Reduced Ultrafine Particle Concentration in Urban Air: Changes in

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Characterization of Natural and Affected Environments

Reduced Ultrafine Particle Concentration in Urban Air: Changes in Nucleation and Anthropogenic Emissions Provat K Saha, Ellis S. Robinson, Rishabh Urvesh Shah, Naomi Zimmerman, Joshua Schulz Apte, Allen L. Robinson, and Albert A Presto Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.8b00910 • Publication Date (Web): 18 May 2018 Downloaded from http://pubs.acs.org on May 18, 2018

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Environmental Science & Technology

Reduced Ultrafine Particle Concentration in Urban Air: Changes in Nucleation and Anthropogenic Emissions Provat K. Sahaa, Ellis S. Robinsona, Rishabh U. Shaha, Naomi Zimmermana,c, Joshua S. Apteb, Allen L. Robinsona, Albert A. Prestoa* a

Center for Atmospheric Particle Studies, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, Pennsylvania 15213, United States b Department of Civil, Architectural and Environmental Engineering, University of Texas at Austin, Austin, Texas 78712, United States c now at: Department of Mechanical Engineering, University of British Columbia, Vancouver, BC V6T 1Z2, Canada Abstract: Nucleation is an important source of ambient ultrafine particles (UFP). We present observational evidence of the changes in the frequency and intensity of nucleation events in urban air by analyzing long-term particle size distribution measurements at an urban background site in Pittsburgh, Pennsylvania during 2001-02 and 2016-17. We find that both frequency and intensity of nucleation events have been reduced by 40-50 % over the past 15 years, resulting in a 70% reduction in UFP concentrations from nucleation. On average, the particle growth rates are 30% slower than 15 years ago. We attribute these changes to dramatic reductions in SO2 (more than 90%) and other pollutant concentrations. Overall, UFP concentrations in Pittsburgh have been reduced by ~ 48% in the past 15 years, with a ~70% reduction in nucleation, ~ 27% in weekday local sources (e.g., weekday traffic) and 49% in the regional background. Our results highlight that a reduction in anthropogenic emissions can considerably reduce nucleation events and UFP concentrations in a polluted urban environment. TOC graphic

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*Address correspondence to: Albert A. Presto, 5000 Forbes Avenue, Doherty Hall 2115, Pittsburgh, Pennsylvania 15213, United States. Email: [email protected], Phone: 412721-5203

1. INTRODUCTION Airborne ultrafine particles (UFP), typically defined as particles with a diameter less than 100 nm, are ubiquitous in urban environments.1 There is growing evidence that UFP have adverse health impacts due to their higher penetration and deposition efficiencies in the lung and likely have a higher toxicity than larger particles. 2–8 UFP is characterized by high number concentration but negligible mass; therefore, the most commonly used metric for characterizing ambient UFP exposure is particle number concentration (PNC). 1,9,10 Many sources contribute to ambient UFP concentrations. In urban areas, both combustion sources (e.g., primary particles from traffic emissions) 10,11 and atmospheric formation of new particles (nucleation) 12–17 are identified as the major contributors to UFP concentrations. 1,18,19 Traffic emissions may also include nanoparticle formation as fresh exhaust rapidly mixes with the ambient atmosphere.20 New particles form in the atmosphere by nucleation of gas-phase species,21–23 characterized by a large increase in particle number concentrations and subsequent particle growth.24 Frequent and intense nucleation events have been reported in many urban locations around the world,14–17,25–28 including very polluted megacities in China with high aerosol loadings.13,14,28–31 Many factors influence the frequency and intensity of nucleation events. High concentrations of gas-phase precursors (e.g., SO2) and oxidants (O3, OH), high insolation, and low pre-existing particle surface area are common features that promote nucleation.18,23,32 Numerous studies have shown strong correlation between ambient SO2 concentrations and occurrence of nucleation events.13– 15,25–27 Several recent studies13,14,30,31 suggest that, even though polluted urban environments have high condensation sink (CS), high gas-phase precursor concentrations and strong oxidant conditions promote the frequency and intensity of nucleation and particle growth. Anthropogenic emissions of gaseous and particulate air pollutants in the US have been substantially reduced over recent years. For example, between 2000 and 2016, national-average ambient SO2 concentrations in the US were reduced by 72 %, NO2 concentrations reduced by 47%, and fine particulate matter (PM2.5) levels reduced by 42% (www.epa.gov/air-trends). However, the effects of the reductions in gaseous and aerosol emissions on atmospheric new particle formation are complex and uncertain because of non-linearities and feedbacks in the system.21 The changes in anthropogenic emissions could either increase or decrease the frequency and intensity of nucleation events and subsequent particle growth. Reductions of particulate emissions decrease the pre-existing aerosols surface area (~CS), which can enhance nucleation. A modeling study by Gaydos et al.33 predicted that reductions of SO2 could either increase or decrease nucleation events, depending on the extent of reductions and season. However, nucleation modeling is uncertain. We need experimental evidence of how a reduction in anthropogenic emissions alters new particle formation events and ambient UFP concentrations to develop and evaluate efficient control strategies for the ambient UFP exposure burden. In this paper, we investigated changes in nucleation and UFP concentrations in urban air with a reduction in anthropogenic emissions by analyzing two long-term particle size distribution datasets measured at an urban background site in Pittsburgh, Pennsylvania. One dataset is from 2 ACS Paragon Plus Environment

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recent years (2016-17) and another from 15 years ago (2001-02). Over this period there have been dramatic reductions of most criteria air pollutants in Pittsburgh. We examine the changes in factors associated with nucleation, including precursor concentrations, oxidants, condensation sink, and meteorology. Finally, we describe the overall changes in UFP concentrations and the contributions of different sources. 2. MATERIALS AND METHOD 2.1 Experimental We measured particle number and other air pollutant concentrations at an urban background site in Pittsburgh, Pennsylvania. Two year-long measurement campaigns were conducted, one from July 2001 to June 2002 as part of the Pittsburgh Air Quality Study (PAQS) 34 and another from September 2016 to August 2017 as part the Center for Air, Climate and Energy Solutions (CACES). Hereafter, these two data sets are referred to as 2001-02 and 2016-17, respectively. The frequency and intensity of the nucleation events in the 2001-02 dataset are described in Stanier et al.. 15 In both campaigns, the submicron particle size distribution measurements were collected continuously using a Scanning Mobility Particle Sizer (SMPS) system (TSI Inc.). The two sampling sites are 250 m apart and located in a similar urban background environmental setting. The sampling setups were similar, both using a cyclone with an inlet ~5 meters above ground level. The PAQS study used two SMPS systems (TSI 3936L10 and TSI 3936N25; TSI butanol CPCs 3010 and 3025.) 15 that were a part of the dry-ambient aerosol sizing system (DAASS), and were alternatively sampled between ambient relative humidity (RH) samples and dried samples. The CACES study used a SMPS system (TSI DMA 3081, TSI butanol CPC 3772) and only measured ambient RH samples. To be consistent with the recent measurements, we analyzed the measurements made at ambient RH in the PAQS dataset. The PAQS data set has been extensively discussed in several previous publications.15,33,34 The size distributions of particles from 3 to 680 nm were measured during PAQS (2001-02), whereas the SMPS sampling size range in recent measurements (2016-17) was ~10-300 nm. Hence, to be consistent with the recent dataset, a size window of 10-300 nm was considered for the analysis presented in this paper for both datasets. Additional supporting measurements included SO2, O3, PM2.5, and meteorological parameters. Instrumentation details for CACES (2016-17) measurements are given in the Supporting Information (SI), Table S1. Details on PAQS (200102) data set and instrumentation can be found in Stanier et al..15 All data were averaged to hourly resolution for analyses presented in this paper. 327 and 270 complete days were available for analysis for the PAQS and CACES datasets, respectively. 2.2 Characterizing nucleation events The particle size distribution measurements from 2001-02 and 2016-17 were analyzed to identify and characterize nucleation events.24,26 We then compared the two data sets to examine changes in nucleation events over time. Figure 1 illustrates the analysis approach. The diurnal plot of size distributions and integrated particle number concentrations on each sampling day were visually inspected to identify 3 ACS Paragon Plus Environment


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nucleation versus non-nucleation days. A day was classified as a nucleation day if a substantial presence of nuclei mode (smaller than ~50 nm) particles (dN50/dt > ~4000 cm-3 h-1) appeared in the size distributions over a period of several (more than 3) hours typically starting around late morning to midday, and subsequently showed a large increase in particle number concentrations. On a nucleation day, if the newly formed particles grow over several hours, resulting in sustained growth (so-called ‘banana’ nucleation, see the example, Figure 1a) of nucleation mode particles to larger sizes, the day was classified as a regional nucleation day. A nucleation day without a significant growth of nuclei mode particles to larger sizes was classified as a “short-lived” nucleation day (see the example, Figure 1b). A non-nucleation day had no or little presence of nuclei mode particles and increase in particle number concentrations in the middle of the day. Example data from a typical non-nucleation day is shown in the SI, Figure S1. B

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analysis for the 2001-02 data, we reanalyzed that dataset to ensure consistency between the two time periods. The results from the re-analysis of the 2001-02 dataset agree to within 3-10% of the Stanier et al.15 analysis (See Table S2). On a nucleation day, we quantified the intensity of the nucleation event in terms of formation rate (# cm-3 s-1), which was estimated as of the rate of change of the particle number concentrations between the nucleation event start time and event peak time.24,26 Details on the formation rate calculations are given in the SI. The event start time is when a substantial presence of smaller size (10-15 nm) particles (dN10-15/dt > 2000 cm-3 h-1) first appeared in the measured size distributions (see Figure 1, point A), typically around late morning/noon. The event peak time is when the particle number concentrations reached a peak during the event (see Figure 1, point B). Finally, the event end time (Figure 1 point C) is when the concentrations decreased to a level closer (within 10-20%) to the starting point (A). The time duration between point A and point C is the event duration. The event start (point A), peak (point B) and end (point C) times were identified by visual inspection of the size distributions and particle number concentrations time series plots 26,35 (Figure 1). The difference in particle number concentrations between point A and point B indicates the maximum enhancement of particle concentrations during the event (referred to as peak Ntot enhancement), and was used as another metric of intensity of nucleation intensity. We estimated the particle growth rate on regional nucleation days from the measured size distributions time series plot, using an approach similar to Hamed et al.26 and Dal Maso et al.35. This involved quantitatively tracking the temporal change of the nucleation mode diameter on a regional nucleation day. In our analysis, we estimated the growth rates (nm h-1) as the slope of the growth curve of nucleation mode particles from ~10 to ~50 nm, as shown in Figure 1a. This window was operationally defined. The lower end was limited by our measured lower size cut. On the other hand, above 50 nm, a clear distinguishing of nucleated particles from background particles was difficult in some cases. Therefore, in practice, the growth time for estimation of growth rate was the time between the growth of smaller size (~ 10 nm; point D, Figure 1a) to a larger size (~ 50 nm; point E, Figure 1a). The slope between points D and E is reported as the growth rate. Our indices for characterizing nucleation events (e.g., formation rate, growth rate) are empirical and limited to the measured size window. Since we seek to quantitatively compare changes in nucleation events between two data sets, consistency in analysis approach between the two data sets is critical. A standard and consistent procedure was followed for analyzing both data sets.

3. RESULTS AND DISCUSSION 3.1 Changes in nucleation events Figure 2 summarizes the different nucleation metrics in the 2001-02 and 2016-17 datasets. Averages are presented for each season: winter (Dec, Jan, Feb), spring (Mar, April, May), summer (June, July, Aug), and fall (Sept. Oct, Nov) as well as the annual (overall) summary. Figure 2a shows frequency of nucleation events during 2001-02 and 2016-17. Nucleation events were observed throughout the year in both datasets, with a higher frequency in warmer months 5 ACS Paragon Plus Environment


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and lower in winter, consistent with previous observations in diverse environmental settings.14,16,25,26,35 Both regional and short-lived nucleation events occurred in all seasons. The frequency of regional nucleation events was higher in spring and fall and lower in summer and winter. During 2001-02, overall, nucleation occurred on ~ 50% of the study days, with regional nucleation on ~30% of days and short-lived nucleation on ~ 20% of days. In 2016-17, the frequency of both regional and short-lived nucleation events was substantially lower; overall nucleation occurred on ~ 27 % of the study days, with regional nucleation on ~10 % of days and short-lived nucleation on ~17% of days. The frequency of nucleation events was reduced across all seasons. The largest change was observed in winter, especially for the regional nucleation. The reduction in regional nucleation frequency was larger than short-lived nucleation frequency. Considering both kinds of nucleation events, the overall nucleation frequency was reduced by ~50% over the past 15 years. b) Formation rate

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Figure 2: Nucleation in Pittsburgh in 2001-02 and 2016-17. a) Frequency of nucleation, b) formation rate, c) peak Ntot enhancement, and d) growth rate on a regional nucleation day. In panel b, c, and d, the box shows interquartile range (25th -75th percentile), the line inside the box is the median, and the star represents the mean. Spring data from the 2016-17 dataset is not included in panel (b-d) because data coverage was relatively low (31 of 92 possible days, see Table S3). Figure 2b shows the estimated new particle formation rates, a measure of the intensity of nucleation events, for the nucleation events observed during 2001-02 and 2016-17. The 6 ACS Paragon Plus Environment

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formation rate has a clear seasonal trend, with higher rates in summer and lower in winter. Although a similar seasonal trend was observed for both datasets, the magnitudes of the formation rates were substantially lower in the 2016-17 dataset. For example, the study-average formation rate was ~3.2 cm-3 s-1 during 2001-02 versus ~1.75 cm-3 s-1 during 2016-17, indicating ~45% reduction in intensity of nucleation events over the past 15 years. Our data coverage for the spring 2016-17 was relatively low (31 days out of 92 days) (see Table S3); therefore, the observed trend may not be representative of the spring, and is not included in Figure 2(b-d). However, this has little influence on the overall trends. If we eliminate the spring measurements from both data sets, the overall trends do not change. For example, after excluding spring measurements from both data sets, the estimated study-average formation rate was 3.1 cm3 -1 s for the 2001-02 measurements, and 2.0 cm-3 s-1 for the 2016-17 measurements, a ~35% reduction. Figure 2c shows peak enhancement of particle number concentrations (peak ∆Ntot) for the nucleation events observed in 2001-02 and 2016-17. This is another measure of the intensity of nucleation events. Similar to the formation rate and frequency, the peak ∆Ntot was higher in warmer seasons and lower in winter. A substantial reduction was observed for the peak ∆Ntot, across all seasons in 2016-2017. While the study-average peak ∆Ntot was 20,500 cm-3 during 2001-02, it was 12,000 cm-3 in 2016-17, indicating an overall ~ 40 % reduction. Hence, both the estimated formation rates (Figure 2b) and peak ∆Ntot (Figure 2c) indicate that the intensity of nucleation events has been reduced by ~ 35-45% over the last 15 years. Figure 2d shows the estimated particle growth rates on regional nucleation days. For both data sets, the maximum growth rates were observed in summer and minimum in winter. The estimated average growth rate of the nucleation mode particles was ~ 5.8 nm h-1 in 2001-02, and ~ 4.1 nm h-1 in 2016-17. These ranges are similar to data from many urban environments.12,14,26,27 Typically, low growth rates are observed in clean environments whereas high growth rates are observed in polluted environments.12,14,26,27,32,35 Many factors, including concentrations of condensable vapors (e.g., sulfuric acid, low volatility organics), oxidant concentrations (O3, OH), and condensation sink (CS) control the particle growth rates.36,37 If the amount of condensable vapors available per particle remains the same, a decrease in CS should increase the particle growth rates. The observed reduction in particle growth rates with the decrease in CS suggests a reduction in the amount of condensable vapor available per particle. High precursor concentrations and strong oxidant conditions in polluted urban environments can accelerate particle growth.13,14,27 On average, our result shows that the particle growth rate during nucleation events in Pittsburgh has been reduced by ~30% over the last 15 years. 3.2 Changes in factors associated with nucleation There have been dramatic improvements in air quality in Pittsburgh over the past 15 years. Many of these changes likely influence the frequency and intensity of nucleation events. In this section, we explore changes in different factors associated with nucleation, including precursor concentrations, oxidants, condensation sink, and meteorology. These factors are plotted in Figure 3 and Figure S4.



Nucleation frequency and intensity depends strongly on precursor concentrations.13,14,23,25–27,35,38 Ternary (NH3-H2SO4-H2O) nucleation is thought to be the controlling mechanism in Pittsburgh 33 and globally 36. Therefore changes in SO2 and NH3 likely will influence nucleation rates. Figure 3a shows that the ambient SO2 concentrations in Pittsburgh have been reduced by more than 90% over the past 15 years, which is somewhat more than the national ~72% decrease. This is due to stringent controls placed on coal-fired power plants. Ambient NH3 concentrations were not measured during our field campaigns. However, data from the Ammonia Monitoring Network (AMoN) (Figure 3b and Figure S3) suggests little change in ambient NH3 concentrations in the northeastern US. Low-volatility organics (LVOCs) can play an important role on particle formation and growth.21–23 We do not have a direct measurement of LVOCs at our site. A comparison of AMS measured oxygenated organic aerosol (OOA, a proxy for LVOCs) concentrations (2.9±1.6 µg m-3 in 2002 versus 3.0±1 µg m-3 in 2016) suggests little change in low-volatility organic compounds in Pittsburgh over the last 15 years. Therefore, it seems likely that the large reduction in ambient SO2 concentrations primarily drives the reduced nucleation frequency, intensity, and particle growth. Gaydos et al.33 simulated how changes in emissions of SO2 and NH3 could alter nucleation observations. They predicted that substantial reductions in SO2 emissions (>40%) would reduce nucleation in both summer and winter. They also predicted that the effects of SO2 reduction on nucleation would be more drastic in winter than summer, consistent with our data. Oxidation reactions generate condensable vapors to drive nucleation and growth. Therefore, elevated oxidant concentrations can accelerate nucleation intensity and growth rates.26,27,39 The 2001-02 and 2016-17 annual average O3 concentrations, shown in Figure 3c, were basically the same, but the extreme O3 levels (e.g., 90th percentile) were reduced by ~10-15%. Reduction of O3 should decrease the nucleation rates, but a change of ~10-15% is likely not big enough to explain the observed changes in nucleation rate.

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Figure 3: Changes in different factors associated with nucleation. (a) SO2, (b) NH3, (c) O3, and (d) condensation sink (CS). The box shows data interquartile range, the line inside the box is the median, the length of the whiskers covers 95% of the data, and the star represents the mean. Meteorological factors are shown in the SI, Figure S4. *NH3 data are shown from AMoN network; concentrations across all available sites in US. 8 ACS Paragon Plus Environment

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The average PM2.5 concentration in Pittsburgh has been reduced by ~35% between 2001-02 and 2016-17, which affects the condensation sink (CS). Lower CS favors nucleation,14,15,26,27 and should counter some reductions in nucleation due to lower SO2 concentrations. We estimated the CS from our measured particle size distributions (10-300 nm) during 2001-02 and 2016-17 (Figure 3d); details on the CS calculations are given in the SI. The overall mean value of CS has been reduced by ~15% between 2001-02 and 2016-17. The estimated CS was only integrated through 300 nm, which likely provides a lower bound estimate of the actual CS. Since nucleation depends inversely on CS, the changes in CS alone cannot explain the observed reduction in nucleation. Multiple meteorological factors can influence nucleation, including solar insolation,15,25,26,40 relative humidity (RH),15,26,38,41 and wind speed 26. No significant differences were observed in any of these between 2001-2002 and 2016-2017 (see Figure S4). Therefore, the changes in nucleation are not driven by changes in meteorology. Overall, we conclude that reductions in nucleation frequency and intensity are the result of lower SO2 concentrations. Reductions in peak O3 concentration may also contribute to less nucleation, while a lower CS may mitigate some of the expected reduction in nucleation due to lower SO2. However, to first order, the reduction in nucleation frequency and intensity is smaller than what would be expected by reductions in SO2 alone. Nucleation rate is often parameterized as a power law (rate = [H2SO4]a[NH3]b), where a is between 1 and 2. This power law parameterization suggests that decreases in [H2SO4] (and its precursor SO2) should result in super-linear reductions in observed nucleation frequency and rate. Ambient SO2 reductions of 90% or more, as has occurred in Pittsburgh, would be expected to produce a ~10-100-fold decrease in nucleation, whereas we only observe a 50% reduction. However, the power-law expression is very simplistic representation of nucleation rate. It does not account for important factors such as the dependence of the initial nucleation rate on CS. In reality, the concentrations of sulfuric acid, low-volatility organic vapors, and CS all influence the new particle formation rates and growth.21–23 Our observed reductions in nucleation events with a large reduction of SO2 concentrations is consistent with Wang et al.42 who analyzed long-term continuous (2001-2009) measurements of particle size distributions (PSD) collected in an urban background site in Rochester, New York. They found about 50-60% reduction in the frequency of nucleation events and 60% reduction of local SO2 concentrations . Nieminen et al.43 reported trends in new-particle formation in a borealforest environment (SMEAR II station, Hyytiälä, Finland) using 16 years of continuous observations (1996-2012). Nieminen et al. 43 observed decreasing nucleation mode (N3-25) particle number concentrations (as well as total PNC) with the decrease in SO2 concentration and condensation sink, along with notable year-to-year variations in the number of new particle formation (NPF) days. One limitation of our study is that we do not have continuous measurements of PSD over 2001-2017 to characterize year-to-year variations in the nucleation events at our site. However, our observed 40-50% reductions in NPF days consistently across all seasons suggest they were not a random fluctuation. One major difference between Hyytiälä and our site is that Hyytiälä is a rural forested site whereas our site is an urban background location. The reduction in SO2 concentrations in Hyytiälä from 1996-2012 was 0.12 ppb whereas we 9 ACS Paragon Plus Environment


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observed 8 ppb reductions in SO2 concentrations between 2001 and 2017 in Pittsburgh. Since the Hyytiälä site has very concentrations of SO2 compared to our site, the effects of the reduction in SO2 on the measured nucleation events may not be as prominent as we observed. More work is needed to further examine the trends in nucleation events in different environmental settings using long-term continuous datasets. 3.3. Changes in UFP concentrations and source contributions The large reduction in nucleation events is expected to influence ambient UFP concentrations. In this section, we discuss the overall changes in UFP concentrations and contribution of different sources to concentration changes between 2001-02 and 2016-17. Figure 4 shows average diurnal UFP concentration profiles for both the 2001-02 and 2016-17 datasets. Profiles are shown for average regional nucleation days, average short-lived nucleation days, average weekdays with no nucleation, and average weekend days with no nucleation. UFP concentrations on each type of day have similar average diurnal profiles in 2001-2002 and 20162017. For example, in both years, the peak concentrations occur around noon on days with nucleation. There is also a clear increase in the UFP concentrations on weekday mornings during traffic-rush hours (7-9 am). However, on average, this traffic peak was weaker than the mid-day nucleation peak. The evening rush hour traffic peak was even weaker than the morning traffic peak, possibly due to a higher atmospheric dilution during the evening. UFP concentrations on non-nucleation weekends showed little diurnal variation. Although there are similar diurnal patterns, the UFP concentrations were substantially lower in the 2016-17, across all types of days (i.e., nucleation days and non-nucleation weekdays and weekends) (Figure 4a). The reduction on non-nucleation days suggests that UFP concentrations from primary sources (e.g., traffic) have also been reduced over the past 15 years. We used the distinct diurnal profiles of UFP concentrations on nucleation and non-nucleation weekdays and weekends (Figure 4a) to perform a simple source apportionment for UFP. Results are shown in Figure 4b and 4c. For this analysis, we assume that the diurnal profiles measured on non-nucleation weekends are the regional background concentrations. More than 75% of the apportioned UFP concentrations are regional background. Since our measurements were collected at an urban background location, away from any local sources (e.g., busy roadside environment), there is likely a higher background UFP concentration at our site compared to the “true” regional background measured at a rural upwind location. What we operationally define here as the regional background UFP concentration is likely comprised of emissions from many sources, including baseline traffic (e.g., traffic on the road both weekdays and weekends), anthropogenic sources upwind, and nucleation from a previous day or upwind location. The difference in concentrations measured on non-nucleation weekdays versus non-nucleation weekends is attributed to local weekday sources, which is likely primarily local traffic. Since the workday local sources (traffic) contribute 5 out of 7 days in a week, their contribution to the annual average UFP profile was estimated as: (non-nucleation weekday – non-nucleation weekend) × (5/7).


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Figure 4: Changes in ultrafine particle (UFP) concentrations and source contributions. a) Average diurnal profile of UFP concentrations on nucleation days and non-nucleation weekdays and weekends in 2001-02 and 2016-17; thick lines show measurements from 2001-02 and thin lines show measurements from 2016-17. b) UFP source apportionment in 2001-02. c) UFP source apportionment in 2016-17. d) Overall UFP concentrations and source contributions in 2001-02 and 2016-17. We define the contribution of nucleation as the difference in concentration profiles measured on nucleation days minus non-nucleation weekdays. We use this particular difference because most nucleation days were weekdays. The overall contribution of nucleation events to the annual average UFP profiles were estimated as: regional nucleation contribution = (regional nucleation day – non-nucleation weekday) × frequency of regional nucleation, and short-lived nucleation contribution = (short-lived nucleation day – non-nucleation weekday) × frequency of short-lived nucleation. The observed overall frequencies of regional and short-lived nucleation events (Figure 2a) were used in the calculations. Our UFP source apportionment analysis results are shown in Figure 4b and 4c for 2001-02 and 2016-17, respectively. The thick black line shows the measured annual average diurnal profiles of UFP concentrations, and different filled areas show the estimated contributions from different sources, such as regional background, local traffic, and nucleation. Overall, there is good closure between the measured total concentrations and the estimated contributions from regional background, local traffic, and nucleation. We slightly under-apportion morning rush hour concentrations in 2001-2002 and afternoon (~12:00-18:00) concentrations in 2016-2017. This may be the result of our simplified treatment of nucleation versus non-nucleation weekdays and 11 ACS Paragon Plus Environment


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weekends. However, the trends obtained by our analysis should be robust to these small errors in UFP closure. The estimated weekday local sources (~ traffic) contribution to the total annual average UFP concentration was ~11% in 2001-02 and ~16% in 2016-17. These estimates are lower than typical estimates of traffic-contributed UFP in urban areas (~40-60%).18,19 Zhou et al. 44 attributed ~20% of UFP concentrations to local traffic by positive matrix factorization (PMF) analysis of the PAQS (2001-02) data. However, our estimate accounts for weekday local traffic, not the total traffic. We attribute a portion of traffic emissions, specifically from gasoline vehicles that operate on both weekdays and weekends, as part of the regional background. Since traffic volumes for gasoline cars are similar on weekdays and weekends, local traffic emissions from gasoline vehicles may constitute a significant fraction of what we define as the regional background. Diesel truck traffic is lower on weekends than weekdays and there is no morning rush on the weekend; our analysis is most sensitive to these weekday-weekend trends for attributing local sources. Our estimated contribution of nucleation events to the total annual average UFP concentrations was ~11% in 2001-02 and ~6% in 2016-17. The contribution is small because nucleation events occur on relatively few days (25-50%) (Figure 2a) and on these days, the elevated UFP concentrations above background levels only lasted for a few (~4-5) hours. This estimated estimate only accounts freshly nucleated particles observed at our site. Our estimated contributions of nucleation to total annual average UFP concentrations are comparable with other recent estimates at different urban locations using different analysis methods.18,19 For example, Sowlat et al.19 reported ~17% contribution from nucleation to the total ambient UFP concentrations in central Los Angeles using PMF analysis. Brines et al.18 reported ~ 14-19% contribution from nucleation in three high-insolation developed world cities (Barcelona, Madrid, Brisbane) using k-means clustering analysis. Figure 4d summarizes the overall changes in UFP concentrations and source contributions between 2001-02 and 2016-17. The annual average UFP concentrations have been reduced by 48% over the past 15 years. Particle number concentrations were lower in all months of the year in 2016-2017 versus 2001-2002 (Figure S5). Our simple source apportionment results suggest a significant drop in UFP concentrations from both nucleation and primary sources. On average, the regional background contribution was reduced by 49%, suggesting a substantial reduction in contribution from many regional sources. The contribution from weekday local sources was reduced by ~27%. This contribution is expected to be primarily traffic; thus changes in traffic activity and emissions would be responsible for the observed changes. Although a comprehensive analysis on changes in trafficrelated UFP contribution is beyond the scope of this paper, we explored the changes in traffic activity and traffic UFP emission factors over the last few years, as shown in Figure S6. The statewide traffic volume in Pennsylvania increased by ~13% between 2001 and 2015, but at the same time, on-road UFP emission factors have reduced significantly. For example, total particle number (PN) emission factors measured in a traffic tunnel in Pittsburgh during 2002 and 2014 showed about 43% reduction over this time (Figure S6). Therefore, the combination of the 12 ACS Paragon Plus Environment

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modest increase in traffic activity and the decrease in traffic PN emission factors is consistent with the estimated ~ 27% decrease in workday local traffic contribution to UFP. Physio-chemical mechanisms other than dilution, including evaporation and coagulation, can influence the evolution of particle size distribution downwind of a roadway 45,46. Therefore, our estimated changes in traffic contributions to UFP at a background location may not imply that roadside concentrations have equally changed.

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The Supporting Information (SI) contains (1) instrumentation details for the 2016-17 dataset (Table S1), (2) summary of month-wise nucleation frequency (Table S2-S3), (3) summary of durations of nucleation events (Table S4), (4) example size distribution plot from a typical nonnucleation day (Figure S1), (5) seasonal ambient O3 concentrations (Figure S2), (6) long term trend in ambient NH3 concentration in the US (Figure S3), (7) temperature and relative humidity in 2001-02 and 2016-17 (Figure S4), (8) monthly average particle number concentrations during 2001-02 and 2016-17 (Figure S5), (9) changes in traffic activity and traffic PN emission factors between 2002 and 2014 (Figure S6), and (10) method for estimation of condensation sink.

There has been an even more dramatic reduction in nucleated particles, ~70% over the last 15 years in Pittsburgh. Since both frequency and intensity of nucleation events reduced by 40-50%, a large reduction in nucleation-sourced UFP contribution is expected, and was evident in our UFP source apportionment analysis. The overall reduction in UFP concentrations reflects the dramatic reductions in emissions from power plants, vehicles, and other sources. However, our measurements were made at an urban background site and therefore do not provide insight into the spatial distribution of UFP concentrations in Pittsburgh. Future work is needed to characterize fine-scale spatial variations in urban UFP exposures.

ACKNOWLEDGEMENTS This publication was developed under Assistance Agreement No. RD83587301 awarded by the U.S. Environmental Protection Agency. It has not been formally reviewed by EPA. The views expressed in this document are solely those of authors and do not necessarily reflect those of the Agency. EPA does not endorse any products or commercial services mentioned in this publication. We thank Charles Stanier (University of Iowa) for providing SMPS data set from 2001-02 (Pittsburgh Air Quality Study). Supporting Information

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Reduced Ultrafine Particle Concentration in Urban Air: Changes in

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