Livestock greenhouse gas emission and mitigation potential in China

Reducing greenhouse gas emissions in livestock farms: A resource orchestration theory perspective on total resource management

Livestock production is a major land user, consumes significant resources, and contributes 14.5 % of human-induced greenhouse gas emissions. This study applies Resource Orchestration Theory (ROT) to examine Total Resource Management (TRM) as a strategic approach to reducing greenhouse gas emissions in livestock farming. ROT emphasizes the synchronized structuring, bundling, and leveraging of resources to optimize TRM practices and enhance their effectiveness in emission mitigation. However, existing research often overlooks this synchronization and lacks insight into how green practices in one process influence others. This study analyzes the causal relationships among TRM attributes and provides actionable strategies for emission reduction. This study identifies key TRM attributes, explores their interrelationships, and highlights areas for performance improvement using a hybrid methodology combining the fuzzy Delphi method and fuzzy decision-making trial and evaluation laboratory (FDEMATEL). The Analytical Network Process validates the interrelationships derived through the FDEMATEL. The findings indicate that out of an initial set of 28 criteria identified in the literature, 20 were validated and subsequently organized under six aspects. In addition, waste valorization, livestock genetics and breeding, and land management are the causal aspects driving TRM. Energy efficiency, feed management, and stakeholder engagement, which impact overall system performance, are improved by enhancing the causal aspects. For practitioners, improvement criteria include feed additive techniques, nutrient management, manure management, and active involvement of farmers and local communities. The results provide strategies to enhance resource utilization, reduce greenhouse gas emissions, and promote sustainable livestock farming practices.

The Nonlinear Effects of Environmental Regulation on Ecological Efficiency of Animal Husbandry-Case Study of China

Developed countries with animal husbandry are confronted with the pressing issues of ensuring stable livestock product supplies while maintaining ecological sustainability. Additional research is required to ascertain whether environmental regulation can effectively facilitate the green transformation of animal husbandry and establish a harmonious equilibrium between environmental protection and economic growth. It is essential for the empirical development of environmental policies in animal husbandry, as it evaluates the impact of regulatory measures on this sector's ecological efficiency and precisely investigates the underlying mechanisms of these effects. This paper evaluates the nonlinear impact of environmental regulation policies on the ecological efficiency of animal husbandry using the super-efficiency EBM model, spatial Durbin model, and panel threshold model, which are based on panel data from 31 Chinese provinces (2010-2022). The findings indicated that: (1) The ecological efficiency and environmental regulation intensity of animal husbandry in China exhibited a fluctuating upward trend. The environmental regulation is ranked from high to low in the following order: Northeast, West, Central, and Eastern regions. Conversely, the regions with high ecological efficiency are concentrated in the Northeast and Western regions. (2) The impacts of environmental regulation on the ecological efficiency of animal husbandry were N-type nonlinear, with the extreme points being 6.322 and 9.456. Environmental regulation also produced an "inverted N" type spatial spillover effect on the ecological efficiency of animal husbandry in adjacent areas, with extreme values of 5.330 and 7.670. (3) Environmental regulation considerably enhanced the ecological efficiency of animal husbandry in the Eastern and Central regions in terms of location characteristics. The influence on the Western and Northeastern regions exhibited N-type nonlinear characteristics. (4) From 2017 to 2022, ER had an N-type nonlinear effect on animal husbandry ecological efficiency in terms of temporal heterogeneity. However, the effect was not significant from 2010 to 2016.

Identifying changes in the drivers of ecosystem services: Socioeconomic changes underlie reduced provision of pollination service

The impact of land use changes on ecosystem services (ES) or Nature's Contributions to People (NCP) is relatively well-known, but the influence of socioeconomic changes on ES remains less clear, especially at larger spatial scales. Multiple socioeconomic factors influence the demand for a service (i.e. higher economic income and human development can increase demand for ES) and the provision of such service (i.e. environmental policies and cultural relationships with nature may enhance access to ES). Such complex relationships require a multidimensional approach to understand the socioeconomic drivers of change of ES. We investigated how socioeconomic drivers affect demand, diversity and provision of crop pollination service. Our Brazil-wide assessment spans a decade (2006-17) and encompasses a period of rapid land use intensification and concentration of land ownership. Our results revealed that the replacement of small and diverse pollinator-dependent farming systems by large pollinator-dependent monocultures has led to deficits in crop pollination services, with demand increasing by 3.3% while diversity and provision have decreased by 16.1 and 22.5%, respectively. These changes are linked to increased wealth concentration and social inequality, as regions that presented concentrated land ownership and limited access to credit were associated with reduced pollination provision. Our study provided a country-wide quantitative assessment of socioeconomic drivers of change in ES to reveal an association between social inequality and reduced ES provision.

Spatiotemporal characteristics and influencing factors of non-CO2 greenhouse gas emission intensity from China's livestock sector

The livestock sector is a major source of non-CO2 greenhouse gas (GHG). As China has the world's largest livestock production, analyzing factors influencing GHG emission intensity of livestock (GEIL) is crucial for guiding its emission reduction policies. Yet, most current studies on livestock GHG focus on emission amount (GEAL) over GEIL, neglecting comprehensive utilization of spatial econometric models. Furthermore, the influencing factors mainly focus on population, economic level, urbanization, and industrial structure, while the exploration of factors such as technological innovation, consumers' age structure, and industrial agglomeration remains insufficient. This study first applied the standard deviation ellipse (SDE) model to describe the spatiotemporal evolution of GEAL and GEIL across 31 Chinese provinces from 2006 to 2022. Then, using extended STIRPAT theory, we analyzed GEIL's influencing factors with exploratory spatial data analysis (ESDA) and the geographically and temporally weighted regression (GTWR) model. The results showed that: (1) GEAL was concentrated in resource-rich grassland pastoral and grain-producing areas. Provincial GEAL trends varied, while national GEAL declined rapidly and then fluctuated slightly. Cattle, pigs, and sheep/goats contributed the most to GEAL. (2) GEIL significantly decreased nationwide and provincially, with Tibet having the highest reduction rate but still leading in GEIL. (3) GEAL followed a northeast-southwest distribution, whereas GEIL exhibited an east (slightly north) to west (slightly south) pattern. (4) Spatial analysis revealed significant GEIL clustering, with higher values in western provinces and lower in central and eastern regions. (5) Population scale, urbanization, age structure, proportion of ruminant animal production value, location quotient of livestock, employment income per capita of agricultural personnel, patent-granted intensity, and educational level in rural areas had diverse spatiotemporal impacts on GEIL across provinces. Tailored emission reduction policies and regional collaborative governance are recommended.

Methodological study on carbon sequestration accounting for emission reductions from the whole-chain utilization of livestock and poultry manure

Effective livestock manure management is crucial for carbon neutrality. Scientific accounting methods and integrated management strategies can help guide reductions in carbon emissions and promote green development. To reduce greenhouse gas emissions by livestock manure, this study analyzed current accounting systems and focused on the complete chain of "collection-treatment-storage-use-returning" of manure based on the theoretical framework of greenhouse gas emissions accounting in the IPCC 2019 Guidelines. Combined with a life cycle assessment, the accounting list and boundaries were clarified, and the whole chain of livestock and poultry manure greenhouse gas accounting methodology system was proposed. Using swine breeding as a case study, this study evaluated the carbon emission reduction and sequestration effect of the whole manure chain using a typical technology model and a typical technological framework. It predicted the carbon reduction potential and sequestration benefits of utilizing swine manure in 2025 and 2030 in four scenarios. The findings indicated that the greenhouse gas emission factor of the whole chain of the six typical swine manure utilization modes in China was -48.82-40.54 kgCO2et-1. In 2022, the net greenhouse gas emissions from swine manure in China totaled approximately 2.0 × 107 tCO2e, with manure resource utilization reducing emissions by 3.2 × 107 tCO2e. Our projections suggest that emissions from swine manure in China may range from -1.8 × 107 to 1.3 × 107 tCO2e by 2025 and from -3.1 × 107 to 4.5 × 106 tCO2e by 2030. This can help guide optimal greenhouse gas emission reduction pathways for livestock and poultry farming and aid in the formulation of policies.

Suitable fermentation temperature of forage sorghum silage increases greenhouse gas production: Exploring the relationship between temperature, microbial community, and gas production

Silage is an excellent method of feed preservation; however, carbon dioxide, methane and nitrous oxide produced during fermentation are significant sources of agricultural greenhouse gases. Therefore, determining a specific production method is crucial for reducing global warming. The effects of four temperatures (10 °C, 20 °C, 30 °C, and 40 °C) on silage quality, greenhouse gas yield and microbial community composition of forage sorghum were investigated. At 20 °C and 30 °C, the silage has a lower pH value and a higher lactic acid content, resulting in higher silage quality and higher total gas production. In the first five days of ensiling, there was a significant increase in the production of carbon dioxide, methane, and nitrous oxide. After that, the output remained relatively stable, and their production at 20 °C and 30 °C was significantly higher than that at 10 °C and 40 °C. Firmicutes and Proteobacteria were the predominant silage microorganisms at the phylum level. Under the treatment of 20 °C, 30 °C, and 40 °C, Lactobacillus had already dominated on the second day of silage. However, low temperatures under 10 °C slowed down the microbial community succession, allowing, bad microorganisms such as Chryseobacterium, Pantoea and Pseudomonas dominate the fermentation, in the early stage of ensiling, which also resulted in the highest bacterial network complexity. According to random forest and structural equation model analysis, the production of carbon dioxide, methane and nitrous oxide is mainly affected by microorganisms such as Lactobacillus, Klebsiella and Enterobacter, and temperature influences the activity of these microorganisms to mediate gas production in silage. This study helps reveal the relationship between temperature, microbial community and greenhouse gas production during silage fermentation, providing a reference for clean silage fermentation.

Comprehensive assessment of refined greenhouse gas emissions from China's livestock sector

Livestock and poultry products are an essential human food source. However, the rapid development of the livestock sector (LS) has caused it to become a significant source of greenhouse gas (GHG) emissions. Consequently, investigating the spatio-temporal characteristics and evolution of GHG emissions is crucial to facilitate the green development of the LS and achieve "peak carbon and carbon neutrality". This study combined life cycle assessment (LCA) with the IPCC Tier II method to construct a novel GHG emissions inventory. The GHG emissions of 31 provinces in China from 2000 to 2021 were calculated, and their spatio-temporal characteristics were revealed. Then, the stochastic impacts by regression on population, affluence, and technology (STIRPAT) model was used to identify the main driving factors of GHG emissions in six regions of China and explore the emission reduction potential. The results showed that GHG emissions increased and then decreased from 2000 to 2021, following a gradual and steady trend. The peak of 628.55 Mt CO2-eq was reached in 2006. The main GHG-producing segments were enteric fermentation, slaughtering and processing, and manure management, accounting for 45.39 %, 26.34 %, and 23.08 % of total GHG emissions, respectively. Overall, the center of gravity of GHG emissions in China migrated northward, with spatial aggregation observed since 2016. The high emission intensity regions were mainly located west of the "Hu Huanyong line". Economic efficiency and emissions intensity were the main drivers of GHG emissions. Under the baseline scenario, GHG emissions are not projected to peak until 2050. Therefore, urgent action is needed to promote the low-carbon green development of the LS in China. The results can serve as scientific references for the macro-prevention and control of GHG emissions, aiding strategic decision-making. Additionally, they can provide new ideas for GHG accounting in China and other countries around the world.

Carbon emissions changes of animal husbandry in China: Trends, attributions, and solutions: A spatial shift-share analysis

China is a major livestock producer confronting the dual challenges of rising demand for animal-based food consumption and decreasing carbon emissions. To effectively address these issues, it is crucial to understand the trends of carbon emissions from animal husbandry and the competitive advantages of carbon emission reduction in different regions. This study uses panel data from 31 provinces from 2004 to 2020 to investigate the contributing factors to carbon emissions and explore ways to reduce carbon intensity in animal husbandry. The analysis employs spatial shift-share analysis and the spatial Durbin model. Our findings indicate that life-cycle carbon emissions associated with animal husbandry in China decreased from 572.411 Mt CO2eq to 520.413 Mt CO2eq over time, with an average annual decline of 0.568 %. The annual contribution of output value and internal industry-mix adjustment to carbon emission growth is 22.639 MT CO2eq and 6.226 MT CO2eq, respectively. On the other hand, the annual contribution of carbon efficiency improvement to carbon emission reduction is much higher, at 36.316 MT CO2eq. However, there is significant regional heterogeneity in the spatial decomposition of the carbon efficiency change component. The Northeastern region, Northwest and along the Great Wall demonstrate neighborhood advantages in enhancing carbon efficiency. In contrast, the South China and Southwest regions rely more on local carbon efficiency advantages to reduce the carbon intensity of animal husbandry. Furthermore, the carbon intensity in local and neighboring areas can be reduced through environmental regulations and industrial agglomeration. While technical progress significantly negatively impacts carbon intensity in neighboring regions, it does not contribute to reducing the carbon intensity of local animal husbandry. The findings provide valuable insights for local governments, aiding them in recognizing the pros and cons of carbon reduction in animal husbandry and strengthening regional cooperation in emission reduction management.

Influencing factors and spatiotemporal heterogeneity of livestock greenhouse gas emission: Evidence from the Yellow River Basin of China

Livestock is one of major sources of greenhouse gas (GHG) emissions in China. Clarifying spatiotemporal characteristics of GHG emissions from livestock and exploring influencing factors can provide reference for grasping regional changes of GHG emission and formulate strategies of carbon reduction for livestock industry. However, existing literatures considered both spatial and temporal impacts and dynamic evolution trend of these factors seldomly. This paper used the life cycle assessment (LCA) method to estimate GHG emissions of livestock in 114 cities of the YRB from 2000 to 2021. On this basis, spatiotemporal heterogeneity of influencing factors was analyzed by using geographically and temporally weighted regression (GTWR) model. Finally, future evolution trend of GHG emissions from livestock was predicted by combining traditional and spatial Markov chain. Four main results were listed as follows. Firstly, GHG emission in the life cycle of livestock industry increased from 57.202 million tons (Mt) carbon dioxide equivalent (CO2e) in 2000 to 77.568 Mt CO2e in 2021. Secondly, structure of livestock industry, labor flow and mechanization were vital factors that led to increase of GHG emissions from livestock. Positive effects of labor flow and mechanization were increasing year by year, while negative effect of urbanization and positive effect of economic development were decreasing year by year. Markov chain analysis shown that probability of keeping high level of GHG emissions of livestock in the YRB unchanged were 96% (T = 1) and 90% (T = 5), and there also existed a Matthew effect. In addition, probability of level transfer of GHG emission in urban livestock was spatially dependent. Government should formulate strategies for livestock development and optimize low-carbon transformation of energy structure for livestock and poultry husbandry based on local conditions and key driving factors in the future. Meanwhile, boundaries of administrative divisions should be broken to promote reduction of GHG emissions in livestock comprehensively.