The influence of data on Carbon Footprint quantification of agricultural raw materials - From a corporate perspective
Parviainen, Lumi Orvokki (2021)
Parviainen, Lumi Orvokki
2021
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2021121526208
https://urn.fi/URN:NBN:fi:amk-2021121526208
Tiivistelmä
Motivation towards comprehensive environmental and carbon accounting is a necessity for a corporation to achieve economic resilience. Understanding the functionality of the carbon footprint metric (CO2eq) is therefore essential.
This study enlightens the influence of data on carbon footprint quantification processes where the produced agricultural commodity is aimed for industrial processing as a valuable part of global food supply chain. The purpose of the study is to bring forth the escalading negative effect a poorly managed carbon footprint quantification process can have when implemented to further processes or long-term strategies.
Three of the main grains cultivated in Finland; Oat, barley and wheat, were chosen for the modelling in order to strengthen the integrity of the results. The purpose was to amend the already available and commonly used scientific data with the most recent information and knowledge in order to see the behavior of resulting carbon footprint estimation. All three grains showed a clear and progressing decrease in CO2eq when more accurate data was included in the modelling, with the difference being a significant –28.5 % at its best.
The veracity of a CO2eq quantification process is highly dependent on the quality of the included data. By focusing on the process details the end-result can be substantially changed, and when the same recurs in several raw materials from primary production the influence can be seen through the end-product in customer choices, product development and strategic planning. A low quality of the quantification process can thus create long term damages, both economic and ecological, through possible misguided decision making.
This study enlightens the influence of data on carbon footprint quantification processes where the produced agricultural commodity is aimed for industrial processing as a valuable part of global food supply chain. The purpose of the study is to bring forth the escalading negative effect a poorly managed carbon footprint quantification process can have when implemented to further processes or long-term strategies.
Three of the main grains cultivated in Finland; Oat, barley and wheat, were chosen for the modelling in order to strengthen the integrity of the results. The purpose was to amend the already available and commonly used scientific data with the most recent information and knowledge in order to see the behavior of resulting carbon footprint estimation. All three grains showed a clear and progressing decrease in CO2eq when more accurate data was included in the modelling, with the difference being a significant –28.5 % at its best.
The veracity of a CO2eq quantification process is highly dependent on the quality of the included data. By focusing on the process details the end-result can be substantially changed, and when the same recurs in several raw materials from primary production the influence can be seen through the end-product in customer choices, product development and strategic planning. A low quality of the quantification process can thus create long term damages, both economic and ecological, through possible misguided decision making.