Environmental footprint assessment method and system for agricultural products

Abstract

An environmental footprint assessment method and system for agricultural products, and the method comprises the following steps: obtaining agricultural original activity data of a target area through an Internet of Things technology, the agricultural original activity data including direct natural resource consumption data, direct emission data, secondary energy consumption data and resource material consumption data; acquiring background environment data of the target area; and setting an initial LCIA model, and improving the LCIA model by using the background environment data to obtain an LCIA evaluation model. According to the application, the Internet of Things platform technology is utilized to solve the problem that agricultural production LCI list data is missing, especially the first-hand primary activity data is not easy to obtain, and particularly, various types of sensors are installed on the first site of agricultural production activities to collect first-hand LCI primary activity data; so that the problem of data deviation caused by the fact that the LCI data is based on the secondary data type at present is solved.

Description

technical field [0001] This application relates to a method and system for evaluating the environmental footprint of agricultural products. Background technique [0002] The LCA (Life Cycle Assessment) method is one of the most important basic methodologies for the sustainable development assessment system and the realization of the goal of carbon neutrality. Concepts such as product environmental footprint, carbon footprint, and water footprint are all based on the LCA methodology. Due to the lack of relevant background data list LCI (life cycle inventory) in China and the lack of LCIA (Life Cycle Impact Assessment), an environmental impact assessment methodology based on my country's environmental background, the current domestic LCA research and the release of related product environmental footprints are very large. To a certain extent, it relies on foreign background databases and environmental impact assessment methods, resulting in large deviations. [0003] For the a...

AI Technical Summary

Problems solved by technology

[0005] In short, the existing domestic agricultural background LCI data is lacking, and traditional data collection methods cannot accurately collect data related to agricultural production activities. At the same time, the LCIA assessment method also lacks regional indicators suitable for my country's environmental background attributes, resulting in errors in product environmental footprint results. Conducive to the formulation of emission reduction policies and the ultimate goal of carbon neutrality

Images