• DocumentCode
    32837
  • Title

    Big Data + Big Cities: Graph Signals of Urban Air Pollution [Exploratory SP]

  • Author

    Jain, Ravinder K. ; Moura, Jose M. F. ; Kontokosta, Constantine E.

  • Author_Institution
    Center for Urban Sci. & Progress, New York Univ., New York, NY, USA
  • Volume
    31
  • Issue
    5
  • fYear
    2014
  • fDate
    Sept. 2014
  • Firstpage
    130
  • Lastpage
    136
  • Abstract
    In this article, we apply signal processing and data science methodologies to study the environmental impact of burning different types of heating oil in New York City, where currently the burning of heavy fuel oil in buildings produces more annual black carbon, a key component of PM2.5, emissions, than all cars and trucks combined. The data utilized in this article are collected through New York City´s Local Law 84 (LL84) energy disclosure mandate. The mandate requires annual energy consumption reporting for large buildings (i.e., approximately greater than 50,000 gross feet) of all use types. This analysis utilizes actual heating oil consumption data for calendar year 2012. The LL84 data set was merged with land use and geographic data at the tax lot level from the Primary Land Use Tax Lot Output (PLUTO) data set from the New York City Department of City Planning. The PLUTO data set provides building and tax lot characteristics, as well as their geographic location.
  • Keywords
    Big Data; aerosols; air pollution; data mining; energy consumption; environmental science computing; fossil fuels; signal processing; AD 2012; Big Data; New York City Department of City Planning; New York LL84 energy disclosure mandate; PLUTO data set; PM2.5, emissions; Primary Land Use Tax Lot Output; USA; Urban; annual energy consumption reporting; data science methodologies; environmental impacts; geographic data; heating oil burning; heating oil consumption data; heavy fuel oil burning; land use data; signal processing methodologies; urban air pollution; Air pollution; Atmospheric modeling; Big data; Buildings; Cities and towns; Environmental factors; Urban areas;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    1053-5888
  • Type

    jour

  • DOI
    10.1109/MSP.2014.2330357
  • Filename
    6879574