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This study focuses on the carbon emissions of key industries in Henan Province, employing techniques of seasonal adjustment, frequency transformation, and statistical modeling to construct an industry-level "Electricity–Energy–Carbon" model to aid in the high-frequency monitoring of carbon emissions in the province's industries. Based on relevant data, this research performs high-frequency calculations of carbon emissions from energy consumption in 34 typical industries and from the production processes of 53 typical sub-categories in the industrial sector of Henan. The findings reveal the following: Firstly, industrial energy consumption in Henan accounts for over half of the total provincial energy consumption, with most months seeing proportions around 60%. Industries such as energy, non-ferrous metals, building materials, steel, chemicals, petrochemicals, and paper making contribute to over 80% of the industrial energy consumption's carbon emissions, often nearing 90% in most months. Secondly, among the major industries, such as non-ferrous metals, chemicals, building materials, and steel, there is a dual challenge of being restricted under the "high energy consumption and high emissions" project while also being required to build key industrial bases, leading to fluctuating trends in historical annual carbon emissions data. Thirdly, six sub-categories, namely plastic products, cement, flat glass, steel, ten types of non-ferrous metals, and alumina, have significant carbon emissions in their production processes, accounting for about 72.3% of the total production-related emissions. [ABSTRACT FROM AUTHOR]

Copyright of Coal Science & Technology (0253-2336) is the property of Coal Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Green and high-efficiency water resource utilization patterns hold paramount importance in promoting sustainable economic and social development, as well as in attaining the goal of carbon neutrality. Most research on water utilization efficiency have taken a general perspective to quantify it, neglecting independent relationships and green effects among water use sectors. This study proposed an integrated measurement model of green water resource utilization efficiency (GWRUE), combined with the carbon dioxide emission equivalent analysis method of water resource behaviors, and constructed an input–output indicator system of GWRUE from four dimensions: domestic, industrial, agricultural, and ecological water. The aim is to achieve the measurement of GWRUE towards carbon neutrality. In this paper, 18 cities in Henan Province were used as instances to carry out the study. The results show that (1) The CO2 emission equivalent from multiple water use sectors in Henan Province showed a tendency of fluctuating reduction during the study period, from a peak of 21,090,100 tons in 2012 to a low of 12,351,900 tons in 2021, with large spatial variations, and the CO2 emission effect existed in most cities, with Zhengzhou being the highest. (2) The GWRUE of domestic, industrial, and agricultural water in Henan Province and 18 cities exhibited an overall upward trend, while that of ecological water presented a downward trend and was at the lowest level among the four sectors. (3) Consolidated GWRUE in Henan Province tended to decrease and then increase; its value was 0.512 in 2011, 0.448 in 2017, and 0.586 in 2021, and most of its cities were at a Medium level. The findings of this study can serve as a theoretical and practical basis for improving the level of green and efficient utilization of water resources, as well as offer references for relevant water use sectors to formulate CO2 emission reduction policies. [ABSTRACT FROM AUTHOR]

Estimating carbon emissions and assessing their contribution are critical steps toward China's objective of reaching a "carbon peak" in 2030 and "carbon neutrality" in 2060. This paper selects relevant statistical data on carbon emissions from 2000 to 2018, combines the emission coefficient method and the Logarithmic Mean Divisia Index model (LMDI) to calculate carbon emissions, and analyses the driving force of carbon emission growth using Henan Province as a case study. Based on the partial least squares regression analysis model (PLS), the contributions of inter-provincial factors of carbon emission are analyzed. Finally, a county-level downscaling estimation model of carbon emission is further formulated to analyze the temporal and spatial distribution of carbon emissions and their evolution. The research results show that: 1) The effect of energy intensity is responsible for 82 percent of the increase in carbon emissions, whereas the effect of industrial structure is responsible for -8 percent of the increase in carbon emissions. 2) The proportion of secondary industry and energy intensity, which are 1.64 and 0.82, respectively, have the most evident explanatory effect on total carbon emissions; 3). Carbon emissions vary widely among counties, with high emissions in the central and northern regions and low emissions in the southern. However, their carbon emissions have constantly decreased over time. 4) The number of high-emission counties, their carbon emissions, and the degree of their discrepancies are gradually reduced. The findings serve as a foundation for relevant agencies to gain a macro-level understanding of the industrial landscape and to investigate the feasibility of carbon emission reduction programs. [ABSTRACT FROM AUTHOR]

As the carrier of human economic activities, the change of territorial space affects the level of regional carbon balance. Therefore, with regional carbon balance as the goal, this paper proposed a framework from the perspective of production-living-ecological space and took Henan Province of China as a study area for empirical research. First, the study area established an accounting inventory that considers nature, society, and economic activities to calculate carbon sequestration/emission. Then, the spatiotemporal pattern of carbon balance was analyzed by ArcGIS from 1995 to 2015. Later, the CA-MCE-Markov model was used to simulate the production-living-ecological space pattern in 2035, and carbon balance in three future scenarios was predicted. The study showed that from 1995 to 2015, the living space gradually expanded, and the aggregation rose while the production space decreased. Carbon sequestration (CS) was less than carbon emission (CE) and presented an unbalanced state of negative income in 1995, while CS exceeded CE and showed a positive income imbalance in 2015. In 2035, living space has the highest carbon emission capacity under natural change scenario (NC), while ecological space has the highest carbon sequestration capacity under ecological protection scenario (EP), and production space has the highest carbon sequestration capacity under food security scenario (FS). The results are crucial for understanding the carbon balance changes in territorial space and supporting regional carbon balance goals in the future. [ABSTRACT FROM AUTHOR]

Unbalanced and inadequate development has led to challenges such as resource shortage, ecological fragility, and economic backwardness in the water-receiving area of Henan Province, which has hindered the high-quality development of the region. This research aims to construct a high-quality development regulation model. The single-indicator quantification–multi-indicator synthesis–multicriteria integration (SMI-P) method was used to evaluate the level of regional development; using the method of embedded system dynamics, the regulation model was constructed and applied. The results show that (1) from 2011 to 2020, the degree of regional high-quality development showed an increasing trend, rising from a low level (0.34) to a medium level (0.57), an increase of one level, but the level of high-quality development still has a lot of room for improvement and faces great challenges; (2) the development of a resource–ecology–economy–social system was in a state of non-harmonious balance, and the proportion of contributions of each system was very different, but the system was developing towards a state of harmony and balance; (3) based on the constructed high-quality development regulation model, the key constraints affecting the high-quality development of the Yellow River water supply area in Henan Province are per capita water consumption, per capita energy consumption, carbon emissions per capita, GDP per capita, etc. The model constructed in this paper can improve the quality development level through the application of examples. The high-quality development degree of the study area was increased from 0.57 to 0.8. [ABSTRACT FROM AUTHOR]

Near-zero carbon emission power (NZCEP) plants, consisting of gas-fired units; wind turbines; power-to-gas (P2G); and carbon capture, utilization and storage (CCUS) systems, have recently received a lot of attention due to their enormous benefits in reducing carbon emissions and increasing the consumption of renewable energy. However, a complex environment of interest and a combination of risks makes their development very slow. This paper establishes a risk analysis framework for NZCEP considering multi-stakeholder participation. Firstly, a synthetic risk factor system was constructed based on stakeholders' interests. Subsequently, interval type II trapezoidal fuzzy numbers were used and final weights were calculated from both subjective and objective aspects. Finally, we applied an acronym in Portuguese of the interactive and multi-criteria decision-making (TODIM) method to site selection to achieve a balance of interests of all stakeholders. In addition, a case study was conducted. The case result demonstrates that Zhengzhou in Henan Province is the best choice for a NZCEP power plant. A further finding is that government plays an important role in the development of NZCEP plants, with site selection results being the most sensitive to changes in the government's risk appetite. Moreover, human resources are an important factor in the siting of an NZCEP plant. [ABSTRACT FROM AUTHOR]

Clarifying the influencing factors of energy consumption in underground production processes of coal mine is the premise and foundation for the coal mining industry to control the energy consumption and intensity to achieve the goal of carbon peak and carbon neutrality. This paper aims to investigate and compare the differences in energy consumption and carbon emissions between a mining‐separating‐backfilling integrated coal mine (MSBICM) and a traditional coal mine and explore the effects of the main production links underground on carbon emission intensity in coal mines. Hence, taking an MSBICM in Henan province as an example, this study constructed an energy consumption and carbon emission model of the mine using system dynamics (SD) method. Based on this model, the energy consumption of the main production logistics system and auxiliary production system in MSBICM was simulated and analyzed. In addition, this study made a comparative analysis of the energy consumption of the different production links in the two types of coal mines. The results showed that: (1) the comprehensive mechanized coal mining with solid filling system and ventilation system were the subsystems with the highest and lowest energy consumption in MSBICM respectively. (2) The influence rates of raw coal mining, gangue filling, coal‐gangue separating, and material transportation on carbon emission intensity in coal mine were 1.09%, 1.34%, 1.09%, and 5.13%, respectively. (3) Under the same production and filling targets, energy consumption of underground transportation systems in MSBICM was found to be 336.66 tons of standard coal less than that in traditional coal mine. This study has helped clarify the complex relationships among the factors that influence energy consumption in coal mines and provided a reference for implementing dual control of energy consumption to promote low‐carbon mining of coal resources. [ABSTRACT FROM AUTHOR]

Mitigating carbon emissions has become a pressing concern in the process of economic development across China due to China's key strategic goal of reaching peak carbon and carbon neutrality. Henan Province, which is located in the Central Plains, has less forest area and coverage than other areas of the nation, but consumes plenty of energy. Therefore, the quantification of Henan's potential carbon sink is crucial for the province's response to climate change due to the national commitment to carbon reduction targets. This research estimated the carbon sink of tree forest vegetation in Henan Province from 2019 to 2060 based on the CO2FIX model using data from the 9th Forest Inventory Report and the forest planning targets of Henan Province. The results show the following: (1) The carbon sink of existing arbor forests is mainly composed of ecological public welfare forests, and a small-year fluctuation in the carbon sink will result from the rotation of commercial forests. (2) The peak carbon sink years for existing forests and new afforestation are between the young and middle ages of the trees, and the peak of the carbon sink in Henan Province as a whole was in 2032. (3) More than 72.4% of the overall carbon sink in Henan Province's arbor forest vegetation comes from the above-ground portion. (4) The energy substitution effect of traditional and improved cookstoves is significantly enhanced during the main cutting period of the existing commercial arbor forest in Henan Province. [ABSTRACT FROM AUTHOR]

Carbon emission reduction is an important part of regional low-carbon economic development. In this paper, gray correlation analysis, neural network model, Gaussian multi-mode fitting and other methods were used to analyze the relationship between total carbon emissions and regional economic development, industrial structure, and energy consumption in Henan Province. On this basis, the future development of carbon emissions is predicted. The calculation results showed that the correlation between the three industries and carbon emissions in Henan Province is more than .7, among which the secondary industry has the highest correlation (.77). In the secondary industry, the correlation coefficient between coal and carbon emissions is the highest .87, while the correlation coefficient between other energy sources is about .5. In the neural network prediction model, the correlation coefficient between the prediction curve and the actual total carbon emission curve is .989, and the prediction results have a good degree of fit. The carbon emission prediction curve was divided into two parts: a linear decline stage from 2018 to 2024, and a rapid decline stage after 2024.The results showed that more efforts should be made in industrial structure, energy consumption structure and environmental protection to achieve low-carbon development in Henan province. [ABSTRACT FROM AUTHOR]

Increased CO2 emissions from urban energy consumption pose a significant challenge to regional carbon mitigation policies. In this paper, we integrated two nighttime light (NTL) data: the Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (NPP) composite data to estimate the energy carbon emissions from 2000 to 2019. Then the spatiotemporal dynamics of carbon footprint and deficit in the Yellow River Basin were analyzed at the provincial, municipal, and county scales combined with NPP data. The study shows that (1) the total amount of energy consumption CO2 emissions in the Yellow River Basin had increased from 1332 Mt in 2000 to 6469 Mt in 2019, but the average annual growth rate slowed down after 2010 from 11.5 to 5.61%. (2) From 2000 to 2018, the provinces with the highest carbon footprint and carbon deficit were concentrated in Inner Mongolia and Shanxi. In 2018, Inner Mongolia's carbon footprint was 1366.91 × 104 km2, accounting for 22.8% of the total. Cities with high carbon footprint were mainly economic centers and energy-intensive areas of various provinces. High-carbon deficit counties were mainly distributed in the western region. In 2018, 954 counties exhibited carbon deficits. (3) The carbon footprint in the Yellow River Basin at the municipal and county scales have a significant spatial correlation. The H–H clusters of the carbon footprint on the municipal scale were distributed in the middle reaches of the Yellow River Basin. At the county scale, the L-L clusters were mainly in Sichuan and eastern Henan regions. Through the analysis of the spatial and temporal evolution of carbon footprint and carbon deficit in the Yellow River Basin, it is significant to measure the degree of comprehensive coordination of carbon sources and sinks in the basin, to grasp the differences in the level of regional carbon emissions, and to promote synergistic regional governance, assist in the formulation of more precise carbon emission reduction policies, and to promote green and high-quality development. [ABSTRACT FROM AUTHOR]

Copyright of China Population Resources & Environment is the property of Shandong Normal University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Global warming caused by carbon emissions has become increasingly prominent. As the world's second-largest economy, China is under enormous pressure to cut down its carbon dioxide emissions. It is urgent to seek effective methods to forecast carbon emissions and put forward the pointed and effective measures to reduce emissions. In this paper, we first use the software Eviews to make an analysis of randomness on data of carbon emissions in the four representative provinces and city, Beijing, Henan, Guangdong, and Zhejiang, in terms of their carbon emissions data from 1997 to 2017. Then, according to their distinct characteristics, the methods of stationary processing of the difference, moving average, and substituting strong impact points, respectively, are adopted to perform the data preprocessing. Then, model identification, parameter estimation, and model test are carried out to establish the model of ARIMA(p , d, q) for the prediction of the carbon emissions of the four regions, respectively. Finally, the model is used to forecast the data and analyze their tendency for their carbon emissions in the next three years. The results can provide guidance for decision-makers to set reasonable carbon emission reduction targets and take appropriate energy conservation and emission reduction measures. [ABSTRACT FROM AUTHOR]

As a pillar industry with high energy consumption and low efficiency, the building industry of China has produced consistently high carbon emission levels in recent years. The important goals in the coordinated development of this industry include the large-scale development of green buildings, the use of energy technologies to reduce carbon emissions, and an effective reduction of carbon intensity. Prefabricated buildings have become popular in this industry due to their low energy consumption, emission, and pollution and environment-friendly nature. This paper examines those factors that influence the carbon emissions from the construction of prefabricated buildings across three phases, namely, production in plants, logistics transportation, and assembly construction, builds an evaluation index system for studying the carbon emissions in the materialization phase of prefabricated buildings, and employs the hierarchical fuzzy comprehensive evaluation method to construct an evaluation model. Results show that the overall energy consumption of prefabricated buildings is lower than that of traditional concrete pouring-type buildings. The hierarchical fuzzy comprehensive evaluation model is scientific and reasonable when used to measure the comprehensive benefits of carbon emissions from prefabricated buildings. By taking a project in Zhengzhou City, Henan Province as an example, the comprehensive evaluation results show that the carbon emissions of this project are at moderate levels. The carbon emissions from prefabricated buildings can be reduced by expanding the market scale of the building industry, adjusting its use of building materials, and setting up special funds for these buildings. The findings of this work provide a certain reference value for analysing the differences between prefabricated and traditional buildings in terms of their carbon emissions in the materialization phase, for evaluating how the carbon emissions of the former can be reduced, and for formulating and executing building emission reduction plans. [ABSTRACT FROM AUTHOR]

The construction industry of China is characterized by its huge consumption and carbon emissions, thereby making this industry one of the most important areas that require energy conservation efforts. Identifying those factors that affect carbon emissions in the construction industry carries great significance in reducing building carbon emissions, promoting low-carbon cities, and achieving China’s emission reduction goals. This paper firstly reviews the literature on those factors that affect the carbon emissions in the construction industries of developed countries. Second, by using Henan Province as an example, those factors that influence carbon emissions are measured by using the classical STIRPAT (Stochastic Impacts by Regression on Population, Affluence and Technology) model. Third, some measures for reducing carbon emissions in the construction industry are developed. Those factors that influence the carbon emissions of buildings are multi-dimensional and diversified. Resident population, urbanization rate, building carbon emission intensity, per capita GDP (Gross Domestic Product), and per capita added value of the tertiary industry all have significant effects on the carbon emissions of buildings in Henan Province. Some policy suggestions can be derived from the findings of this work, such as encouraging building energy conservation, improving the energy efficiency of the construction industry, adjusting the use of building materials, and improving the extant policies for building emission reduction. The results also provide a theoretical basis for identifying those factors that affect the carbon emissions in the construction industry and for formulating and implementing strategies for the low-carbon development of this industry. [ABSTRACT FROM AUTHOR]

As human consumption expands, four environmental footprints (EFs) exceed the planetary boundaries (PBs) at the global scale. Managing absolute environmental sustainability (AES) based on PBs and EFs at the subnational level is crucial for policy insights. However, a consumption‐based AES management framework still needs to be developed. A framework, including five nexus environmental pressures embodied in the supply chain, was developed and tested in our study across China's 30 provinces to address this knowledge gap. The framework involved three steps: (a) assessing AES for five environmental pressures, (b) measuring environmental surplus and overshoot and composition of EFs, and (c) identifying priority areas for AES management. The results showed that only some provinces are sustainable for three impact‐oriented indicators, especially those with larger populations. Moreover, the embodied environmental pressure mainly flows from the Northwest to Southeast China. For two resource‐oriented indicators, over 74% of provinces are absolutely sustainable. From a nexus perspective, Shandong and Shanghai are identified as priorities for AES management due to their low IESI values of 0.32, 0.33, and 0.40, respectively, which means the worst performance. To improve their IESI, Shanghai needs to control the consumption of blue water‐intensive products, while Shandong and Henan should consume fewer CO2 emissions and N‐ and P‐loss‐intensive products. This framework can clarify subnational responsibilities of environmental overshoots, guide sustainable development, and be widely used at the subnational level in countries worldwide. Plain Language Summary: Earth's ecosystem has a limited ability to provide natural resources and accept pollutants. Absolute environmental sustainability (AES) assumes that irreversible impacts will occur once human needs surpass this capacity, emphasizing the need for policymaking based on the current situation. As a crucial policy‐related entity, subnational regions urge AES management. Here, we focus not only on assessing AES of five environmental pressures (including carbon dioxide (CO2) emission, freshwater use, Nitrogen (N) loss, Phosphorus (P) loss, and land use) embodied in supply chains but also on identifying the priorities of AES management among 30 Chinese provinces. We found that the CO2, N, and P driven by final demands have transgressed the absolute limits in all provinces, especially with larger populations. They mainly consume products from Northwest China. More than 74% of the provinces are within the freshwater and land use boundaries. Shanghai, Shandong, and Henan are identified as priorities of AESA management because of their lousy performance from a nexus perspective. They should be responsible for consumption. Applying this framework globally at the subnational scale is crucial for consumption‐based AES management and global environmental preservation. Key Points: A consumption‐based integrated framework for subnational environmental sustainability management within planetary boundaries was developedAll Chinese provinces overconsumed Nitrogen, Phosphorus, and Carbon dioxide‐intensive productsHenan, Shandong, Shanghai, and Jiangsu were identified as priorities for absolute environmental sustainability management [ABSTRACT FROM AUTHOR]

This study aims to examine the impact of land use variations on carbon emissions by incorporating the development of photovoltaics as a scenario. To meet this end, we investigate the carbon emissions fluctuations resulting from different development scenarios: natural development, low-carbon strategies, and widespread adoption of photovoltaic technology. We identify important influencing factors related to these changes and utilize multi-objective optimization and the PLUS model to simulate land use patterns in Lingbao City projected for 2035, with a focus on achieving carbon neutrality. Through multiple scenarios, we analyze differences in carbon emissions, economic benefits, ecological impacts, and land use allocations. Our findings demonstrate that the photovoltaic scenario leads to a substantial 3500-ton reduction in carbon emissions and boosts overall benefits by RMB 85 million compared to the low-carbon scenario. This highlights the significant role of photovoltaic systems inefficient land utilization, meeting carbon emission targets, and generating economic gains. This research explores the relationship between land use alterations and carbon emissions, aiming to achieve ambitious carbon reduction objectives by integrating photovoltaic applications across diverse land types. It provides fresh perspectives for examining urban land utilization and strategies to reduce carbon emissions. [ABSTRACT FROM AUTHOR]

Unveiling the variation mechanism of vegetation net primary productivity (NPP) and elucidating the underlying drivers of these changes is highly necessitated for terrestrial carbon cycle research and global carbon emission control. Taking Henan Province, renowned as the anciently central China and current China's foremost grain producer, as an example, this study employed the Theil–Sen Median Trend Analysis to evaluate the spatiotemporal characteristics and trends of NPP. Correlation Analysis and Residual Analysis were used to explain the drivers of NPP dynamics. To deepen the inquiry, the Geodetector method was employed to scrutinize the multifaceted effects and interplay among diverse variables influencing NPP. The result showed demonstrated that approximately 85.72% of the area showed an increase in NPP, covering a broad geographical distribution. Notably, 89.31% of the province has witnessed a positive human-driven NPP change. It means human activities emerged as a driving force with a positive effect on vegetation NPP, consequently fostering an increasing trend of NPP. Among climatic factors, the correlation between NPP and precipitation was stronger than that between the temperature and NPP, the determined power of factors in Henan Province was population density, (0.341) > GDP (0.326) > precipitation (0.255) > elevation (0.167) > slope (0.136) > temperature (0.109), and a single factor had a lesser interaction effect than two factors. The implications of these findings extend beyond the realms of research, potentially offering valuable insights into the formulation of targeted ecosystem restoration measures tailored to the distinct context of Henan Province, and also expect to provide crucial references for carbon emission control in China and across the world. [ABSTRACT FROM AUTHOR]

With the increase in energy demand, environmental issues such as carbon emissions are becoming more and more prominent. China will scale its intended nationally determined contributions by adopting more vigorous policies and measures. China aims to have CO2 emissions peak before 2030 and achieve carbon neutrality before 2060. The current challenge and priority of China's high-quality development is to ensure a harmonious balance between the ecological environment and the economy. The South-to-North Water Diversion Project passes through Beijing, Tianjin, Henan, and Hebei, which were chosen as the study sites. The carbon emission data was from the China Carbon Emission Database 2000–2019. Decoupling modeling using statistical yearbook data from four provinces and municipalities. KMO and Bartlett's test used SPSS 27 software. The selection of indicators was based on relevance. Analyses were performed using the extended STIRPAT model and ridge regression. Moreover, projections of carbon peaks in the study area for 2020–2035 under different rates of change were simulated by the scenario analysis method. The results show that: (1) The decoupling analysis of the four provinces and cities from 2000-2019 gradually shifts to strong decoupling; (2) Resident population, energy structure, and secondary industry as a proportion of GDP significantly impact carbon emissions; (3) From 2000–2035, Beijing and Henan experienced carbon peaks. The peak time in Beijing was 96.836 million tons in 2010. The peak time in Henan was 654.1004 million tons in 2011; (4) There was no peak in Hebei from 2000–2035. [ABSTRACT FROM AUTHOR]

In a global context where sustainable growth is imperative, understanding carbon emissions in significant regions is essential. Henan Province, being a vital region in China for population, agriculture, industry, and energy consumption, plays a crucial role in this understanding. This study, rooted in the need to identify strategies that not only meet China's broader carbon neutrality objectives but also offer insights regarding global sustainability models, utilizes the STIRPAT model combined with scenario analysis. The aim was to forecast carbon emission trajectories from 2020 to 2060 across the key industries—electricity, steel, cement, transportation, coal, and chemical—that are responsible for over 80% of the total emissions in Henan. The findings suggest a varied carbon peak timeline: the steel and cement industries might achieve their peak before 2025, and the transportation, coal, and chemical sectors might achieve theirs around 2030, whereas that of the power industry could be delayed until 2033. Significantly, by 2060—a landmark year for Chinese carbon neutrality ambitions—only the electricity sector in Henan shows potential for zero emissions under an extreme scenario. This study's results underscore the importance of region-specific strategies for achieving global carbon neutrality and offer a blueprint for other populous, industrialized regions worldwide. [ABSTRACT FROM AUTHOR]

The carbon emission from major sectors and key industries is the main source of regional carbon emission, which has caused severe climate anomalies. Decoupling analysis and prediction of carbon emissions are helpful to formulate effective carbon emission reduction targets and coordinate the relationship between carbon emission and economic development. Considering the differences between sectors, this paper selects 12 major industrial carbon emitting sectors in Henan Province as the research object, decomposes the carbon emission driving factors by Logarithmic Mean Divisia Index (LMDI) method, analyzes the decoupling relationship of carbon emission and economic development by Tapio decoupling model, constructs a decoupling effort model by combining the LMDI method and Tapio decoupling model to analyze the influence of each effect on the decoupling relationship, and sets up baseline scenario, low carbon scenario and enhanced low carbon scenario to forecast carbon emission and its decoupling state with economic development by the Long-range Energy Alternatives Planning system (LEAP) model. It is concluded that the restraining effects of energy structure, energy intensity and industrial structure are increasing. The decoupling index between carbon emission and economic development of 12 sectors shows a downward trend. Both energy structure effect and energy intensity effect have made weak decoupling efforts, and the decoupling efforts of industrial structure effect were relatively small, especially in Ferrous metal smelting and calendering industry and other five sectors. In 2035, four sectors will achieve carbon neutralization and the overall decoupling effect of carbon emissions will be obvious. Finally, this paper puts forward some recommendations to promote carbon emission reduction. • Decomposition, decoupling and forecasting analysis of carbon emission. • Combining decomposition and decoupling analysis to construct decoupling effort model. • Differences between sectors of industry are considered. • The decoupling efforts of industrial structure effect were relatively small. • Four industrial sectors will achieve carbon neutralization in 2035. [ABSTRACT FROM AUTHOR]

In order to cope with global warming, China has put forward the "30 · 60" plan. We take Henan Province as an example to explore the accessibility of the plan. Tapio decoupling model is used to discuss the relationship between carbon emissions and economy in Henan Province. The influence factors of carbon emissions in Henan Province were studied by using STIRPAT extended model and ridge regression method, and the carbon emission prediction equation was obtained. On this basis, the standard development scenario, low-carbon development scenario, and high-speed development scenario are set according to the economic development model to analyze and predict the carbon emissions of Henan Province from 2020 to 2040. The results show that energy intensity effect and energy structure effect can promote the optimization of the relationship between economy and carbon emissions in Henan Province. Energy structure and carbon emission intensity have a significant negative impact on carbon emissions, while industrial structure has a significant positive impact on carbon emissions. Henan Province can achieve the "carbon peak" goal by 2030 years under the standard and low-carbon development scenario, but it cannot achieve this goal under the high-speed development scenario. Therefore, in order to achieve the goals of "carbon peaking" and "carbon neutralization" as scheduled, Henan Province must adjust its industrial structure, optimize its energy consumption structure, improve energy efficiency, and reduce energy intensity. [ABSTRACT FROM AUTHOR]

It is significant to investigate the coupling and coordination between agricultural carbon emission efficiency (ACEE) and food security and to achieve peak carbon dioxide emissions and carbon neutrality in agriculture as early as possible while ensuring national food security. The Super-SBM (slack-based model) and the comprehensive index method were used to measure the ACEE and food security level in Henan province from 2010 to 2020. The coupling coordination degree (CCD) and the relative state of ACEE and food security were analyzed using the coupling coordination degree model (CCDM) and the relative development degree model (RDDM). In addition, the interaction between ACEE and food security and the spatial–temporal heterogeneity were analyzed by combining with the geographically and temporally weighted regression (GTWR) model. The results showed that: Firstly, the overall level of ACEE was high, and the spatial heterogeneity of ACEE was significant. The spatial pattern of food security is relatively stable, with high levels in the south and low levels in the north. Secondly, The CCD between ACEE and food security in Henan province generally shows a decreasing trend. In the spatial dimension, the CCD between ACEE and food security in Henan province exhibits a spatial divergence characteristic of low in the center and high in the north and south, with significant regional variations. Finally, there is spatial and temporal heterogeneity between ACEE and food security. The regression coefficients differ significantly among different cities, the regression coefficients do not show a consistent positive or negative correlation, and the regression coefficients are distributed both positively and negatively. This study serves as a guide for achieving the goal of double carbon in agriculture and ensuring food security. [ABSTRACT FROM AUTHOR]

Few studies have investigated agricultural carbon emissions peaks, especially from the financial development perspective. This study focuses on the effects of financial scale and efficiency to achieve an agricultural carbon emissions peak in China's Henan Province. Using an extended STIRPAT model and scenario analysis, we find: (1) with the inverted U-shaped influence mechanism of rural financial scale and incorporating rural financial efficiency, agricultural carbon emissions in Henan will peak at 14.17 million tons in 2040, 12.50 million tons in 2034, and 11.73 million tons in 2023 under the baseline low-carbon, moderately accelerated low-carbon, and stringent low-carbon development scenarios; (2) without financial efficiency improvements, carbon emissions will peak five years, three years, and six years later, and the peak value will increase 0.97 million tons, 0.65 million tons, and 0.30 million tons. Therefore, agricultural carbon emissions will peak earlier with continuous and strong financial policy adjustment to facilitate financial development. We also find that agricultural carbon absorption exceeds emissions, achieving carbon neutrality. The policy implication is that financial development matters to sustainable agricultural development. Developing countries could learn from the financial development experience (i.e., gradual financial reform and a stable financial environment) in Henan and China in general. [ABSTRACT FROM AUTHOR]

The grey GM(1,1) model is widely used due to its relatively sintple structure, few paranieters, easy training, and considering the grey characteristics of known information and unknown information. However, the GM(1. 1) model is weak in mining complex information, and it is difficult to deal with sequences with both linear and nonlinear characteristics. In response to this problem, the BP neural network is introduced, and the combination model Of the GM-BP neural network is constructed by using the powerful nonlinear data mining ability of the BP neural network. And the GM-BP neural network is used to predict the agricultural eco-efficiency of Henan province. On this basis, the development trend of agricultural eco-efficiency in Henan is analyzed. The results show that the GM-BP neural network model can describe the complex changes in agricultural eco-eficiency in Henan and has a good prediction effect. The agricultural eco-eficiency in Henan from 2020 to 2025 is effective, with a continuous upward trend, but the increasing rate has slowed down. In space, the agricultural eco-efficiency of Henan shows the characteristics of gradually increasing from north to south, high in the east and west, low in fhe middle, and slightly higher in the west than in the east. [ABSTRACT FROM AUTHOR]

Enhancing energy efficiency is globally regarded as an effective way to reduce carbon emissions. In recent years, the energy efficiency of China has gradually improved; however, energy consumption and CO2 emissions are still increasing. To better understand the reasons for this, we evaluated the energy rebound effect (RE) of 30 provinces in China over the period 2001–2017 by employing stochastic frontier analysis (SFA) and the system generalized method of moments (system-GMM) approach, and explored the extent to which the RE affects CO2 emissions. Asymmetric and regional heterogeneity analyses were also conducted. The results indicate that the national average RE was 90.47% in the short run, and 78.17% in the long run, during the sample period. Most of the provinces experienced a partial RE, with a backfire effect occurring in some provinces such as Guangxi and Henan. The RE was associated with significant increases in CO2 emissions; specifically, a 1% increase in the short-run RE led to an increase in CO2 emissions of approximately 0.818%, and a 1% increase in the long-run RE resulted in an increase in CO2 emissions of approximately 0.695%. Moreover, significant regional differences existed in the impact of the RE on CO2 emissions; in regions with high emissions and a high RE, the CO2 reduction effect from the marginal decline in the RE was much more pronounced than that in other regions. [ABSTRACT FROM AUTHOR]

Although central to the promotion of regional economic development, industrial parks discharge large quantities of air pollutants and CO2, counter to the goals of air quality improvement and CO2 reductions in China. In this study, 13 industrial parks in seven cities in Henan Province were chosen to evaluate their emission of air pollutants and CO2 in 2017, their reduction potential under different green measures, and their air quality improvements under a Green Upgrade scenario. The results show that: (1) The total emissions of SO2, NOx, CO, PM10, PM2.5, VOCs and CO2 in the 13 industrial parks were 43, 39, 351, 19, 7, 18, 2 kt and 36 Mt, and would decrease by 72, 56, 19, 30, 26, 77 and 30%, respectively, under the Green Upgrade scenario. (2) The industrial process was the major source of CO, PM2.5, VOCs and NH3, whereas power plants were the largest source of SO2 and NOx, and they would be reduced by 93, 59, 94, 91, 23 and 28%, respectively, under the Green Upgrade scenario. (3) The terminal energy use sector (including industrial boilers and industrial process sources) was the main source of CO2, accounting for 75% of total CO2 emissions, and would be reduced by 76% under the Green Upgrade scenario. (4) WRF-CMAQ simulation results show that, under the Green Upgrade scenario, the concentration of PM2.5 in a transmission channel city would be improved by 1–36 μg/m3, with an annual average value of 9 μg/m3. Our results demonstrate the significant effect of the synergistic reduction in air pollutants and CO2 emissions using Green Technologies in industrial parks and the subsequent improvement in regional air quality. [ABSTRACT FROM AUTHOR]

Carbon emission is further intensified as urbanization and industrialization continue to accelerate. China has maintained its rapid economic development and urbanization in the last 2 decades. The development of the construction industry has not only consumed a large number of energy sources but also resulted in significant carbon emissions, causing some environmental damage. Recognizing the major influencing factors of carbon emissions in the construction industry has become a research hotspot to alleviate environmental pollution caused by the construction industry and meet industrial demands for energy saving and emission reduction. In this study, the factors that influence annual carbon emissions of different building types in China from 2011 to 2018 were decomposed by Logarithmic Mean Divisia Index (LMDI) through a case study in Henan Province. The major influencing factors of carbon emissions have been identified. Results demonstrate that the per capita carbon emission in the construction industry in Henan Province remains high from 2011 to 2018, but it decreases year by year. Carbon emissions from the construction industry in Henan Province increase due to economic development and energy structure. Energy efficiency can inhibit carbon emissions from the construction industry in Henan Province. The obtained conclusions have a positive effect on analyzing annual variations in carbon emissions from the construction industry in a region, identifying influencing factors, and proposing specific countermeasures of energy saving and emission reduction. [ABSTRACT FROM AUTHOR]

Low energy utilization is observed in China due to the extensive economic growth mode, which further leads to considerable energy wastes and environmental pollution. The construction industry plays an important role in the national economic development of China and consumes tremendous materials; thus, this industry discharges abundant CO2. The energy consumption growth rate of the construction industry in China is far higher than the national energy consumption growth rate, resulting in the prominent situation of high energy consumption and low yield. A case study based on Henan Province, China, was conducted to further analyze the environmental efficiency of the construction industry. An index system was established by using the Super-slack-based model (Super-SBM). This system chooses the following: labor, energy, capital, and technology of the construction industry as the input variables, economic output as the output variable, and carbon emissions as the unexpected output. This system was also used to investigate the energy efficiency of the construction industry in Henan Province from 2008 to 2019. Results demonstrated that the construction industry in Henan Province has failed to eliminate the extensive development mode thus far. The environmental efficiency of the construction industry presents a fluctuating growth with a mean of 1.048, which generally remains at a relatively low level. The numbers of construction machines and enterprises in the construction industry have redundancy in approximately 50% of the years. Thus, this study can provide some positive references to enrich the evaluation index system and estimation model of energy efficiency of the construction industry, which includes unexpected output. Moreover, the current study can provide a comprehensive understanding of the environmental efficiency of the construction industry in a province in China and realize reasonable allocation of construction industrial resources. [ABSTRACT FROM AUTHOR]

Energy demand and carbon emission in building construction and utilization have presented an increasing trend with urbanization development and improvement of living standard. Improving the carbon emission efficiency of the construction industry is a precondition for allocating carbon emission reduction objectives and interregional experience exchange over carbon emission reduction. An inputoutput index system was first constructed in this study to obtain the carbon emission efficiency of the construction industry. Carbon dioxide emission of the construction industry was taken as unexpected output, and the super efficiency slack-based measure-data envelopment analysis (SBM–DEA) model was used to estimate the carbon emission efficiency of the construction industry in Henan Province, China during 2008-2019. Finally, treatment measures were proposed to retard the rising trend of carbon emission in the construction industry. Results showed that the mean carbon emission efficiency of the construction industry in Henan Province during 2008-2019 is 1.007 and the carbon emission efficiency of the construction industry reaches the minimum value of only 0.807 in 2012. The carbon emission efficiency of the construction industry in Henan Province demonstrated an overall rising trend with a small amplitude during the investigation period. The results of this study can provide a reference for exploring the efficiency of the construction industry in Henan Province under carbon emission constraint, analyzing and identifying efficiency improvement objectives and methods for the construction industry, and facilitating its sustainable development. [ABSTRACT FROM AUTHOR]

The economy of China is growing rapidly. With this overwhelming growth, the country is experiencing a higher level of carbon emissions. Amid this backdrop, China is under immense pressure to reduce carbon emissions up to a sustainable level. This study adapted 31 provincial panel data from 2007 to 2017 using factor analysis system SBM-undesirable model to calculate the agro-ecological output of each province respectively and used a carbon transfer network impact analysis panel to calculate ecological performance impacts. Results show that (1) overall agro-ecological efficiency in China shows an upward trend but regional differences are evident. The efficiency in the eastern region is higher than that in the central and western regions but the extent of informatization in the central region is higher than that in the western region. (2) Informatization will significantly promote agro-ecological efficiency. (3) Changes in agricultural planting structure, agricultural value-added per capita, employment of human capital in the agricultural sector, and agricultural scale management are also important factors affecting agro-ecological growth. (4) China's amount of carbon transfer is growing year by year, and energy-intensive areas and heavy industry bases are undertaking carbon transfer from the eastern coastal regions; (5) Jiangsu, Henan, and Hebei (Hubei) have the highest centers between 2007 and 2012; (6) inter-provincial carbon transmission is concentrated mainly in the metal smelting and rolling processing industries as well as in the coal, heat, and supply industries. [ABSTRACT FROM AUTHOR]