A few weeks ago, we reported that the study “Procedure for estimating variances and covariances of GHG emissions and inventories”, carried out by our team of researchers, was recognized and published by the international scientific journal Carbon Management.
To help understand the purpose of this study and the important advance it represented, in the sense of making impact data increasingly reliable, we present Prof. Dr. Ernesto Marujo, professor at ITA and member of the DEEP expert council, who brings a hypothetical example, based on real situations:
“A company has four sources of carbon emissions: burning bagasse, straw, other waste and LPG. According to on-site measurements, during one year, these sources generated, respectively, 100, 200, 300 and 400 kg of CO2e. Under normal conditions, all these average measurements are subject to an uncertainty of 20%.
The average total emission is actually equal to the sum of the average emissions from all sources – 1000 kg. A simplistic and very common treatment is to consider that the total emission is subject to the same uncertainty for each component, that is, 20%. But, considering that the emission value of each source is independent of that generated by another source, we were able to calculate the true uncertainty in the total emitted: 11%.
Considering 95% confidence intervals, simplistic calculations would point to an emission between 608 and 1392 kg of CO2e. Using the appropriate methodology proposed by the study, we arrived at a significantly more accurate range, between 785 and 1215 kg CO2e.”
“There is an irreversible trend of increasing demand for accuracy and reliability in impact information. This study shows that Deep has a pioneering role in preparing companies for this future”, explains Arthur Covatti, Co-founder and CEO of DEEP.
