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

Historical development, impact mechanism and future trends of nitrogen footprint in Wuxi City, China

Human activities have changed the biogeochemical cycle of nitrogen, leading to a large amount of reactive nitrogen (Nr) into the environment, aggravating a series of environmental problems, affecting human and ecosystem health. Cities are the core areas driving nitrogen cycling in terrestrial ecosystems, however, there are numerous influencing factors and their contributions are unclear. The nitrogen footprint is an important index to understand the impact of human activities on the environment, however, the calculation of urban nitrogen footprint needs a simplified and accurate system method. Here we use a nitrogen footprint calculation model at the urban system level based on system nitrogen balance, and a multi-factor extended STIRPAT (stochastic impact by regression on population, affluence, and technology) model suitable for analyzing the impact mechanism of nitrogen footprint to estimate nitrogen footprint of Wuxi City during 1990-2050. We find that: (1) from 1990 to 2020, the total nitrogen footprint of Wuxi City was in an increasing trend, but the per capita nitrogen footprint was in a decreasing trend. The per capita nitrogen footprint of 22.36 kg capita-1 in 2020 was at a lower level globally. (2) Nr discharge from fossil fuel combustion and Haber-Bosch nitrogen fixation accounted for the main proportion of nitrogen footprint. (3) Dietary choice (Ad), GDP per capita (Ag), urbanization rate (Au), population (P), and fossil energy productivity (Te) were the key factors contributing to the increase of the nitrogen footprint, which resulted in an annual increase of 1.39 %. While nitrogen footprint productivity (Tn), nitrogen use efficiency in crop farming (Tc), and nitrogen use efficiency in animal breeding (Ta) were the key inhibit factors that inhibit the increase of nitrogen footprint, and these factors slow down the annual growth rate of nitrogen footprint by 0.39 %. (4) The continuous growth of nitrogen footprint in the baseline and population growth scenarios will bring more environmental problems and greater environmental governance pressure to Wuxi City, while the sustainable scenario that includes comprehensive means such as economic adaptation and technological improvement is more in line with the requirements of high-quality development in China. Several mitigation measures are then proposed by considering Wuxi's realities from both key impact factors and potential for nitrogen footprint reduction in different scenarios, which can provide valuable policy insights to other cities, especially lakeside cities to mitigate nitrogen footprint.

Re-measurement and influencing factors of agricultural eco-efficiency under the 'dual carbon' target in China

Given that agriculture is both a carbon source and sink, the sustainability goals of carbon peaking and neutrality place high demands on the green and low-carbon agricultural development in China, and the exploration of a realistic path for a sustainable agricultural development is urgently needed. Under the above 'dual carbon' target, this study focused on the key issue of how to improve China's agricultural eco-efficiency (AEE) and constructed an innovative AEE indicator system that can reflect carbon constraint and coordinated agricultural economic development, resource use and ecological environment. The super-efficient slack-based measured Data Envelopment Analysis (SBM-DEA) method, which considers undesirable outputs, was applied to re-measure the AEE of 30 provinces and cities in China from 2001 to 2020, and its spatial and temporal evolution was analysed in conjunction with kernel density estimation. The Tobit regression model was used to explore various influencing factors by region. The results show that the AEE re-measurements, which take into account the 'dual carbon' requirement, are significantly better than the traditional AEE. From 2001 to 2020, China had an overall V-shaped fluctuation curve AEE, with a small decline and several inter-annual fluctuations, and exhibited a large potential to rise. China's AEE showed a spatially uneven regional development at different stages of distribution and evident multi-polar differentiation. Inter-provincial differences were observed in China's AEE, and the vicious circle of low-level green and low-carbon agricultural development was difficult to break. Urbanisation had a significant positive effect on national and eastern AEE but a significant negative effect on central AEE. The agricultural carbon offset rate had a significant effect on AEE nationally and in the three regions. Thus, the introduction of 'dual carbon' target effectively drove the development of AEE. Agricultural industry structure inhibited the improvement of AEE nationally and in the western region. Agricultural economic development hindered the national AEE improvement but promoted that of the central region, where China showed an environment Kuznets curve. Hopefully, this study can provide data support and theoretical reference for the green and low-carbon agricultural development and help achieve the 'dual carbon' target.

Agricultural tridimension pollution emission efficiency in China: An evaluation system and influencing factors

We innovated traditional one-sided agricultural carbon emission efficiency research, comprehensively explored the agricultural tridimension pollution emission efficiency (ATPEE), constructed an ATPEE evaluation system considering technological heterogeneity characteristics based on the meta-frontier nonradial directional distance function (NDDF) model in a total-factor framework, evaluated the ATPEE in 30 mainland China provinces from 1997 to 2021 for the first time, and empirically studied the factors influencing the ATPEE in China with the Tobit model. The results showed the following: (1) ATPEE improvement potentials of 75.16 % and 50.88 % occur under the meta and group frontiers, respectively. (2) The eastern region represents the potential optimal agricultural tridimension pollution emission technology, while the central and western regions exhibit a large gap with the national potential optimal technology level. (3) The ATPEE loss in the eastern and western regions mainly results from management inefficiency, while that in the central region largely results from technology gap inefficiency. (4) The effects of the industrialization rate, urban-rural income gap, agricultural production structure, financial support for agriculture, natural conditions and effective irrigation rate on the ATPEE in the different regions vary.

Impacts of land use transitions on ecosystem services: A research framework coupled with structure, function, and dynamics

Rapid urbanization in China has resulted in drastic land use transitions (LUT) and has had a severe impact on the supply of regional ecosystem services (ESs). To improve ecosystem security and promote sustainable development regionally, it is essential to clarify spatial correlations between the multi-dimensional characteristics of LUT and ESs. We developed a theoretical framework to examine how LUT influenced regional ESs in three dimensions: land use structure, function, and dynamics. Using the Taihu Lake Rim urban agglomeration (TLRUA) as an example, we explored the process by which LUT affected the change in regional ESs. The results indicated that the TLRUA experienced accelerated urbanization between 2000 and 2018, with LUT and ESs exhibiting distinct characteristics in urban, suburban, and rural areas in different regions. The impact of LUT on ESs, as we analyzed them from different dimensions, embraced interactive effects and significant spatial spillover effects. The land use structural transitions were globally positively correlated with habitat maintenance, carbon sequestration, and recreation potential, whereas land use intensity and dynamics transitions exhibited negative correlations. Given their interactions at the local scale, we propose corresponding land management strategies, which can offer practical guidance for coordinating regional land resource development and ecosystem conservation.

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.

Phytoplankton in headwater streams: spatiotemporal patterns and underlying mechanisms

Phytoplankton are key members of river ecosystems wherein they influence and regulate the health of the local environment. Headwater streams are subject to minimal human activity and serve as the sources of rivers, generally exhibiting minimal pollution and strong hydrodynamic forces. To date, the characteristics of phytoplankton communities in headwater streams have remained poorly understood. This study aims to address this knowledge gap by comparing phytoplankton communities in headwater streams with those in plain rivers. The results demonstrated that within similar watershed sizes, lower levels of spatiotemporal variability were observed with respect to phytoplankton community as compared to plain rivers. Lower nutrient levels and strong hydrodynamics contribute to phytoplankton growth limitation in these streams, thereby reducing the levels of spatiotemporal variation. However, these conditions additionally contribute to greater phytoplankton diversity and consequent succession towards Cyanophyta. Overall, these results provide new insights into the dynamics of headwater stream ecosystems and support efforts for their ecological conservation.

Low-carbon transformation of China's smallholder agriculture: exploring the role of farmland size expansion and green technology adoption

Farmland size and green technology have a significant impact on agricultural carbon emissions. However, more research needs to consider the impact of their interaction on agricultural carbon neutralization. In this paper, the impact of farmland size on the net carbon effect and its underlying mechanisms from the perspective of green agricultural technology adoption were empirically examined using a tracking survey of 2600 farming households. The results show that farmland size expansion at both household and plot levels can increase the net carbon effect of the planting industry, which is more pronounced for grain crops than cash crops. Specifically, a 1% increase in the total area of household farmland or the largest contracted plot area can increase the net carbon effect by more than 3%. Green technology also plays a mediation effect in their relationship. Increasing farmland size can generate sufficient economic incentives to encourage green technology adoption, contributing to carbon sequestration and emissions reduction and increasing the crop's net carbon effect. Furthermore, we find that farmland expansion can significantly encourage the adoption of efficiency-enhancing technologies but not environmentally friendly technologies. Our findings suggest that promoting farmland expansion and green technology extension is effective for the low-carbon transformation of Chinese agriculture. The government should make distinct promotion policies for various green agricultural technologies and differentiating incentives and support policies for different-sized farmers. Our study provides insights into the path to Chinese-style agricultural modernization in the context of a smallholder economy.

Spatiotemporal characteristics and determinants of agricultural carbon offset rate in China based on the geographic detector

This paper attempts to explore the spatiotemporal variation characteristics of the agricultural carbon offset rate (ACOR) and the reasons that shape its differentiation characteristics in China. To achieve this objective, the Dagum Gini coefficient, kernel density estimation, and geographic detector model are employed in this study. The results show that there are some differences in ACOR among regions in China. Interregional differences are the main source of their overall variation. Excluding the spatial conditions, the ACOR of each province in the sample period shows low mobility characteristics. Considering the spatial conditions, there is convergence in the lower-middle neighborhoods. The three-year lag period did not significantly affect the interaction of ACOR between regions under the accession time horizon. At the aggregate level, the spatial and temporal divergence in China's ACOR is driven by urbanization rate, agricultural fiscal expenditure, and rural education level. As for the regional level, the scale of household farmland operation plays a greater role in determining the spatiotemporal variation of the eastern and central regions' ACOR. While urbanization rate is more determinant for the western region, the interaction between any two factors has significantly higher explanatory power for the spatial and temporal variation of ACOR than the single factor.

Driving factors of spatial-temporal difference in China's transportation sector carbon productivity: an empirical analysis based on Geodetector method

Carbon productivity is the core index to measure the performance of carbon emission reduction. Exploring the driving factors of the spatial-temporal differences in China's transportation sector, carbon productivity (TSCP) is conducive to the low-carbon sustainable development of the transportation sector. Based on the calculation of TSCP in 30 provinces in China from 2000 to 2019, we use time series, spatial visualization, and Dagum Gini coefficient to reveal the characteristics of spatial-temporal evolution and regional differences of TSCP, and uses Geodetector to identify the driving factors that affecting the spatial-temporal differences of TSCP. The results are as follows: (1) from 2000 to 2019, China's TSCP shows a U-shaped change trend of "decline to rise," and shows a spatial pattern of "high in the eastern and central, low in the western". (2) There are obvious regional differences in China's TSCP. The differences within each region show the trend of "eastern > central > western," while the differences between regions show the trend of "central-western > eastern-western > eastern-central," and the differences between regions are the main reason for the overall differences. (3) The spatial-temporal differences in China's TSCP are affected by many factors, such as social economy and self-endowment. Overall, energy intensity, foreign trade, technological innovation level, energy structure, and industrial structure are the dominant factors. Additionally, the interaction between the driving factors enhances the impact on the spatial-temporal differences of TSCP. Finally, according to the analysis results, some policy suggestions are put forward to improve TSCP.

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.

Impacts of Land-Use Change on the Spatio-Temporal Patterns of Terrestrial Ecosystem Carbon Storage in the Gansu Province, Northwest China

Land-use change is supposed to exert significant effects on the spatio-temporal patterns of ecosystem carbon storage in arid regions, while the relative size of land-use change effect under future environmental change conditions is still less quantified. In this study, we combined a land-use change dataset with a satellite-based high-resolution biomass and soil organic carbon dataset to determine the role of land-use change in affecting ecosystem carbon storage from 1980 to 2050 in the Gansu province of China, using the MCE-CA-Markov and InVEST models. In addition, to quantify the relative size of the land-use change effect in comparison with other environmental drivers, we also considered the effects of climate change, CO2 enrichment, and cropland and forest managements in the models. The results show that the ecosystem carbon storage in the Gansu province increased by 208.9 ± 99.85 Tg C from 1980 to 2020, 12.87% of which was caused by land-use change, and the rest was caused by climate change, CO2 enrichment, and ecosystem managements. The land-use change-induced carbon sequestration was mainly associated with the land-use category conversion from farmland to grassland as well as from saline land and desert to farmland, driven by the grain-for-green projects in the Loess Plateau and oasis cultivation in the Hexi Corridor. Furthermore, it was projected that ecosystem carbon storage in the Gansu province from 2020 to 2050 will change from −14.69 ± 12.28 Tg C to 57.83 ± 53.42 Tg C (from 105.62 ± 51.83 Tg C to 177.03 ± 94.1 Tg C) for the natural development (ecological protection) scenario. By contrast, the land-use change was supposed to individually increase the carbon storage by 56.46 ± 9.82 (165.84 ± 40.06 Tg C) under the natural development (ecological protection) scenario, respectively. Our results highlight the importance of ecological protection and restoration in enhancing ecosystem carbon storage for arid regions, especially under future climate change conditions.

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.

Digital Economy, Agricultural Technological Progress, and Agricultural Carbon Intensity: Evidence from China

China is the largest carbon emitter in the world, with agricultural carbon emissions accounting for 17% of China’s total carbon emissions. Agricultural carbon emission reduction has become the key to achieving the “Double Carbon” goal. At the same time, the role of the digital economy in achieving the “dual carbon” goal cannot be ignored as an important engine to boost the high-quality development of China’s economy. Therefore, this paper uses the panel data of 30 provinces in mainland China from 2011 to 2019 to construct a spatial Durbin model and a mediation effect model to explore the impact of the digital economy on agricultural carbon intensity and the mediating role of agricultural technological progress. The research results show that: (1) China’s agricultural carbon intensity fluctuated and declined during the study period, but the current agricultural carbon intensity is still at a high level; (2) The inhibitory effect of the digital economy on agricultural carbon intensity is achieved by promoting agricultural technological progress, and the intermediary role of agricultural technological progress has been verified; (3) The digital economy can significantly reduce the carbon intensity of agriculture, and this inhibition has a positive spatial spillover effect. According to the research conclusions, the government should speed up the development of internet technology and digital inclusive finance, support agricultural technology research and improve farmers’ human capital, and strengthen regional cooperation to release the contribution of digital economy space.

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.