Project description:Despite the negative externalities on the environment and human health, today's economies still produce excessive carbon dioxide emissions. As a result, governments are trying to shift production and consumption to more sustainable models that reduce the environmental impact of carbon dioxide emissions. The European Union, in particular, has implemented an innovative policy to reduce carbon dioxide emissions by creating a market for emission rights, the emissions trading system. The objective of this paper is to perform a counterfactual analysis to measure the impact of the emissions trading system on the reduction of carbon dioxide emissions. For this purpose, a recently-developed statistical machine learning method called matrix completion with fixed effects estimation is used and compared to traditional econometric techniques. We apply matrix completion with fixed effects estimation to the prediction of missing counterfactual entries of a carbon dioxide emissions matrix whose elements (indexed row-wise by country and column-wise by year) represent emissions without the emissions trading system for country-year pairs. The results obtained, confirmed by robust diagnostic tests, show a significant effect of the emissions trading system on the reduction of carbon dioxide emissions: the majority of European Union countries included in our analysis reduced their total carbon dioxide emissions (associated with selected industries) by about 15.4% during the emissions trading system treatment period 2005-2020, compared to the total carbon dioxide emissions (associated with the same industries) that would have been achieved in the absence of the emissions trading system policy. Finally, several managerial/practical implications of the study are discussed, together with its possible extensions.
Project description:Carbon dioxide removal technologies, such as bioenergy with carbon capture and direct air capture, are valuable for stringent climate targets. Previous work has examined implications of carbon removal, primarily bioenergy-based technologies using integrated assessment models, but not investigated the effects of a portfolio of removal options on power systems in detail. Here, we explore impacts of carbon removal technologies on electric sector investments, costs, and emissions using a detailed capacity planning and dispatch model with hourly resolution. We show that adding carbon removal to a mix of low-carbon generation technologies lowers the costs of deep decarbonization. Changes to system costs and investments from including carbon removal are larger as policy ambition increases, reducing the dependence on technologies like advanced nuclear and long-duration storage. Bioenergy with carbon capture is selected for net-zero electric sector emissions targets, but direct air capture deployment increases as biomass supply costs rise.
Project description:Emissions of aerosols and their precursors are declining due to policies enacted to protect human health, yet we currently lack a full understanding of the magnitude, spatiotemporal pattern, statistical significance, and physical mechanisms of precipitation responses to aerosol reductions. We quantify the global and regional precipitation responses to U.S. SO2 emission reductions using three fully coupled chemistry-climate models: Community Earth System Model version 1, Geophysical Fluid Dynamics Laboratory Coupled Model 3, and Goddard Institute for Space Studies ModelE2. We contrast 200 year (or longer) simulations in which anthropogenic U.S. sulfur dioxide (SO2) emissions are set to zero with present-day control simulations to assess the aerosol, cloud, and precipitation response to U.S. SO2 reductions. In all three models, reductions in aerosol optical depth up to 70% and cloud droplet number column concentration up to 60% occur over the eastern U.S. and extend over the Atlantic Ocean. Precipitation responses occur both locally and remotely, with the models consistently showing an increase in most regions considered. We find a northward shift of the tropical rain belt location of up to 0.35° latitude especially near the Sahel, where the rainy season length and intensity are significantly enhanced in two of the three models. This enhancement is the result of greater warming in the Northern versus Southern Hemispheres, which acts to shift the Intertropical Convergence Zone northward, delivering additional wet season rainfall to the Sahel. Two of our three models thus imply a previously unconsidered benefit of continued U.S. SO2 reductions for Sahel precipitation.
Project description:A grand challenge facing society is climate change caused mainly by rising CO2 concentration in Earth's atmosphere. Terrestrial plants are linchpins in global carbon cycling, with a unique capability of capturing CO2 via photosynthesis and translocating captured carbon to stems, roots, and soils for long-term storage. However, many researchers postulate that existing land plants cannot meet the ambitious requirement for CO2 removal to mitigate climate change in the future due to low photosynthetic efficiency, limited carbon allocation for long-term storage, and low suitability for the bioeconomy. To address these limitations, there is an urgent need for genetic improvement of existing plants or construction of novel plant systems through biosystems design (or biodesign). Here, we summarize validated biological parts (e.g., protein-encoding genes and noncoding RNAs) for biological engineering of carbon dioxide removal (CDR) traits in terrestrial plants to accelerate land-based decarbonization in bioenergy plantations and agricultural settings and promote a vibrant bioeconomy. Specifically, we first summarize the framework of plant-based CDR (e.g., CO2 capture, translocation, storage, and conversion to value-added products). Then, we highlight some representative biological parts, with experimental evidence, in this framework. Finally, we discuss challenges and strategies for the identification and curation of biological parts for CDR engineering in plants.
Project description:Borneo has accumulated an abundance of woody carbon in its forests and peat. However, agricultural land conversion accompanied by plantation development, dead wood burning, and peat drying from drainage are major challenges to climate change mitigation. This study aimed to develop a method of estimating carbon dioxide (CO2) emissions from land use change, forest and peat fires, and oxidative peat decomposition, and CO2 uptake from biomass growth across Borneo using remote sensing data from 2001 to 2016. Although CO2 uptake by biomass growth in vast forests has shown a significant increasing trend, an annual net release of 461.10 ± 436.51 (average ± 1 standard deviation) Tg CO2 year-1 was observed. The estimated emissions were predominantly characterized by land use changes from 2001 to 2003, with the highest emissions in 2001. Land use change was evaluated from annual land use maps with an accuracy of 92.0 ± 1.0% (average ± 1 standard deviation). Forest and peat fires contributed higher emissions in 2002, 2006, 2009, 2014, and 2015 compared to other years and were strongly correlated with the Southern Oscillation Indexes. These results suggest that more CO2 may have been released into the atmosphere than previously thought.
Project description:Information on global future gridded emissions and land-use scenarios is critical for many climate and global environmental modelling studies. Here, we generated such data using an integrated assessment model (IAM) and have made the data publicly available. Although the Coupled Model Inter-comparison Project Phase 6 (CMIP6) offers similar data, our dataset has two advantages. First, the data cover a full range and combinations of socioeconomic and climate mitigation levels, which are considered as a range of plausible futures in the climate research community. Second, we provide this dataset based on a single integrated assessment modelling framework that enables a focus on purely socioeconomic factors or climate mitigation levels, which is unavailable in CMIP6 data, since it incorporates the outcomes of each IAM scenario. We compared our data with existing gridded data to identify the characteristics of the dataset and found both agreements and disagreements. This dataset can contribute to global environmental modelling efforts, in particular for researchers who want to investigate socioeconomic and climate factors independently.
Project description:Achieving net-zero climate targets requires some level of carbon dioxide removal. Current assessments focus on tonnes of CO2 removed, without specifying what form these removals will take. Here, we show that countries' climate pledges require approximately 1 (0.9-1.1) billion ha of land for removals. For over 40% of this area, the pledges envisage the conversion of existing land uses to forests, while the remaining area restores existing ecosystems and land uses. We analyse how this demand for land is distributed geographically and over time. The results are concerning, both in terms of the aggregate area of land, but also the rate and extent of land use change. Our findings demonstrate a gap between governments' expected reliance on land and the role that land can realistically play in climate mitigation. This adds another layer to the observed shortcomings of national climate pledges and indicates a need for more transparency around the role of land in national climate mitigation plans.
Project description:International carbon markets are an appealing and increasingly popular tool to regulate carbon emissions. By putting a price on carbon, carbon markets reshape incentives faced by firms and reduce the value of emissions. How effective are carbon markets? Observers have tended to infer their effectiveness from market prices. The general belief is that a carbon market needs a high price in order to reduce emissions. As a result, many observers remain skeptical of initiatives such as the European Union Emissions Trading System (EU ETS), whose price remained low (compared to the social cost of carbon). In this paper, we assess whether the EU ETS reduced [Formula: see text] emissions despite low prices. We motivate our study by documenting that a carbon market can be effective if it is a credible institution that can plausibly become more stringent in the future. In such a case, firms might cut emissions even though market prices are low. In fact, low prices can be a signal that the demand for carbon permits weakens. Thus, low prices are compatible with successful carbon markets. To assess whether the EU ETS reduced carbon emissions even as permits were cheap, we estimate counterfactual carbon emissions using an original sectoral emissions dataset. We find that the EU ETS saved about 1.2 billion tons of [Formula: see text] between 2008 and 2016 (3.8%) relative to a world without carbon markets, or almost half of what EU governments promised to reduce under their Kyoto Protocol commitments. Emission reductions in sectors covered under the EU ETS were higher.
Project description:Scientifically rigorous guidance to policy makers on mitigation options for meeting the Paris Agreement long-term temperature goal requires an evaluation of long-term global-warming implications of greenhouse gas emissions pathways. Here we employ a uniform and transparent methodology to evaluate Paris Agreement compatibility of influential institutional emission scenarios from the grey literature, including those from Shell, BP, and the International Energy Agency. We compare a selection of these scenarios analysed with this methodology to the Integrated Assessment Model scenarios assessed by the Intergovernmental Panel on Climate Change. We harmonize emissions to a consistent base-year and account for all greenhouse gases and aerosol precursor emissions, ensuring a self-consistent comparison of climate variables. An evaluation of peak and end-of-century temperatures is made, with both being relevant to the Paris Agreement goal. Of the scenarios assessed, we find that only the IEA Net Zero 2050 scenario is aligned with the criteria for Paris Agreement consistency employed here. We investigate root causes for misalignment with these criteria based on the underlying energy system transformation.
Project description:Energy-intensive industries are difficult to decarbonize. They present a major challenge to the emerging countries that are currently in the midst of rapid industrialization and urbanization. This is also applicable to Japan, a developed economy, which retains a large presence in heavy industries compared to other developed economies. In this paper, the results obtained from four energy-economic and integrated assessment models were utilized to explore climate mitigation scenarios of Japan's industries by 2050. The results reveal that: (i) Japan's share of emissions from industries may increase by 2050, highlighting the difficulties in achieving industrial decarbonization under the prevailing industrial policies; (ii) the emission reduction in steelmaking will play a key role, which can be achieved by the implementation of carbon capture and expansion of hydrogen technologies after 2040; (iii) even under mitigation scenarios, electrification and the use of biomass use in Japan's industries will continue to be limited in 2050, suggesting a low possibility of large-scale fuel switching or end-use decarbonization. After stocktaking of the current industry-sector modeling in integrated assessment models, we found that such limited uptake of cleaner fuels in the results may be related to the limited interests of both participating models and industry stakeholders in Japan, specifically the interests on the technologies that are still at the early stage of development but with high reduction potential. It is crucial to upgrade research and development activities to enable future industry-sector mitigation as well as to improve modeling capabilities of energy end-use technologies in integrated assessment models.Supplementary informationThe online version contains supplementary material available at 10.1007/s11625-021-00905-2.