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1. Simulating the Impact of the U.S. Inflation Reduction Act on State-Level CO2 Emissions: An Integrated Assessment Model Approach

   https://doi.org/10.3390/su152416562  

   Wang, Tianye; Shittu, Ekundayo (December 2023, Sustainability)

   Climate change mitigation measures are often projected to reduce anthropogenic carbon dioxide concentrations. Yet, it seems there is ample evidence suggesting that we have a limited understanding of the impacts of these measures and their combinations. For example, the Inflation Reduction Act (IRA) enacted in the U.S. in 2022 contains significant provisions, such as the electric vehicle (EV) tax credits, to reduce CO2 emissions. However, the impact of such provisions is not fully understood across the U.S., particularly in the context of their interactions with other macroeconomic systems. In this paper, we employ an Integrated Assessment Model (IAM), the Global Change Assessment Model (GCAM), to estimate the future CO2 emissions in the U.S. GCAM is equipped to comprehensively characterize the interactions among different systems, e.g., energy, water, land use, and transportation. Thus, the use of GCAM-USA that has U.S. state-level resolution allows the projection of the impacts and consequences of major provisions in the IRA, i.e., EV tax credits and clean energy incentives. To compare the performance of these incentives and credits, a policy effectiveness index is used to evaluate the strength of the relationship between the achieved total CO2 emissions and the overarching emission reduction costs. Our results show that the EV tax credits as stipulated in the IRA can only marginally reduce carbon emissions across the U.S. In fact, it may lead to negative impacts in some states. However, simultaneously combining the incentives and tax credits improves performance and outcomes better than the sum of the individual effects of the policies. This demonstrates that the whole is greater than the sum of the parts in this decarbonization approach. Our findings provide insights for policymakers with a recommendation that combining EV tax credits with clean energy incentives magnifies the intended impact of emission reduction. 

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2. Pandemic restrictions in 2020 highlight the significance of non-road NO _x sources in central London

   https://doi.org/10.5194/acp-23-2315-2023  

   Cliff, Samuel J.; Drysdale, Will; Lee, James D.; Helfter, Carole; Nemitz, Eiko; Metzger, Stefan; Barlow, Janet F. (January 2023, Atmospheric Chemistry and Physics)

   Abstract. Fluxes of nitrogen oxides (NOx=NO+NO2) and carbon dioxide (CO2) were measured using eddy covariance at the British Telecommunications (BT) Tower in central London during the coronavirus pandemic. Comparing fluxes to those measured in 2017 prior to the pandemic restrictions and the introduction of the Ultra-Low Emissions Zone (ULEZ) highlighted a 73 % reduction in NOx emissions between the two periods but only a 20 % reduction in CO2 emissions and a 32 % reduction in traffic load. Use of a footprint model and the London Atmospheric Emissions Inventory (LAEI) identified transport and heat and power generation to be the two dominant sources of NOx and CO2 but with significantly different relative contributions for each species. Application of external constraints on NOx and CO2 emissions allowed the reductions in the different sources to be untangled, identifying that transport NOx emissions had reduced by >73 % since 2017. This was attributed in part to the success of air quality policy in central London but crucially due to the substantial reduction in congestion that resulted from pandemic-reduced mobility. Spatial mapping of the fluxes suggests that central London was dominated by point source heat and power generation emissions during the period of reduced mobility. This will have important implications on future air quality policy for NO2 which, until now, has been primarily focused on the emissions from diesel exhausts. 

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3. Net-Zero Scheduling of Multi-Energy Building Energy Systems: A Learning-Based Robust Optimization Approach With Statistical Guarantees

   https://doi.org/10.1109/TSTE.2024.3437210  

   Yang, Yijie; Shi, Jian; Wang, Dan; Wu, Chenye; Han, Zhu (October 2024, IEEE Transactions on Sustainable Energy)

   Buildings produce a significant share of greenhouse gas (GHG) emissions, making homes and businesses a major factor in climate change. To address this critical challenge, this paper explores achieving net-zero emission through the carbon-aware optimal scheduling of the multi-energy building integrated energy systems (BIES). We integrate advanced technologies and strategies, such as the carbon capture system (CCS), power-to-gas (P2G), carbon tracking, and emission allowance trading, into the traditional BIES scheduling problem. The proposed model enables accurate accounting of carbon emissions associated with building energy systems and facilitates the implementation of low-carbon operations. Furthermore, to address the challenge of accurately assessing uncertainty sets related to forecasting errors of loads, generation, and carbon intensity, we develop a learning-based robust optimization approach for BIES that is robust in the presence of uncertainty and guarantees statistical feasibility. The proposed approach comprises a shape learning stage and a shape calibration stage to generate an optimal uncertainty set that ensures favorable results from a statistical perspective. Numerical studies conducted based on both synthetic and real-world datasets have demonstrated that the approach yields up to 8.2% cost reduction, compared with conventional methods, in assisting buildings to robustly reach net-zero emissions. 

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4. US Clean Energy Futures—Air Quality Benefits of Zero Carbon Energy Policies

   https://doi.org/10.3390/atmos13091401  

   Vasilakos, Petros N.; Shen, Huizhong; Mehdi, Qasim; Wilcoxen, Peter; Driscoll, Charles; Fallon, Kathy; Burtraw, Dallas; Domeshek, Maya; Russell, Armistead G. (September 2022, Atmosphere)

   In this work, we compare the air quality benefits of a variety of future policy scenarios geared towards controlling EGU (electricity generating units) emissions between the present-day conditions and 2050. While these policies are motivated by reducing CO2 emissions, they also yield significant co-benefits for criteria pollutants, such as ozone and PM2.5. An integrated set of clean energy policies were examined to assess the time-varying costs and benefits of a range of decarbonization strategies, including business as usual and the Affordable Clean Energy plan, with a primary focus on others that look to achieve very low, if not zero, CO2 emissions from the EGU sector by 2050. Benefits assessed include mitigation of greenhouse gas emissions as well as air quality co-benefits. In this introductory work, we describe the potential air quality changes from various clean air policies, to set the stage for upcoming work looking at health and monetized benefits. Emission changes for key pollutants are forecast using the Integrated Planning Model (IPM), which are then transformed into emission inputs for the Community Multiscale Air Quality Model (CMAQ). For all primary scenarios considered that achieve large greenhouse gas decreases, significant reductions in ozone and PM are realized, mainly in the eastern US, and all policies produce air quality benefits. 

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5. Spatially Explicit Life Cycle Global Warming and Eutrophication Potentials of Confined Dairy Production in the Contiguous US

   https://doi.org/10.3390/environments11110230  

   Romeiko, Xiaobo Xue; Zhang, Wangjian; Zhang, Xuesong; Choi, Jun-Ki (November 2024, Environments)

   Assessing the spatially explicit life cycle environmental impacts of livestock production systems is critical for understanding the spatial heterogeneity of environmental releases and devising spatially targeted remediation strategies. This study presents the first spatially explicit assessment on life cycle global warming and eutrophication potentials of confined dairy production at a county scale in the contiguous US. The Environmental Policy Integrated Climate model was used to estimate greenhouse gases (GHGs), NH3, and aqueous nutrient releases of feed production. The Greenhouse gases, Regulated Emissions, and Energy use in Transportation model and Commodity Flow Survey were used to assess GHGs and NH3 from feed transportation. Emission-factor-based approaches were primarily used to calculate GHGs from enteric fermentation, and GHGs, NH3, and aqueous nutrient releases from manure management. Characterization factors reported by the Intergovernmental Panel on Climate Change and Tool for Reduction and Assessment of Chemicals and other Environmental Impacts model were used to compute global warming and eutrophication potentials, respectively. The analyses revealed that life cycle global warming and eutrophication potentials of confined dairy production presented significant spatial heterogeneity among the US counties. For example, the life cycle global warming potential ranged from 462 kg CO2-eq/head to 14,189 kg CO2-eq/head. Surprisingly, sourcing feed locally cannot effectively reduce life cycle global warming and eutrophication potentials of confined dairy production. The feed supply scenarios with the lowest life cycle environmental impacts depend on the life cycle environmental impacts of feed production, geographic locations of confined dairy production, and specific impact categories. In addition, installing buffer strips in feed-producing hotspots can effectively reduce life cycle nutrient releases of confined dairy production. If 200 counties with the highest life cycle EP of corn adopt buffer strips, the reduction in life cycle EP of confined dairy production could reach 24.4%. 

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