Life Cycle Assessment Method
AGRIBALYSE® data is based on the Life Cycle Assessment (LCA) method. To understand the data, you need to know the basic principles of LCA.
Last updated
AGRIBALYSE® data is based on the Life Cycle Assessment (LCA) method. To understand the data, you need to know the basic principles of LCA.
Last updated
The Life Cycle Assessment method is a method recognized and used internationally by the scientific community, private actors and political powers. It is framed by the ISO 14044 standard. It is recommended in particular because it is the only standardized, multi-criteria, multi-stage environmental assessment methodology applicable to all economic sectors.
LCA methodology is essential for the evaluation of food products, but does not claim to cover all the dimensions and all the complexity of food systems.
LCA is a method for quantifying the impact of a product on the environment throughout its life cycle (e.g. agriculture, transport, packaging, etc.). In addition to being a method taking into account all stages of the product life cycle, this method takes into account several major environmental issues (climate change, water quality, air quality, impact on soils ...) and not just the climate.
At each stage of the chain, material, energy and pollutant emission balances are produced and aggregated in the form of a set of environmental indicators: 16 indicators are provided for each product. These are the indicators recommended by the European Commission (Product Environmental Footprint project, see table below).
Impact indicators
Details
Units
Climate change
The best known indicator, corresponds to the modification of the climate, affecting the global ecosystem.
kg CO2 eq
Particulate matters
Particulate matters enter organisms, especially through the lungs. They have an effect on human health.
disease incidence
Water use
Corresponds to the consumption of water and its depletion in certain regions. This category takes into account scarcity (it has more impact of consuming a liter of water in Morocco than in Brittany).
m3 world eq
Resource use, fossils
Corresponds to the depletion of non-renewable energy resources: coal, gas, oil, uranium, etc.
MJ
Land Use
Land is a finite resource, which is shared between "natural" (forest), productive (agriculture) and urban environments. Land use and habitats largely determine biodiversity. This category therefore reflects the impact of an activity on land degradation, with reference to "the natural state".
point
Resource use, minerals and metals
Corresponds to the depletion of non-renewable mineral resources: copper, potash, rare earths, sand, etc.
kg Sb eq
Ozone depletion
The ozone layer is located at high altitude in the atmosphere, it protects from solar ultraviolet rays. Its impoverishment increases the exposure of all living beings to these negative radiations (carcinogens in particular).
kg CFC-11 eq
Acidification
Result of chemical emissions in the atmosphere which are redeposited in ecosystems. This problem is known in particular through the phenomenon of acid rain.
mol H+ eq
Ionizing radiation, effect on human health
Corresponds to the effects of radioactivity. This impact corresponds to the radioactive waste resulting from the production of nuclear electricity.
kBq U235 eq
Photochemical ozone formation, effect on human health
Corresponds to a deterioration in air quality, mainly via the formation of low altitude fog called "smog". It has negative health consequences.
kg NMVOC eq
Eutrophication, terrestrial
As in water, terrestrial eutrophication corresponds to an excessive enrichment of the environment, in nitrogen in particular, leading to an imbalance and a depletion of the ecosystem. This mainly concerns agricultural soils.
mol N eq
Eutrophication, marine
Corresponds to an excessive enrichment of natural environments in nutrients, which leads to proliferation and asphyxiation (dead zone). It is this phenomenon which is at the origin of green algae.
kg N eq
Eutrophication, freshwater
Corresponds to an excessive enrichment of natural environments in nutrients, which leads to proliferation and asphyxiation (dead zone). It is this phenomenon which is at the origin of green algae. It can be found in rivers and lakes too.
kg P eq
A single score is also proposed: it is the "single EF score" recommended by the European Commission, calculated with weighting factors for each of the indicators; the weighting takes into account both the relative robustness of each of these indicators and the environmental challenges.
For more information on the “single EF score”, refer to the documentation of the European Commission.
The European Commission has established a classification of indicators, based on the robustness and the level of scientific consensus of the indicators.
Data Quality Ratio
A quality score - the Data Quality Ratio (DQR) - from 1, very good, to 5, very poor - is associated with each agricultural and food product for which Agribalyse provides life cycle inventories and impact indicators. The European Commission recommends caution in using data with DQRs greater than 3. In the AGRIBALYSE database, 67% of the data have a DQR judged to be good or very good (1 to 3).
Limitations and needs for evolution of the LCA methodology
In the current state of knowledge, the usual LCA indicators do not correctly reflect all the environmental stakes. Among the main challenges for the food sector, the limits and needs for evolution of LCA indicators, in particular on:
Water consumption at the agricultural level
Storage and release of carbon in soils
Impact of phytosanitary products on human and ecosystem health
Biodiversity
In short-term vision, this means that LCA cannot be used as a single measure to compare the environmental impacts of different production systems (organic farming versus conventional farming for example).
Agribalyse® work systematically seeks to use available international standards (FAO, European Commission, ISO, etc.). The data is designed to evolve in line with new knowledge, improved methodologies and the integration of new products. Regular updates are carried out (every 18/24 months). Although every effort is made to ensure data quality, several sources of uncertainty remain.
Uncertainty concerning the data used to calculate impacts is highlighted by a reliability score associated with each piece of data (the DQR, or Data Quality Ratio). This score (from 1, very good quality, to 5, poor quality) is calculated according to the method recommended by the European Commission. It is not possible at this stage to provide quantitative uncertainty data (standard deviation): estimating these uncertainties would require unavailable data.
Uncertainty concerning the models used to calculate impacts through a robustness classification of indicators drawn up by the European Commission. (see previous paragraph).
