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*Intended as contribution to the focus issue on 'Demand-Side Solutions for Transitioning to Low-Carbon Societies' in Environmental Research Letters. (19th February 2021)

• Record Type: Journal Article
• Authors: Creutzig, Felix; Callaghan, Max; Ramakrishnan, Anjali; Javaid, Aneeque; Niamir, Leila; Minx, Jan; Müller-Hansen, Finn; Sovacool, Benjamin; Afroz, Zakia; Andor, Mark; Antal, Miklos; Court, Victor; Das, Nandini; Díaz-José, Julio; Döbbe, Friederike; Figueroa, Maria J; Gouldson, Andrew; Haberl, Helmut; Hook, Andrew; Ivanova, Diana; Lamb, William F; Maïzi, Nadia; Mata, Érika; Nielsen, Kristian S; Onyige, Chioma Daisy; Reisch, Lucia A; Roy, Joyashree; Scheelbeek, Pauline; Sethi, Mahendra; Some, Shreya; Sorrell, Steven; Tessier, Mathilde; Urmee, Tania; Virág, Doris; Wan, Can; Wiedenhofer, Dominik; Wilson, Charlie;
• Is Part Of: Environmental research letters. Volume 16:Number 3(2021)
• Publication Date: 2021-02-19
• Subjects: demand -- services -- climate change mitigation -- IPCC -- behavior -- social norm -- machine learning; Environmental sciences -- Periodicals; Human ecology -- Research -- Periodicals; Environmental health -- Periodicals; 333.7
• DOI: 10.1088/1748-9326/abd78b
• Languages: English
• ISSNs: 1748-9326

Abstract

Abstract: 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.