TY - JOUR
T1 - Reviewing the scope and thematic focus of 100 000 publications on energy consumption, services and social aspects of climate change: a big data approach to demand-side mitigation*
AU - Creutzig, Felix
AU - Callaghan, Max
AU - Ramakrishnan, Anjali
AU - Javaid, Aneeque
AU - Niamir, Leila
AU - Minx, Jan
AU - Müller-Hansen, Finn
AU - Sovacool, Benjamin
AU - Afroz, Zakia
AU - Andor, Mark
AU - Antal, Miklos
AU - Court, Victor
AU - Das, Nandini
AU - Díaz-José, Julio
AU - Döbbe, Friederike
AU - Figueroa, Maria J
AU - Gouldson, Andrew
AU - Haberl, Helmut
AU - Hook, Andrew
AU - Ivanova, Diana
AU - Lamb, William F
AU - Maïzi, Nadia
AU - Mata, Érika
AU - Nielsen, Kristian S
AU - Onyige, Chioma Daisy
AU - Reisch, Lucia A
AU - Roy, Joyashree
AU - Scheelbeek, Pauline
AU - Sethi, Mahendra
AU - Some, Shreya
AU - Sorrell, Steven
AU - Tessier, Mathilde
AU - Urmee, Tania
AU - Virág, Doris
AU - Wan, Can
AU - Wiedenhofer, Dominik
AU - Wilson, Charlie
PY - 2021/3/1
Y1 - 2021/3/1
N2 - As current action remains insufficient to meet the goals of the Paris agreement let alone to stabilize the climate, there is increasing hope that solutions related to demand, services and social aspects of climate change mitigation can close the gap. However, given these topics are not investigated by a single epistemic community, the literature base underpinning the associated research continues to be undefined. Here, we aim to delineate a plausible body of literature capturing a comprehensive spectrum of demand, services and social aspects of climate change mitigation. As method we use a novel double-stacked expert—machine learning research architecture and expert evaluation to develop a typology and map key messages relevant for climate change mitigation within this body of literature. First, relying on the official key words provided to the Intergovernmental Panel on Climate Change by governments (across 17 queries), and on specific investigations of domain experts (27 queries), we identify 121 165 non-unique and 99 065 unique academic publications covering issues relevant for demand-side mitigation. Second, we identify a literature typology with four key clusters: policy, housing, mobility, and food/consumption. Third, we systematically extract key content-based insights finding that the housing literature emphasizes social and collective action, whereas the food/consumption literatures highlight behavioral change, but insights also demonstrate the dynamic relationship between behavioral change and social norms. All clusters point to the possibility of improved public health as a result of demand-side solutions. The centrality of the policy cluster suggests that political actions are what bring the different specific approaches together. Fourth, by mapping the underlying epistemic communities we find that researchers are already highly interconnected, glued together by common interests in sustainability and energy demand. We conclude by outlining avenues for interdisciplinary collaboration, synthetic analysis, community building, and by suggesting next steps for evaluating this body of literature.
AB - As current action remains insufficient to meet the goals of the Paris agreement let alone to stabilize the climate, there is increasing hope that solutions related to demand, services and social aspects of climate change mitigation can close the gap. However, given these topics are not investigated by a single epistemic community, the literature base underpinning the associated research continues to be undefined. Here, we aim to delineate a plausible body of literature capturing a comprehensive spectrum of demand, services and social aspects of climate change mitigation. As method we use a novel double-stacked expert—machine learning research architecture and expert evaluation to develop a typology and map key messages relevant for climate change mitigation within this body of literature. First, relying on the official key words provided to the Intergovernmental Panel on Climate Change by governments (across 17 queries), and on specific investigations of domain experts (27 queries), we identify 121 165 non-unique and 99 065 unique academic publications covering issues relevant for demand-side mitigation. Second, we identify a literature typology with four key clusters: policy, housing, mobility, and food/consumption. Third, we systematically extract key content-based insights finding that the housing literature emphasizes social and collective action, whereas the food/consumption literatures highlight behavioral change, but insights also demonstrate the dynamic relationship between behavioral change and social norms. All clusters point to the possibility of improved public health as a result of demand-side solutions. The centrality of the policy cluster suggests that political actions are what bring the different specific approaches together. Fourth, by mapping the underlying epistemic communities we find that researchers are already highly interconnected, glued together by common interests in sustainability and energy demand. We conclude by outlining avenues for interdisciplinary collaboration, synthetic analysis, community building, and by suggesting next steps for evaluating this body of literature.
KW - Behavior
KW - Climate change mitigation
KW - Demand
KW - IPCC
KW - Machine learning
KW - Services
KW - Social norm
UR - http://www.scopus.com/inward/record.url?scp=85102480380&partnerID=8YFLogxK
U2 - 10.1088/1748-9326/abd78b
DO - 10.1088/1748-9326/abd78b
M3 - Review article
VL - 16
JO - Environmental Research Letters
JF - Environmental Research Letters
SN - 1748-9326
IS - 3
M1 - 033001
ER -