TY - JOUR
T1 - Increasing Precision in Greenhouse Gas Accounting Using Real-Time Emission Factors: A Case Study of Electricity in Spain
AU - Patel, Martin K.
AU - Méndez, Gara Villalba
AU - Chavez, Abel
AU - Spork, Charlie C.
AU - Gabarrell Durany, Xavier
PY - 2015/6/1
Y1 - 2015/6/1
N2 - © 2014 by Yale University. For many companies, the greenhouse gas (GHG) emissions associated with their purchased and consumed electricity form one of the largest contributions to the GHG emissions that result from their activities. Currently, hourly variations in electricity grid emissions are not considered by standard GHG accounting protocols, which apply a national grid emission factor (EF), potentially resulting in erred estimates for the GHG emissions. In this study, a method is developed that calculates GHG emissions based on real-time data, and it is shown that the use of hourly electricity grid EFs can significantly improve the accuracy of the GHG emissions that are attributed to the purchased and consumed electricity of a company. A model analysis for the electricity delivered to the Spanish grid in 2012 reveals that, for companies operating during the day, GHG emissions calculated by the real-time method are estimated to be up to 5% higher (and in some special cases up to 9% higher) than the emissions calculated by the conventional method in which a national grid EF is applied, whereas for companies operating during nightly hours, GHG emissions are estimated to be as low as 3% below the GHG emissions determined by the conventional method. A significant error can therefore occur in the organizational carbon footprint (CF) of a company and, consequently, also in the product CF. It is recommended that hourly EFs be developed for other countries and power grids.
AB - © 2014 by Yale University. For many companies, the greenhouse gas (GHG) emissions associated with their purchased and consumed electricity form one of the largest contributions to the GHG emissions that result from their activities. Currently, hourly variations in electricity grid emissions are not considered by standard GHG accounting protocols, which apply a national grid emission factor (EF), potentially resulting in erred estimates for the GHG emissions. In this study, a method is developed that calculates GHG emissions based on real-time data, and it is shown that the use of hourly electricity grid EFs can significantly improve the accuracy of the GHG emissions that are attributed to the purchased and consumed electricity of a company. A model analysis for the electricity delivered to the Spanish grid in 2012 reveals that, for companies operating during the day, GHG emissions calculated by the real-time method are estimated to be up to 5% higher (and in some special cases up to 9% higher) than the emissions calculated by the conventional method in which a national grid EF is applied, whereas for companies operating during nightly hours, GHG emissions are estimated to be as low as 3% below the GHG emissions determined by the conventional method. A significant error can therefore occur in the organizational carbon footprint (CF) of a company and, consequently, also in the product CF. It is recommended that hourly EFs be developed for other countries and power grids.
KW - Industrial ecology
KW - Power generation mix
KW - Hourly emission factors
KW - National electric grid
KW - Carbon footprint
KW - Greenhouse gas (GHG) emissions
UR - https://dialnet.unirioja.es/servlet/articulo?codigo=5106668
UR - http://dialnet.unirioja.es/servlet/articulo?codigo=5106668
U2 - 10.1111/jiec.12193
DO - 10.1111/jiec.12193
M3 - Article
SN - 1088-1980
VL - 19
SP - 380
EP - 390
JO - Journal of Industrial Ecology
JF - Journal of Industrial Ecology
IS - 3
ER -