ArticleEnvironmental science & technology2018
Evolution of the United States Energy System and Related Emissions under Varying Social and Technological Development Paradigms: Plausible Scenarios for Use in Robust Decision Making.
Article in Environmental science & technology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- Bridging Existing Energy and Chemical Transport Models to Enhance Air Quality Policy Assessment.Environmental modelling & software : with environment data news · 2025Article
- Economy-wide evaluation of CONature communications · 2022Article
- Evaluating long-term emission impacts of large-scale electric vehicle deployment in the US using a human-Earth systems model.Applied energy · 2021Article
- Transportation emissions scenarios for New York City under different carbon intensities of electricity and electric vehicle adoption rates.Nature energy · 2021Article
- State-level drivers of future fine particulate matter mortality in the United States.Environmental research letters : ERL [Web site] · 2019Article
- What is the role of distributed energy resources under scenarios of greenhouse gas reductions? A specific focus on combined heat and power systems in the industrial and commercial sectors.Applied energy · 2019Article
- Energy and emissions implications of automated vehicles in the U.S. energy system.Transportation research. Part D, Transport and environment · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
The energy system is the primary source of air pollution. Thus, evolution of the energy system into the future will affect society's ability to maintain air quality. Anticipating this evolution is difficult because of inherent uncertainty in predicting future energy demand, fuel use, and technology adoption. We apply scenario planning to address this uncertainty, developing four very different visions of the future. Stakeholder engagement suggested that technological progress and social attitudes toward the environment are critical and uncertain factors for determining future emissions. Combining transformative and static assumptions about these factors yields a matrix of four scenarios that encompass a wide range of outcomes. We implement these scenarios in the U.S. Environmental Protection Agency MARKet ALlocation (MARKAL) model. Results suggest that both shifting attitudes and technology transformation may lead to emission reductions relative to the present, even without additional policies. Emission caps, such as the Cross-State Air-Pollution Rule, are most effective at protecting against future emission increases. An important outcome of this work is the scenario-implementation approach, which uses technology-specific discount rates to encourage scenario-specific technology and fuel choices. End-use energy demands are modified to approximate societal changes. This implementation allows the model to respond to perturbations in manners consistent with each scenario.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.