• Energy Research
• CN close
• Frontiers in Environmental Science close

The influence of climate change on the regional hydrological cycle has been an international scientific issue that has attracted more attention in recent decades due to its huge effects on drought and flood. It is essential to investigate the change of regional hydrological characteristics in the context of global warming for developing flood mitigation and water utilization strategies in the future. The purpose of this study is to carry out a comprehensive analysis of changes in future runoff and flood for the upper Huai River basin by combining future climate scenarios, hydrological model, and flood frequency analysis. The daily bias correction (DBC) statistical downscaling method is used to downscale the global climate model (GCM) outputs from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) and to generate future daily temperature and precipitation series. The Xinanjiang (XAJ) hydrological model is driven to project changes in future seasonal runoff under SSP245 and SSP585 scenarios for two future periods: 2050s (2031–2060) and 2080s (2071–2100) based on model calibration and validation. Finally, the peaks over threshold (POT) method and generalized Pareto (GP) distribution are combined to evaluate the changes of flood frequency for the upper Huai River basin. The results show that 1) GCMs project that there has been an insignificant increasing trend in future precipitation series, while an obvious increasing trend is detected in future temperature series; 2) average monthly runoffs in low-flow season have seen decreasing trends under SSP245 and SSP585 scenarios during the 2050s, while there has been an obvious increasing trend of average monthly runoff in high-flow season during the 2080s; 3) there is a decreasing trend in design floods below the 50-year return period under two future scenarios during the 2050s, while there has been an significant increasing trend in design flood during the 2080s in most cases and the amplitude of increase becomes larger for a larger return period. The study suggests that future flood will probably occur more frequently and an urgent need to develop appropriate adaptation measures to increase social resilience to warming climate over the upper Huai River basin.

The global community has set intensive targets in Sustainable Development Goals (SDGs) to better people’s lives after closing the Millennium Development Goals (MDGs). It corresponds to the 2030 aspirations of the United Nations to enhance and promote the sustainable development of human society. The current paper explores the impact of fiscal hedging and R&D in energy Using a green-energy system in SDGs. To do this, we used TOPSIS and QARDL methodologies on a 21-year dataset of South and Southeast Asian economies from 2000 to 2020. The study results show that fiscal hedging contributes favourably to the environmental degradation of the underlying economy. Research and development (R&D) in renewables has contributed negatively to ecological degradation and SDGs in the economies of South & Southeast Asia. This study suggests policy guidelines for advanced and developing economies based on fiscal stability and technical innovation through R&D to meet SDG.

The accuracy of carbon emission data is essential for various disciplines to maintain reasonable expectations and certainty regarding the carbon emission rights trading market. However, the management of carbon emission data quality faces many challenges, especially due to the harmful behavior of enterprises that falsify such data, which seriously disrupts the order and credibility of the carbon market. Currently, few studies focus on the behavior and mechanism of corporate carbon emission data fraud, which requires an in-depth stakeholder analysis to obtain theoretical and empirical support for the formulation of effective regulatory policies. To investigate the influence of government regulation and media monitoring on addressing enterprise carbon emission data falsification, as well as to analyze the game behaviors and equilibrium outcomes among the government, media, and enterprises under different policy combinations and market environments, this study develops an evolutionary game model incorporating the government, media, and enterprises as three key stakeholders. Furthermore, numerical simulations are conducted for empirical validation. The key findings of this research highlight the significant impact of government regulation and media monitoring on deterring enterprise carbon emission data falsification, thus effectively reducing falsification motives and behaviors and enhancing the quality of carbon emission data. Additionally, the game between the government, media, and enterprises reveals the existence of multiple evolutionary stable strategies. Of these, the optimal strategy is the comprehensive implementation of all three elements: government regulation, media monitoring, and corporate integrity disclosure. This paper comprehensively examines the influence of government regulation and media monitoring on enterprise carbon emission data falsification and addresses the gaps in existing research. Moreover, it provides theoretical guidance and policy recommendations for establishing a high-quality carbon market.

The global economy is undergoing a transformative shift propelled by continuous technological advancements. This digital revolution has ushered in a new era characterized by the pervasive influence of the digital economy. Notably, the inherent “green” attributes of the digital economy, such as reduced marginal costs and diminished environmental impact, have injected fresh momentum into the green transformation of the industrial sector. Using spatial econometric model, we examine the impact of the digital economy on the green transformation of the manufacturing industry using panel data for 283 prefecture-level Chinese cities from 2011 to 2019. We first calculate the level of the manufacturing industry’s green transformation in this paper according to the Slack-Based Measure model. The green transformation of the industrial sector is facilitated by the digital economy in both the eastern and central regions, as revealed by heterogeneity analysis based on geographical areas. The moderating effect analysis reveals a distinct negative moderating impact of industrial structure upgrading and industrial agglomeration. Additionally, the threshold effect tests indicate significant nonlinear features in the influence of industrial structure upgrading on the green transformation of the manufacturing industry.

The contribution of artificial reservoirs to greenhouse gas (GHG) emissions has been emphasized in previous studies. In the present study, we collected and updated data on GHG emission rates from reservoirs at the global scale, and applied a new classification method based on the hydrobelt concept. Our results showed that CH4 and CO2 emissions were significantly different in the hydrobelt groups (p < 0.01), while no significant difference was found for N2O emissions, possibly due to their limited measurements. We found that annual GHG emissions (calculated as C or N) from global reservoirs amounted to 12.9 Tg CH4-C, 50.8 Tg CO2-C, and 0.04 Tg N2O-N. Furthermore, GHG emissions (calculated as CO2 equivalents) were also estimated for the 1950–2017 period based on the cumulative number and surface area of global reservoirs in the different hydrobelts. The highest increase rate in both the number of reservoirs and their surface area, which occurred from 1950 to the 1980s, led to an increase in GHG emissions from reservoirs. Since then, the increase rate of reservoir construction, and hence GHG emissions, has slowed down. Moreover, we also examined the potential impact of reservoir eutrophication on GHG emissions and found that GHG emissions from reservoirs could increase by 40% under conditions in which total phosphorus would double. In addition, we showed that the characteristics of reservoirs (e.g., geographical location) and their catchments (e.g., surrounding terrestrial net primary production, and precipitation) may influence GHG emissions. Overall, a major finding of our study was to provide an estimate of the impact of large reservoirs during the 1950–2017 period, in terms of GHG emissions. This should help anticipate future GHG emissions from reservoirs considering all reservoirs being planned worldwide. Besides using the classification per hydrobelt and thus reconnecting reservoirs to their watersheds, our study further emphasized the efforts to be made regarding the measurement of GHG emissions in some hydrobelts and in considering the growing number of reservoirs.

There is no consensus on whether state-owned enterprises (SOEs) or privately-owned enterprises (POEs) pollute more. This study explores the impact of ownership on pollution emission intensity using micro-data from Chinese industrial enterprises. From the perspective of energy efficiency, the mechanism of ownership affecting pollution emissions is explored further. Research results show that the pollution emission intensity of SOEs is significantly higher than that of POEs. The underlying reason is the low energy efficiency of SOEs, and energy efficiency plays an important mediating role in the relationship between ownership and pollution emissions. Among industrial waste gas, nitrogen oxides (NOx) and dust emissions, energy efficiency plays the largest mediating effect between ownership and NOx emissions. Additionally, in both high-polluting and low-polluting industries, SOEs’ pollutant emission intensity is higher than that of POEs, however, the mediation effect of energy efficiency is greater in low-polluting industries. In cities with high growth pressure, SOEs’ pollutant emission intensity is more significant than that of POEs. On the contrary, there are no noticeable differences in pollutant emission intensity between SOEs and POEs in cities with low growth pressure. But the mediation effect of energy efficiency is more significant in cities with high growth pressure. Industrial enterprises are the ultimate sources of industrial pollution. Therefore, the formulation of effective environmental policies cannot be separated from the analysis of enterprises’ emission behaviors and the assessment of micro factors affecting emissions. The conclusions of this study provide a basis for developing countries to formulate environmental policies for industrial enterprises.

Geothermal energy is a renewable energy source, and geothermal heating is a livelihood project, so a resource tax can protect resources and regulate prices. Reasonable geothermal energy resource tax collection standards are conducive to high-quality industrial development. This paper takes 15 provinces and cities that clearly levy geothermal resource taxes in China as the research object, constructs an System Dynamics model of geothermal resource tax, and studies the impact of geothermal resource tax on the income of geothermal enterprises and CO2 emission reduction. Then, the forecast simulates the economic and environmental benefits brought about by the use of geothermal resources from 2021 to 2035. The research results show that using geothermal resources for heating can significantly reduce CO2 emissions, and the higher the proportion of geothermal use is, the greater the CO2 emission reduction before 2035. The fifteen provinces and cities that clearly levy geothermal resource taxes will find it difficult to achieve corporate profits at the current residential heating utilization price and geothermal energy resource tax rate; that is, to achieve a balance of income and expenditures for geothermal enterprises without financial subsidies, the price of geothermal heating will be significantly higher than the heating price of traditional central heating and the price of electric self-heating.

Climate change has become a major challenge in recent decades as a result of rapid economic growth due to increased energy use and a rise in urbanization. Environmental damage induced by energy use, urbanization, and economic growth can be overcome by technological advancement and good governance. This study examines the effect of urbanization, technological innovations, and economic growth on carbon dioxide emissions in the Belt and Road initiative countries from 2002 to 2022. By using GMM model, the results show that, technological innovations and foreign direct investment raise carbon dioxide emissions however, research and development enhance environmental quality. This study also found that urbanization has a nonlinear relationship with carbon emission where effective governance exert a moderating role in this association. This study provides important policy suggestions for BRI countries.

Population and industry are closely related to CO2 emissions in Cities. However, few studies have explored the joint influence of population size and industrial structure on CO2 emissions. This paper examined the nonlinear influence of population size and industrial structure on CO2 emissions by using a threshold-STIRPAT model with the latest available data in 2001–2017 from 255 cities in China. Results indicated that the promotion effect of urban population size on CO2 emissions increased in the first two stages and then decreased in the third stage when the industrial structure exceeded the threshold value of 1.22. Meanwhile, the industrial structure had a positive impact on CO2 emissions if the urban population was less than 1.38 million. However, the previous promotional effect became an inhibitory effect when the urban population exceeded 1.38 million. According to the above findings, it is necessary to find a reasonable match between urban population size and industrial structure. Specifically, China should formulate differentiated urban population policies in cities with different industrial structures. In addition, for cities with a population size of more than 1.38 million, adjusting the industrial structure to give priority to the tertiary industry will be an effective way to reduce CO2 emissions.

Regional carbon emissions related to forest cover change (FCC) and wood harvest (WH) are critical for the accurate estimates of global carbon balance over an extended time period. Using remote sensing and inventory data, this study provides a comprehensive record of FCC, WH, and their integrated carbon emissions between 1908 and 2015 in the dry temperate regions of Pakistan. Results demonstrate a significant decline in forest area (21,034 ha) at an annual rate of 0.56% from 1973 to 2015. The total WH was 24.84 million m3 (0.23 million m3 yr−1) between 1908 and 2015. Deforestation was responsible for a net loss of 1.39 million Mg C (0.018 million Mg C yr−1), while WH-related carbon emissions accounted for 11.29 million Mg C (0.52 million Mg C yr−1). The present results indicate that under the existing FCC and WH harvest scenario, the forests are acting as a net source of 0.29 million Mg C yr−1. Agriculture expansion and the heavy dependency of local communities on the forest’s resources, exclusion of conservation and local communities from forest management, insufficient monitoring, and weak law-enforcement were the striking drivers of FCC, WH, and their related emissions. These findings suggest that to maintain forest carbon and meet the communities’ requirements, counter approaches such as agriculture incentives, agroforestry, trophy hunting, alternative energy sources, and inclusion of conservation and secure community-based management are needed.