healthy China. [ABSTRACT FROM AUTHOR]

As major strategic development areas in China, the provinces around the Yangtze River are facing the pressure of large aggregate CO 2 emissions and high per capita CO 2 emissions. The study on the pathway of reducing CO 2 emissions and increasing carbon sequestration will help China better clarify the ways realize the goals of carbon peak and carbon neutrality as soon as possible. In this paper, the extended STIRPAT model and OLS regression were used to establish a prediction model to estimate the CO 2 emissions during 2010–2060 under different scenarios. Meanwhile, the InVEST model was used to estimate the carbon sequestration, and the comparison with the CO 2 emissions was analyzed. The results show that Qinghai and Yunnan have achieved the goal of carbon neutrality in 2010. Under the low-carbon and energy-saving scenario and the baseline scenario, all provinces within the study area are anticipated to attain their emissions peak by 2030 or earlier, and the CO 2 emissions peak value of the whole study area is 3111 Mt and 3199 Mt, respectively. While under the high emissions scenario, only Chongqing and Qinghai will reach the emissions peak in 2030, and the whole study area will reach the emissions peak in 2040, with peak value of 3470 Mt. Under the three scenarios, the whole study area cannot achieve carbon neutrality before 2060. Only Sichuan and Hubei can achieve carbon neutrality in 2050 and 2060 under the low-carbon and energy-saving scenario. All provinces and municipalities in the lower reaches of the Yangtze River are facing huge pressure of emissions reduction. The research reveals that the goals of carbon peak and carbon neutrality should be achieved by developing clean energy, transforming industrial structure, increasing carbon sequestration and improving carbon emissions trading system. [Display omitted] • The CO 2 emissions showed a pattern of increase during 2010–2020. • The whole study area will achieve carbon peak by 2040 or earlier. • The whole study area cannot achieve carbon neutrality before 2060. • The realization pathway of carbon peak and neutrality was proposed. [ABSTRACT FROM AUTHOR]

Carbon peaking and carbon neutrality goals are proposed by the Chinese government, which aims to reach the highest level of CO 2 emissions by 2030 and achieve carbon neutrality by 2060. It is of great significance to accelerate green production and lead high-quality development. Energy carbon emissions account for 88% of total CO 2 emissions, while forest carbon sequestration account for 80% of China's terrestrial ecosystems. In this paper, we analyzed the spatial and temporal evolutions of industrial energy consumption carbon emissions and forest carbon sequestration of Hubei Province, then demonstrated the offsetting effect of forest carbon sequestration on the industrial CO 2 emissions. Our results documented energy carbon emissions and forest carbon sequestration in Hubei Province both increased from 2000 to 2020, with the growth rates of 4.9423 Mt/yr and 0.28015 Mt/yr. Forest carbon sequestration could offset energy carbon emissions before 2005, while the offsetting effect was weak due to the continuous increase in industrial energy consumption after 2005. Significant spatial heterogeneity was observed in both energy carbon emissions and forest carbon sequestration. Wuhan had the biggest carbon emission with annual average carbon emission of about 20.046 Mt, while Enshi had the biggest carbon sequestration with annual average forest carbon sequestration of about 14.411 Mt. Spatial autocorrelation between energy carbon emissions and forest carbon sequestration was significant in Hubei Province in the past two decades. Our findings provided evidence that local-scale forest carbon sequestration could offset carbon emissions caused by industrial energy consumption at a certain extent, helping to draw up the scientific energy-saving and emissions-reducing measures. [Display omitted] [ABSTRACT FROM AUTHOR]

The European Union's aim to achieve climate neutrality by 2050 relies on reducing emissions from the industrial sector. There is a lack of guidance and technical support at the organisational level for industrial organisations, particularly for non-energy-intensive industries. Existing approaches do not offer structured pathways to carbon neutrality. This study involves the development, verification, and validation of a novel modelling tool aimed at assisting Irish industrial organisations in achieving carbon neutrality. The generated outputs are an organisation-specific carbon neutrality waterfall as the roadmap, and a financial analysis to indicate the breakeven year where the financial savings equal the investment costs of implementing the proposed measures. This modelling tool is a decision-support tool capable of scenario modelling, which provides the user with an overview of possible decarbonisation timelines and financial impacts. First, this paper presents the user-defined and built-in inputs, followed by the first-principles mathematical model that forms the basis of the modelling tool. Then, the modelling tool is verified by a code-to-code process using representative dummy data, and is found to be accurate against the mathematical model. The final step is the use of an actual dataset from an industry partner in a validation process to determine the applicability of the modelling tool to industrial organisations. It is found to be applicable in terms of the type of data output (carbon neutrality waterfall and financial analysis). However, the inaccurate negative emissions balance of the waterfall indicates that the modelling tool is not applicable in its current state; this highlights the importance of considering the interaction effects of implementing multiple emissions-reduction measures, which is the next step in the tool development. Moreover, this tool is applicable to organisations that have completed energy audits, heat studies, and renewable energy studies and have created a register of performance improvement measures that serve as the model inputs. As such, it has a niche market and represents an initial approach to carbon neutrality planning, with the future focus on expanding its applicability by developing a heuristic knowledge-based modelling tool that acts as a recommender system. [Display omitted] • Modelling tool developed to aid carbon neutral industrial manufacturing. • Open access, cross-sectoral tool aimed at the organisational level. • Functions as a decision-support tool based on scenario modelling. • Generates waterfall graph as the carbon neutrality roadmap. • Generates a financial analysis graph to indicate breakeven year. [ABSTRACT FROM AUTHOR]

Carbon emission trading, a market-incentive environmental regulation, plays a critical role in leading China towards the carbon peaking and carbon neutrality. To improve the national carbon emission trading in China, we analyze the effects of the policy in pilot provinces and pilot A-share listed firms from 2008 to 2016. Particularly, to explore the pilot policy's environmental and financial impacts, this paper applies a difference-in-difference method. After the robustness check, the results confirm the carbon emission trading pilot's significantly positive impact at both firm- and province-level regarding carbon emission reduction. Meanwhile, corporate innovation seems to partially mediate the relationship between the policy and corporate carbon emission reduction. Plus, the policy promotes firms' market-based financial performance but such impact on accounting-based financial performance is insignificant. Ultimately, the operational mechanism of the policy is proved to be effective. In this paper, industry- and firm-level carbon emissions databases are established via environmental extended input-output table, which fill the research gap of China's firm-level carbon emissions. To ensure the reliability of results, the list of covered firms is sorted out manually in accordance with the disclosed data of seven carbon trading markets. Our results are meaningful for avoid productivity reduction and mechanism re-design in the context of the national carbon emission trading launched in 2021. Specifically, encouraging firms to further improve their productivity and competitiveness by innovation could eventually achieve a win-win situation between economic performance and environmental merits in the long run. [ABSTRACT FROM AUTHOR]

Promoting low-carbon development in the iron and steel industry (ISI) is essential for China to achieve the carbon neutrality targets. This paper separately adopts the Logarithmic Mean Divisia Index (LMDI) technique and the Mean Impact Value (MIV) method to analyze the impact of driving factors on the CO 2 emissions of ISI in the historical and future dimensions. Furthermore, this paper establishes the extreme learning machine model optimized by the bat algorithm (BA-BP) to explore the carbon emission reduction pathways of ISI in the business-as-usual (BAU) scenario, the low-speed, medium-speed and high-speed development scenarios considering the constraints of carbon neutrality targets. The results reveal that: (1) Production capacity and energy efficiency are important drivers of CO 2 emissions in ISI; (2) The emission reduction situation is not optimistic under the BAU scenario, and it is difficult to accomplish the carbon neutrality goals by 2060; (3) Under the most ideal emission reduction pathway (corresponding to the high-speed development scenario), ISI will reach its peak in 2022 with the peak value of 2143.42 MtCO 2. Compared to the peak year, the CO 2 emissions will be reduced by 654.69 MtCO 2 and 1558.61 MtCO 2 in 2030 and 2050, respectively. Moreover, the achievement of short-term and long-term emission reduction targets depends on production capacity decline and technological progress, respectively. The optimal emission reduction pathway provides a reference for ISI to formulate periodic emission reduction targets. • The improved extreme learning machine is employed to predict the carbon emissions. • The emission reduction pathways are explored under the carbon neutrality target. • Controlling production capacity is a crucial reduction strategy. • The energy rebound effect is supposed to be weakened. • The application of advanced technologies will greatly promote emission reduction. [ABSTRACT FROM AUTHOR]

To support high-quality carbon peaking, a scenario analysis of carbon peaking pathways according to an industrial chain perspective considering both material and part production needs exploring. As a critical segment in the aluminum industrial chain, aluminum casting industry was focused on in this paper. A bottom-up scenario analysis approach was proposed for the carbon emission simulation of China's aluminum casting industry, including: (1) a carbon emission assessment model based on material flow analysis and life-cycle assessment, (2) key influence factor selection and variation scenario prediction, (3) static and dynamic scenario analysis, and (4) driving factor decomposition analysis. Key findings are as follows: (1) China's aluminum casting industry accounted for about 1.1% of the national carbon emissions in 2020; (2) the production stage accounted for around 15% of the total carbon emissions of China's aluminum casting industry in 2020; (3) carbon peaking probabilities before 2030 for the static and dynamic scenario analysis are around 60% and 35%, respectively; and (4) the carbon peaking result differences in whether considering the production stage are about 20% for the static simulation and average 40% for the dynamic simulation. These findings effectively support the formulation of a high-quality carbon peaking pathway. • A bottom-up approach of scenario analysis was proposed for carbon peaking pathways. • Carbon emission assessment model was built with corresponding inventory data. • Static and dynamic scenario analyses of carbon emissions were compared. • Decomposition and sensitivity analysis of driving factors were conducted. • Production stage accounted for around 15% of the total carbon emissions. [ABSTRACT FROM AUTHOR]

Achieving carbon neutrality is the ultimate goal of the global economy. By leveraging Internet of Things (IoT) technology to gather users' data, smart home devices can effectively achieve energy conservation and reduce carbon emissions. The strategic allocation of investment by smart device producers towards environmentally-friendly functionality and choosing the optimal sales mode have emerged as significant research questions. Addressing consumer concerns regarding data privacy sensitivity, this paper presents a game-theoretical model, involving manufacturers, e-commerce platforms, and consumers, to explore the intricate dynamics among investment in smart environmental functionality, sales mode selection, and pricing strategies. The results indicate that manufacturers consistently benefit from such investments. If the number of data-sensitive consumers is considerable, manufacturers will subsidize the platform to encourage the purchase of smart devices, thereby gaining from cross-selling opportunities. When the commission ratio is low, the equilibrium strategy shifts from the agency selling mode to wholesale pricing one, in response to the advent of investments in smart environmental functionality. Furthermore, the commission ratio, consumer perceived environmental value, and unit carbon emissions collectively impact social welfare. This study offers valuable theoretical insights for manufacturers in making informed decisions regarding pricing strategies and sales mode selection, by analyzing the interplay between profit margin and cross-selling income resulting from demand expansion. [ABSTRACT FROM AUTHOR]

With the general recognition of the awareness of carbon neutrality, economic development growth momentum for carbon neutrality scenario has become research focus. This paper introduces the carbon neutrality double input level based on the perspective of the initiative, consciousness, and self-discipline of firms and residents to practice green low-carbon behavior. By constructing a balanced economic system of green low-carbon behavior, this paper explores the new endogenous growth power in production and consumption, and finds that there exists a carbon neutrality realization regulation of green low-carbon behavior in the new system. Based on the penetration capacity of green low-carbon behavior, this paper studies the endogenous growth law of economic system driven by the evolution of carbon neutrality double input level. The production and consumption processes are considered in the new economic system in this paper, the production of green low-carbon goods is considered in the production sector and the technical equation under carbon neutrality double input level is studied, the consumption process of green goods affected by environment and carbon emissions is considered in the household, then the household utility function is constructed, and the new growth rate is obtained. Using carbon emissions growth rate of green low-carbon goods and its relationship with absorption rate derive the carbon neutrality realization regulation. Then the general equilibrium solution and growth rate under endogenous growth driven by carbon neutrality double input level are also obtained. Furthermore, the carbon neutrality effects which are the endogenous effect of carbon neutrality double input level and the effect of carbon neutrality realization regulation are obtained by numerical simulation and empirical analysis. [ABSTRACT FROM AUTHOR]

The Yangtze River Delta region is one of the key areas of energy transition for China's carbon neutrality. The pathways to carbon neutrality are diverse in the regional level due to the different conditions on the energy supply and demand side. How to construct comprehensive assessment index system and evaluate regional pathways to carbon neutrality is an urgent problem to be solved. To fill this gap, this paper evaluates the carbon neutrality pathways of supply-side and demand-side coordination in the Yangtze River Delta region using the Low Emissions Analysis Platform with five scenarios (64 sub-scenarios): Business as usual, energy intensity decrease, energy structure reform, power supply technology innovation and policies mix. The simulation results indicate that: (1) 22 of the 64 sub-scenarios can achieve carbon neutrality by 2060. (2) In energy intensity decrease scenario, an annual 6% reduction in energy intensity could achieve carbon neutrality before 2060. (3) The policies mix scenario can lead to 21 sub-scenarios with pathways to achieve carbon neutrality when the average annual energy intensity decreases by 4% or more. Additionally, the end-use sectors electrification level should reach 64.19% at least by 2060. (4) There can be 14 sub-scenarios to achieve zero carbon emissions in the power plant sector, but annual energy intensity should be reduced by at least 4%. Applying Analytic Hierarchy Process analysis, the article evaluated the 22 sub-scenarios with the index of regional pathways to carbon neutrality. The result shows that the mixed policies of energy intensity reduction, energy structure reformation and power technology innovation can promote the coordination of supply-side and demand-side. This study can provide reference for policymakers to formulate effective policies to realize carbon neutrality. • The coordination of energy supply and energy demand is assessed. • A model with five scenarios (64 sub-scenarios) is developed for carbon neutrality. • Energy intensity drops by 4% or more can lead to multiple carbon neutral pathways. • A comprehensive assessment index of regional carbon neutral pathways is developed. [ABSTRACT FROM AUTHOR]

The use of the minimum energy to maintain the indoor thermal comfort of the large-space public building is always a challenging task due to the complex outdoor environment and indoor requirements. The lack of monitoring data and effective approaches limits the understanding of building thermal and energetic performance. This paper thus proposes a hybrid machine learning model based on factor generators and an optimization approach to address this research topic, aiming to provide the essential guide for future retrofit and design of large-space public buildings. The four machine learning (ML)-based factor generators are compared using the one-year monitoring data of building facility and indoor thermal management, where the high-performance multilayer perceptron neural networks (MLPNN) model is chosen as the data-driven method to generate the input data as the parent or intermediate populations in the GA optimization algorithm. Such a hybrid machine learning model can solve the multi-objective functions of thermal comfort and carbon emissions. The optimization results demonstrate that this model can achieve a maximum 29% improvement for thermal comfort and a reduction of 386.9 kg CO 2 (11.06%) for carbon emissions in comparisons with the human-based management. Moreover, such hybrid machine learning model exhibits tolerance for moderate deficit in one objective. Therefore, the optimal thermal comfort and carbon emissions of large-space public buildings are achieved and thus contributing to the carbon neutrality in the building sector. • The multi-objective problem of thermal comfort and carbon emission is addressed. • The MLPNN models perform well according to the prediction evaluation criteria. • A 29% thermal comfort improvement and the 386.9 kg CO 2 reduction are achieved. • The new model reduces the wasteful energy from human-based decision-making. • The hybrid machine learning model can tolerate the moderate deficit. [ABSTRACT FROM AUTHOR]

Implementing nationally determined contributions is more challenging for developing countries given potential economic consequences. Chile, a developing economy, is committed to reaching carbon neutrality by 2050. To do so, Chile announced multiple mitigation strategies such as phasing out coal by 2040, peaking emissions by 2025, and developing renewable energies. Fortunately, Chile holds a prominent renewable potential, standing out for solar, but it also has a significant challenge decarbonizing an economy that heavily relies on fossil fuels. The contribution of this paper is twofold. First, the first country-level disaggregated version of GCAM Latin America (GCAM-LA) was developed, where all South American countries are modeled as an independent energy-economy region. This model includes Chile as a separated region and incorporates interactions among the energy, water, agriculture and land use, economy, and climate systems. Second, different decarbonization strategies to reach carbon neutrality by 2050 were obtained, considering technology availability and high renewable energy potential. Results indicate that carbon neutrality is feasible when enforcing different combinations of the current Chilean mitigation strategies, even delaying coal phase-out by five years and failure of developing advanced solar technologies. If some policies are not fully implemented, such as delaying coal phase-out by five years or failure of developing advanced solar technologies, carbon neutrality can be achieved by incurring in a higher capital cost in the power sector. Moreover, decarbonization is mainly driven by high electrification levels in the final demand sector, reaching 53.7%–62.9% of the total consumption. However, such levels of electrification are reduced, particularly in the transport sector, when Chile relies on negative emissions from the land use and forestry sector. [ABSTRACT FROM AUTHOR]

As the climate is warming up and climate disasters occur more frequently, China's carbon peak and carbon neutrality targets are gaining attention, with provinces starting to set carbon peak targets and constantly exploring low carbon economic development opportunities. However, the existing evaluation index system mainly focuses on low carbon cities and green cities, and there is no evaluation index system for carbon peak and carbon neutrality. This study adopts a combination of theoretical and empirical research and draws on domestic and international research results to construct the first index system for evaluating China's provincial carbon peak and carbon neutrality. The evaluation index system includes 18 indicators from three dimensions: climate ambition, low carbon status, and emissions trends. Using this index system, we calculated the carbon peak and carbon neutrality indices of 30 Chinese provinces. Further, the 30 provinces were classified into six categories, and corresponding policy recommendations for achieving the "Dual carbon" targets were put forward. The evaluation index system constructed in this paper can provide a reference for future carbon peak and carbon neutrality assessments. By disclosing the integrated index of each province, we hope to effectively curb the increasing local carbon emissions; avert inaction in areas with good natural endowments; and motivate the advancement of the latter, to boost the implementation of the "Dual carbon" targets coherently for the whole country. [Display omitted] • An integrated evaluation system on China's Provincial "Dual carbon" was proposed. • 30 provinces in mainland China were ranked based on the integrated index. • 6 groups were classified to show provincial differences on dual carbon performance. • Policy recommendations to fulfill China's climate commitment were put forward. [ABSTRACT FROM AUTHOR]

The year 2022 is the seventh year since the Paris Agreement was signed. In the context of the same goals of achieving carbon neutrality and transforming the energy structure, hydrogen has become one of the most appealing options for realizing a better vision. This paper reviews the status and challenges of hydrogen application paths in high carbon emission sectors, especially in the electricity and heating, transportation, and steel industries. The discussions focus on the potential contribution from the replacement of primary energy and the reduction in carbon emission by switching to a hydrogen economy. In the case of China in 2030, the application of hydrogen in a single sector is expected to save up to $27.8 billion in carbon tax. Additionally, the key technologies for hydrogen production, storage, and carbon footprint in the industry chain are discussed. In contrast, the cost-effective blue hydrogen is still the best choice. The hydrogen storage technologies suitable for large-scale and low energy consumption need to be broken through. The study of carbon footprint in the industry chain will promote the development of hydrogen in the designated sectors and provide insights for the policy decision on hydrogen development at the regional or industrial level. • The hydrogen application paths for decarbonization are thoroughly compared. • Hydrogen production paths are reviewed in aspects of cost and carbon intensity. • Hydrogen production from fossil energy with CCS is a positive choice. • The LCA method of the industry chain is conducive to the hydrogen promotion. • Specific suggestions for the sustainable development of hydrogen are proposed. [ABSTRACT FROM AUTHOR]

China has proposed to achieve the carbon neutrality target by 2060. It is important for China to clearly understand the carbon sink of ecosystems. Most current studies focus on accounting for the carbon sink or carbon emission in the past and ignore the contribution of ecosystems to carbon neutrality in the future. The work presented in this paper projects land use changes in 2030 and 2060 under the business as usual (BAS), rapid economic development (RED), and ecological land protection (ELP) scenarios based on Multiple Objective Programming and GeoSOS-FLUS and calculates the carbon budgets and contributions of ecosystems to carbon neutrality in Qinghai during 2000–2060. The key findings are that the contributions of the terrestrial ecosystem to carbon neutrality in Qinghai are 9.92% (BAS), 10.03% (ELP) and 7.56% (RED) in 2030, and 3.23% (BAS), 3.28% (ELP) and 2.91% (RED) in 2060. These results indicate that the Qinghai ecosystem has carbon sink potential and the reduction of carbon emissions by humans is the core challenge in achieving carbon neutrality. Therefore, some recommendations have been made: 1) optimizing the land use structure to enhance the ecosystem sink in Qinghai; 2) continuing to implement the policies of ecological protection in Qinghai; 3) reducing the anthropogenic carbon emissions is the key to achieving carbon neutrality in 2060. This study not only offers data support and related policy recommendations to realize carbon neutrality goals but also provides a feasible method for future ecosystem contribution assessments under the goal of carbon neutrality. • Current land use policies in Qinghai are partial to ecological land protection. • Terrestrial ecosystem contributions to carbon neutrality are decreasing. • Terrestrial ecosystem contributions are similar in 2060 under three scenarios. • Carbon emission reduction of social system is key to achieving carbon neutrality. [ABSTRACT FROM AUTHOR]

Decarbonizing energy sector through deploying the technology of carbon capture, utilization and storage (CCUS) is required to keep global temperature rise below 1.5 °C by 2060. The true roles of CCUS have to be validated from the perspective of integrated energy system with features of high penetration of uncertain renewable power and strong interactions among multiple energy generation, conversion and storage technologies. To this end, this paper proposes a stochastic power-heat-gas-carbon scheduling approach for the wind-solar-thermal-battery energy mix integrated with CCUS (WSTB-CCUS) to manage the operation of energy conversion devices and CCUS in a coordinated manner. Coal/biomass co-fired and natural gas fired cogeneration units integrated with carbon capture system are built to reflect complex relationship between fuel, power, heat and carbon. A stochastic optimization model based on chance-constrained programming is presented to fully consider the uncertainties of renewable power and load demands. Case study shows that the stochastic scheduling can reduce 7.25% of average total operating costs compared with the deterministic scheduling by providing a more robust solution for the WSTB-CCUS. Discussions are then carried out to explore the roles of CCUS in carbon reduction, flexibility enhancement, negative emission and robustness improvement from the perspective of energy system operation through stochastic scheduling. The influences of other low carbon technologies on the operation of carbon capture are further discussed to provide more insight on the low carbon transformation of energy system. [Display omitted] • Cooperative scheduling of modern energy system integrated with CCUS. • Stochastic optimization to reflect the impacts of uncertain renewable sources. • The roles of CCUS on carbon reduction and flexibility improvement are evaluated. • The roles of CCUS on negative emission and robustness improvement are explored. • The beneficial and adverse effects of renewable power on CCUS are investigated. [ABSTRACT FROM AUTHOR]

To achieve carbon neutrality by 2060, China must tackle CO 2 emission from its power sector which contributes to 40% (11.8 Gt in 2019) of its total CO 2 emission. Previous studies have shown that China has enough subsurface CO 2 storage capacity (3,145 Gt) to store 200–300 years of CO 2 emission nationwide or 600–700 years of CO 2 emission from the power sector. This paper evaluates the economic benefits of using carbon capture and storage (CCS) technology to decarbonize China's coal-fired power plants and conducts a techno-economic analysis of four scenarios to achieve carbon neutrality in China's power sector by 2050. A model of levelized cost of electricity (LCOE) for coal-fired power plants equipped with CCS (CP-CCS) is used for comparing the economic competitiveness of CP-CCS with those of nuclear (NP), hydro (HP), wind (WP) and solar photovoltaic (PV) power plants. Results show that the LCOE of CP-CCS with a CO 2 transportation distance of 100 km or less and coal price below 455 CNY/t (70.54 USD/t with the exchange rate set at 1 USD = 6.45 CNY) is less than those of NP, WP and solar PV especially for a high discount rate. The cost of coal and CO 2 transportation are the two greatest contributors to the LCOE of CP-CCS. In addition, LCOE is sensitive to operation time of the CP-CCS. Retrofitting an existing coal-fired power plant with CCS reduces the LCOE by 10–18% compared to a newly built CP-CCS. Furthermore, a scenario of gradual increase (average annual growth rate of 0.93%) in electricity generation by CP-CCS has a lower total cost than one where coal-fired power plants are aggressively replaced by wind and solar PV power plants. This is especially true if the coal price is low and CO 2 transportation distance is short. The result is savings of trillions of CNY in costs for the power sector. [ABSTRACT FROM AUTHOR]

In this paper, a novel dynamic optimization control based on multi-objective ant lion optimization (DMOALO) and deep learning algorithm is proposed, which could optimize energy consumption (EC) and effluent quality (EQ) simultaneously in the wastewater treatment processes. In order to overcome the difficulty that there is no clear function relationship between the dynamic parameters and the performance indicators, a novel deep belief network (DBN) model for predicting EC and EQ as objective function is proposed. Then, this objective function with constraints is solved by DMOALO method, and the optimal solution would be selected by the intelligent decision system. Finally, Proportional Integral (PI) controllers would be used to track and control these optimal dynamic parameters. DBN-DMOALO-PI optimization control strategy is evaluated in benchmark simulation model 1(BSM1), the simulation results demonstrated this novel optimization control strategy could reduce the EC significantly while meeting the standards of effluent quality parameters. EC is decreased by 3.31% compared with PI optimization control strategy. Therefore, this novel method may reduce the cost of wastewater treatment process effectively, and realize the carbon neutrality in wastewater treatment process. [Display omitted] • A novel dynamic optimization control based on multi-objective ant lion optimization (DMOALO) and deep learning is proposed. • A deep learning model for predicting energy consumption (EC) and effluent quality (EQ) as objective function is proposed. • DMOALO algorithm was proposed to solve objective function overcame the dynamic characteristic difficulties of process data. • The optimization control can optimize EC and EQ simultaneously in the wastewater treatment processes. [ABSTRACT FROM AUTHOR]

Emissions trading system (ETS) is a cost-effective way towards achieving the carbon neutrality goal. Based on the gaps in the research on carbon allowance allocation vis-à-vis the carbon neutrality target, this study examines how to allocate carbon allowances equitably and effectively among Chinese provinces. Different from the previous research that mainly considers responsibility, ability, and potential of equity dimensions, this paper proposes a composite indicator allocation approach based on the equity of history, demand, contribution, and guarantee, and it also employs the entropy method and expert survey method to obtain the indicator weight values in different scenarios. Results show that the carbon allowances of some provinces, such as the forest-rich province of Yunnan, vary significantly in five scenarios, but little differences are observed for some provinces, such as the high historical emissions province of Shanxi. More provinces achieve data envelopment analysis efficiency in the preferred scenario. Compared with the objective scenario, the required emission reduction in the preferred gross domestic product (GDP) scenario is 231 million tonnes less, and the emission reduction cost is 190 billion yuan less. It is suggested that the Chinese government should adopt the allocation scheme in preference for the GDP scenario. [ABSTRACT FROM AUTHOR]

Carbon emission right allowance is a double-edged sword, one edge is to reduce emission as its original design intention, another edge has in practice slain many less developed coal-consuming enterprises, especially for those in thermal power industry. Partially governed on the hilt in hands of the authority, body of this sword is the prices of carbon emission right. How should the thermal power plants dance on the blade motivates this research. Considering the impact of price fluctuations of carbon emission right allowance, we investigate the operation of Chinese thermal power plant by modeling the decision-making with optimal stopping problem, which is established on the stochastic environment with carbon emission allowance price process simulated by geometric Brownian motion. Under the overall goal of maximizing the ultimate profitability, the optimal stopping indicates the timing of suspend or halt of production, hence the optimal stopping boundary curve implies the edge of life and death with regard to this enterprise. Applying this methodology, real cases of failure and survival of several Chinese representative thermal power plants were analyzed to explore the industry ecotope, which leads to the findings that: 1) The survival environment of existed thermal power plants becomes severer when facing more pressure from the newborn carbon-finance market. 2) Boundaries of survival environment is mainly drawn by the technical improvements for rising the utilization rate of carbon emission. Based on the same optimal stopping model, outlook of this industry is drawn with a demarcation surface defining the vivosphere of thermal power plants with different levels of profitability. This finding provides benchmarks for those enterprises struggling for survival and policy makers scheming better supervision and necessary intervene, and the methodology developed in this paper provides a research paradigm for enterprise survival analysis. [ABSTRACT FROM AUTHOR]