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Long term trends in source apportioned particle number concentrations in Rochester NY.
Hopke, Philip K; Chen, Yunle; Chalupa, David C; Rich, David Q.
Afiliación
  • Hopke PK; Department of Public Health Sciences, University of Rochester School of Medicine and Dentistry, Rochester, NY, 14642, USA; Institute for a Sustainable Environment, Clarkson University, Potsdam, NY, 13699, USA. Electronic address: phopke@clarkson.edu.
  • Chen Y; Department of Public Health Sciences, University of Rochester School of Medicine and Dentistry, Rochester, NY, 14642, USA.
  • Chalupa DC; Department of Environmental Medicine, University of Rochester School of Medicine and Dentistry, Rochester, NY, 14642, USA.
  • Rich DQ; Department of Public Health Sciences, University of Rochester School of Medicine and Dentistry, Rochester, NY, 14642, USA; Department of Environmental Medicine, University of Rochester School of Medicine and Dentistry, Rochester, NY, 14642, USA.
Environ Pollut ; 347: 123708, 2024 Apr 15.
Article en En | MEDLINE | ID: mdl-38442826
ABSTRACT
During the past two decades, efforts have been made to further reduce particulate air pollution across New York State through various Federal and State policy implementations. Air quality has also been affected by economic drivers like the 2007-2009 recession and changing costs for different approaches to electricity generation. Prior work has focused on particulate matter with aerodynamic diameter ≤2.5 µm. However, there is also interest in the effects of ultrafine particles on health and the environment and analyses of changes in particle number concentrations (PNCs) are also of interest to assess the impacts of changing emissions. Particle number size distributions have been measured since 2005. Prior apportionments have been limited to seasonal analyses over a limited number of years because of software limitations. Thus, it has not been possible to perform trend analyses on the source-specific PNCs. Recent development have now permitted the analysis of larger data sets using Positive Matrix Factorization (PMF) including its diagnostics. Thus, this study separated and analyzed the hourly averaged size distributions from 2005 to 2019 into two data sets; October to March and April to September. Six factors were resolved for both data sets with sources identified as nucleation, traffic 1, traffic 2, fresh secondary inorganic aerosol (SIA), aged SIA, and O3-rich aerosol. The resulting source-specific PNCs were combined to provide continuous data sets and analyzed for trends. The trends were then examined with respect to the implementation of regulations and the timing of economic drivers. Nucleation was strongly reduced by the requirement of ultralow (<15 ppm) sulfur on-road diesel fuel in 2006. Secondary inorganic particles and O3-rich PNCs show strong summer peaks. Aged SIA was constant and then declined substantially in 2015 but rose in 2019. Traffic 1 and 2 have steadily declined bur rose in 2019.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Contaminantes Atmosféricos / Contaminación del Aire País/Región como asunto: America do norte Idioma: En Revista: Environ Pollut Asunto de la revista: SAUDE AMBIENTAL Año: 2024 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Contaminantes Atmosféricos / Contaminación del Aire País/Región como asunto: America do norte Idioma: En Revista: Environ Pollut Asunto de la revista: SAUDE AMBIENTAL Año: 2024 Tipo del documento: Article