The Two‐Column Aerosol Project: Phase I—Overview and impact of elevated aerosol layers on aerosol optical depth

Berg, Larry K.; Fast, Jerome D.; Barnard, James C.; Burton, S. P.; Cairns, Brian; Chand, D.; Comstock, J. M.; Dunagan, Stephen E.; Ferrare, R. A.; Flynn, Connor; Hair, Johnathan W.; Hostetler, C. A.; Hubbe, J. M.; Jefferson, Anne; Johnson, R. R.; Kassianov, Evgueni I.; Kluzek, C.; Kollias, Pavlos; Lamer, Katia; Lantz, Kathleen; Mei, Fan; Miller, Mark A.; Michalsky, Joseph; Ortega, Ivan; Pekour, Mikhail; Rogers, R. R.; Russell, Philip B.; Redemann, Jens; Sedlacek, Arthur J.; Segal-Rosenheimer, Michal; Schmid, Beat; Shilling, John E.; Shinozuka, Y.; Springston, Stephen; Tomlinson, Jason; Tyrrell, Megan C.; Wilson, Jacqueline; Volkamer, Rainer; Zelenyuk, Alla; Berkowitz, Carl M.

doi:10.1002/2015jd023848

Cited by 39 publications

(59 citation statements)

References 89 publications

(127 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Generally, there is a positive correlation between the MAC and the imaginary part of the RI (i) although the relationship is not linear (Bond and Bergstrom, 2006). This tells us that the i of BrC is likely to be positively correlated with the mass ratio of BC / OC in a certain environment, as shown by Saleh et al (2014).…”

Section: Relationship Between Brc-aaod and Bc-aaodmentioning

confidence: 94%

“…An AAE of 1 is reasonable when the diameter of the BC particle is smaller than 10 nm. However, BC associated with biomass burning and biofuel sources is typically larger than 70 nm (Bond and Bergstrom, 2006). For these larger BC particles, the AAE is highly sensitive to the size.…”

Section: Methods For Deriving Brc Absorption From Observationsmentioning

confidence: 99%

“…The observed size distribution of BC is typically lognormal, with geometric median diameter (GMD) ranging from 20 to 300 nm and standard deviation (δ) ranging from 1.4 to 2.2 (Akagi et al, 2012;Schwarz et al, 2008;Lack et al, 2012;Dubovik et al, 2002;Shamjad et al, 2012;Moffet and Prather, 2009;Knox et al, 2009;Lewis et al, 2009). We perform Mie calculations using these size distributions and a refractive index of 1.95-0.79i, as suggested by Bond and Bergstrom (2006). We also perform an additional set of calculations for coated BC.…”

Section: Methods For Deriving Brc Absorption From Observationsmentioning

confidence: 99%

“…To identify whether the correlation is different under different conditions, we further disaggregate the data by emission type and region. We use the anthropogenic emission inventory of Bond et al (2007) and biomass burning emission inventory from GFED4 (Giglio et al, 2013) to identify the dominant emission type for each data point. For a given month, if the biofuel or biomass burning emissions of both BC and OC contribute more than 60 % of the total emissions in a 2 • × 2 • area around a given AERONET site, we identify the corresponding data points as dominated by that source (70 % of data points that do not meet this criterion and are thus excluded).…”

Section: Methods For Deriving Brc Absorption From Observationsmentioning

confidence: 99%

“…relative differences in losses and sources are negligible). Based on the biofuel emissions of Bond et al (2007), the BC / OC emission ratio is 0.18 ± 0.03 in North America and Europe and 0.24 ± 0.06 in other regions. The BC / OC emission ratio for biomass burning in the GFED4 inventory is 0.12 ± 0.06 for different source types.…”

Section: Relationship Between Brc-aaod and Bc-aaodmentioning

confidence: 99%

See 4 more Smart Citations

Deriving brown carbon from multiwavelength absorption measurements: method and application to AERONET and Aethalometer observations

et al. 2016

Self Cite

View full text Add to dashboard Cite

Abstract. The radiative impact of organic aerosols (OA) is a large source of uncertainty in estimating the global direct radiative effect (DRE) of aerosols. This radiative impact includes not only light scattering but also light absorption from a subclass of OA referred to as brown carbon (BrC). However, the absorption properties of BrC are poorly understood, leading to large uncertainties in modeling studies. To obtain observational constraints from measurements, a simple absorption Ångström exponent (AAE) method is often used to separate the contribution of BrC absorption from that of black carbon (BC). However, this attribution method is based on assumptions regarding the spectral dependence of BC that are often violated in the ambient atmosphere. Here we develop a new AAE method which improves upon previous approaches by using the information from the wavelengthdependent measurements themselves and by allowing for an atmospherically relevant range of BC properties, rather than fixing these at a single assumed value. We note that constraints on BC optical properties and mixing state would help further improve this method. We apply this method to multiwavelength absorption aerosol optical depth (AAOD) measurements at AERONET sites worldwide and surface aerosol absorption measurements at multiple ambient sites. We estimate that BrC globally contributes up to 40 % of the seasonally averaged absorption at 440 nm. We find that the mass absorption coefficient of OA (OA-MAC) is positively correlated with the BC / OA mass ratio. Based on the variability in BC properties and BC / OA emission ratio, we estimate a range of 0.05-1.5 m 2 g −1 for OA-MAC at 440 nm. Using the combination of AERONET and OMI UV absorption observations we estimate that the AAE 388/440 nm for BrC is generally ∼ 4 worldwide, with a smaller value in Europe (< 2). Our analyses of observations at two surface sites (Cape Cod, to the southeast of Boston, and the GoAmazon2014/5 T3 site, to the west of Manaus, Brazil) reveal no significant relationship between BrC absorptivity and photochemical aging in urban-influenced conditions. However, the absorption of BrC measured during the biomass burning season near Manaus is found to decrease with photochemical aging with a lifetime of ∼ 1 day. This lifetime is comparable to previous observations within a biomass burning plume but much slower than estimated from laboratory studies. Given the large uncertainties associated with AERONET retrievals of AAOD, the most challenging aspect of our analysis is that an accurate, globally distributed, multiple-wavelength aerosol absorption measurement dataset is unavailable at present. Thus, achieving a better understanding of the properties, evolution, and impacts of global BrC will rely on the future deployment of accurate multiple-wavelength absorption measurements toPublished by Copernicus Publications on behalf of the European Geosciences Union.

show abstract

Section: Relationship Between Brc-aaod and Bc-aaodmentioning

confidence: 94%

Section: Methods For Deriving Brc Absorption From Observationsmentioning

confidence: 99%

Section: Methods For Deriving Brc Absorption From Observationsmentioning

confidence: 99%

Section: Methods For Deriving Brc Absorption From Observationsmentioning

confidence: 99%

Section: Relationship Between Brc-aaod and Bc-aaodmentioning

confidence: 99%

See 3 more Smart Citations

Deriving brown carbon from multiwavelength absorption measurements: method and application to AERONET and Aethalometer observations

et al. 2016

Self Cite

View full text Add to dashboard Cite

show abstract

Model representations of aerosol layers transported from North America over the Atlantic Ocean during the Two‐Column Aerosol Project

et al. 2016

Self Cite

View full text Add to dashboard Cite

The ability of the Weather Research and Forecasting model with chemistry (WRF‐Chem) version 3.7 and the Community Atmosphere Model version 5.3 (CAM5) in simulating profiles of aerosol properties is quantified using extensive in situ and remote sensing measurements from the Two‐Column Aerosol Project (TCAP) conducted during July of 2012. TCAP was supported by the U.S. Department of Energy's Atmospheric Radiation Measurement program and was designed to obtain observations within two atmospheric columns; one fixed over Cape Cod, Massachusetts, and the other several hundred kilometers over the ocean. The performance is quantified using most of the available aircraft and surface measurements during July, and 2 days are examined in more detail to identify the processes responsible for the observed aerosol layers. The higher‐resolution WRF‐Chem model produced more aerosol mass in the free troposphere than the coarser‐resolution CAM5 model so that the fraction of aerosol optical thickness above the residual layer from WRF‐Chem was more consistent with lidar measurements. We found that the free troposphere layers are likely due to mean vertical motions associated with synoptic‐scale convergence that lifts aerosols from the boundary layer. The vertical displacement and the time period associated with upward transport in the troposphere depend on the strength of the synoptic system and whether relatively high boundary layer aerosol concentrations are present where convergence occurs. While a parameterization of subgrid scale convective clouds applied in WRF‐Chem modulated the concentrations of aerosols aloft, it did not significantly change the overall altitude and depth of the layers.

show abstract

Characterizing model uncertainties in simulated coast-to-offshore wind over the northeast U.S. using multi-platform measurements from the TCAP field campaign

Tai,

Gaudet,

Feng

et al. 2025

Renewable Energy

View full text Add to dashboard Cite

The Two‐Column Aerosol Project: Phase I—Overview and impact of elevated aerosol layers on aerosol optical depth

Cited by 39 publications

References 89 publications

Deriving brown carbon from multiwavelength absorption measurements: method and application to AERONET and Aethalometer observations

Deriving brown carbon from multiwavelength absorption measurements: method and application to AERONET and Aethalometer observations

Model representations of aerosol layers transported from North America over the Atlantic Ocean during the Two‐Column Aerosol Project

Characterizing model uncertainties in simulated coast-to-offshore wind over the northeast U.S. using multi-platform measurements from the TCAP field campaign

Contact Info

Product

Resources

About