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Nova · Professor Researcher · re-ranking top 20…
Noah Kittner

Noah Kittner

· Assistant Professor, Environmental Sciences and EngineeringVerified

University of North Carolina at Chapel Hill · Ecology and Evolutionary Biology

Active 2012–2026

h-index21
Citations2.3k
Papers6337 last 5y
Funding
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Research topics

  • Business
  • Engineering
  • Computer Science
  • Environmental science
  • Economics
  • Natural resource economics
  • Microeconomics
  • Ecology
  • Environmental economics
  • Economic system
  • Chemistry
  • Systems engineering
  • Process engineering
  • Geography
  • Electrical engineering
  • Reliability engineering

Selected publications

  • Assessing vehicle-to-grid integration for carsharing fleets using empirical data and simulation

    Transportation Research Part D Transport and Environment · 2026-03-17

    articleSenior author
  • Sand thermal energy storage: Technology, economics, environmental sustainability, and deployment strategies

    Journal of Energy Storage · 2026-01-10 · 1 citations

    articleSenior authorCorresponding
  • Evaluating long-term emission impacts of large-scale electric vehicle deployment in the US using a human-Earth systems model

    UNC Libraries · 2025-02-18

    articleOpen access1st authorCorresponding
  • Will the public in emerging economies support renewable energy? Evidence from Ho Chi Minh City, Vietnam

    UNC Libraries · 2025-02-18

    articleOpen access
  • Environmental impacts associated with hydrogen production in La Guajira, Colombia

    UNC Libraries · 2025-02-18

    articleOpen access1st authorCorresponding

    The global push to decarbonize sectors of the economy and phase-out coal use has attracted a renewed interest in hydrogen. At the forefront of this debate, Colombia, the world’s 6th largest coal exporter, must consider strategies to support a just transition for regions that depend economically on coal exports. However, the role of hydrogen as a part of the energy transition has yet to be examined from an environmental justice lens. A full-chain life-cycle assessment of hydrogen production is yet to be considered in Colombia. Using life-cycle assessment (LCA) methodology, we examine the greenhouse gas emissions, water consumption, and trace metal emissions associated with six potential Colombian liquid hydrogen production strategies: (1) electrolysis powered by the country’s national electricity grid, (2) on-site electrolysis powered by electricity produced by a wind farm, (3) off-site electrolysis powered by electricity produced by a wind farm, (4) electrolysis powered by electricity produced from a coal-fired power plant, (5) coal gasification without carbon capture and storage (CCS), and (6) coal gasification with CCS. Upstream conversion has an outsized influence on the sustainability of a hydrogen transition in Colombia. Impact levels for wind-powered electrolysis are lower than those of the coal- and grid-powered scenarios for every impact category analyzed, apart from emissions of aluminum to air, nitrogen emissions to water, and phosphorous, nitrate, and nitrite emissions to soil. The grid-based electrolysis scenario is found to consume the largest amount of water, while coal-fueled scenarios pathways raise concerns of greater life-cycle mercury, nickel, and arsenic emissions. While coal gasification with CCS reduced gasification CO2 emissions by 35%, the CCS scenario’s VOC emissions were 37% greater than gasification without CCS, given that increased levels of coal inputs were required to account for the loss of efficiency associated with the addition of CCS technology. For Colombia to benefit most from a hydrogen-based decarbonization transition with minimal environmental impacts, community-focused planning and wind-based hydrogen systems should be prioritized.

  • Mapping Spatiotemporal Disparities in Residential Electricity Inequality Using Machine Learning

    UNC Libraries · 2025-10-30

    articleOpen access

    The move toward electrification is critical for decarbonizing the energy sector but may exacerbate energy unaffordability without proper safeguards. Addressing this challenge requires capturing neighborhood-scale dynamics to uncover the blind spots in residential electricity inequality. Based on publicly available, multisourced remote sensing and census data, we develop a high-resolution, spatiotemporally explicit machine learning (ML) framework to predict tract-level monthly electricity consumption across the conterminous U.S. from 2013-2020. We then construct the electricity affordability gap (EAG) metric, defined as the gap between electricity bills and 3% of household income, to better identify energy-vulnerable communities over space and time. The results show that our framework largely improves the resolution of electricity consumption data while achieving an <i>R</i><sup>2</sup> of 0.82 compared to the Low-Income Energy Affordability Data (LEAD). We estimate an annual $16.18 billion economic burden on the ability to afford electricity bills, exceeding current federal appropriations in alleviating energy difficulties. We also observe pronounced seasonal and urban-rural disparities, with monthly EAG in summer and winter being 2-3 times greater than other seasons and rural residents facing burdens up to 1.7 times higher than their urban counterparts. These insights inform equitable electrification by addressing spatiotemporal mismatches and multiple jurisdictional challenges in energy justice efforts.

  • Charging forward: A greenhouse gas emissions analysis of New York State's electric vehicle and clean energy goals

    Energy Policy · 2025-03-05 · 8 citations

    articleSenior authorCorresponding
  • Deforestation and biomass fuel dynamics in Uganda

    UNC Libraries · 2025-02-18

    articleOpen accessSenior author
  • New Insight into the Measurements of Particle-Bound Metals in the Urban and Remote Atmospheres of the Sarajevo Canton and Modeled Impacts of Particulate Air Pollution in Bosnia and Herzegovina

    UNC Libraries · 2025-02-18

    articleOpen access

    The Sarajevo Canton Winter Field Campaign 2018 (SAFICA) was a project that took place in winter 2017-2018 with an aim to characterize the chemical composition of aerosol in the Sarajevo Canton, Bosnia and Herzegovina (BiH), which has one of the worst air qualities in Europe. This paper presents the first characterization of the metals in PM<sub>10</sub> (particulate matter aerodynamic diameters &le;10 &mu;m) from continuous filter samples collected during an extended two-months winter period at the urban background Sarajevo and remote Ivan Sedlo sites. We report the results of 18 metals detected by inductively coupled plasma mass spectrometry (ICP-MS) and electrothermal atomic absorption spectrometry (ETAAS). The average mass concentrations of metals were higher at the Sarajevo site than at Ivan Sedlo and ranged from 0.050 ng/m<sup>3</sup> (Co) to 188 ng/m<sup>3</sup> (Fe) and from 0.021 ng/m<sup>3</sup> (Co) to 61.8 ng/m<sup>3</sup> (Fe), respectively. The BenMAP-CE model was used for estimating the annual BiH health (50% decrease in PM<sub>2.5</sub> would save 4760+ lives) and economic benefits (costs of $2.29B) of improving the air quality. Additionally, the integrated energy and health assessment with the ExternE model provided an initial estimate of the additional health cost of BiH's energy system.

  • Decline processes in technological innovation systems: Lessons from energy technologies

    UNC Libraries · 2025-02-18

    articleOpen accessSenior author

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