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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]

As one of the most vital wood-based products, the carbon footprint of wooden doors has received increasing attention in recent years. The studies on the carbon footprints of different types of wooden doors are few. In this study, the cradle-to-grave carbon footprints of three types of wooden doors produced in China were comparatively analyzed. Models used for calculating the total life-cycle carbon footprint of a wood-based composite door, a solid wood composite door, and a solid wood door were developed. Considering the biogenic carbon storage and its delayed emissions, the wood-based composite door, solid wood composite door, and solid wood door featured carbon footprints of 0.379, 0.257, and −0.277 kg CO 2 e per kg product, respectively. The solid wood door exhibited a negative carbon footprint, indicating that its carbon storage was higher than the carbon emission during the life cycle stage. The raw material acquisition (38%–66%) and the transportation stages (23%–38%) of the three types of wooden doors were the main contributors to the total carbon footprints (excluding the biogenic carbon). The product manufacturing stage released relatively small emissions (11%–24%). The waste disposal treatment at the end-of-life phase, the degradation of wood materials in landfills, and their service life displayed significant impacts on the carbon footprints of the three types of wooden doors. Fiberboard, laminated veneer lumber, sawn lumber, finger-jointed lumber, and electricity were identified as the main emission hotspots. This study provides guidelines for low-carbon development in the wooden door industry. [Display omitted] • The full life cycle carbon footprint of three types of wooden door were compared. • Solid wood door showed the best profile, followed by the solid wood composite door and wood-based composite door. • The disposal at the end of life significantly impacted the carbon footprint of wooden door. [ABSTRACT FROM AUTHOR]

Embodied carbon emissions have an important role in China's "dual carbon" target and carbon reduction policy. Our study applied a multiregional input–output (MRIO) model and structural decomposition analysis (SDA) to examine the spatiotemporal evolution and driving forces of embodied carbon emissions in the specific region of Shanxi Province, an energy-rich region in China, in the empirical study using MRIO data. First, we found that Shanxi had considerable net embodied carbon outflow in interprovincial trade, with outflow increasing from 216.18 Mt in 2012 to 221.60 Mt in 2017. Second, the main driving forces of embodied carbon outflow include technological level and trade demand. We then classified 29 sectors into six categories, including mainly developed, controlled, moderately guided, moderately controlled, cost guided, and maintained to describe the relationship between the net transfer of embodied carbon emissions and value added, and formulated proposed sectoral development policies. Third, the sectors with the highest net embodied carbon outflow include electricity and heat production and supply; metal smelting and rolling processing; and petroleum processing, coking, and nuclear fuel processing. We constructed a coupled relationship model to adjust the technology and scale of interprovincial trade to reduce carbon emissions with lower cost and higher equity. The results can be used as a reference for formulating carbon reduction policies in energy-rich regions. [Display omitted] • We calculate the amount of net embodied carbon transferred from Shanxi. • We estimate the sectors' embodied carbon emissions in inter-provincial trade. • Driving forces are decomposed of embodied carbon outflowed from Shanxi. • A classification model is constructed to identify sectoral characteristics. • The key sectors are identified and then trade relationships are adjusted. [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]

Under the dual policy targets of carbon emission peaking (CEP) and industrial green transformation (IGT) in China, where a top-down policy implementation is usually adopted, a more integrative planning mode needs to be constructed for greening industrial development. This paper proposes a technical framework to tackle the weakness faced when integrating IGT-associated issues with CEP factors during the development of IGT options, with an application in the Hohhot–Baotou–Ordos–Yulin (HBOY) city cluster. A CEP-IGT model was built to portray the effects of seven selected indicators on industrial carbon emissions, and help develop six options by defining the transformation strengths of HBOY's energy-intensive industrial system. Particularly, the CEP times and volumes were employed as the criteria for evaluating the IGT options. We found that the regional CEP goal will not be accomplished by even 2035 under the business-as-usual scenario. To halt the emission growth trend will rely much on the structural factors of energy mix and industrial output, which were also determinants of the IGT performance. Option 3, representing a moderate level transformation, was the preferred IGT plan, reaching a peak volume of 255.27 MtCO 2 eq·a−1 in 2026. The preferred plan will result in the replacement of at least 14% of the coal used in thermal power by renewable energy, and an increase in industrial coal-use efficiency by 32.02%. Policy measures need to be implemented to cap the total industrial coal consumption to no more than 2494 Mt and sustain an industrial growth by developing lower-energy or carbon-intensive industries. By 2030, the intensity and volume of industrial carbon emissions will reach 1.89 tCO 2 eq·10,000 CNY−1 and 224.85 MtCO 2 eq·a−1, respectively. This CEP-IGT progress will benefit the goal of being carbon neutral. As such, we concluded that this new framework will aid the IGT planning process, not only improving our understanding of the relationships between carbon emission control and industrial updating levels, but also presenting an integrative path for China's city clusters to promote green, low-carbon industrial development. • A technical framework is raised to tackle the weakness of integrating the CEP factors into IGT planning. • The peaking time and volumes of carbon emissions are used as the criteria for determining the preferred plan. • Both industrial updating and carbon emission control rely on the structural factors. • The preferred Option 3 can achieve the peaking goal in 2026 with a moderate transformation strength. • The new framework presents an integrative path to promote the transformation to green, low-carbon industrial growth. [ABSTRACT FROM AUTHOR]

As a kind of zero-carbon and high-efficiency energy, hydrogen plays a vital role in environment protection and industry application. However, large-scale green hydrogen production is difficult to be promoted because of its high production cost. China is rich in hydropower resources, but the utilization rate is low. It is an ideal solution to combine a hydrogen energy system with the current installed hydropower system to promote the use of hydropower and the application of hydrogen energy. To study the capacity planning problem of a hydropower–hydrogen system, a bi-level programming model is first developed to maximize the system profit through incorporating long-term investment decision and operation strategy within a framework. Then, the developed model is solved based on Particle Swarm Optimization (PSO) algorithm and Cplex. Finally, the model is verified through the empirical study of China's Hongru River basin over a five-year planning horizon. Multiple scenarios related to different seasonal and load demand characteristics are examined. Sensitivity analysis is discussed considering the impact of investment cost and hydrogen price. [ABSTRACT FROM AUTHOR]

"Carbon Peaking and Carbon Neutrality" is one of the important tasks of China's current and future economic construction and development, but the carbon emission reduction effect of High-speed rail (HSR) has not yet been fully studied. In this paper, based on the panel data of 274 cities in China from 2003 to 2016, we take the opening of HSR in the cities as a "Quasi-natural Experiment", and construct the Multi-period Difference-in-Difference Model to explore whether the opening of HSR can reduce carbon emissions of cities along the route, and use the mediating effect model and moderating effect model to further analyze its internal mechanisms. We find that:①The opening of HSR can significantly reduce the carbon emissions of cities along the route, and the opening of HSR in a city will reduce the carbon emissions of the city by about 2.4% on average, and this carbon emission reduction effect usually manifests significantly in the first year after the opening of HSR, and increases year by year thereafter.②The mechanism test shows that the traffic substitution effect, the optimization of the industrial structure and the promotion of economic agglomeration have partial mediating effect on the influence between the opening of HSR and urban carbon emissions. In addition, the increase in the intensity of government environmental regulations can strengthen the effect of the opening of HSR on reducing urban carbon emissions.③The regional heterogeneity research shows that the opening of HSR has a more significant impact on the carbon emissions of cities in the eastern coastal region and western region of China. Moreover, in the western region, the reduction effect of the opening of HSR on carbon emissions is only reflected in the key cities rather than ordinary prefecture-level cities. This paper provides certain reference significance for promoting low-carbon and green economy and helping China to achieve the "Carbon Neutrality" climate action goal. [ABSTRACT FROM AUTHOR]

The oil-bearing drilling cuttings (OBDC) produced in the petrochemical industry contain a large number of hydrocarbons, and their direct discharge will not only fail to recover the organic matter, but will also seriously harm the environment. In the process of treating OBDC, the consumption of resources and energy and pollution problems may arise, and the current clean production focusing on reduction, non-hazardous and resourcefulness has become the focus of achieving sustainable development. However, there is a lack of studies that consider treatment technology, resource consumption and utilization, and environmental impact under the perspective of cleaner production. In this paper, by studying the indicators related to cleaner production and the Driving Force-Pressure-State-Impact-Response (DPSIR) model, an evaluation index system for OBDC processing technology in the petrochemical industry under cleaner production is constructed. The evaluation results can provide reference for the selection of OBDC treatment process, and provide direction for the development and promotion of the treatment process. In the evaluation system, the DPSIR model can evaluate and manage the OBDC process from different levels and perspectives. The combination of the G1 method and the C-OWA operator method was used to calculate and analyze the index weights, and the improved matter-element analysis method was used to comprehensively evaluate the treatment of OBDC to determine the treatment of technical methods. The evaluation system is applied to actual cases in China. The results show that the low-temperature extraction technique was the best and the chemical washing method was the lowest compared with the three treatment techniques. The oil removal rate of OBDC, recovery of organic matter, secondary waste gas pollution and other indicators have a great impact on the evaluation of the OBDC treatment process under clean production. In order to contribute to the optimal recovery and utilization of resources, it is recommended to develop improvements to the treatment pair technology treatment process based on the results of the evaluation. • Analysis of oil-bearing drilling cuttings hazardous waste from the perspective of clean production. • Established the evaluation index system of oily drill cuttings treatment process under cleaner production. • A new set of oil-bearing drilling cuttings evaluation model under cleaner production was constructed. • Apply the improved matter-element analysis method to evaluate and analyze indicators at different levels. • Analyze and evaluate actual cases and propose areas for improvement. [ABSTRACT FROM AUTHOR]

Rapid industrialization and urbanization have caused serious conflict between humans and nature due to the spatial variability of natural environmental conditions. Integrated environmental zoning (IEZ) is an efficient tool to regulate sustainable development in developing countries such as China. Previous studies explore application of IEZ based on assessment of resource and environmental carrying capacity (RECC) and evaluation of urban development land-use suitability (UDLS). However, existing IEZ oversimplify the complexity of UDLS evaluation, and have low spatial resolution. In addition, it is difficult to express overlay results of RECC and UDLS from a multi-dimensional perspective. Therefore, this study sets forth an improved IEZ by a logic scoring of preference (LSP) and a comparative advantage evaluation. The LSP method and normalized revealed comparative advantage (NRCA) index is applied to assess UDLS and the comparative advantage of RECC (CARECC). The results of IEZ are integrated by overlaying the CARECC zones with numerically processed UDLS maps. A small-scale, rapid development area, Liangjiang New Area (LJNA), serves as the study area. The highly suitable, suitable, moderately suitable, marginally suitable, and not suitable land of LJNA covers 276.60, 368.40, 183.45, 143.22, and 228.33 km2, respectively. Furthermore, the spatial distribution of RECC in LJNA clearly differ. Based on the results of UDLS and RECC, ten types of integrated environmental zones in the form of "category + intensity" are delineated. The improved IEZ is consistent with the LJNA Master Plan, reflects the logic of human reasoning more accurately, increases the spatial resolution, achieves zoning from multi-dimensional perspectives, restricts the category and determines the sequence of urban development, which can serve as a reference for optimization of land space in LJNA and is also significant to other areas and places. [Display omitted] • An improved IEZ is proposed based on UDLS and RECC maps. • The advantages of LSP and comparative evaluation are combined. • The method enable more accurate and multi-dimensional zoning results. • UDLS determines the sequence and scale of urban development. • CARECC restricts the category of urban development. [ABSTRACT FROM AUTHOR]