Agricultural Greenhouse Gas Research Articles

The potential for bioenergy generated on marginal land to offset agricultural greenhouse gas emissions in China

Rational use of marginal land for cultivation of bioenergy crops is an effective means to solve land use competition and is an important way to reduce greenhouse gas (GHG) emissions and improve energy supply. This study conducted an evaluation of the suitability of marginal land for growing energy crops in China during 1990–2020 using the GIS and multi-factor analysis method and revealed the quantitative relationship between bioenergy produced by marginal land energy crops and carbon reduction potential. The Intergovernmental Panel on Climate Change (IPCC) coefficient method and life cycle method were applied to measure the biofuel yield of the Jatropha curcas and assessed its potential to offset agricultural greenhouse gas emissions. The findings are: (1) The marginal land area available for energy crops in 2020 is 1.63 × 106 km2, which is 8.35 % lower than the area planted in 1990. (2) When the reclamation index is 60 %, all suitable marginal land can be used to grow energy crops, and biofuels can replace 3.31 × 1011 tons of conventional energy. (3) In 2020, agricultural greenhouse gas emissions will be 9.02 × 108 tons, and the potential of bioenergy crop cultivation to offset agricultural greenhouse gas emissions amounts to 4.31 × 108 tons, or 47.88 %. In the future, the pressure of agricultural GHG emission reduction will be further exacerbated by population growth and agricultural land supply, etc. Rational use of marginal land and development of bioenergy crops are effective ways for China to cope with climate change and realize its renewable energy strategy.

Trade-induced land-use transitions and greenhouse gas emissions: The case of the EU-Mercosur free-trade agreement

Currently, land use change (LUC) accounts for approximately 18.8% of all greenhouse gas (GHG) emissions globally, and up to 66% and 70% in Brazil and Paraguay respectively. However, owing to measurement difficulties, examining the effects of changing trade patterns is often overlooked in studies. This study aims to investigate the induced effects of LUC and their consequences concerning GHG emissions for the EU-Mercosur free trade agreement. A multi-regional computable general equilibrium (CGE) model with an explicit land module is used to simulate the effects of the free trade agreement. GHG emissions are calculated for LUC, fossil energy CO2, and non-CO2 emissions to capture a wide range of sources and reveal their relative contributions. The study finds that as a more extensive liberalization scheme is implemented, the majority of global GHG emissions change are driven by LUC, consisting up to 89.9% of the total increase. These findings align with previous studies. Nonetheless, we argue that for Latin America, where LUC and deforestation are historical problems, careful consideration of LUC and agriculture GHG sources is necessary to address the potential environmental impacts of trade agreements.

A global dataset for the production and usage of cereal residues in the period 1997–2021

Crop residue management plays an important role in determining agricultural greenhouse gas emissions and related changes in soil carbon stocks. However, no publicly-available global dataset currently exists for how crop residues are managed. Here we present such a dataset, covering the period 1997–2021, on a 0.5° resolution grid. For each grid cell we estimate the total production of residues from cereal crops, and determine the fraction of residues (i) used for livestock feed/bedding, (ii) burnt on the field, (iii) used for other off-field purposes (e.g. domestic fuel, construction or industry), and (iv) left on the field. This dataset is the first of its kind, and can be used for multiple purposes, such as global crop modelling, including the calculation of greenhouse gas inventories, estimating crop-residue availability for biofuel production or modelling livestock feed availability.

Estimation of Agricultural Greenhouse Gas Emissions and Emission Reduction Potential of Beijing During the 14th Five-Year Plan Period Under the Background of "Carbon Peak and Neutrality"

To achieve the goal of "carbon peak and neutrality," the strict requirements for greenhouse gas (GHG) emissions control in the agricultural sector were recommended in relevant plans for Beijing during the 14th Five-Year Plan period. Through collecting agricultural activity data and calculating and screening the emission factors, the amount and emission characteristics of agricultural GHG emissions in Beijing in 2020 were estimated and set as the baseline condition. On this basis, the GHG emissions in 2025 with optimized measurements implemented, which were selected in combination with the natural conditions and planting-breeding mode of Beijing, were set as the reduction condition. The emission reduction potential and its distribution during the 14th Five-Year Plan Period were predicted simultaneously. Meanwhile, the reduction effects on the GHG emissions of optimized measurements were evaluated. In addition, relevant policy recommendations on GHG reduction were proposed accordingly. The results revealed that the total agricultural GHG emissions in Beijing were estimated to be 456000 t (CO2-eq) in 2020, primarily from sources of animal intestinal fermentation and manure management, with contribution rates of 50.7% and 26.7%, respectively. Spatially, it was mainly distributed in districts with large livestock and poultry breeding scales, such as Shunyi District, Miyun District, and Yanqing District, etc. It was predicted that in 2025, the total agricultural GHG emissions would be 349000 t (CO2-eq), and the emission reduction potential in the 14th Five-Year Plan period would be 107000 t (CO2-eq). Animal intestinal fermentation would be the emission source with the largest reduction potential (60000 tons, CO2-eq), followed by the emission source of animal manure management (37000 tons, CO2-eq). Adjusting fodder composition and optimizing manure management were analyzed to be the most effective optimized measurements for agricultural GHG emission reduction. Moreover, the emission reduction potential of CH4 would be greater than that of N2O. The emission reduction potential would be mainly distributed in Miyun District, Shunyi District, Yanqing District, Fangshan District, Tongzhou District, and other suburbs with large livestock and poultry breeding scales, accounting for more than 10% of the total emission reduction potential for each. These regions with large emission reduction potential should be prioritized and then the assessments should be extended to the whole city. The measurements were recommended as follows:① the research and promotion of technologies such as fodder optimization and the efficient treatment of manure should be strengthened, ② the scope of the combination of planting and breeding model should be expanded to promote the development of circular agriculture, and ③ relevant standards, guidelines, and specifications for green and low-carbon agriculture should be formulated, and the regulatory and policy system for synergy reduction of agricultural pollution and GHG should be developed.

Agricultural transformation towards delivering deep carbon cuts in China’s arid inland areas

Since agriculture is a main source of global greenhouse gas (GHG) emissions, reducing agricultural GHG emissions is crucial for achieving global climate goals. Nevertheless, there has been a lack of thorough and systematic assessment of the spatiotemporal distribution of agricultural GHG emissions at the county level, considering many factors such as crop and livestock products, different processes and gases, and the impact of carbon fixation. Furthermore, the potential of comprehensive technical strategies to reduce GHG emissions remains uncertain. Considering the unique attributes of agricultural development in arid areas of northwest China, this study aimed to explore long-term changes in agricultural net GHG emissions by county, product group, process, and gas and quantify the future reduction potential based on the Agricultural System-induced GreenHouse Gases INVentory (ASGHG-INV) econometric model. The results showed increasing trends in carbon emissions (CE), carbon sequestration (CS), carbon footprint (CF), crop carbon footprint per unit area (CFCF), and crop carbon footprint per unit product (CPCF) in various regions from 1991 to 2019, while there was a decreasing trend in livestock carbon footprint per unit product (LPCF). Focus on reducing GHG emissions in the crop-sector should be in Shihezi, Alaer, and Liangzhou; those of the livestock-sector should be in Xinyuan, Yecheng, Liangzhou, and Gaotai. Scenario analysis indicated that agricultural transformation could substantially reduce GHG emissions in all regions. Reducing the loss of reactive nitrogen was shown to be the most effective single strategy for reducing crop emissions. A comprehensive scheme further integrating the optimization of nitrogen fertilizer management, increasing water-saving, manure application, and straw returning measures, and using biochar and inhibitors can decrease CE, CF, CFCF, and CPCF by 22.62–43.45%, 40.55–111.60%, 41.38–111.78%, and 43.33–111.32%, respectively, increase CS by 9.07–39.97%. Optimizing forage composition was the most influential strategy for reducing livestock GHG emissions. The integrated strategy of further using forage additives, breeding low-emission varieties, and optimizing fecal management can reduce CF and LPCF by 37.32–76.42% and 40.51–78.70%, respectively. This study’s results can be a reference for developing more effective GHG emissions reduction and green transformation pathways for global dryland agriculture.

Exploring low-carbon mulching strategies for maize and wheat on-farm: Spatial responses, factors and mitigation potential

Mulching strategies - including plastic film mulching (FM) and straw mulching (SM) - can enhance crop yields while affecting multiple greenhouse gas (GHG) fluxes. However, most of currently published site-based studies only focus on a certain gas, resulting in an inability to spatially integrated understanding of changes in agricultural global warming potential (GWP) and greenhouse gas intensity (GHGI) caused by mulching across China. Thus, we developed an optimal model considering crop type, meteorology, soil and management variables by four machine learning methods, namely support vector machine, multilayer perceptron, random forest, and gradient boosting machine (GBM). Then we mapped the relative changes in yield and GHG fluxes caused by mulching strategies. The GBM model had the best simulation capability for yield and GHGs in China. Our result showed that FM increased yield in maize (25 %) and wheat (19 %), while SM respectively increased by 14 % and 11 %. Among the relative changes due to mulching strategies, yield and N2O emissions were mainly influenced by soil fertility and soil properties, CH4 uptakes and CO2 emissions were more affected by environmental factors. GWP in maize and wheat average increased by 40 % under FM, while SM decreased GWP by 14 % and 2 %, respectively. Besides, FM average increased GHGI in maize and wheat by 17 % and 9 %, and SM decreased GHGI by 22 % and 12 %, respectively. Spatially, FM reduced maize GWP on 19 % of cropland, while SM reduced maize and wheat GWP on 71 % and 64 % of cropland, respectively. Soil pH was significantly correlated with ΔGHGI in maize and wheat. Our analysis not only estimated for the first time the spatial effects of mulching strategies across China, but also systematically analyzes the agricultural carbon emission mitigation potential of mulching strategies, which promote the development of low-carbon agriculture based on locally appropriate mulching strategies.

Research on the impact of fiscal environmental protection expenditure on agricultural carbon emissions

China’s agricultural and rural greenhouse gas emissions account for about 15% of its total emissions. Studying how to reduce China’s agricultural carbon emissions (ACEs) is of great strategic significance. Based on the panel data of 31 provinces (cities) in China from 2007 to 2020, this paper empirically tests the impact of fiscal environmental protection expenditure (FEPE) on ACEs. The results reveal that: FEPE has significant negative impacts on ACEs; FEPE has a heterogeneous impact on ACEs in different regions, which shows that it has a significant impact on the eastern and central regions and provinces with relatively “high” carbon emissions, while it has no significant impact on the western regions and provinces with relatively “low” carbon emissions; Further the results of mechanism analysis show that the impact of FEPE on ACEs is mainly manifested in its inhibiting effect on agricultural diesel, fertilizer and film use of carbon emissions. In light of these findings, it is imperative for the government to ensure steady and substantial investments in environmental protection. Moreover, implementing region-specific measures is essential to effectively curbing ACEs. The findings of this study offer invaluable insights that can guide the formulation of policies aimed at effectively reducing ACEs.

Accounting for and Comparison of Greenhouse Gas (GHG) Emissions between Crop and Livestock Sectors in China

The synergistic greenhouse gas (GHG) emission reduction of the crop production (CP) and livestock farming (LF) sectors is of great significance for food security and low-carbon development, especially for China, the world leader in agricultural production. In this paper, the GHG emissions from the CP and LF sectors are accounted for and compared, and the spatial econometric model is adopted for comparative study based on the panel data from 1997 to 2021. The results show that: (1) The total amount and intensity of GHG emissions from both sectors showed obvious spatial heterogeneity and spatial dependence, and the spatial distribution pattern was relatively stable. (2) The influence of each factor on the GHG intensity and spatial characteristics of CP and LF varies widely. For the CP sector, economic development (local effect −0.29, adjacent effect +1.13), increased urbanization rate (−0.24, +0.16), agricultural structure (−0.29, +0.05), and urban-rural disparity (−0.03, +0.17) all reduce the GHG intensity of local region, while increasing the GHG intensity of its adjacent areas, signifying leakage. The economic structure (+0.06, +0.16), agricultural finance support (+0.02, +0.26), mechanization level (+0.05, +0.03), and land occupancy rate (+0.54, +0.44) all play a role in increasing the GHG intensity of CP in the local region and its adjacent areas. The disaster degree (−0.03, −0.03) also reduced the GHG intensity of CP. For the LF sector, economic structure (+0.08, +0.11), urban-rural disparity (+0.11, +0.21), agricultural development level (+0.03, +0.50), and increased land occupancy rate (+0.05, +0.01) can improve the GHG intensity of the one region and adjacent areas. Economic development (+0.03, −0.15), urbanization rate (+0.04, −0.30), agricultural structure (+0.09, −0.03), and disaster degree (+0.02, −0.06) can increase the GHG intensity of the local region while reducing the GHG intensity of adjacent areas. Based on the results, under the background of carbon peaking and carbon neutralization(dual-carbon) goals, this study first puts forward collaborative emission reduction measures for CP and LF, respectively, then further rises to sector synergy and regional synergy, and constructs the countermeasure system framework of collaborative emission reduction from three levels, to provide guidance and reference for the realization of dual goals of agricultural GHG reduction and food security.

Gas-sensing properties and first-principles comparative study of metal (Pd, Pt)-decorated MoSe2 hierarchical nanoflowers for efficient SO2 detection at room temperature

The online detection and control of concentration for agricultural greenhouse gas SO2 is an important technology to ensure normal agricultural production. This paper reports on a facile hydrothermal method to synthesis Pd-decorated and Pt-decorated MoSe2 nanomaterials, i.e. multistage flower-like structures with attached nanometallic particles and nanosheets hierarchical structures. The Pd/MoSe2 and Pt/MoSe2 hierarchical materials were characterized for the nanostructure, microscopic morphology and elemental compositions. The gas-sensing properties results show that the Pd/MoSe2 and Pt/MoSe2 nanofilm sensors have good sensitivity, stability and response rate to SO2 gas. The response values for the metal Pd and Pt decorated samples to 20 ppm SO2 were 2.04 and 3.42 times higher than those for the intrinsic MoSe2 samples at room temperature. The hierarchical flower-like structure proved to be beneficial in providing more adsorption drop points. In addition, based on the first-principles, the geometrical parameters and electronic properties of the metal-decorated modified structures were calculated to comparatively investigate the enhanced sensing mechanism of SO2 by nanoflower materials. The Pt-MoSe2 nanofilm sensor achieves a high sensitivity detection with a response value of 2.89 for low concentration (1 ppm) of SO2, which is confirming the promotion of charge transfer by metal decorating. This study suggests that Pd-MoSe2 and Pt-MoSe2 hierarchical structures may be recommended for the detection of the agricultural greenhouse gas SO2.

Assessment of sectoral greenhouse gas emission effects of biomass, fossil fuel, and (non)metallic ore utilization of the Nordic economy

AbstractIn a rare empirical approach, and considering the uniqueness of the Nordic economy, this study examines the differential effect of domestic material utilization, i.e., biomass, fossil fuel, metallic ores, and non-metallic ores on the sectoral greenhouse gas (GHG) emission, i.e., industrial, agricultural, land use, land use change and forestry (LULCF), waste management, and energy GHG emissions in the period 1990–2020. By applying competent econometric tools that accounts for potential estimation bias, the result revealed that metallic ore consumption among the Nordic countries is detrimental to the region’s environmental sustainability, more so to the region’s greening circular economy drive. This is because metallic ore utilization spurs industrial, agricultural, LULCF, waste management, and energy GHG emissions. Similarly, biomass material consumption spurs GHG emissions arising from the LULCF, waste management, and energy sector activities while fossil fuel materials spur LULCF and energy GHG emissions. However, non-metallic ores consumption provides a desirable outcome as it mitigates GHG emission with respective elasticities of ~0.06, ~0.01, and ~0.05, in the industrial, agricultural, and waste management sector activities while biomass also plays a statistically significant role of reducing agricultural GHG emission by ~0.02% when there is a percent increase in the consumption of biomass. Important policy measures are put forward following the interesting revelation from the investigation.

The Influence of Climatic Conditions and Agronomic Practices on Greenhouse Gas Emissions in a Conventional Vineyard (DOCa. Rioja, Spain)

Greenhouse gas (GHG) emissions are influenced by physical, chemical, biological, and anthropogenic factors. The objective of the study is to carry out a comprehensive analysis of the emissions of three important agricultural GHGs (CO2, N2O, and CH4) in both rows and alleys of a vineyard (1) and to understand their interactions with the agricultural operations carried out in the experimental plot, namely tillage, inter-row management, application of mineral and organic fertilizers, and irrigation and pruning, as well as the agroclimatic conditions of the plot (2). The study was conducted in a vineyard of Vitis vinifera L. cv. Tempranillo blanco in the DOCa. Rioja grape-growing region, during 2017, 2018, and 2019. Cumulative CO2 emissions were highest in 2018, reaching 934.7 ± 66.5 kg ha−1 day−1 in the alleys and 926.8 ± 76.5 kg ha−1 day−1 in the rows, in agreement with the wetter year and organic matter decomposition at the end of 2017. N2O emissions during the three-year study were mainly affected by mineral fertilizer application, with increases of 41.1 g ha−1 day−1 in the alleys and 49.3 g ha−1 day−1 in the rows during 2018, and 33.1 g ha−1 day−1 in the alleys and 39.6 g ha−1 day−1 in the rows in 2019. Regarding CH4, anaerobic soil conditions in 2018 (the year with the highest rainfall) led to the highest flux of CH4 emissions to the atmosphere, with 215.5 ± 51.0 g ha−1 day−1 in the corridors and 238.4 ± 54.9 g ha−1 day−1 in the rows. This study emphasizes the complex interplay of physical, chemical, biological, and human-related factors affecting GHG emissions in viticultural soils. Understanding these dynamics is essential for developing sustainable vineyard practices that minimize emissions and contribute to climate change mitigation.

Responses of soil CO2 efflux and microbial activity to water deficit under conventional and adaptation technology

Frequent periods of low rainfall accompanying climate change are expected to affect many aspects of agricultural production and greenhouse gas emissions. In this work, we conducted field experiments on soil CO2 efflux and soil microbial activity using two precipitation treatments and two crop management technologies. While the control treatment was exposed to natural precipitation, the reduced water availability was induced during the early stages of crop growth using rain-exclusion shelters within the water deficit treatment. We aimed to test the difference in the response to water deficit between two management technologies: conventional tillage (CT - ploughed without cover crops) and adaptation technology (AT - no-till with species rich cover crops). After a month of simulated water deficit, the soil CO2 efflux under a regime of adaptation technology was essentially the same as that under the conventional technology, and the decrease in soil CO2 efflux ranged between 22 % and 55 %. The water deficit had a technology-specific effect on microbes. While no effect on the microbial carbon under CT was observed, the water deficit decreased Cmic under AT. In contrast, the opposite pattern was observed for DHA. When a normal soil water regime was restored, CO2 efflux recovered rapidly while recovery of microbial biomass and dehydrogenase activity was more variable. Generally, the soil microbial biomass and activity recovered better under AT. The results show that while the reduction in Rs during water deficit and its recovery after the restoration of the ambient precipitation regime were not affected by the technology, the response of microbial biomass and activity to water deficit depended on the technology with better recovery under AT.

Soil carbon sequestration potential bounded by population growth, land availability, food production, and climate change

Improving soil management to enhance soil carbon sequestration (SCS)—a cost-efficient carbon dioxide (CO2) removal approach—can result in co-benefits or trade-offs. Here we address this issue by setting up a modeling framework for Switzerland that combines soil carbon (C) storage, food production and agricultural greenhouse gas (GHG) emissions. The link to food production is crucial because crop types and livestock numbers influence soil organic C (SOC) stocks, through soil C inputs from plants and manure. We estimated SCS rates for the years 2020–2050 for three scenarios, each with two variants for biochar: cover cropping (0.30 t CO2 equivalents [CO2-eq] ha−1 yr−1), biochar addition (0.36–1.8 t CO2-eq ha−1 yr−1) and agroforestry-biochar addition (2.2–2.3 t CO2-eq ha−1 yr−1). Different limiting factors (land and biomass availability, population growth) affected SCS rates and indicated that they cannot be sustained until 2100 under all scenarios (cover cropping: 0.10 t CO2-eq ha−1 yr−1 [2051–2100]; biochar addition: 0.35–1.8 t CO2-eq ha−1 yr−1; agroforestry-biochar addition: 1.0–1.7 t CO2-eq ha−1 yr−1). This information together with the associated GHG emissions is critical for planning net zero strategies and highlights the importance of integrated assessments that capture links between SCS and the food system.

Soil Greenhouse Gas Emissions in Intercropped Systems Between Melon and Cowpea

There is a need to assess alternative cropping systems for climate change mitigation. Hence, we aimed to evaluate if cowpea, a legume crop with high climate adaptability and active rhizodeposition, can reduce GHG emissions when intercropped with melon, if different intercropping patterns can affect these soil GHG emissions, and elucidate if GHG emissions are related by soil and crop properties. We compared a cowpea and melon monocultures with different melon-cowpea intercropping patterns during two crop cycles. The different melon-cowpea intercropping patterns were: row intercropping 1:1 (melon:cowpea), row intercropping 2:1 (melon:cowpea) and mixed intercropping (alternate melon/cowpea plants within the same row), receiving 30% less fertilizers than monocrops. Results showed that CO2 emission rates were higher in the row 2:1 and row 1:1 intercropping systems compared to mixed intercropping, melon monocrop and cowpea monocrop, with the lowest emissions, likely due to the highest density of both plant species, which may stimulate microbial communities. Soil N2O emission rates were not affected by crop diversification, with very low values. Soil CO2 and N2O emissions were not correlated with environmental factors, soil properties or crop yield and quality, suggesting that crop management and plant density and growth were the main factors controlling GHG emissions. When the GHG emissions were expressed on a crop production basis, the lowest values were observed in mixed intercropping, owing to higher crop production. However, the 1:1 and 2:1 cowpea intercropping systems, with the lowest overall crop production, showed higher values of GHG emissions per unit of product, compared to cowpea monocrop. Thus, intercropping systems, and mostly mixed intercropping, have the potential to contribute to sustainable agriculture by increasing land productivity, reducing the need for synthetic fertilizers and decreasing GHG emissions per unit of product. These results highlight the importance of considering both agricultural productivity and greenhouse gas emissions when designing and implementing intercropping systems.

Simulation and Prediction of Greenhouse Gas Emissions from Beef Cattle

Greenhouse gas emission is a key issue in the sustainable development of agriculture. To effectively predict the greenhouse gas emissions of beef cattle, a model is proposed based on system dynamics and greenhouse gas emission calculation methods, and a scenario is set as a ‘Straw to Beef’ project in Jilin Province. The model was built on a baseline emission scenario (feed precision: 60%, breeding environment: dry fattening farm, corn straw utilization: burning straw), with single- and comprehensive emission reduction scenarios considered, predicting trends and reduction potentials in greenhouse gas emissions from cattle breeding and straw burning in Jilin Province from 2013 to 2028, measured in CO2-eq (CO2 equivalent). The model also explored the impact of 11 controllable variables on greenhouse gas emissions. Results showed that (1) From 2013 to 2022, greenhouse gas emissions from straw burning and cattle breeding in Jilin Province increased significantly and had an annual growth rate of 6.51% in 2020. (2) Single emission reduction scenarios showed an increasing trend in greenhouse gas emissions, while comprehensive emission reduction scenarios showed a decreasing trend. Among them, the S2.2.1 scenario (feed precision: 80%, breeding environment: livestock barn manure pit, corn straw utilization: burning straw) had the strongest emission reduction ability in the single reduction scenario, the S3.2.2 scenario (feed precision: 80%, breeding environment: livestock barn manure pit, corn straw utilization: Feed-processing straw) had the strongest emission reduction ability in the comprehensive reduction scenario, reducing emissions by 5.10% and 69.24%, respectively, compared to the baseline scenario. This suggests that the comprehensive emission reduction scenarios which utilized straw resources reasonably can greatly reduce agricultural greenhouse gas emissions. (3) The optimal emission reduction scenario indicated that the higher the proportion of digestible energy in beef cattle’s total energy intake, the more perfect the fecal treatment process, and the higher the utilization rate of straw feed, the lower the greenhouse gas emissions. Therefore, to effectively reduce greenhouse gas emissions from cattle breeding and straw burning in Jilin Province, it is important to implement comprehensive emission reduction scenarios prioritizing the efficient utilization of straw resources and improving beef cattle management practices.

Carbon footprint in agriculture sector: a literature review

As the climate problem becomes more serious, controlling greenhouse gas emissions has become an overarching issue facing all countries. The agriculture sector is one of the main sources of carbon emissions. The measurement of its carbon footprint not only can quantitatively evaluate agricultural greenhouse gas emissions but also provide technical support for low-carbon agricultural construction. However, most reviews focus on the carbon footprint of manufacturing or international trade. Thus, this study selects the agriculture sector and summarizes the literature associated with the carbon footprint. First, this paper analyzes the different definitions of carbon footprint at macroscopic and microscopic levels. Then, Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis is used to summarize the advantages and disadvantages of two main accounting methods, Life Cycle Assessment (LCA) and Input-Output Analysis (IOA). Third, the research on carbon footprint in the agricultural sector is concluded and quantified using CiteSpace. Therefore, this paper gives the implications and prospects of carbon footprint in the agriculture sector. It is necessary to further agree on the definition of carbon footprint and consider other pollutants, water, and energy footprints to optimize agricultural management. Additionally, establishing a carbon footprint accounting model in line with local realities will provide scientific support for developing low-carbon agriculture.

The nexus between agricultural land use, urbanization, and greenhouse gas emissions: Novel implications from different stages of income levels

The current study establishes theoretical and empirical linkages among urbanization, economic growth, land use, and greenhouse gas (GHG) emissions. The prime objective of this article is to draw novel conclusions and policies for the different income levels of countries regarding the urbanization and agriculture sector land on environmental pollution. Employing panel data of 50 countries for the period 1990 to 2019, this study uses the lasso regression and non-parametric regression panel data methods to investigate the impacts of land use (arable, permanent pastures, and cropland), urbanization growth, and economic progress on the pollution levels. After estimating a Lasso regression to find the best auto-regressive predictive specification, we used an auto-regressive partially linear regression where each of the drivers’ effects was modelled non-parametrically. The elasticity effect of the urban population on emissions is significantly positive and sizable. In addition, the effect distribution shows a non-negligible share of observations with an elasticity higher than one. Urban population growth is a serious threat to climate change, as it seems to increase sharply CO2 emissions (although with an elasticity pace smaller than one). The elasticity effect of GDP is significantly negative, which implies that the scale of production, by triggering efficiency, can have a positive effect on emissions reduction. The results argue that agglomeration negative effects put in place by larger urban population can partly explain this finding. Overall, the study argues that urbanization growth and economic activities lead to GHG emissions, whereas the study also discusses novel implications and the role of agricultural land use apropos Sustainable Development Goals (SDGs). The empirical findings allow us to draw novel conclusions and guidelines in line with SDGs. The agricultural reforms might include irrigation and farming techniques such as spin farming, solar tube wells, tunnel farming, technology use agreements, plant double helix, etc.

Editorial: Agricultural non-point source pollution and greenhouse gas: emission, control, and management

Editorial: Agricultural non-point source pollution and greenhouse gas: emission, control, and management

Land Use Policy Recommendations——Based on Empirical Analysis of The Effect of Agricultural Land Expansion on Greenhouse Gas Emission

Agricultural activities emit about 10-12% greenhouse gases each year. Moreover, the total amount is on the rise, which can significantly contribute to global warming. To get governments to pay more attention to greenhouse gas emissions from agricultural activities, so that the necessary regulations can be implemented. This paper studies the relationship between agricultural land expansion and greenhouse gas emissions. My initial hypothesis was that ceteris paribus, the agricultural land expansion would cause a rise in greenhouse gas emissions. I obtained 25 years of data for 12 countries from the World Development Indicators Database of the World Bank. And created a panel data frame. The variables exist in it are: Total greenhouse gas emissions (kt of CO2 equivalent), Energy use (kg of oil equivalent per capita), Alternative and nuclear energy (% of total energy use), Agricultural land (% of land area), GDP per capita (current US$). In order to cope with the possible heteroscedasticity problem in the regression, several of the variables were processed logarithms. This paper used a Two-way Fixed effect model which controls fixed effects from both cross section and time. The explained variable is log (GHG emissions), and the explanatory variables are log (energy use per capita), log (GDP per capita), clean energy using rate, and percentage of agricultural land in total land. However due to the presence of multicollinearity, log (GDP per capita) was removed. This paper also tested the autocorrelation and used the Cochrane-Orcutt Iterative Process to estimate the autocorrelation coefficient to transform all variables so that solve the autocorrelation issue. The final regression model is as follows: ln(Greenhouse Gases emission)= + 1.06*ln(Energy use per capita) – 0.009*(Alternative and nuclear energy % of total energy use) + 0.0074*(Agricultural land % of land area). = . The overall F-test of this model is significant, and the individual t-tests of the coefficients of each variable are all significant. R2=92.18, adjR2=91.04. This shows that the explanatory power of the model is strong. This outcome is consistent with my initial hypothesis that agricultural land expansion does lead to an increase in greenhouse gas emissions. The other two coefficients are also consistent with our common sense. This result can help governments to decide on the planning of land use. If the current amount of energy used and the types of energy used do not change, a country develops agriculture, it will inevitably lead to more greenhouse gas emissions. More Importantly, it is not like industrial manufacture, normally there are few regulations and policies on agricultural GHG emissions. But the quantitative results of the model tell us that as agriculture expands, it is necessary for the government to implement regulations and policies on it.

A study on GHG emission assessment in agricultural areas in Sri Lanka: the case of Mahaweli H agricultural region.

Agricultural activities contribute 7% to Sri Lanka's economy and account for 20% of the national greenhouse gas (GHG) emissions. The country aims to achieve zero net emissions by 2060. This study was aimed at assessing the present state of agricultural emissions and identifying mitigation strategies. The assessment involved estimating agricultural net GHG emissions from non-mechanical sources in the Mahaweli H region, Sri Lanka, in 2018 using the Intergovernmental Panel on Climate Change (IPCC 2019) guidelines. New indicators were developed to measure emissions for major crops and livestock and used to show the flow of carbon and nitrogen. The region's agricultural emissions were estimated to be 162,318 t CO2eq y-1, of which 48% was from rice field methane (CH4) emissions, 32% from soil nitrogen oxide emissions, and 11% from livestock enteric CH4 emissions. Biomass carbon accumulation offset 16% of the total emissions. Rice crops exhibited the highest emission intensity of 4.77 t CO2eq ha-1 y-1, while coconut crop had the highest abatement potential of 15.58 t CO2eq ha-1 y-1. Approximately 1.86% of the carbon input to the agricultural system was released as carbon-containing GHG (CO2 and CH4), whereas 1.18% of the nitrogen input was released as nitrous oxide. The findings of this study suggest extensive adaptations of agricultural carbon sequestration strategies and increased nitrogen use efficiency to achieve GHG mitigation targets. The emission intensity indicators derived from this study can be used for regional agricultural land use planning to maintain designated levels of emissions and implement low-emission farms.