Sustainability Assessment of Agricultural Waste Biogas Production System in China Based on Emergy and Carbon Evaluation Methods

Abstract

Biogas production is widely recognized as an effective solution for addressing agricultural waste treatment in rural areas. However, its development is often hindered by economic and environmental constraints. This study combined emergy evaluation and carbon footprint analysis methods to establish a new environmental radius assessment model for evaluating the ecological performance and optimization direction of an agricultural waste biogas production system, using a biogas production company in China as a case study. Compared with the straw return model and straw power generation model, the results of emergy indicators and carbon accounting showed that the biogas production model had a lower environmental load and higher economic output and level of emergy sustainability. Additionally, the biogas production system was found to reduce 0.47 kg of carbon emissions per 1 kg of agricultural waste utilized. The application of the biogas production model in rural areas had high ecological sustainability and carbon emission reduction benefits. Environmental radius assessment results confirmed that the reasonable changes in resource collection distance could further enhance the ecological sustainability, carbon mitigation ability, and economic benefits of the biogas production system. The environmental radius assessment method offers a new approach to the location planning of agricultural waste biogas utilization companies in rural areas.

1. Introduction

In the context of global warming, the development of renewable energy has become a crucial strategy for mitigating climate change [1]. Agricultural waste, including crop straw and livestock manure, is widely utilized as a primary source of renewable energy feedstock. At the same time, the resource utilization of agricultural waste can also alleviate environmental pollution issues such as rural straw burning and river discharge of livestock manure [2].

As one of the largest agricultural countries in the world, China has abundant agricultural waste resources, especially in rural areas [3]. Currently, biogas production has become an efficient way to convert agricultural wastes into renewable energy, which has great potential in rural waste management, carbon emission reduction, and energy development [4]. However, due to the traditional production methods of farmers, the complexity of resource collection, transportation, and storage, as well as the volatility of demand in the biogas market, the development of agricultural waste biogas production is progressing slowly [5]. It is necessary to further analyze the key factors influencing the sustainable development of agricultural waste biogas production systems. Kapoor et al. proposed that there is a requirement for an in-depth understanding of the supply chain from the collection, storage, transport, pre-processing, and conversion to facilitate the sustainable development of agricultural waste biogas production [6]. Liu et al. evaluated the biogas potential and carbon reduction benefit of agricultural waste utilization in Hubei Province, China, and analyzed the reason for the huge gap between agricultural waste biogas utilization and biogas potential [7]. Singh et al. assessed the comprehensive benefits of agricultural waste biogas power generation in India from the perspectives of resource potential, environmental impact, and economic benefits [8]. According to Odum’s emergy theory [9], the agricultural waste biogas production system can be viewed as a complex eco-economic system requiring significant natural and social resource inputs. While there has been extensive research on the sustainability evaluation of agricultural waste biogas production, previous studies have primarily focused on assessing economic output, resource potential, and environmental impact of biogas production systems [10] without adequately accounting for the value of natural resource input. The development characteristics of biogas production systems have not been estimated comprehensively.

The emergy evaluation method focuses on assessing the total inputs of material, labor, and information in the formation of products or services from the aspect of “donors”. Different forms of natural and social resources can be converted into standard solar emergy value (sej) through the emergy conversion coefficients [11], which are utilized for quantitative assessment of the ecological, economic, and social value of the ecological system. Numerous recent studies have utilized energy value theory to assess the sustainability of agricultural production systems. Sun et al. [12] analyzed the emergy input–output of the straw collection, storage, and transportation system in China, revealing that the emergy value of the commercial price of baled straw was significantly lower than the emergy inputs of the company to produce one kilogram of commercial straw, thus hindering sustainable development in straw utilization markets due to cost–income imbalance. Xu et al. [13] used emergy theory to evaluate straw utilization industries in China and proved that the regional straw biogas production had strong sustainability; then, the regional utilization scheme of straw in the study area was optimized by the multi-objective planning method. Liu et al. [14] applied the emergy evaluation method to evaluate the sustainability of the crop rotation system following straw return in the Loess Plateau region of China. The findings indicated that the crop rotation system, post-straw return, was not sustainable and that long-term human exploitation had reduced the resilience of the local agri-ecosystem. The application of the emergy theory can provide reasonable suggestions for the sustainability assessment of agricultural waste biogas production systems from the perspectives of ecology and economics. In addition, the processes of agricultural waste collection and energy utilization consume a variety of energy materials, leading to significant carbon emissions. Most of the past studies only discussed the consumption of fossil fuels while neglecting indirect energy consumption, such as electricity [15]. Among the carbon estimation tools, the carbon footprint analysis method is an effective measurement tool for assessing direct and indirect carbon emissions and offsets of the biogas production system [16].

Currently, the integrated assessment method combining carbon footprint analysis and emergy evaluation has become an important research approach for understanding natural–social complex systems from multiple perspectives [17]. Fang et al. [18] established an emergy-based embodied carbon accounting framework to evaluate the input–output structure and development performance of low-carbon industrial parks. Fan et al. [19] developed a unified accounting framework that integrates emergy analysis and carbon accounting to quantitatively evaluate the sustainability and ecological efficiency of low-carbon power systems. Emergy evaluation and carbon footprint analysis can explain the development characteristics of biogas production systems from the perspectives of natural resource input, social economic input, and environmental emissions. This integrated assessment method provides a new theoretical framework for quantifying the ecological sustainability of agricultural waste biogas production systems.

The purpose of this study is to assess the ecological performance of agricultural waste biogas production systems using emergy evaluation and carbon footprint analysis methods. Environmental radius models are constructed to optimize the layout problem of the biogas production system so as to improve the ecological sustainability of the system. The marginal contribution of this paper is, on the one hand, that this study integrates the emergy and carbon footprint theories to comprehensively evaluate the ecological benefit and optimization direction of the agricultural waste biogas production model, which enriches the literature research on the sustainability assessment of agricultural waste biogas utilization model. On the other hand, a new environmental radius assessment model is constructed, and the application of the model provides a new practical reference for location planning of agricultural waste biogas production model in rural China.

2. Method

2.1. Study Object and System Boundary

Nowadays, the main participants in agricultural waste biogas production in rural China include farmers, intermediate brokers, and biomass energy utilization companies. Farmers and brokers are responsible for collecting agricultural waste and earning profits by selling the collected agricultural waste to biomass energy companies, such as the straw collection, transportation, and storage model in rural China. Some biomass energy utilization companies replace the role of intermediate brokers and complete the unified mechanical collection of agricultural waste by themselves. Biomass energy enterprises commonly utilize large resource conversion facilities and specialized production equipment to efficiently convert agricultural waste into clean energy.

A biomass energy company (115°17′ E, 36°9′ N) in Henan province, China, was selected for empirical study. The study area exhibits a rapid development trend in the planting industry and animal husbandry, resulting in significant emissions of agriculture and breeding wastes annually [20]. The company initially focused on straw returning and straw electricity but later shifted to agricultural waste biogas production due to operational losses. In this paper, three common models of agricultural waste utilization, including the straw return to field model, straw power generation model, and biogas production model, were compared to explore the sustainable ways of agricultural waste utilization. Currently, the company has established several biogas conversion stations to assist local farmers in collecting and processing agricultural waste resources (primarily corn stover and livestock manure) free of charge. Additionally, farmers have the option to sell straw to the company for 1 CNY per kilogram.

To enhance the efficiency of agricultural waste recycling, the company has been equipped with a variety of agricultural collection and transportation equipment, including straw self-propelled balers, straw-grabbing machines, agricultural tractors, and manure collection tankers. Figure 1 describes the system boundary of the agricultural waste biogas production system. In the collection phase, livestock manure and crop residue are collected by the pre-laid sump and straw baler, respectively, and then the collected wastes are transported to the biogas conversion station by agricultural tankers and trucks. In the production stage, the biogas plant transfers agricultural wastes into biogas, biogas slurry, and biogas residue, relying on anaerobic fermentation. The biogas products are used for power generation and fertilizer preparation. In the utilization part, the biomass electricity is mainly put on the power grid, and a sliver of electricity is supplied for the self-operation of the biogas plant. Organic fertilizers are sold to local farmers for agricultural cultivation, and the remaining biogas slurry and residues are used for crop irrigation and fertilization in facility-based agriculture.

2.2. Emergy Evaluation Method

The detailed steps of emergy accounting for the agricultural waste biogas production system are in accordance with the guidelines established by Odum [10]. The emergy baseline (1.2 × 10²⁵ sej/year) used in this study is chosen from the study of Brown et al. [21]. Firstly, the emergy boundary of the agricultural waste biogas production system needs to be defined, the system boundary of this study includes the agricultural waste collection, biogas production, and product utilization parts (not considering the crop cultivation and animal breeding phases). Secondly, the emergy system diagram and table are made according to the actual characteristics of the study object. As shown in Figure 2, the diagram of emergy flows of the agricultural waste biogas production system is consisted of natural renewable resources (R), natural non-renewable resources (N), purchased renewable resources (P_R), purchased non-renewable resources (P_N), and product yield (Y). Among them, R is referred to the emergy value of sunlight, wind, rainfall, and agricultural wastes. N stands for the emergy value of soil loss. P_R refers to the emergy value of labor and water. P_N describes the emergy value of fuel, electricity, and infrastructure. Y represents the emergy value of biomass electricity, waste management subsidy, and vegetable. The emergy tables are mainly used to list the emergy inputs and outputs of the biogas production system, usually shown in the result section. Thirdly, Equation (1) explains that the emergy value of each resource is determined by the resource energy and the emergy transformity. Fourthly, some emergy indexes [22] are listed in

Table 1. Emergy index of the biogas production system.

Emergy Indicator	Expression Equation	Interpretation
Unit emergy value (UEV)	UEV = I/Q	The conversion rate of the solar emergy.
Emergy self-sufficiency (ESR)	ESR = (R + N)/T	Degree of local resource development.
Emergy yield ratio (EYR)	EYR = Y/(PR + PN)	Economic output efficiency of the system.
Environmental loading ratio (ELR)	ELR = (N + PN)/(R + PR)	Environmental burden from the system.
Emergy sustainable index (ESI)	ESI = EYR/ELR	Development potential of the system.
Economic benefit (EB)	EB = Revenue − Cost	Economic return of the system.

Note. Total emergy inputs of product formation are I; consumption quantities of product are Q; T is the total emergy input of the system, and T = R + N + P_R + P_N.

to analyze the development potential and ecological sustainability of the agricultural waste biogas production system.

$${Emergy}_{\mathit{x}}={Energy}_{\mathit{x}}\times {Emergy}_{{Transformity}_{\mathit{x}}}$$

(1)

2.3. Carbon Footprint Analysis Method

The carbon footprint analysis in this paper focuses on rural energy utilization enterprises, and, therefore, the ISO 14,064 standard has been selected for carbon emissions accounting. The standard stipulates that the consumption of fossil energy, electricity, or energy-intensive materials in production activities will result in carbon emissions, and the activities that emit no less than 1% of the total carbon emissions within the system boundary should be included in the scope of carbon accounting [23]. Consequently, based on the actual characteristics of agricultural waste biogas utilization, the carbon accounting scope includes straw baling, agricultural waste transportation, waste pre-treatment, and biogas energy production. The carbon emissions of agricultural waste biogas production can be calculated through the multiplication of the carbon emission factor and amounts of energy consumption, which can be seen in Equation (2). The carbon emission factor values can be acquired in Appendix A,

Table A1. Carbon emission factors of consumption and economic cost [55].

Item	Value	Unit
Carbon factor of diesel oil	3.0959	kgCO2/kg diesel
Carbon factor of electricity	0.738	kgCO2/kwh electricity
Carbon factor of open-air pollution	1.3904	kgCO2/kg straw
Carbon factor of chemical fertilizer	1.475	kgCO2/kg fertilizer

. The carbon reduction potential of biomass products, as opposed to open-air pollution, fossil fuels, and chemical fertilizers, has also been estimated in order to quantify the environmental performance of the system.

$${CarbonEmission}_{\mathit{x}}={Quantities}_{\mathit{x}}\times {CarbonFactor}_{\mathit{x}}$$

(2)

In the process of biogas production, there is a possibility of biogas leakage due to pipeline or tank breakage. Additionally, some biogas may escape through the inlet and outlet of the biogas digester, as they are in direct contact with outside air. Biogas contains large amounts of methane gas, and the greenhouse effect caused by its fugitive emissions needs to be included in carbon footprint accounting. The calculation method [24] is shown in Equation (3). According to the average biogas supply records of the research company, the difference between the gas production from the biogas project and the final gas consumption was regarded as the biogas leakage without considering the meter measurement error, and the value was taken as 3%.

$${CarbonEmission}_{CH4}=BiogasLeakage\cdot {Content}_{CH4}\cdot {Density}_{CH4}\cdot GW{P}_{CH4}$$

(3)

2.4. Environmental Radius Assessment Method

The optimization decision of agricultural waste collection radius is important for the sustainable development of biogas production companies [25]. Currently, there are many methods for radius optimization, such as spatial geographic information analysis [26], linear programming [27], and technology upgrading for biomass treatment [28], etc., but few studies consider the emergy flow of the natural–social system [29]. The emergy method focuses on various material flows, information flows, and monetary flows in the input–output of the system, which can comprehensively and scientifically analyze multiple influencing factors of agricultural waste collection radius.

In this study, the concept of “environmental radius” was proposed, and the impact of resource recovery radius on system sustainability was expressed in terms of emergy value, economy, and carbon emissions. Firstly, it was assumed that the agricultural waste was uniformly distributed in ‘round island’, and the biogas production station was located at the center of the island. Secondly, referring to the biomass supply chain model constructed by Sun et al. [30] and Zhao et al. [31], Equations (1) and (2) were improved, then the environmental radius evaluation model of agricultural waste biogas production system was constructed in

Table 2. Calculation formulas of emergy and economic value.

Calculation Formulas	Symbol Explanations
$E_{m1}={\pi r^2·∆E}_n·T_r$	$E_{m1}$ (R and N) is referred to the emergy value of natural environmental resource inputs, including sunlight, rainfall, wind, and agricultural wastes, etc.; $r$ is the collection radius of agricultural waste; ${∆E}_n$ represents energy flow of different natural resource of unit area; $T_r$ indicates emergy conversion ratio of different materials. To avoid double counting of emergy, the maximum emergy flow (agricultural waste) is selected to represent the natural resource input.
$q_2=\left({\displaystyle \frac{O_1}{v_1}}+{\displaystyle \frac{O_2}{v_2}}\right)·{\displaystyle \frac{\mu }{2}}$	$q_2$ is the diesel consumption of unit agricultural waste transportation; $O_1$ and $O_2$ and are the transportation speed of full-loaded and empty-loaded vehicle, reseverally; $v_1$ and $v_2$ are the transportation speed of full-loaded and empty-loaded vehicle, severally; $\mu$ is equal to the ratio of power and load.
$L={\int }_0^{r}2\Pi \rho r^{2}dr={\displaystyle \frac{2}{3}}\rho \mathrm{r}$	$L$ represents the transportation distances of vehicles from collection points to biogas plant; $\rho$ describes the road tortuous factor.
$\mathrm{M}=\pi r^2·\sigma$	M stands for the annual collection quantities of agricultural waste; $\sigma$ is the resource density of available agricultural waste.
$C_1=\mathrm{M}·({\displaystyle \frac{q_1}{\alpha }}+L·q_2+q_3)·C_d$	$C_1$ is the economic cost of diesel consumption, $\alpha$ is referred to the working efficiency of a straw baler; $q_1$$,q_2$$,\mathrm{and}{q}_3$ are set to the unit fuel consumption of agricultural waste balers, carriers, and conversion station, respectively; $C_d$ is the price of unit diesel.
$E_{m2}=\mathrm{M}·({\displaystyle \frac{q_1}{\alpha }}+L·q_2+q_3)·{\delta }_1·T_r$	$E_{m2}$ (PN) is the emergy value of diesel fuel input; ${\delta }_1$ represents the energy conversion ratio of 1 kg diesel.
$C_2=\mathrm{M}·({\displaystyle \frac{l_1}{t·\alpha }}+L·l_2+l_3)$	$C_2$ represents the total costs of labor; $C_m$ is the daily wage of worker. $l_1$$,l_2$$,\mathrm{and}{l}_3$ are unit worker costs of agricultural waste collection, transportation, and production; $t$ is the effective time of agricultural waste collection.
$E_{m3}=\mathrm{M}·({\displaystyle \frac{l_1}{t·\alpha }}+L·l_2+l_3)·T_r$	$E_{m3}$ (PR) is the emergy value of labor input.
$C_3=\mathrm{M}·({\displaystyle \frac{m_1}{t·\alpha }}+L·m_2)+m_3$	$C_3$ represents the total costs of equipment purchase; $m_1$$,m_2$ are net present value of collection machine and vehicle, and $m_3$ is the unit costs of facility.
$E_{m4}=\left[\mathrm{M}\left({\displaystyle \frac{m_1}{t·\alpha }}+L·m_2+\right)m_3\right]·T_r$	$E_{m4}$ (PN) indicates the total emergy value of equipment purchase.
$C_4=\mathrm{M}·G·l_4·C_w$	$C_4$ represents the total costs of water consumption; $G$ is the production efficiency of biogas; $l_4$ are unit water consumption of biogas production; $C_w$ is the unit price of water.
$E_{m5}=\mathrm{M}·G·l_4·T_r$	$E_{m5}$ (PR) indicates the total emergy value of water consumption.
$C_5=\mathrm{M}·G·e·C_e$	$C_5$ represents the total costs of electricity consumption; $e$ are unit electricity consumption of biogas production; $C_e$ is the unit price of electricity.
$E_{m6}=\mathrm{M}·G·e·{\delta }_2{·T}_r$	$E_{m6}$ (PN) indicates the total emergy value of electricity consumption. ${\delta }_2$ represents the energy conversion ratio of 1 kwh electricity.
$C_6={\sum }_{i=1}^n{Y}_i·P_i$	$C_6$ represents the total revenue of biomass products; $Y_i$ is assumed as output of different biomass products, $P_i$ are market price of different biomass product.
$E_{mY}={\sum }_{i=1}^n\mathrm{M}{·Y}_i·T_r$	$E_{mY}$ (Y) quantifies emergy value of different agricultural waste products.

and

Table 3. Calculation formulas of carbon footprint.

Formulars	Explanation of Variables
${CE}_1={\displaystyle \frac{\pi r^2}{\alpha }}\sigma {·q}_1·{\mu }_1$	${CE}_1$ is referred to the carbon emission of straw baler; ${\mu }_1$ indicates carbon emission factor of diesel; $\sigma$ stands for the available agricultural waste resource of unit area. $q_1$ is set to the unit fuel consumption of straw balers.
${CE}_2={\displaystyle \frac{2\pi r^3}{3}}{·q}_2·\rho {·\mu }_1$	${CE}_2$ is the carbon emission from the diesel consumption of agricultural waste vehicles; $\rho$ describes the road tortuous factor. $q_2$ is the unit fuel consumption of agricultural waste carriers.
${CE}_3=\pi r^2·\sigma ·w_1·{\mu }_2$	${CE}_3$ represents the carbon emission from electricity consumption; ${\mu }_2$ indicates carbon emission factor of electricity; $w_1$ is the electricity consumption of agricultural waste recycling system.
${CE}_4=\pi r^2·\sigma ·q_3·{\mu }_1$	${CE}_4$ is the carbon emission from the fossil fuel in production phase. $q_3$ is set to the unit fuel consumption of conversion station.
${CE}_5=\pi r^2·\sigma {·w}_2·{\mu }_3$	${CE}_5$ is the carbon emission from the biogas leakage; $w_2$ is the methane production from agricultural waste; ${\mu }_3$ indicates the carbon emission factor of methane.
${CE}_6=\pi r^2·\sigma {·w}_3·{\mu }_2$	${CE}_6$ indicates the carbon offset from agricultural waste power generation; $w_3$ is the power generation used by the system itself.
${CE}_7=\pi r^2·\sigma {·w}_4·{\mu }_4$	${CE}_7$ indicates the carbon offset from agricultural waste utilization instead of waste emission; $w_4$ is the amount of agricultural waste utilization. ${\mu }_4$ indicates carbon emission factor of agricultural waste pollution.
${CE}_8=\pi r^2·\sigma {·w}_5·{\mu }_5$	${CE}_8$ indicates the carbon offset from organic fertilizer preparation; $w_5$ is the amount of fertilizer savings. ${\mu }_5$ indicates carbon emission factor of unit fertilizer manure.
$NCE={CE}_1+{CE}_2+{CE}_3+{CE}_4+{CE}_5-{CE}_6$	$NCE$ is the net carbon emission of the system.

. Table 2 includes accounting modeling of economic cost, economic revenue, and emergy values (R, N, P_R, P_N). Table 3 includes accounting modeling of carbon emissions. Thirdly, combined with the definition of emergy indicators, economic benefits, and carbon emissions, the dynamic diagrams of the environmental radius assessment of the biogas production system were pictured through the simulation software. Particularly, the original supply distance of the investigated biogas production system was 7.5 km. Finally, the sensitivity analysis was conducted to understand the impact of parameter changes on the environmental radius consequences and summarize the significance of these results in practical production and optimization decisions.

2.5. Data Source

The data involved in this study were acquired from the field research and company survey in 2022. The original data of the straw returning, straw electricity, and agricultural waste biogas production system, including natural environmental parameters, material input–output lists, economic costs, and carbon emission factors, can be referred to in the Appendix A,

Table A2. Natural environmental parameter of study area.

Parameter	Value	Unit
Average solar radiation	125.07	kcal/cm2
Average annual precipitation	599.70	mm
Average elevation	46.0	m
Average wind speed	2.7	m/s

,

Table A3. Data of the agricultural waste collection phase.

Item	Value	Unit
Collection quantities of crop straw	73,000	ton
Collection quantities of animal waste	182,500	ton
Practical feedstock supply radius	7.5	km
Purchase price of straw baler	20,601.1	$
Working efficiency of straw baler	2	ton/h
Number of straw balers	13	num
Unit diesel consumption of straw baler	15.6	kg/h
Annual number of livestock and poultry	125,000	head
Laying cost of water well	31,694	$
Effective annual working days	330	day

,

Table A4. Data of the agricultural waste transportation phase.

Item	Truck	Tanker	Unit
Full-load speed	20	40	km/h
Empty-load speed	25	60	km/h
Full-load oil consumption	0.24	0.26	kg/kwh
Empty-load oil consumption	0.20	0.23	kg/kwh
Power-load ratio	13.3	8.3	kw/ton
Machine price	11,045.36	31,694	$
Number of vehicles	10	10	num

,

Table A5. Data of the agricultural waste production phase.

Item	Value	Unit
Annual electricity consumption	873,226	kwh
Annual fuel consumption	135,916	tce
Labor management cost	34,170.45	$
Machine maintenance cost	42,472.73	$
Purchased price of anaerobic jar	39,617.5	$
Number of anaerobic jars	5	num
Capacity of the anaerobic jar	1500	m3
Government subsidy	79,235	$
Collection revenue of livestock manure	1,095,000	$
Biogas electricity	9,855,000	kwh
Fertilizer yield	1,830,000	kg
Biogas yields	8,760,000	m3

and

Table A6. Summaries of material consumption and economic cost.

Item	Value	Unit
Labor numbers	56	person
Labor costs	4.35 × 105	$
Diesel consumption	5.45 × 105	kg
Diesel costs	7.60 × 105	$
Electricity consumption	8.75 × 105	kwh
Electricity costs	4.08 × 105	$
Equipment costs	5.71 × 105	$
Water consumption	7.80 × 107	kg
Water costs	1.04 × 105	$

. In addition, all data on the emergy, economy, and carbon accounting were converted to one year based on a 15-year cycle of system operation, and the cost of the equipment investment was the net present value after conversion.

3. Result and Discussion

3.1. Emergy Evaluation Result

Agricultural waste such as straw is a kind of scattered throw-type, low-capacity resource and has the characteristics of dispersed resources and concentrated collection time, which requires the establishment of a professional straw collection, transportation, and storage system for recycling [32]. The three agricultural waste utilization models compared in this paper included collection, transportation, and storage processes.

Table 4. Emergy flows of straw collection, transportation, and storage system.

Item	Quantity	Unit	Transformity (Sej/Unit)	Emergy (Sej)	Reference
Local renewable resources (R)
Sunlight	9.25 × 1017	J/y	1.00	9.25 × 1017	[6]
Wind, kinetic	6.15 × 1011	J/y	8.00 × 102	4.92 × 1014	[33]
Rain, chemical	5.24 × 1013	J/y	7.00 × 103	3.67 × 1017	[33]
straw	1.13 × 1015	J/y	2.70 × 104	3.05 × 1019	[12]
Total				3.05 × 1019
Local non-renewable resource (N)
Topsoil loss	6.67 × 1013	J/y	7.40 × 104	4.94 × 1018	[12]
Total				4.94 × 1018
Renewable external inputs (PR)
Labor	3.00 × 105	$/y	4.94 × 1012	1.48 × 1018	[34]
Total				1.48 × 1018
Non-renewable external inputs (PN)
Diesel oil	1.65 × 1013	J/y	6.60 × 104	1.09 × 1018	[35]
Electricity	1.52 × 1012	J/y	3.36 × 105	5.11 × 1017	[35]
Equipment	2.29 × 105	$/y	4.94 × 1012	1.13 × 1018	[34]
Total				2.73 × 1018

shows the emergy value of the straw collection, transportation, and storage system. Then, the emergy flows of external inputs were calculated for straw returning, straw power generation, and agricultural waste biogas production models, which can be seen in

Table 5. Emergy flows of straw return to field.

Item	Quantity	Unit	Transformity (Sej/Unit)	Emergy (Sej)	Reference
Renewable external inputs (PR)
Labor	9.25 × 104	$/y	4.94 × 1012	4.57 × 1017	[34]
Total				4.57 × 1017
Non-renewable external inputs (PN)
Diesel oil	3.56 × 1012	J/y	6.60 × 104	2.35 × 1017	[35]
Equipment	1.34 × 105	$/y	4.94 × 1012	6.62 × 1017	[34]
Total				8.97 × 1017
Outputs
Straw return	8.24 × 1013	J/y	2.96 × 104	2.44 × 1018	[13]
Straw product	5.18 × 105	$/y	4.94 × 1012	2.56 × 1018	[34]
Total				5.00 × 1018

,

Table 6. Emergy flows of straw power generation.

Item	Quantity	Unit	Transformity (Sej/Unit)	Emergy (Sej)	Reference
Renewable external inputs (PR)
Labor	1.97 × 105	$/y	4.94 × 1012	9.75 × 1017	[34]
Cooling water	1.97 × 1012	g/y	5.03 × 105	9.91 × 1017	[36]
Oxygen	1.35 × 1010	g/y	5.16 × 107	6.96 × 1017	[37]
Total				2.66 × 1018
Non-renewable external inputs (PN)
Fuel	8.18 × 1012	J/y	6.60 × 104	5.40 × 1017	[35]
Electricity	5.40 × 1011	J/y	3.36 × 105	1.81 × 1017	[35]
Equipment	6.05 × 105	$/y	4.94 × 1012	2.99 × 1018	[34]
Total				3.71 × 1018
Outputs
Straw electricity	2.89 × 1013	J/y	3.36 × 105	9.72 × 1018	[35]
Total				9.72 × 1018

and

Table 7. Emergy flows of agricultural waste biogas production.

Item	Quantity	Unit	Transformity (Sej/Unit)	Emergy (Sej)	Reference
Renewable external inputs (PR)
Labor	1.35 × 105	$/y	4.94 × 1012	6.65 × 1017	[34]
Water	7.80 × 1010	g/y	1.00 × 105	7.80 × 1015	[36]
Manure waste	3.25 × 1013	J/y	1.24 × 105	4.03 × 1018	[38]
Total				4.70 × 1018
Non-renewable external inputs (PN)
Diesel oil	6.74 × 1012	J/y	6.60 × 104	4.45 × 1017	[35]
Electricity	1.63 × 1012	J/y	3.36 × 105	5.49 × 1017	[35]
Investment	3.42 × 105	$/y	4.94 × 1012	1.69 × 1018	[34]
Total				2.68 × 1018
Outputs
Ecological subsidy	1.70 × 105	$/y	4.94 × 1012	8.40 × 1017	[34]
Organic fertilizer	1.83 × 109	g/y	2.80 × 109	5.12 × 1018	[39]
Biogas electricity	3.55 × 1013	J/y	3.36 × 105	1.19 × 1019	[35]
Total				1.79 × 1019

. The emergy input–output structures of the three models are illustrated in

Table 8. Emergy input–output structure of different agricultural waste utilization modes.

Emergy Index	Straw Return	Power Generation	Biogas Production
R (×1018 sej)	30.5	30.5	30.5
N (×1018 sej)	4.94	4.94	4.94
PR (×1018 sej)	1.94	4.14	6.18
PN (×1018 sej)	3.63	6.44	5.41
T (×1018 sej)	41.01	46.02	47.03
Y (×1018 sej)	5.00	9.72	17.86
Ratio of renewable resource	0.79	0.75	0.78
Ratio of non-renewable resource	0.21	0.25	0.22

, and emergy index diagrams of the three models are pictured in Figure 3.

3.1.1. Emergy Value Accounting

As shown in Table 8, the resource input–output structures of all three models were characterized by a high proportion of renewable resource inputs. As the source of raw materials for the production of the system, agricultural waste had a high solar emergy value and was the main component of renewable resources in the system. Biogas production provides an alternative strategy for a large amount of surplus agricultural residues, such as straw, which can both protect the environment and utilize the inherent energy present in such raw materials [40]. The total emergy input and output of the three models were unbalanced. It was obvious that the three models were characterized by high inputs and low outputs. The full potential of resource utilization for agricultural waste has yet to be realized in the market. On the one hand, how to enhance the value of agricultural waste biogas and achieve a high return on resource utilization remains a critical issue to be addressed at present [6]. On the other hand, policy support and subsidies are key elements in ensuring the steady development of biogas production enterprises [41]. The external emergy inputs of the biogas production model were larger than those of the other two models. The agricultural waste biogas production model produced biogas through the synergistic anaerobic fermentation of straw and organic matter, which was used to produce electricity and prepare organic fertilizers. Biogas production occurs during many processes, including pretreatment, reactor reactions, biogas upgrading, and gas storage. The agricultural waste biogas production models required more external economic resource inputs. Hence, new pretreatment methods or alternative ways for digestate utilization could be explored to improve the economic benefit of biogas production [42].

3.1.2. Emergy Indicator Evaluation

From the perspective of emergy indicators, the ESR values of the three models were close to 0.8, indicating that the three models had a high degree of dependence on local natural resources and were largely driven by demands for agricultural waste resource utilization. The biogas production model could recycle and treat an average of 73,000 tons of straw and 182,500 tons of manure waste annually, making an important contribution to the management of rural agricultural waste. The EYR value of the agricultural waste biogas production model was 1.54, which was higher than that of the other two models. The emergy output of the biogas production model came from biogas electricity, organic fertilizer, ecological service subsidy, and service payments received after helping livestock and poultry farmers collect manure. The biogas production system had more diversified economic output models compared with the other two models, proving that anaerobic digestion to produce biogas is an effective way to improve circularity and add additional value to agricultural waste [43]. The ELR values indicated that the straw power generation model had the highest degree of environmental loading, followed by the agricultural waste biogas production model and straw return to the field model. The environmental impact generated by the three models was at a low level, according to the study by Cheng et al. [35]. From the ESI values of the three models, it could be seen that the agricultural waste biogas production model had the highest ecological sustainability, followed by the straw return model and straw power generation model, which was consistent with the findings of Xu et al. [13] and Liu et al. [44]. The biogas production model has obvious advantages in achieving sustainable development of resource utilization of agricultural waste in rural areas [45].

3.2. Carbon Footprint Analysis Result

3.2.1. Carbon Emission Accounting

According to the field research, the carbon emissions of the three agricultural waste utilization models were mainly produced by the consumption of fossil fuel and grid electricity.

Table 9. Carbon emission results of different agricultural waste utilization modes.

Category	Straw Return	Power Generation	Biogas Production	Unit
Total carbon emission	1.77 × 106	1.74 × 106	4.97 × 106	kgCO2
Emission from fossil fuels	1.46 × 106	1.32 × 106	1.68 × 106	kgCO2
Emission from grid electricity	3.11 × 105	4.23 × 105	6.45 × 105	kgCO2
Emission from biogas leakage			2.64 × 106
Carbon emission of utilizing 1 kg agricultural waste	6.93	6.81	19.45	gCO2
Carbon emission density of 1 kwh biomass electricity	/	0.22	0.50	kgCO2
Instead of agricultural waste pollution	1.01 × 108	1.01 × 108	1.10 × 108	kgCO2
Instead of chemical fertilizer	0	0	2.70 × 106	kgCO2
Instead of coal-fired electricity	0	5.92 × 106	7.28 × 106	kgCO2

shows the carbon emission results of agricultural waste utilization models. The carbon emission of the biogas production model was 4.97 × 10⁶ kg, which was higher than that of the straw return model (1.77 × 10⁶ kg) and the straw power generation model (1.74 × 10⁶ kg). Among them, the carbon emission produced by electricity was lower than that of diesel. In the activities of agricultural waste resource utilization, the operation of agricultural collection machines, vehicles, and production tools consumed much diesel oil, thus generating a large amount of carbon emission pollution. Daily lighting, warehouse ventilation, and electrical equipment operation consume electricity in production activities, leading to indirect carbon emissions pollution, indicating that the carbon emissions from electricity consumption cannot be ignored. In particular, carbon emissions from biogas leaks (2.64 × 10⁶ kg) account for most of the total carbon emissions of the biogas production system.

The carbon emission density of the biogas production model (19.45 gCO₂) was significantly higher than that of the straw return model (6.81 gCO₂) and the straw power generation model (6.93 gCO₂). The main reason for this discrepancy was that the biogas production model had more carbon emission sources than the other two models, including waste collection, waste pretreatment, biogas production, and biogas power generation, which increased the demand for fossil fuels and electricity. As shown in Figure 4, carbon emissions from the feedstock transportation phase accounted for the largest proportion of total carbon emissions of the biogas production system, followed by the electricity utilization for the production, agricultural waste collection, agricultural waste storage, and fuel consumption of the production stage. Biogas production is seen as one of the key measures in the circular economy, providing several benefits for environmental improvement. However, these benefits may not be achieved if the production is not implemented in ways that reduce carbon emissions. Lehtoranta et al. proposed that adopting different advanced carbon reduction management measures throughout the lifecycle of biogas production is crucial for alleviating the climate impacts [46]. Therefore, to reduce the carbon emissions of the biogas production system, the use of energy-saving agricultural equipment or the scientific planning of vehicle distribution routes was an effective measure in the phases of agricultural waste collection, transportation, and storage. For the production stage, it was useful to increase the carbon mitigation measures for energy recycling, such as photovoltaic roofs [47], waste heat utilization [48], and carbon capture [49], etc., to achieve the synergistic development of carbon emission reduction and efficient energy use. Additionally, biogas leaks were a major source of carbon emissions from biogas production. It is necessary to use flares or upgrade biogas systems to avoid more methane discharge into the environment from biogas plants [50].

3.2.2. Carbon Emission Reduction Accounting

From the aspect of carbon emission reduction, the three models of agricultural waste resource utilization had significant carbon reduction benefits in terms of replacing agricultural waste emission, fertilizer use, and coal-fired power generation [51]. Firstly, resource utilization of agricultural waste could avoid the phenomena of straw burning, open accumulation of livestock manure, and their discharge into rivers. This approach has the potential to reduce approximately 1.10 × 10⁸ kg of carbon pollution that may be generated by the improper disposal of agricultural wastes. Secondly, biomass electricity from agricultural waste replaced traditional coal-based power generation. The straw power generation model and biogas production model outputted biomass clean power to reduce 5.92 × 10⁶ kg and 7.28 × 10⁶ kg of carbon pollution generated by coal-based electricity, respectively. Thirdly, the biogas slurry and residues from the biogas production model were used to prepare organic fertilizers, which could replace the use of traditional chemical fertilizers and reduce 2.70 × 10⁶ kg of carbon pollution. Therefore, although the biogas production model had the highest carbon emission intensity when utilizing agricultural waste, its actual carbon emission reduction benefit was significantly better than that of the straw return and straw power generation models. Moreover, the carbon emission density of straw electricity and biogas electricity in this study was 0.22 gCO₂/kwh and 0.50 gCO₂/kwh, respectively. Referring to the latest carbon emission factor data of regional electricity released by the Chinese Academy of Environmental Planning in 2022, the carbon emission factor for electricity in the study area (central China) was 0.738 gCO₂/kwh. It was clear that the carbon emission factors of electricity under the two models of straw power generation and biogas power generation were lower than the average carbon emission factor of the region, which proved the cleanliness of biomass electricity. Biogas production plays an important role in the coordinated development of renewable power utilization and carbon emission reduction in the power sector [52].

3.3. Environmental Radius Assessment Result

3.3.1. Environmental Radius Accounting

The emergy evaluation and carbon footprint analysis results indicated that implementing the biogas production model for agricultural waste utilization in rural areas offers higher ecological sustainability and greater reduction in carbon emissions compared to straw return to field and straw power generation models. However, this green and sustainable utilization model relied heavily on the feedstock supply of agricultural waste in actual development. The usability of biomass resources and feedstock collection distance directly affected the output benefits of biogas production enterprises [53]. Therefore, it was necessary to rationalize the siting of biogas production plants through scientific methods.

Environmental radius diagrams, including the emergy index diagram, carbon emission diagram, and economic return diagram, are exhibited in Figure 5, Figure 6 and Figure 7. Constrained by the actual range of rural waste utilization, the numerical analysis of the emergy index was analyzed within the range of from 0 km to 20 km in this paper. The emergy index diagram manifested that the biogas production system had higher values in terms of emergy yield rate (1.55) and emergy sustainability index (5.53) but a lower emergy self-sufficiency rate (0.74) and environmental loading rate (0.27) at 9.6 km. Compared to the original collection radius (7.5 km), the self-organization and ecological sustainability of the biogas production system were improved when the collection radius reached 9.6 km. The carbon emission map illustrated that both the total carbon emissions and the alternative carbon reduction benefits of the system increase as the resource collection radius increases; however, the increasing degree in the alternative carbon reductions of the system was much greater than the increase in the total carbon emissions. The expansion of the resource collection radius significantly improved the carbon reduction benefits of the system. The economic benefit diagram revealed that the biogas production system achieved maximum economic benefit at 8.6 km, and the economic benefit of the system was increased at 9.6 km compared to the original distance (7.5 km).

From the perspectives of emergy evaluation, economic accounting, and carbon footprint, it could be concluded that the ecological performance, economic benefit, and carbon mitigation ability of the agricultural waste biogas system were effectively improved by increasing the resource collection radius distance. Moreover, the optimal supply distance derived from the environmental radius assessment method was larger than the maximum radius obtained from the economic view because the emergy assessment method comprehensively analyzed the natural resource inputs and social resource inputs of the biogas production system and maximized the sustainability of the system based on the optimal emergy output and optimal environmental load. The economic accounting methods only considered the economic costs and benefits of the system, which could not assess the optimal performance of the biogas production system comprehensively [30]. Andric et al. [54] constructed computational models for the maximum supply distance of biomass heating systems by using the emergy and carbon footprint analysis theories and found that the maximum supply distance of the emergy value model was lower than that of the carbon footprint, which proved the comprehensiveness of the emergy assessment from the aspect of input–output analysis. Based on the comprehensiveness advantages of the emergy theory, Xu et al. [13] constructed a method combining energy-value analysis and multi-objective planning to solve the optimization problem of the regional straw comprehensive utilization scheme in China. The emergy theory was suitable for scientific assessment of the layout and planning of agricultural waste biogas production in Chinese rural areas. The environmental radius assessment method proposed in this paper, including the emergy index radius, economic benefit radius, and carbon emission reduction radius, will provide a new reference angle for the site optimization of agricultural waste utilization enterprises.

3.3.2. Sensitivity Analysis

Referring to the results of the emergy evaluation, the inputs of agricultural waste, labor, energy, and infrastructure were the main sources of external inputs to the biogas production system. As shown in

Table 10. Sensitivity analysis results of the environmental radius assessment.

Parameter	Baseline	Scenario 1		Scenario 2		Scenario 3		Scenario 4
Rate of change	0%	−10%	10%	−10%	10%	−10%	10%	−10%	10%
EYR	1.55	1.41	1.70	1.63	1.46	1.57	1.50	1.58	1.50
ELR	0.27	0.27	0.29	0.28	0.27	0.27	0.29	0.27	0.29
ESR	0.74	0.74	0.77	0.76	0.74	0.76	0.75	0.76	0.75
ESI	5.53	5.22	5.86	5.75	5.34	5.82	5.27	5.81	5.28
Optimal radius (km)	9.6	9.9	9.4	9.5	9.6	9.9	9.4	9.3	9.9
Carbon reduction (108 kg)	1.9	1.7	2.0	1.8	1.9	2.0	1.8	1.8	2.0
Economy (104 $)	6.23	4.73	7.11	7.72	5.29	9.65	3.12	8.13	4.27

Note: Scenario 1 represented changes of resource density; Scenario 2 represented changes of labor input; Scenario 3 represented changes of energy consumption; Scenario 4 represented changes of investment input.

, resource density, labor use, energy consumption, and infrastructure inputs were selected as influencing variables for sensitivity analysis. The changes in environmental assessment indicators when each of the four variables is reduced by 10% and increased by 10% are analyzed. It was obvious that the ecological sustainability and economic benefits of biogas production systems decrease with increasing inputs of labor, energy, and infrastructure but increase with enhancing resource density. The difference illustrated the importance of resource availability for the sustainable development of the biogas production system. The rational allocation of labor, energy, and production equipment could also improve the ecological sustainability of the biogas production system. The carbon reduction benefit of the biogas production system decreased with increasing energy use and increased in other cases. Reducing fossil energy use was the most effective path to achieving carbon emission reduction. In addition, all the optimal radii of feedstock supply changed in the four scenarios, which indicated that site selection for biogas production was influenced by a variety of factors. When the price of energy rises, transportation costs increase and it might be necessary to shorten the supply radius to keep production costs optimal. When resources are lacking, labor inputs increase, or infrastructure is improved, the supply radius might be allowed to expand to cover more resource points.

3.4. Limitations of This Study

Environmental radius assessment models were constructed to analyze the relationship between the ecological performance of the biogas production system and the feedstock supply distance, which provided a new perspective for the site selection of agricultural waste biogas utilization enterprises. However, constrained by the complexity of the actual production of agricultural waste biogas, the optimal supply distance calculated in this study was closely related to the research area and enterprise, and its actual values would still be affected by labor, energy, production facilities, agricultural waste resources, and other factors. Therefore, the optimal supply distance of the agricultural waste biogas production system was not a fixed value, only an optimal solution under specific conditions. In practical production applications, it is important to maintain a certain level of flexibility in order to adjust the supply radius promptly in response to changes in external conditions. In the future, the adaptive development of biogas production systems can also be realized by establishing a dynamic prediction and adjustment mechanism.

4. Conclusions

In this study, emergy and carbon footprint analysis methods were employed to assess the ecological advantages of the agricultural waste biogas system. A typical biomass energy enterprise based on agricultural waste biogas production in China was selected for empirical analysis. The straw return to the field model and straw power generation model were compared with the biogas production model to reveal the current situation of agricultural waste biogas utilization models in Chinese rural areas. Moreover, a new method of environmental radius assessment was proposed to investigate the influence of resource collection radius on the sustainability of agricultural waste biogas systems.

From the emergy evaluation aspect, the agricultural waste biogas production model was characterized by an imbalance of emergy inputs and outputs, indicating that the real market value of agricultural waste products had been seriously neglected. The emergy index results and carbon footprint results illustrated that the application of the biogas production model has higher economic output, ecological sustainability, and carbon reduction benefits in rural areas compared with the straw-to-field and straw-to-power models. The agricultural waste biogas production model plays an important role in green and sustainable agricultural production, and its stable development still needs to be supported by a series of financial policies.

The results of environmental radius evaluation, including emergy value index radius, economic benefit radius, and carbon emission radius evaluation, proved that the ecological sustainability, economic benefit, and carbon emission reduction capacity of agricultural waste biogas systems could be improved by rationally enlarging the resource collection distance. In order to improve the economic benefits of agricultural waste biogas production, biomass utilization enterprises tended to reduce the supply radius of agricultural waste feedstock as a way to reduce the supply cost of agricultural waste. The reason for this gap was that the emergy evaluation theory fully took into account the natural and social resource inputs to the biogas production system, and the results were more comprehensive compared to the economic radius. Therefore, the method of environmental radius assessment provided a new perspective to make a decision on the location planning of agricultural waste biogas utilization enterprises. Combined with specific production characteristics, the environmental radius assessment model can also be used for the sustainability assessment and optimization of other agricultural waste utilization systems.