Chinese Journal of Population Resources and Environment最新文献

{"title":"Artificial intelligence-driven low-carbon transition in energy consumption structure","authors":"Haiyang Zhang,&nbsp;Cheng Zhang,&nbsp;Yi Ning,&nbsp;Zhiying Xu","doi":"10.1016/j.cjpre.2026.08.005","DOIUrl":"10.1016/j.cjpre.2026.08.005","url":null,"abstract":"<div><div>As the global technological revolution and industrial transformation advance, artificial intelligence (AI) has emerged as a critical catalyst for transitioning to low-carbon energy consumption. This study used data from 30 Chinese provinces spanning 2006–2022 to construct a comprehensive index system for evaluating AI development. We systematically examined the impact of AI on the low-carbon transformation of energy-consuming structures. Empirical results indicate that AI significantly promotes low-carbon energy consumption structures. Mechanistic analysis revealed that AI drives this transformation through three primary channels: behavior-driven effects, ecological innovation, and data flow. Further analysis shows that during the AI gestation stage, the potential energy rebound effect may weaken AI’s positive impact on low-carbon energy consumption structures; however, this mitigating effect diminishes during the AI explosive growth phase. Heterogeneity analysis further demonstrates that AI’s influence on low-carbon energy consumption structures is more pronounced in provinces with a more developed industrial structure, higher external openness, and non-resource endowments. This study highlights the need for tailored empowerment policies and optimized industrial ecosystem frameworks to fully leverage AI’s potential in accelerating the transition toward a low-carbon energy system.</div></div>","PeriodicalId":45743,"journal":{"name":"Chinese Journal of Population Resources and Environment","volume":"24 3","pages":"Pages 348-359"},"PeriodicalIF":4.7,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149175762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Has environmental regulation increased the green total factor productivity of urban agglomerations? A study of urban agglomerations in the Yellow River Basin of China","authors":"Jing Zhu,&nbsp;Yuxiao Qu,&nbsp;Shibin Lyu,&nbsp;Xuening Fang","doi":"10.1016/j.cjpre.2026.08.008","DOIUrl":"10.1016/j.cjpre.2026.08.008","url":null,"abstract":"<div><div>Environmental regulation (ER) refers to various measures taken to address the negative externalities caused by socio-economic activities that are considered effective means to enhance the green total factor productivity (GTFP). However, existing research on whether this conclusion applies to urban agglomeration remains insufficient. Constrained by resource endowments and environmental conditions, the urban agglomeration in the Yellow River Basin of China has long faced multiple pressures concerning economic and social development, environmental improvement, and carbon reduction. Therefore, this study selects the area to verify whether ER can improve the GTFP in urban agglomerations. The study reveals that: (1) the GTFP of the urban agglomeration in the Yellow River Basin of China has shown a fluctuating upward trend; (2) ER effectively enhances the GTFP of this region, with technological innovation and human capital playing intermediary roles; and (3) ER exhibits spatial spillover effects, which has a significant positive impact on GTFP of local cities, as well as in surrounding cities. These findings elucidate how ER influences the GTFP and aids the formulation of effective environmental policies. The study provides a research foundation for the sustainable development of urban agglomeration and serves as a case study for similar regions worldwide.</div></div>","PeriodicalId":45743,"journal":{"name":"Chinese Journal of Population Resources and Environment","volume":"24 3","pages":"Pages 390-406"},"PeriodicalIF":4.7,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149175584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multidimensional perspectives on the role of green transformation on the evolution of low-carbon collaborative governance network: Evidence from a temporal exponential random graph model","authors":"Zheng Gao,&nbsp;Zhiyuan Zeng","doi":"10.1016/j.cjpre.2026.05.004","DOIUrl":"10.1016/j.cjpre.2026.05.004","url":null,"abstract":"<div><div>Within the prevailing consensus on sustainable development, energy efficiency exhibits pronounced spatial externalities. The intertwining of national policy resources has generated a rapidly expanding yet increasingly balanced global low-carbon collaborative governance network (GTFEN).This study examines the structural properties of the GTFEN to analyze empirical characteristics low-carbon collaborative governance using a three-tier indicator system. It employs a temporal exponential random graph model to map the spatial pattern and drivers of GTFEN. The findings reveal that economies with limited green technology innovation or low environmental taxes continue to participate in low-carbon collaboration and assume distinct governance roles. The network is strongly homophilous in carbon productivity, with weak-tie bridges and preference for degree uniformity influence link formation. Heterogeneity tests reveal that higher environmental taxes most effectively spur cooperation among resource-rich countries, whereas gains in carbon productivity and environmental tax revenue foster the integration of developed economies. The study conclusions present important implications for worldwide green transformation: it is imperative to deepen transnational policy coordination and technology-sharing mechanisms to dismantle technological barriers and build an equitable global low-carbon governance network, while simultaneously strengthening the policy leadership of developed economies.</div></div>","PeriodicalId":45743,"journal":{"name":"Chinese Journal of Population Resources and Environment","volume":"24 2","pages":"Pages 200-211"},"PeriodicalIF":4.7,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148546834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of climate policy uncertainty on urban carbon emissions: Empirical evidence from China","authors":"Changfei Nie,&nbsp;Jiaxin Peng,&nbsp;Yuan Feng","doi":"10.1016/j.cjpre.2026.05.001","DOIUrl":"10.1016/j.cjpre.2026.05.001","url":null,"abstract":"<div><div>The effect of climate policy on carbon emissions has been widely analyzed; however, the literature on climate policy uncertainty (CPU) is limited. We used panel data from 281 Chinese cities from 2006 to 2022 to construct a fixed effects model that examines the causal relationship between CPU and carbon emissions (CE). The results reveal that CPU significantly increases urban CE and the potential mechanisms lie in two aspects: increasing urban energy consumption on the demand side and inhibiting urban green innovation on the supply side. The moderating effect indicates that the emissions trading scheme pilot policy mitigates the carbon-increasing effect. Additionally, the heterogeneity analysis reveals that CPU strongly affects CE in southeastern coastal cities, cities with lower administrative levels, large cities, and non-resource-based cities. Our findings provide novel insights for policymakers in designing flexible climate policies to address climate challenges and promote sustainable development.</div></div>","PeriodicalId":45743,"journal":{"name":"Chinese Journal of Population Resources and Environment","volume":"24 2","pages":"Pages 169-179"},"PeriodicalIF":4.7,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148546835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Forest eco-products value realization and urban–rural income gap in China: Stumbling block or stepping stone?","authors":"Huaiyu Huang,&nbsp;Qingsong Zhang,&nbsp;Xiaojuan Chen,&nbsp;Zhiwen Gong,&nbsp;Keshve Ghimire","doi":"10.1016/j.cjpre.2026.05.009","DOIUrl":"10.1016/j.cjpre.2026.05.009","url":null,"abstract":"<div><div>China is undergoing a critical economic transition amidst the double pressures of growing environmental demands and an increasing urban–rural income gap. The forest eco-products value realization (FEPVR) mechanism helps resource-rich but economically underdeveloped regions overcome development constraints and boost revenue. This study investigates the impact of FEPVR on the urban–rural income gap by quantifying FEPVR using an evaluation index system of conversion efficiency. Using panel data from China’s pilot regions for the eco-product value realization mechanism from 2005 to 2023, a fixed effects model and panel quantile regression are used to empirically assess the impact of FEPVR on the urban–rural income gap. The main findings are as follows: (1) FEPVR effectively narrows the urban–rural income gap. (2) The relationship follows an inverted U-shaped pattern, initially widening the gap before subsequently reducing it. (3) The significant income improvement among rural residents, particularly those in low-income groups, primarily drives this reduction. (4) Heterogeneity analysis reveals that regions with larger rural populations and higher-quality forest resources derive greater benefits from FEPVR in narrowing the income gap. This effect was significant between 2012 and 2023 but less notable between 2005 and 2011. This study provides direct implications for Chinese policymakers and offers valuable insights for advancing the Sustainable Development Goals (SDGs), particularly in eradicating poverty (SDG 1) and reducing inequality (SDG 10).</div></div>","PeriodicalId":45743,"journal":{"name":"Chinese Journal of Population Resources and Environment","volume":"24 2","pages":"Pages 259-271"},"PeriodicalIF":4.7,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148546553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating the economic growth effects of China’s “Area-Based Evaluation Mechanism” Reform: Evidence from county-level panel data","authors":"Jinhuan Lang,&nbsp;Yanwei Gu,&nbsp;Pinjie Lyu","doi":"10.1016/j.cjpre.2026.05.012","DOIUrl":"10.1016/j.cjpre.2026.05.012","url":null,"abstract":"<div><div>China’s rapid economic growth has long relied on a model of large-scale urban land acquisition and transfer, which is now increasingly constrained by central government policies. In response, local governments have implemented the “Area-Based Evaluation Mechanism” Reform to reallocate land resources to more efficient enterprises; however, the specific effects of this reform remain unclear. This study investigates the economic impact of China’s “Area-Based Evaluation Mechanism” Reform using panel data on 2 530 county-level units from 2011 to 2020 and a multiperiod difference-in-differences model. The results show that the reform increased county-level economic growth by approximately 1.4 percentage points in the baseline case. Two mechanisms are identified: (1) a positive incentive channel, which reduces resource misallocation between efficient and inefficient enterprises by 0.254 units; and (2) a reverse pressure channel, which drives enterprises to increase R&amp;D investment by 0.207, boosts innovation output by 0.119, and thereby enhances total factor productivity by 0.283. Heterogeneity analyses reveal that the reform’s effects are more pronounced in eastern and Yangtze River Delta regions, counties with higher land output values, and those with a lower proportion of industrial activity. In contrast, the impact is limited in inland regions, areas with lower land output values, and regions with higher industrial proportions. These results remain robust after a series of tests and suggest that promoting economic growth through land reform requires advancing market-oriented approaches to fully utilize the market mechanism. The study offers practical implications for designing more effective and incentive-compatible governance frameworks.</div></div>","PeriodicalId":45743,"journal":{"name":"Chinese Journal of Population Resources and Environment","volume":"24 2","pages":"Pages 297-308"},"PeriodicalIF":4.7,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148546558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Green finance, trade diversification, and institutional quality as catalysts for sustainable industrialization: An empirical analysis of selected Asian Belt and Road Initiative Economies","authors":"Shahid Akbar,&nbsp;Sher Akbar","doi":"10.1016/j.cjpre.2026.05.007","DOIUrl":"10.1016/j.cjpre.2026.05.007","url":null,"abstract":"<div><div>Asian economies of the Belt and Road Initiative (BRI) face growing pressure to sustain industrial expansion while meeting environmental goals, yet limited cross-country evidence exists on how green finance, trade diversification, and institutional quality jointly shape sustainable industrialization. This study empirically examines how green finance, trade diversification, and institutional quality act as catalysts for sustainable industrialization in selected Asian BRI economies. Using panel data for 30 Asian BRI countries over the 2004–2022 period, the analysis evaluates how these factors jointly shape sustainable industrialization under the dual pressures of industrial expansion and environmental sustainability. To address endogeneity and unobserved heterogeneity, we employ fixed effects models, the Kiviet-corrected estimator, and the two-step System Generalized Method of Moments. Our findings show that green finance and import diversification significantly promote sustainable industrialization, measured by the United Nations Industrial Development Organization’s Sustainable Industrial Development Index. Green finance supports a greener industrial transition by channeling resources toward environmentally sustainable technologies and investments, whereas import diversification facilitates access to clean technologies and strengthens supply chain resilience. Institutional quality amplifies these benefits, with stronger governance frameworks accelerating the implementation of green industrial policies. By contrast, export diversification undermines sustainable industrialization when it remains concentrated in resource-intensive, low value-added items, highlighting the risks associated with the “resource curse”. The findings underscore the need for integrated policy measures that combine green financing incentives, strategic trade reorientation, and institutional reform. Control variables such as gross domestic product, trade openness, information and communication technology, and natural resource endowments also shape industrialization trajectories. Overall, this study contributes to the sustainable development literature by providing empirical evidence on how financial, trade, and governance systems foster green industrial transitions. The policy implications emphasize targeted green funding, technology-oriented import strategies, anti-corruption measures, and value-added export diversification to align BRI-related economic growth with environmental sustainability objectives.</div></div>","PeriodicalId":45743,"journal":{"name":"Chinese Journal of Population Resources and Environment","volume":"24 2","pages":"Pages 238-248"},"PeriodicalIF":4.7,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148546556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Restructuring without marketization? Utilization and profitability of China’s coal-fired power plants under “dual-track” wholesale competition","authors":"Zichao Yu,&nbsp;Ping Qin,&nbsp;Lunyu Xie,&nbsp;Jun Li","doi":"10.1016/j.cjpre.2026.05.005","DOIUrl":"10.1016/j.cjpre.2026.05.005","url":null,"abstract":"<div><div>In this study, we examine China’s partially marketized wholesale power generation sector. A political economy approach is adopted to understand the “dual-track” system in which electricity production is coordinated through a combination of government planning and market transactions. By reviewing and synthesizing China’s policies and institutions that govern the dispatch of power generation, we develop a competitive bargaining model, under which power plants compete for production quotas by bargaining with government superiors using both market and nonmarket leverage. First, we hypothesize that power plants that are larger, cleaner, more fuel-efficient, and more politically powerful can bargain for more production quotas. Second, we hypothesize that long-term power purchase contracts can increase eligible power plants’ production and profitability. Then, we analyze data on the operational characteristics of China’s coal-fired power plants, and the empirical results largely verify the two hypotheses. Overall, this study demonstrates that even though China’s mixed wholesale generation market does not explicitly internalize fuel and environmental costs, it can promote energy conservation and pollution reduction when supported by the right policies. In addition, this “dual-track” approach is more politically viable than the fully marketized economic dispatch model because it more accurately aligns with China’s long-standing institutions of economic transition and governance.</div></div>","PeriodicalId":45743,"journal":{"name":"Chinese Journal of Population Resources and Environment","volume":"24 2","pages":"Pages 212-224"},"PeriodicalIF":4.7,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148546837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Empowering innovation in small and medium-sized enterprises through public data openness: Mechanism exploration and empirical evidence based on “specialized, refined, distinctive, and innovative” enterprises","authors":"Yafei Wang,&nbsp;Zhengyi Liu,&nbsp;Xiye Chen,&nbsp;Yao Chen,&nbsp;Ni Li","doi":"10.1016/j.cjpre.2026.05.006","DOIUrl":"10.1016/j.cjpre.2026.05.006","url":null,"abstract":"<div><div>This study draws on public data openness policies of local governments and micro-level data from A-share listed enterprises across 30 provinces in China from 2011 to 2022. Thus, the study examines the mechanisms through which public data openness affects the innovation quality of “specialized, refined, distinctive, and innovative” (SRDI) enterprises. Furthermore, it analyzes the mediating effects of artificial intelligence (AI) development and enterprise research and development (R&amp;D) costs, as well as the moderating effects of government subsidies, information infrastructure, and industrial agglomeration. The results indicate that public data openness significantly enhances the innovation quality of SRDI enterprises. However, this impact varies across regions, industries, and types of enterprises: inland cities, areas with lower education levels, and regions with underdeveloped digital infrastructure exhibit stronger effects. Non-state-owned enterprises are more responsive to public data openness compared to state-owned ones, and non-manufacturing enterprises benefit more than manufacturing ones. Mediation analysis indicates that public data openness enhances innovation capability, primarily by increasing local AI development and reducing R&amp;D costs. Moreover, government subsidies and information infrastructure strengthen this positive effect, while industrial agglomeration may suppress it.</div></div>","PeriodicalId":45743,"journal":{"name":"Chinese Journal of Population Resources and Environment","volume":"24 2","pages":"Pages 225-237"},"PeriodicalIF":4.7,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148546836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Governance efficiency of rural human settlement environment in the Yangtze River Economic Belt in China: Regional differences, dynamic evolution, and influencing factors","authors":"Wenwen Qiu,&nbsp;Ya Zhang","doi":"10.1016/j.cjpre.2026.05.010","DOIUrl":"10.1016/j.cjpre.2026.05.010","url":null,"abstract":"<div><div>Based on an index system established from the dimensions of ecology, life, and production, this study measures the governance efficiency of rural human settlements in the Yangtze River Economic Belt (YREB) using the super-efficient slack-based measure model. The Gini coefficient, Markov chain, and Tobit regression model are employed to analyze the YREB’s regional disparities, dynamic trends, and influencing factors, providing a theoretical basis for promoting rural revitalization and regional coordination development. The results show that: (1) The overall governance efficiency exhibits a fluctuating uptrend, with a spatial pattern of “downstream &gt; midstream &gt; upstream”. (2) Moreover, regional differences of efficiency show a fluctuating downtrend, with inter-regional disparities as the primary sources. (3) The Markov chain indicates strong convergence in low-efficiency regions and low stability in high-efficiency regions. (4) Finally, governance efficiency can be significantly influenced by financial support, informatization, economic development, and education level. These results demonstrated the need for differentiated policies to narrow regional gaps and enhance synergistic, sustainable improvement in rural human settlements.</div></div>","PeriodicalId":45743,"journal":{"name":"Chinese Journal of Population Resources and Environment","volume":"24 2","pages":"Pages 272-281"},"PeriodicalIF":4.7,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148546554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}