High fuel prices could cut US greenhouse-gas emissions

The announcement by the Biden Administration to reengage the Paris climate process and lower US greenhouse gas (GHG) emissions 50% by the end of this decade is an essential development in the global effort to avoid the worst impacts of climate change (1). However, promises to reduce US GHG emissions are not new and have thus far delivered little real and sustainable emissions reductions (2). The result? Climate change continues unabated, and we forgo the associated jobs and technological innovation that will fuel economic growth in climate friendly businesses. It must be different this time—pledges must lead to practical policy and quickly. To mitigate greenhouse gas emissions, we need accurate and transparent emissions data infrastructure that maps when emissions are happening and where they’re coming from. Image credit: Shutterstock/Tatiana Grozetskaya. To meet the US emission pledge, practical policies will need to reach broadly across the US economy and mobilize new technologies, behavioral change, and private capital. Regardless of policy specifics, actionable GHG reduction policies will fundamentally rest on critical climate data infrastructure that comprehensively and reliably quantifies and tracks GHG emissions in the United States from the local to the national scale. Ideally, all citizens should be able to see a daily map of detailed emissions across the US landscape, much like viewing daily weather. In other words, we need a “US Greenhouse Gas Information Service.” Such a service would provide local emission context to our daily lives and is essential to determine whether emission reduction claims are real, if they’re targeting the best opportunities from neighborhoods to the nation, and whether they’re establishing the trust necessary to mobilize and sustain reduction investment. Right now, however, US climate data collection and dissemination efforts are falling short. Measurement and tracking of GHG emissions reflect a collection of ad hoc mandates and … [↵][1]1To whom correspondence may be addressed. Email: kevin.gurney{at}nau.edu. [1]: #xref-corresp-1-1

Major US electric utility climate pledges have the potential to collectively reduce power sector emissions by one-third

Using advanced technologies to reduce motor vehicle greenhouse gas emissions

Greenhouse gas emissions from milk production and consumption in the United States: A cradle-to-grave life cycle assessment circa 2008

Annual greenhouse gas (GHG) emissions from residential energy use in the United States peaked in 2005 at 1.26 Gt CO2-eq yr−1, and have since decreased at an average annual rate of 2% yr−1 to 0.96 Gt CO2-eq yr−1 in 2019. In this article we decompose changes in US residential energy supply and GHG emissions over the period 1990–2015 into relevant drivers for four end-use categories. The chosen drivers encompass changing demographics, housing characteristics, energy end-use intensities, and generation efficiency and GHG intensity of electricity. Reductions in household size, growth in heated floor area per house, and increased access to space cooling are the main drivers of increases in energy and GHG emissions after population growth. Growing shares of newer homes, and reductions in intensity of energy use per capita, household, or floor area have produced moderate primary energy and GHG emission reductions, but improved generation efficiency and decarbonization of electricity supply have brought about far bigger primary energy and GHG emission reductions. Continued decline of residential emissions from electrification of residential energy and decarbonization of electricity supply can be expected, but not fast enough to limit climate change to 1.5 °C warming. US residential final energy demand will therefore need to decline in absolute terms to meet such a target. However, without changes in the age distribution, type mix, or average size of housing, improvements in energy efficiency are unlikely to outweigh growth in the number of households from population growth and further household size reductions.

For many developing countries, the land use sector, particularly agriculture and forestry, represents a large proportion of their greenhouse gas (GHG) emissions, making this sector a priority for GHG mitigation activities. Previous global surveys (e.g., IPCC 2000) as well as the most recent IPCC assessment report clearly indicate that the greatest technical potential for carbon sequestration and reductions of non-CO2 GHG emissions from the land use sector is in developing countries. Estimates that consider economic feasibility suggest that agriculture and forestry together provide among the greatest opportunities for short-term and low-cost mitigation measures across all sectors of the global economy1 (IPCC 2007). In addition, it is widely recognized that the ecosystem changes entailed by most mitigation practices, i.e., building soil organic matter, reducing losses and tightening nutrient cycles, more efficient production systems and preserving native vegetation, are well aligned with goals of increasing food security and rural development as well as buffering land use systems against climate change (Lal 2004). Hence, there is growing interest in jump-starting the capacity for broad-based engagement in agriculturally-based GHG mitigation projects in developing countries.

Background: Healthcare accounts for 8.5% of total US greenhouse gas emissions (GHGE), with US healthcare the main contributor. Yet little effort has been made to measure healthcare related GHGE. Specifically, GHGE related to unnecessary antibiotic prescriptions is unclear, and to our knowledge, no one has used estimates of GHGE of unnecessary antibiotics as an antibiotic stewardship tool. We aimed to measure GHGE from solid waste associated with unnecessary antibiotic prescriptions for respiratory conditions. Methods: We calculated emissions for an outpatient prescription including the plastic bottle, paper leaflet, and paper bag (photos) based on the weight of each item multiplied by US Environmental Protection Agency (EPA) GHGE factors. Emission factors depend on waste type and treatment method which we assumed to be landfilled. To estimate unnecessary antibiotic prescriptions for respiratory infections, visits from nine University of Utah Health Urgent Care Centers from 2019-2022 were electronically identified and included if they had an ICD-10-CM code for a respiratory diagnosis where antibiotics are not indicated. Waste emissions of the paper and plastic in an individual prescription were then multiplied by the number of unnecessary respiratory antibiotic prescriptions for designated time periods to arrive at total landfilled waste emissions. We used similar methods applied to published 2014 data from CDC to estimate national waste emissions due to unnecessary antibiotic prescriptions for respiratory infections. Finally, we used the EPA’s GHG Equivalencies Calculator to convert emissions into tangible GHGE for providers and patients. Results: A prescription has 32g of paper and 15g of plastic waste. Among 124,461 urgent care visits (Table 1) in 2019-2022, 18,531 (14.9%) received an antibiotic. This equates to 593 kg of paper waste and 278 kg of plastic waste leading to a total landfilled waste emissions of 0.479 MT CO2e/ton. Using the EPA GHG Equivalencies Calculator, this equates to driving an average gasoline-powered car 1,228 miles. There were 14,482,976 unnecessary antibiotic prescriptions (Table 2) in the US for respiratory infections in 2014. Our estimates suggest these prescriptions led to 375.109 CO2e/ton of GHGE, the same as driving 961,610 miles by an average gasoline-powered vehicle. Conclusion: Unnecessary antibiotic prescriptions are associated with substantial GHGE. This estimate demands further evaluation across diagnoses and care delivery sites, and most importantly action. Additionally, the large GHG contribution of unnecessary antibiotics should be used as a stewardship tool to highlight low-value care that is likely contributing to global climate change.

With light duty vehicles (LDVs) responsible for 17% of annual US greenhouse gas (GHG) emissions, integrating emerging GHG-reducing technologies into the fleet is essential. However, the slow rate of vehicle turnover presents a significant barrier to the market penetration of new technologies, with adoption delayed by the low number of vehicles needing replacement each year. A strategy of accelerated vehicle turnover through a vehicle lifespan cap could potentially mitigate this limit. While older studies reach differing conclusions on their effectiveness, two newer studies that incorporate life cycle assessment find that accelerated turnover strategies can be effective if coupled with high levels of electric vehicle deployment. We seek to determine whether a vehicle lifespan cap strategy can be an effective and efficient (cost-effective) method for reducing US LDV fleet GHG emissions. We augment the capabilities of the Fleet Life Cycle Assessment and Material Flow Estimation (FLAME) fleet life cycle assessment model, integrating vehicle lifespan caps and comprehensive calculations of cost along with sensitivity analysis for electric vehicle survival curves and battery degradation. The augmented FLAME model is used to analyse the impact of vehicle lifespan caps of varying lengths on a suite of scenarios, including a business as usual (BAU) scenario and eight scenarios modelling different technology improvement assumptions. This work confirms that vehicle lifespan caps have limited effectiveness in reducing GHG emissions under a BAU scenario but show potential to meaningfully reduce GHG emissions in a scenario with accelerated deployment of electric vehicles. However, abatement costs are high, exceeding 2020 USD 1000/tCO2eq under baseline assumptions, but falling within the range of current estimates of the social cost of carbon under more optimistic assumptions. Overall, vehicle lifespan caps must be carefully considered as they accelerate both the benefits and costs of new vehicle technologies, and are best positioned as part of a larger integrated strategy for tackling transportation GHG emissions.

In 2007 the US Congress began considering a set of bills to implement a cap-and-trade system to limit the nation's greenhouse gas (GHG) emissions. The MIT Integrated Global System Model (IGSM)—and its economic component, the Emissions Prediction and Policy Analysis (EPPA) model—were used to assess these proposals. In the absence of policy, the EPPA model projects a doubling of US greenhouse gas emissions by 2050. Global emissions, driven by growth in developing countries, are projected to increase even more. Unrestrained, these emissions would lead to an increase in global CO2 concentration from a current level of 380 ppmv to about 550 ppmv by 2050 and to near 900 ppmv by 2100, resulting in a year 2100 global temperature 3.5–4.5°C above the current level. The more ambitious of the Congressional proposals could limit this increase to around 2°C, but only if other nations, including developing countries, also strongly controlled greenhouse gas emissions. With these more aggressive reductions, the economic cost measured in terms of changes in total welfare in the United States could range from 1.5% to almost 2% by the 2040–2050 period, with 2015 CO2-equivalent prices between $30 and $55, rising to between $120 and $210 by 2050. This level of cost would not seriously affect US GDP growth but would imply large-scale changes in its energy system.

Activities to reduce net greenhouse gas emissions by biological soil or forest carbon sequestration predominantly utilize currently known, readily implementable technologies. Many other greenhouse gas emission reduction options require future technological development or must wait for turnover of capital stock. Carbon sequestration options in soils and forests, while ready to go now, generally have a finite life, allowing use until other strategies are developed. This paper reports on an investigation of the competitiveness of biological carbon sequestration from a dynamic and multiple strategy viewpoint. Key factors affecting the competitiveness of terrestrial mitigation options are land availability and cost effectiveness relative to other options including CO2 capture and storage, energy efficiency improvements, fuel switching, and non-CO2 greenhouse gas emission reductions. The analysis results show that, at lower CO2 prices and in the near term, soil carbon and other agricultural/forestry options can be important bridges to the future, initially providing a substantial portion of attainable reductions in net greenhouse gas emissions, but with a limited role in later years. At higher CO2 prices, afforestation and biofuels are more dominant among terrestrial options to offset greenhouse gas emissions. But in the longer run, allowing for capital stock turnover, options to reduce greenhouse gas emissions from the energy system and biofuels provide an increasing share of potential reductions in total US greenhouse gas emissions.

In 2007 the US Congress began considering a set of bills to implement a cap-and-trade system to limit the nation's greenhouse gas (GHG) emissions. The MIT Integrated Global System Model (IGSM)—and its economic component, the Emissions Prediction and Policy Analysis (EPPA) model—were used to assess these proposals. In the absence of policy, the EPPA model projects a doubling of US greenhouse gas emissions by 2050. Global emissions, driven by growth in developing countries, are projected to increase even more. Unrestrained, these emissions would lead to an increase in global CO2 concentration from a current level of 380 ppmv to about 550 ppmv by 2050 and to near 900 ppmv by 2100, resulting in a year 2100 global temperature 3.5–4.5°C above the current level. The more ambitious of the Congressional proposals could limit this increase to around 2°C, but only if other nations, including developing countries, also strongly controlled greenhouse gas emissions. With these more aggressive reductions, the economic c...

The Intergovernmental Panel on Climate Change has warned that there is significant concern that increasing manmade greenhouse gas (GHG) emissions are leading to climate change and global warming. Climate models indicate that to minimize the damage caused by global warming, governments need to limit the global temperature increase to 2°C. This requires stabilizing the concentration of GHGs in the atmosphere to 450 parts per million in carbon dioxide equivalents (CO2e) by 2050. Many countries concur that the level of emissions per citizen for every country should converge by then. This will require the emissions of developed countries to decline by 50–90% by 2050. This paper examines the building and utilities sectors that account for 68% of total US GHG emissions and proposes a potential solution of adopting a carbon tax (revenues) with reinvestment (power plant construction) that reduces US emissions by 48% and building/utility emissions by 67% within 20 years. This paper then examines two potential optio...

Revoking the state’s tough fuel-efficiency standards would increase US greenhouse-gas emissions. Revoking the state’s ability to set tough fuel-efficiency standards would increase US greenhouse-gas emissions.

The health-care industry is a substantial contributor to global greenhouse gas emissions, yet the specific environmental impact of radiotherapy, a cornerstone of cancer treatment, remains under-explored. We aimed to quantify the emissions associated with the delivery of radiotherapy in the USA and propose a framework for reducing the environmental impact of oncology care. In this multi-institutional retrospective analysis and simulation study, we conducted a lifecycle assessment of external beam radiotherapy (EBRT) for ten anatomical disease sites, adhering to the International Organization for Standardization's standards ISO 14040 and ISO 14044. We analysed retrospective data from Jan 1, 2017, to Oct 1, 2023, encompassing patient and staff travel, medical supplies, and equipment and building energy use associated with the use of EBRT at four academic institutions in the USA. The primary objective was to measure the environmental impacts across ten categories: greenhouse gases (expressed as kg of carbon dioxide equivalents [CO2e]), ozone depletion, smog formation, acidification, eutrophication, carcinogenic and non-carcinogenic potential, respiratory effects, fossil fuel depletion, and ecotoxicity. Human health effects secondary to these environmental impacts were also estimated as disability-adjusted life years. We also assessed the potential benefits of hypofractionated regimens for breast and genitourinary (ie, prostate and bladder) cancers on US greenhouse gas emissions using an analytic model based on the 2014 US National Cancer Database for fractionation patterns and patient commute distances. We estimated that the mean greenhouse gas emissions associated with a standard 25-fraction EBRT course were 4310 kg CO2e (SD 2910), which corresponded to 0·0035 disability-adjusted life years per treatment course. Transit and building energy usage accounted for 25·73% (1110 kg CO2e) and 73·95% of (3190 kg CO2e) of total greenhouse gas emissions, respectively, whereas supplies contributed only 0·32% (14 kg CO2e). Across the other environmental impact categories, most of the environmental impact also stemmed from patient transit and energy use within facilities, with little environmental impact contributed by supplies used. Hypofractionated treatment simulations suggested a substantial reduction in greenhouse gas emissions-by up to 42% for breast and 77% for genitourinary cancer-and environmental impacts more broadly. This comprehensive lifecycle assessment of EBRT delineates the environmental and secondary health impacts of radiotherapy, and underscores the urgent need for sustainable practices in oncology. The findings serve as a reference for future decarbonisation efforts in cancer care and show the potential environmental benefits of modifying treatment protocols (when clinical equipoise exists). They also highlight strategic opportunities to mitigate the ecological footprint in an era of escalating climate change and increasing cancer prevalence. Mount Zion Health Fund.

Analyses of the Environmental Kuznet’s Curve (EKC) hypothesis have largely focused on economy level data with occasional analyses exploring sector level data. This paper exploits a new data set which contains sector level data on greenhouse gas emissions from the US energy sector as well as subsector data from six disjoint subsectors which together comprise the entire energy sector. The data contained in this data set is annual data at the state level from 1990 through 2011. Using differenced data, we specify an econometrically sound EKC model and compare it against a model containing only a linear GDP per capita term. We find that using a subsector level modeling approach, evidence for the EKC hypothesis is virtually nonexistent. Moreover, we find that aggregated subsector level estimates outperform sector-level estimate on in-sample accuracy. These estimated models are then used to forecast emissions for the energy sector. We find evidence that US greenhouse gas emissions from energy production are at or near a peak.