Optimization Analysis of Yellowtail Kingfish (Seriola aureovittata) Land–Sea Relay Farming Based on Life Cycle Environment and Cost Assessment in Dalian, China

Abstract

The farming mode of yellowtail kingfish (Seriola aureovittata) in China tends to be mature. However, there are some problems with environmental impact and economic benefits that cannot be ignored in the sustainable farming process. This study focused on a yellowtail kingfish aquaculture company in Dalian, China, and carried out a life cycle environmental and cost assessment (LCA and LCC) study to evaluate the environmental impact and economic benefits of the yellowtail kingfish farming process. According to the LCA and LCC results, the environmental impact is significantly influenced by fossil energy consumption and feed production. Moreover, five improvement scenarios were proposed and discussed, and the results show that replacing coal and thermal power generation with wind power generation will comprehensively (scenario 5) reduce environmental impact by 82.14% and decrease costs by 24.25%. The results of this study can provide effective improvement scenarios for yellowtail kingfish aquaculture enterprises and enrich the international aquaculture LCA basic database with data support.

1. Introduction

Aquaculture plays a crucial role in securing global food supply and providing high-quality protein, with fish being among the most significant aquaculture species. In 2020, global aquaculture production hit a record high of 122.6 million tons, with aquaculture contributing 49.2% to global aquatic animal production, both reaching a record high [1]. As the world’s largest producer, China’s aquaculture output in 2020 reached 52.242 million tons [2], accounting for approximately 46.4% of the world’s aquaculture production. This sector significantly contributes to food supply, security, and high-quality protein supply. With the promotion of factors such as aquaculture and fishing technology, feed composition, aquaculture management, supply chain improvement, population growth, and rapid growth in fish farming production, its share in the global consumption of aquatic food increased from 48% in 1961 to 72% in 2019 [1]. In addition to meeting people’s needs for high-quality protein supplementation, its by-products are also used in feed, fuel, health products, pharmaceuticals, etc. [3].

Yellowtail kingfish (Seriola aureovittata) is a deep-sea marine species widely distributed in temperate and subtropical coastal waters [4]. It is known for its high nutritional value and it being rich in 16 amino acids required by the human body [5], especially its “EPA + DHA” content of up to 20.77% [6]. Yellowtail kingfish is one of the important aquatic products exported from China to Japan [7,8]; the domestic and international market consumption demand is strong. However, the breeding of yellowtail kingfish in China is still in its infancy, and the supply of juvenile fish is all from wild capture; thus, the yield is greatly affected by natural resources, and there is also limited research on the genus of yellowtail kingfish.

Yellowtail kingfish is suited for aquaculture models such as deep-sea cage and land-based industrial recirculating aquaculture. It is an excellent variety for the development of deep and distant sea fish aquaculture in China [5,9]. The land–sea relay aquaculture model integrates these methods to achieve efficient breeding with benefits such as rapid growth, disease resistance, and high-quality fish production. It reduces construction and operational costs and shortens aquaculture cycles, enhancing antioxidant capacity and immune resistance. Offshore fence aquaculture fully utilizes the natural sea environments, reducing aquaculture costs.

After investigating yellowtail kingfish farming enterprises in Dalian, enterprises have adopted the land–sea relay aquaculture mode. Seedlings are initially raised in a controlled factory park for temporary rearing and overwintering; then, they are transferred to deep-sea cages in ocean ranches for summer breeding. Due to the rapid growth of yellowtail kingfish, feed demand is high, resulting in a substantial feed cost. In addition, advanced breeding technology and significant manpower are also invested in breeding management, increasing overall farming expenses. At present, the current cultivation of yellowtail kingfish focuses on survival rates and feasibility, neglecting environmental impacts and economic costs, necessitating a comprehensive analysis and evaluation from environment and economy perspectives.

Currently, life cycle assessment (LCA) is the optimal method by which to evaluate the environmental impact of fish farming, focusing on researching environmental sustainability and friendliness. The LCA method can quantitatively evaluate environmental impacts across the entire life cycle production process of a product or service [10]. It is widely utilized to identify environmental impacts and analyze and compare the differences in environmental impacts caused by different industries, processes and technologies [11]. The LCA method examines resource and environmental issues comprehensively throughout production, making it a crucial tool for government departments and enterprises in formulating macro-environmental policies for industrial development [12]. Currently, LCA research in aquaculture has seen increasing interest. Regarding LCA research on fish farming, there are relatively rich research papers published abroad. In 2004, Papatryphon et al. [13] took the lead in evaluating the environmental impact of feed production for French rainbow trout. Subsequently, research mainly focused on the environmental impacts of single fish farming systems like Finnish rainbow trout [14] and global salmon (Salmo salar) farming [15]. With the improvement of aquaculture intensification and system complexity, research boundaries are expanding, comparing salmon farming environmental impacts across Norway, the United Kingdom, Canada, and Chile [16] and revealing regional production emission variations. In addition, comparative research of LCA has also analyzed freshwater rainbow trout, deep-sea cage European seabass (Dicentrarchus labrax) and land-based recirculating aquaculture systems for turbot (Scophthalmus maximus) [17]. Domestically, with the innovation of aquaculture technology, corresponding LCA research has been carried out on European seabass [18,19], large yellow croaker (Larimichthys crocea) [20], carp (Cyprinus carpio) [21,22,23], and tiger puffer (Takifugu rubripes) [24]. This research was found to be consistent with the results of Boxman et al. [25] through LCA research. Electricity and feed are key factors driving environmental impacts. Furthermore, energy consumption from coal and gasoline [24] is a significant environmental impact factor. Currently, China’s aquaculture heavily relies on coal and thermal power, elevating greenhouse gas emissions, with auxiliary equipment like water pumps and aerators that consume substantial energy, exacerbating carbon emissions and environmental pollution [26]. These studies provide valuable information for assessing China’s aquaculture environmental impact. However, China still needs to enhance its research on integrating LCA and Life Cycle Cost (LCC) to explore opportunities for reducing environmental impacts and economic costs. This will facilitate the coordinated development of both the environment and the economy.

In the study of LCA improvement design, the main focus is the evaluation of a technology, a process, a project or even a region to achieve the optimization of the advantages and disadvantages of different processes. Zhang et al. [27] conducted a full lifecycle LCA optimization analysis of LNG in different usage scenarios, with the goal of achieving minimum environmental impact, to determine the optimal layout structure of LNG. Bernier et al. [28] combined emission reduction cost estimation with LCA to properly handle the supply chain emissions in the NGCC natural gas combined cycle power generation process. Cao et al. [29] identified that LCA plays an important role in the formulation of sustainable production and consumption policies in the aquaculture industry.

In summary, this study employs LCA and LCC methods to analyze the environmental impact and economic benefits in yellowtail kingfish land–sea relay farming. By constructing a life cycle environmental impact and economic benefit list, we identify the life cycle environmental impact and economic costs in the process of land–sea relay farming. Through scenario analysis and proposed optimal improvement strategies, we offer scientific insights and decision-making support for coordinated development of environmental economy of yellowtail kingfish land–sea relay farming.

2. Materials and Methods

2.1. Goal and Scope Definition

LCA is a standardized method for assessing the environmental impact associated with a product or process [30]. Based on the LCA standards of ISO14040 [31] and ISO14044 [32], LCA consists of four steps: Goal and Scope Definition, Inventory Analysis, Life Cycle Impact Assessment, and Results [33].

The purpose of this study is to assess the economic costs and environmental impacts of the land–sea relay breeding process for yellowtail kingfish. Figure 1 illustrates the aquaculture yield of yellowtail kingfish from 2003 to 2022. A breeding enterprise in Dalian, China was selected as the research object, the system boundary studied is from cradle to gate, analyzing the land–sea relay farming mode and its effects on resources, energy, and the environment using the life cycle assessment (LCA) method, identifying the key environmental impact nodes and suggesting improvements to minimize the impacts and economic costs. In addition, to improve the environmental performance, the life cycle inventory (LCI) of the land–sea relay farming of yellowtail kingfish was established to obtain important information, enrich the aquaculture LCI database, and support LCA research. Based on LCA and LCC, the environmental impact and economic benefit analysis were carried out to provide optimization decision-making suggestions for the land–sea relay farming model. Dalian City, Liaoning Province was selected as the main research area, due to data availability and industry representativeness.

Based on a review of the literature and published LCA studies on aquaculture, 1 t live-weight yellowtail kingfish was used as the functional unit. The following describes the breeding process of yellowtail kingfish:

The Stage Description of Seed Rearing (Stage One): In May to June of the first year, artificial breeding of yellowtail kingfish was conducted in the workshop, and the seedling pond was disinfected with quicklime before feeding. Cultivated to a body length of 5–10 cm, the yellowtail kingfish were transported to the next breeding stage. During this period, a brine shrimp feed was the main feed, which consumed purified seawater and electricity. The primary emissions include carbon dioxide from energy consumption during power generation, as well as total nitrogen, total phosphorus, and chemical oxygen demand (COD) in wastewater produced during seedling breeding.

The Stage Description of Deep-Sea Cage Farming-1 (Stage Two/Stage Four/Stage Six): After the seed-rearing stage, deep-sea cage farming commenced, deploying cages in natural sea areas to prevent fish escape. Juvenile fish were carefully transported by live fish carts and boats to designated offshore natural cages to ensure their survival. Breeding periods typically span from August to October in the first year (Stage Two), mid-June to October in the second year (Stage Four), and mid-June in the third year (Stage Six). Subsequently, the juveniles were relocated to industrial recirculating aquaculture workshops for overwintering. During this process, primary feeding consists of sand eels sourced from fishing activities. Notably, gasoline powers ship navigation, and the use of live fish carts for seedling transport contributes significantly to fossil energy consumption. As fish weight increases with further farming, energy and feed usage are expected to rise accordingly.

The Stage Description of Industrial Recirculating Aquaculture-1 (Stage Three/Stage Five): As sea temperatures drop in winter, yellowtail kingfish are transferred to the industrial recirculating aquaculture workshop for overwintering, spanning from November of the first year to mid-June of the second year (Stage Three) and November of the second year (Stage Five). This stage requires substantial electricity and coal for maintaining optimal room and water temperatures essential for their growth. Floating pellets were used as the primary feed. While the Circular Aquaculture System (RAS) could effectively reuse the waste seawater, it still necessitates seawater inputs and wastewater discharge of containing total nitrogen, total phosphorus, and COD. During this stage, electricity and coal were predominantly consumed, and quicklime was used for sterilization. As the yellowtail kingfish gain weight, energy consumption and feed usage also increase accordingly. Figure 2 depicts the schematic diagram of the yellowtail kingfish farming process.

2.2. Inventory Analysis

Life cycle inventory analysis (LCI) refers to the process of listing inputs, outputs, and their relationships in the studied system after determining the goals and scope [34]. It is a relatively tedious step in LCA research, requiring the collection of input and output data from various production stages within the system boundary. By conducting on-site research and collecting relevant material consumption lists and expert consultations from the case enterprise, the material input and pollutant emission data within the entire system boundary were determined, and the LCI of the land–sea relay breeding stage of the yellowtail kingfish was calculated. The LCI of the breeding process of the yellowtail kingfish is shown in

Table 1. Life cycle inventory for each stage in the yellowtail kingfish process.

	Object/Stage	Stage 1	Stage 2	Stage 3	Stage 4	Stage 5	Stage 6
Input	Electricity (kwh)	-	-	312.89	-	1042.9	-
	Coal(kg)	101.5	-	2498.43	-	8328.12	-
	Feed (kg)	35	75	125	1320	1660	2400
	Quick lime (kg)	40	62.5	93.75	250	312.5	500
	Gasoline (L)	-	37.5	-	150	-	300
Output	CO2 (kg)	233.45	86.25	5746.389	345	19,154.676	690
	SO2 (kg)	0.86275	0.31875	21.236655	1.275	70.78902	2.55
	NOx (kg)	0.7511	0.2775	18.488382	1.11	61.628088	2.22
	Total N (kg)	0.28	-	0.43	-	1.44	-
	Total P (kg)	0.134	-	0.21	-	0.68	-
	COD (kg)	0.28	-	0.48	-	1.6	-

. The functional unit is the breeding of 1 ton of live-weight yellowtail kingfish. Input data for electricity, coal, seawater, fresh water, gasoline, and feed were sourced from the company’s actual production reports, while data for quicklime and disinfectants were obtained through interviews with engineers. Background data on energy and materials were extracted from the LCA for Experts 2021 professional database. The background data for pellet feed production was sourced from the Chinese Life Cycle Database (CLCD), a high-quality resource developed by Ike Co., Ltd., Chengdu, China, and aligns with the actual production conditions in China. In the output data, the emission results of CO₂, SO₂, and NO_X are from the Ecoinvent 3.7 database, and total nitrogen, total phosphorus, and COD were measured in the laboratory based on the wastewater discharged from the workshop.

Life cycle cost (LCC) is an economic analysis method. In the process of allocating environmental costs, the purpose of the life cycle cost method is to develop environmental coordination products and seek opportunities for improvement. The cost of yellowtail kingfish in the whole cycle from seed rearing to final breeding to adult fish is analyzed in detail, including environmental cost, reducing unnecessary cost, so as to improve the value of the whole life cycle of the product and reduce the total cost [35].

Life cycle cost (LCC) refers to all costs related to a product that occur during its economically effective use. The concept of LCC originated from the Swedish railway system, and in 1965, the US Department of Defense researched and implemented LCC technology. In the 1990s, Fabrychy et al. [36] proposed using LCC analysis to select the optimal production plan. Singh et al. [37] used ecological factors to incorporate environmental costs into LCC analysis for evaluating displays. In the past two decades, the application scope of LCC at home and abroad has become increasingly broad, including in multiple fields such as bridges [38], industrial products [39,40], sewage treatment [41], packaging [42], etc. There is relatively little research on food and agricultural by-products. Li et al. [43] evaluated the utilization mode of marine shellfish, but there is currently no life cycle cost analysis in the process of fish farming.

This study establishes the relationship between economic and environmental attributes to optimize the optimal configuration plan for the land–sea relay aquaculture of the yellowtail kingfish. Therefore, the product costs involved mainly include environmental related costs during the raw material acquisition stage and the product manufacturing stage. By conducting research on enterprises and consulting the literature, relevant cost data were obtained. The LCC of the breeding process of yellowtail kingfish is shown in

Table 2. List of Life Cycle Costs for yellowtail kingfish Farming Process.

Classification of Life Cycle Costs	Cost Components	Cost Budgeting
Conventional Costs	Electricity (USD/kwh)	0.075
	Coal (USD/kg)	0.307
	Feed (USD/kg)	1.923
	Quick lime (USD/kg)	0.077
	Gasoline (USD/L)	1.207
	Labor, depreciation of fixed assets (USD)	5.597
	Personal accident insurance (USD)	0.044

Note: The functional unit is for breeding 1 t live-weight yellowtail kingfish.

. According to Table 2, the cost of raising 1 kg of live-weight yellowtail kingfish is USD 9.23. Through visiting enterprises, we learned that the market price of yellowtail kingfish is USD 18.46.

2.3. Life Cycle Impact Assessment

At present, there are two commonly used environmental impact classification methods: the midpoint (CML2001) [44] and the endpoint method [45]. Since the midpoint method has strong scientific robustness, the midpoint method is used to illustrate the environmental impact [44]. The advantage of the midpoint method is that it focuses on the current environmental impact issues and can directly explain the contribution of inventory data to environmental impact issues. This study used LCA for Experts 10.5 software (academy version) to evaluate the environmental impact of the land–sea relay aquaculture process of yellowtail kingfish. The results were classified across stages and impact categories using the CML-IA-Jan.2016-world method, an updated version of CML2001.known for its precise data and comprehensive environmental impact indicators. This method focuses on energy consumption, pollution output, and ecological damage, and its characteristics are very suitable for this LCA. It was applied to feature and normalize the life cycle impact assessment steps for the land–sea relay aquaculture process of yellowtail kingfish. The main environmental issues and pollution prevention opportunities were analyzed, and the normalization results of different impact categories can be added up because their weights are equal. The feature results were used to analyze the environmental contributions of each impact category and aquaculture stage, ensuring the accuracy of the evaluation results. In addition, a comprehensive LCA analysis for evaluating the environmental impact of products requires extensive data, which are difficult to obtain. Meanwhile, the process is very complex, time consuming, and expensive, so only the following 11 LCA impact categories were considered in the assessment: Global Warming Potential (GWP, kg CO₂ eq.), Acidification Potential (AP, kg SO₂ eq.), Eutrophication Potential (EP, kg phosphate eq.), Photochemical Ozone Creation Potential (POCP, kg ethene eq.), Abiotic Depletion Potential (elements) (ADP, kg sb eq.), Abiotic Depletion Potential (fossil) (ADP, MJ), Freshwater Aquatic Ecotoxicity Potential (FAETP, kg DCB eq.), Human Toxicity Potential (HTP, kg DCB eq.), Marine Aquatic Ecotoxicity Potential (MAETP, kg DCB eq.), Ozone Layer Depletion Potential (ODP, kg R11 eq.) and Terrestrial Ecotoxicity Potential (TETP, kg DCB eq.).

Consistently with similar studies, this study used the life cycle cost method to evaluate the economic sustainability of various improvement plans [46,47]. Considering the same functional units, system boundaries, and scenario setting schemes considered in LCA, we conducted LCC analysis on all improvement schemes. Therefore, utilizing Equation (1), we calculated the total LCC value of the baseline scenario and each improvement plan. The calculation method for economic cost is the sum of energy cost, breeding cost, and raw material cost for the enterprise. The calculation formula can be expressed as:

$${LCC}_B=C_Z+C_H+C_K$$

(1)

In the formula, $C_Z$ is the operating cost of the enterprise, $C_H$ is the energy cost of the enterprise, $C_K$ is the breeding cost of the enterprise, and is the raw material cost of the enterprise.

The energy cost calculation formula for a certain enterprise can be expressed as:

$$C_Z=\left[\sum _g^G\left(e_g\times {\vartheta }_g\right)\right]\times X,\forall g,g\in G$$

(2)

In the formula, $C_Z$ is the energy cost of the enterprise, $e_g$ is the energy consumption per unit product of the type of energy, ${\vartheta }_g$ is the price of the $gth$ type of energy used, and $X$ is the production of yellowtail kingfish raised by the enterprise.

$$C_H=C_h\times X$$

(3)

The formula for calculating the breeding cost of a certain enterprise can be expressed as:

In the formula, $C_H$ is the breeding cost of the enterprise, $C_h$ is the unit product manufacturing cost of the enterprise, and $X$ is the breeding yield of the yellowtail kingfish of the enterprise.

The formula for calculating the raw material cost of a certain enterprise can be expressed as:

$$C_K=C_k\times X$$

(4)

In the formula, $C_K$ is the raw material cost of the enterprise, $C_k$ is the unit product manufacturing cost of the enterprise, and $X$ is the production output of the enterprise’s yellow striped catfish farming.

The economic cost of raising yellowtail kingfish by enterprises was clarified through the above formula.

2.4. Interpretation

In life cycle assessment, result interpretation is a comprehensive analysis based on the results of inventory analysis and impact assessment, aiming to reveal key issues in the product or service life cycle and comprehensively evaluate these results. It can be said that explaining the results is a crucial aspect. In this process, the integrity, sensitivity, and consistency of the data are considered to ensure the reliability and accuracy of the evaluation. By conducting in-depth analysis of the evaluation results and limitations, targeted suggestions and measures can be proposed to provide useful references for enterprises to improve product life cycle management and promote the achievement of sustainable development goals.

Moreover, in LCA research, uncertainty analysis of data quality is an important aspect for decision makers to judge the significance of differences in product or process options [48,49]. In LCA studies, the evaluation results are uncertain under the influence of different system boundaries, different technical levels, different data acquisition channels and different energy efficiency. Therefore, statistical methods are encouraged to analyze the uncertainty of evaluation results. Hung et al. [50] proposed that the Monte Carlo method can use probability distribution to quantify variability and uncertainty, which can help to reveal the impact of uncertainty.

2.5. Scenario Description

Baseline Scenario (S0): Based on the current survey data and scenarios, this study sets it as the baseline scenario (scenario S0). Based on the baseline scenario, make the following S1–S5 scenario improvement settings.

Scenario 1 (S1): Due to excessive feeding, the cultured organisms cannot be completely fed, and the remaining feed will be decomposed at the bottom of the circulating water pond and the cage to produce organic waste. These organic wastes undergo anaerobic decomposition under the action of microorganisms, producing gases such as carbon dioxide. Therefore, reducing the amount of feed can not only reduce the generation of organic waste, but also reduce carbon dioxide emissions. At present, about 10% of aqua-culture feed is directly wasted [51]. Therefore, in the improvement scenario setting of the breeding process of the yellowtail kingfish land–sea relay, S1 is set to reduce the feeding amount of feed by 10%.

Recent Scenario 1 (S2): In aquaculture, coal is not only used as fuel for heating equipment to maintain the water temperature of aquaculture ponds, but also as fuel for power supply. In addition, the heat generated by coal combustion can cause an increase in water temperature, which not only increases the metabolic rate of aquaculture organisms and their oxygen consumption, but also may lead to eutrophication of water bodies, causing problems such as excessive growth of algae. These issues not only affect the health and growth of aquaculture organisms, but may also have negative impacts on water quality. Therefore, reducing the use of coal is one way to reduce carbon dioxide. Reducing the use of coal can not only reduce carbon dioxide emissions, but also help improve water quality and aquaculture environment. Consequently, in the breeding process of the land–sea relay of the yellowtail kingfish, the recent scenario 1 (S2) is set to change from coal-fired power generation to photovoltaic power generation, and continue to maintain the use of thermal power.

Convert the coal used in the land–sea relay farming process of the yellowtail kingfish into standard coal according to the conversion coefficient in the Chinese national standard [52], and further convert it according to the coefficient of photovoltaic power generation to calculate the environmental impact. The comprehensive energy consumption calculation formula for converting hard coal into photovoltaic power generation can be expressed as follows:

$$Q_n={\displaystyle \frac{\left[{\sum }_m^M\left(Z_m\times r_m\right)\right]\times G_n}{E_n}}$$

(5)

In the formula, $Q_n$ is the usage of photovoltaic power generation, $Z_m$ is the energy consumption per unit product of the $mth$ energy source, $r_m$ is the conversion coefficient of the $mth$ energy source, $G_n$ is the total usage of the $nth$ energy source, and $E_n$ is the conversion coefficient of photovoltaic power generation of the $nth$ energy source.

Recent Scenario 2 (S3): Relying on a single fossil energy source (such as coal) not only increases environmental risks, but also limits the reliability and stability of energy supply. In the breeding process of the land–sea relay of the yellowtail kingfish, we added the recent scenario 2 (S3), changed coal power generation to wind power generation, and continued to maintain the use of thermal power. Convert the coal used in the land–sea relay farming process of the yellowtail kingfish into standard coal according to the conversion coefficient in the Chinese national standard [52], and then further convert it according to the coefficient of wind power generation and calculate the environmental impact. The comprehensive energy consumption calculation formula for converting hard coal into wind power generation can be expressed as follows:

$$Y_u={\displaystyle \frac{{\sum }_m^M\left(Z_m\times r_m\right)\times G_n}{E_n}}$$

(6)

In the formula, $Y_u$ is the usage of wind power generation, $Z_m$ is the energy consumption per unit product of the $m_{th}$ energy source, $r_m$ is the conversion coefficient of the $mth$ energy source, $G_n$ is the total usage of the $nth$ energy source, and $E_n$ is the conversion coefficient of wind power generation for the $uth$ energy source.

Forward Scenario 1 (S4): The long-term scenario focuses more on long-term trends and development potential, considering possible new technologies, policies, markets, and other factors in the future, predicting the impact of future aquaculture processes on the environment. In order to achieve this goal, some farmers have started to adopt other clean energy sources, such as photovoltaic power generation, wind power, etc., to replace traditional coal-fired boilers. Therefore, we set Forward Scenario 1 (S4) to change the use of both hard coal and thermal power in the baseline scenario to photovoltaic power generation. Convert the coal and thermal power used in the land–sea relay farming process of the yellowtail kingfish into standard coal according to the conversion coefficient in China’s national standard [52], and then further convert and calculate the environmental impact based on the coefficient of photovoltaic power generation. The comprehensive energy consumption calculation formula for converting both hard coal and thermal power into photovoltaic power generation can be expressed as follows:

$${Q_n}^{*}={\displaystyle \frac{\left[{\sum }_m^M\left(Z_m\times r_m\right)\right]\times G_n+\left[{\sum }_a^A\left(P_a\times r_a\right)\right]\times D_n}{E_n}}$$

(7)

In the formula, ${Q_n}^{*}$ is the usage of photovoltaic power generation, $Z_m$ is the energy consumption per unit product of the $mth$energy source, $r_m$ is the conversion coefficient of the $mth$ energy source, and$G_n$ is the total usage of the $nth$ energy source; $P_a$ is the energy consumption per unit product of the $ath$ energy source, $r_a$ is the conversion coefficient of the $ath$ energy source to standard coal, $D_n$ is the total usage of the $nth$ energy source, and $E_n$ is the conversion coefficient of photovoltaic power generation for the $nth$ energy source.

Forward Scenario 2 (S5): Forward Scenario 2 (S5) is set to change the use of both hard coal power generation and thermal power in the baseline scenario to wind power. The setting of this forward scenario aims to reduce carbon emissions during aquaculture, reduce environmental pressure, and enhance the sustainability and competitiveness of the aquaculture industry by shifting towards cleaner energy forms. Convert the coal and thermal power used in the land–sea relay farming process of the yellowtail kingfish into standard coal according to the conversion coefficients in China’s national standard [52], and then further convert and calculate the environmental impact based on the coefficients of wind power generation. The comprehensive energy consumption calculation formula for converting both hard coal and thermal power into wind power generation can be expressed as follows:

$${Y_u}^{*}={\displaystyle \frac{\left[\sum _m^M\left(Z_m\times r_m\right)\right]\times G_n+\left[{\sum }_a^A\left(P_a\times r_a\right)\right]\times D_n}{W_u}}$$

(8)

In the formula, ${Y_u}^{*}$ is the usage of photovoltaic power generation, $Z_m$ is the energy consumption per unit product of the $mth$ energy source, $r_m$ is the conversion coefficient of the $mth$ energy source, and $G_n$ is the total usage of the $nth$ energy source; $P_a$ is the energy consumption per unit product of the $ath$ energy source, $r_a$ is the conversion coefficient of the $ath$ energy source to standard coal, $D_n$ is the total usage of the $nth$ energy source, and $W_u$ is the conversion coefficient of photovoltaic power generation for the $uth$ energy source.

2.6. TOPSIS Method

Technique for order preference by similarity to ideal solution (TOPSIS) is a common multi-objective decision analysis and evaluation method that determines the order preference by the similarity with the ideal solution. This method was proposed by Hwang and Yoon [53] in 1981 and quickly began to be applied to the construction industry. It is one of the classic methods of multi-objective decision making. Based on given criteria and parameters, this method is used to evaluate the relative advantages and disadvantages of a set of alternative solutions and to make decisions and sort the distribution of individual alternative solutions. This method can evaluate a given set of alternative data without directly comparing the alternative data. The result is represented as the value of the scale between an ideal solution and a negative ideal solution, with the closest ideal solution and the farthest negative ideal solution being the best decision solution. The biggest advantage of the TOPSIS method is that it can consider the distance between the positive and negative ideal solutions of each index, and better reflect the difference of each index, so as to carry out the weighting ranking more pertinently. It can also consider the relative importance of indicators, and the importance of indicators can be adjusted by weighting coefficients to better reflect the actual situation.

The basic algorithm of the TOPSIS method is to evaluate the decision matrix and m alternatives for the evaluation of n criteria are given. The specific calculation steps are as follows:

Step 1: Polarity of the evaluation index is processed to obtain the polarity consistent matrix.

Step 2: The decision matrix is normalized.

Step 3: Determine positive and negative ideal solutions.

Step 4: Calculate the Euclidean distance between the evaluation object and the positive and negative ideal solutions.

Step 5: Calculate the relative proximity of each scheme to the optimal scheme.

Step 6: Comparing each scheme, the relative proximity is between 0 and 1. The closer it is to 1, the closer the user is to the optimal level of evaluation.

3. Results and Discussion

3.1. Characterization Results of Yellowtail Kingfish Land–Sea Relay Farming

In this study, the LCA characterization results for the land–sea relay farming process of yellowtail kingfish (

Table 3. Life cycle characterization results for six stages in the yellowtail kingfish land–sea relay farming process.

Category/Stage	Stage 1	Stage 2	Stage 3	Stage 4	Stage 5	Stage 6
GWP (kg CO2 eq.)	3.52 × 102	2.80 × 102	7.02 × 103	2.81 × 103	2.55 × 104	5.22 × 103
AP (kg SO2 eq.)	1.72	1.20	3.76 × 10	1.23 × 10	1.34 × 102	2.28 × 10
EP (kg phosphate eq.)	6.64 × 10−1	9.92 × 10−2	3.60	1.10	1.28 × 10	2.04
POCP (kg ethene eq.)	8.81 × 10−2	7.28 × 10−2	1.90	7.70 × 10−1	6.93	1.43
ADPe (kg Sb eq.)	3.08 × 10−6	1.13 × 10−5	6.33 × 10−5	8.94 × 10−5	2.65 × 10−4	1.68 × 10−4
ADPf (MJ)	3.12 × 103	2.66 × 103	7.11 × 104	2.22 × 104	2.51 × 105	4.16 × 104
FAETP (kg DCB eq.)	1.44 × 10−1	1.27	2.27	7.28	1.02 × 10	1.41 × 10
HTP (kg DCB eq.)	4.05	8.21	7.95 × 10	9.22 × 10	3.37 × 102	1.70 × 102
MAETP (kg DCB eq.)	2.88 × 103	6.75 × 103	5.28 × 104	8.60 × 104	2.48 × 105	1.58 × 105
ODP (kg R11 eq.)	8.47 × 10−11	2.13 × 10−14	3.05 × 10−10	3.19 × 10−9	4.02 × 10−9	5.81 × 10−9
TETP (kg DCB eq.)	4.23 × 10−2	1.16 × 10−1	8.22 × 10−1	1.10	3.52	2.05

) were calculated, providing comprehensive environmental emission data for the entire life cycle. Figure 3 provides an overview of the outcomes for each environmental impact category across the six farming stages.

Industrial recirculating aquaculture in Stage 5 plays a significant role in the environmental impact of the land–sea relay farming process for yellowtail kingfish, showing the highest impact in eight categories (excluding FAETP and ODP). Among these, AP contributes 64% (equivalent to 134 kg SO₂ eq.) and EP contributes 63% (equivalent to 12.8 kg phosphate eq.), ranking highest. In Stage 6, deep-sea cage farming contributes the highest proportions of ODP (43%, equivalent to 5.81 × 10⁻⁹ kg R11 eq.) and FAETP (40%, equivalent to 14.1 kg DCB eq.). The environmental impact of seedling cultivation (Stage 1), deep sea cage farming-1 (Stage 2), industrial recirculating aquaculture-1 (Stage 3), and deep-sea cage farming-2 (Stage 4) is lower than that of Stage 5 and Stage 6.

3.2. Normalization Results of Yellowtail Kingfish Land–Sea Relay Farming

The normalization results of LCA were calculated and the environmental impact ranking, main environmental issues, and opportunities for pollution prevention and control in different stages and categories of yellowtail kingfish farming were analyzed (

Table 4. Life cycle normalization results for six stages in the yellowtail kingfish land–sea relay farming process.

Category/Stage	Seed Rearing	Deep-Sea Cage Farming-1	Industrial Recirculating Aquaculture-1	Deep-Sea Cage Farming-2	Industrial Recirculating Aquaculture-2	Deep-Sea Cage Farming-3
GWP	8.35 × 10−12	6.62 × 10−12	1.66 × 10−10	6.66 × 10−11	6.04 × 10−10	1.24 × 10−10
AP	7.21 × 10−12	5.02 × 10−12	1.57 × 10−10	5.15 × 10−11	5.63 × 10−10	9.56 × 10−11
EP	4.20 × 10−12	6.28 × 10−13	2.28 × 10−11	6.98 × 10−12	8.10 × 10−11	1.29 × 10−11
POCP	2.40 × 10−12	1.98 × 10−12	5.17 × 10−11	2.10 × 10−11	1.88 × 10−10	3.89 × 10−11
ADP elements	8.55 × 10−15	3.14 × 10−14	1.75 × 10−13	2.48 × 10−13	7.33 × 10−13	4.67 × 10−13
ADP fossil	8.22 × 10−12	7.01 × 10−12	1.87 × 10−10	5.84 × 10−11	6.61 × 10−10	1.10 × 10−10
FAETP	6.11 × 10−14	5.38 × 10−13	9.61 × 10−13	3.09 × 10−12	4.34 × 10−12	5.95 × 10−12
HTP	1.57 × 10−12	3.19 × 10−12	3.08 × 10−11	3.58 × 10−11	1.31 × 10−10	6.62 × 10−11
MAETP	1.47 × 10−11	3.46 × 10−11	2.71 × 10−10	4.41 × 10−10	1.27 × 10−9	8.11 × 10−10
ODP	3.75 × 10−19	8.03 × 10−19	1.35 × 10−18	1.41 × 10−17	1.78 × 10−17	2.57 × 10−17
TETP	3.88 × 10−14	1.06 × 10−13	7.55 × 10−13	1.01 × 10−12	3.23 × 10−12	1.88 × 10−12

). ADP (fossil), GWP, MAETP, HTP, EP, and AP impact categories were selected, which are closely related to energy use, carbon emissions, wastewater emissions, and eutrophication; The other five environmental categories were integrated into “other categories” (Figure 4).

The environmental impact contribution rates of the four aquaculture stages are sequentially as follows: stage 5, stage 6, stage 3, stage 4, stage 2, and stage 1 (Table 4). Among the environmental impact categories, the contribution rate of MAETP was the highest, accounting for 31%, 58%, 31%, 64%, 36%, and 64% of the total environmental impact across the six farming stages, respectively. This indicates a significant use of fossil energy and electricity in the land–sea relay farming process of yellowtail kingfish, with coal and electricity being the main contributors. The case enterprise, located in northern China, relies heavily on thermal power, which exacerbates the energy use impact. During the seed rearing stage, energy is primarily consumed to maintain water temperatures for the growth of yellowtail kingfish. From an environmental impact perspective, global warming potential (GWP), abiotic resource depletion potential (fossil) (ADP fossil), and marine aquatic ecotoxicity potential (MAETP) are higher than other impact types. In the stages of deep-sea cage farming-1, deep-sea cage farming-2, and deep-sea cage farming-3, electricity is mainly used for freezing and maintaining brine shrimp. In the industrial recirculating aquaculture stage, energy is mainly consumed for pellet feed, maintaining winter aquaculture water temperatures, and operating water purification equipment. ADP and GWP are closely linked to electricity and fossil energy consumption, contributing significantly to the environmental impact across the six farming stages. Gasoline is used in various stages of deep-sea cage farming, such as transporting yellowtail kingfish to offshore areas via live fish carts and boats. These transporting processes increase the environmental impact, particularly in terms of HTP contributions. The environmental impacts of AP and EP are consistent with other aquaculture LCA studies, primarily influenced by emissions of total nitrogen, total phosphorus, and COD from aquaculture wastewater, further amplifying the HTP impact.

3.3. Uncertainty Analysis

In this study, Crystal ball numerical simulation software 11.1 version was used to carry out Monte Carlo simulation analysis on the input and output list data of the whole life cycle of yellowtail kingfish farming process to evaluate the impact of uncertainty. The statistical hypothesis was based on the triangular distribution model. The number of simulations was 1000 times, and the confidence interval was set to 95%. From the simulation results, the trend of the uncertainty interval was relatively close, and the overall ranking of each stage did not change much (

Table 5. Monte Carlo simulation results for the four stages of the yellowtail kingfish farming process.

Stages	Normalization Results (yr)	Monte Carlo Simulation Results
		Confidence interval 95% (yr)	Mean (yr)	SD (yr)
Stage 1	4.68 × 10−11	4.52 × 10−11–4.84 × 10−11	4.68 × 10−11	9.61 × 10−13
Stage 2	5.97 × 10−11	4.51 × 10−11–4.84 × 10−11	4.68 × 10−11	9.72 × 10−13
Stage 3	8.89 × 10−10	4.52 × 10−11–4.84 × 10−11	4.68 × 10−11	9.78 × 10−13
Stage 4	6.86 × 10−10	4.53 × 10−11–4.85 × 10−11	4.69 × 10−11	9.47 × 10−13
Stage 5	3.51 × 10−9	4.53 × 10−11–4.84 × 10−11	4.69 × 10−11	9.45 × 10−13
Stage 6	1.27 × 10−9	4.51 × 10−11–4.84 × 10−11	4.68 × 10−11	9.53 × 10−13

).

3.4. Scenario Analysis

The land–sea relay farming model integrates industrial recirculating aquaculture with deep-sea cage farming to enhance farming efficiency but also faces environmental and economic challenges, such as high investment cost in both inland and marine facilities, including recirculating aquaculture systems, deep-sea cages, water pump equipment, etc., all of which require a large amount of capital investment. Meanwhile, high technical proficiency is crucial due to diverse environmental conditions, particularly in managing water quality. Moreover, transporting products between land and sea increases logistics costs and risks. Therefore, the environmental concerns caused include pollution from aquaculture byproducts, disease risks to marine ecosystems, and impacts on coastal areas such as increased water consumption and habitat disruption, etc.

Based on the above analysis, the optimization design of the land–sea relay aquaculture model should prioritize minimizing environmental impact while maximizing economic performance. Section 2.5 outlines five improvement scenarios, starting with the key environmental issues in the enterprise’s breeding process through on-site research and other methods. The results indicate that feed quantity and coal usage significantly impact the environment. Additionally, the study evaluates total energy consumption, comparing the conversion coefficient of hard coal into standard coal according the Chinese national standard [52] and explores optimizing coal conversion into thermal, photovoltaic, and wind power. Economically, product cost is crucial, reflecting enterprise performance. An assessment of production costs versus profits under varying energy constraints informs economic strategy.

Scenario 1: In the yellowtail kingfish land–sea relay farming process, approximately 10% of aquaculture feed is currently directly wasted. In the improvement scenario, a 10% reduction in feed intake was recalculated using CML-IA-Jan.2016 method to normalize the environmental impact results. The analysis revealed that decreasing feed intake by 10% led to a 0.69% decrease in environmental impact and reduced economic costs by 7.23%.

Similar to Scenario 1, the environmental impact results were recalculated, and conducted an economic cost analysis of Scenario 2–5 using formulas Equations (5)–(8) in Section 2.5. The results are as follows.

Scenario 2: Recent improvement scenarios have focused on improving aquaculture in the short term, particularly transitioning from coal-based to photovoltaic power while maintaining some thermal power applications. The emphasis is on evaluating current environmental impacts of aquaculture and identifying achievable improvement measures in the short term. Strategies include improving production processes, optimizing raw materials, and enhancing energy efficiency to reduce emissions and resource consumption. These efforts resulted in an 87.46% reduction in environmental impact but alongside a 47.18% increase in economic costs.

Scenario 3: By reducing dependence on coal, promoting the adoption of renewable energy sources like solar, wind, and biomass is encouraged. These alternatives not only cut carbon dioxide emissions but also helps to achieve energy supply diversity and sustainability. The scenario resulted in an 87.51% decrease in environmental impact and a 24.15% reduction in economic costs.

Scenario 4: In pursuit of long-term goals, some farmers were adopting clean energy sources that do not generate pollutant emissions during operation, which promote green and sustainable aquaculture. This scenario resulted in a 60.79% decrease in environmental impact but a 47.68% increase in economic costs.

Scenario 5: Scenario 5, akin to Scenario 4, focuses on transitioning to cleaner energy sources, specifically exploring the environmental and economic impacts of wind power generation. This transition resulted in an 82.14% decrease in environmental impact and a 24.25% reduction in economic costs.

In order to further compare the proportion of baseline scenarios and five improvement scenarios in both environmental and economic aspects, a comparative analysis was conducted using a pyramid diagram as an example, as shown in Figure 5:

3.5. TOPSIS Results

This study combines LCA with the TOPSIS model, first using LCA to calculate the environmental and economic evaluation results of each scheme, and then using the TOPSIS model to evaluate the baseline and improvement scenario schemes of the land–sea relay breeding process of yellow striped catfish in order to identify the best improvement scheme. The normalized environmental impact results of four improved design scenarios in the near and forward were calculated, and we analyzed the overall environmental impact during the yellowtail kingfish farming process. The evaluation results are shown in

Table 6. TOPSIS results for improving scenario design S1–S5.

Scenario		S0	S1	S2	S3	S4	S5
Euclidean Distance	${D_i}^{+}$	5.42 × 10−1	5.41 × 10−1	1.90 × 10−1	1.30 × 10−1	4.63 × 10−1	2.27 × 10−1
	${D_i}^{-}$	1.54 × 10−1	1.92 × 10−1	5.39 × 10−1	5.45 × 10−1	1.20 × 10−1	3.61 × 10−1
Relative Proximity		2.21 × 10−1	2.62 × 10−1	7.39 × 10−1	8.07 × 10−1	2.06 × 10−1	6.14 × 10−1

:

According to the results of TOPSIS in Table 6, although S1 reduced the environmental impact caused by aquaculture and the operating costs of enterprises in the five scenario scenarios, the overall decline trend was not significant, with 0.69% and 7.23%, respectively. From the perspective of recent scenarios, the relative closeness of S3 is close to 1, and TOPSIS ranks first, making it the optimal improvement plan. Due to the inability to directly improve thermal power soon, research has shifted the use of both hard coal and thermal power to wind power from a long-term perspective, ranking second. Therefore, wind power generation is considered to be the most long-term energy alternative. In addition, research has shown that both S2 and S4 use cleaner energy compared to traditional fuels and reduce environmental impact, but they increase the operating costs of the enterprise. Each enterprise needs to adjust and replace energy according to the actual situation.

The aquaculture industry makes a significant contribution to global food security, but its environmental impact should not be overlooked. The International Energy Agency (IEA) statistical analysis shows that the share of photovoltaic and wind power generation has increased worldwide, while other forms of renewable energy are less common. The most considered aquaculture systems are solar and wind energy. Currently, a large amount of funds is being invested in the development of new technologies related to solar energy. In this scenario, photovoltaic (PV) technology provides an affordable energy source and is not a problem in marine aquaculture, with suitable installation space [54]. In addition, in recent years, with the significant increase in wind energy development, the cost has also increased due to harsh environmental conditions. Compared to other energy development methods, the layout and operation of wind power in the marine environment have less impact on the marine ecosystem. The research results of this study are consistent with those of Garacia et al. [19], indicating that the use of wind power can greatly reduce energy consumption and environmental impact on fish farming processes.

This study determined the optimization model and algorithm for the land–sea relay farming of yellowtail kingfish. Using a Dalian-based enterprise as a case study, the study conducts scenario-based optimization. By collecting and analyzing real production data, with the optimization goal of minimizing comprehensive energy consumption and product cost, four improvement scenarios were proposed for targeting both current and future goals. Through systematic optimization and balancing enterprise costs with energy consumption, the optimal improvement scenario was identified, offering technical backing for optimizing yellowtail kingfish land–sea relay farming.

In addition, there are some limitations to this study. The investment cost, maintenance, and effective sunlight of photovoltaic (PV) systems, especially in northern China, make photovoltaic power generation unstable, which can be catastrophic for aquaculture. Wind power is a green energy source, but it has high initial investment, long payback period, high maintenance cost, strong intermittency, and instability. Therefore, its applicability still needs further research. Wind turbines are typically located near bird migration routes or habitats and may pose a threat to birds and other flying objects, leading to ecological imbalances. These links still need further consideration in actual production and construction. This study only focuses on Dalian City in northern China. In the future, further data collection from other regions should be conducted to make the data more comprehensive.

4. Conclusions

This study proposes an evaluation model combining environmental impact and economic benefits, and implementing LCA in aquaculture identifies resource consumption, energy use, waste emissions, and environmental pollution, offering insights for pollution prevention and sustainable enterprise development. The improvement measures proposed in this study can be adopted, such as establishment of an integrated management system for electricity, wind energy, and solar energy; we recommend implementing Pre-LCA for optimizing parameters in future technology R&D and constructing a comprehensive multi-level nutrient aquaculture system using innovative models like “fish-vegetable symbiosis” and “integrated fishing and lighting” to enhance energy utilization efficiency.

The specific contributions are as follows:

(1).

Assist aquaculture decision makers to formulate comprehensive and effective strategies to improve environmental quality, and provide measures and recommendations for the coordinated development of environment and economy to achieve sustainable development goals.

(2).

Provide effective improvement scenarios for aquaculture enterprises to promote the environmental performance and economic benefits. Focus on achieving carbon neutrality, provide key information and feasible suggestions for effective carbon reduction pathways and sustainable development, and advocate for achieving long-term sustainability.

(3).

Enrich the international aquaculture LCA basic database with valuable data support for aquatic LCA research. In addition, other LCA researchers could use this data to conduct comparative studies on environmental performance such as industrial recirculating aquaculture and deep-sea cage farming.