TY - JOUR
T1 - Life cycle impact assessment of home energy management systems (HEMS) using dynamic emissions factors for electricity in Finland
AU - Louis, Jean Nicolas
AU - Pongrácz, Eva
N1 - Funding Information:
This research was made possible by the funding provided by the Academy of Finland for the SEN2050 project (Decision 287748 ), and the Fortum Foundation (Grant 201500108 ).
Publisher Copyright:
© 2017 Elsevier Inc.
PY - 2017/11
Y1 - 2017/11
N2 - Decarbonising the European economy is a long-term goal in which the residential sector will play a significant role. Smart buildings for energy management are one means of decarbonisation, by reducing energy consumption and related emissions. This study investigated the environmental impacts of smart house automation using life cycle impact assessment. The ReCiPe method was selected for use, in combination with dynamic emissions factors for electricity in Finland. The results indicated that a high level of technology deployment may be counter-effective, due to high electricity consumption by the sensor network, automation system and computing devices. The results also indicated that number of inhabitants per household directly affected the environmental impacts of home automation. A single-person household saw its environmental impacts increase by 15%, while those of a five-person household increased by 3% in the worst-case scenario. The manufacturing phase contributed the major share of environmental impacts, exceeding the use phase in multiple categories. These findings indicate that finding the sweet spot in which technology can promote decarbonisation will be crucial to achieving the goal of a low‑carbon economy.
AB - Decarbonising the European economy is a long-term goal in which the residential sector will play a significant role. Smart buildings for energy management are one means of decarbonisation, by reducing energy consumption and related emissions. This study investigated the environmental impacts of smart house automation using life cycle impact assessment. The ReCiPe method was selected for use, in combination with dynamic emissions factors for electricity in Finland. The results indicated that a high level of technology deployment may be counter-effective, due to high electricity consumption by the sensor network, automation system and computing devices. The results also indicated that number of inhabitants per household directly affected the environmental impacts of home automation. A single-person household saw its environmental impacts increase by 15%, while those of a five-person household increased by 3% in the worst-case scenario. The manufacturing phase contributed the major share of environmental impacts, exceeding the use phase in multiple categories. These findings indicate that finding the sweet spot in which technology can promote decarbonisation will be crucial to achieving the goal of a low‑carbon economy.
KW - Dynamic indicators
KW - Life-cycle impact assessment
KW - Modelling
KW - ReCiPe model
KW - Smart house
KW - Technology deployment
UR - http://www.scopus.com/inward/record.url?scp=85029468691&partnerID=8YFLogxK
U2 - 10.1016/j.eiar.2017.08.009
DO - 10.1016/j.eiar.2017.08.009
M3 - Article
AN - SCOPUS:85029468691
SN - 0195-9255
VL - 67
SP - 109
EP - 116
JO - Environmental Impact Assessment Review
JF - Environmental Impact Assessment Review
ER -