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Systematic review and meta-analysis of ex-post evaluations on the effectiveness of carbon pricing
(2024)
Today, more than 70 carbon pricing schemes have been implemented around the globe, but their contributions to emissions reductions remains a subject of heated debate in science and policy. Here we assess the effectiveness of carbon pricing in reducing emissions using a rigorous, machine-learning assisted systematic review and meta-analysis. Based on 483 effect sizes extracted from 80 causal ex-post evaluations across 21 carbon pricing schemes, we find that introducing a carbon price has yielded immediate and substantial emission reductions for at least 17 of these policies, despite the low level of prices in most instances. Statistically significant emissions reductions range between –5% to –21% across the schemes (–4% to –15% after correcting for publication bias). Our study highlights critical evidence gaps with regard to dozens of unevaluated carbon pricing schemes and the price elasticity of emissions reductions. More rigorous synthesis of carbon pricing and other climate policies is required across a range of outcomes to advance our understanding of “what works” and accelerate learning on climate solutions in science and policy.
Production and consumption of goods and services are interlinked through complex global supply-chain networks; so are the greenhouse gas emissions associated with them. Using a model that represents global supply-chain networks, we identified supply-chain clusters with high CO2 emissions within more than 300 million individual supply chains. We distinguished 4756 significant CO2 clusters and found that in 2008, global supply-chain networks associated with U.S. transport equipment and construction demand included relatively large CO2 clusters in China, accounting for 17% and 10%, respectively, of the U.S. CO2 footprint. Of added importance is the fact that these two clusters in China had annual growth rates of 42% and 58%, respectively, during the period 1995–2008. Our results show the importance for climate policy of monitoring these CO2 clusters that dominate CO2 emissions in global supply chains, and they offer insights on where climate policy can be effectively directed.
Summary for Policymakers
(2014)
Technical Summary
(2014)
Cities are becoming increasingly important in combatting climate change, but their overall role in global solution pathways remains unclear. Here we suggest structuring urban climate solutions along the use of existing and newly built infrastructures, providing estimates of the mitigation potential.
To have a >50% chance of limiting warming below 2 °C, most recent scenarios from integrated assessment models (IAMs) require large-scale deployment of negative emissions technologies (NETs). These are technologies that result in the net removal of greenhouse gases from the atmosphere. We quantify potential global impacts of the different NETs on various factors (such as land, greenhouse gas emissions, water, albedo, nutrients and energy) to determine the biophysical limits to, and economic costs of, their widespread application. Resource implications vary between technologies and need to be satisfactorily addressed if NETs are to have a significant role in achieving climate goals.
Increasing demand for solution-oriented environmental assessments brings significant opportunities and challenges at the science–policy–society interface. Solution-oriented assessments should enable inclusive deliberative learning processes about policy alternatives and their practical consequences.
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.
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.
Despite Germany’s Paris Agreement pledge and coal exit legislation, the political debate around carbon-intensive coal remains heated. Coal power and mining have played an important, yet changing role in the history of German politics. In this paper, we analyze the entire parliamentary debate on coal in the German parliament (Bundestag) from its inception in 1949 to 2019. For this purpose we extract the more than 870,000 parliamentary speeches from all protocols in the history of the Bundestag. We identify the 9167 speeches mentioning coal and apply dynamic topic modeling – an unsupervised machine learning technique that reveals the changing thematic structure of large document collections over time – to analyze changes in parliamentary debates on coal over the past 70 years. The trends in topics and their varying internal structure reflect how energy policy was discussed and legitimized over time: Initially, coal was framed as a driver of economic prosperity and guarantee of energy security. In recent years, the debate evolved towards energy transition, coal phase-out and renewable energy expansion. Germany’s smaller and younger parties, the Greens and the Left Party, debate coal more often in the context of the energy transition and climate protection than other parties. Our results reflect trends in other countries and other fields of energy policy. Methodologically, our study illustrates the potential of and need for computational methods to analyze vast corpora of text and to complement traditional social science methods.
CITIES: Car Industry, Road Transport and an international Emission Trading Scheme. Policy options
(2010)
Consumer Emissions
(2010)