Carbon Sequestration and Carbon Management Policy Effects on Production Agriculture in the Texas High Plains

<sec><title>Objective</title> The world is still in a phase of rapid industrialization and urbanization. Excessive carbon emissions has become the primary root cause of various urban or even global environmental problems, further impacting human physiological and psychological health. Cities are the largest sources of carbon emissions and are crucial regions for achieving carbon neutrality goals. Urban blue-green infrastructure (UBGI), comprising natural, semi-natural, or artificial green and blue spaces within cities, is considered as the most important carbon sink space in urban areas and has increasingly attracted widespread attention from researchers. However, there are still many unresolved issues regarding the effectiveness of UBGI in carbon sink enhancement and emission reduction: 1) How is the energy efficiency of carbon sink enhancement and emission reduction measured, and what factors influence it? 2) What are the mechanisms and pathways through which UBGI enhances carbon sink and reduces carbon emission? 3) How can UBGI be regulated to better enhance its effectiveness in carbon sink enhancement and emission reduction? 4) What are the limitations and potential directions for future research? This research aims to address these issues and propose scientifically sound planning strategies for UBGI construction to achieve urban carbon neutrality goals. </sec><sec><title>Methods</title> Through literature synthesis and deduction, this research organizes and analyzes the multi-scale measurement methods for UBGI’s efficiency in carbon sink enhancement and emission reduction, identifies corresponding influencing factors at each scale, and constructs multi-scale planning strategies for UBGI based on the logical framework of “measurement methods–influencing factors – planning strategies”. </sec><sec><title>Results</title> The research proposes UBGI planning strategies across three spatial scales (site, community and urban area), covering three key aspects: Carbon sequestration and sink enhancement, carbon reduction based on temperature reduction (or preservation), and travel-related carbon reduction. Based on current research gaps and planning needs, five major research topics are further identified. This research provides a detailed analysis of the measurement methods and influencing factors of UBGI’s efficiency in carbon sink enhancement and emission reduction from three perspectives: Carbon sequestration and sink enhancement, carbon reduction based on temperature reduction (or preservation), and travel-related carbon reduction. The research finds significant differences in the measurement methods for UBGI’s efficiency in carbon sink enhancement and emission reduction efficiency across different scales. Contradictory results may occur at different scales, and large-scale research often lacks characterization of internal features, leading to unclear mechanisms of influencing factors and obstructing practical planning. Based on the interpretation of UBGI’s mechanisms for carbon sink enhancement and emission reduction at different scales, this research formulates UBGI planning strategies across three spatial scales (site, community, and urban area). These strategies include: 1) At the site scale, for carbon sequestration and sink enhancement – carbon sink at the source, land balance, and ecological design; for emission reduction – symbiosis with buildings and integration into daily life. 2) At the community scale, for carbon sequestration – overall balance of revenue and expenditure, precise positioning, and proper interconnection of the carbon chain; for emission reduction – incorporation of cool islands and co-construction. 3) At the urban area scale, for carbon sequestration – enhancement of ecological space management and establishment of a carbon-safe pattern; for emission reduction – demand-based layout and organic dispersion. Finally, the research proposes five major research topics for the planning of UBGI’s carbon sink enhancement and emission reduction: How to construct unified measurement methods for UBGI’s efficiency in carbon sink enhancement and emission reduction across scales? How to measure UBGI’s efficiency in carbon reduction based on temperature reduction (or preservation) at the site scale? How to integrate the pathways of carbon sink enhancement and emission reduction for a life cycle assessment of UBGI? How to balance UBGI’s carbon sink enhancement and emission reduction with other functions to achieve the optimal layout for comprehensive benefits? How to achieve urban “carbon justice” through UBGI? </sec><sec><title>Conclusion</title> The carbon sink pathway of the strategy framework requires “carbon sink at the source – precise positioning – safe pattern”, and the emission reduction pathway requires “symbiotic integration – co-construction and sharing – organic dispersion”. The key trade-offs between these two pathways at three spatial scales may provide theoretical support and practical guidance for UBGI construction and management. The five major research topics mentioned above may offer valuable assistance for UBGI construction and future research. </sec>

Rice-crayfish farming represents a typical green and low-carbon alternative to rice monoculture. It is important to investigate the carbon sequestration and emission reduction effect of rice-crayfish farming to improve paddy soil quality, ensure food security, and address climate change challenges. In this study, we systematically evaluated the carbon sequestration and emission reduction effects of rice-crayfish farming through field experiment, carbon footprint assessment, and the DeNitrification-DeComposition (DNDC) model. Compared with rice monoculture, rice-crayfish farming increased the soil organic carbon (SOC) storage, and reduced the annual CH4 emissions, annual N2O emissions, and global warming potential (GWP) by 6.4, 2.4 and 6.2%, respectively. Field engineering, nutrient management and regional variations contributed to differences in carbon emissions and carbon footprints associated with rice-crayfish farming. Moreover, reduction of CH4 emissions was pivotal for decreasing carbon footprint in rice-crayfish farming. DNDC model simulation revealed that the carbon sequestration potential of the rice-crayfish system is influenced by agronomic practices (planting pattern, area proportion of culture ditch, proportion of straw returning, nitrogen fertilizer application, tillage depth, and irrigation regime) and regional climate, landform, and soil. Optimized rice-crayfish farming exhibited varying carbon sequestration effects across different regions. Conversion from rice monoculture to optimized rice-crayfish farming altered the regional carbon sequestration and source dynamics. This study provides a rationale for developing tailored strategies to maximize carbon sequestration and minimize carbon emissions at the regional or farm scales.

The Hu-Bao-O-Yu urban agglomeration is an important energy exporting and high-end chemical base in China, and is an important source of carbon emissions in China. The early achievement of peak carbon emissions in this region is particularly crucial to achieving the national carbon emission reduction targets. However, there is a lack of multi-factor system dynamics analysis of resource-dependent urban agglomerations in Northwest China, as most studies have focused on single or static aspects of developed urban agglomerations. This paper analyses the relationship between carbon emissions and their influencing factors, constructs a carbon emission system dynamics model for the Hu-Bao-O-Yu urban agglomeration, and sets up different single regulation and comprehensive regulation scenarios to simulate and predict the carbon peak time, peak value, and emission reduction potential of each city and urban agglomeration under different scenarios. The results show that: (1) Hohhot and Baotou are expected to reach peak carbon by 2033 and 2031 respectively, under the baseline scenario, while other regions and the urban agglomeration will not be able to reach peak carbon by 2035. (2) Under single regulation scenarios, the effect of factors other than the energy consumption varies across cities, but the energy consumption and environmental protection input are the main factors affecting carbon emissions in the urban agglomeration. (3) A combination of the economic growth, industrial structure, energy policy, environmental protection, and technology investment is the best measure to achieve carbon peaking and enhance the carbon emission reduction in each region as soon as possible. In the future, we need to coordinate the economic development, energy structure optimisation and transformation, low-carbon transformation of industry, strengthen research on carbon sequestration technology, and further increase the investment in environmental protection to make the Hu-Bao-O-Yu urban agglomeration a resource-saving urban agglomeration with an optimal emission reduction.

The application of magical microalgae in carbon sequestration and emission reduction: Removal mechanisms and potential analysis

A comprehensive understanding of land use carbon metabolism characteristics from the production-living-ecological space (PLES) perspective is crucial for formulating carbon reduction strategies. As the core economic zone of northern China, the Beijing-Tianjin-Hebei (BTH) region faces severe carbon emission pressures due to rapid urbanization and intensive land use transformation. However, focusing solely on carbon metabolism calculation without considering future changes and optimization effects may prevent achieving carbon emission reduction targets. This study assessed carbon emissions and sequestration based on different land use types in PLES, constructed a multi-objective carbon reduction scenario utilizing the Dinamica-EGO model, nondominated sorting genetic algorithm II, and entropy weight-TOPSIS model, and simulated 2035 carbon reduction characteristics by coupling PLES changes. Taking the BTH region as a case study, a methodological framework and corresponding models were established. The results show that from 2000 to 2020, the total carbon emissions in the BTH region increased significantly, presenting a spatial pattern of high emissions in the southeast and low emissions in the northwest. In contrast, the overall carbon sequestration capacity showed a decreasing trend, with stronger capacity in the northwest and weaker capacity in the southeast. The multi-variable 2035 carbon emission reduction prediction model achieved an accuracy of 82.24%. The 2035 carbon reduction plan developed based on this framework outperformed the original land use plan: economic benefits, emission reduction efficiency, spatial compactness, and accessibility are projected to increase by 15.8%, 7.9%, 2.5%, and 8.3%, respectively, while carbon emissions are expected to decrease by 19.04%. The proposed PLES-based framework for carbon metabolism measurement and emission reduction simulation exhibits good applicability in regional spatial emission reduction. These findings contribute to exploring regional carbon dynamics and provide references for governments to formulate carbon reduction policies.

The capacity of agricultural cultivation for carbon sequestration and emission reduction plays a key role in advancing the green and sustainable development of agriculture and achieving both emission reduction and carbon sink objectives. This study constructs an index for agricultural carbon sequestration and emission reduction capacity using spatial autocorrelation analysis, Theil index, and kernel density estimation, to thoroughly explore spatiotemporal changes and regional differences in carbon sequestration and emission reduction capacity across China and its different grain functional areas. Major findings include: (1) From 2000 to 2020, China’s agricultural carbon sequestration and emission reduction capacity exhibited a fluctuating upward trend, consistent in grain main production areas, while production–consumption and main marketing areas showed a fluctuating decline. (2) From 2000 to 2020, positive spatial correlation in carbon sequestration and emission reduction capacity increased at both national and regional levels, particularly in the main production and production–consumption areas, while the main consumption areas demonstrated a trend toward negative correlation. (3) The Theil index of China’s agricultural carbon sequestration and emission reduction capacity showed an overall fluctuating increase, with interregional differences contributing over 54%, significantly surpassing intra-regional contributions. Moreover, the main producing regions are the main source of the overall national variance. (4) Kernel density analysis highlights that there are significant differences in the distribution and evolution of carbon sequestration and emission reduction capacity among different grain functional areas, and the overall development is unbalanced. Therefore, each region needs to formulate tailored measures to improve agricultural carbon sequestration efficiency, promote regional sustainable development, and achieve carbon reduction goals.

The current landscape indicates that sustainability is gaining traction as one of the core business strategies. The use of data analytics to monitor and improve sustainability measures in organizations has remained one of the most effective approaches. Thus, this study examines the impact of Big Data Analytics (BDA) capabilities on process eco-innovation and sustainability performance across industries. We focus on four core capabilities—information technology, personnel expertise, management, and BDA—and their role in achieving sustainability goals. Our results reveal that predictive analytics can significantly reduce carbon emissions by 15% over five years, with emissions projected to drop from 100 metric tons in 2024 to 65 metric tons by 2030. Additionally, energy consumption accounts for 33% of overall resource usage, followed by carbon emissions (33%), water usage (24%), and waste generation (10%). Comparative metrics indicate a 30-40% reduction in carbon emissions, water consumption, and waste generation after adopting sustainability practices, underscoring the importance of data-driven innovation. Our findings highlight the varying needs across industries: the financial sector demands real-time decision- making, healthcare focuses on cost optimization, and retail prioritizes customer satisfaction and operational efficiency. Furthermore, regulatory compliance and resource heterogeneity shape BDA adoption, influencing organizational performance. This study offers practical insights into how industries can align analytics with eco-innovation, driving sustainable growth and operational excellence. These results emphasize the transformative potential of predictive analytics in enhancing sustainability, making BDA a critical component of future industrial strategies. The current landscape indicates that sustainability is gaining traction as one of the core business strategies. The use of data analytics to monitor and improve sustainability measures in organizations has remained one of the most effective approaches. Thus, this study examines the impact of Big Data Analytics (BDA) capabilities on process eco-innovation and sustainability performance across industries. We focus on four core capabilities—information technology, personnel expertise, management, and BDA—and their role in achieving sustainability goals. Our results reveal that predictive analytics can significantly reduce carbon emissions by 15% over five years, with emissions projected to drop from 100 metric tons in 2024 to 65 metric tons by 2030. Additionally, energy consumption accounts for 33% of overall resource usage, followed by carbon emissions (33%), water usage (24%), and waste generation (10%). Comparative metrics indicate a 30-40% reduction in carbon emissions, water consumption, and waste generation after adopting sustainability practices, underscoring the importance of data-driven innovation. Our findings highlight the varying needs across industries: the financial sector demands real-time decision- making, healthcare focuses on cost optimization, and retail prioritizes customer satisfaction and operational efficiency. Furthermore, regulatory compliance and resource heterogeneity shape BDA adoption, influencing organizational performance. This study offers practical insights into how industries can align analytics with eco-innovation, driving sustainable growth and operational excellence. These results emphasize the transformative potential of predictive analytics in enhancing sustainability, making BDA a critical component of future industrial strategies.

IntroductionGlobal climate change, increase in human activities, and prominence of ecological issues have led to uneven quantitative and spatial distributions of carbon emission and sequestration of terrestrial ecosystems. Such uneven distributions can lead to more negative impacts on the natural environment and human living conditions.MethodsTherefore, based on the carbon neutralization policy, we conducted geographically weighted regression (GWR) modeling in this study using panel data from 352 Chinese prefectural administrative districts in 2000, 2005, 2010, and 2017 to analyze and determine the impact factors and their spatial distribution for carbon emission and sequestration of terrestrial ecosystems.ResultsOur results showed that total population (TP), per capita gross domestic product (GDP) (PCG), proportion of secondary industry output (PSIO), scale of urban built-up area (SUB), green space proportion in city areas (GSP), normalized difference vegetation index (NDVI), and temperature (TEM) are factors driving carbon sequestration and carbon emission. The spatial distribution of these driving factors in mainland China is: (1) TP showed a negative correlation to carbon emission in most areas, while it exhibited a positive correlation to carbon sequestration in the southern, southwestern, and western parts of northwest China; however, in all other areas, TP showed a negative correlation with carbon sequestration; (2) PCG was positively correlated to carbon emission in most areas of China and to carbon sequestration in southwest, south, central, and northeast China; however, PCG demonstrated a negative correlation to carbon sequestration in the remaining areas; (3) PSIO and SUB presented a positive correlation to carbon emission and a negative correlation to carbon sequestration in most areas; (3) In contrast, GSP showed a negative correlation to carbon emission and a positive correlation to carbon sequestration in most areas; (5)NDVI showed a negative correlation to carbon emission and carbon sequestration in most areas toward the east of the “Heihe-Tengchong Line”; NDVI was positively correlated to both carbon emission and sequestration toward the west of this line; (6)TEM was positively correlated to carbon emission and sequestration in most parts of China.DiscussionBased on these results, we further divided the Chinese cities into 6 groups: (1) Groups 1, 2, 3, and 6 are areas where carbon emission and sequestration are governed by both socioeconomic and natural ecological factors. The major driving factors of carbon emission and carbon sequestration in group 1 are PSIO, GSP, and NDVI; the driving factors of group 2 are SUB and NDVI. Meanwhile, carbon emission and sequestration in group 3 are governed by PCG, GSP, and NDVI; for group 6, carbon emission and sequestration are controlled by PCG, SUB, GSP, and NDVI; (2) Group 4 represents areas where carbon emission and sequestration are majorly impacted by PCG and SUB, thereby rendering socioeconomic factors as the major driving forces. Group 5 represents areas where carbon emission and sequestration are sensitive to the natural environment, with GSP and NDVI being the driving factors. Considering the uneven distribution of carbon sequestration and emission and the diverse driving factors in different areas of China, we provided guidance for future environmental policies aimed at reducing the uneven distribution of carbon sequestration and emission in different areas to achieve carbon neutralization.

Carbon emission has negative externalities, which will cause severe natural and social problems. In recent years, more and more attention has been paid to carbon emission reduction issue both in academic and application fields. This paper aims to explore the impact of punitive carbon tax and incentive carbon emission reduction subsidy on economy and environment through the dynamic stochastic general equilibrium (DSGE) framework. The results show that both carbon tax and carbon emission reduction subsidy policies can help to reduce carbon emissions and to improve environment quality. In addition, carbon emission reduction subsidy has a positive impact on economy, while carbon tax has the opposite impact. It follows that the incentive carbon emission reduction policy is more conducive to the coordinated development of economy and environment. This research can be a guideline for the government to formulate carbon emission abatement policies from the perspective of coordinated development.

Faced with increasingly strict carbon emission control, high-emission enterprises need scientific and rational management systems and methods to strengthen carbon emission reduction management. Among the many management systems and methods, the carbon budget has become an effective emission reduction management tool, allowing the planning of carbon emissions and emission reduction activities and rational arrangement of economic inputs. However, judging from the research status and business practices in China and abroad, there is no general carbon budget system to guide the development of carbon emission and emission reduction activities. Based on this background, this paper first attempts to construct an enterprise carbon budget system comprising four sub-budgets: carbon emission, carbon emission reduction and cost, carbon emission rights trading, and carbon emission reduction net profit/loss. It draws on the idea of interactive control to consider the impact of changes in carbon prices, energy prices, and policy guidelines on carbon emission reductions and losses. A carbon budget management system based on interactive control is then constructed and applied to China National Aviation Holding Air China Group (AC Aviation). The research results show that the carbon budget system based on interactive control can dynamically adjust carbon emission reduction behavior based on changes in carbon and energy prices to make carbon budgeting a more viable carbon reduction tool and institutional arrangement.

The emission of greenhouse gases poses enormous pressure on current carbon emissions and carbon reduction. Accurate quantification of carbon emissions from coal-fired power plants is of great significance for achieving the dual carbon goal. To enable enterprises to better understand their carbon emissions, this study constructs a carbon emission model and carbon emission data accounting model for coal-fired power plants. Case data calculations and a carbon emission reduction analysis were conducted. The experiment showcases that the carbon sensitivity of the inner side of the boiler under control conditions is higher than that of the operating parameters controlled on the inner side of the steam turbine, with a maximum total value of 16.67 g/MJ; the annual average low calorific value of coal remains between 16,000 kJ/kg; the activity level of coal remains between 30,000 TJ; and the oxidation probability of coal char during combustion fluctuates, with a maximum of 99.8%. In the calculation of coal-fired carbon emissions, the fitting difference between the emissions of generator unit 1 and generator unit 2 is maintained within 2%. Overall, the CO2 emissions of power plants involved in the study are generally high. The model built through this study has well analyzed the carbon emissions of power plants. It is of great significance for the actual carbon emission reduction of coal-fired power plants.

Conducting research on food security with multi-dimensional resource orientation. is of great significance. It ensures a stable food supply, alleviates hunger and promotes social and economic stability worldwide. This study constructed a functional zoning of food production security from the perspective of “water-energy” constraints. It was based on the production, water consumption, carbon emission and resource endowment data of four staple foods in 17 cities of Henan Province in 2020. Five methods, such as location entropy, resource endowment coefficient and carbon emission equation, etc., were used. Based on the seventh national population census data and scenario simulations for the “15th Five-Year Plan” period (2026–2030), the queuing element method and the grey GM (1, 1) prediction model were adopted to estimate the population changes and food demand in Henan Province during the “15th Five-Year Plan” period. According to the zoning and demand estimation results, an optimization plan for the planting structure of food crops toward the “15th Five-Year Plan” period was proposed. The results are as follows: ① the food production advantage areas are distributed around the two core areas of “Anyang-Xinxiang” and “Zhumadian”; ② the total population of Henan Province shows a trend of first increasing and then decreasing, but the per capita food demand and total food demand continue to grow; ③ the optimized planting structure of food crops, except for rice, has obvious differences in yield increase in other major food crops; ④ after optimizing the planting structure, water and energy resources consumption is significantly reduced, with a 17.90% reduction in carbon emissions and a 23.32% reduction in water consumption. In this study, a more reasonable yield increase scheme was formed by optimizing the food planting structure. It can effectively reduce the potential hidden dangers of food security caused by the tightening of “water-energy” resources during the “15th Five-Year Plan” period.

PurposeOutsourcing remanufacturing is a major form of remanufacturing, and emission reduction is an important part of a manufacturer's production. This paper aims to investigate carbon emission reduction strategies in a closed-loop supply chain (CLSC) with outsourcing remanufacturing and design a contract to coordinate the CLSC.Design/methodology/approachThe authors establish two-period game models between an original equipment manufacturer (OEM) and third-party remanufacturer (TPR) in different scenarios, including decentralized decision, centralized decision and coordinated decision. Furthermore, the authors study the optimal decisions by maximizing the profit model. The authors also investigate the impact of a carbon tax and emission reduction on the optimal decisions through comparative analysis.FindingsEmission reduction increases the quantity of new products and the OEM's profit. However, emission reduction decreases the outsourcing fee, which is not conducive to remanufacturing; thus, the TPR's profit does not necessarily increase. Compared with a decentralized scenario, the output of remanufactured products and the total profit increase. When the acceptance level of remanufactured products is high enough or when emissions from remanufacturing are low enough, the total carbon emissions are reduced in the centralized scenario. For the coordination of the CLSC, the OEM needs to increase the outsourcing fee and the TPR needs to share part of the emission reduction costs.Research limitations/implicationsThe TPR can choose three different remanufacturing strategies, namely, no remanufacturing, partial remanufacturing or full remanufacturing. For the majority of firms, it is difficult to remanufacture all used products. Therefore, the analysis is based only on partial remanufacturing.Practical implicationsThe results provide insights for remanufacturing and emission reduction decisions, as well as a decision basis for the cooperation between the OEM and TPR.Originality/valueThe authors combine the OEM's carbon emission reduction with outsourcing remanufacturing, and investigate the impact of technological spillover on the TPR's profit.

HighlightsThe broad scope of CSA may hinder the development of projects that include agricultural mitigation strategies.The state of soil carbon contracts and offset markets could limit engagement in carbon initiatives by THP producers.Climate-smart practices aimed at carbon sequestration in the THP may offer co-benefits for water conservation, helping to alleviate pressures on limited water resources.Mitigation initiatives should consider regional climatic and economic conditions in future development.ABSTRACT. Agricultural production in the Texas High Plains (THP) has the potential to sequester carbon and mitigate increasing emissions levels, but the semi-arid climate in the region poses challenges such as limited precipitation and dwindling groundwater resources. This review examines the potential for agricultural carbon sequestration in the THP, producer incentives for engaging in carbon related initiatives, key attributes of soil carbon contracts, and the relationship between climate-smart agriculture (CSA) and water conservation. The review highlights the importance of considering regional climatic and economic conditions in advancing CSA and recognizes the current state of carbon contracts as a barrier to producer participation in carbon sequestration initiatives. Moreover, as water becomes increasingly scarce in the THP, the integration of water conservation strategies with carbon sequestration projects may enhance economic and environmental sustainability in the region. The review underscores the importance of regionally tailored strategies when developing both CSA and carbon sequestration initiatives to address unique environmental concerns while supporting long-term economic feasibility and agricultural sustainability. Keywords: Carbon contracts, Carbon sequestration, Climate-smart agriculture, Economics, Incentives, Ogallala aquifer, Soil carbon, Texas high plains, Water conservation.

This paper aims to establish a more standardized and regulated carbon emission accounting model for sponge cities by unifying the accounting content for carbon emissions and clarifying the relationships between carbon reduction benefits, carbon reduction effects, and carbon sequestration, in order to evaluate the carbon reduction outcomes and mechanisms of sponge city construction. Based on a Life Cycle Assessment (LCA) carbon emission accounting model using the carbon emission factor method, a newly constructed residential area in Tianshui City, Gansu Province, was selected as a case study, and the carbon emission reduction effect of sponge city construction was then investigated. Results indicated that the 30-year full life cycle carbon emissions for sponge city construction in the newly constructed residential area amounted to 828.98 tons, compared to 744.28 tons of CO2 reduction in traditional construction, representing a 47.31% reduction in carbon emissions. Over a 30-year life cycle, this equated to a total carbon emission reduction effect of 1460.31 tons. Additionally, under various rainfall scenarios in a typical year, the carbon emission reduction effect of sponge city construction exceeded the carbon emissions, achieving carbon neutrality within 22 to 30 years of operation. This demonstrates that the carbon emission reduction effect of sponge city communities is significant. The findings of this study provide data and a theoretical basis for the low-carbon construction of sponge cities in China.