the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Light-absorbing black carbon and brown carbon components of smoke aerosol from DSCOVR EPIC measurements over North America and Central Africa
Abstract. Wildfires and agricultural burning generate seemingly increasing smoke aerosol emissions, impacting societal and natural ecosystems. To understand smoke’s effects on climate and public health, we analyzed the spatiotemporal distribution of smoke aerosols, focusing on two major light-absorbing components, black carbon (BC) and brown carbon (BrC) aerosols. Using NASA’s Earth Polychromatic Imaging Camera (EPIC) instrument aboard the NOAA’s Deep Space Climate Observatory (DSCOVR) spacecraft, we inferred BC and BrC volume fractions and particle mass concentrations based on spectral absorption provided by the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm with 1–2 hours temporal resolution and ~10 km spatial resolution over North America and Central Africa. Our analyses of regional smoke properties reveal distinct characteristics for aerosol optical depth (AOD) at 443 nm, spectral single scattering albedo (SSA), aerosol layer height (ALH), and BC and BrC amounts. Smoke cases in North America show extremely high AOD up to 6, with elevated ALH (6–7 km) and significant BrC components up to 250 mg/m2 along the transport paths, whereas the smoke aerosols in Central Africa exhibited stronger light absorption (i.e., lower SSA) and lower AOD, resulting in higher BC mass concentrations and similar BrC mass concentrations than the cases in North America. Seasonal burning source locations in Central Africa following the seasonal shift of Inter Tropical Convergence Zone and diurnal variations in smoke amounts were also captured. Comparison of retrieved AOD443, SSA443, SSA680, and ALH with collocated AERONET and CALIOP measurements shows agreement with rmse of 0.2, 0.03–0.04, 0.02–0.04, and 0.8–1.3 km, respectively. Analysis of spatiotemporally average reveals distinct geographical characteristics in smoke properties closely linked to burning types and meteorological conditions. Forest wildfires over western North America generated smoke with small BC volume fraction of 0.011 and high ALH with large variability (2.2 ± 1.2 km), whereas smoke from wildfires and agricultural burning over Mexico region shows more absorption and low ALH. Smoke from savanna fires over Central Africa has the most absorption with high BC volume fraction (0.015) and low ALH with small variation (1.8 ± 0.6 km) among the analyzed regions. Tropical forest smoke was less absorbing and had a high variance in ALH. We also quantify the estimation uncertainties related to the assumptions of BC and BrC refractive indices. The MAIAC EPIC smoke properties with BC and BrC volume and mass fractions and assessment of layer height provide observational constraints for radiative forcing modeling and air quality and health studies.
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Status: open (until 27 Jun 2024)
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RC1: 'Comment on egusphere-2024-1327', Anonymous Referee #1, 05 Jun 2024
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This paper uses observations from EPIC instrument onboard the DSCOVR spacecraft to study aerosol plumes generated by biomass burning over North America and central Africa with a focus on their light absorption properties.
The paper is very clear, it uses an original dataset and focus on a process that can be of interest for a wide community. It could then be published with little change. I feel nevertheless that some of the figure contain little information and could therefore be removed.
Figure 5 and 7 show Hovmöller diagrams of various aerosol parameters. The physical interpretation of these diagrams is unclear. It seems difficult to interpret these figure as an evolution of the aerosol plume during transport as one can observe an increase of the optical depth. Also, the direction of the transport is not fully clear. Since little interpretation is made from these figure, I recommend to remove them.
Similarly, I am not sure how figure 9, that shows mean parameters over a full year can be interpreted. The averages put together situations that are very different, with days that are affected by biomass burning plumes and other that are not. As a consequence, I wonder what sense what can make from the mean SSA values (or the aerosol height).
Finally, Figure 11 shows 4 plots of the monthly variations of the BC and BrC column concentrations. There is no significant monthly variations to show. As a consequence, I think that a single sentence “there is no significant temporal variation in the monthly mean values” would be sufficient to carry the message.
Other comment
There seem to be some error in Figure 8 or its legend.
- It is hard to see a “gray dashed line”
- There are some lines on the SSA plots the meaning of which are unclear
- For the SSA, the expected error is 0.03 or 0.05, not Aeronet SSA+0.03 (ie the error does not vary with the value, contrarily to that of the AOD)
Citation: https://doi.org/10.5194/egusphere-2024-1327-RC1 -
RC2: 'Comment on egusphere-2024-1327', Anonymous Referee #2, 08 Jun 2024
reply
What made you set maximum AOD value to 6?
AOD is better correlated to BrC in northern America (see in Fig 5), while it shows a better correlation in central Africa (see in fig 7). why is that? Or why do BC not correlate well with AOD in NA?
Do you think ALH correlates with convection due to the high surface temperature in Africa? How do fires in NA have more thermal energy for higher ALH?
How do the size distributions look between NA and Africa during fires
What impact do you think an externally mixed assumption would have made?
Did you also take the non-absorbing components into AOD,SSA,ALH etc calculation?
Citation: https://doi.org/10.5194/egusphere-2024-1327-RC2
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