The development of information and communication technology (ICT) has significantly transformed various aspects of our daily lives, including health. This study aims to investigate the impact of ICT on self-assessed health (SAH) and explore the mechanisms through which this relationship operates. Based on data from the China Health and Nutrition Survey (CHNS) collected between 2004 and 2015, we employ ordinary least squares regression, an ordered probit model, and a structural equation model to examine the impact of ICT on SAH. The results show that ICT has a significant positive effect on SAH, particularly among high-income, rural, and younger to middle-aged individuals. On average, an additional one-percentage-point increase in ICT diffusion is associated with a 0.236-point improvement in SAH. Furthermore, the mechanism analysis reveals that approximately 17.50% of ICT’s impact on SAH can be attributed to improvements in physical activity (13.3%) and nutrition (4.2%). Additionally, a back-of-the-envelope calculation suggests that approximately 0.78–2.09 million Chinese individuals would benefit from greater access to ICT in terms of health. This study highlights the critical role of ICT in improving health outcomes, provides feasible policy recommendations for leveraging ICT for development (ICT4D), and contributes to achieving Sustainable Development Goal 3 (Good Health and Well-Being) in emerging economies during the digital era.

Effective management of protection areas (PAs) has long been a world-wide difficulty, especially for developing countries. National nature reserves, as the highest level of officially certified PAs in China, have been widely established for the purpose of strengthening ecological protection. In this study, we use the establishment of 471 national nature reserves (NNRs) as a quasi-natural experiment to evaluate their performance on anti-human disturbance based on the multi-period difference-in-difference model. We find that: (1) there is a significant threshold in the effects of upgrading administrative level for PAs: the establishment of national nature reserves has led to a significant decrease in nighttime light intensity, while other administrative level upgradation has little influence.; (2) effectiveness of PAs differs across geographic areas and management situations. Our findings suggest that (1) providing sufficient authority for PAs in to operate independently from grassroot governments is of great necessity; (2) clarifying government responsibilities, increasing resources investment, and strengthening supervision are key to improve effectiveness of PAs; (3) allowing regulations to vary in stringency over space may provide greater environmental benefits. These empirical findings provide evidence that establishing national PAs is critical for addressing conservation gaps and enhancing conservation effectiveness.

One popular explanation for the Easterlin paradox is that income growth over time is usually accompanied by industrialization and pollution, which cause damage to happiness that cannot be reflected by income change. We examine this explanation by exploring the effects of a large-scale environmental regulation program -the "Two Control Zones (TCZ)" Policy- on subjective well-being (SWB) using data from a series of household surveys in China. We find that, the regulation has successfully mitigated air pollution in the implemented area, although at the cost of local income. Overall, the environmental effect dominates the income effect and TCZ policy increases the SWB of affected people. In particular, despite its negative effect on income, by controlling air pollution, the TCZ policy brought a net increase in residential happiness with a money value of ￥59.04 per month in terms of 2009 CNY. This finding supports the environmental explanation of the Easterlin paradox.

Gender equality, as a fundamental human right, is a key pillar of sustainable development because it boosts productivity, promotes social cohesion, and supports green growth. This study investigates how gender equality (GEQ) and green finance (GRF) influence green growth (GRG) across 36 OECD countries from 1990 to 2022, using a double machine learning method to address potential endogeneity and model uncertainty. The results show that both GEQ and GRF have a positive impact on GRG, with regulatory quality serving as a moderating factor. Specifically, a one-unit increase in GEQ and GRF corresponds to a 0.55% and 0.13% increase in GRG, respectively. Furthermore, GEQ promotes GRG through enhancing environmental tax effectiveness, supporting green technology and boosting green R&D investment. These results provide valuable policy recommendations to improve gender equality and support Sustainable Development Goal (SDG) 8.

As a key stakeholder in global economic and environmental progress, China plays a pivotal role in advancing sustainability. This study examines China's Go Global (GG) strategy impact on green growth (GRG) across BRI and non-BRI economies from 2000 to 2023. The findings from double machine learning (DML) and traditional econometric methods indicate that the GG strategy significantly enhances GRG in BRI and non-BRI economies. These findings are further validated through the absence of endogeneity issues and robustness checks. Meanwhile, green initiatives like BRIGC, BRF, and BRI are instrumental in linking the GG strategy and GRG. Moreover, considering aggregate analysis and excluding global major shocks (i.e., the COVID-19 pandemic, the US-China trade war, and the global financial crisis) confirms that the GG strategy consistently promotes GRG, highlighting its resilience and effectiveness. Policymakers should integrate sustainable practices into infrastructure and transport, enhance biodiversity finance, and prioritize green energy and green innovation through expanded green financing to support green growth (SDG 8) across BRI and non-BRI countries.

Preserving energy security and promoting sustainable development in the face of globalization constitute essential challenges. Hence, this study focuses on how green technology innovation (GRTI) and globalization (GLOB) influence renewable (RE) and non-renewable (NRE) energy demand, employing panel data from 15 emerging nations from 1990 to 2023. The study discloses major insights employing several panel data approaches to tackle cross-sectional dependency, slope heterogeneity, and structural breaks in cointegration. The results indicate that a 1 % change in GRTI leads to a 0.13 % rise in REN at a 1 % significance level, whereas its impact on NRE is negligible, reducing it by 0.01 % in the long run. Conversely, a 1 % increase in GLOB leads to an insignificant 2.62 % rise in REN and a significant 1.02 % increase in NRE at the 5% significance level. Besides, in terms of aggregate energy consumption, GRTI has an unfavorable impact, whereas GLOB holds a positive impact. Notably, the interaction between regulatory quality (REQ) and IVA implies a substantial fall, although the interaction between GLOB and REQ remains promising for aggregate energy demand. Finally, the COVID-19 epidemic markedly enhanced environmental awareness and energy-saving behaviors beyond the explanatory variables. Policies should encourage green technology innovation and prudent globalization to conserve energy demand.

The shift to zero-carbon emissions nurtures enormous economic opportunities owing to stimulating the creation of new industries, offering jobs, and driving technological innovation. This study aims to investigate the dynamics among public–private energy investment, natural resources rent, environmental technologies, and carbon neutrality in China over the period spanning from 1984 to 2021. We employ the autoregressive distributed lag (ARDL) method to determine the long-term and short-term connections between those factors. The Kernel-based Regularized Least Squares (KRLS) machine learning approach is used for the robustness check. Our findings demonstrate that while public-private energy investment and environmental technology decrease, natural resources rent is linked to increased carbon emissions. Moreover, the moderating effect of natural resources rent and environmental technology raises the success rate of public-private energy investment in supporting net-zero emissions. . The study findings call for reassessing policy priorities to harness the potential of investments and innovations in environmental protection, while addressing the challenges of urbanization and economic growth.

This study investigates the impact of green finance (GF) and green innovation (GI) on corporate credit rating (CR) performance in Chinese A-share listed firms from 2018 to 2021. The least absolute shrinkage and selection operators (LASSOs) machine learning algorithms are first used to select the critical drivers of corporate credit performance. Then, we applied partialing-out LASSO linear regression (POLR) and double selection LASSO linear regression (DSLR) machine learning techniques to check the impact of GF and GI on CR. The main results reveal that a 1% increase in GF diminishes CR by 0.26%, whereas GI promotes CR performance by 0.15%. Moreover, the heterogeneity analysis reveals a more significant negative effect of GF on the CR performance of heavily polluting firms, non-state-owned enterprises, and firms in the Western region. The findings raise policies for managing green finance and encouraging green innovation formation, as well as addressing company heterogeneity to support sustainability.

[Objective] This study aimed to explore the intrinsic mechanisms of intelligent collaborative management of resources and the environment, providing valuable insights to advance the integration of collaborative management theory and smart technologies in the field of resource and environmental management. The objective was to facilitate research in the Chinese context and promote green sustainable development. [Methods] Starting with a review of relevant literature in collaborative resource and environmental management, we synthesized an integrated research framework for intelligent collaborative management of resources and the environment. The framework elucidates the conceptual content, key issues, methodological systems, and implementation pathways of intelligent collaborative management, offering a forward-looking perspective on future research directions and emphasizing topics that need further exploration in the Chinese context. [Results] The proposed integrated research framework encompasses the core content of intelligent collaborative management of resources and the environment, addressing three key issues related to mechanism and standards, theories and methods, and industrial models. Three intersecting research methods are delineated, along with three pathways for achieving collaborative development through the innovation of intelligent technologies, platforms, and models. [Conclusion] There is a need to emphasize the indigenous characteristics of intelligent collaborative management of resources and the environment in the Chinese context. The study underscored the importance of exploring how environmental regulations can promote collaborative development of resources and the environment, researching the architecture and mechanisms of intelligent ecological governance systems, and addressing potential regional development inequalities resulting from digitalization and intellectualization. This research provides valuable Chinese experiences and insights to empower global sustainable development goals through intelligent technologies.

Docked vessels in ports can be one of the dirtiest emitters in terms of local air pollutants. This paper evaluates whether the regulation of Emission Control Areas in China reduces air pollutants emissions in port cities. The transboundary spillovers of air pollution, induced by meteorological conditions, results in air pollution concentrations at specific locations encompassing both locally generated pollutants and those originating from elsewhere. Therefore, it is challenging to discern the emission reduction effects of environmental regulatory policies through air pollutant monitoring concentrations. This paper develops an approach to isolate transboundary spillovers induced by the wind, estimate locally produced pollution, and utilize the concentrations of locally produced pollution to identify the treatment effects of the Chinese Emission Control Areas policy. The results find that the policy has significantly reduced the locally produced sulfur dioxide concentrations by 3.41% in port cities. However, the omission of transboundary spillovers could yield contrasting results, suggesting that ignoring the pollution transport could lead to erroneous conclusions. The research findings of this study hold significant policy implications, highlighting the importance of accounting for transboundary transport of air pollution in evaluating the local government’s environmental efforts and implementing supra-city environmental policies to prevent air pollution.

As a critical digital infrastructure,computing power has become the core productivity and a new engine driving economic growth in the digital economy.Nevertheless,the power-hungry nature of computing/data centers,representing the computing infrastructure,consumes a significant amount of electrical energy.Currently,China's economy is transitioning from high-speed growth to high-quality development.It is imperative to study how to coordinate the development of computing power while ensuring its safety and achieving green and low-carbon goals.Based on an overview of the current status of computing power development,this study predicts the future demand for computing power in China,analyzes the relationship between future computing power growth and electricity consumption,and discusses the associated challenges.From the perspectives of top-level design,regional layout,platform construction,and market mechanisms,this study proposes strategies and measures to accelerate the green and low-carbon transformation of computing power,providing support for sustainable computing power transformation and empowering the high-quality development of the digital economy.

Extreme weather poses significant challenges to agricultural supply chain management, especially in developing countries. In this paper, we investigate to what degree can the adjustment of sales channels mitigate the economic consequences of supply chain risks of fresh agricultural products driven by extreme weather. Exploiting a field survey of fresh agricultural products from smallholder farmers in rural China, we empirically show that the high temperatures driven-supply risks can be mitigated by sales channel adjustment from offline to online and thus increase producers' agricultural profit. One percentage point increase in online channel sales driven by high temperature raises farmers' unit profit growth by 1.12 CNY. In the absence of sales channel adjustment, farmers’ agricultural economic losses due to high temperatures could be up to 26.65% higher. These findings are significant not only because high temperature events are predicted to increase significantly in the future, but also because they shed light on how smallholder farmers with limited adaptability to extreme weather can better adapt to adverse conditions by supply chain management - thus prospering rural e-commerce and development.

The assessment of environmental and health impacts stemming from sports mega-events plays an important role in evaluating the overall cost–benefit of the events. This study utilizes microdata sourced from the China Household Income Project in conjunction with a time-varying difference-in-differences methodology. Through this approach, we estimated the impact of the 2010 Guangzhou Asian Games on both air quality and public health conditions within China. The results reveal the following: (1) The Games wield substantial and favorable effects on self-perceived health; (2) The primary avenue through which the Games improve self-perceived health is by mitigating air pollution levels in the cities associated with the Games; (3) The cost–benefit analysis unveils that hosting the Games has led to a reduction of 1103.12 million RMB in residents’ medical expenses, with the improved air quality accounting for 20.15% of the cost reduction.

This paper examines how foreign direct investments (FDI) affect energy consumption in the panel data of 29 Belt and Road Initiative (BRI) economies from 2000 to 2021. The paper runs several panel data techniques, which concurrently accommodate the dataset's cross-sectional dependency, slope heterogeneity, and structural break concerns in the cointegration. The results show that global FDI positively affects energy consumption. China's FDI dominance also has a favorable effect on energy consumption. In addition, green technologies increase energy consumption. These results emphasise the significance of FDI policies and green technologies regarding promoting energy demand in the BRI economies.

全球气候变化引起了世界各地的广泛关注,国际社会呼吁严格控制与能源相关的二氧化碳排放,企业实施节能减排投资是减缓气候变化的重要策略.基于期权价值理论,本文提出了一个企业依据产出水平应对气候变化不确定性的节能减排投资决策规则.首先给出了一个传统的企业投资决策规则;然后在期权价值理论基础上,构建了一个不确定性产出模型,并分别基于不同的减排成本函数形式,推导出新的企业最优减排项目投资规则;最后进行数值模拟,分析了气候变化不确定性和社会贴现率等因素对企业最优投资时点的影响及企业投资期权价值的动态变化路径,验证了该投资规则的适用性.本研究设计的企业最优适应性投资规则考虑了气候变化的不确定性和贴现率,可以为企业应对气候变化的投资决策提供理论指导,具有重要的实践意义.

This paper analyzes how air pollution disclosure reshapes tourism in China. We show, in theory, that air pollution information may change tourism activities, depending on the pollution level disclosed. Using the difference-in-differences approach and panel data across 297 cities, our empirical analyses confirm significant positive effects of air pollution information disclosure. The impact, however, is moderated by the level of air pollution. Only cities with low air pollution are happy with disclosing the information while in cities with high air pollution, disclosing air pollution may exert negative effects. Overall, the results indicate that air pollution reduces information transparency's positive impact on tourism. This urges tourism managers to use the instrument of environmental information to reduce pollution and boost local tourism.