Potential and Pathways of Carbon Emission Reduction in China’s Beef Production from the Supply Chain Perspective

Abstract

Beef production is the primary contributor to greenhouse gas emissions in animal husbandry. But the carbon emission distribution, potential for carbon reduction, and pathways in the main links of the beef cattle industry chain are not yet clear. Balancing efficiency and fairness while taking tailored emission reduction paths according to local conditions is crucial in helping to achieve the low-carbon animal husbandry and “dual carbon” goals. This research adopts an industry chain perspective to assess four leading beef production regions’ carbon emissions, potential, and pathways in China from 2007 to 2021. We use life cycle assessment, the potential index which considers efficiency and fairness; the results are as follows: (1) The potential for carbon emission reduction in China’s beef industry showed an inverted U-shaped change trend from 2007 to 2021, and the average potential for carbon emission reduction in most provinces fluctuated around 0.500. (2) The main producing areas of China’s beef industry were divided into four areas of high efficiency and low fairness (Area A); high efficiency and high fairness (Area B); low efficiency and low fairness (Area C); and low efficiency and high fairness (Area D). (3) Differentiated emission reduction pathways were designed to reduce emissions, highlighting the need to implement region-specific carbon reduction policies.

1. Introduction

Since the beginning of the 21st century, global warming has become increasingly severe, and the livestock industry’s greenhouse gas emissions (GHGs) are a significant contributing factor. Steinfeld et al. (2006) pointed out that the global livestock sector emits about 7.1 billion tons of carbon dioxide equivalent (CO₂e) per year, representing 18% of the total global emissions, similar to the transportation sector [1]. Following the “dual-carbon” goal in China in 2020, the government has issued policy documents guiding the reduction in carbon emissions in animal husbandry [2,3]. In 2022, the Ministry of Agriculture and Rural Affairs released two implementation plans—one for a synergistic efficiency increase in pollution reduction and carbon emission reduction, and the other for reducing pollution and sequestering carbon in agriculture and rural areas—which put forward specific implementation strategies focusing on energy conservation, emission reduction, pollution control, variety improvement, and a reduction in methane (CH₄) gas from ruminant animal digestive systems. As large ruminant animals, beef cattle emit 2–3 times more greenhouse gases than pigs and 5–20 times more than chickens [4].

As the third largest beef producer globally, China’s beef industry contributes to GHGs mostly through animal husbandry, comprising 41% of all emissions, and its carbon emissions should not be underestimated [5,6]. With the acceleration of adjustments in residents’ dietary structures, the enormous demand for green, low-fat beef products by consumers poses a real challenge to the overall industry accounting for carbon reduction and improving efficiency overall. Meanwhile, the emergence of the first “zero-carbon” beef in China signifies the potential of achieving a zero-carbon beef industry. Balancing efficiency and fairness while taking tailored emission reduction paths according to local conditions is crucial to help achieve the low-carbon animal husbandry and “dual carbon” goals.

In recent years, researchers have been analyzing the carbon emissions from beef and related industries, as well as studying the characteristics of these emissions. Calculating carbon emissions mainly relies on the IPCC coefficient method and research data. From 2000 to 2020, emissions of greenhouse gas from livestock in China decreased by 18.29% due to improvements in animal intestinal fermentation and fecal management. Ruminant livestock account for 90% of methane emissions from animal intestines, with beef cattle accounting for over 70% [7]. The largest source in beef production is the cattle herd, accounting for 89–99% of the observed carbon footprint of the cattle farm. The emissions from intestinal fermentation account for 67–79% [8]. Beef production emits methane at a rate of 22 kg CO₂e per kilogram of carcass, representing 63% of the total emissions [9]. In the animal husbandry industry of China, there is no convergence of regions and spaces in carbon emissions [10].

China’s beef industry carbon emissions have not yet peaked [11,12]. In terms of the entire value chain, beef cattle have the highest carbon footprint, followed by lamb, pork, poultry, and eggs of livestock products in the European Union [13]. Various factors such as production methods, manure management, and technological progress have significant influences on carbon emissions [14,15,16,17]. The focus of research in the beef industry regarding carbon emissions primarily centers on calculating emissions during the breeding process. China has different resource endowments compared to other major beef-producing countries, and there is an urgent need to calculate the carbon emissions of the beef industry chain. Accurately calculating total carbon emissions and emissions from different stages in the beef industry is crucial for analyzing carbon emission reduction efforts.

Regarding research on the potential for carbon reduction in beef and related industries, the current potential for reducing carbon emissions is calculated using the input–output model, the carbon reduction potential model, the carbon reduction index, and multiplier reversal in carbon emission calculation [17,18]. In the agricultural sector, carbon emission reduction calculations are primarily conducted through the development of an index that considers principles of fairness and efficiency [19]. Many scholars mainly calculate a carbon reduction index on carbon emission efficiency. The carbon emission efficiency evaluation mainly comprehensively considers factors like labor, capital, energy consumption, and carbon emissions, incorporating carbon emissions as a non-desired output into the index system [20,21,22]. The research results show that the greenhouse gas reduction potential of most livestock mitigation solutions is less than 20% [23]. The higher the efficiency of livestock production, the smaller the potential for emission reduction [24]. The potential for reducing carbon emissions is greater in small and medium-scale breeding entities [25,26]. Reducing meat consumption has a high emission reduction potential [27].

In the process of beef production, the efficiency of carbon emissions from farming in China is relatively low, with an uneven spatial distribution [28]. The GHG per kilogram of carcass weight of beef cattle breeds are 29% lower than those of dairy cattle breeds, indicating more significant emission reduction potential [29]. We primarily focus on calculating carbon emission efficiency in the breeding link, neglecting the overall carbon emission efficiency of the industry chain, which has a relatively high proportion of GHGs. Currently, the emission reduction potential primarily relies on different breeds. Exploring the overall and regional emission reduction potential is crucial for developing various regional carbon emission reduction strategies, and this area has yet to be thoroughly investigated.

Regarding research on carbon emission reduction measures and pathways in beef and related industries, relevant scholars mainly propose carbon emission reduction measures and pathways from micro and macro perspectives. At the micro level, scholars have proposed adding substances such as biochar, fats and oils, algae, and methane inhibitors to the livestock diet. The forage undergoes ammoniation treatment. Reducing livestock numbers improves grassland quality. Scholars have proposed various methods to achieve carbon emission reduction in livestock farming [14,30,31,32,33]. Additionally, scholars have suggested the use of anaerobic fermentation systems or aerobic fermentation with additives such as biochar, calcium dihydrogen phosphate, vermicompost, and straw ash to reduce GHGs in manure management processes [34]. Furthermore, from the perspective of different-scale farmers, some scholars have emphasized the need to improve the construction and management of biogas projects in medium-to-large-scale farming operations and to implement dry–wet separation, compost maturation, and the construction of multi-stage sedimentation and fermentation tanks in small-scale farms to reduce carbon emissions [35,36]. At the macro level, government environmental regulations significantly impact carbon reduction effectiveness and low-carbon strategy progress [37,38]. Scholars have proposed incentive policies to reduce food waste, promoted low-carbon subsidy policies to encourage large-scale farmers to adopt low-carbon farming practices, and implemented intensive management on farms [9,39,40]. The above research focuses on specific technologies and overall policies to reduce carbon emissions. It aims to develop differentiated emission reduction paths for the beef industry, which has large GHG emissions, in order to formulate effective carbon emission reduction policies.

While existing research has laid the foundation for this study, there are still issues that require further investigation. Current research focuses mainly on the breeding stage; however, the carbon emissions from subsequent stages cannot be ignored, requiring research on chains’ carbon footprint. Regarding research content, the focus is mainly on calculating carbon emissions and analyzing the carbon reduction potential across various modes and varieties. The carbon reduction potential and specific reduction pathways that balance efficiency and equity need to be further considered. Based on an industry chain perspective, this article analyzes the carbon footprint of the beef industry, calculates potential carbon reduction based on efficiency and equity considerations, and formulates differential reduction pathways. This provides a scientific basis for developing and adjusting emission reduction policies in beef-producing areas with different characteristics.

2. Materials and Methods

2.1. Calculation of Carbon Emission and Data Sources

2.1.1. Calculation of Carbon Emissions in the Entire Life Cycle

This paper refers to the research conducted by Yao et al. (2017) [15], Li et al. (2022) [41], and Zhang and Yan (2022) [42], and subdivides the carbon emission process of the beef industry into six links: feed grain planting, feed grain transportation and processing, rumen fermentation, manure management system, feeding energy consumption, and product processing. This study calculated the carbon emissions of the beef industry by using the life cycle assessment method. The meanings of the alphabetical symbols in Equations (1)–(7) are shown in

Table 1. The greenhouse gas emission coefficients for each link of the beef industry.

Link	Symbol	Meaning	Numerical Value	Unit	Reference
Feed grain planting	efu1	The CO2e coefficient of corn	1.5000	t/t	Tan, 2011 [43]
Feed grain transportation and processing	efu2	The CO2e coefficient of corn	0.0102	t/t	FAO, 2006 [1]
		The CO2e coefficient of soybean	0.1013
		The CO2e coefficient of wheat	0.0319
Rumen fermentation	ef1	The CH4 emission coefficient	51.4000	kg/head/a	2006 IPCC National Greenhouse Gas Inventory Guidelines [44]
Manure management system	ef2	The CH4 emission coefficient in the north China region	2.8200	kg/head/a	Guidelines for Provincial Greenhouse Gas Inventories (Trial) [45]
		The CH4 emission coefficient in the northeast region	1.0200
		The CH4 emission coefficient in the nast China region	3.3100
		The CH4 emission coefficient in the central and south region	4.7200
		The CH4 emission coefficient in the northwest region	1.8600
	ef3	The N2O emission coefficient in the north China region	0.7940	kg/head/a
		The N2O emission coefficient in the northeast region	0.9130
		The N2O emission coefficient in the east China region	0.8460
		The N2O emission coefficient in the central and south region	0.8050
		The N2O emission coefficient in the northwest region	0.5450
Feeding energy consumption	Pricee	The electricity unit price for beef cattle farming	0.4275	¥/kW/h	“Compilation of National Agricultural Cost-Effectiveness Data”, ”China Energy Statistical Yearbook” [46]
	Efe	The CO2 emission coefficient of electricity consumption	0.9734	t/MWh
	Pricec	The coal unit price for beef cattle farming	800.00	¥/t
	Efc	The CO2 emission coefficient of coal consumption	1.9800	t/t
Product processing	MJ	The energy consumption coefficient for beef slaughter and processing	4.3700	MJ/kg	Yao et al., 2017 [15]
	e	The heat value of one kilowatt-hour (kWh) of electricity	3.6000	MJ
Other coefficients	ghp1	The global warming potential value of CH4	21.0000	——	Sun et al., 2010 [47] 2006 IPCC National Greenhouse Gas Inventory Guidelines [44]
	ghp2	The global warming potential value of N2O	310.0000	——
	etpf	The conversion of CO2e to standard carbon coefficient	0.2728	——

Note: The average CH₄ emissions from water buffaloes and yellow cattle are used for beef cattle.

.

Feed grain planting link: Feed for beef cattle includes energy and protein feed. Energy feed mainly includes corn, wheat bran, etc. Protein feed mainly refers to soybean meal, etc. By-products of soybeans and wheat were excluded from the accounting process. Only the carbon emissions from corn planting of beef cattle feed were considered. Cpit represents CO₂e (10,000 tons) of beef cattle feed grain planting in region i of year t, and the formula is as follows:

$$C{p}_{it}={\displaystyle {\sum }_{\mu =1}^n{Q}_{it}\times m_{it}\times r_u\times e{f}_{u1}}$$

(1)

where Q_it represents beef production in region i and in year t. mit represents the beef consumption coefficient in region i of year t; it is the proportion of cattle consumption per head to the primary product output. r_u represents the ratio of u kinds of grains in the formulation of beef cattle feed. efu1 represents the CO₂e emission factor for corn cultivation in feed production.

Feed grain transportation and processing link: Raw materials like corn, soybeans, and wheat need to undergo a series of processes including drying, screening, transportation, crushing, mixing, etc., to obtain feed for beef cattle consumption. The GHG generated during this process needs to be included in the calculation scope. Cg_it represents the CO₂e (10,000 tons) from the transportation and processing link of beef cattle feed in region i, in year t; the formula is as follows:

$$C{g}_{it}={\displaystyle {\sum }_{\mu =1}^n{Q}_{it}\times m_{it}\times r_u}\times e{f}_{u2}\times i_u$$

(2)

where ef_u2 represents the CO₂e emission factor for the transportation of the feed grains corn, soybean, and wheat. i_u represents the grain allocation coefficient.

Rumen fermentation link: Beef cattle produce a significant amount of CH₄, 25 times the equal volume of carbon dioxide, which is converted into CO₂ at a certain ratio. Ce_it represents the CO₂e (10,000 tons) from the rumen fermentation link of beef cattle in region i of year t. The formula is as follows:

$$C{\mathrm{e}}_{\mathrm{it}}=ap{p}_{it}\times e{f}_1\times gh{p}_1$$

(3)

where app_it represents the average annual rearing amount of beef cattle in region i of year t. ef₁ represents the coefficient for methane emissions resulting from rumen fermentation in beef cattle. ghp₁ represents the global warming potential value of CH₄.

Manure management system link: Beef cattle manure generates CH₄ gas mainly under anaerobic conditions and produces N₂O gas mainly under aerobic conditions, converting them to CO₂ emissions. Cm_it represents the CO₂e (10,000 tons) from the manure management system link in region i and in year t. The formula is as follows:

$$C{m}_{it}=ap{p}_{it}\times e{f}_2\times gh{p}_1+ap{p}_{it}\times e{f}_3\times gh{p}_2$$

(4)

where ef₂ represents the emission coefficient of N₂O from the manure management system. ef₃ represents the emission coefficient of CH₄ from the same system. ghp₂ represents the global warming potential value of N₂O.

Feeding energy consumption link: Large energy consumption is required during the beef cattle feeding process, such as barn heating, ventilation for heat dissipation, production lighting, and manure treatment, all of which consume electricity, coal, and other resources, directly or indirectly resulting in GHGs. Cd_it represents the CO₂ emission equivalent (10,000 tons) from the feeding energy consumption link in region i and year t. The formula is as follows:

$$C{d}_{it}=ap{p}_{it}\times {\displaystyle \frac{{ }_{{{\displaystyle \cos t}}_e}}{pric{e}_e}}\times e{f}_e+ap{p}_{it}\times {\displaystyle \frac{{ }_{{{\displaystyle \cos t}}_c}}{pric{e}_c}}\times e{f}_c$$

(5)

where cost_e represents the electricity cost for beef cattle farming. price_e represents the unit electricity price of beef cattle farming. ef_e represents the CO₂ emission coefficient of electricity consumption. price_c represents the unit price of coal for beef cattle farming. ef_c represents the CO₂ emission coefficient associated with coal consumption.

Product processing link: Before beef is sold in commercial form, it needs to undergo processes such as cooling, sterilization, packaging, etc., and the energy consumption during this period also needs to be included within the system boundary. Cb_it represents the CO₂ emission equivalent (10,000 tons) from the product processing stage of beef in region i and in year t. The formula is as follows:

$$C{b}_{it}=Q_{it}\times {\displaystyle \frac{MJ}{e}}\times e{f}_e$$

(6)

where MJ represents the energy consumption coefficient.

Total standard CO₂ emissions: Based on the calculations from Equations (1) to (6), multiplying by the equivalent CO₂ conversion standard carbon coefficient yielded the standard carbon emissions. C_it represents the CO₂ emission equivalent (10,000 tons) of the full life cycle in region i during year t. The formula is as follows:

$$C_{it}={\displaystyle {\sum }_{\mu =1}^n(C{p}_{it}+C{g}_{it}}+C{e}_{it}+C{m}_{it}+C{d}_{it}+C{b}_{it})\times e_{tpf}$$

(7)

where e_tpf represents the equivalent CO₂ conversion standard carbon coefficient.

2.1.2. Data Sources

The data utilized in this study were acquired from the following sources: the “China Statistical Yearbook”, the “China Rural Statistical Yearbook”, the “China Animal Husbandry and Veterinary Yearbook”, and the Bric database. The carbon emissions were calculated by relying on the relevant literature by Li et al. (2022) [41], the “2006 IPCC National Greenhouse Gas Inventory Guidelines”, and the “Guidelines for Provincial Greenhouse Gas Inventories (Trial)”. Some missing data were processed using linear interpolation.

The CO₂ equivalent emission coefficients for feed grain planting and processing, the CH₄ and N₂O emission coefficients for rumen fermentation and manure management systems in beef cattle breeding, the energy consumption for beef cattle farming, slaughter, and processing, and other coefficients are shown in Table 1.

2.2. Model for Calculating Potential Reduction in Carbon Emissions

The potential for carbon reduction in the beef industry lies in its capacity to significantly decrease CO₂ emissions, taking into account the resource availability and production conditions of the primary beef production regions in China. This potential should consider fairness and efficiency. Referencing the studies by Shi et al. (2023) [48] and Li et al. (2020) [49], considering the coordination of fairness and efficiency, the Carbon Abatement Capacity Index (CACI) reflects China’s beef industry’s potential for carbon reduction, where a more significant value indicates a greater reduction potential. The formula is as follows:

$$CAC{I}_{\begin{array}{l}it\\ \end{array}}=\theta \times Equit{y}_{it}+(1-\theta )\times Efficienc{y}_{it}$$

(8)

where θ represents the weight, with a value of 0.5. Equity_it represents the emission reduction fairness index in region i of year t. Efficiency_it represents the emission reduction efficiency index in region i of year t.

Equityit is mainly determined by the CO₂ emissions per capita and the total output value per capita of the beef industry weighted equally. The formula is as follows:

$$Equit{y}_{it}=1/2PD+1/2PC$$

(9)

where PD represents the CO₂ emissions per capita from the beef industry. PC represents the beef industry’s total output value per capita.

Efficiency_it is mainly determined by the CO₂ emission intensity and CO₂ emission shadow price. The formula is as follows:

$$Efficienc{y}_{it}=1/2CP+1/2PB$$

(10)

where CP represents the CO₂ emission intensity. PB represents the CO₂ emission shadow price. Both are reverse processed and given equal weight.

PB is mainly determined by the marginal virtual income expected output. Virtual prices of expected and unexpected outputs are reverse processed. The formula is as follows:

$$PB=P^g\times {\displaystyle \frac{u^b}{u^g}}$$

(11)

where P^g represents the expected output price. U^b and u^g represents virtual prices of expected non-expected output and unexpected outputs, respectively.

u^b and u^g were calculated by the following formula. The above indicators were all standardized through “MinMax” before being substituted into the formula for calculation.

$$\begin{array}{l}\max u^g{y}_0^g-v{x}_0-u^{\mathrm{b}}{y}_0^b\\ s.t.\{\begin{array}{l}{u}^g{Y}^g-vX-u^b{Y}^b\le 0\\ v\ge {\displaystyle \frac{1}{m}}\left[1/x_o\right]\\ u^y\ge {\displaystyle \frac{1+u^g{y}_0^g-v{x}_o-u^b{y}_0^b}{s}}\left[1/y_0^g\right]\\ u^b\ge {\displaystyle \frac{1+u^g{y}_0^g-v{x}_o-u^b{y}_0^b}{s}}\left[1/y_0^b\right]\end{array}\\ \end{array}$$

(12)

where X, y^g, and Y_b are the defining matrices; v represents the antithetic variable of the non-expected output super-efficiency SBM model, representing the virtual prices of inputs.

2.3. Variable Declaration

2.3.1. Regional Selection

This research took the leading beef production areas as the research area. According to the “National Layout Planning of Advantageous Regions for Beef Cattle (2008–2015)”, the leading beef production areas are national key development areas and accounted for 85.07% of the total in 2021. They can represent the overall development level of China. The leading beef production areas were divided into four regions: central plains, northeast, northwest, and southwest (Figure 1). The four main production areas included 17 beef-producing provinces. The central plains region included Hebei, Shandong, Henan, and Anhui; the northeast region included Jilin, Heilongjiang, Liaoning, and Inner Mongolia; the northwest region included Xinjiang, Gansu, Shanxi, and Ningxia; the southwest region included Sichuan, Chongqing, Yunnan, Guizhou, and Guangxi. In the Central plains and northeast, large-scale house feeding is mainly used. The northwest and southwest mainly focus on grassland free-range farming. Where the map used Map Approval Number GS (2019) 1822 (Monitored by the Ministry of Natural Resources), the base map was unaltered, and did not include data from Hong Kong, Macao, and Taiwan.

2.3.2. Indicator Selection

The calculation of carbon emission reduction potential mainly involved four categories of indicators: CO₂ emissions per capita, gross domestic product per capita, CO₂ emission intensity, and CO₂ emission shadow price. The CO₂ emission shadow price mainly involved three categories of indicators: input, expected output, and non-expected output. Input indicators include labor input, machinery input, capital input, etc. The variables selected were as shown in

Table 2. Variables selected.

Indicator	Variables Selected	References
CO2 emission per capita	Ratio of CO2 emissions to the quantity of individuals employed in the beef industry	Wu et al., 2015 [50] Li et al., 2020 [51]
Gross domestic product per capita	Ratio of output value to the quantity of individuals employed in the beef industry
CO2 emission intensity	Ratio of total CO2 emissions to the total output value in the beef industry
CO2 emission shadow price	Labor input—employment in the beef industry (10,000 person) Machinery input—the total mechanical power (Mw) Capital input—fixed asset investment in the beef industry (CNY 100 million)	Shang et al., 2023 [52] Li et al., 2022 [41] Zhang et al., 2020 [21]
	Expected output: total output value of beef (CNY 100 million)
	Unexpected output: carbon emissions of the beef industry chain (10,000 tons)

. The input–output indicators were adjusted to the base period of 2007. Labor input, machinery input, and capital input indicators were adjusted using the agricultural production input price index. The expected total beef output was adjusted according to the meat consumption price index.

3. Results

3.1. Analysis of Carbon Emission Calculation Results in the Beef Industry

3.1.1. Proportion of Carbon Emissions in Different Emission Stages

The industry carbon emissions involved planting, the transportation and processing of feed grain, energy consumption in breeding, rumen fermentation, manure management systems, and product processing. The carbon emissions of the main processes are shown in Figure 2. The average carbon emissions of various processes in the beef industry from 2007 to 2021, sorted by percentage from largest to smallest, were as follows: rumen fermentation phase (66.90%), manure management phase (19.32%), product processing phase (8.48%), feed grain planting phase (3.66%), energy consumption in breeding phase (1.50%), and feed grain transportation and processing phase (0.13%).

3.1.2. Time Evolution Trend of Carbon Emissions

As illustrated in Figure 2, the carbon emissions stemming from the beef industry showed a fluctuating upward trend. From 2007 to 2021, the carbon emissions increased from 3.54 to 5.29 Mt, representing a growth rate of 2.91%. The carbon emission change is divided into four stages: 2007–2010, 2011–2016, 2017–2018, and 2019–2021. It showed a process of “rapid increase–fluctuating growth–slight decrease–slow growth”. The average annual growth rates for these four stages were 9.5%, 2.03%, −0.08%, and 5.10%, respectively.

3.1.3. Evolution Trend in Regional Distribution of Carbon Emission

The regional carbon emissions were divided into the categories of 0–1, 1–4, 4–7, and 7–13 Mt. From the perspective of regional changes, the emissions in areas ranging from 0 to 1 Mt showed a trend from strip-like to sporadic, eventually disappearing. In 2007, the group of Ningxia and Shaanxi in the northwest and Chongqing and Guizhou in the southwest was reduced to Ningxia alone in the northwest in 2012 and disappeared from this category altogether until 2021, and emissions in the 1–4 Mt range showed a slow movement from the western–central production region to the central–-northeast production region.

In 2007, the areas were concentrated in the Xinjiang and Gansu regions of the northwest production region, the Yunnan region of the southwest production area, and the Hebei and Anhui regions of the central plains production region. In 2012 and 2017, there was a diffusion trend towards the northeast. In 2021, they were concentrated in the central plains and northeast production areas. In the 4–7 Mt emissions area, there was a feature of shifting from the northern to the central region in 2007, mainly concentrated in the northeast production areas of Inner Mongolia, Heilongjiang, and Jilin. In 2012, it was expanded to include provinces such as Gansu, Liaoning, and Shandong. By 2021, the regional scope had shifted southwards, mainly concentrated in the Hebei, Henan, and Shandong areas of the central plains production region. The regional range of the 7–13 Mt emissions gradually expanded from 2007 to 2021. In 2007, the areas were concentrated in Henan Province of the central plains production region and Sichuan Province of the southwest region, gradually spreading southward in 2012 and 2017, and further expanding to the northern region in 2021, mainly located in Xinjiang of the northwest production region, Inner Mongolia of the northeast production region, and Sichuan, Yunnan, and Guizhou in the southwest production region (Figure 3).

3.1.4. Changing Trend of Carbon Emission Growth Rate

The areas with negative growth rates of carbon emissions gradually disappeared, while the areas with medium to high growth rates increased. The high-growth-rate areas decreased and dispersed gradually. These changes categorize the regions based on the growth rate ranges of carbon emissions: −50–0%, 0–5%, 5–10%, and 10–130%. Specifically, regions with negative growth (−50–0%) experienced less–more–less fluctuations. They shifted from the northwest and northeast production regions to the central and southwest production areas, and by 2020–2021, negative growth regions disappeared nearly. The number of regions with low growth (0–5%) followed a similar pattern. The widely distributed periods were mainly concentrated in 2012–2013 and 2017–2018. In 2012–2013, low-growth areas including 10 provinces were spread across the northwest, northeast, central, and southwest areas. By 2017–2018, this decreased to six provinces. The medium-to-high-growth areas (5–10%) showed a trend of spreading from the northeast and North China to the northeast, North China, and southwest. Over the first three stages, moderate-to-high-growth regions remained steadily declining. However, by the 2020–2021 stage, they began to increase gradually. The high-speed growth regions were initially concentrated in the central and southern regions in 2007–2008, decreased, and became mainly concentrated in the northwest and northeast production regions by 2020–2021 (Figure 4).

3.2. Analysis of Carbon Emission Potential of the Beef Industry

3.2.1. Potential Carbon Emission Reductions Overall

According to the carbon emission reduction potential index model, the reduction potential of the four major beef-producing regions from 2007 to 2021 was calculated with a focus on both equity and efficiency. The specific results are depicted in Figure 5.

In terms of temporal changes, the reduction potential shows a reverse U-shaped trend, with relatively small differences between years. It is segmented into three stages of fluctuation. The first stage showed a continuous growth trend from 2007 to 2010, increasing from 0.413 to 0.513, at an average annual growth rate of 7.46%. The second stage was relatively stable from 2011 to 2018, with the potential value fluctuating between 0.493 and 0.526. The third stage showed a downward trend in carbon emission reduction potential from 2019 to 2021, with an average annual decrease rate of 8.68%.

In terms of regional distribution, the potential level of carbon emission presented a high-to-low pattern in the following order: southwest production region, northeast production region, northwest production region, and central plains production region. Among these, Gansu province had the highest emission reduction potential, with an average potential value of 0.605. The carbon emission reduction potential of Hebei, Henan, and Anhui fluctuated between 0.376 and 0.424, indicating a relatively small space for carbon emission reduction. The emission reduction potential index of other provinces fluctuated around 0.500.

3.2.2. Carbon Reduction Potential of Spatial Differentiation Characteristics

The representative years of 2007, 2012, 2017, and 2021 were selected as time nodes, and the method of “natural break point” was adopted. With reference to Yan and Zhang (2023) [28], they were divided into low-potential areas [0.000, 0.500], medium-potential areas (0.500, 0.600], and high-potential areas (0.600, 1.500] to draw the spatial distribution characteristics of carbon emission reduction potential (Figure 6).

In 2007, the reduction potential of carbon emission in the leading beef-producing areas of China was at a medium-to-low level. The high-potential areas were primarily situated in Guangxi Province of the southwestern production region; the medium-potential areas were primarily situated in the provinces of Inner Mongolia, Heilongjiang, and Liaoning in the northeastern production region and Gansu Province of the northwestern production region. The low-potential areas were mainly distributed in the provinces of Hebei, Shandong, Henan, and Anhui in the central plains production region; the provinces of Xinjiang, Shaanxi, and Ningxia regions in the northwestern production region; and the provinces of Sichuan, Chongqing, Guizhou, and Yunnan in the southwestern production region.

In 2012, the high- and-medium-potential areas showed an upward trend. The number of high-potential areas increased to four provinces of Gansu, Sichuan, Yunnan, and Chongqing, primarily in the southwestern production region. The number of medium-potential areas increased to five provinces, mainly in the northwestern and northeastern production regions. The low-potential areas were the provinces of Hebei, Shandong, Henan, and Anhui, which were located in the central production region.

In 2017, there was an increase in the number of areas with medium potential for carbon emission reduction. There were still three high-potential areas including the provinces of Heilongjiang, Inner Mongolia, and Sichuan. Compared to 2012, the high-potential areas had begun to shift to the northern regions. The medium emission reduction potential areas increased to six provinces, mainly in the northeastern, central, and northwestern production regions. Shandong Province, which was at a low potential level, rose to a medium potential level.

In 2021, the carbon emission reduction potential was low. The areas with high potential for reducing carbon emissions had vanished. From 2017 to 2021, the quantity of provinces with medium potential descended from six to four, while the provinces with low potential increased from eight to thirteen.

3.2.3. Regional Difference Classification in Carbon Emission Reduction Potential

In order to achieve precision in emission reduction, fairness and efficiency were taken into consideration. Based on the average results of the fairness and efficiency index calculations for each province, if a province’s carbon emission efficiency index was higher than the average, it was considered to have high emission efficiency; conversely, it was considered to have low efficiency. Similarly, if a province’s carbon emission fairness index was higher than the average fairness index, it was considered to have high emission fairness; conversely, it was considered to have low fairness. The average efficiency index for carbon emissions from 2007 to 2021 was 0.618, and the average fairness index for carbon emissions was 0.351. The four leading beef cattle production regions were categorized into four distinct groups: “high efficiency, low fairness”, “high efficiency, high fairness”, “low efficiency, low fairness”, and “low efficiency, high fairness”. Specific classification results are shown in Figure 7.

Areas with high efficiency and low fairness (hereinafter referred to as Area A) included Ningxia Province in the northwest production region and the provinces of Yunnan, Guizhou, and Guangxi in the southwest production region, with their fairness index for emission reduction being 0.277, 0.292, 0.261, and 0.305, lower than the average levels of 0.074, 0.059, 0.090, and 0.046, respectively. Their efficiency indexes for emission reduction were 0.626, 0.763, 0.695, and 0.639, higher than the national average levels of 0.007, 0.144, 0.076, and 0.020, respectively.

Areas with high efficiency and high fairness (hereinafter referred to as Area B) included Inner Mongolia province in the northeast production region, Gansu province in the northwest production region, and the provinces of Sichuan and Chongqing in southwestern production region. The reduction potential was comparatively high, mainly depending on carbon emissions per capita and high carbon emission intensity. The average carbon emissions per capita in the four provinces were 13.778, 14.927, 14.984, and 12.293 tons, exceeding the national average by 3.912, 5.061, 5.118, and 2.427 tons, respectively. The carbon emission intensity averaged 6.337, 13.717, 8.634, and 6.991 tons per CNY 10,000, respectively, exceeding the national average by 0.431, 7.811, 2.728, and 1.085 tons per CNY 10,000.

Areas with low efficiency and low fairness (hereinafter referred to as Area C) included the provinces of Hebei, Henan, and Anhui in the central plains production region, Jilin Province in the northeastern production region, and Shanxi Province in the northwestern production region. The main features of these areas were that both the carbon emission fairness and efficiency indices were below average, mainly due to the low carbon emissions per capita and the low carbon emission intensity. The carbon emissions per capita in five provinces were 4.528, 6.616, 5.462, 8.305, and 6.592 tons, lower than the average of 5.338, 3.25, 4.404, 1.561, and 3.274 tons, respectively. The carbon emission intensity averaged 2.125, 3.368, 3.566, 3.665, and 3.964 tons per CNY 10,000, lower than the national average of 3.781, 2.538, 2.34, 2.241, and 1.942 tons per CNY 10,000, respectively.

Areas with low efficiency and high fairness (hereinafter referred to as Area D) included Shandong province in the central plains production region, the provinces of Heilongjiang and Liaoning in the northeastern production region, and Xinjiang Province in the northwestern production region. They had relatively high-equity indices and low-efficiency indices, mainly depending on factors such as the output value per capita and the carbon emission intensity. The output value per capita in the four provinces was CNY 24.02 thousand, CNY 32.34 thousand, CNY 28.59 thousand, and CNY 25.73 thousand, higher than the national average of CNY 4.83 thousand, CNY 13.15 thousand, CNY 9.4 thousand, and CNY 6.54 thousand, respectively. The carbon emission intensity was 4.294, 3.653, 3.252, and 4.319 tons per CNY 10,000, lower than the national average of 1.612, 2.253, 2.654, and 1.587 tons per CNY 10,000, respectively.

4. Discussion

4.1. The Changing Trend of Carbon Emissions

The carbon emissions from the beef industry breeding phase are the largest. The majority of emissions, totaling 86.22% of the overall amount, are attributed to the enteric fermentation phase (66.90%) and the manure management phase (19.32%). This finding is in line with the carbon emission trend and results of the livestock and dairy cattle industries studied by Li et al. (2022) [41,53].

Regarding the temporal trend, the period of rapid increase in carbon emissions was from 2007 to 2010. During this period, China’s pig industry was impacted by blue ear disease in 2006, leading to a rapid decrease in the pig population by 14.647 million heads compared to 2005. People were increasingly inclined to choose beef over pork for their health considerations. Simultaneously, the price of pork rose rapidly in 2007, reaching 21.35 CNY/kg, narrowing the price gap between beef and pork and increasing rational consumers’ beef consumption [54], thereby driving the increase in beef cattle farming. As a substitute for pork, the quantity of beef cattle increased from 45.878 million heads in 2007 to 67.389 million heads in 2010, leading to a sharp rise in carbon emissions.

From 2011 to 2016, carbon emissions experienced fluctuating growth. During this period, changes in urbanization and the household registration system, as well as the formation of large economic circles, led to a decrease in beef cattle stocks. Additionally, the issuance of the No. 1 Central Document in 2012 proposed the standardization of beef cattle production in major counties and the construction of original seed farms, accelerating the transformation and upgrade of the industry, as well as improving its scale, which contributed to the slower growth in carbon emissions during this period compared to the previous one.

Carbon emissions experienced a rapid decline from 2017 to 2018. During this period, carbon emissions decreased by 11.45%, exhibiting a precipitous decline. The main reason for this is the implementation of the “grain to feed” policy in 2015. In 2017, the beef industry entered a critical period of transformation. In the grain-to-feed-conversion areas and poverty-stricken counties, the amount of beef cattle farming increased slightly, while small-scale farming continued to decline. The trend towards large-scale farming became more apparent, leading to decreased carbon emissions.

From 2019 to 2021, an increase in carbon emissions was observed. During this period, the emissions increased from 4.4754 Mt to 5.3377 Mt CO₂e. On the one hand, influenced by African swine fever in 2019, pork consumption decreased, leading to a surge in demand for beef as a substitute for pork, which increased carbon emissions. On the other hand, the government requirements for environmental protection policies during this period to reduce carbon emissions gradually increased, guiding animal husbandry toward a greener, more circular, and low-carbon direction, resulting in a slow growth in carbon emissions.

4.2. Carbon Emission Reduction Potential Level and Regional Differences

The potential of carbon emission is relatively stable, showing a slight increasing trend. The potential shows an inverted “U” shape. Until 2019, Chinese government focused on reducing the impact of pollutant emissions on the surrounding environment and land, with less emphasis on GHGs. In 2020, China proposed the “dual carbon” goal and implemented a series of policies and plans aimed at reducing carbon emissions [2,55]. The variety of policy tools also became increasingly abundant, and the implementation of strict carbon emission standards was effective, leading to a decrease in the potential.

In terms of regional distribution, the carbon reduction potential presents a pattern of “southwest production area > northeast production area > northwest production area > central plains production area” in descending order. This indicates that differences in breeding conditions, breeding levels, and other factors will result in variations in the carbon reduction potential across different production areas. The regional differences in carbon reduction potential are related to regional policy differences, land resource endowments, and the degree of livestock scale intensification.

From the perspective of spatial differentiation, there is a gradient difference in the carbon reduction potential, showing an evolution of the carbon reduction potential pattern from “concentration of medium-and-low-value areas, dispersion of high-value areas” to “concentration of medium-and-high-value areas, dispersion of low-value areas” and then to “concentration of medium-and-low-value areas”.

In 2007, the carbon reduction potential was generally at a medium-to-low level. The main reason for this was that the beef industry was in a stage of industrial adjustment and development during the “11th Five-Year Plan” period, with extensive development, low levels of breed specialization, and insufficient scale. The foundation for the development of low-carbon industries was relatively weak.

In 2012, the carbon reduction potential showed high- and-medium-potential regions on the rise. The proportion of high-level and medium-level regions was relatively large, possibly due to the acceleration of small-scale household retirement, insufficient momentum for the growth of large-scale farms, insufficient cattle sources, and factors such as rising costs of land, labor, environmental protection, and feed, leading to a loss of carbon emission efficiency [28].

In 2017, the carbon reduction potential showed an increase in medium-potential regions. The number of provinces with medium potential levels further increased, mainly benefiting from the promulgation of documents such as the “Comprehensive Work Plan for Energy Conservation and Emission Reduction in the 13th Five-Year Plan” and the “2017 Work Plan for Promoting Green Development of Agriculture through Agricultural Mechanization”, as well as the fact that the beef industry entered a period of transformation and arduous battle in 2017, with technological advancements in beef cattle genetic breeding, feed nutrition, and other aspects.

The leading beef production region in 2021 was at a low level of carbon emission reduction potential. From the “11th Five-Year Plan”, proposing to reduce energy intensity, to the “14th Five-Year Plan”, setting emission reduction targets and the 2030 peak carbon emission target, the government has gradually increased its climate action intensity, continuously promoting the synergy of energy conservation, emission reduction, and carbon reduction work, prompting various industries including the beef industry to reduce energy consumption and CO₂ emissions continuously.

4.3. Emission Reduction Paths in Different Regions

Li et al. (2020) [49] designed a carbon emission reduction path for agriculture. According to their design and considering the regional differences and path feasibility of the beef industry, carbon emission reduction for the chain is realized under different emission reduction paths. The government should formulate relevant policies according to local conditions, focusing on supporting provinces in the low-fairness and low-efficiency areas (Area C) and avoiding the one-size-fits-all phenomenon. In order to improve the carbon emission efficiency of C regions and achieve carbon emission reduction, it is crucial to establish a regional mechanism for sharing the responsibility of reducing emissions and a system for compensating emission reductions for different livestock breeds. So, the provinces in Area C enter Area A; that is, the carbon reduction path of C→A is realized.

Area A is currently considered the more ideal area, primarily due to the extensive production methods in the leading beef-producing region, such as the provinces of Guizhou and Yunnan in the southwest. The low utilization of manure resources has led to higher carbon emission intensity compared to the national average. However, the relatively low level of development and scale of the beef industry in this area result in lower emission risk, keeping the carbon emission shadow price relatively low.

Area B is primarily driven by high carbon emissions per capita and carbon emission intensity. On the one hand, this is mainly due to the stock of beef cattle in the area. In 2021, the stock of beef cattle in Inner Mongolia, Gansu, Sichuan, and Chongqing was 5.859 million heads, 4.801 million heads, 5.245 million heads, and 930,000 heads, holding the 3rd, 7th, 5th, and 22nd positions in China, leading to higher carbon emissions. On the other hand, the high carbon emissions of beef industry output value per capita are related to the higher development level of the beef industry. The high carbon emission reduction fairness index and efficiency index in this area indicate a substantial potential for emission reduction. Strategies for emission reduction in these regions include implementing grassland protection techniques to reduce overgrazing and feed consumption [56,57] and cultivating high-quality forage species to increase grassland coverage and utilize grassland carbon sinks [58]. All of the above strategies can realize the carbon reduction path B→A.

In Area C, the issue of carbon emission solidification is more severe than that of fairness solidification. As a result, the focus of regional carbon reduction should be on this area, which is mainly influenced by the lower carbon emissions per capita and higher carbon emission shadow prices. Compared to high-efficiency and low-fairness areas and high-efficiency and moderate-fairness areas, these areas have a higher degree of industrial scale, relying on housed feeding, and are influenced by a larger permanent population. All lead to lower carbon emissions per capita. However, the high industrial scale also leads to higher carbon emission risk and greater difficulty in emission reduction. We can improve feed efficiency through technology promotion and increase the use of straw ammonia treatment measures to decrease carbon emissions per unit [59]. The above measures can enhance the efficiency of carbon reduction effectively, thereby achieving the path of C→A.

Areas D’s relatively high beef production value per capita and carbon emissions per capita determine its relatively higher fairness index. The higher carbon emission shadow price also leads to greater difficulty in emission reduction, indicating lower efficiency. In 2021, the beef cattle production provinces in Area D ranked among the top ten nationwide, with high industrial scale and high stocking density. This means that some regions have higher carbon reduction investment levels under equal investment conditions. The carbon emissions per capita and beef cattle production value per capita in this area are significantly higher than those in Area C. Strategies for emission reduction in this region include improving cattle manure management, increasing the efficiency of back-end manure utilization, and effective composting [35]. This may lead to the carbon reduction path D→B→A.

4.4. Carbon Reduction by Different Regional Emission Reduction Paths

In various stages of the beef industry in China from 2007 to 2021, the highest carbon emissions came from the enteric fermentation and fecal management stages, followed by the product processing stage, feed grain planting stage, and feed energy consumption stage, with the lowest emissions coming from the feed grain transportation and processing stage. Thus, it is important to concentrate on the carbon emissions produced by beef cattle excretion.

Based on Figure 7, we designed an implementation pathway for carbon emission reduction that takes both into account. Using the carbon emissions from China’s beef cattle industry in 2021 as the base scenario, predictions and assessments have been made for the development potential in 2025 and 2030, with different carbon reduction measures shown in

Table 3. Carbon emission reduction measures and applicable regions in different stages of the beef industry.

Links	Measure	Expected Effect	Zone of Application Resources	References
Planting link	(1) Improve the self-sufficiency rate of silage corn	Reduce greenhouse gases by 16%.	All regions	Huang et al., 2021 [60]
	(2) Grassland improvement	The restorative carbon sequestration potential of degraded grassland can reach an average of 31.58 tons per hectare for grassland and 34.26 tons per hectare for alpine meadow grassland.	Degraded grassland; degraded grassland of alpine meadow	Sun, 2021 [58]
Breeding link	(3) Improve nutrition of ruminants by ammoniating straw	Reduce CH4 by 15–21%	All regions	Benchaar et al., 2001 [61]
	(4) In high-concentrate and high-roughage diets for beef cattle, 200 mg/kg DM of 3-NOP was, respectively, added	Reduce CH4 by 37%.	All regions	Vyas et al., 2018 [59]
	(5) Ammonia treatment of straw	Reduce CH4 by 16–30%	Central Plains	Dong et al., 2004 [62]
	(6) Multi-stage separation of dry and wet, composting and maturation, and sewage collection sedimentation and fermentation tanks	Reduce CH4 by 48.25%; reduce N2O by 53.54%	All regions	Liu and Yong, 2019 [35]

.

Area B, mainly located in the western region, has higher carbon emission efficiency compared to the other two types of regions. Its carbon emissions per capita and beef cattle production value are also relatively high. This region has a relatively large area of natural grassland and grassland slopes, giving it a natural advantage in providing high-quality forage for the beef cattle industry. Referring to the correlation coefficients in Table 3, it is estimated that the potential for carbon sequestration from degraded grassland restoration will be 22.3975 and 57.4628 Mt in 2025 and 2030, respectively.

Area C, where the shadow price of carbon reduction is relatively high, is mainly located in the central plain region. This region is the traditional main grain-producing area of China with abundant feed raw materials, but also faces the risk of land fecal pollution overload. Referring to the correlation coefficients in Table 3, it is estimated that the carbon emissions can be reduced by 6.4345 and 5.5479 Mt by 2025 and 2030, respectively.

Area D, with equally low carbon emission efficiency, is mainly located in the northeast production area, which is the main grain-producing area for corn and soybeans and has abundant roughage resources. Referring to the correlation coefficients in Table 3, the carbon emissions are expected to be reduced by 1.5354 and 0.3423 Mt by 2025 and 2030, respectively.

4.5. Theoretical and Practical Implications for Carbon Emission Reduction in Animal Husbandry

Numerous studies have been conducted to research the variations and efficiency of carbon emissions in animal husbandry, including Wei et al. (2023) [63], Shang et al. (2023) [52], and Yan and Zhang (2023) [28]. However, research on the beef industry is limited to the characteristics and efficiency of carbon emissions, and the focus on emission reduction is limited to the breeding process. This paper enhances the theoretical framework for reducing emissions in animal husbandry from an industry chain perspective, by analyzing the overall changes in carbon emission reduction potential, regional distribution, and other aspects. The classification of emission reduction potential areas and the design and analysis of pathways provide a basis for different regions in China’s beef industry to achieve reduced carbon emissions, such as key areas and directions for beef carbon emission reduction, focusing on key processes and methods.

5. Conclusions

This research adopts an industry chain perspective to assess four leading beef production regions’ carbon emissions, potential, and pathways in China from 2007 to 2021. We use life cycle assessment, the potential index which considers efficiency and fairness; the conclusions as follows:

(1)

The main carbon emission links in the beef cattle industry are rumen fermentation and manure management. The average carbon emissions of various processes, sorted by percentage from largest to smallest, were as follows: rumen fermentation phase (66.90%), manure management phase (19.32%), product processing phase (8.48%), feed grain planting phase (3.66%), energy consumption in breeding phase (1.50%), and feed grain transportation and processing phase (0.13%).

(2)

The beef cattle industry showed a process of “rapid increase–fluctuating growth–slight decrease–slow growth”, presenting a U-shape. The carbon emission change is divided into four stages: 2007–2010, 2011–2016, 2017–2018, and 2019–2021. The average annual growth rates for these four stages were 9.5%, 2.03%, −0.08%, and 5.10%, respectively. These changes were affected by the pig industry disease and government policies.

(3)

There are differences in the carbon emission reduction potential levels of major beef cattle producing areas, but they are relatively stable. The carbon reduction potential presents a pattern of “southwest production area > northeast production area > northwest production area > central plains production area” in descending order. From an individual perspective, Hebei, Anhui, and Shaanxi have lower emission reduction potential indices and limited emission reduction space; Gansu has the highest emission reduction potential index and huge emission reduction space. The emission reduction potential of other provinces fluctuates around 0.500, indicating a certain degree of emission reduction space.

(4)

The main production areas of beef cattle were divided into four categories based on the fairness and efficiency index: high efficiency and low fairness (Areas A); high efficiency and high fairness (Area B); low efficiency and low fairness (Area C); and low efficiency and high fairness (Area D).

(5)

There are differences in emission reduction pathways among different regions. Strategies for emission reduction in B areas can realize the carbon reduction path B→A. Strategies for promoting technology can improve feed efficiency and decrease carbon emissions to achieve the path of C→A. Strategies for emission reduction, such as increasing the efficiency of back-end manure utilization and effective composting, may lead to the carbon reduction path D→B→A.

These findings imply that, firstly, promoting standardized beef cattle breeding models, encouraging the integration of planting and breeding, and building a healthy beef cattle industry ecosystem can reduce carbon emissions in the breeding process. Secondly, based on the differences in the fairness and efficiency of emission reduction, relevant policy formulation should be tailored to local conditions, with a focus on supporting provinces in “unfair and inefficient” regions, avoiding the phenomenon of “one size fits all”. Finally, balancing industrial development and carbon reduction, we will focus on improving the carbon emission efficiency of the beef cattle industry.