Groundwater-dependent irrigation costs and benefits for adaptation to global change

Unintended consequences: China's pairing assistance policy and carbon emissions in administrative border areas -evidence from China.

Using panel data of 30 provinces and regions in Mainland China (excluding Tibet) from 2006 to 2016, the Spatial Durbin Model was employed for the empirical research, and the spatial impact of fiscal decentralization and environmental decentralization on regional carbon emissions were analyzed from the perspective of promotion pressure of officials. The empirical study concludes: ① Fiscal decentralization, both within the region and in its neighborhood, will contribute to carbon emissions in the region; ② Environmental decentralization will help reduce carbon emissions, while environmental decentralization in neighboring regions will increase carbon emissions in the region; ③ The promotion pressure of officials plays a positive role in moderating the impact of fiscal decentralization on carbon emissions, and at the same time weakens the suppression of carbon emissions by environmental decentralization; ④ From a regional point of view, there is a positive relationship between fiscal decentralization and carbon emissions in various regions; but environmental decentralization has obvious spatial heterogeneity. The research suggests that reducing the degree of local fiscal decentralization, investment in major infrastructure projects involving high carbon emissions should be relatively centralized; appropriately increase the environmental management authority of local environmental protection agencies, fully use the advantages of local environmental protection departments to protect the environment according to local conditions; gradually improve the assessment system for local officials, moderately reduce the proportion of fiscal revenue and GDP assessment in areas with fragile ecological environment, and increase incentives for ecological performance assessment, put the development of low-carbon economy into practice.

The massive use of energy has caused a rapid increase in global carbon dioxide emissions, resulting in a series of environmental problems such as climate warming. Investment in the energy industry can guide funds into green and clean production, reduce carbon emissions in the energy industry, and promote the green development of the energy industry. This paper considers the energy, the environment, the economy, and other factors and focuses on energy consumption and investment structure. Taking 30 provinces in China as research samples, a dynamic spatial Durbin model is established. The results show that the first-order term of carbon emissions has a driving force of 0.5068% for current carbon emissions at a significance level of 1% and that the increase in current carbon emissions will lead to a continued increase in carbon emissions in the next period. The increase in the carbon emissions of neighbouring provinces will increase their carbon emissions through the spatial spillover effect. Whether in the short term or long term, the increase in energy investment and the optimization of the energy investment structure can reduce carbon emissions. The above conclusions can provide a reference for the formulation of government environmental policies.

In the context of the "dual carbon" strategy, the transportation industry actively seeks a new development path of low-carbon transformation, which is one of the hot spots in China's carbon emission reduction. Based on the Tapio decoupling and logarithmic mean Divisia index （LMDI） models, this study analyzed the carbon emission characteristics, decoupling status, and driving factors of China's provincial transportation industry from multiple perspectives, such as overall, time period, and regional decomposition from 2012 to 2021. The results showed that China's total carbon emissions from transport sector exhibited an increasing trend with passing years overall, but growth rate showed decreasing trend. The spatial distribution pattern of carbon emissions from transportation industry was higher in the southeast and lower in northwest. During the past decade, 40.0% of the provinces achieved absolute decoupling between carbon emissions from transportation industry and economic development, and 53.3% of the provinces achieved relative decoupling. From the perspective of the transportation industry, economic growth, population size, and carbon emission coefficient promoted an increase in carbon emissions, while transportation energy intensity and industry scale inhibited the increase in carbon emissions. Therefore, during the process of realizing the "dual carbon" goal in China, each province should formulate differentiated reduction policies in regional carbon emissions according to local conditions, actively assume emission reduction responsibilities, increase efforts to promote the decoupling process, and promote the green and low-carbon transformation of the transportation industry.

Since the reform and opening-up, China has made remarkable achievements in economic growth, but also led to a substantial increase in carbon emissions. The Chinese government has actively formulated energy intensity reduction targets and taken carbon emission reduction measures. The paper investigates the impact of energy intensity reduction targets on carbon emissions using a dynamic spatial Durbin model based on panel data from 30 provinces in China from 2006 to 2019. The results show that energy intensity reduction targets promote the reduction of local carbon emissions, but have a positive spillover effect on carbon emissions in adjacent regions. Meanwhile, green technology innovation has a non-linear moderating effect between energy intensity reduction targets and carbon emissions. Energy intensity reduction targets promote carbon emission reduction when green technology innovation is less than a threshold, while the promotion effect disappears when green technology innovation exceeds a threshold. The mechanism analysis shows that energy consumption structure is a channel through which energy intensity reduction targets affect carbon emissions in both local and adjacent regions. Further research found that peer competitive pressure promotes carbon emission reduction and alleviates pollution spillover, while central assessment pressure increases carbon emissions and aggravates pollution spillover. Based on the above findings, this study provides suggestions for policymakers aiming at carbon emission reduction by implementing target management policies and optimizing target management systems.

The existing literature tends to overlook the trade‐off between the local government's dual goals of achieving economic growth targets and protecting the environment. This study reveals the adverse effects that local governments may have on the environment under the pressure of economic growth, indicating that an increase in regional economic growth targets is associated with an increase in local carbon emissions. Using data from Chinese prefecture‐level cities from 2000 to 2021, we find a 1% increase in the GDP growth target is associated with an increase in carbon emissions per unit of GDP of 1.6%. The mechanism analysis indicates that a higher regional growth target results in the entry of highly polluting new enterprises and a reduction in environmental protection‐related inputs, which consequently leads to an increase in carbon emissions. The implementation of administrative and market‐based policies, including government policy planning and piloting of emission rights, can mitigate the driving effect of growth targets on carbon emissions. This study provides new evidence on the impact of regional economic growth pressures on carbon emissions and serves as an important reference for governments seeking to formulate effective carbon emission reduction policies.

Global warming continues to be an intimidating factor for environmental protection, and reducing carbon emissions is an effective way to deal with the phenomenon. However, the energy sector is a significant contributor to greenhouse gas emissions. Therefore, investment in environmental regulations and research and development (R&D), is critical for fostering a low-carbon growth model. This study focuses on 30 provinces in China from 2004 to 2019. We used the spatial Durbin model to investigate how the spatial spillover effect of R&D and environmental regulation impacts carbon emissions. In addition, we applied the dynamic threshold panel model to mitigate potential problems of endogeneity. The results reveal that carbon emissions have a considerable spatial correlation in both temporal and spatial dimensions, exhibiting high and low-value accumulation characteristics. Furthermore, the combined effect of R&D intensity, environmental regulation, and energy consumption were found to contribute to the increase in carbon emissions across China's provinces, and they also suggest different influencing mechanisms. The spillover effects of increased carbon emissions in neighboring regions also contribute to the increase in local carbon emissions. The study also found that R&D and stringent environmental regulations measures strongly moderate the link between energy consumption and carbon emissions. In promoting carbon reduction, by breaking the dynamic equilibrium in China, the provincial investment outflow on R&D intensity could be optimized, and the regional levels should focus more on tightening environmental regulatory measures and promoting the development of energy-conserving technologies.

The carbon emission level and spatiotemporal characteristics in Hubei Province were estimated and studied using the Intergovernmental Panel on Climate Change (IPCC) carbon emission coefficient technique based on county data from Hubei Province from 2000 to 2020. The relationship between carbon emissions from cultivated land utilization and agricultural economic growth was examined using the Tapio decoupling index, and the factors influencing carbon emissions in Hubei Province were further examined using the Logarithmic Mean Divisia Index (LMDI model). The results demonstrate that: (1) Spatiotemporal variations in carbon emissions are evident. In terms of time, the volume of carbon emissions in Hubei Province is still substantial, and the transition to low-carbon land use is quite gradual. Geographically, the high-value region of the middle east coexists with the low-value zone of the west, with apparent regional contrasts. (2) The decoupling between carbon emissions and agricultural economic growth is becoming more and more obvious in Hubei Province. The number of counties and cities in a negative decoupling state has significantly decreased, and the majority of counties are now in a strong decoupling condition. (3) Agricultural production efficiency is the most significant driving factor for restricting carbon emission, according to the decomposition results of carbon emission driving factors based on the LMDI model. In addition, the results of sample decomposition based on topographic characteristics indicate that agricultural production efficiency is primarily responsible for the suppression of carbon emissions in flat regions. The increase in carbon emissions in hilly regions is primarily influenced by agricultural productivity. The increase in carbon emissions in mountainous regions is mostly influenced by agricultural labor intensity. This study′s finding has enlightening implications for the high-quality growth of agriculture.

Energy investment, economic growth and carbon emissions in China—Empirical analysis based on spatial Durbin model

With the accelerated development of the aging trend in Chinese society, the aging problem has become one of the key factors affecting sustainable economic and social development. Given the importance of controlling carbon emissions for achieving global climate goals and China's economic transformation, studying the spatial and temporal effects of population aging on carbon emissions and their pathways of action is of great significance for formulating low-carbon development strategies adapted to an aging society. This paper aims to explore the spatial-temporal effects of population aging on carbon emissions, identify the key pathways through which aging affects carbon emissions, and further explore the variability of these effects across different regions. The findings will provide theoretical support and empirical evidence for government departments to formulate policies to promote the coordinated development of a low-carbon society and an aging society. Based on the panel data of 30 provinces in China from 2004 to 2022, this paper systematically investigates the impact of population aging on carbon emission intensity from both spatial and temporal dimensions by using the spatial Durbin model and the mediating effect model. The direct effect of aging on carbon emission intensity, the spatial spillover effect, and the indirect effect through mediating variables such as residents' consumption, environmental regulation, and new urbanization are analyzed in depth. The study found that population aging in China has significant spatial and temporal effects on carbon emissions. From the spatial dimension, there is a significant spatial spillover effect of the effect of aging on carbon emissions, and aging reduces local carbon emissions but increases carbon emissions in adjacent regions. From the time dimension, the effect of aging on carbon emissions shows a stage characteristic, initially it will reduce carbon emissions, but with the deepening of aging, its effect may tend to weaken. In addition, this study identifies a number of key pathways through which aging affects carbon emissions, including reducing residential consumption, promoting new urbanization, and increasing the intensity of environmental regulations. Finally, this study explores the regional heterogeneity of the impact of aging on carbon emissions and its mechanism of action. This study is instructive: first, the complex impact of population aging on carbon emissions should be fully recognized to formulate a comprehensive low-carbon development strategy; second, attention should be paid to the spatial spillover effect of aging on carbon emissions to strengthen inter-regional cooperation and coordination; and lastly, differentiated low-carbon policies should be formulated to address the characteristics of aging in different regions and stages in order to promote the synergistic development of a low-carbon society and an aging society.

In the context of trade protectionism impacting economic and environmental sustainability, a more comprehensive understanding of the impact of trade on carbon emissions is critical to economic and environmental sustainability. Existing literature mainly explores the impact of trade on carbon emissions from the perspective of trade openness, neglecting the perspectives of trade diversification and trade direction. This study aims to fill this gap by investigating the impact of trade openness (measured by trade volume, import, and export), and trade diversification (measured by import diversification and export diversification) on carbon emissions based on data from OECD and G20 countries between 1997 and 2019. The study further explores the heterogeneity, asymmetry, and mediation effects. The results demonstrate that (i) the impact of trade on carbon emissions is heterogeneous, with trade openness leads to an increase in carbon emissions, while trade diversification leads to a reduction in carbon emissions. Moreover, import diversification has the strongest effect on reducing carbon emissions. (ii) The impact of trade openness on carbon emissions is asymmetry. Trade openness increases carbon emissions at 10%–50% quantile levels and reduces carbon emissions at 80%–90% quantile levels. However, the impact of trade diversification on carbon emissions is consistent. (iii) The impact of trade openness on carbon emissions is mediated by technology effect and structural effect. On one hand, trade openness leads to an increase in carbon emissions by the industrial structure. On the other hand, it contributes to the reduction of carbon emissions by technological progress. These findings could serve to better understand the complexity of free trade's impact on economic and environmental sustainability.

Spatial and temporal evolution characteristics and spillover effects of China's regional carbon emissions

Banking competition and regional carbon emissions: Intensifying or suppressing? – Estimation based on a bilateral random frontier model

Exploring the role of nuclear energy in the energy transition: A comparative perspective of the effects of coal, oil, natural gas, renewable energy, and nuclear power on economic growth and carbon emissions

Decoupling China's economic growth from carbon emissions: Empirical studies from 30 Chinese provinces (2001–2015)