Selecting low-carbon technologies and measures for high agricultural carbon productivity in Taihu Lake Basin, China

Carbon metabolism in "production-living-ecological" space in urban agglomeration based on land use change

To grasp the impact of carbon metabolism on the evolution of "production-living-ecological" (PLE) space due to land use change in the Changsha-Zhuzhou-Xiangtan (CZT) urban agglomeration, this study delves into the temporal and spatial distribution of PLE space carbon metabolism by constructing a carbon flow model. We evaluate the influence of positive and negative carbon flows on carbon metabolism using ecological network analysis and utility assessment. Furthermore, we delve into the driving factors behind carbon metabolism through redundancy analysis (RDA). The findings of this study included mainly the following aspects. (1) From 2000 to 2020, the net carbon flow in the CZT urban agglomeration consistently remained negative, with the primary source of negative carbon flow being the transition from ecological space to production space. (2) Within the ecological utility network, the dominant ecological relationship shifted from a period of control and exploitation relationship (counted for 61.91%) between 2000 and 2005 to one of competition relationship that counted for 83.33% in 2005-2010, 47.62% in 2010-2015, and 66.67% in 2015-2020. Mutualism relationship, present in the 2000-2005 period, completely disappeared in subsequent years. (3) The value of the utility function M was 0.88, 0.36, 0.48, and 0.40 in four stages (all less than 1), which meant that PLE space evolution on regional carbon metabolism was negative. (4) The key drivers influencing carbon metabolism in PLE space were mainly Change in the Comprehensive Land Use Index (CL), Change in the Proportion of Manufacturing Land (CM), Change in the Proportion of Forestland (CF), and Change in the Proportion of Cultivated Land (CC). Carbon metabolism holds a critical role in the urban material and energy cycle. Studying carbon metabolism within PLE space carries great importance for regional carbon cycling, carbon emission and sequestration, efforts to mitigate climate change, and the maintenance of regional sustainable development.

Agricultural carbon emissions in Zhejiang Province, China (2001-2020): changing trends, influencing factors, and has it achieved synergy with food security and economic development?

Given the huge carbon footprint of agricultural activities, reduction in agricultural carbon emission (ACE) is important to achieve China's carbon peaking and carbon neutrality goals, but it may affect agricultural food security and economic development. Therefore, it is important for scientific carbon reduction measures to understand the multi-year trends and the influencing factors of ACE, and clarify whether the process of ACE affects food security and economic development. This study analyzed the trends of total ACE and ACE caused by different agricultural carbon sources (ACS) from 2001 to 2020 in Zhejiang Province, then we revealed the main influencing factors of ACE based on the logarithmic mean Divisia index (LMDI) model and dissected the relationship between ACE and food security and economic development. Results show that the total ACE fluctuated from 6.10 Mt in 2001 to 3.93 Mt in 2020, and the process included a decrease in 2001-2003 and 2005-2020 and an increase in 2003-2005. The decrease in ACE, from 2001 to 2014, was mainly due to the decline in rice acreage, which contributed 90.38%; from 2014 to 2020, it was by the reduction in the use of fertilizer, diesel, and pesticide, which contributed 83.9%. As drivers, agricultural economic development effect and total population size effect drove 4.25 and 1.54 Mt of ACE, respectively. As inhibitors, planting structure effect, technology development effect, and population structure effect inhibited 3.12, 2.11, and 2.74 Mt of ACE, respectively. With the reduction of ACE, the agricultural economy continued to grow, but the food security situation was pessimistic, indicating that ACE reduction has achieved synergy with economic development, but not with food security.

Investigating the rationale for low-carbon production techniques in agriculture for climate change mitigation and fostering sustainable development via achieving lowcarbon targets

In China, agricultural activities are a major source of greenhouse gas emissions, ranking second only to another significant source. This presents a significant obstacle to reducing emissions and jeopardizes both the availability of food and the sustainable growth of agriculture. It is primarily the farmers who utilize cultivated land and are thus accountable for the initiation of these emissions. Farmers' role is significant in adopting green and low-carbon (LC) agricultural production practices, and their actions are directly tied to the achievement of the dual goals of carbon reduction. Understanding their motivations for engaging in LC production and the factors that influence their willingness to do so is important for both theory and practice. In this study, data was collected from 260 questionnaires in 13 counties across five major cities in Shaanxi Province. The purpose was to identify factors that impact farmers' motivation and willingness to engage in LC agriculture using linear regression analysis. A structural equation model was constructed to better understand the underlying mechanisms that influence farmers' actions towards LC farming practices. The study's findings indicate that (1) farmers' behavior towards LC production practices is notably impacted by internal motivation based on joy and internal motivation based on responsibility (IMR); (2) IMR has the most pronounced effect on farmers' adoption of LC production practices; (3) the internal motivation based on joy, IMR, behavior attitude, subjective norm, and perceived behavior control are related to each other; and (4) the multi-group analysis of the data indicates that the impact of internal motivation based on joy and IMR on adopting sustainable farming practices may vary among different groups. It is essential to support farmers who have strong intrinsic motivation to engage in sustainable agriculture. Additionally, policymakers must promote positive attitudes towards sustainable farming to achieve the desired environmental (LC) objectives.

How does Internet use affect farmers' low-carbon agricultural technologies in southern China?

Agricultural low-carbon emission reduction is an essential part of China's ecological civilization construction. Farmers' low-carbon agricultural technology (LCAT) adoption has become an important means to achieve agricultural low-carbon emission reduction. Based on the survey data of 1080 farmers in Sichuan Province, farmers' LCAT adoption has been empirically studied using the combined estimate conditional mixed treatment model (CMP). The results show that the use of the Internet will substantially promote farmers' low-carbon tillage technology adoption and low-carbon fertilization technology adoption but has no significant impact on farmers' low-carbon pharmaceutical application technology adoption, low-carbon irrigation technology adoption, low-carbon agricultural film recycling technology adoption, and straw recycling technology adoption. Mechanism analysis shows that Internet use mainly affects farmers' low-carbon fertilization technology adoption through economic benefit cognition and affects farmers' low-carbon tillage technology adoption through ecological benefit cognition. This study can enhance our understanding of the relationship between Internet use and LCAT adoption and serve as a resource for rural digital infrastructure development and LCAT adoption-related policy design.

Reactive nitrogen budgets in human-nature coupling system in lakeside area with insufficient data - A case study of Mwanza, Tanzania

Nitrogen (N) is an essential nutrient element for life, and also a major element involved in the composition of greenhouse gases, surface water pollutants, air pollutants, etc. Quantifying and evaluating the nitrogen budget of a region is very important for effectively controlling the nitrogen discharge and scientifically managing the nitrogen cycle. In this paper, the urban Rural Complex N Cycling (URCNC) model was used to analyze the nitrogen budget of Mwanza region, a typical lakeside area with insufficient data, and the nitrogen flow process of livestock subsystem, cropland subsystem, human subsystem and landfill subsystem was clearly described and the nitrogen input sources of atmospheric subsystem and surface water subsystem were clarified. And the results demonstrated: (1) the cropland subsystem was the subsystem with the largest nitrogen flux, and the input, output and accumulation of nitrogen were 33,116 t of N, 31,925 t of N and 1191 t of N, respectively. Livestock subsystem was the second largest subsystem of nitrogen flux, and the input, output and accumulation of nitrogen were 31,013 t, 30,183 t and 830 t, respectively. The nitrogen flux of the human subsystem was also large, and the nitrogen input, output and accumulation were 17,905, 17,125 and 780 t, respectively. The nitrogen input, output and accumulation of the landfill subsystem were 3700 t, 770 t and 2930 t, respectively. (2) 8093 t of N, 6864 t of N, 3959 t of N, and 758 t of N emitted into the atmospheric subsystem from the livestock subsystem, cropland subsystem, human subsystem, and landfill subsystem, respectively. (3) The total Nr input of surface water subsystem increased from 18,545 t of N in 2010 to 20,174 t of N in 2020, with an increase of 8.78 % in the past decade. It was estimated that by 2030, the total Nr input of the surface water subsystem would reach 24,946 t of N with an increase of 23.65 % compared with 2020. The livestock subsystem was the largest source, the cropland subsystem was the second largest source and human subsystem was an important source. (4) Population growth, economic development and urbanization are the main nitrogen driving factor. (5) Technology and policy together have important contributions to the reduction of nitrogen pollution in surface water.

Examining key impact factors of energy-related carbon emissions in 66 Belt and Road Initiative countries

Climate change with global warming as the main feature associated with fossil energy use has been recognized as a threat to public health and welfare. Energy-related carbon emission reduction is a more serious challenge for BRI (Belt and Road Initiative) countries with rapid economic development. Examining key impact factors is necessary and helpful. This paper is the first study providing detailed country-by-country analyses aiming to identify the key drivers and inhibitors of energy-related carbon emission in 66 BRI countries with more systematic impact factors. The results show that: (1) Economic development (A), population (Ps), urbanization (Pu), and industrialization (Ss) are the key drivers for 52%, 26%, 11%, and 6% countries of BRI countries. Technological progress (T), energy consumption structure (E), and tertiary industry proportion (St) serve as key inhibitors for 65%, 17%, and 8% countries of BRI countries. (2) Different carbon emission reduction strategies should be formed on different geographical scales. At the international level, carbon emission reduction consensus should be reached and carbon emission reduction targets should be formulated. At the regional level of the Belt and Road Initiative, a carbon emission reduction cooperation fund should be established, and carbon emission reduction technologies and measures should be exchanged and data should be shared to promote the green development of the Belt and Road. At the national level, there should be carbon emission reduction policies reflecting national characteristics. At the local level, there should be specific carbon reduction measures in line with local conditions.

Pro-Environmental Behavior: Examining the Role of Ecological Value Cognition, Environmental Attitude, and Place Attachment among Rural Farmers in China

Studies on the factors that influence farmers' pro-environmental behavior could promote environmental management in rural areas. Jinan of China was selected as the case study area in this study. A structural equation model and multiple hierarchical regression analysis were applied to analyze the influence mechanism of ecological value cognition on pro-environmental behavior. Environmental attitudes were set as the mediating variable and place attachment was selected as the moderating variable. The results showed that (1) ecological value cognition exhibited a positive influence on pro-environmental behavior in both direct and indirect ways. The indirect influence was mediated by environmental attitude. (2) Place identity and place dependence showed a positive direct influence on pro-environmental behavior. (3) It is suggested that in order to improve pro-environmental behavior, enhancing ecological value cognition, cultivating farmers' positive environmental attitude, increasing farmers' place attachment, and releasing reward and punishment measures are good strategies. The findings in this study are important to the improvement of the rural ecological environment and the quality of life of farmers. Meanwhile, the findings shed light on the construction process of ecological civilization and the improvement of public welfare.

A Study on the Impact of Low-Carbon Technology Application in Agriculture on the Returns of Large-Scale Farmers

The relationship and mechanism between agricultural low-carbon technology application and farm household returns are not yet clear, especially the lack of evidence from developing countries. This paper takes large-scale farming households in Jiangxi Province, China, from 2019 to 2020 as the research object, and obtains relevant data from field research to explore the intrinsic impact of agricultural low-carbon technology application on the returns of large-scale farming households. Based on the relevant theoretical analysis, the division dimensions of agricultural low-carbon technologies were proposed, and agricultural low-carbon technologies were subdivided into ten specific low-carbon technologies according to six dimensions: tillage system, breeding, fertilization, irrigation, medicine application, and waste treatment. Relevant questions were designed and researched to obtain data on the application status of low-carbon technologies in agriculture and the income cost status of large-scale farmers. Based on the theoretical analysis, the research hypotheses were proposed, and an empirical analysis was conducted based on the obtained data from large-scale farmers. The application of seven low-carbon technologies in agriculture: conservation tillage system, direct sowing technology, selection of compound fertilizer/organic fertilizer/controlled-release fertilizer, soil formula fertilization technology, deep fertilization/irrigation fertilization, sprinkler/drip irrigation/wet irrigation/intermittent irrigation, and straw resourceization significantly improved the income level of large-scale farmers. Furthermore, the application of biodegradable agricultural membranes, biopesticides, and new pesticide-controlled release technologies did not have significant effects on the income level of large-scale farmers, due to their low application and penetration rate. Based on the findings of the paper, the government should strengthen the promotion and subsidies of agricultural low-carbon technologies, especially those technologies that have no significant impact on large-scale farmers' income, such as biodegradable agricultural membranes, biopesticides, and new pesticide controlled-release technologies, so as to achieve a win-win situation of reducing carbon emissions and increasing farmers' income.

Influencing mechanism of non-CO2 greenhouse gas emissions and mitigation strategies of livestock sector in developed regions of eastern China: a case study of Jiangsu province

The livestock sector not only provides people with meat, eggs, milk, and other nutrients but also causes a large number of non-CO₂ greenhouse gas emissions. It is urgent to explore the influence mechanism of non-CO₂ greenhouse gas emission from the livestock sector and formulate effective mitigation strategies. Taking Jiangsu province as an example, we analyzed the influencing factors of non-CO₂ greenhouse gas emissions from the livestock sector based on sources and modified the STIRPAT (stochastic impact by regression on population, affluence, and technology) model, proposed the directions, designed the generally circular path, and determined the focus of non-CO₂ greenhouse gas emissions reduction from the livestock sector. The results demonstrated: (1) the top priority of emission reduction of livestock sector in Jiangsu province was the reasonable treatment of manure produced by livestock (non-CO₂ greenhouse gas emissions from manure had accounted for more than 60% of the total emissions from the livestock sector since 2007.), and the core was pig manure management (the CH₄ and N₂O emissions from pig manure accounted for more than 90 and 50% of the total CH₄ and N₂O emissions from all livestock manure, respectively). (2) The decrease of the agricultural population, the increase of livestock output value per capita of the agricultural population, and the improvement of livestock carbon productivity all reduced non-CO₂ greenhouse gas emissions of the livestock sector. For every 1% decrease in agricultural population, for every 1% increase in livestock carbon productivity and livestock output value per capita of the agricultural population, non-CO₂ greenhouse gas emissions from the livestock sector would be reduced by 0.0859%, 0.1748%, and 0.0400%, respectively. (3) To construct and improve the low carbon industrial chain of the livestock sector, to promote low carbon technology research and development and introduction are two focuses for non-CO₂ greenhouse gas emission reduction in the livestock sector. The research can provide a basis for non-CO₂ greenhouse gas emissions reduction from the livestock sector in China, especially in the developed eastern regions.

The influence mechanism and spatial effect of carbon emission intensity in the agricultural sustainable supply: evidence from china's grain production

Agricultural carbon mitigation is critical for China to encourage the sustainable development of agriculture and achieve the carbon peak by 2030 and carbon neutrality by 2060. By exploring the impact mechanism of the carbon emission intensity (CEI) of grain production, we can effectively promote the low-carbon transformation of agricultural production and ensure the sustainable development of the food supply. This article analyzes the temporal and spatial evolution of the total carbon emission (TCE) and CEI of staple crops and adopts a dynamic spatial model to explore the influence mechanism and spatial spillover effects of the CEI of grain production based on evidence from China's major grain-producing provinces from 2002 to 2018. The results indicate that the TCEs of rice, wheat, and maize fluctuate upward and that the CEI in most producing areas decreases with low-low agglomeration (or high-high agglomeration). Among the influencing factors, technology is the main factor reducing CEI. Technical efficiency, urbanization, industrial structure, agricultural agglomeration, and agricultural trade openness can be transmitted to neighboring areas through spatial spillover mechanisms. The spatial spillover mechanisms are resource flow, technology spillover, and policy learning, producing the demonstration effect and siphon effect. Based on our findings, agricultural technology innovation and popularization, urbanization, optimization of the agricultural structure, financial payments, and factor flow among regions should be improved to encourage the low carbon transformation of grain production.

The farm-by-farm relationship among carbon productivity and economic performance of agriculture

The mitigation of agricultural greenhouse gases emissions is a globally relevant environmental and policy issue. For efficient mitigation, it is important to appraise whether and how much these emissions are linked to the economic performance of farms. This study aims to reconstruct a Carbon Productivity (CP) indicator at the farm level to analyse its eventual relationship with the farm's economic performance as measured by its Farm Net Value Added (FNVA). This assessment could allow emerging win-win situations where more emission-efficient farms are also more economically viable. This study is conducted at the micro-level using individual farm data extracted from the Italian Farm Accountancy Data Network from 2008 to 2017. The estimation procedure is based on a dynamic panel model that exploits the wide heterogeneity of farms using structural and policy variables. Results show that the relationship between CP and FNVA is non-linear and changes among farm types. Overall, absolute higher levels of CP seem to be associated with better economic performance, suggesting a double-dividend path of green growth for agricultural production. Policy implications drawn suggest tailored intervention according to farm type.

What drives low-carbon agriculture? The experience of farms from the Wielkopolska region in Poland

Because of global environmental problems, low-carbon agriculture has gained increasing importance both in developed and developing countries. Hence, there is a need to find ways to develop more efficient agricultural systems. The purpose of this article is to identify the drivers of low-carbon agriculture on farms in the Wielkopolska region (in Poland). We aimed to take an original approach to investigate low-carbon agriculture with a unique set of different economic and environmental variables and contribute to the literature, which is not very extensive in terms of microeconomic research, including research on farmers in the Wielkopolska region. Therefore, we employed a multiple-factor measurement model for structural equation modeling (SEM) of data collected individually from 120 farms in 2020. As a result, we formulated the following conclusions: the increasing productivity of factors (land, labor, and capital) have a positive effect on low-carbon farming, just as increasing fertilizer and energy efficiency. Moreover, thermal insulation is also important for low-carbon agriculture, with efficiency of fertilizer use being the most important factor. We believe that the issues of farm use of fertilizers and thermal insulation of buildings should be more broadly included in energy policy, both at the national and the European Union (EU) levels. Some of these factors however are already present in the common agricultural policy (CAP) for 2021-2027.

Spatial differentiation identification of influencing factors of agricultural carbon productivity at city level in Taihu lake basin, China

Improving carbon productivity is the main way to deal with climate change under China's targets for carbon emissions to peak by 2030 and carbon neutrality by 2060. This study identified the spatial differentiation of influencing factors of agricultural carbon productivity at the city level in Taihu lake basin, and formed differentiated agricultural management strategies. The results show that: (1) Spatial differentiation of agricultural carbon productivity is obvious at city level. It can be divided into three echelons: the first echelon is Shanghai and Hangzhou (agricultural carbon productivity≥10,000 Yuan/t in 2019 with a growth rate ≥ 600% compared with 1992), the second echelon is Suzhou, Wuxi and Changzhou (9000 Yuan/t ≤ agricultural carbon productivity<10,000 Yuan/t in 2019 with 381% ≤ growth rate < 600% compared with 1992), and the third echelon is Zhenjiang, Huzhou and Jiaxing (agricultural carbon productivity<9000 Yuan/t in 2019 or a growth rate < 381% compared with 1992). (2) There is a synergetic evolution law between agricultural carbon productivity and agricultural economy, that is, agricultural economic development level is the first factor affecting agricultural carbon productivity, whether in the whole basin or in the city level. (3) There are significant differences in the influencing factors of agricultural carbon productivity at the city level. Finally, according to the spatial differentiation characteristics of influencing factors of agricultural carbon productivity at the city level in Taihu lake basin, we put forward different emphases of agricultural development in different cities.