Method for evaluating carbon footprint of undaria pinnatifida culture system

Abstract

The invention belongs to the technical field of life cycle evaluation methods, and relates to a method for evaluating carbon footprint of an undaria pinnatifida culture system. Firstly, the life cycle boundary of the undaria pinnatifida culture system is determined, the life cycle boundary comprises all stages from seedling culture, temporary culture, culture to harvesting, and the recovery and treatment process of waste plastic culture ropes and floating balls is considered. Secondly, data such as material input, energy consumption and waste discharge of the system are collected, and life cycle list analysis is carried out; then, modeling is carried out on the breeding system by utilizing GaBi software, and the carbon footprint and other environmental influences of the breeding system are quantified by adopting a ReCiPe 2016v1.1 Midpoint (H) method; and finally, comprehensively analyzing the result, identifying key links and substances influencing carbon emission, and proposing corresponding optimization and improvement measures. The invention not only provides a scientific carbon emission reduction path for the seaweed culture industry, but also provides a theoretical basis and technical support for improving the environmental sustainability of the industry.

Description

Technical Field

[0001] The present invention belongs to the technical field of life cycle assessment methods and relates to a method for evaluating the carbon footprint of a kelp cultivation system, specifically a method for evaluating the carbon footprint of a kelp cultivation life cycle, including the recovery and treatment of discarded cultivation ropes and floats. Background Art

[0002] As global climate change becomes increasingly severe, reducing greenhouse gas emissions has become a global concern. Agriculture, particularly agricultural production systems, is a significant source of greenhouse gas emissions. In recent years, seaweed has garnered widespread attention as an environmentally friendly crop with the potential to reduce carbon emissions. Seaweed cultivation requires far less land, freshwater, and fertilizer than traditional agricultural crops, and it absorbs nitrogen and phosphorus from seawater, mitigating marine eutrophication.

[0003] The environmental impact of seaweed farming is generally considered to be minimal, but research indicates that the use of plastic farming ropes and buoys, as well as the disposal of these waste, is a major source of carbon emissions from seaweed farming. Existing life cycle assessment (LCA) studies have not fully considered the recycling and reuse of these waste plastics, and therefore fail to accurately reflect the environmental impact of seaweed farming. Furthermore, factors such as the location of aquaculture (e.g., nearshore versus offshore) and the production methods of plastic materials can significantly influence aquaculture's carbon footprint.

[0004] Therefore, there is an urgent need for an LCA method that can comprehensively evaluate greenhouse gas emissions during seaweed farming, taking into account the recycling and treatment of waste plastics, so as to more accurately quantify its environmental impact and provide theoretical support and technical solutions for the green development of the seaweed farming industry. Summary of the Invention

[0005] To address these issues, the present invention provides a method for evaluating the carbon footprint of kelp cultivation systems based on a life cycle assessment (LCA) approach. This method comprehensively assesses the carbon emissions of seaweed cultivation by combining factors such as the recycling of waste plastics during cultivation, different waste plastic treatment methods, the production paths of different plastic materials, and the choice of cultivation environment (e.g., nearshore versus offshore).

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A method for evaluating the carbon footprint of a kelp cultivation system comprises the following steps:

[0008] (1) Determination of objectives and scope: The present invention selects "production of 1 ton of wet weight of kelp" as the functional unit, which is a standard unit for measuring the carbon footprint of the aquaculture process. The selection of functional units ensures that the research results are comparable and can be compared with the production processes of other crops or foods. The system boundary of the present invention is "from cradle to gate", which covers the process from seaweed seedling cultivation, temporary breeding, cultivation to harvesting. In this process, the focus is on the use of plastic aquaculture ropes and buoys, and their waste disposal methods. In addition, the system boundary also includes the treatment process of waste generated during the aquaculture process (such as waste plastics, wastewater, etc.). The present invention excludes the construction of aquaculture facilities, equipment maintenance, and subsequent processing and transportation links in the evaluation.

[0009] (2) Inventory analysis (LCI): Based on the field survey data of kelp farms, a detailed life cycle inventory was constructed. The life cycle inventory mainly includes the raw material input, energy consumption, and waste generation and treatment of the seaweed cultivation process, including seedling cultivation, temporary cultivation, growout, and harvesting.

[0010] (3) Impact Assessment: This paper uses the ReCiPe v1.10 Midpoint(H) method to assess the impact of greenhouse gas emissions during the life cycle. This method quantifies the impact of greenhouse gas emissions on the global warming potential (GWP) in kgCO2e. The carbon footprint of a product is calculated as follows:

[0011] E GHG =∑(AD i,j ×EF j )

[0012] Among them, E GHG is the carbon footprint of the product, kgCO2e;

[0013] AD i,j is the activity level of activity j in process i, in kg or kWh; for process i, 1 represents seedling cultivation, 2 represents temporary cultivation, 3 represents grow-out, and 4 represents harvesting; for activity j, 1 represents electricity production, 2 represents fertilizer NaNO3 production, 3 represents fertilizer KH2PO4 production, 4 represents seawater introduction, 5 represents wastewater treatment, 6 represents aquaculture rope production, 7 represents float production, 8 represents fixed base production, 9 represents diesel production and combustion, 10 represents waste aquaculture rope treatment, 11 represents waste float treatment, and 12 represents waste fixed base treatment.

[0014] EF j is the greenhouse gas emission factor corresponding to activity j, kgCO2eq / kg or kgCO2eq / kWh.

[0015] (4) Results Analysis: This paper combines the results of inventory analysis and impact assessment to comprehensively assess the carbon footprint of seaweed aquaculture and conducts a scenario analysis. Using Monte Carlo simulation, the paper analyzes the uncertainty of key parameters, thereby obtaining a probability distribution of the carbon footprint results and providing optimization recommendations based on the results.

[0016] Beneficial effects of the present invention:

[0017] (1) Through a life cycle assessment (LCA) approach, the present invention can comprehensively and accurately quantify greenhouse gas emissions (carbon footprint) throughout the seaweed aquaculture process. The present invention incorporates the recycling and disposal of discarded aquaculture ropes and buoys, providing a more comprehensive carbon footprint assessment.

[0018] (2) The carbon emission assessment and optimization strategy proposed in this invention has important guiding significance for seaweed farming enterprises and also provides a scientific decision-making basis for policy makers. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 Schematic diagram of the carbon footprint assessment boundary of kelp cultivation system. DETAILED DESCRIPTION

[0020] The specific implementation of the present invention is further explained in conjunction with the technical solution and the accompanying drawings.

[0021] This example systematically analyzes the carbon footprint of kelp cultivation using a life cycle assessment (LCA) approach, specifically the impact of the recycling and disposal of discarded plastic cultivation ropes and floats on carbon emissions. The life cycle encompasses seaweed seedling cultivation, temporary aquaculture, growout, harvesting, waste plastic recycling, and associated energy consumption. Carbon emissions from raw materials and transportation are disregarded, and all data are derived from a survey of seaweed farms in a specific location.

[0022] In the seaweed cultivation process, waste plastics mainly come from cultivation ropes and buoys. The impact of waste plastic recovery rate, different waste plastic treatment methods (recycling, incineration, landfill) and aquaculture material production process (polyethylene production path) on carbon footprint was analyzed.

[0023] The IPCC 2013 Global Wastewater Treatment Project (GWP) 100a was selected as the impact assessment method for this example. Using GaBi software modeling and combining it with life cycle inventory data from the LCA model, we derived carbon footprint results for different waste plastic treatment methods, plastic production pathways, recycling rates, and aquaculture environments. The results showed that the carbon footprint per wet ton of seaweed produced varied under different scenarios, as follows:

[0024] Without considering the disposal of waste plastics, the average carbon footprint of kelp is 89.5 kg CO2e / t;

[0025] In the case of waste plastic recycling, the carbon footprint is reduced to 41.4kgCO2e / t;

[0026] In the case of incineration of waste plastics, the carbon footprint is 100.1 kg CO2e / t;

[0027] In the case of landfill disposal of waste plastics, the carbon footprint is 92.0 kg CO2e / t;

[0028] Under the current scenario of waste aquaculture rope and float disposal at a certain location, the carbon footprint is 56.4kgCO2e / t.

[0029] This example also examined the impact of different plastic production pathways on carbon footprints. It was found that polyethylene produced using coal-based methanol-to-ethylene (CMTE) had a significantly higher carbon footprint than polyethylene produced using naphtha-to-ethylene (OTE) pathways. Using low-carbon production pathways, such as OTE, can significantly reduce carbon emissions from seaweed cultivation.

[0030] The impact of aquaculture environments (nearshore vs. offshore) on carbon footprints was also analyzed. Results showed that offshore aquaculture typically has a carbon footprint 1.8 to 2.3 times greater than offshore aquaculture. This is primarily due to the increased use of plastic materials and higher fuel consumption. Diesel consumption increases significantly with increasing distance from shore, further driving up carbon emissions.

[0031] This study quantified the carbon footprint of seaweed farming and identified its main contributors, including the use of plastic farming ropes and buoys, waste plastic disposal methods, and plastic production processes. By optimizing these factors, carbon emissions from seaweed farming can be effectively reduced, thereby improving the environmental sustainability of seaweed farming. This research helps inform green development plans for the seaweed farming industry and promote its role in global climate change response.

Claims

1. A method for evaluating the carbon footprint of a kelp cultivation system, characterized in that: The following steps are involved: (1) Objective and scope determination: "producing 1 ton of wet weight of kelp" was selected as the functional unit, which is the standard unit for measuring the carbon footprint of the aquaculture process; the system boundary was "cradle to gate", which covers the process from seaweed seedling cultivation, temporary cultivation, grow-out to harvesting; in this process, the focus was on the use of plastic aquaculture ropes and buoys, and their waste disposal methods; in addition, the system boundary also included the treatment process of waste generated during the aquaculture process; the construction of aquaculture facilities, equipment maintenance, and subsequent processing and transportation were excluded from the assessment; (2) Inventory analysis (LCI): Based on field survey data of kelp farms, a detailed life cycle inventory was constructed; the life cycle inventory included raw material inputs, energy consumption, and waste generation and treatment during the seaweed cultivation process, including seedling raising, temporary rearing, growing, and harvesting; (3) Impact assessment: The ReCiPe v1.10 Midpoint (H) method was used to assess the impact of greenhouse gas emissions during the life cycle. The impact of greenhouse gas emissions on the global warming potential (GWP) was quantified in kgCO2e. The carbon footprint of the product was calculated as follows: AND GHG =∑(AD i,j ×EF j ) Among them, E GHG is the product carbon footprint, kgCO2e; AD i,j is the activity level of activity j in process i, kg or kWh; where, for process i, 1 represents seedling cultivation, 2 represents temporary cultivation, 3 represents grow-out, and 4 represents harvest; for activity j, 1 represents electricity production, 2 represents fertilizer NaNO3 production, 3 represents fertilizer KH2PO4 production, 4 represents seawater introduction, 5 represents wastewater treatment, 6 represents aquaculture rope production, 7 represents float production, 8 represents fixed base production, 9 represents diesel production and combustion, 10 represents waste aquaculture rope treatment, 11 represents waste float treatment, and 12 represents waste fixed base treatment; EF j is the greenhouse gas emission factor corresponding to activity j, kgCO2eq / kg or kgCO2eq / kWh; (4) Result analysis: Combining the results of inventory analysis and impact assessment, the carbon footprint of seaweed aquaculture was comprehensively evaluated, and a scenario analysis was conducted. The uncertainty of key parameters was analyzed through the Monte Carlo simulation method to obtain the probability distribution of the carbon footprint results, and optimization suggestions were made based on the results.

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