Strategies toward ambitious climate targets usually rely on the concept of 'decoupling'; that is, they aim at promoting economic growth while reducing the use of natural resources and GHG emissions. GDP growth coinciding with absolute reductions in emissions or resource use is denoted as 'absolute decoupling' , as opposed to 'relative decoupling' , where resource use or emissions increase less so than does GDP. Based on the bibliometric mapping in part I (Wiedenhofer et al, 2020 Environ. Res. Lett. 15 063002), we synthesize the evidence emerging from the selected 835 peer-reviewed articles. We evaluate empirical studies of decoupling related to final/useful energy, exergy, use of material resources, as well as CO 2 and total GHG emissions. We find that relative decoupling is frequent for material use as well as GHG and CO 2 emissions but not for useful exergy, a quality-based measure of energy use. Primary energy can be decoupled from GDP largely to the extent to which the conversion of primary energy to useful exergy is improved. Examples of absolute long-term decoupling are rare, but recently some industrialized countries have decoupled GDP from both production-and, weaklier, consumption-based CO 2 emissions. We analyze policies or strategies in the decoupling literature by classifying them into three groups:(1) Green growth, if sufficient reductions of resource use or emissions were deemed possible without altering the growth trajectory.(2) Degrowth, if reductions of resource use or emissions were given priority over GDP growth. (3) Others, e.g. if the role of energy for GDP growth was analyzed without reference to climate change mitigation. We conclude that large rapid absolute reductions of resource use and GHG emissions cannot be achieved through observed decoupling rates, hence decoupling needs to be complemented by sufficiency-oriented strategies and strict enforcement of absolute reduction targets. More research is needed on interdependencies between wellbeing, resources and emissions.
The dynamics of societal
material stocks such as buildings and
infrastructures and their spatial patterns drive surging resource
use and emissions. Two main types of data are currently used to map
stocks, night-time lights (NTL) from Earth-observing (EO) satellites
and cadastral information. We present an alternative approach for
broad-scale material stock mapping based on freely available high-resolution
EO imagery and OpenStreetMap data. Maps of built-up surface area,
building height, and building types were derived from optical Sentinel-2
and radar Sentinel-1 satellite data to map patterns of material stocks
for Austria and Germany. Using material intensity factors, we calculated
the mass of different types of buildings and infrastructures, distinguishing
eight types of materials, at 10 m spatial resolution. The total mass
of buildings and infrastructures in 2018 amounted to ∼5 Gt
in Austria and ∼38 Gt in Germany (AT: ∼540 t/cap, DE:
∼450 t/cap). Cross-checks with independent data sources at
various scales suggested that the method may yield more complete results
than other data sources but could not rule out possible overestimations.
The method yields thematic differentiations not possible with NTL,
avoids the use of costly cadastral data, and is suitable for mapping
larger areas and tracing trends over time.
As long as economic growth is a major political goal, decoupling growth from resource use and emissions is a prerequisite for a sustainable net-zero emissions future. However, empirical evidence for absolute decoupling, i.e. decreasing resource use and emissions at the required scale despite continued economic growth, is scarce and scattered across different research streams. In this two-part systematic review, we assess how and to what extent decoupling has been observed and what can be learnt for addressing the sustainability and climate crisis. Based on a transparent approach, we systematically identify and screen more than 11 500 scientific papers, eventually analyzing full texts of 835 empirical studies on the relationship between economic growth (GDP), resource use (materials and energy) and greenhouse gas emissions. Part I of the review examines how decoupling has been investigated across three research streams: energy, materials and energy, and emissions. Part II synthesizes the empirical evidence and policy implications (Haberl et al 2020 Environ. Res. Lett. 15 065003). In part I, we examine the topical, temporal and geographical scopes, methods of analysis, institutional networks and prevalent conceptual angles. We find that in this rapidly growing literature, the vast majority of studies-decomposition, 'causality' and Environmental Kuznets Curve analysis-approach the topic from a statistical-econometric point of view, while hardly acknowledging thermodynamic principles on the role of energy and materials for socio-economic activities. A potentially fundamental incompatibility between economic growth and systemic societal changes to address the climate crisis is rarely considered. We conclude that the existing wealth of empirical evidence merits braver conceptual advances than we have seen thus far. Future work should focus on comprehensive multi-indicator long-term analyses, conceptually grounded on the fundamental biophysical basis of socio-economic activities, incorporating the role of global supply chains as well as the wider societal role and preconditions of economic growth.
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.
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