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

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

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

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

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

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

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

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

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

Abstract Despite the impact of urbanization on carbon emission has been extensively studied in recent years, the mechanisms by which urbanization, real estate investment affect carbon emissions are still unclear. Different from previous studies focused on direct effect, this paper investigated the impact of urbanization and real estate investment on China's carbon emissions with considering of the provincial contribution and spatial spillover effect. Using the multiplicative logarithmic mean Divisia index (M- LMDI) model, spatial panel data model and panel data of 30 provinces in China over the period 1997–2015, the results suggested that the contributions to carbon emissions and their driving mechanisms were significantly different across provinces. The top five provinces in China that contributed the most to the growths of carbon emissions in China were Shandong, Guangdong, Hebei, Jiangsu, and Henan, with cumulative effects of 10.28%, 10.28%, 5.44%, 5.19%, and 5.09% respectively. The direct impact of urbanization on carbon emissions was significantly negative, but its spatial spillover effect was significantly positive, which suggested that the effect of urbanization on carbon emissions shows significant "pollution transfer effect" after introducing the spillover effect. Due to the characteristics of non-movability and long investment period, the impact of real estate investment on carbon emissions was fixed in the local region, and there was no spillover effect to the adjacent regions. Because of the existence of mutual promotion mechanism between urbanization and real estate investment, the interaction between the two had significant positive direct and spillover effects on carbon emissions, which indicated that the interaction between the two created a reduction effect on both local and adjacent regions. The research can effectively identified the provinces that contribute a lot to China's carbon emissions, and made the decomposition and implementation of the national carbon emission reduction targets more targeted. At the same time, urbanization policies should be combined with real estate policies in the process of carbon emission reduction. [ABSTRACT FROM AUTHOR]

Abstract Economic development has promoted urbanization in the Beijing-Tianjin-Hebei (BTH) region. With the improvement of living standards, residential consumption have become an important contributor to regional carbon emissions. Using an input-output model, we calculated direct and indirect carbon emissions from both urban and rural residential consumption in the BTH region from 2002 to 2012, and then explored the main factors contributing to indirect carbon emissions from residential consumption using a structural decomposition analysis. Results showed that direct carbon emissions from residential consumption increased from 47.13 million tons (MtC) in 2002 to 123.34 MtC in 2012 and indirect carbon emissions from residential consumption increased from 210.36 MtC in 2002 to 550.00 MtC in 2012. Carbon emission intensity and residential consumption level were the main factors affecting indirect carbon emissions during 2002–2012, with varying effects in different sub-regions. Carbon emission intensity played negative effects in Beijing (−37.19 MtC) and Tianjin (−55.39 MtC), positive effects in Hebei (92.89 MtC). Residential consumption level played positive effects in the three sub-regions (79.94 MtC in Beijing, 31.91 MtC in Tianjin and 155.52 MtC in Hebei). Increases in intermediate demand, residential consumption level and population size enhanced indirect carbon emissions. Based on the analysis, this paper contributed to carbon emission reduction strategies in the BTH region. Highlights • Direct carbon emissions from residential consumption increased to 123.34 MtC in 2012. • Indirect carbon emissions from residential consumption increased to 550.00 MtC in 2012. • Carbon emission intensity and residential consumption level were the main impact factors. • Intermediate demand, residential consumption level and population size played positive effects. [ABSTRACT FROM AUTHOR]

Urbanization results in a considerable economic disparity between urban and rural areas in developing countries, which has had a consequent significant impact on CO 2 emissions. To accommodate this directly, this paper presents a modified version of the Kaya Identity formula, U-Kaya, that includes a direct urbanization factor to determine the relationship between energy consumption intensity, population growth, urbanization rates, urban and rural GDP per capita and the volume of carbon emissions, for application in the dynamic forecasting of carbon emissions by Monte Carlo simulation. The method is demonstrated in forecasting China's likely carbon emissions in 2020 by three different modes of urbanization policy: the government-dominant mode, market-dominant mode and a hybrid government market-dominant mode. The results indicate that a higher urbanization rate, energy carbon emission coefficient and energy intensity will lead to increased carbon emissions. Finally, three policy implications are identified, comprising the narrowing of the economic gap between urban and rural areas, adjustments to the energy structure and technical innovation, which will provide a valuable reference for developing countries in their efforts to reduce carbon emissions. [ABSTRACT FROM AUTHOR]

In the social context of mitigating climate change and achieving carbon neutrality, the improvement of carbon emissions efficiency and the protection of biological carbon sequestration have emerged as hot topics recently due to their prospects in carbon dioxide emissions reductions. A large volume of studies has identified the spatial distribution characteristics and influencing factors of carbon emissions efficiency. The contributions of our study lied in constructing a system to measure net carbon sink efficiency. Secondly, this study discussed the carbon neutrality performance of Chinese cities from three different aspects of carbon dioxide emissions, carbon sequestration of vegetation and net carbon sink efficiency. Thirdly, this paper identified the influencing factors of net carbon sink efficiency, and examined the direct and indirect effect of different factors. For this purpose, we evaluated the net carbon sink efficiency of 285 cities in China from 2012 to 2017 using a slacks-based measure model, and explored its spatial distribution characteristics, then employed a spatial Durbin model to explore the influencing factors of net carbon sink efficiency. Our main findings indicate that the net carbon sink efficiency steadily increased during the study period, whereas their spatial characteristics were "high at both ends and low in the middle" from the south to the north. There is a significant spatial autocorrelation in the net carbon sink efficiency of Chinese cities. Several kinds of measures can be applied to promote net carbon sink efficiency, such as increasing the proportion of tertiary industry, promoting economic growth, attracting foreign direct investment, increasing road area, promoting technological progress and strengthening environmental regulation. However, the increase of urban population may decrease efficiency. Nevertheless, an obvious spatial spillover effect exists in the net carbon sink efficiency of Chinese cities. The results can provide policy recommendations for the government to formulate differentiated carbon neutralization policies. [Display omitted] • The carbon sequestration is considered to calculate net carbon sink efficiency (NCSE). • The NCSE is used to discuss the carbon neutral performance of Chinese cities. • Chinese NCSE steadily increased and showed significant spatial autocorrelation. • Spatial Durbin model was adopted to study the influencing factors of NCSE. [ABSTRACT FROM AUTHOR]

Since the combustion of fossil fuel became the largest contributing factor of greenhouse gas emissions in China, the growth of energy consumption caused by urbanization has led to significant increase in carbon emissions. Applying both the carbon-emissions-coefficient and the sector-energy-consumption method, we predicted the energy consumption and carbon emissions, explored the characteristics of energy consumption and carbon emissions in different urbanization stages, and analyzed the energy crisis in Shandong which is a typical province in China. The results indicate that in 2015 and 2020, the total primary energy consumption will be 1.57 times and 1.85 times higher than that of in 2009, and the carbon emissions are estimated to be 1.48 times and 1.67 times respectively. The urbanization has distinct positive effects on energy consumption and carbon emissions, and the influence is more obvious in the intermediate-stage than in the early-stage. From a policy perspective, this paper could provide valuable information for planners and decision makers to formulate feasible and practical polices with a view to optimize energy structure and mitigate carbon emissions. [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]

The increasing energy and material consumption associated with global economic growth has resulted in the need for more severe efforts at mitigating global climate change. The iron and steel industry consumes 8% of energy and emits 7% of total CO 2 globally. China's iron and steel industry contributes to 15% of that country's total CO 2 emissions. Therefore, there is an urgent need to explore the possibility of net zero emissions in the iron and steel industry in China to meet China's goal of carbon neutrality before 2060. In the study presented in this paper, the MESSAGEix–China iron and steel model was developed by integrating the process-based technology of the sector into the IIASA's MESSAGEix framework to explore zero CO 2 emission pathways and their associated impacts on resources, energy, and water in China's iron and steel industry up to 2100. We found that there are multiple pathways to achieving zero CO 2 emissions in the Chinese iron and steel industry by the end of the 21st century. More specifically, in all the pathways developed in this study, CO 2 emissions decreased significantly between 2030 and 2060 due to the rapid application of 100% scrap-based Electric Arc Furnaces (EAFs) and hydrogen-based Direct Reduced Iron (DRI)-EAFs steel-making technologies. However, by 2060, there will still be 70–360 Mt of CO 2 emissions from China's iron and steel industry; consequently, carbon sink or negative emission technologies are required to offset this and achieve the country's carbon neutrality goal. Furthermore, technologies for achieving zero emissions differ widely in terms of their impacts on the consumption of materials and energy. Compared to the electric (ELE) scenarios, 25–40% of extra iron ore is consumed in the current and new national policy (NPS) scenarios and the DRI scenarios, but 25–220% of scrap is required. At the same time, 20–150% more energy will be saved in the ELE scenarios than in the NPS and DRI scenarios. Finally, we recommend that policy makers design a cross-cutting strategy to achieve zero CO 2 emissions and enhance efforts for material recycling and the provision of clean energy and water. • There are multiple pathways to achieving net zero emissions in China's iron and steel industry. • Steel outputs are essential for reducing CO 2 emissions and conserving materials, energy, and water. • Hydrogen-based DRI and 100% scrap-EAFs technologies are key to achieving zero emissions. • CO 2 mitigation measures have limited impacts on water consumption. [ABSTRACT FROM AUTHOR]