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Introduction: Strengthening the early warning of greenhouse gas emissions from agriculture is an important way to achieve Goal 13 of the Sustainable Development Goals. Agricultural carbon emissions are an important part of greenhouse gases, and accelerating the development of green and low-carbon agriculture is of great significance for China to ac...
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Green economy has emerged as a significant pillar of sustainable development in the current global context, and the unpredictability of economic policy has progressively garnered the interest of businesses and government officials as one of the obstacles they must confront. This paper examines how uncertainty in the green economy impacts the green...
Citations
... It is mainly calculated by using urban and rural power consumption data and based on annual power carbon dioxide emission factors. This index has not been fully reflected in previous studies (Zhang et al., 2019;Guo et al., 2023;Wei et al., 2023). ACE has the characteristics of multiple sources and subjects, and the construction of a specialized carbon emission accounting inventory will make the results closer to the real value of agricultural economic development. ...
Introduction
Agricultural carbon emission reduction is the meaning of realizing the goal of double carbon, and Sichuan province, as one of the main grain producing areas in China, it is urgent to realize agricultural carbon reduction.
Methods
Based on the data of 18 cities in Sichuan province from 2000 to 2022, this paper calculates the total agricultural carbon emission and carbon emission intensity in Sichuan province by using IPCC guidelines, and measures its temporal, spatial evolution trend and regional differences, and further evaluates the driving factors by using fixed effect model.
Results
The results show that: (1) The total quantity of agricultural carbon emissions in Sichuan province has increased, but the carbon intensity has decreased, among which agricultural carbon emissions caused by agricultural land planting and residents’ life are the main carbon sources; (2) The regional differences of agricultural carbon emissions in Sichuan province are narrowing, among which the gap between groups is the root of the regional differences of agricultural carbon emissions, which shows that the agricultural carbon emissions in eastern Sichuan and western Sichuan, eastern Sichuan and southern Sichuan, western Sichuan and southern Sichuan, are quite different; (3) Agricultural carbon emissions in Sichuan province are characterized by agglomeration and spatial spillover, mainly showing a High-High agglomeration mode, but a few cities have changed their agglomeration modes; (4) The agricultural carbon intensity in Sichuan province is influenced by multiple factors. Population density, industrial structure, social wealth, agricultural mechanization and technological progress have negative effects on agricultural carbon intensity, while macro-control has increased agricultural carbon intensity.
Discussion
In this study, a complete accounting system for agricultural carbon emissions was established, and a series of statistical methods were used to analyze and obtain insightful results. It is a useful exploration of low-carbon agricultural models in the context of climate change. The results of this paper have important implications for the green development of agriculture in Sichuan province.
... Since the reform and opening-up, China's economy has developed rapidly, becoming the world's second-largest economy, but it also ranks among the highest in global carbon emissions [1]. China's carbon emissions account for 28% of global emissions [2,3], with 17% of these emissions coming from the agricultural system [4]. Crop production is the foundation of agriculture and a major source of agricultural carbon emissions [5,6]. ...
Reducing carbon emissions in crop production not only aligns with the goal of high-quality agricultural development but also contributes to achieving the “dual carbon goals”. Based on panel data from 31 provinces in China between 2010 and 2019, this paper explores the impact of Agricultural Socialized Services on carbon emissions in China’s crop production. Utilizing the classical IPCC carbon emission calculation model and spatial econometrics models, this study analyzes the temporal and spatial distribution characteristics of crop production carbon emissions and their driving factors, with a particular focus on evaluating the role of Agricultural Socialized Services in reducing carbon emissions in crop production. The empirical results reveal a “reverse U-shaped” curve for carbon emissions in crop production from 2010 to 2019, with a peak in 2015. Agricultural Socialized Services significantly reduced carbon emissions in crop production, especially in terms of emissions reductions from fertilizer and pesticide use, although the impact on other carbon sources such as plastic mulch, diesel, and tillage was relatively limited. Furthermore, Agricultural Socialized Services exhibited significant spatial spillover effects, effectively reducing local carbon emissions and generating positive carbon reduction effects in neighboring regions through cross-regional services. Based on these findings, the paper suggests improving the Agricultural Socialized Services system according to regional conditions to fully leverage its positive role in reducing carbon emissions in crop production. It also advocates accelerating the innovation of low-carbon agricultural technologies, encouraging farmers’ participation, and utilizing the organizational advantages of village collectives to jointly promote the development of Agricultural Socialized Services and achieve carbon reduction goals.
... Moreover, their study found that institutional support in a circular agriculture economy would promote sustainable farming practices. Guo et al. (2023) examined China and found that using the circular economy concept in the agriculture sector would help mitigate carbon dioxide emissions through green and low-carbon agricultural development and suggested some valuable policies mitigating emissions. Xie and Wu (2023) explored and found that economic integration mitigated emissions' efficiency with the help of low-carbon technologies in China from 2005-20. ...
The agriculture sector and other agribusinessescan have a long-lasting effect on the environment. The present studyinvestigates the effect of Agricultural Supply Chain Management (ASCM), fromproducer to consumer, on Environmental Sustainability (ES) in the Alkharj governorateby collecting primary data from 312 respondents in the ASCM in Alkharj and byapplying Structural Equation Modelling (SEM). Moreover, the moderating roles ofeconomic and social sustainability in the nexus between ASCM and the ES arealso tested. The results of the analyses show that ASCM directly improves theES in the agriculture sector. Moreover, ASCM also improves both economic andsocial sustainability. Consequently, economic and social sustainability improvesthe ES. Thus, economic and social sustainability have positively moderated therelationship between ASCM and the ES. The results suggest that the governmentof Alkharj governorate should further improve the economic sustainability ofagribusinesses in Alkharj by providing incentives. Moreover, education andtraining programs should be initiated to improve social sustainability. Thus,both improved social and economic sustainability of agribusinesses could encouragesustainable practices to promote the ES in the whole ASCM in Alkharj.
... Considering differences in agricultural policy support, resource endowment, and agricultural development status among regions, it is easy to cause mismatch of high-quality production factors, affecting the development level of digital inclusive finance and the agricultural ecological environment in various regions. Concurrently, amidst the incessant surge in urbanization, spatial interconnectedness emerges in agricultural carbon emissions and energy utilization among adjacent urban agglomerations, thereby exerting an influence on the agriculture's pursuit of high-quality green development [60]. In view of this, this paper divides the samples according to the basic characteristics of the three major economic zones of east, central, and west formed from China's coast to the interior, and further examines the differences in the impact of digital inclusive finance on the high-quality development of agriculture. ...
With the deep integration of digital technology and inclusive finance, digital inclusive finance has provided a new opportunity for agricultural high-quality development through “overtaking on curves”. This article empirically examines the impact of digital inclusive finance on agricultural high-quality development and the dynamic mechanism of land circulation in its transmission process, utilizing panel data from various provinces in China from 2011 to 2021. The research indicates that digital inclusive finance has a significant improvement effect on agricultural high-quality development, and this conclusion remains valid after a series of endogenous treatments and robustness tests. Meanwhile, intelligent manufacturing has a more pronounced role in promoting agricultural high-quality development in China’s eastern regions, regions with sound infrastructure, and regions with high environmental regulation intensity. Further research reveals that digital inclusive finance can promote agricultural high-quality development through the mechanism of promoting land circulation. The research conclusions provide important empirical evidence and policy implications for achieving coordinated development of agricultural economic growth and environmental protection, thereby realizing the beautiful vision of comprehensive rural revitalization.
... The graph shows a decrease in CO 2 emissions over time, with a sharp decrease starting in 2022. The ELM model can only "learn" from the data it's trained on, and if the training data does not capture all the real-world factors influencing CO 2 emissions, the forecast may not perfectly reflect reality [ 5 ]. ...
Understanding and predicting CO2 emissions from individual power plants is crucial for developing effective mitigation strategies. This study analyzes and forecasts CO2 emissions from an engine-based natural gas-fired power plant in Dhaka Export Processing Zone (DEPZ), Bangladesh. This study also presents a rich dataset and ELM-based prediction model for a natural gas-fired plant in Bangladesh. Utilizing a rich dataset of Electricity generation and Gas Consumption, CO2 emissions in tons are estimated based on the measured energy use, and the ELM models were trained on CO2 emissions data from January 2015 to December 2022 and used to forecast CO2 emissions until December 2026. This study aims to improve the understanding and prediction of CO2 emissions from natural gas-fired power plants. While the specific operational strategy of the studied plant is not available, the provided data can serve as a valuable baseline or benchmark for comparison with similar facilities and the development of future research on optimizing operations and CO2 mitigation strategies. The Extreme Learning Machine (ELM) modeling method was employed due to its efficiency and accuracy in prediction. The ELM models achieved performance metrics Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Scaled Error (MASE), values respectively 3494.46 (<5000), 2013.42 (<2500), and 0.93 close to 1, which falls within the acceptable range. Although natural gas is a cleaner alternative, emission reduction remains essential. This data-driven approach using a Bangladeshi case study provides a replicable framework for optimizing plant operations and measuring and forecasting CO2 emissions from similar facilities, contributing to global climate change.
... At the same time, with the continuous acceleration of urbanization, the carbon emissions between neighboring provinces are spatially dependent. In view of this, referring to the research results of China Physical Geography and Guo et al. (2023), this paper divides the geographical region of China into eastern region, central region, western region and northeast region, so as to further investigate the differences in the impact of green finance on carbon emissions. Among them, each region contains provinces as shown in the table 8. ...
Introduction: Achieving peak carbon dioxide emissions and carbon neutrality is an extensive and profound systematic economic and social change. Through market-oriented financial means, green finance has moved forward the effective governance port, curbed polluting investment and promoted technological progress such as green low-carbon, energy conservation and environmental protection, which has become a powerful starting point to support the practice of low-carbon development.
Methods: Based on the panel data of 30 provinces in China (except Tibet, Hongkong, Macau and Taiwan Province) from 2004 to 2021, this paper calculates the development level of green finance in China provinces by using entropy weight method, and on this basis, uses mathematical statistical model to verify the impact of green finance and its sub-dimensions on carbon emissions and the regulatory effect of heterogeneous environmental regulation tools.
Results: The results show that the development of green finance has a significant inhibitory effect on carbon emissions during the investigation period, and there is a time lag effect. After a series of robustness tests and considering endogenous problems, this conclusion still holds. From the results of heterogeneity analysis, the carbon emission reduction effect of green credit is the most obvious, and the impact of green finance on carbon emission is slightly different in different regions. Besides, Command-controlled environmental regulation tools and public participation environmental regulation tools play a positive regulatory role in the transmission path of green finance’s impact on carbon emissions, but market-driven environmental regulation tools cannot effectively enhance the carbon emission reduction effect of green finance development.
Discussion: The research results of this paper provide a basis for the government to formulate flexible, accurate, reasonable and appropriate green financial policies, help to strengthen the exchange and cooperation between regions in reducing carbon and fixing carbon, and actively and steadily promote China’s goal of “peak carbon dioxide emissions, carbon neutrality”.
... Notably, GA exhibits the capability to identify superior solutions, achieving higher fuel efficiency and lower NOx emissions within a reduced computational time compared to traditional methods. The expansibility and flexibility of GA further enhance its utility, allowing seamless adaptation to more comprehensive parameter ranges or the incorporation of more optimized parameters through updates to the associated ANN model (Guo et al., 2023). GA's superiority becomes apparent in terms of time efficiency, saving almost half of the optimization time and more than 75% in scenarios requiring reeoptimizations, while concurrently discovering more optimal solutions that improve all targeted objectives simultaneously. ...
Promoting low-carbon agriculture is vital for climate action and food security. State farms serve as crucial agricultural production bases in China and are essential in reducing China’s carbon emissions and boosting emission efficiency. This study calculates the carbon emissions of state farms across 29 Chinese provinces using the IPCC method from 2010 to 2022. It also evaluates emission efficiency with the Super-Slack-Based Measure (Super-SBM model) and analyzes influencing factors using the Logarithmic Mean Divisia Index (LMDI) method. The findings suggest that the three largest carbon sources are rice planting, chemical fertilizers, and land tillage. Secondly, agricultural carbon emissions in state farms initially surge, stabilize with fluctuations, and ultimately decline, with higher emissions observed in northern and eastern China. Thirdly, the rise of agricultural carbon emission efficiency is driven primarily by technological progress. Lastly, economic development and industry structure promote agricultural carbon emissions, while production efficiency and labor scale reduce them. To reduce carbon emissions from state farms in China and improve agricultural carbon emission efficiency, the following measures can be taken: (1) Improve agricultural production efficiency and reduce carbon emissions in all links; (2) Optimize the agricultural industrial structure and promote the coordinated development of agriculture; (3) Reduce the agricultural labor scale and promote the specialization, professionalization, and high-quality development of agricultural labor; (4) Accelerate agricultural green technology innovation and guide the green transformation of state farms. This study enriches the theoretical foundation of low-carbon agriculture and develops a framework for assessing carbon emissions in Chinese state farms, offering guidance for future research and policy development in sustainable agriculture.
