IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v59y2013icp459-469.html
   My bibliography  Save this article

Residential demand response reduces air pollutant emissions on peak electricity demand days in New York City

Author

Listed:
  • Gilbraith, Nathaniel
  • Powers, Susan E.

Abstract

Many urban areas in the United States have experienced difficulty meeting the National Ambient Air Quality Standards (NAAQS), partially due to pollution from electricity generating units. We evaluated the potential for residential demand response to reduce pollutant emissions on days with above average pollutant emissions and a high potential for poor air quality. The study focused on New York City (NYC) due to non-attainment with NAAQS standards, large exposed populations, and the existing goal of reducing pollutant emissions. The baseline demand response scenario simulated a 1.8% average reduction in NYC peak demand on 49 days throughout the summer. Nitrogen oxide and particulate matter less than 2.5μm in diameter emission reductions were predicted to occur (−70, −1.1metric tons (MT) annually), although, these were not likely to be sufficient for NYC to meet the NAAQS. Air pollution mediated damages were predicted to decrease by $100,000–$300,000 annually. A sensitivity analysis predicted that substantially larger pollutant emission reductions would occur if electricity demand was shifted from daytime hours to nighttime hours, or the total consumption decreased. Policies which incentivize shifting electricity consumption away from periods of high human and environmental impacts should be implemented, including policies directed toward residential consumers.

Suggested Citation

  • Gilbraith, Nathaniel & Powers, Susan E., 2013. "Residential demand response reduces air pollutant emissions on peak electricity demand days in New York City," Energy Policy, Elsevier, vol. 59(C), pages 459-469.
    • Handle: RePEc:eee:enepol:v:59:y:2013:i:c:p:459-469
    DOI: 10.1016/j.enpol.2013.03.056
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301421513002346
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.enpol.2013.03.056?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Newsham, Guy R. & Bowker, Brent G., 2010. "The effect of utility time-varying pricing and load control strategies on residential summer peak electricity use: A review," Energy Policy, Elsevier, vol. 38(7), pages 3289-3296, July.
    2. Allcott, Hunt, 2011. "Rethinking real-time electricity pricing," Resource and Energy Economics, Elsevier, vol. 33(4), pages 820-842.
    3. Muller, Nicholas Z. & Mendelsohn, Robert, 2007. "Measuring the damages of air pollution in the United States," Journal of Environmental Economics and Management, Elsevier, vol. 54(1), pages 1-14, July.
    4. Ashok, S. & Banerjee, R., 2003. "Optimal cool storage capacity for load management," Energy, Elsevier, vol. 28(2), pages 115-126.
    5. Gottwalt, Sebastian & Ketter, Wolfgang & Block, Carsten & Collins, John & Weinhardt, Christof, 2011. "Demand side management—A simulation of household behavior under variable prices," Energy Policy, Elsevier, vol. 39(12), pages 8163-8174.
    6. Ahmad Faruqui & Sanem Sergici, 2010. "Household response to dynamic pricing of electricity: a survey of 15 experiments," Journal of Regulatory Economics, Springer, vol. 38(2), pages 193-225, October.
    7. Nicholas Z. Muller & Robert Mendelsohn, 2009. "Efficient Pollution Regulation: Getting the Prices Right," American Economic Review, American Economic Association, vol. 99(5), pages 1714-1739, December.
    8. Hawkes, A.D., 2010. "Estimating marginal CO2 emissions rates for national electricity systems," Energy Policy, Elsevier, vol. 38(10), pages 5977-5987, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Howard, B. & Waite, M. & Modi, V., 2017. "Current and near-term GHG emissions factors from electricity production for New York State and New York City," Applied Energy, Elsevier, vol. 187(C), pages 255-271.
    2. Hyun, Minwoo & Kim, Yeong Jae & Eom, Jiyong, 2020. "Assessing the impact of a demand-resource bidding market on an electricity generation portfolio and the environment," Energy Policy, Elsevier, vol. 147(C).
    3. Smith, Alexander M. & Brown, Marilyn A., 2015. "Demand response: A carbon-neutral resource?," Energy, Elsevier, vol. 85(C), pages 10-22.
    4. Nikolaos Iliopoulos & Motoharu Onuki & Miguel Esteban, 2021. "Shedding Light on the Factors That Influence Residential Demand Response in Japan," Energies, MDPI, vol. 14(10), pages 1-23, May.
    5. Nsanzineza, Rene & O’Connell, Matthew & Brinkman, Gregory & Milford, Jana B., 2017. "Emissions implications of downscaled electricity generation scenarios for the western United States," Energy Policy, Elsevier, vol. 109(C), pages 601-608.
    6. Bastida, Leire & Cohen, Jed J. & Kollmann, Andrea & Moya, Ana & Reichl, Johannes, 2019. "Exploring the role of ICT on household behavioural energy efficiency to mitigate global warming," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 455-462.
    7. Krieger, Elena M. & Casey, Joan A. & Shonkoff, Seth B.C., 2016. "A framework for siting and dispatch of emerging energy resources to realize environmental and health benefits: Case study on peaker power plant displacement," Energy Policy, Elsevier, vol. 96(C), pages 302-313.
    8. Guo, Peiyang & Li, Victor O.K. & Lam, Jacqueline C.K., 2017. "Smart demand response in China: Challenges and drivers," Energy Policy, Elsevier, vol. 107(C), pages 1-10.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Woo, C.K. & Sreedharan, P. & Hargreaves, J. & Kahrl, F. & Wang, J. & Horowitz, I., 2014. "A review of electricity product differentiation," Applied Energy, Elsevier, vol. 114(C), pages 262-272.
    2. Qiu, Yueming & Colson, Gregory & Wetzstein, Michael E., 2017. "Risk preference and adverse selection for participation in time-of-use electricity pricing programs," Resource and Energy Economics, Elsevier, vol. 47(C), pages 126-142.
    3. Boßmann, Tobias & Eser, Eike Johannes, 2016. "Model-based assessment of demand-response measures—A comprehensive literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1637-1656.
    4. Layer, Patrick & Feurer, Sven & Jochem, Patrick, 2017. "Perceived price complexity of dynamic energy tariffs: An investigation of antecedents and consequences," Energy Policy, Elsevier, vol. 106(C), pages 244-254.
    5. Yan, Xing & Ozturk, Yusuf & Hu, Zechun & Song, Yonghua, 2018. "A review on price-driven residential demand response," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 411-419.
    6. Dütschke, Elisabeth & Paetz, Alexandra-Gwyn, 2013. "Dynamic electricity pricing—Which programs do consumers prefer?," Energy Policy, Elsevier, vol. 59(C), pages 226-234.
    7. LaPlue, Lawrence D., 2022. "Environmental consequences of natural gas wellhead pricing deregulation," Journal of Environmental Economics and Management, Elsevier, vol. 116(C).
    8. Feuerriegel, Stefan & Neumann, Dirk, 2014. "Measuring the financial impact of demand response for electricity retailers," Energy Policy, Elsevier, vol. 65(C), pages 359-368.
    9. Meyabadi, A. Fattahi & Deihimi, M.H., 2017. "A review of demand-side management: Reconsidering theoretical framework," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 367-379.
    10. Mattias Vesterberg and Chandra Kiran B. Krishnamurthy, 2016. "Residential End-use Electricity Demand: Implications for Real Time Pricing in Sweden," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    11. Y, Kiguchi & Y, Heo & M, Weeks & R, Choudhary, 2019. "Predicting intra-day load profiles under time-of-use tariffs using smart meter data," Energy, Elsevier, vol. 173(C), pages 959-970.
    12. Takanori Ida, Kayo Murakami, and Makoto Tanaka, 2016. "Electricity demand response in Japan: Experimental evidence from a residential photovoltaic power-generation system," Economics of Energy & Environmental Policy, International Association for Energy Economics, vol. 0(Number 1).
    13. Miller, Reid & Golab, Lukasz & Rosenberg, Catherine, 2017. "Modelling weather effects for impact analysis of residential time-of-use electricity pricing," Energy Policy, Elsevier, vol. 105(C), pages 534-546.
    14. Gambardella, Christian & Pahle, Michael, 2018. "Time-varying electricity pricing and consumer heterogeneity: Welfare and distributional effects with variable renewable supply," Energy Economics, Elsevier, vol. 76(C), pages 257-273.
    15. Milan Ščasný & Emanuele Massetti & Jan Melichar & Samuel Carrara, 2015. "Quantifying the Ancillary Benefits of the Representative Concentration Pathways on Air Quality in Europe," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 62(2), pages 383-415, October.
    16. Nicholas Z. Muller, 2014. "Toward the Measurement of Net Economic Welfare: Air Pollution Damage in the US National Accounts–2002, 2005, 2008," NBER Chapters, in: Measuring Economic Sustainability and Progress, pages 429-459, National Bureau of Economic Research, Inc.
    17. Vesterberg, Mattias, 2017. "Power to the people: Electricity demand and household behavior," Umeå Economic Studies 942, Umeå University, Department of Economics.
    18. Britt Groosman & Nicholas Muller & Erin O’Neill-Toy, 2011. "The Ancillary Benefits from Climate Policy in the United States," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 50(4), pages 585-603, December.
    19. Ren'e Aid & Dylan Possamai & Nizar Touzi, 2018. "Optimal electricity demand response contracting with responsiveness incentives," Papers 1810.09063, arXiv.org, revised May 2019.
    20. Lorraine Conway & David Prentice, 2020. "How Much do Households Respond to Electricity Prices? Evidence from Australia and Abroad," Economic Papers, The Economic Society of Australia, vol. 39(3), pages 290-311, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:enepol:v:59:y:2013:i:c:p:459-469. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/enpol .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.