Point-by-point response to review comments on manuscript acp-2019-654 “Amplification of black carbon light absorption induced by atmospheric aging: temporal variation at seasonal and diel scales in urban Guangzhou”

constructive to improve the manuscript. Our point-by-point responses to the review comments are listed below as shown in blue. Changes to the manuscript are marked in teal blue in the revised manuscript. The marked manuscript is submitted together with this response document.


As summarized in
, the TD approach has high time resolution but limited sampling duration, while the AFD approach potentially has long sampling duration coverage but low time resolution. As a result, Eabs studies with both high time resolution and long sampling duration remained limited, leading to a lack of knowledge on Eabs variability on both seasonal and diel scales. To fill this knowledge gap, the aims of this study include: 1) to explore the temporal dynamics of Eabs on both seasonal and diel scales using the recently developed MRS approach; 2) to investigate the influencing factors on Eabs temporal variability, including photochemical aging, biomass burning (BB) and BC mixing state. In this study, filed measurements with one-hour time resolution were conducted in urban Guangzhou, a typical megacity in southern China in both wet (July 31-September 10, 2017) and dry (November 15, 2017-January 15, 2018 seasons.
We added a new section to discuss the comparison between Eabs by this study and previous studies.

Comparison of Eabs with previous studies
Filed measurements of Eabs values around the world are summarized in Table 2. Studies using the TD approach can achieve sub-hour time resolution, but studies using the TD approach had limited temporal coverage (normally less than a month). The AFD approach can potentially provide long-term Eabs results as long as filter samples are available. However, the measurement duration of existing AFD studies was less than one month as shown in Table 2. The limited temporal coverage of existing AFD studies was likely due to the intense labor involved in filter treatment. In addition, the time resolution of existing AFD studies (8-24 hour) was not sufficient to fully resolve Eabs diurnal pattern. As a result, diurnal variations of Eabs values at different seasons were not covered in previous studies. In comparison, the MRS approach is a good alternative to explore the Eabs variations at both seasonal and diurnal scales. As shown in Table 2, low Eabs values were found in California (1.06@532 nm) (Cappa et al., 2012) and Japan (1.06@532 nm) (Ueda et al., 2016). Liu et al. (2017) observed a moderate Eabs in UK (1.0-1.3@532 nm) and suggested that the small Eabs observed by Cappa et al. (2012) was a result of mixing state diversity. A recent study in California  found moderate Eabs at Fresno (1.22@532 nm) but low Eabs at Fontana (1.07@532 nm), which was partially associated with unequal distribution of coating between different BC-containing particle types . In general, higher Eabs values had been observed in more polluted urban areas, such as France (Paris, 1.53@880 nm) (Zhang et al., 2018a) and India (Kanpur, 1.8@781 nm) (Thamban et al., 2017). High Eabs values had been reported in various locations in China. The Eabs value in the wet season in our study (1.51) is higher than that in Nanjing (1.42) (Ma et al., 2019) but lower than those in central China (Shouxian, 2.3) (Xu et al., 2018), eastern China (Jinan, 1.9) (Bai et al., 2018) and northern China (Yuncheng, 2.25) (Cui et al., 2016b). The Eabs value in the dry season in our study (1.29) is lower than those in other locations in China, such as Beijing (1.66-4.0) (Xu et al., 2016;Zhang et al., 2018b), Nanjing (1.6) (Cui et al., 2016a), Xi'an (1.8) (Wang et al., 2014) and Jinan (2.07) (Chen et al., 2017). Since the collocated comparison of the three Eabs methods do not exist, a direct comparison between the three methods remain difficult. Nevertheless, a few studies, which conducted at the same city but during different periods, yielded comparable Eabs values. For example, Eabs in Nanjing by MAE method (1.6) (Cui et al., 2016a) was higher than that by the TD method (1.42) (Ma et al., 2019). This difference in Eabs might not only due to the different Eabs determination methods, but could also be a result of seasonal variations of Eabs.

R1-Q4.
The authors need to clearly state what is new in this paper and highlight which are the major new findings. I feel that the current writing style makes this paper look more like a data report of some measurement in a different location.
Author's Response: Thanks for the suggestion. We rewritten some of the contents to show the new findings clearly.
An example in abstract is shown below.
Eabs520 correlated well with nitrate and show a clear dependence on temperature. This new finding implies that gas-particle partitioning of semi-volatile compounds may potentially play an important role in steering the diurnal fluctuation of Eabs520.

R1-Q5.
When analyzing diurnal patterns of BC particles, I would always recommend to separate weekdays and weekends.
Author's Response: Thanks for the suggestion. Now we included Figure S10 to show the weekday/weekend effect on diurnal patterns. Corresponding discussions were added and also shown below.
To explore the effect of traffic volume, the weekday/weekend effect was investigated in Figure S10. The evening EC peak reduced substantially during weekend, implying that traffic volume has a strong influence on shaping the diurnal pattern of EC.
The difference of diurnal OC/EC pattern between weekday and weekend is negligible ( Figure S10), suggesting that the portion of different vehicle type (e.g. diesel vs. gasoline) is relatively constant between weekday and weekend.

R1-Q6.
This paper is quite long and not well written. I think the authors should make it more concise and improve its writing.
Author's Response: Thanks for the suggestion. To shorten the length of the manuscript, we had moved back trajectory and wind rose discussions to the supplement. We had also made necessary revisions to improve the conciseness of the manuscript.
Author's Response: Thanks for pointing out. The following content is added. EC in Eq. 3 and 4 represents elemental carbon mass concentration determined by the thermal optical analysis method (Wu et al., 2012), which can be considered as a surrogate of BC mass concentration.

R1-Q8. L104: "to low" should be "too low"
Author's Response: Thanks for pointing out the typo. Revision made. R1-Q9. L108: Consider revising the sentence "Third, the TD is not the ideal time machine for reversing the morphology transformation of BC." Author's Response: Thanks for the suggestion. The sentence had been rewritten as shown below.
Third, the TD approach cannot perfectly reverse the morphology transformation of BC from aged state back to freshly emitted state.

R1-Q10. L169: what are these "MAE values"?
Author's Response: Thanks for the suggestion. We add Table S1 to show theses literature values and the sentence had been rewritten as shown below. MAE values from study by Drinovec et al. (2015) was adopted for σ _ backcalculations from eBC at different wavelengths as shown in Table S1. Author's Response: Thanks for the suggestion. The sentence had been rewritten as shown below.
In MRS calculation, the correlation (R 2 ) between measured EC and estimated hypothetical σ _ is examined as a function of a series of hypothetical MAEp (MAEp_h). Since σ _ was resulted from secondary processing while EC was coming from primary emissions, a MAEp_h that leads to a minimum R 2 (EC, σ _ _ ) can best represents the independent nature between EC and σ _ . As a result, MAEp_h at minimum R 2 (EC, σ _ _ ) corresponds to the authentic MAEp.
R1-Q12. L620: The sentence "As a result, the increasing nitrate might potentially affect BC's radiative forcing in China." should be rewritten.
Author's Response: Thanks for the suggestion. The sentence had been rewritten as shown below.
If the nitrate fraction in the coating materials on BC increases, the diurnal pattern of Eabs for BC may be affected by the fluctuation of nitrate content in aerosol particles. As a result, the increasing concentration of nitrate might potentially affect radiative forcing by BC in China.

Anonymous Referee #2
General comments: The manuscript presents a comprehensive study on the black carbon light absorption enhancement (Eabs) in urban China. They used a newly developed method for Eabs determination, which utilizes measurements from a filter-based absorption instrument and a thermal-optical analysis OC/EC analyzer. The seasonal and diurnal patterns of Eabs were analyzed, and the potential influencing factors were discussed. This manuscript includes sufficient originality, and the topic seems to fit the scope of ACP.
In general, the overall quality of the manuscript is good yet the logic of some contents, especially the introduction, can be improved. I believe that the points below should be addressed. I therefore recommend a Minor Revision before publication in ACP.

Author's Response:
We appreciate the valuable time spent and efforts from the referee to improve the manuscript. Please see below for point-by-point response to reviewers' comments.

Major comments:
R2-Q1. The introduction is long but the motivation of this study seems missing. The authors should state clearly what's the scientific question that this study is trying to answer.
Author's Response: Thanks for the suggestion. We have made substantial revisions in the introduction section by emphasizing the motivation and scientific question.
The motivation of this study is emphasized as shown below.
As summarized in Table 1, the TD approach has high time resolution but limited sampling duration, while the AFD approach potentially has long sampling duration coverage but low time resolution. As a result, Eabs studies with both high time resolution and long sampling duration remained limited, leading to a lack of knowledge on Eabs variability on both seasonal and diel scales. To fill this knowledge gap, the aims of this study include: 1) to explore the temporal dynamics of Eabs on both seasonal and diel scales using the recently developed MRS approach; 2) to investigate the influencing factors on Eabs temporal variability, including photochemical aging, biomass burning (BB) and BC mixing state. In this study, filed measurements with one-hour time resolution were conducted in urban Guangzhou, a typical megacity in southern China in both wet (July 31-September 10) and dry (November 15, 2017-January 15, 2018) seasons.

R2-Q2. Since this study uses a new method for Eabs quantification, a comparison with
previous studies should be given in more details. Table 2 provides a useful summary but corresponding discussions seems too simple in the current manuscript.
Author's Response: Thanks for the suggestion. We added a separated section to discuss the comparisons of the current study and previous studies.

Comparison of Eabs with previous studies
Filed measurements of Eabs values around the world are summarized in Table 2. Studies using the TD approach can achieve sub-hour time resolution, but studies using the TD approach had limited temporal coverage (normally less than a month). The AFD approach can potentially provide long-term Eabs results as long as filter samples are available. However, the measurement duration of existing AFD studies was less than one month as shown in Table 2. The limited temporal coverage of existing AFD studies was likely due to the intense labor involved in filter treatment. In addition, the time resolution of existing AFD studies (8-24 hour) was not sufficient to fully resolve Eabs diurnal pattern. As a result, diurnal variations of Eabs values at different seasons were not covered in previous studies. In comparison, the MRS approach is a good alternative to explore the Eabs variations at both seasonal and diurnal scales. As shown in Table 2, low Eabs values were found in California (1.06@532 nm) (Cappa et al., 2012) and Japan (1.06@532 nm) (Ueda et al., 2016). Liu et al. (2017) observed a moderate Eabs in UK (1.0-1.3@532 nm) and suggested that the small Eabs observed by Cappa et al. (2012) was a result of mixing state diversity. A recent study in California  found moderate Eabs at Fresno (1.22@532 nm) but low Eabs at Fontana (1.07@532 nm), which was partially associated with unequal distribution of coating between different BC-containing particle types . In general, higher Eabs values had been observed in more polluted urban areas, such as France (Paris, 1.53@880 nm) (Zhang et al., 2018a) and India (Kanpur, 1.8@781 nm) (Thamban et al., 2017). High Eabs values had been reported in various locations in China. The Eabs value in the wet season in our study (1.51) is higher than that in Nanjing (1.42) (Ma et al., 2019) but lower than those in central China (Shouxian, 2.3) (Xu et al., 2018), eastern China (Jinan, 1.9) (Bai et al., 2018) and northern China (Yuncheng, 2.25) (Cui et al., 2016b). The Eabs value in the dry season in our study (1.29) is lower than those in other locations in China, such as Beijing (1.66-4.0) (Xu et al., 2016;Zhang et al., 2018b), Nanjing (1.6) (Cui et al., 2016a), Xi'an (1.8) (Wang et al., 2014) and Jinan (2.07) (Chen et al., 2017). Since the collocated comparison of the three Eabs methods do not exist, a direct comparison between the three methods remain difficult. Nevertheless, a few studies, which conducted at the same city but during different periods, yielded comparable Eabs values. For example, Eabs in Nanjing by MAE method (1.6) (Cui et al., 2016a) was higher than that by the TD method (1.42) (Ma et al., 2019). This difference in Eabs might not only due to the different Eabs determination methods, but could also be a result of seasonal variations of Eabs. Figure 6 shows a clear dependency of Eabs on SOC/OC. However, the correlation between organics and Eabs is not that good as expected. The authors should explain why a good dependency was observed in Figure 6 but meanwhile a low r 2 was found in Figure 7. Author's Response: Thanks for the comments. There are several possibilities for the lower R 2 of organics in Figure 7. First, Organics shown in Figure 7 contain both primary and secondary organics, two types or organics that might have different impacts on Eabs values. Second, the dependency of Eabs on SOC/OC might not necessarily be reflected in the form of correlation on a diurnal scale.
It should be noted that a good Eabs dependence on SOC/OC observed in Figure 6 does not necessarily lead to a good diurnal correlation between Eabs and SOC/OC (e.g. Figure  4a). In other words, the dependency of Eabs on SOC/OC might not necessarily be reflected in the form of correlation on a diurnal scale. Thus, the poor diurnal correlation between SOC/OC and Eabs520 observed in the wet season ( Figure 4a) cannot rule out the contribution of SOC on Eabs520. The following contents in section 3.7 were rephased.
There are two possibilities for the lower R 2 (Organics, Eabs) in Figure 7d comparing to R 2 (SOC/OC, Eabs) in Figure 4b. First, organics shown in Figure 7d contain both primary and secondary organics, while SOC/OC shown in Figure 4b represents the secondary portion only. Second, poor diurnal correlations do not necessarily rule out the contribution of organics and sulfate to Eabs by analogy with the SOC correlation with Eabs as discussed in Section 3.6.

R2-Q4.
As related to comment # 3) above, one of the most interesting findings of this study is that Eabs exhibits dependency on SOC/OC ratio and has good correlation with nitrate. For Eabs dependency on SOC/OC ratio, one might believe that it is the "concentration" of SOC in total OC that affects the absorption enhancement. For good correlation between nitrate and Eabs, is there any possible reason other than partitioning behavior that would potentially contribute to the good correlation? Author's Response: Thanks for the suggestion. Besides lensing effect of nonabsorbing coatings (e.g. nitrate) induced light absorption enhancement, formation of light-absorbing components could also lead to light absorption enhancement. For example, nitro-aromatic compounds (NACs) are secondary formed light-absorbing components that contribute light absorption enhancement. Since NAC formation is strongly associated with NOx, a good correlation between NACs and nitrate had been observed (Chow et al., 2016). However, NACs are part of Brown Carbon (BrC), thus have strong wavelength dependency. If a considerable fraction of NACs is present in PM2.5, an elevated AAE would be observed. The AAE observed in this study was <2, implying a weak signature of BrC. In our study, the abundance of NACs was not measured, therefore Eabs contribution from NACs remains unclear. But considering the fact that typical NAC concentration in PM2.5 was low (<10 ng m -3 ) (Chow et al., 2016) and their contribution to light absorption was small (<1%@370 nm) (Teich et al., 2017), the contribution of NACs to R 2 (Nitrate, Eabs) is expected to be very small.

R2-Q5. How measurement uncertainties would affect Eabs determination by MRS method?
Author's Response: The measurement uncertainties of MRS method for Eabs determination had been systematically examined in our previous study . Thus, only a brief introduction is given here. Three scenarios are considered using the data from our previous study . Scenario A represents systematic biases in Aehtalometer and OCEC measurements in the form of multipliers. The biased data are marked as ′ and EC', respectively, as shown below: The Eabs remain the same in scenario A, suggesting that MRS is not sensitive to the systematic biases that are in the form of multipliers.
In scenario B, EC by different TOA protocols are compared to investigate the effect of different EC determination approaches while remains unchanged. EC by IMPROVE TOR protocol is calculated from NIOSH TOT EC following an empirical formula for suburban sites derived from a 3-year OCEC dataset in PRD (Wu et al., 2016): In scenario B, EC uncertainty induced Eabs change is small (from 1.44 to 1.40) as shown in Figure R2, suggesting that the MRS is not sensitive to the systematic biases that contain both multipliers and offsets.
Scenario C examines the impact of sample-dependent bias as a function of Eabs. Unlike the proportional bias in Scenario A and B that is the same for all data points, the bias in Scenario C depends on the Eabs550 of individual samples, which are parametrized by Eqs. (R-4) and (R-5).
′ (R-4) ′ (R-5) As shown in Eqs. (R-4) and (R-5), the positive bias of and negative bias of EC are proportional to Eabs550. The magnitude of Eabs550-dependent bias is regulated by the factor k. Since ′ and EC' are biased in different directions, resulting a further amplification in MAE biases, which could be considered as the extreme case. As shown in Figure R3, for k=10% (corresponding to a bias of 10% when Eabs=2), the bias of MRS-derived Eabs is very small (1%). For k=20%, the MRS-derived Eabs changes from 1.44 to 1.66, leading to a bias of 15%. These results imply that if the measurement bias follows the same form as demonstrated in scenario C, the bias is not negligible but still acceptable. If the impact only affects or EC rather than impacting both, the bias is expected to be smaller than the estimation shown in Scenario C.
In summary, Eabs determination by MRS method is not sensitive to measurement uncertainties in light absorption or EC mass. Figure R1. Comparison of Eabs from original data and systematically biased data (Scenario A). It should be noted that the Eabs shown here is ratio of averages, which is different form the annual average Eabs calculated from average of ratios. Figure R2. Comparison of Eabs from data using NIOSH EC and data using IMPROVE EC (Scenario B). It should be noted that the Eabs shown here is ratio of averages, which is different form the annual average Eabs calculated from average of ratios. Figure R3. Comparison of Eabs from data using original data and Eabs depended biased data (Scenario C). It should be noted that the Eabs shown here is ratio of averages, which is different form the annual average Eabs calculated from average of ratios.