Chinese Journal of Population Resources and Environment最新文献

{"title":"Decoding China’s urban transformation: Multiscale analysis of urban spatial structures and their influencing factors (2007–2023)","authors":"Yan Wang ,&nbsp;Kai Liu","doi":"10.1016/j.cjpre.2026.03.005","DOIUrl":"10.1016/j.cjpre.2026.03.005","url":null,"abstract":"<div><div>Investigating urban spatial structures (USSs) and their influencing factors at different spatial scales is crucial for promoting sustainable urban transformation. Based on nighttime light datasets and the Herfindahl–Hirschman index (HHI), this study analyzes USS characteristics in China from 2007 to 2023 on two spatial scales—prefecture-level cities and urban agglomerations. It also explores structural influencing factors, including the economy, infrastructure, society, and government intervention. We find that: (1) HHI values for both cities and urban agglomerations exhibit a decreasing trend, indicating a USS for both that is evolving toward polycentricity; (2) economic development promotes a polycentric structure at both spatial scales, whereas government intervention drives a monocentric structure; and (3) postal and communication infrastructure have conflicting effects on USSs, encouraging a monocentric structure at the city scale but fostering polycentricity at the urban agglomeration scale.</div></div>","PeriodicalId":45743,"journal":{"name":"Chinese Journal of Population Resources and Environment","volume":"24 1","pages":"Pages 54-66"},"PeriodicalIF":4.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147636800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The spillover effect of separating household waste on water conservation: A perspective of self-determination theory","authors":"Jianguo Wang ,&nbsp;Yanyan Kong","doi":"10.1016/j.cjpre.2026.03.010","DOIUrl":"10.1016/j.cjpre.2026.03.010","url":null,"abstract":"<div><div>Taking the view that pro-environmental behaviors can have spillover effects, this study examines how household waste separation (an environmental behavior with a high degree of difficulty) impacts consumers’ water-saving efforts (an environmental behavior with a low degree of difficulty). We assess the mediating effects of self-efficacy and ego depletion in this relationship and the moderating effect of the need for self-determination in the mediated relationships. The results show separating household waste significantly enhances consumers’ water-saving efforts. Both self-efficacy and ego depletion partially mediate the relationship between household waste separation and efforts to reduce water consumption. Specifically, if consumers engage in pro-environmental behaviors based on their internal, rather than external sense of moral identity, their sense of self-efficacy increases after separating household, which motivates them to engage in subsequent water-saving behaviors. In addition, consumers’ sense of ego depletion declines when they engage in household waste separation, which increases subsequent water-saving behavior. Compared to low-level self-determination needs, high-level self-determination needs weaken the positive impact of household waste separation on consumers’ perceived self-efficacy, but strengthens the negative impact of household waste separation on consumers’ perceived ego depletion and promotes subsequent water-saving behavior. These findings suggest policymakers should pay attention to the spillover effects pro-environmental behaviors and use household waste separation policies to promote other pro-environmental behaviors such as reducing water consumption.</div></div>","PeriodicalId":45743,"journal":{"name":"Chinese Journal of Population Resources and Environment","volume":"24 1","pages":"Pages 129-137"},"PeriodicalIF":4.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147636808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impacts of land finance on labor mobility willingness","authors":"Yu Jin ,&nbsp;Caiyun Lv ,&nbsp;Lianying Fan","doi":"10.1016/j.cjpre.2026.03.012","DOIUrl":"10.1016/j.cjpre.2026.03.012","url":null,"abstract":"<div><div>This study empirically examines how land finance in destination and origin cities affects willingness to engage in labor mobility and explores the underlying mechanisms. Using a two-way fixed effects model, we match macro data from 287 prefecture-level cities in China from 2000 to 2020 with data from the 2018 China Migrant Dynamic Survey (CMDS). The results are as follows: First, land finance in destination cities inhibits labor mobility willingness, while land finance in origin cities and labor mobility willingness have a U-shaped relationship, decreasing initially and then increasing. Second, local governments’ dependence on land finance increases local housing prices and suppresses investment in non-economic public goods in the administrative area, thereby inhibiting labor mobility willingness; however, this also increases investment in economic public goods, attracting labor mobility willingness. Third, labor force age weakens the impact of land finance in origin cities on labor mobility willingness; however, age does not affect the impact of land finance in destination cities on labor mobility willingness. Fourth, land finance increases laborers’ willingness to settle.</div></div>","PeriodicalId":45743,"journal":{"name":"Chinese Journal of Population Resources and Environment","volume":"24 1","pages":"Pages 151-164"},"PeriodicalIF":4.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147636810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trends, drivers, and reduction pathways for food-related greenhouse gas emissions in China: 1961–2050","authors":"Jinyu Han ,&nbsp;Jiansheng Qu ,&nbsp;Tek Narayan Maraseni ,&nbsp;Dai Wang ,&nbsp;Jianpeng Zhang ,&nbsp;Li Xu ,&nbsp;Yujie Ge ,&nbsp;Dingye Wu","doi":"10.1016/j.cjpre.2026.03.002","DOIUrl":"10.1016/j.cjpre.2026.03.002","url":null,"abstract":"<div><div>Greenhouse gas (GHG) emissions from China’s food system are a major environmental concern; however, studies quantifying their drivers and future projections remain limited. This study uses structural decomposition analysis and growth curve models to assess food-related GHG trends from 1961 to 2020, identify key drivers and their contributions, and project emissions for 2050 under six economic and population scenarios. It also proposes reduction pathways to help China achieve its 2060 carbon neutrality goal. Animal and plant foods are categorized into 14 groups based on the similarity of their emission coefficients. China’s total food-related GHG emissions rose tenfold, from 351.7 to 3 719.8 million tons CO₂-equivalent (CO₂e)/year, between 1961 and 2020. Per-capita emissions increased from 532.1 to 2 584.4 kg CO₂e/year. Emissions from plant-based foods grew from 435.0 to 824.6 kg CO₂e/year, while animal-based emissions surged from 97.1 to 1 759.8 kg CO₂e/year, with animal products contributing more owing to their higher emission coefficients. Key drivers include rising food intake, increasing demand for animal-based foods (especially red meat), and population growth. Scenario analyses predict that emissions will peak at 3 826.2 million tons CO₂e/year in 2031 (low economy-low population) and 3 971.0 million tons CO₂e/year in 2039 (high economy-medium population). Compared with Australian, Indian, and Japanese diets, Chinese diets exhibit lower per-capita emissions than Australia and India but have higher emissions than in Japan. Adhering to China’s national dietary guidelines could reduce Chinese per-capita food-related GHGs by 31.5%, and optimized diets could lower them by 45.3%. This study provides valuable insights for Chinese policymakers to reduce food-related GHG emissions, refine national dietary guidelines, and raise public awareness regarding the food system’s environmental impact, thus encouraging people to follow sustainable diets.</div></div>","PeriodicalId":45743,"journal":{"name":"Chinese Journal of Population Resources and Environment","volume":"24 1","pages":"Pages 14-26"},"PeriodicalIF":4.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147636797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum to “Critical factors influencing consumer purchases of new energy vehicles: Evidence from a hybrid simulation model and machine learning” [Chinese Journal of Population, Resources and Environment 23 (2025) 494‒504]","authors":"Yong Liu ,&nbsp;Xin Chen","doi":"10.1016/j.cjpre.2026.03.013","DOIUrl":"10.1016/j.cjpre.2026.03.013","url":null,"abstract":"","PeriodicalId":45743,"journal":{"name":"Chinese Journal of Population Resources and Environment","volume":"24 1","pages":"Pages 165-168"},"PeriodicalIF":4.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147636811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect evaluation of carbon sequestration of grassland ecological compensation policy: Evidence from China’s Yellow River Basin","authors":"Xiao Zhang ,&nbsp;Daoxiong Chen ,&nbsp;Shunbo Yao","doi":"10.1016/j.cjpre.2026.03.003","DOIUrl":"10.1016/j.cjpre.2026.03.003","url":null,"abstract":"<div><div>The Grassland Ecological Compensation Policy (GECP) is a large-scale project that has been investing in China since 2011. Despite the significant investment and long duration of the GECP, its impact on carbon sequestration in grasslands remains unclear. Based on panel data from prefecture-level cities in the Yellow River Basin (YRB) from 2000 to 2020, this study explored the effects of the GECP on grassland carbon sequestration in the YRB and its heterogeneity using a time-varying difference-in-differences (TV-DID) model. Subsequently, we predicted changes in carbon sequestration in grasslands under the influence of the GECP from 2021 to 2040 using a simulation. The main conclusions are as follows: First, the implementation of the GECP promoted carbon sequestration in grasslands. This conclusion was validated after conducting a series of robustness tests. Moreover, the effects of the GECP were heterogeneous across different geographical locations, highway densities, and grassland areas. Finally, the simulation results indicated that over the next 20 years, grassland carbon sequestration will generally increase but exhibit cyclical changes. The government should align the principles and objectives of the GECP with local geographic conditions, resource availability, and socio-economic development. It must formulate and implement tailored policies that maximize the ecological protection benefits of the GECP and promote carbon sequestration in the grasslands of the YRB.</div></div>","PeriodicalId":45743,"journal":{"name":"Chinese Journal of Population Resources and Environment","volume":"24 1","pages":"Pages 27-40"},"PeriodicalIF":4.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147636749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cross-border e-commerce pilot zones and corporate carbon emissions reduction: A quasi-natural experiment from China","authors":"Na Jiang ,&nbsp;Qianqian Shang ,&nbsp;Ge Wu","doi":"10.1016/j.cjpre.2026.03.001","DOIUrl":"10.1016/j.cjpre.2026.03.001","url":null,"abstract":"<div><div>Against the backdrop of accelerated development of new forms of trade, the question of whether rapid expansion of cross-border e-commerce (CBEC) can help to reduce carbon emissions among Chinese enterprises is of great significance for seizing new opportunities in foreign trade, and advancing firms’ green and low-carbon transformation. This study treats the creation of CBEC pilot zones as a quasi-natural experiment, employing panel data from Chinese A-share listed companies matched with city-level information from 2006 to 2021. We construct a multi-period difference-in-differences model to identify the impact of CBEC pilot zone policy on corporate carbon emissions. Our findings indicate the construction of these pilot zones significantly reduces firms’ carbon emissions intensity, and the results are robust across multiple tests. We show the pilot zone initiative contributes to emission reductions by enhancing the adoption of digital infrastructure, promoting green technological innovation, and increasing environmental awareness among enterprises. Quantile regressions reveal pilot zones exert a more pronounced carbon-reduction effect on firms characterized by high carbon emissions intensity and advanced levels of digital transformation. Moreover, the policy effect is especially significant in heavily polluting industries, and regions with weaker governmental environmental regulations or lower public environmental concerns. This study makes an innovative contribution to the literature by empirically verifying the environmental governance effect of establishing CBEC pilot zones, and offers practical guidance for governments in formulating cross-border e-commerce policies and for enterprises pursuing low-carbon development.</div></div>","PeriodicalId":45743,"journal":{"name":"Chinese Journal of Population Resources and Environment","volume":"24 1","pages":"Pages 1-13"},"PeriodicalIF":4.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147636796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Urban ecological wealth and digital economy development: Evidence from China","authors":"Pengcheng Bao","doi":"10.1016/j.cjpre.2025.10.002","DOIUrl":"10.1016/j.cjpre.2025.10.002","url":null,"abstract":"<div><div>Existing research has emphasized the environmental effects of the digital economy. However, the question of whether ecological wealth can stimulate digital economic growth remains unanswered. Using panel data from Chinese cities spanning 2011–2022, this study empirically examines how urban ecological wealth affects digital economy development. The results reveal that ecological wealth significantly promotes digital economy growth, with stronger effects observed in coastal and highly urbanized cities. Mechanism analysis shows that ecological wealth advances digital economy development by fostering green technology innovation and enhancing human capital. Additional tests indicate a significant negative spatial spillover effect, suggesting that local ecological wealth may inhibit digital economy growth in neighboring areas. These findings offer valuable policy insights for strengthening ecological wealth accumulation and advancing digital economy development.</div></div>","PeriodicalId":45743,"journal":{"name":"Chinese Journal of Population Resources and Environment","volume":"23 4","pages":"Pages 441-449"},"PeriodicalIF":4.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145847669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Green supply chain management and low-carbon innovation spillover effects","authors":"Xueqin Li ,&nbsp;Chenyang Meng ,&nbsp;Daqian Shi","doi":"10.1016/j.cjpre.2025.10.006","DOIUrl":"10.1016/j.cjpre.2025.10.006","url":null,"abstract":"<div><div>Supply chain partnerships are an essential component of business innovations. This study uses data on A-share listed companies on the Shanghai and Shenzhen stock exchanges from 2012 to 2022 to conduct a multi-period difference-in-differences analysis based on a list of green supply chain management (GSM) companies. We find that GSM significantly promotes low-carbon technology innovations (LCT) of upstream enterprises. The mechanism analysis indicates that GSM has a resource effect and signal effect that generate LCT spillovers. In terms of the resource effect, GSM companies offer green credit and support green procurement, thereby providing financial support for green investments in upstream LCT. In terms of a signaling effect, GSM strengthens the effectiveness of institutional investors, the public, and online media in supervising upstream suppliers’ green credentials, thereby promoting upstream LCT. A heterogeneity analysis shows that when midstream companies are state-owned enterprises or industry leaders, and when the concentration and stability of supply chain purchase relationships are higher, the LCT spillover effects of GSM are more pronounced. Further analysis reveals that GSM has bidirectional horizontal spillover effects and that upstream unidirectional vertical spillover effects are limited to first-level suppliers. Additionally, under the premise of not compromising economic benefits and stability, GSM shows an emerging trend of transitioning from environmentally compliant “light green” supply chains to “deep green” supply chains focused on pollution reduction, carbon reduction, and energy conservation.</div></div>","PeriodicalId":45743,"journal":{"name":"Chinese Journal of Population Resources and Environment","volume":"23 4","pages":"Pages 480-493"},"PeriodicalIF":4.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145847685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Does the integration of finance and technology bring policy dividends for low-carbon development? Quasi-experimental evidence from China","authors":"Ruizeng Zhao ,&nbsp;Jiasen Sun ,&nbsp;Jie Wu","doi":"10.1016/j.cjpre.2025.10.005","DOIUrl":"10.1016/j.cjpre.2025.10.005","url":null,"abstract":"<div><div>Financial technology (FinTech) has emerged as a key policy instrument for transforming economic development models. Whether it can energize the low-carbon economy and enhance carbon emission efficiency (CEE) has drawn increasing scholarly attention. Using panel data from 278 Chinese cities (2006–2021), this study constructs a quasi-natural experiment and applies a difference-in-differences (DID) model to evaluate the policy effects of FinTech on CEE. Mediation and moderation models further explore the mechanisms underlying this relationship. The findings reveal that FinTech significantly improves CEE, generating policy dividends that advance low-carbon development. This conclusion remains robust under dual machine learning causal inference, propensity score matching DID, and other robustness tests. Financing constraints, innovation level, and industrial structure upgrading fully mediate the effect of FinTech on CEE, where financing constraints and innovation show positive mediation effects, while industrial structure upgrading has a negative one. Moreover, financial agglomeration weakens FinTech’s positive influence on CEE, and the effects differ across regions, development levels, and resource endowments. This study broadens the analytical framework connecting FinTech and CEE and deepens understanding of the mechanisms linking financial innovation to low-carbon transition.</div></div>","PeriodicalId":45743,"journal":{"name":"Chinese Journal of Population Resources and Environment","volume":"23 4","pages":"Pages 470-479"},"PeriodicalIF":4.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145847672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}