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: open (extended)
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RC1: 'Comment on egusphere-2023-367', Anonymous Referee #1, 22 May 2023
reply
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
Sujan Shrestha et al.
Sujan Shrestha et al.
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