the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Evaluation of aerosol- and gas-phase tracers for identification of transported biomass burning emissions in an industrially influenced location in Texas, USA
Sujan Shrestha
Shan Zhou
Manisha Mehra
Meghan C. Guagenti
Subin Yoon
Sergio L. Alvarez
Fangzhou Guo
Chun-Ying Chao
James H. Flynn III
Yuxuan Wang
Robert J. Griffin
Sascha Usenko
Rebecca J. Sheesley
Abstract. As criteria pollutants from anthropogenic emissions have declined in the US in the last two decades, biomass burning (BB) emissions are becoming more important for urban air quality. Tracking the transported BB emissions and their impacts is challenging, especially in areas that are also burdened by anthropogenic sources like the Texas Gulf coast. During the Corpus Christi and San Antonio (CCSA) field campaign in Spring 2021, two long-range transport BB events (BB1 and BB2) were identified. The observed patterns of absorption Ångström Exponent (AAE), high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) BB tracer (f60), equivalent black carbon (eBC), acetonitrile and carbon monoxide (CO) during BB1 and BB2 indicated differences in the mixing of transported BB plumes with local anthropogenic sources. The combined information from HYSPLIT backward trajectory (BTs) and satellite observations revealed that BB1 had mixed influence of transported smoke plumes from fires in Central Mexico, the Yucatan peninsula, and the Central US, whereas BB2 was influenced majorly by fires in the Central US. The estimated transport time of smoke from the Mexican fires and the Central US fires to our study site were not too different (48–54 hours and 24–36 hours, respectively) and both events appeared to have undergone similar levels of atmospheric processing, as evident in the elemental ratios of bulk organic aerosol (OA). We observed a progression of f44 vs. f60 as a function of time elapsed during BB2. Positive matrix factorization (PMF) analysis of OA showed that BB1 had a mixture of organics from aged BB emission with an anthropogenic marine signal while the oxidized organic compounds from aged BB emissions dominated the aerosols during BB2. While aerosol measurements exhibited good agreement with respect to the BB designation, the CO and acetonitrile trends revealed more complicated source contributions. Our analysis from mobile and stationary measurements highlights that both CO and acetonitrile are likely impacted by local sources even during the BB events and specifically that acetonitrile cannot be used as a unique BB tracer for dilute BB plumes in an industrially influenced location. Finally, we provide evidence of the potential regional impacts of these transported BB events on urban O3 levels using measurements from the surface air quality monitoring network in Texas.
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Sujan Shrestha et al.
Status: closed
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RC1: 'Comment on egusphere-2023-367', Anonymous Referee #1, 22 May 2023
This study evaluated aerosol and gas-phase tracers of transported biomass burning emissions in an industrially influenced location. This work has several unique elements, such as implementing an extended network of low-cost aerosol optical measurements to identify the influence of BB plumes, especially in cities designated as non-attainment or marginal nonattainment of criteria air pollutants. There are a few issues to be addressed before it can be accepted.
Major comments:
1. In your abstract, now that you highlight that both CO and acetonitrile cannot be used as a unique BB tracer for diluting BB plumes in industrially influenced locations, you ought to point out what other superior tracers are. Additionally, it is imperative to emphasize the significance and contribution of this research in this area, by explicitly stating the importance of identifying more precise and effective BB tracers for industrialized locations. This will allow readers to fully appreciate the value and relevance of the study, and make it clearer why this research is a notable and valuable addition to this field.
2. Your manuscript does not address the impacts of transported BB on urban O3. Various factors such as boundary layer dynamics, transport, mixing, precursors, and local sources can complicate the observed relationship between fire influence and O3 (as highlighted in references 10.1021/acs.est.2c06157 and 10.1029/2019JD031777), particularly with single-point measurements. Therefore, it would be beneficial to utilize the NOx and PTR data to provide more detailed insights into the impact of BB on O3. This will greatly help to promote the impact of this manuscript.
3. I appreciate your support for the motivation behind using an extended network of low-cost aerosol optical measurements to identify the influence of BB plumes in cities designated as non-attainment or marginal non-attainment of criteria air pollutants. Nonetheless, the measurement method employed may be low in efficiency and prone to high errors. Although the authors used a combination of multiple measurement instruments, such as TAP for absorption and integrating nephelometer for scattering, they also needed to estimate the mass concentration of BC. Considering this, it is worth exploring alternative measurement instruments and methods, such as AE33 and MA200, to improve the accuracy and efficiency of the measurement process. These technologies offer advanced performance characteristics and can provide more accurate results compared to the instruments used in the present study.
4. Line 375-380, Please add the time series comparison between NO+, NO2+, and AAE, or scatter plot figures, and explore the potential indication of BrC in detail.
5. Line 410-415, Why BB1 data can not be colored as a function of time of the day?
6. Section 2.2.3, Line 385-395,
In your PMF results, how did you determine and identify these factors, including less-oxidized oxygenated OA (LO-OOA), less oxidized OOA, ammonium sulfate (AS-OOA), and acidic sulfate (acidic-OOA)? These factors are not well explained or discussed in the manuscript. It will be useful to add some diagnoses for the PMF results. More discussions on the choice of PMF factors should be given.
7. Figure 6, the mobile measurement shows a significant difference between the estimated acetonitrile on drive day 1 and day 2, did the authors use the average value for the calculation of estimated acetonitrile and what was the error in the calculation?
8. PTR-MS data: It seems like the PTR-MS data are not being well leveraged to explain the temporal trends of plumes. Other VOCs like furans and phenol have been used as the BB tracer, and some carboxylic acid compounds were the main gaseous products. Do the authors consider that these species are more advantageous than acetonitrile as tracers of BB in further studies? These need to be discussed.
9. Previous field and laboratory studies have found rapid modification of aerosol and gas properties of biomass burning emissions within a few hours, such as the regional and nearfield influences of wildfire emissions (10.1021/acs.est.6b01617), the strong SOA formation and evaporation of primary semi-volatile species (10.1029/2021JD034534), change of optical properties (10.1021/acs.est.0c07569), aging effects on biomass burning aerosol mass and composition (10.1021/acs.est.9b02588). These evolutions of BB properties may influence the tracers for tracking BB sources, which may be referenced to aid some of your discussions.
Technical comments:
1. Line 233, delete the first (AAE and f60).
2. Line 46, analyzing
3. Line 55, reactions
4, Line 119, During the campaign,
5, Line 124, using Eq. (1)
6, Line 140, will result
7, Line 310, The influence of BB
8, Line 346, a significant increase
9, Line 413, an increase in f44 and a decrease in f60
10, Line513, can be an important factor
-
RC2: 'Comment on egusphere-2023-367', Anonymous Referee #2, 02 Jun 2023
General comment
The paper is focused on the characterization of biomass burning events impacting SW Texas, and their association with local air quality, while trying to disentangle the impact of urban and regional anthropogenic sources. The subject is timely, and it is treated in an interesting multi-angle approach combining high-end instrumentation (AMS, PTR MS) with mobile measurements and low-cost photometers.
The inadequacy of acetonitrile as a BB tracer in urban environments is an important result, well-justified by this study. However, a similar result for CO should have been expected and probably its description as a salient finding could be toned down. In the absence of clear markers for aged BB, the combination of AMS-driven PMF analysis backed up by satellite imagery and trajectory analysis appears as a key option for the characterization of processed aerosol from wildfires. Although this might not be feasible everywhere, it is a main message of the manuscript and should be stressed further.
This study also verifies that measurements and analysis of optical properties (although not without limitations) provide also possibilities for BB aerosol identification (also if Brown Carbon aerosol can be apportioned), but advanced multi-wavelength photometers are necessary to this end in order to reduce uncertainties. The used absorption photometers provide valuable solutions for flexible monitoring, but there are some inherent biases that should be acknowledged, as most probably there would be more confidence in the absorption results if a desktop multi-wavelength photometer had been available.
Overall the paper is well-written, well-referenced and it can be considered for publication after sharpening its take-home messages based on the arguments above, and addressing the following technical comments.
Specific comments
Abstract: Some results related to the mass size distributions and different mixing states of BB1, BB2 should be included in the abstract.
Line 47: It is somewhat of a stretch to classify CO, BC and even BrC as BB markers. It would be better to rephrase.
Line 52: SSA on its own does not characterize wavelength dependence.
Line 61: Changes on episodic scale or affecting air quality indicators in the long run?
Line 63: Again, which is the temporal scale of this exacerbation?
Lines 59-64: Impacts from agricultural burning have also been extensively documented in the SE US.
Line 70: Not clear how BB transport will lead into ozone exceedances. Please explain, for the specific case. It should be also considered that BB plumes containing absorbing BC and organics could also modulate photolysis and have a reverse O3 effect than the one described.
Lines 83-84: Mention the frequency.
Lines 136-137: It would be better to keep the “identify events above the baseline” and omit the “indicate periods of BB influence”, since based on results from aerosol typing studies an AAE of 1.2 might be too low to indicate pure BB aerosol.
Line 140-142: Take into account that these estimates refer to top-of-atmosphere forcing.
Line 152: Mention also here the MAC value you calculated. You should also acknowledge limitations around loading and multi-scattering absorption effects that are not compensated in the TAP/CLAP.
Line 158-165: Are these results from PMF analysis conducted in the present paper? More details are needed.
Section 2.1: The monitoring periods should be defined here.
Line 253-254: The AAE values for the events are somewhat low, for what is usually expected for BB aerosols. Do you expect that uncertainties in absorption measurements by the low-cost devices in the near-UV range play a part in this?
Line 284: Would this comment imply that UV-absorbing chromophore would be more susceptible to photo-bleaching? It tends to be the other way round (non-polar chromophores absorbing in the visible range tend to be more sensitive to degradation). Discuss.
Section 3.3: It is not clear how shipping emissions translate into the PMF factors identified here. Based on recent literature, there is the possibility to both influence HOA from near-coast activity, and OOA factors as processed aerosol from open-sea navigation. Some implications should be included here, since due to the location of the measurements, such activity can drive non-BB OA.
Line 348: It is difficult to follow which is the study period you are referring to. Is it 3-15 April, or just the event days.
Line 350-352: Or it could be interpreted as the BB events not being severe enough to have an impact at ground level.
Line 362: What do you mean by lower range? Your reported fractions place somewhere in the middle of the values from the other listed studies.
Line 364: Write correctly the chemical formula for the sulfate ion.
Line 395: Rephrase, it cannot be supported that MO-OOA factors in AMS studies are generally indicators of aged BB.
Figure 7: Event periods could be shaded similar to the other line figures.
For editing
Line 26: “as a function of time elapsed during BB2”. Not clear.
Line 65: Verb missing
Line 90: “anthropogenic influenced area”. Simplify.
Lines 171-173: Rewrite sentence, difficult to read.
Line 217: “Results”.
Citation: https://doi.org/10.5194/egusphere-2023-367-RC2 - AC1: 'Comment on egusphere-2023-367', Sujan Shrestha, 11 Jul 2023
Status: closed
-
RC1: 'Comment on egusphere-2023-367', Anonymous Referee #1, 22 May 2023
This study evaluated aerosol and gas-phase tracers of transported biomass burning emissions in an industrially influenced location. This work has several unique elements, such as implementing an extended network of low-cost aerosol optical measurements to identify the influence of BB plumes, especially in cities designated as non-attainment or marginal nonattainment of criteria air pollutants. There are a few issues to be addressed before it can be accepted.
Major comments:
1. In your abstract, now that you highlight that both CO and acetonitrile cannot be used as a unique BB tracer for diluting BB plumes in industrially influenced locations, you ought to point out what other superior tracers are. Additionally, it is imperative to emphasize the significance and contribution of this research in this area, by explicitly stating the importance of identifying more precise and effective BB tracers for industrialized locations. This will allow readers to fully appreciate the value and relevance of the study, and make it clearer why this research is a notable and valuable addition to this field.
2. Your manuscript does not address the impacts of transported BB on urban O3. Various factors such as boundary layer dynamics, transport, mixing, precursors, and local sources can complicate the observed relationship between fire influence and O3 (as highlighted in references 10.1021/acs.est.2c06157 and 10.1029/2019JD031777), particularly with single-point measurements. Therefore, it would be beneficial to utilize the NOx and PTR data to provide more detailed insights into the impact of BB on O3. This will greatly help to promote the impact of this manuscript.
3. I appreciate your support for the motivation behind using an extended network of low-cost aerosol optical measurements to identify the influence of BB plumes in cities designated as non-attainment or marginal non-attainment of criteria air pollutants. Nonetheless, the measurement method employed may be low in efficiency and prone to high errors. Although the authors used a combination of multiple measurement instruments, such as TAP for absorption and integrating nephelometer for scattering, they also needed to estimate the mass concentration of BC. Considering this, it is worth exploring alternative measurement instruments and methods, such as AE33 and MA200, to improve the accuracy and efficiency of the measurement process. These technologies offer advanced performance characteristics and can provide more accurate results compared to the instruments used in the present study.
4. Line 375-380, Please add the time series comparison between NO+, NO2+, and AAE, or scatter plot figures, and explore the potential indication of BrC in detail.
5. Line 410-415, Why BB1 data can not be colored as a function of time of the day?
6. Section 2.2.3, Line 385-395,
In your PMF results, how did you determine and identify these factors, including less-oxidized oxygenated OA (LO-OOA), less oxidized OOA, ammonium sulfate (AS-OOA), and acidic sulfate (acidic-OOA)? These factors are not well explained or discussed in the manuscript. It will be useful to add some diagnoses for the PMF results. More discussions on the choice of PMF factors should be given.
7. Figure 6, the mobile measurement shows a significant difference between the estimated acetonitrile on drive day 1 and day 2, did the authors use the average value for the calculation of estimated acetonitrile and what was the error in the calculation?
8. PTR-MS data: It seems like the PTR-MS data are not being well leveraged to explain the temporal trends of plumes. Other VOCs like furans and phenol have been used as the BB tracer, and some carboxylic acid compounds were the main gaseous products. Do the authors consider that these species are more advantageous than acetonitrile as tracers of BB in further studies? These need to be discussed.
9. Previous field and laboratory studies have found rapid modification of aerosol and gas properties of biomass burning emissions within a few hours, such as the regional and nearfield influences of wildfire emissions (10.1021/acs.est.6b01617), the strong SOA formation and evaporation of primary semi-volatile species (10.1029/2021JD034534), change of optical properties (10.1021/acs.est.0c07569), aging effects on biomass burning aerosol mass and composition (10.1021/acs.est.9b02588). These evolutions of BB properties may influence the tracers for tracking BB sources, which may be referenced to aid some of your discussions.
Technical comments:
1. Line 233, delete the first (AAE and f60).
2. Line 46, analyzing
3. Line 55, reactions
4, Line 119, During the campaign,
5, Line 124, using Eq. (1)
6, Line 140, will result
7, Line 310, The influence of BB
8, Line 346, a significant increase
9, Line 413, an increase in f44 and a decrease in f60
10, Line513, can be an important factor
-
RC2: 'Comment on egusphere-2023-367', Anonymous Referee #2, 02 Jun 2023
General comment
The paper is focused on the characterization of biomass burning events impacting SW Texas, and their association with local air quality, while trying to disentangle the impact of urban and regional anthropogenic sources. The subject is timely, and it is treated in an interesting multi-angle approach combining high-end instrumentation (AMS, PTR MS) with mobile measurements and low-cost photometers.
The inadequacy of acetonitrile as a BB tracer in urban environments is an important result, well-justified by this study. However, a similar result for CO should have been expected and probably its description as a salient finding could be toned down. In the absence of clear markers for aged BB, the combination of AMS-driven PMF analysis backed up by satellite imagery and trajectory analysis appears as a key option for the characterization of processed aerosol from wildfires. Although this might not be feasible everywhere, it is a main message of the manuscript and should be stressed further.
This study also verifies that measurements and analysis of optical properties (although not without limitations) provide also possibilities for BB aerosol identification (also if Brown Carbon aerosol can be apportioned), but advanced multi-wavelength photometers are necessary to this end in order to reduce uncertainties. The used absorption photometers provide valuable solutions for flexible monitoring, but there are some inherent biases that should be acknowledged, as most probably there would be more confidence in the absorption results if a desktop multi-wavelength photometer had been available.
Overall the paper is well-written, well-referenced and it can be considered for publication after sharpening its take-home messages based on the arguments above, and addressing the following technical comments.
Specific comments
Abstract: Some results related to the mass size distributions and different mixing states of BB1, BB2 should be included in the abstract.
Line 47: It is somewhat of a stretch to classify CO, BC and even BrC as BB markers. It would be better to rephrase.
Line 52: SSA on its own does not characterize wavelength dependence.
Line 61: Changes on episodic scale or affecting air quality indicators in the long run?
Line 63: Again, which is the temporal scale of this exacerbation?
Lines 59-64: Impacts from agricultural burning have also been extensively documented in the SE US.
Line 70: Not clear how BB transport will lead into ozone exceedances. Please explain, for the specific case. It should be also considered that BB plumes containing absorbing BC and organics could also modulate photolysis and have a reverse O3 effect than the one described.
Lines 83-84: Mention the frequency.
Lines 136-137: It would be better to keep the “identify events above the baseline” and omit the “indicate periods of BB influence”, since based on results from aerosol typing studies an AAE of 1.2 might be too low to indicate pure BB aerosol.
Line 140-142: Take into account that these estimates refer to top-of-atmosphere forcing.
Line 152: Mention also here the MAC value you calculated. You should also acknowledge limitations around loading and multi-scattering absorption effects that are not compensated in the TAP/CLAP.
Line 158-165: Are these results from PMF analysis conducted in the present paper? More details are needed.
Section 2.1: The monitoring periods should be defined here.
Line 253-254: The AAE values for the events are somewhat low, for what is usually expected for BB aerosols. Do you expect that uncertainties in absorption measurements by the low-cost devices in the near-UV range play a part in this?
Line 284: Would this comment imply that UV-absorbing chromophore would be more susceptible to photo-bleaching? It tends to be the other way round (non-polar chromophores absorbing in the visible range tend to be more sensitive to degradation). Discuss.
Section 3.3: It is not clear how shipping emissions translate into the PMF factors identified here. Based on recent literature, there is the possibility to both influence HOA from near-coast activity, and OOA factors as processed aerosol from open-sea navigation. Some implications should be included here, since due to the location of the measurements, such activity can drive non-BB OA.
Line 348: It is difficult to follow which is the study period you are referring to. Is it 3-15 April, or just the event days.
Line 350-352: Or it could be interpreted as the BB events not being severe enough to have an impact at ground level.
Line 362: What do you mean by lower range? Your reported fractions place somewhere in the middle of the values from the other listed studies.
Line 364: Write correctly the chemical formula for the sulfate ion.
Line 395: Rephrase, it cannot be supported that MO-OOA factors in AMS studies are generally indicators of aged BB.
Figure 7: Event periods could be shaded similar to the other line figures.
For editing
Line 26: “as a function of time elapsed during BB2”. Not clear.
Line 65: Verb missing
Line 90: “anthropogenic influenced area”. Simplify.
Lines 171-173: Rewrite sentence, difficult to read.
Line 217: “Results”.
Citation: https://doi.org/10.5194/egusphere-2023-367-RC2 - AC1: 'Comment on egusphere-2023-367', Sujan Shrestha, 11 Jul 2023
Sujan Shrestha et al.
Sujan Shrestha et al.
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