TY - JOUR A1 - Minx, Jan C. A1 - Baiocchi, Giovanni A1 - Wiedmann, Thomas T1 - Carbon footprints of cities and other human settlements in the UK JF - Environmental Research Letters Y1 - 2013 U6 - https://doi.org/10.1088/1748-9326/8/3/035039 IS - 8 SP - 1 EP - 10 ER - TY - JOUR A1 - Minx, Jan C. A1 - Baiocchi, Giovanni A1 - Peters, Glen P. T1 - A 'carbonizing dragon': China’s fast growing CO2 emissions revisited. JF - Environmental science & technology Y1 - 2011 U6 - https://doi.org/10.1021/es201497m VL - 45 IS - 21 SP - 9144 EP - 9153 ER - TY - JOUR A1 - Baiocchi, Giovanni A1 - Minx, Jan C. T1 - Understanding changes in the UK’s CO2 emissions: A global perspective JF - Environmental Science & Technology Y1 - 2010 U6 - https://doi.org/10.1021/es902662h SN - 0013-936X VL - 44 IS - 4 SP - 1177 EP - 1184 ER - TY - JOUR A1 - Baiocchi, Giovanni A1 - Minx, Jan C. A1 - Hubacek, Klaus T1 - The impact of social factors and consumer behavior on CO2 emissions in the UK: A panel regression based on input-output and geo-demographic consumer segmentation data JF - Journal of Industrial Ecology Y1 - 2010 N1 - Free online Access / Freier online Zugriff: http://re.indiaenvironmentportal.org.in/files/The%20Impact%20of%20Social%20Factors.pdf VL - 14 SP - 50 EP - 72 ER - TY - JOUR A1 - Baiocchi, Giovanni A1 - Creutzig, Felix A1 - Minx, Jan C. T1 - A spatial typology of human settlements and their CO2 emissions in England JF - Global Environmental Change Y1 - 2015 U6 - https://doi.org/10.1016/j.gloenvcha.2015.06.001 N1 - Available as e-publication in your Hertie Library. Als elektronische Ausgabe in der Hertie Bibliothek verfügbar. VL - 34 SP - 13 EP - 21 ER - TY - RPRT A1 - Khanna, Tarun A1 - Baiocchi, Giovanni A1 - Callaghan, Max W. A1 - Creutzig, Felix A1 - Bogdan Guias, Horia A1 - Haddaway, Neal A1 - Hirth, Lion A1 - Javaid, Aneeque A1 - Koch, Nicolas A1 - Laukemper, Sonja A1 - Loeschel, Andreas A1 - Del Mar Zamora, Maria A1 - Minx, Jan C. T1 - Reducing carbon emissions of households through monetary incentives and behavioral interventions: a meta-analysis N2 - Despite the importance of evaluating all mitigation options so as to inform policy decisions addressing climate change, a systematic analysis of household-scale interventions to reduce carbon emissions is missing. Here, we address this gap through a state-of-the-art machine-learning assisted meta-analysis to comparatively assess the effectiveness of a range of monetary and behavioral interventions in energy demand of residential buildings. We identify 122 studies and extract 360 effect sizes representing trials on 1.2 million households in 25 countries. We find that all the studied interventions reduce energy consumption of households. Our meta-regression evidences that monetary incentives are on an average more effective than behavioral interventions, but deploying the right combinations of interventions together can increase overall effectiveness. We estimate global cumulative emissions reduction of 8.64 Gt CO2 by 2040, though deploying the most effective packages and interventions could result in greater reduction. While modest, this potential should be viewed in conjunction with the need for de-risking mitigation with energy demand reductions and realizing substantial co-benefits.  Y1 - 2021 U6 - https://doi.org/10.21203/rs.3.rs-124386/v1 ER - TY - JOUR A1 - Khanna, Tarun A1 - Baiocchi, Giovanni A1 - Callaghan, Max A1 - Creutzig, Felix A1 - Guias, Horia A1 - Haddaway, Neal R. A1 - Hirth, Lion A1 - Javaid, Aneeque A1 - Koch, Nicolas A1 - Laukemper, Sonja A1 - Löschel, Andreas A1 - del Mar Zamora Dominguez, Maria A1 - Minx, Jan C. T1 - A multi-country meta-analysis on the role of behavioural change in reducing energy consumption and CO2 emissions in residential buildings JF - Nature Energy N2 - Despite the importance of evaluating all mitigation options to inform policy decisions addressing climate change, a comprehensive analysis of household-scale interventions and their emissions reduction potential is missing. Here, we address this gap for interventions aimed at changing individual households’ use of existing equipment, such as monetary incentives or feedback. We have performed a machine learning-assisted systematic review and meta-analysis to comparatively assess the effectiveness of these interventions in reducing energy demand in residential buildings. We extracted 360 individual effect sizes from 122 studies representing trials in 25 countries. Our meta-regression confirms that both monetary and non-monetary interventions reduce the energy consumption of households, but monetary incentives, of the sizes reported in the literature, tend to show on average a more pronounced effect. Deploying the right combinations of interventions increases the overall effectiveness. We have estimated a global carbon emissions reduction potential of 0.35 GtCO2 yr−1, although deploying the most effective packages of interventions could result in greater reduction. While modest, this potential should be viewed in conjunction with the need for de-risking mitigation pathways with energy-demand reductions. Y1 - 2021 U6 - https://doi.org/10.1038/s41560-021-00866-x VL - 6 SP - 925 EP - 932 ER - TY - RPRT A1 - Minx, Jan C. A1 - Baiocchi, Giovanni A1 - Wiedmann, Thomas T1 - Understanding Changes in the UK's CO2 Emissions: A Structural Decomposition Approach BT - Report to the Department of Environment, Food and Rural Affairs Y1 - 2010 PB - London ER - TY - RPRT A1 - Scott, K. A1 - Barrett, John A1 - Baiocchi, Giovanni A1 - Minx, Jan C. T1 - Meeting the UK Climate Change Challenge: The Contribution of Resource Efficiency”. Report to the Waste und Resources Action Programme, York, UK Y1 - 2009 ER -