In the past several decades, a variety of efforts have been made in the United States to improve air quality, and ambient particulate matter (PM) concentrations have been used as a metric to evaluate the efficacy of environmental policies. However, ambient PM concentrations result from a combination of source emission rates and meteorological conditions, which also change over time.
Dispersion normalization was recently developed to reduce the influence of atmospheric dispersion and proved an effective approach that enhanced diel/seasonal patterns and thus provides improved source apportionment results for speciated PM mass and particle number concentration (PNC) measurements. In this work, dispersion normalization was incorporated in long-term trend analysis of 11–500 nm PNCs derived from particle number size distributions (PNSDs) measured in Rochester, NY from 2005 to 2019.
Before dispersion normalization, a consistent reduction was observed across the measured size range during 2005–2012, while after 2012, the decreasing trends slowed down for accumulation mode PNCs (100–500 nm) and reversed for ultrafine particles (UFPs, 11–100 nm). Through dispersion normalization, we showed that these changes were driven by both emission rates and dispersion.
Thus, it is important for future studies to assess the effects of the changing meteorological conditions when evaluating policy effectiveness on controlling PM concentrations. Before and after dispersion normalization, an evident increase in nucleation mode particles was observed during 2015–2019.
This increase was possibly enabled by a cleaner atmosphere and will pose new challenges for future source apportionment and accountability studies.