Significant light absorption of brown carbon during the 2020 California wildfires.

In this study, the contribution of brown carbon (BrC) to the absorption aerosol optical depth (AAOD) during the August to October 2020 California wildfires in Fresno, Monterey, and the University of California Santa Barbara (UCSB) was investigated using Aerosol Robotic Network (AERONET) column measurements with Moderate Resolution Imaging Spectroradiometer (MODIS) fire pixel counts. There was an approximate three to five times increase in AAOD and fine-mode aerosols during intensive wildfires in August-October 2020 compared to the wildfires in the previous 18 years (2002-2019). Substantial daily variation in the contribution of BrC to AAOD was correlated with the fire pixel counts (correlation coefficients of 0.63, 0.40, and 0.57 at Fresno, Monterey, and UCSB, respectively). This variation was influenced by regional topography, atmospheric conditions, and distance from the fire. Between August and October 2020, the average contribution of BrC to AAOD at 440 nm due to wildfires was 35.3 ± 5.6, 35.1 ± 6.8, and 40.6 ± 9.5% at Fresno, Monterey, and UCSB, respectively. This was approximately twice as high as for those sites without a direct wildfire influence. The BrC contribution with direct wildfire influence over the period of January-December 2020 at Fresno, Monterey, and UCSB (32.8 ± 7.5, 31.6 ± 7.9, and 40.0 ± 3.5%, respectively) and from 2002 to 2019 (30.7 ± 8.3, 28.5 ± 4.8, and 35.7 ± 14.6%, respectively) was approximately 20% greater than other BrC sources including vehicles, fossil fuel combustion, and residential heating.

Impacts of local versus long-range transported aerosols on PM10 concentrations in Seoul, Korea: An estimate based on 11-year PM10 and lidar observations.

Extreme haze episodes have frequently occurred in Seoul since mid-2010s by the combined contributions of transboundary transported aerosols as well as locally emitted pollutants. In this study, we developed a novel method to estimate the contribution of long-range transport (LRT, aerosols are transported from any regions except local area near Seoul) and local pollution (LP, aerosols are originated from local area near Seoul) cases to the PM10 concentration in Seoul, Korea, using the PM10 concentration ratio between surface (PM10S) and mountaintop (PM10M) sites and the lidar-derived mixing layer height. The overall contributions of LRT and LP events to nighttime high-PM10 episodes (PM10 > 50 µg m-3) during the period of May 2008-April 2019 were estimated to be approximately 32% and 47%, respectively. The monthly contribution of LRT events to the PM10 concentration varied from approximately 18% (July) to 43% (January), whereas the contribution of LP events was estimated between 39% (March) and 69% (July); this pattern was associated with seasonal synoptic circulations. The similar PM10S values between the LRT (71 ± 22 µg m-3) and LP (73 ± 26 µg m-3) cases during the nighttime suggest that a reduction in local PM10 emissions is crucial to decrease the PM10 concentration during high-PM10 events. The high PM10S for daytime LRT cases can be explained by the combined effects of increased local emissions and LRT aerosols.

The CALIPSO Version 4 Automated Aerosol Classification and Lidar Ratio Selection Algorithm.

The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) version 4.10 (V4) level 2 aerosol data products, released in November 2016, include substantial improvements to the aerosol subtyping and lidar ratio selection algorithms. These improvements are described along with resulting changes in aerosol optical depth (AOD). The most fundamental change in V4 level 2 aerosol products is a new algorithm to identify aerosol subtypes in the stratosphere. Four aerosol subtypes are introduced for the stratospheric aerosols: polar stratospheric aerosol (PSA), volcanic ash, sulfate/other, and smoke. The tropospheric aerosol subtyping algorithm was also improved by adding the following enhancements: (1) all aerosol subtypes are now allowed over polar regions, whereas the version 3 (V3) algorithm allowed only clean continental and polluted continental aerosols; (2) a new "dusty marine" aerosol subtype is introduced, representing mixtures of dust and marine aerosols near the ocean surface; and (3) the "polluted continental" and "smoke" subtypes have been renamed "polluted continental/smoke" and "elevated smoke", respectively. V4 also revises the lidar ratios for clean marine, dust, clean continental, and elevated smoke subtypes. As a consequence of the V4 updates, the mean 532 nm AOD retrieved by CALIOP has increased by 0.044 (0.036) or 52 % (40 %) for nighttime (daytime). Lidar ratio revisions are the most influential factor for AOD changes from V3 to V4, especially for cloud-free skies. Preliminary validation studies show that the AOD discrepancies between CALIOP and AERONET/MODIS (ocean) are reduced in V4 compared to V3.

Quantifying the low bias of CALIPSO's column aerosol optical depth due to undetected aerosol layers.

The CALIOP data processing scheme only retrieves extinction profiles in those portions of the return signal where cloud or aerosol layers have been identified by the CALIOP layer detection scheme. In this study we use two years of CALIOP and MODIS data to quantify the aerosol optical depth of undetected weakly backscattering layers. Aerosol extinction and column-averaged lidar ratio is retrieved from CALIOP Level 1B (Version 4) profile using MODIS AOD as a constraint over oceans from March 2013 to February 2015. To quantify the undetected layer AOD (ULA), an unconstrained retrieval is applied globally using a lidar ratio of 28.75 sr estimated from constrained retrievals during the daytime over the ocean. We find a global mean ULA of 0.031 ± 0.052. There is no significant difference in ULA between land and ocean. However, the fraction of undetected aerosol layers rises considerably during daytime, when the large amount of solar background noise lowers the signal to noise ratio (SNR). For this reason, there is a difference in ULA between day (0.036 ± 0.066) and night (0.025 ± 0.021). ULA is larger in the northern hemisphere and relatively larger at high latitudes. Large ULA for the Polar Regions is strongly related to the cases where the CALIOP Level 2 Product reports zero AOD. This study provides an estimate of the complement of AOD that is not detected by lidar, and bounds the CALIOP AOD uncertainty to provide corrections for science studies that employ the CALIOP Level 2 AOD.