From the journal Environmental Science: Atmospheres Peer review history

15-Aug-2021

Dear Dr Gani:

Manuscript ID: EA-ART-07-2021-000058
TITLE: Spatiotemporal profiles of ultrafine particles differ from other traffic-related air pollutants: Lessons from long-term measurements at fixed sites and mobile monitoring

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************

Reviewer 1

Review of Gani et al.

Journal: Environmental Science: Atmospheres

Manuscript #: EA-ART-07-2021-000058

Title: Spatiotemporal profiles of ultrafine particles differ from other traffic-related air pollutants: Lessons from long-term measurements and mobile monitoring.

The study described in the manuscript is well-executed and quite interesting. The datasets utilized are rich, long-term, and high quality. The results and conclusions are well-supported by the data. The paper is generally very well written and will likely be of interest to many readers of your journal and to a wider audience of urban air pollution researchers and stakeholders. The key finding is that individual constituent pollutants in complex mixtures of traffic-related air pollutants cannot always serve as proxies for one another – specifically, NOx cannot always serve as a proxy for UFP. The clear demonstration of this point is both the strength of the paper and the contribution it makes to the literature. I recommend it for publication after a few relatively minor comments are addressed, as described below.

Main and minor issues mixed together:
1. Tables 1 and 2. Why is Pearson-R2 used as the statistical test variance/covariance? Assuming that the pollutant distribution data is non-uniformly distributed, it would make more sense to use a non-parametric statistical test such as the Spearman correlation. Either change statistical analysis method to a non-parametric test or justify the use of Pearson based on the distribution of the data.
2. Add missing CO plots to Fig 1 – CO near-highway and CO-suburban. Or, if they cannot be added, indicate in figure caption why they are absent so that reader is not left to wonder.
3. Line 32. Change to “…periods, NPF can become….”
4. Line 24-5. This sentence is a little vague. Important sources are left out including non-combustion emissions like brakeware and tireware. This sentence would be better if rewritten as follows: “In urban areas the principal sources of UPF include vehicular traffic (tailpipe emissions, brakeware, tireware), other combustion of fossil fuels, cooking and nucleation events”
5. Line 114. Change to “… near-highway site:….urban site, and…”
6. Line 130-1. Discussion of seasonal variation PBLH and its impact on pollutant concentrations needs clarifying. PBL is likely higher during morning and evening rush hours in summer compared to winter. Instead of pointing out that the morning and evening rush hours occur at dawn and dusk in winter, authors should make the contrast with summer in terms of the PBL for consistency.
7. Line 53. TSI model 3783 measures particle number concentration for particles in 7-3000 nm size range. The instrument reports particle number concentration (PNC). The article reports the measurements as UFP (<100 nm), which is misleading. Change “UFP” to “PNC” here and throughout the MS and in figures and tables. Same thing for TSI model 3788 measurements.
8. Line 136. The sentence starting with “The summertime peak.. was convoluted…”. Please rewrite for clarity. “Convoluted” could be interpreted in more than one way and thus it is not clear what your point is.
9. Line 218. It is very interesting that PNC – NOx divergence is most pronounced in residential streets. What could explain this? Specifically, what could explain the PNC blooms in residential areas? Where are the vapors coming from that are nucleating there? This could use a sentence or two and some references to substantiate any hypotheses that might be advanced (to avoid being overly speculative).
10. Line 237-8. The sentence with “…health consequences of freshly-nucleated vs. traffic-emitted particles are still not well understood” needs some details. The sentence implies that the differences between primary and secondary particle tox and/or epi are at least partially understood. If this is the case, then authors should cite the relevant studies. If not, then authors might be advised to simply delete this sentence and avoid the problem since health effects are not central to their study.
11. Discussion of previous studies showing mid-day secondary PNC peaks is missing. This needs to be corrected; reader needs to know that many other studies have reported this same phenomenon. A quick search of studies from the LA basin revealed two studies: (1) Inter-community variability in total particle number concentrations in the eastern Los Angeles air basin N. Hudda, K. Cheung, K. F.Moore, and C. Sioutas, Atmos. Chem. Phys., 10, 11385–11399, 2010 www.atmos-chem-phys.net/10/11385/2010/, and (2) Katharine Moore , Margaret Krudysz , Payam Pakbin , Neelakshi Hudda & Constantinos Sioutas (2009) Intra-Community Variability in Total Particle Number Concentrations in the San Pedro Harbor Area (Los Angeles, California), Aerosol Science and Technology, 43:6, 587-603, DOI: 10.1080/02786820902800900. [this is in fact reference 16 in the MS]. Also, references 52-55 in the manuscript, which are cited in line 30, could be used to help make this point. I suspect that other research groups have reported similar findings for other well-studied urban areas like Mexico City, Pittsburgh, and Melbourne and Sydney, Australia. A second important reason to add discussion of the previous literature is that reader needs to know the extent to which the results from the present study in San Francisco Bay area can be generalized geographically.
12. Environmental Significance Statement. First sentence is problematic. It has not been demonstrated that UFP is a “major cause of mortality and morbidity around the world” (or anywhere really). Same thing for TRAP; jury is still out. Authors should recraft sentence to better reflect state of knowledge of UFP and TRAP epidemiology.

Reviewer 2

This paper presents the plentiful spatiotemporal characteristic of ultrafine particles (UFP) through analyzing an amount of observation data. It further discusses the diversity between UFP and other typical traffic emission pollutants so as to verify that it is not appropriate to use NOx or NO2 as an indicator instead of UFP in epidemiology studies. This article has a substantial workload and certain innovation, which well provides a basic information of UFP characteristic for health and model studies. However, there are unclear and inadequate interpretations in the experimental results. Therefore, the following issues should be solved before the manuscript can be considered.

Major comments:
1. It may not be a very good research design to explore the role of a pollution source on the influence of pollutants based on the observation data of large area. There are other potential sources to emit the same pollutants, not just only the traffic source. It needs further to illustrate the observation environment information in this text.
2. Since the traffic flow data is obtained, why not use the traffic flow data to calculate the emissions to further verify the correlation of UFP and emissions?
3. The increase of UFP concentrations is mainly attributed to the formation of NFP in this study. Is it possible that the increase is from the emissions of other pollution sources?
3. In the writing of this paper, pay attention to the transformation and consistency of tenses in grammar.

Minor comments:
Introduction
1. Line 19 Please explain the main pollution sources of UFP before introducing the method of replacing UFP with TRAPs, and adjust it with the latter paragraph. In addition, is it more appropriate to use traffic related pollutants as alternative pollutants in the traffic environment other than the whole atmosphere?
2. Line 21 It states that the spatiotemporal signatures of UFP may differ meaningfully from those of other TRAPs as you explore here. Is there any literature to support this argument, or is the research result of this study put in the introduction section?
Materials and methods
3. Line 44 Weird order of figures in SI. I would expect to see them in order they show up in the text.
4. Line 49 Please provide the map tagging the four fixed sites in SI.
5. Line 50 Replace “reports” with “measures”.
6. Line 50 “two additionally report black carbon (BC)?” Please write another one pollutant.
7. Line 54 Use “were” instead of “are”, and use “was” instead of “is”.
Results and discussion
8. Line 110 All numbers should be presented with range or SD.
9. Line 121 What activities were decreased?
10. Line 124 What kind of pollutants were presented a strong peak?
11. Line 125 Figure S2 plots the change of traffic volume and can not reflect the atmospheric dilution status.
12. Line 130 No references support this viewpoint. Please add the relevant refences.
13. Line 134 TRAPs?
14. Line 134 The viewpoint “indicative of NPF from nucleation” is too arbitrary. There is no direct evidence to prove the formation of NFP in this experiment.
15. Line 137 Which of pollutant concentrations had the early morning and evening peaks?
16. Line 141 Figure S1 not Figure S2?
17. Line 146 Use “was” instead of “is”.
18. Line 158 What is the basis of this argument “Furthermore, the seasonal differences……”
19. Line 164 It is not appropriate to use the word “moderate” descripting the range (0.09-0.42).
20. Line 189 Is it appropriate to classify the samples using “low-NFP” and “high NFP”. There is no direct measurement to verify the formation of new particles. It needs to use these two phases carefully in Section 3.2.

This text has been copied from the PDF response to reviewers and does not include any figures, images or special characters.

Referee: 1
The study described in the manuscript is well-executed and quite interesting. The datasets
utilized are rich, long-term, and high quality. The results and conclusions are well-supported
by the data. The paper is generally very well written and will likely be of interest to many
readers of your journal and to a wider audience of urban air pollution researchers and
stakeholders. The key finding is that individual constituent pollutants in complex mixtures of
traffic-related air pollutants cannot always serve as proxies for one another – specifically,
NOx cannot always serve as a proxy for UFP. The clear demonstration of this point is both
the strength of the paper and the contribution it makes to the literature. I recommend it for
publication after a few relatively minor comments are addressed, as described below.

Response: We would like to thank Reviewer-1 for the positive words about the study and the manuscript
and for suggesting changes that we believe have made this manuscript much better. Thank
you for your time and effort. Responses to individual comments are provided below.

Main and minor issues mixed together:
1. Tables 1 and 2. Why is Pearson-R2 used as the statistical test variance/covariance?
Assuming that the pollutant distribution data is non-uniformly distributed, it would make
more sense to use a non-parametric statistical test such as the Spearman correlation. Either
change statistical analysis method to a non-parametric test or justify the use of Pearson based
on the distribution of the data.

Response: Use of the Pearson-R2 for assessing correlation among pollutants has been replaced with the
Spearman’s rho correlation (Tables 1–2, Tables S2–4, and the manuscript text).

Lines 163-170:
“We present in Table 1 the Spearman correlation (rs) matrix among the TRAPs for the nearhighway, urban, suburban, and the rural sites based on hourly-average concentrations. At all
sites, the correlation between PN and any other TRAP was 0.41–0.76. The inter-pollutant
correlation among non-PN pollutants were generally higher compared to PN. NOx and BC
were highly correlated at the near-highway site (rs = 0.91) and at the suburban site (rs =
0.91). NOx and CO were well correlated at the near-highway site (rs = 0.70) and the urban (rs
= 0.81) site. Furthermore, for all the sites, PN concentrations were better correlated with NOx
(rs, near-highway = 0.72, rs, urban = 0.66, rs, suburban = 0.49, rs, rural = 0.69) than either
NO (0.76, 0.59, 0.44, 0.56) or NO2 (0.57, 0.66, 0.52, 0.68)”
Lines 174-177:
“Lower pairwise correlation between PN and other TRAPs 175 was driven by differences in
summertime patterns — PN and NOx were least correlated during the summer daytime. For
the nonnear-highway sites, the summer daytime rs values were 0.01–0.53, suggesting that
particularly during periods of higher photochemical activity, the dominant influence on NOx
concentrations”

2. Add missing CO plots to Fig 1 – CO near-highway and CO-suburban. Or, if they cannot
be added, indicate in figure caption why they are absent so that reader is not left to wonder.

Response: While PN and NOx measurements are available at all four sites, CO measurements are only
available for three sites (near-highway, urban, and rural) and BC measurements are available
for only two sites (near-highway and suburban). In Fig. 1 we have presented PN, NOx, and a
third TRAP (either CO or BC) depending on availability of the site. The only missing plot
was CO-Near-Highway which was excluded for efficiently utilizing space in the figure. We
have included the diurnal plots including BC and CO for the near-highway site along with all
other diurnal plots in the SI (Figure S14).

3. Line 32. Change to “…periods, NPF can become….”

Response: Fixed.

4. Line 24-5. This sentence is a little vague. Important sources are left out including noncombustion emissions like brakeware and tireware. This sentence would be better if rewritten
as follows: “In urban areas the principal sources of UPF include vehicular traffic (tailpipe
emissions, brakeware, tireware), other combustion of fossil fuels, cooking and nucleation
events”

Response: We have incorporated this change and added a citation for brake wear and tire wear (Harrison
et al., 2012: https://pubs.acs.org/doi/10.1021/es300894r).
“In urban areas the principal sources of UFP include vehicular traffic (tailpipe emissions,
brake wear, and tire wear), other combustion of fossil fuels, cooking, and nucleation events.”

5. Line 114. Change to “… near-highway site:….urban site, and…”

Response: Fixed.

6. Line 130-1. Discussion of seasonal variation PBLH and its impact on pollutant
concentrations needs clarifying. PBL is likely higher during morning and evening rush hours
in summer compared to winter. Instead of pointing out that the morning and evening rush
hours occur at dawn and dusk in winter, authors should make the contrast with summer in
terms of the PBL for consistency.

Response: We have moved the discussion of meteorological factors that was included later in the results
section to appear before line 130 to provide the necessary context and we have expanded on
the influence of boundary layer height combined with rush hour emissions.
“Average diurnal profiles indicate the combined influence of the traffic activity and
ventilation patterns. In the winter, all sites showed a strong peak for all pollutants (PN, NOx,
BC, and CO) during morning and evening rush hours, with concentrations 2–7× greater than
the mid-day trough in concentrations (Figure 1). In the SI (Figure S1) we present the diurnal
and seasonal averages for the ventilation coefficient (and other meteorological parameters) in
the SF Bay Area. The lower wind speeds and mixing height during mornings and evenings of
winter months result in lower ventilation. Conversely, owing to higher wind speeds and
mixing height, warmer periods were generally more ventilated with the summer mid-days
having the highest ventilation coefficient. Furthermore, some of the highest solar radiation
was also observed during the summer daytime. The midday trough observed in all diurnal
pollution profiles except those of summertime PN reflects the strong effect of increased
atmospheric dilution during the middle of the day coupled with a reduction in traffic volumes
on many urban roads outside of rush hour.”

7. Line 53. TSI model 3783 measures particle number concentration for particles in 7-3000
nm size range. The instrument reports particle number concentration (PNC). The article
reports the measurements as UFP (<100 nm), which is misleading. Change “UFP” to “PNC”
here and throughout the MS and in figures and tables. Same thing for TSI model 3788
measurements.

Response: Thank you for identifying this opportunity to be more precise. We have now replaced “UFP
concentrations” with “PN concentrations” throughout the manuscript and SI (text, figures,
and tables) while reporting our results.

8. Line 136. The sentence starting with “The summertime peak.. was convoluted…”. Please
rewrite for clarity. “Convoluted” could be interpreted in more than one way and thus it is not
clear what your point is.

Response: Fixed.
“At the near-highway site, high midday concentrations resulted in high concentrations
throughout the day, without distinct peaks corresponding to morning and evening trafficrelated sources.”

9. Line 218. It is very interesting that PNC – NOx divergence is most pronounced in
residential streets. What could explain this? Specifically, what could explain the PNC blooms
in residential areas? Where are the vapors coming from that are nucleating there? This could
use a sentence or two and some references to substantiate any hypotheses that might be
advanced (to avoid being overly speculative).

Response: Thanks for this suggestion. On the contrary, we do not necessarily think that there is more
nucleation in the residential areas, but rather simply that nucleation contributes a relatively
larger share of PN on streets with lower primary emissions. NPF as a regional event is more
uniformly spread across neighborhoods or part of a city (including residential, arterial,
highway in this case). Our data strongly suggest it is the lower denominator (NOx) driving the
higher PN/NOx ratio for the residential locations, as logically follows given that traffic
emissions are principally concentrated on the major thoroughfares, with a smaller rate of
direct emissions on residential streets. So, the seasonal divergence in this ratio is more
dramatic in areas with lower primary contributions to PN and lower total concentrations of
NOx. The updated manuscript includes the following text (lines 215-218).
“The PN/NOx ratio was highest for residential streets since they have the lowest NOx
concentrations and the PN concentrations would be less spatially variable during NPF events
(a regional phenomenon). Overall, the diurnal profiles of the PN/NOx ratio from on-road
measurements corroborate the findings from the fixed sites (Figure 2), and emphasize how
the seasonal divergence in this ratio is most strongly observed in locales that are relatively
less influenced by direct traffic emissions.”

10. Line 237-8. The sentence with “…health consequences of freshly-nucleated vs. trafficemitted particles are still not well understood” needs some details. The sentence implies that
the differences between primary and secondary particle tox and/or epi are at least partially
understood. If this is the case, then authors should cite the relevant studies. If not, then
authors might be advised to simply delete this sentence and avoid the problem since health
effects are not central to their study.

Response: Sentence deleted.

11. Discussion of previous studies showing mid-day secondary PNC peaks is missing. This
needs to be corrected; reader needs to know that many other studies have reported this same
phenomenon. A quick search of studies from the LA basin revealed two studies: (1) Intercommunity variability in total particle number concentrations in the eastern Los Angeles air
basin N. Hudda, K. Cheung, K. F.Moore, and C. Sioutas, Atmos. Chem. Phys., 10, 11385–
11399, 2010 www.atmos-chem-phys.net/10/11385/2010/, and (2) Katharine Moore ,
Margaret Krudysz , Payam Pakbin , Neelakshi Hudda & Constantinos Sioutas (2009) IntraCommunity Variability in Total Particle Number Concentrations in the San Pedro Harbor
Area (Los Angeles, California), Aerosol Science and Technology, 43:6, 587-603, DOI:
10.1080/02786820902800900. [this is in fact reference 16 in the MS]. Also, references 52-55
in the manuscript, which are cited in line 30, could be used to help make this point. I suspect
that other research groups have reported similar findings for other well-studied urban areas
like Mexico City, Pittsburgh, and Melbourne and Sydney, Australia. A second important
reason to add discussion of the previous literature is that reader needs to know the extent to
which the results from the present study in San Francisco Bay area can be generalized
geographically.

Response: We have included the recommended literature and improved the discussion in the
introduction to reflect previous studies that show the midday PN peak.
Lines 27-35
“In recent years, studies from various cities and background sites across the world show
particle number (PN) concentrations (an approximation of UFP concentrations) peak during
periods with increased solar radiation.16,45–54 Short term studies that have investigated both
particle formation and growth have found NPF to be an important contributor to overall UFP
concentrations.55–58 Brines at al.21 studied multiple cities in the Mediterranean climatic
regions (Barcelona, Madrid, Rome and Los Angeles) and found that although traffic remains
the main source of UFP in urban areas, during high insolation (sunny) periods, NPF can
become the main source of UFP. Under these conditions UFP concentrations can become
decoupled from TRAP concentrations, which are driven primarily by emissions activity.
However, most observational comparisons between UFP and other TRAPs are generally
based on short-term mobile or distributed-sampler studies, 18,19,59–63 usually not capable of
comprehensively characterizing seasonal patterns.”

12. Environmental Significance Statement. First sentence is problematic. It has not been
demonstrated that UFP is a “major cause of mortality and morbidity around the world” (or
anywhere really). Same thing for TRAP; jury is still out. Authors should recraft sentence to
better reflect state of knowledge of UFP and TRAP epidemiology.

Response: “Although particle number (PN) is theorized to be more strongly linked with adverse health
effects than total particle mass, difficulty in producing an accurate characterization of spatial
variation of PN in urban areas remains an impediment to evaluating its health effects. Longterm fixed-site measurements and extensive mobile monitoring data show complementary
evidence that elevated summertime PN concentrations, arising from new particle formation,
follow spatial and temporal patterns that diverge from those of other traffic-related air
pollutants such as NOx and black carbon. For example, seasonal PN-NOx decoupling was
especially pronounced in residential areas that are less influenced by vehicle emissions.
These findings indicate the importance of considering complex atmospheric processes along
with key emission sources (i.e., traffic) in models of ultrafine particle exposure and strategies
for reducing ambient ultrafine particle levels.”

Referee: 2
This paper presents the plentiful spatiotemporal characteristic of ultrafine particles (UFP)
through analyzing an amount of observation data. It further discusses the diversity between
UFP and other typical traffic emission pollutants so as to verify that it is not appropriate to
use NOx or NO2 as an indicator instead of UFP in epidemiology studies. This article has a
substantial workload and certain innovation, which well provides a basic information of UFP
characteristic for health and model studies. However, there are unclear and inadequate
interpretations in the experimental results. Therefore, the following issues should be solved
before the manuscript can be considered.

Response: We would like to thank Reviewer-2 for their helpful comments and suggestion. We hope that
the edits made to the manuscript have improved our interpretations of the results among other
aspects of the manuscript. Thank you for your time and effort. Responses to individual
comments are provided below.

Major comments:
1. It may not be a very good research design to explore the role of a pollution source on the
influence of pollutants based on the observation data of large area. There are other potential
sources to emit the same pollutants, not just only the traffic source. It needs further to
illustrate the observation environment information in this text.

Response: Thank you for your comment. As you rightly point out, there are multiple likely primary
(direct) emitters of PN in our study area. The discussion on primary emitters of PN in the
manuscript has been improved in response to your specific comments (see response to Minor
Comment 1).
Lines 19-24
“In urban areas, the principal sources of UFP include vehicular traffic (tailpipe emissions,
brake wear, and tire wear), other combustion of fossil fuels, cooking, and nucleation events.
Because traffic is often assumed to be a dominant source of UFP, exposure to UFP is
sometimes approximated based on more commonly observed traffic-related air pollutants
(commonly NOx or NO2) as indicator values. However, the strength of correlation between
UFP and other traffic-related air pollutants (TRAP, including NO, NO2, CO, and BC) varies
among sites. In this study we examine conditions under which the spatiotemporal signatures
of UFP may differ meaningfully from those of other TRAP”.

2. Since the traffic flow data is obtained, why not use the traffic flow data to calculate the
emissions to further verify the correlation of UFP and emissions?

Response: The traffic data is only available for one site (near-highway) for one year and does not
include detailed information about the vehicle fleet (beyond total vehicles and heavy-duty
traffic volume estimates), nor does it reflect the vehicle fleet has possibly evolved over the
study period. Our goal with including a “snapshot” of the traffic summary was to illustrate
the decoupling of traffic (as well as NOx and BC) and PN concentrations. In the figure below
(Figure R1), we illustrate that traffic and all the pollutants follow similar diurnal patterns
during winter (holds for “low-NPF” period) as compared to the summer (“high NPF” period).
However, the diurnal profile of PN concentrations diverge during the weekend-summer, best
illustrated by the daytime peak in the summer-weekend PN plot below.
Figure R1: Diurnal profiles of PN, NOx, BC, total vehicles, and truck traffic at the near-highway site during summer and
winter. This figure is a combination of Figure 1 (manuscript) and Figure S3 (supplement).
Unfortunately, we only have the traffic data for the near-highway site – where nearby vehicle
emissions are presumably dominated by the very large traffic flows along a single road, i.e.,
the highway – and are therefore unable to show the above plots for the urban, suburban, or
the rural sites.

3. The increase of UFP concentrations is mainly attributed to the formation of NFP in this
study. Is it possible that the increase is from the emissions of other pollution sources?

Response: While there may be sources which are more strongly associated with emissions of UFP than
NOx (e.g., restaurants), we still believe that NPF is the key process in play that causes the
decoupling of PN concentrations from NOx that we observe. This is supported by the distinct
seasonal difference in decoupling of PN from other pollutants, the fact that we do not observe
distinct summertime spatial peaks or hot spots in PN concentration where there are none
during the winter, and the strong decoupling of NOx and PN in residential areas. We do not
have reason to believe that a source that predominately emits UFP would operate only during
summer midday hours, nor that those sources would be distributed relatively uniformly
throughout residential areas. Because the temporal patterns align with periods of high
intensity solar radiation favorable for NPF, we believe that is the most likely explanation.

4. In the writing of this paper, pay attention to the transformation and consistency of tenses in
grammar.

Response: We have reviewed and edited the manuscript keeping this comment in mind.

Minor comments:
Introduction
1. Line 19 Please explain the main pollution sources of UFP before introducing the method of
replacing UFP with TRAPs, and adjust it with the latter paragraph. In addition, is it more
appropriate to use traffic related pollutants as alternative pollutants in the traffic environment
other than the whole atmosphere?

Response: We have clarified some points and rearranged the discussion. (Starting line 19, updated
document)
“In urban areas, the principal sources of UFP include vehicular traffic (tailpipe emissions,
brake wear, and tire wear), other combustion of fossil fuels, cooking, and nucleation events.
Because traffic is often assumed to be a dominant source of UFP, exposure to UFP is
sometimes approximated based on more commonly observed traffic-related air pollutants
(commonly NOx or NO2) as indicator values. However, the strength of correlation between
UFP and other traffic-related air pollutants (TRAP, including NO, NO2, CO, and BC) varies
among sites. In this study we examine conditions under which the spatiotemporal signatures
of UFP may differ meaningfully from those of other TRAP”.

2. Line 21 It states that the spatiotemporal signatures of UFP may differ meaningfully from
those of other TRAPs as you explore here. Is there any literature to support this argument, or
is the research result of this study put in the introduction section?

Response: Thank you for pointing this out. As per your previous comment, we have rearranged/clarified
this discussion. In the updated manuscript references 30–35 support this argument.
Materials and methods

3. Line 44 Weird order of figures in SI. I would expect to see them in order they show up in
the text.

Response: Thank you for pointing this error. We have now fixed the numbering in the text after
including the new SI figure (see following comment).

4. Line 49 Please provide the map tagging the four fixed sites in SI.

Response: Included map of fixed sites (Figure S1 in updated version). Referenced in text appropriately.

5. Line 50 Replace “reports” with “measures”.

Response: Fixed

6. Line 50 “two additionally report black carbon (BC)?” Please write another one pollutant.

Response: Fixed
“UFP and NOx are measured at each of these four sites, CO at three sites (near-highway,
urban, and rural), and BC at two sites (near-highway and suburban).”

7. Line 54 Use “were” instead of “are”, and use “was” instead of “is”.

Response: Fixed

Results and discussion
8. Line 110 All numbers should be presented with range or SD.

Response: We have now included the ranges (5th–95th percentile values).
“For 2015 (year with almost full coverage for measured pollutants at all sites), from nearhighway to rural, the annual average (5th–95th percentile) UFP concentrations were 29900
cm−3 (7960–65500 cm−3), 11900 cm−3 (1850–31100 cm−3), 10100 cm−3 (1990–21100 cm−3),
and 3500 cm−3 (430–10500 cm−3) respectively. Annual average NOx concentrations followed
the same order — 34.7 ppb (7.1–87.7 ppb) for the near-highway, 18.8 ppb (2.3–61.1 ppb) for
the urban, 17.4 ppb (1.9–63.4 ppb) for the suburban, and 8.4 ppb (1.2–28.6 ppb) for the rural
site. Among these sites, BC was only monitored at the near-highway and the suburban sites
for which the annual average concentrations were 1.43 μg m−3 (0.28–3.65 μg m−3) and 0.78
μg m−3 (0.09–2.61 μg m−3) respectively. CO annual average concentrations were 0.47 ppm
(0.25–0.86 ppm) at the near-highway site, 0.44 ppm (0.23–0.92 ppm) at the urban site, and
0.38 ppm (0.20–0.66 ppm) at the rural site.”

9. Line 121 What activities were decreased?

Response: Clarification that the port is closed on the weekends in now included in the text.
“The lower weekend heavy duty truck traffic is consistent with the decreased activity at the
nearby port of Oakland during the weekends (the port is closed on the weekends).”

10. Line 124 What kind of pollutants were presented a strong peak?

Response: The strong peaks were present for all pollutants (PN, NOx, BC, and CO) as shown in Figure
1. This has been clarified in the text now.
“In the winter, all sites show a strong peak for all pollutants (PN, NOx, BC, and CO) during
morning and evening rush hours, with concentrations 2–7× greater than the mid-day trough in
concentrations (Figure 1).”

11. Line 125 Figure S2 plots the change of traffic volume and can not reflect the atmospheric
dilution status.

Response: This was a typo and has now been fixed to refer to the correct figure.

12. Line 130 No references support this viewpoint. Please add the relevant refences.

Response: This discussion has been changed and now put in context of the boundary layer height
(Figure S1). [Also suggested by Reviewer 1]
Beginning on line 123:
“Average diurnal profiles indicate the combined influence of the traffic activity and
ventilation patterns. In the winter, all sites showed a strong peak for all pollutants (PN, NOx,
BC, and CO) during morning and evening rush hours, with concentrations 2–7× greater than
the mid-day trough in concentrations (Figure 1). In the SI (Figure S1) we present the diurnal
and seasonal averages for the ventilation coefficient (and other meteorological parameters) in
the SF Bay Area. The lower wind speeds and mixing height during mornings and evenings of
winter months result in lower ventilation. Conversely, owing to higher wind speeds and
mixing height, warmer periods were generally more ventilated with the summer mid-days
having the highest ventilation coefficient. Furthermore, some of the highest solar radiation
was also observed during the summer daytime. The midday trough observed in all diurnal
pollution profiles except those of summertime PN reflects the strong effect of increased
atmospheric dilution during the middle of the day coupled with a reduction in traffic volumes
on many urban roads outside of rush hour.”

13. Line 134 TRAPs?

Response: We have used Traffic-related air pollutants (plural) to refer to multiple pollutants.

14. Line 134 The viewpoint “indicative of NPF from nucleation” is too arbitrary. There is no
direct evidence to prove the formation of NFP in this experiment.

Response: We have updated this sentence (now on line 139 of the updated manuscript).
“This increase in PN without concomitant increases in other products of primary combustion,
occurring during high-insolation midday hours (10am to noon) and independent of
weekend/weekday traffic differences, strongly suggests NPF.”

15. Line 137 Which of pollutant concentrations had the early morning and evening peaks?

Response: All pollutants (PN, NOx, BC, and CO) had the early morning and evening peaks (Figure 1).
This has been clarified in the text now.
“For winters, all sites except the near-highway site had early morning (∼6am) and evening
peaks (∼6pm) for all pollutants (PN, NOx, BC, and CO).”

16. Line 141 Figure S1 not Figure S2?

Response: Fixed.

17. Line 146 Use “was” instead of “is”.

Response: Fixed.

18. Line 158 What is the basis of this argument “Furthermore, the seasonal differences……”

Response: Thank you for pointing this out. We have clarified it in the text below (line 156, updated
manuscript) and as response to a similar comment from Reviewer 1 (Comment 9, Reviewer
1) in lines 221.
“Furthermore, summer PN/NOx were markedly higher on weekends which is consistent with
the assumption that reduced weekend traffic results in lower concentrations of both NOx and
associated directly-emitted PN, further accentuating the relative contribution of PN
associated with NPF.”

19. Line 164 It is not appropriate to use the word “moderate” descripting the range (0.09-
0.42).

Response: This discussion has been updated to reflect comments from Reviewer 1 (to use Spearman
correlation instead of Pearson correlation). We have also incorporated your comment to not
use “moderate”.

20. Line 189 Is it appropriate to classify the samples using “low-NFP” and “high NFP”.
There is no direct measurement to verify the formation of new particles. It needs to use these
two phases carefully in Section 3.2.

Response: We acknowledge that we do not have size distribution measurements, and that the
descriptions of “low-NPF” season and “high-NPF” season correspond to our hypothesized
explanation of the decoupling rather than to direct measurements. The “low-NPF” and “highNPF” classifications are based on Figure 3 (replicated for other sites in the supplement) and
helps us incorporate more data for our analysis (since “low-NPF” has 3 more months than
winter) which is useful for the spatial analysis. It should be noted that we use “low-NPF” and
“high-NPF” for blocks of months and not for specific days as explained in the manuscript:
“To further illustrate the dynamics of PN against other TRAPs at a higher temporal
resolution, we developed a set of heatmaps representing the full timeseries of PN, NOx, and
BC measurements with each day of the year (x-axis) divided into hourly concentrations(yaxis). Figure 3 presents heatmaps for the suburban site, with the heatmaps for all sites
presented in the SI (Figures S5–S8). This visualization clearly illustrates how the diurnal
profile of PN concentrations tracks the diurnal cycle of other traffic related air pollutants
during winter months, and decouples from the TRAPs in other seasons. While the daytime
PN concentration peaks are most apparent in the peak summer months (June–August), some
daytime PN peaks can also be observed in April, May, and September. Based on this yearlong heatmap, the months between October and March can be classified as the “low-NPF”
season as compared to the summer which is the “high-NPF” season. To maximize the amount
of mobile monitoring data that we can include for analysis (and thus improve our analytical
precision and spatial coverage), we therefore use these low-NPF and high-NPF measurements
in our core analysis of mobile monitoring data. Sensitivity analyses presented in the SI
demonstrate strong agreement in the spatial and temporal patterns of data between the lowNPF and winter periods, and between the high-NPF and summer periods (Figures S9–S12).”

29-Sep-2021

Dear Dr Gani:

Manuscript ID: EA-ART-07-2021-000058.R1
TITLE: Spatiotemporal profiles of ultrafine particles differ from other traffic-related air pollutants: Lessons from long-term measurements at fixed sites and mobile monitoring

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