Bioenergy consumption, carbon emissions, and agricultural bioeconomic growth: A systematic approach to carbon neutrality in China

Can the development of the rural digital economy reduce agricultural carbon emissions? A spatiotemporal empirical study based on China's provinces

Rapid advancement of the rural digital economy has intensified the demand for leveraging digital tools to foster low-carbon and sustainable agricultural practices, garnering widespread academic and bureaucratic attention. Understanding how the rural digital economy influences agricultural carbon emissions is crucial for unlocking emission reduction potential, facilitating a transition towards sustainable energy usage in rural areas, and nurturing green agricultural development. In this study, we employ the entropy method, a spatial Durbin model, and a panel threshold model to assess the impact of the rural digital economy on agricultural carbon emissions across each province in China from 2010 to 2022. Additionally, we delve into the mechanism through which the rural digital economy facilitates agricultural carbon reduction, particularly in terms of "agricultural socialized services". Our findings reveal several key insights. Firstly, the rural digital economy contributes significantly to reducing agricultural carbon emission intensity. Secondly, there is a non-linear relationship between the rural digital economy and agricultural carbon emissions. With the development of rural digital economy showing a marginal decreasing trend, there is an obvious threshold effect. Thirdly, enhancing agricultural socialized services through the rural digital economy can curb agricultural carbon emissions. Lastly, the carbon reduction effect of the rural digital economy is more significant in more economically developed areas, areas with moderate levels of economic development, and areas with low technological investment; implementation of a "zero growth" policy for fertilizers strengthens this carbon reduction effect. This study sheds light on the mechanisms and effects of agricultural carbon emissions, offering quantitative evidence and theoretical support for the transition towards low-carbon and sustainable agricultural development.

Agricultural carbon reduction in China: The synergy effect of trade and technology on sustainable development

The control of carbon emissions from agriculture is imperative in addressing the challenges posed by the greenhouse effect. China must develop a specific pathway for reducing its agricultural carbon emissions, accounting for its unique circumstances and considering the impacts of trade liberalization. (1) The study revealing that agricultural trade liberalization (ATL) has a marked effect on lowering China's agricultural carbon emission intensity (ACEI), with robustness and endogeneity tests supporting these findings. (2) In the pursuit of emissions reduction, the crucial role of technology spillovers (TS) and the optimization of industrial structure (OIS) are essential. (3) The reduction in ACEI is particularly notable in coastal regions, areas with low environmental regulations and during periods characterized by more stable agricultural tariffs. This study shows a synergistic association between ATL and ACEI, indicates the potential for a mutually beneficial situation with advantages in both economic and environmental aspects.

The trajectory of carbon emissions and terrestrial carbon sinks at the provincial level in China

Global greenhouse gas emission, major factor driving climate change, has been increasing since nineteenth century. STIRPAT and CEVSA models were performed to estimate the carbon emission peaks and terrestrial ecosystem carbon sinks at the provincial level in China, respectively. Utilizing the growth characteristics and the peak time criteria for the period 1997-2019, the patterns of energy consumption and CO2 emissions from 30 Chinese provinces are categorized into four groups: (i) one-stage increase (5 provinces), (ii) two-stage increase (10 provinces), (iii) maximum around 2013 (13 provinces), and (iv) maximum around 2017 (2 provinces). According to the STIRPAT model, the anticipated time of peak CO2 emissions for Beijing from the third group is ~ 2025 in both business-as-usual and high-speed scenarios. For Xinjiang Uygur autonomous region from the first group and Zhejiang province from the second group, the expected peak time is 2025 to 2030. Shaanxi province from the fourth group is likely to reach carbon emission peak before 2030. The inventory-based estimate of China's terrestrial carbon sink is ~ 266.2 Tg C/a during the period 1982-2015, offsetting 18.3% of contemporary CO2 emissions. The province-level CO2 emissions, peak emissions and terrestrial carbon sinks estimates presented here are significant for those concerned with carbon neutrality.

Study of the Mechanism of Hydrolysis of Hemicellulose from Lignocellulose during Alkali Thermal Pretreatment by Density Functional Theory and Experiment

The covalent bond fracture of hemicellulose leads to hemicellulose hydrolysis during lignocellulosic alkali thermal pretreatment, which has not previously been reported. Density functional theory was used to study the mechanism of hydrolysis of the hemicellulose model compounds under alkali conditions. There are four reaction paths for xylose formation, among which the reaction path with the lowest energy barrier is that in which the nucleophile captures H30 to generate water. The deprotonated hydroxyl group attacks the carbon on the glycoside bond, resulting in the cleavage of the glycoside bond and the formation of a new carbon-oxygen covalent bond, with an energy barrier of 154.2 kJ/mol. The nucleophile further attacks the glycosidic bond to form a new xylose residue with an energy barrier of 111.9 kJ/mol. When the glycosidic bond breaks, the orbital interaction with the largest proportion causes the transfer of ∼0.511 electron from the glycosidic bond oxygen to the deprotonated hydroxy oxygen. In situ Fourier transform infrared spectroscopy is used for the identification of functional groups during the alkali thermal pretreatment. As the temperature increases, the feasibility of the reaction increases. This study lays a theoretical foundation for the development of the alkali thermal pretreatment of lignocellulose.

How to achieve carbon neutrality and low-carbon economic development-evidence from provincial data in China

"Carbon Peaking and Carbon Neutrality" is a major strategy for China to cope with climate change at present. We define the carbon neutrality capability (CNC) to reflect the current situation of regional carbon neutrality, and propose a new coupling model to explore the coupling relationship between regional economic development and carbon neutrality capability (CNC). Finally, the influence mechanism of the energy consumption structure on CNC was further discussed by using STRIPAT model. The results show that: during we study period, the national average carbon sink was about 77.89 Mt, and the carbon sinks in Inner Mongolia, Heilongjiang, Sichuan and Yunnan were as high as 164 Mt, mainly concentrated in the western region. The national average carbon source is 222.12 Mt, which is about three times that of carbon sink. The carbon source in Shandong, Hebei and Jiangsu are as high as 400 Mt or more, mainly concentrated in the eastern region. In addition, the growth rate of carbon source is much faster than that of carbon sink, especially the carbon emission caused by energy consumption, which leads to a general decline in CNC, and the development of CNC in various provinces is not optimistic. CNC and economic development level of most provinces are in a state of recession decoupling, and the coupling state of the provinces studied in certain years is significantly different. The spatial distribution of CNC and GDP has shown a northeast-southwest pattern. In addition, the influence of coal consumption structure on CNC is significantly negative, so we should optimize the energy consumption structure and increase the proportion of clean energy consumption. This study can make clear the current carbon neutrality capability of provinces in China, facilitate the formulation and adjustment of emission reduction strategies of provinces and cities, and help China to achieve carbon neutrality as soon as possible.

Can financial technology development reduce household energy consumption? Evidence from China

This paper examines whether financial technology (FinTech) development affect household energy consumption. The proposed point that FinTech can reduce household energy consumption is theoretically discussed and empirically tested using data from the 2017 Digital Financial Inclusion Index, the 2018 China Family Panel Studies (CFPS), the 2018 China Environmental Statistical Yearbook and the 2018 China Science and Technology Statistical Yearbook. The results show that FinTech contributes to reducing household energy consumption. Several retests, including the instrumental variable, replacement sample and propensity score matching methods, prove its robustness. Mechanism tests show that investment in environmental governance and technological innovation promotion are the two main transmission channels. We also find that the reducing effect is more significant in the following groups: the low-middle income level classes, the eastern regional residents, those with bachelor's degrees and above, the those aged over 60 and rural residents. The outcomes of this paper call for government departments to positively guide FinTech development to reduce household energy consumption. From another perspective, the conclusions drawn from our analysis make a great reference value for countries and provide new ideas for Chinese carbon peaking and carbon neutralisation goals.

Nassani A, H. Binsaeed R, Zaman K. Green investing in China's air cargo industry: Opportunities and challenges for sustainable transportation

Aviation cargo remains vital in the economic activities to transported goods from one place to another. The developed and developing countries mainly consider the transaction routes for air transportation for safe and quickest mode. Chinese economy is attracting the global World through its exports. The country's air cargo system is mainly reliant on gasoline and petroleum-based fuels, which harms the country's green transportation agenda. The high use of fuel combustions in the aviation sector needed greenfield investment that helps to use green energy as an alternative sustainable fuel. Further, sustainable aviation insurance and financial coverage are needed to mitigate the adverse negative externalities from air cargo operations. Based on the crucial facts, the study used air cargo operations, transportation fuel combustions, private investment in the transportation and insurance coverage in the pollution damage function for the China economy using data from 1975 to 2020. The research employed a non-linear ARDL Bounds testing strategy to break down the sequence of variables into dynamic positive and negative multipliers. Positive shocks in air freight, insurance services, and greenfield investment have been shown to reduce carbon emissions immediately and over the long term. In the short term, carbon damages are exacerbated by the negative shocks resulting from the use of transportation fuel and the availability of insurance. Moreover, both the positive and negative shocks associated with transportation fuel combustions and air transportation freights contribute to a rise in carbon damage. The variance decomposition analysis validated the asymmetric correlations between the aforementioned variables in the intertemporal environment. Based on the findings, negative shocks from total fuel combustions are expected to impose the greatest carbon damages over the next decade, followed by insurance services and air freight operations. The study concludes that air cargo operations need to be sustainable transacting routes fueled by biofuel energy sources, greenfield investment, and sustainable aviation insurance coverage to achieve the 'green is clean' transportation agenda.

A biotechnological roadmap for decarbonization systems combined into bioenergy production: Prelude of environmental life-cycle assessment

Decarbonization has become a critical issue in recent years due to rising energy demands and diminishing oil resources. Decarbonization systems based on biotechnology have proven to be a cost-effective and environmentally benign technique of lowering carbon emissions. Bioenergy generation is an environmentally friendly technique for mitigating climate change in the energy industry, and it is predicted to play an important role in lowering global carbon emissions. This review essentially provides a new perspective on the unique biotechnological approaches and strategies based decarbonization pathways. Furthermore, the application of genetically engineered microbes in CO₂ biomitigation and energy generation is particularly emphasized. The production of biohydrogen and biomethane via anaerobic digestion techniques has been highlighted in the perspective. In this review, role of microorganisms in bioconversion of CO₂ into different types of bioproducts such as biochemical, biopolymers, biosolvents and biosurfactant was summarized. The current analysis, which includes an in-depth discussion of a biotechnology-based roadmap for the bioeconomy, provides a clear picture of sustainability, forthcoming challenges, and perspectives.

Carbon emission efficiency evaluation of wastewater treatment plants: evidence from China

A scientific evaluation of the carbon emission efficiency is crucial for ensuring the sustainable development of wastewater treatment plants (WWTPs). In this paper, we applied a non-radial data envelopment analysis (DEA) model to calculate the carbon emission efficiency of 225 WWTPs located in China. The results showed that the average carbon emission efficiency of China's WWTPs was 0.59, indicating that the efficiencies of most samples still require improvement. The carbon emission efficiency of WWTPs from 2015 to 2017 decreased because of the decrease in technology efficiency. Among the influencing factors, different treating scales had positive impact on carbon emission efficiency improvement. WWTPs with anaerobic oxic process and the first-class A standard were likely to have higher carbon emission efficiency in the 225 WWTPs. By incorporating direct and indirect carbon emissions into WWTP efficiency evaluation, this study helped decision-makers and related water authorities to better understand the contribution of WWTPs to the aquatic and atmospheric environments.

Probing environmental sustainability pathways in G7 economies: the role of energy transition, technological innovation, and demographic mobility

Global warming remains the most devastating environmental issue embattling the global economies, with significant contributions emanating from CO₂ emissions. The continued rise in the level of greenhouse gas (GHG) emissions serves as a compelling force which constitutes the core of discussion at the recent COP26 prompting nations to commit to the net-zero emission target. The current research presents the first empirical investigation on the roles of technological advancement, demographic mobility, and energy transition in G7 pathways to environmental sustainability captured by CO₂ emissions per capita (PCCO2) from 2000 to 2019. The study considers the additional impacts of structural change and resource abundance. The empirical backings are subjected to pre-estimation tests consisting of cross-sectional dependence, second-generation stationarity, and panel cointegration tests. The model estimation is based on cross-sectional augmented autoregressive distributed lag, dynamic common correlated effects mean group, and augmented mean group for the main analysis and robustness checks. The findings reveal the existence of EKC based on the direct and indirect effects of the components of economic growth. The indicators of demographic mobility differ in the direction of influence on PCCO2. For instance, while rural population growth negatively influences PCCO2 in the short-run alone, urban population growth increases PCCO2 in the short-run and long-run periods. Nonrenewable energy, information computer technology (ICT) imports, and mobile cellular subscriptions serve as positive predictors of PCCO2, while ICT exports and renewable energy moderate the surge in PCCO2. Policy implications that enhance environmental sustainability are suggested following the empirical verifications.

Modelling and forecasting non-renewable energy consumption and carbon dioxide emissions in China using a PSO algorithm-based fractional non-linear grey Bernoulli model

In China, the consumption of non-renewable energy increases not only in general economic growth but also in large amounts of carbon dioxide (CO₂) emissions which cause disasters and catastrophic damages to the environment. To alleviate environmental pressure, it is neccessary to forecast and model the relationship between energy consumption and CO₂ emissions. In this study, a fractional non-linear grey Bernoulli (FANGBM(1,1)) model based on particle swarm optimization is proposed to forecast and model non-renewable energy consumption and CO₂ emissions in China. Firstly, based on the FANGBM(1,1) model, non-renewable energy consumption in China is predicted. The comparison results of several competitive models show that the FANGBM(1,1) model has the best predictive performance. Then, the relationship between non-renewable energy consumption and CO₂ emissions is modeled. On this basis, China's future CO₂ emissions are effectively predicted based on the established model. The forecast results show that the growth trend of China's CO₂ emissions will continue to grow to 2035, while the prediction results in different scenarios also show that that the different growth rates of renewable energy share lead to different times to peak CO₂ emissions. In the end, relevant suggestions are proposed to support China's dual carbon goals.

What role does digital finance play in low-carbon development? Evidence from five major urban agglomerations in China

In the epoch of the digital economy, digital finance (DF) has become an indispensable engine driving the high-quality development of the Chinese economy. The issues of how DF can be used to alleviate environmental pressure and how a long-term governance mechanism for carbon emissions reduction be formed have become particularly important. Based on the panel data of five national urban agglomerations in China from 2011 to 2020, this study utilizes the panel double fixed-effects model and chain mediation model to verify the impact mechanism of DF on carbon emissions efficiency (CEE). Some valuable findings are drawn below. First, the overall CEE of the urban agglomerations has potential for improvement, and the CEE and DF development level of each urban agglomeration have regional heterogeneity. Second, a U-shaped correlation is observed between DF and CEE. Technological innovation and industrial structure upgrading have a chain mediating effect in DF affecting CEE. In addition, the breadth and depth of DF have a notable negative impact on CEE, and the digitalization degree of DF shows a significant positive correlation with CEE. Third, the influencing factors of CEE have regional heterogeneity. Finally, this study provides relevant suggestions based on the empirical conclusions and analysis.

In situ synthesis of a Bi2O3 quantum dot decorated BiOCl heterojunction with superior photocatalytic capability for organic dye and antibiotic removal

As a decoration method, coupling a photocatalyst with semiconductor quantum dots has been proven to be an efficient strategy for enhanced photocatalytic performance. Herein, a novel BiOCl nanosheet decorated with Bi₂O₃ quantum dots (QDs) was first synthesized by a facile one-step in situ chemical deposition method at room temperature. The as-prepared materials were characterized by multiple means of analysis. The Bi₂O₃QDs with an average diameter of about 8.0 nm were uniformly embedded on the surface of BiOCl nanosheets. The obtained Bi₂O₃QDs/BiOCl exhibited significantly enhanced photocatalytic performance on the degradation of the rhodamine B and ciprofloxacin, which could be attributed to the band alignment, the photosensitization effect and the strong coupling between Bi₂O₃ and BiOCl. In addition, the dye photosensitization effect was demonstrated by the monochromatic photodegradation experiments. The radical trapping experiments and the ESR testing demonstrated the type II charge transfer route of the heterojunction. Finally, a reasonable photocatalytic mechanism based on the relative band positions was discussed to illustrate the photoreaction process. These findings provide a good choice for the design and potential application of BiOCl-based photocatalysts in water remediation.

Urban growth boundary: a revolution for low-carbon development

A major environmental concern today is the carbon emissions caused by rapid urbanization. As the largest developing country and carbon emitter, China has controlled the urban growth boundary (UGB) as a quasi-experimental policy to achieve carbon neutrality. Therefore, this paper employs the difference in differences (DID) method, for panel data from 2000 to 2019 in China to shed light on the effects on carbon emissions. Results show that the UGB can reduce carbon emissions considerably. After the implementation of the policy, the carbon emissions of the pilot cities decreased by 23.91%. Additionally, a series of robustness tests such as PSM-DID and Placebo tests support the conclusions. Moreover, the greater influence is reflected in the scope of the whole city and the intensity of the permanent plan. The UGB is more susceptible to cities in the central and western areas and cities with weak environmental regulations. Through the mechanism tests, the emission reduction effect of the UGB will be greater in cities with larger vegetation coverage and advanced industry structure. Furthermore, our analysis suggests the UGB needs to be adequately promoted as a policy to achieve carbon neutrality in cities. To make the policy more effective, vegetation cover and industrial structure ought to be taken into consideration.

Provincial and regional analysis of carbon neutrality policy and the environmental Kuznets curve: examining their effect on CO2 emissions in China

China is making a challenging effort to achieve its ambitious goal of becoming carbon-neutral by 2060. Therefore, the Chinese government should develop effective policy tools to improve its carbon neutrality plan. Due to this importance, an empirical study is required to examine the comprehensive effect of the carbon neutrality policy on CO₂ emissions in China. Also, the role of economic development on the environment, the environmental Kuznets curve (EKC) hypothesis in the carbon neutrality-CO₂ emissions nexus, has yet to be examined. Considering this gap, the present study investigates the impacts of carbon neutrality policy and the economy on CO₂ emissions at China's provincial and regional levels from 2006 to 2017. We use a comprehensive approach to measure the carbon neutrality policy through the source control and sink increase perspectives. This study performs the panel-corrected standard errors (PCSE) and the feasible generalised least squares (FGLS) regression techniques to control the heteroscedasticity and cross-sectional correlation issues. The results show that an improvement in energy efficiency and renewable energy power generation decreases the per capita CO₂ emissions at the provincial level from the source control perspective. From the sink increase perspective, only green space development affects CO₂ emissions reduction; the development of carbon capture, utilisation, and storage (CCUS) does not. Also, this study shows that the EKC hypothesis holds true in China nationally and in the central region. Due to differing regional development patterns, the impact of carbon neutrality policy on CO₂ emissions varies across regions. This study suggests specific policy implications such as increasing R&D investment per unit of GDP to support CCUS technologies at provincial and regional levels.

Production-based disaggregated analysis of energy consumption and CO2 emission nexus: evidence from the USA by novel dynamic ARDL simulation approach

The study investigates the effects of energy consumption on carbon dioxide (CO₂) emissions by focusing on production sources. In this context, the study focuses on the USA as the leading economy, includes monthly data between January 1973 and April 2022, and performs dynamic autoregressive distributed lag (ARDL) (DYNARDL) simulations. Besides, kernel-based regularized least squares (KRLS) and cointegrating regression approaches are applied for robustness checks. The results reveal that (i) there is cointegration between sub-components of the energy production and CO₂ emissions in the long run; (ii) fossil energy and nuclear energy production have an increasing effect on the CO₂ emissions in the both short and long run; (iii) renewable energy production has an increasing effect on the CO₂ emissions in the short run, but has a decreasing effect in the long run; (iv) negative (positive) shocks in the fossil energy production have a decreasing (increasing) effect on the CO₂ emissions, whereas negative (positive) shocks in the renewable energy production have an increasing (decreasing) effect on the CO₂ emissions in case of counterfactual shocks; (v) there is a casual-effect nexus between energy production sources and CO₂ emissions; and (vi) KRLS and cointegrating regression results validate the robustness of the DYNARDL simulation outcomes. Moreover, policy implications are discussed.

Using a combination of nighttime light and MODIS data to estimate spatiotemporal patterns of CO2 emissions at multiple scales

Accurate mapping spatiotemporal patterns of CO₂ emissions and understanding its driving factors are very important, it is useful for the scientific and rational formulation of carbon emission reduction policies. Nevertheless, due to data availability issues, most studies have been limited to the global and national scales, and the models used were relatively simple. In this paper, we used the 500 m Visible Infrared Imaging Radiometer Suite Day/Night Band (VIIRS-DNB) data and the 250 m Moderate Resolution Imaging Spectroradiometer normalized difference vegetation index (MODIS NDVI) and proposed an improved CO₂ emissions index (ICEI) to calculate CO₂ emissions. Compared with the total nighttime light (NTL), the average regression coefficient (R²) can be improve from 0.73 to 0.78. We also used the coefficient of variation, spatial autocorrelation, and geographically weighted regression models to analyze the temporal and spatial variation mode of CO₂ emissions, as well as the associated correlation and heterogeneity, at three different administrative unit scales during 2012-2019. Our experimental results demonstrate that: (1) the improved index (ICEI) is better than the traditional variable (NTL) in estimating CO₂ emissions; (2) the highest CO₂ emissions are primarily gathered in the developed coastal areas in eastern China; and (3) at the provincial level, the added value of the secondary industry is the most significant factor, whereas the added value of the tertiary industry is negatively correlated with CO₂ emissions.

Spatial effect analysis of heterogeneous green technology innovations on pollution emission reduction: evidence from China's power industry

Based on the provincial panel dataset of the power industry in China from 1997 to 2020, this study employed the dynamic spatial Durbin model (SDM) to investigate the spatial effects of heterogeneous green technology innovations (GTIs) of the power industry chain-clean energy GTIs (GTI1), fossil-fueled GTIs (GTI2), energy-saving GTIs (GTI3), and power transmission technology innovations (GTI4)-on three pollution emission reduction: SO_2, solid waste (SW), and waste water (WW). The empirical results revealed that three pollution emissions showed "path dependent" and "snowball effects." GTI1, GTI2, and GTI3 reduced local SO₂ and SW emissions, while GTI2 and GTI4 had no obvious reduction effects on WW emissions. Different GTIs had the same spatial "symbiotic effects" on SO₂ emission reduction in the short term, showing positive spatial spillover reduction effects. Finally, it is of great significance to make full use of the positive spatial spillover effects of GTIs to promote the regional collaborative linkage of pollutant governance in the power industry.

Carbon Neutrality in the Middle East and North Africa: The Roles of Renewable Energy, Economic Growth, and Government Effectiveness

Carbon neutrality is a 21st-century priority area, with the Middle East and North Africa (MENA) countries making significant investments in renewable energy and climate mitigation initiatives to attain it. However, carbon neutrality research in the MENA region is under-developed, particularly when considering the roles of renewable energy, economic growth, and effectiveness of government. To address this gap, this research investigates the roles of renewable energy, economic growth, and government effectiveness toward the MENA region's carbon neutrality goal. We implemented heterogeneous and second-generation panel data techniques that are resilient to cross-sectional dependency and slope heterogeneity to panel data spanning 16 MENA countries from 1996 to 2018. We discovered that MENA data are cross-sectionally dependent, heterogeneous, and cointegrated. We found that government effectiveness and renewable energy bring carbon neutrality closer, but economic growth initially delays it. We detected Environmental Kuznets Curve (EKC) in the MENA region, specifically in the High-Income Countries. Although there were signs of EKC in the Middle-Income Countries, this was not significantly validated. Finally, we found a one-way causal link from government effectiveness and renewable energy to carbon neutrality but a feedback mechanism between economic growth and carbon neutrality in the MENA region. As a result of these findings, it is recommended that the MENA region's policymakers prioritize renewable energies and improve the effectiveness of government to drive economic growth toward the carbon neutrality goal.

Assessment of food-energy-environmental pollution nexus in Iran: the nonlinear approach

Iran's agricultural production has expanded significantly in recent years. Environmental pollution caused by the use of energy and chemical fertilizers, depletion of groundwater resources, and soil erosion, on the other hand, demonstrates a lack of attention to the environmental dimension of production in this country. In addition to these issues, climate change has exacerbated the agriculture sector's difficulties. This study intends to investigate the asymmetric relationship between energy consumption, chemical fertilizer consumption, CO₂ emissions, temperature changes, and production from 1961 to 2019 using the NARDL approach and Granger causality test in the frequency domain (Breitung and Candelon.). Short-term and long-term estimates revealed that the positive and negative shock effects of energy consumption on production are both positive. As a result, it was observed that the negative shock of increased energy consumption had a greater influence on agricultural output than the positive shock. In the long run, the positive shock of fertilizer use has a positive effect on and improves production. But the effect of a negative shock is insignificant. Furthermore, the negative shock of CO₂ emission has a positive effect on production. Finally, positive and negative shocks in temperature changes were discovered to have an increasing and reducing influence on production. The results of the Granger causality test in the frequency domain test showed that there is a bidirectional causality relationship between energy consumption and agro-production in the long term. There is also unidirectional causality from CO₂ emissions and fertilizer consumption to production and from production to climate change. According to the findings, reforming energy prices, investing in mechanized agriculture, shifting away from fossil fuel consumption towards renewable energy, and tending to green growth are all necessary to achieve multiple goals such as optimizing energy consumption, reducing environmental pollution, and improving efficiency.

Quantified impacts of international trade on the United States' carbon intensity

After the USA reached its carbon emission peak in 2007, the share of carbon emissions from its energy activities showed a downward trend. As a country that accounts for even close to 80% of the tertiary industry, the final demands from other industries are usually met by other countries in the form of international trade. While trade is realizing economic transfer, it also realizes the transfer of carbon emissions to a certain extent, helping the country achieve the peaks. From the perspective of combining carbon emission transfer and economic transfer, are there transfers and impacts? In this study, the quantified impact of international trade on the USA's carbon intensity has been investigated by a novel framework, based on a porposed scenario analysis using MRIO. As it gets lower aggregate carbon intensity value under trade scenario, it concludes that international trade is more conducive to the needs of this country for carbon emission reduction and economic development in general. From the different trade patterns, all of them get lower carbon intensity values under trade than no-trade scenario. From trade partners' perspectives, the positive and negative of the intensity gap cannot be kept uniform for all traders. Sectoral driving factors are decomposed by LMDI method, with the sectoral effect of aggrerate value-added structure and sectoral aggregate embodied carbon intensity. Among obvious carbon-intensive sectors, transport sectors always show a negative effect for the gap, and heavy manufacturing and electricity sectors usually give positive effects. As a major trading country in the world, trade and exchanges with other countries are more conducive to this country with a lower carbon intensity, and it also requires the country to shoulder coresponding responsiblities as a great power while enjoying the benefies. It is conducive to the further strengthening of unity of the international community, to jointly address the challenges of climate change and achieve the subsequent carbon neutral targets.

Divergences of soil carbon turnover and regulation in alpine steppes and meadows on the Tibetan Plateau

The grasslands of the Tibetan Plateau store approximately 2.5% of global soil organic carbon (SOC) and considerable soil inorganic carbon (SIC) and have the potential to become a vast carbon source or sink as climate change progresses. However, the soil carbon (C) sequestration mechanisms that occur across large-scale natural gradients remain unclear. Here, humic substances (HS) were utilized to trace soil C turnover at 0-20 cm, and we compared divergences among three main grassland types (alpine meadow, alpine steppe, and artificial plantation) using structural equation modeling (SEM). The results showed that the alpine meadows sequestered the most soil C (63.99 ± 4.41 g kg^-1 SOC and 4.11 ± 0.63 g kg^-1 SIC), sequestering 2-3 times more than the alpine steppe ecosystems (19.78 ± 1.98 g kg^-1 SOC and 9.21 ± 0.66 g kg^-1 SIC). The alpine steppe and artificial plantation regions have strong C sink potential due to their low C/N ratios (P < 0.05). Importantly, SIC played an important role in the alpine steppes, accounting for nearly 26-37% of soil C. The ratios of recalcitrant HS to SOC were estimated as 46.50%, 65.09%, and 78.17% in the alpine meadow, alpine steppe, and artificial plantation ecosystems, respectively, indicating that SOC in the alpine meadow was the most sensitive to climate change. Fulvic acid (FA) accounted for 50.86% of SOC in the 0-20-cm interval, contributing most to the formation of SOC in all vegetation types. In addition, in contrast to climatic controls on soil C turnover in the alpine meadow, climate conditions rarely controlled C turnover in the alpine steppe. Moreover, sand and silt were the main soil minerals involved in C turnover in alpine meadow and alpine steppe ecosystems, respectively. Our study improves understanding of the mechanism by which soil C sinks form on the Tibetan Plateau under warming and wetting conditions.

Does it pay to develop a ground source heat pump system? Evidence from China

The application potential and environmental benefits of ground source heat pump (GSHP) systems have become the focal points of decarbonization in the building sector. Synchronized and scientific analysis of GSHP systems' environmental and economic performance, however, remains lacking. This study analyzes the application prospects of GSHP systems via a life cycle assessment-based life cycle costing method, and considers China's actual status quo. The internal and external annual costs of a GSHP system per square meter are $ 4.05 and $ 1.37, respectively. Electricity generation and steel production are key processes to improve the environmental performance of a GSHP system further. Compared with coal-based heating, a GSHP system can mitigate 65%-95% of the environmental impact and 85% of external costs, except for the metal depletion impact which is 1.5 times higher than that of coal-based heating. In Shandong Province, promoting GSHP systems can substitute up to 69.4% of the district heating area, which implies reductions in fossil depletion, greenhouse gas emissions, human health impact, ecosystem quality impact, and external costs by up to 2.37 × 10¹⁰ kg oil eq, 1.08 × 10¹¹ kg CO₂ eq, 3.87 × 10⁵ DALY, 1.18 × 10³ Species. year, and $ 2.51 × 10¹⁰, respectively. In consideration of environmental and economic aspects, a GSHP system can exhibit benefits compared with coal-based heating after 2.34 years of operation. To improve the economic and environmental performance of GSHP systems, a series of recommendations on financial subsidies, renewable energy development, inter-regional power transmission, steel scrap utilization, and hydrogen reduction steelmaking is provided.

Exploring the Road toward Environmental Sustainability: Natural Resources, Renewable Energy Consumption, Economic Growth, and Greenhouse Gas Emissions

Despite the fact that China’s economy has grown swiftly since the reform and opening up, the problem of environmental degradation in China has become increasingly significant. Therefore, this paper uses China as an example to examine the dynamic relationship between the highlighted variables (renewable energy consumption, economic growth, oil rent, and natural resources) and greenhouse gas emissions (a proxy for environmental sustainability). Using annual data over the period 1971–2018 and employing the auto-regressive distributed lag bounds approach to perform an empirical analysis, the results suggest that there is a long-run equilibrium relationship between the highlighted variables and greenhouse gas emissions. Specifically, renewable energy consumption and oil rent contribute to environmental sustainability because of their negative effects on greenhouse gas emissions. On the contrary, economic growth and natural resources hinder environmental sustainability due to their positive effects on greenhouse gas emissions. In addition, using the fully modified ordinary least squares approach and dynamic ordinary least squares approach to conduct a robustness test, the results also support the previous findings. To conclude, the findings of this paper may provide some solutions for China’s environmental sustainability.

Spatiotemporal Heterogeneity of Agricultural Land Eco-Efficiency: A Case Study of 128 Cities in the Yangtze River Basin

Analysis of spatiotemporal heterogeneity and evolutionary characteristics of agricultural land eco-efficiency is of great significance for achieving a rational use of natural resources and coordinated development of the agricultural economy as well as the ecological environment. In this study, we construct the “ecological space–agricultural production–carbon emission” framework, incorporate carbon emission intensity as an undesired output into the evaluation index system of agricultural land eco-efficiency, calculate the eco-efficiency of agricultural land in 128 cities in the Yangtze River basin from 2009 to 2018 by adopting the super-efficiency SBM model, and discuss the spatial and temporal changes using methodology such as hotspot analysis and kernel density estimation by ArcGIS. The results show the following. The overall trend of agricultural land eco-efficiency in the Yangtze River basin is increasing year by year and still has potential for improvement. However, there are significant discrepancies among cities, with the eco-efficiency of the downstream being much higher than that of the midstream and upstream regions, and demonstrating the pattern of “big dispersion–small agglomeration”. Some cities are still facing pressure to improve the eco-efficiency of agricultural land. Correspondingly, this paper puts forward optimization recommendations: Firstly, the downstream cities should give full play to their geographical advantages, actively introduce advanced production technologies, and reasonably allocate agricultural resources. Secondly, the upstream and midstream regions should formulate reasonable regional strategies in accordance with their natural resource endowments to improve the ecological benefits of agricultural land and narrow the regional disparities. This paper gives targeted policy recommendations at the levels of paying attention to education of farmers, providing incentives for ecological planting, strengthening agricultural infrastructure construction, reasonably controlling the use of agricultural materials, and increasing investment in agricultural pollutant emission management.

Foreign direct investment, financial development, energy consumption, and air quality: A way for carbon neutrality in China

Air quality is a social, economical, and health issue for fast-developing countries such as China. Due to the overuse of nonrenewable energy, industrialization, and the population put pressure on air quality, which seriously threatens public health and economic growth. This study focuses on air quality and also aims to investigate the short-and long-run correlation between foreign direct investment, energy consumption, domestic credit, and financial development. The Autoregressive distributed lag model and the Granger non-causality test were carried out over the period from 1985 to 2018. The main findings of this study show a positive and significant long-run impact of energy consumption on air quality. In addition, domestic credit and financial development similarly show a significant positive short-run association with air quality. Moreover, the unidirectional causality correlation running from foreign direct investment and domestic credit to air quality was concluded by the Granger non-causality test. Considering the empirical analysis, this study suggests that domestic financial institutions should offer credit to industries at a low-interest rate in order to help them to switch from non-renewable to renewable energy consumption towards the promotion of sustainable and healthy air quality.

Do Green Finance and Environmental Regulation Play a Crucial Role in the Reduction of CO2 Emissions? An Empirical Analysis of 126 Chinese Cities

Green finance and environmental regulation can reduce CO2 emissions and promote the sustainability of economic development. Based on panel data of 126 resource-based prefecture-level cities in China from 2005 to 2017, the current study used a dynamic panel data model to empirically determine the CO2 emission reduction effects of different green finance instruments under different environmental regulatory intensities. The results showed that green finance tools had significant negative effects on the intensity of CO2 emissions, and green finance can adapt to environmental regulations of different intensities, which cooperated to promote carbon emission reduction. Moreover, in comparison, the debt-based green finance instrument had a stronger effect than the equity-based green finance instrument, and they did not show a coupling relationship. An administrative adjustment in green finance and environmental regulation is required to reduce environmental emissions and to improve sustainable development.

The effect of energy resources on economic growth and carbon emissions: A way forward to carbon neutrality in an emerging economy

Globally, all countries have producing different levels of carbon emissions and also facing both the problems of climate change and global warming due high carbon emissions in the atmosphere. Therefore, it is important to cutting carbon emissions in the atmosphere. This is only possible by switching to cleaner fuels, use of innovation technologies and development of carbon capture storages. These can substantially help the nations to reaching carbon neutrality. Given this background, this paper examines the effect of disaggregated energy consumption, technological innovations, capital on economic output and CO₂ emissions in India for the period of 1990-2018. Based on empirical analysis, our long-run elasticities indicate that disaggregated energy consumption and technological innovations have a positive impact on economic growth, while renewable energy consumption and technological innovations have a positive impact on CO₂ emissions. It implies that more use of energy consumption producing significant amount of CO₂ emissions and by using renewable energy consumption and technological innovations (i.e. carbon capture storages) can significantly lowering CO₂ emissions, which is clearly indicating that India has moving towards carbon neutrality. The causality analysis further indicates a unidirectional causal relationship running from disaggregated energy usage to economic growth and carbon emissions. These empirical findings suggest that the increased consumption of renewable power does not lead to rise carbon emissions, which, in turn, ensures sustainable economic growth.

Evaluating the Dynamic Changes of Urban Land and Its Fractional Covers in Africa from 2000–2020 Using Time Series of Remotely Sensed Images on the Big Data Platform

Dramatic urban land expansion and its internal sub-fraction change during 2000–2020 have taken place in Africa; however, the investigation of their spatial heterogeneity and dynamic change monitoring at the continental scale are rarely reported. Taking the whole of Africa as a study area, the synergic approach of normalized settlement density index and random forest was applied to assess urban land and its sub-land fractions (i.e., impervious surface area and vegetation space) in Africa, through time series of remotely sensed images on a cloud computing platform. The generated 30-m resolution urban land/sub-land products displayed good accuracy, with comprehensive accuracy of over 90%. During 2000–2020, the evaluated urban land throughout Africa increased from 1.93 × 104 km2 to 4.18 × 104 km2, with a total expansion rate of 116.49%, and the expanded urban area of the top six countries accounted for more than half of the total increments, meaning that the urban expansion was concentrated in several major countries. A turning green Africa was observed, with a continuously increasing ratio of vegetation space to built-up area and a faster increment of vegetation space than impervious surface area (i.e., 134.43% vs., 108.88%) within urban regions. A better living environment was also found in different urbanized regions, as the newly expanded urban area was characterized by lower impervious surface area fraction and higher vegetation fraction compared with the original urban area. Similarly, the humid/semi-humid regions also displayed a better living environment than arid/semi-arid regions. The relationship between socioeconomic development factors (i.e., gross domestic product and urban population) and impervious surface area was investigated and both passed the significance test (p < 0.05), with a higher fit value in the former than the latter. Overall, urban land and its fractional land cover change in Africa during 2000–2020 promoted the well-being of human settlements, indicating the positive effect on environments.