The importance of light-absorbing organic aerosols, often called brown carbon
(BrC), has become evident in recent years. However, there have been
relatively few measurement-based estimates for the direct radiative effect of
BrC so far. In earlier studies, the AErosol RObotic NETwork
(AERONET)-measured aerosol absorption optical depth (AAOD) and absorption
Angstrom exponent (AAE) were exploited. However, these two pieces of
information are clearly not sufficient to separate properly carbonaceous
aerosols from dust, while imaginary indices of refraction would contain more
and better justified information for this purpose. This is first time that
the direct radiative effect (DRE) of BrC is estimated by exploiting the
AERONET-retrieved imaginary indices. We estimated it for four sites in the
Indo-Gangetic Plain (IGP), Karachi, Lahore, Kanpur and Gandhi College. We
found a distinct seasonality, which was generally similar among all the
sites, but with slightly different strengths. The monthly warming effect up
to 0.5 W m

Aerosols affect the Earth's climate both directly (by
scattering and absorbing radiation) and indirectly (by serving as nuclei for
cloud droplets). Currently, aerosol forcing is the largest uncertainty in
assessing the anthropogenic climate change

The approach of

AERONET (AErosol RObotic NETwork) is a globally distributed network of
automatic Sun and sky scanning radiometers that measure at several
wavelengths, typically centered at 0.34, 0.38, 0.44, 0.50, 0.67, 0.87, 0.94,
and 1.02

The estimated uncertainty in AOD (Level 2) is 0.01–0.02 and is primarily due
to the calibration uncertainty

Since the shortest sky radiance wavelength is 440 nm, AERONET wavelengths are not ideal for detecting BrC absorption, which is much stronger at shorter than at 440 nm wavelengths. However, it is also stressed that AOD is very high for all sites that were analyzed, allowing for sufficient robustness in the retrieved spectral signal in the imaginary refractive index.

In our study, we used Level 2 data of size distributions and refractive
indices at four retrieval wavelengths 0.44, 0.67, 0.87 and 1.02. Moreover, we
also included some Level 1.5 refractive indices, when
0.2

We included four AERONET sites for our data analysis, covering wide
conditions in the Indo-Gangetic Plain (IGP): Karachi and Lahore in Pakistan,
and Kanpur and Gandhi College in India. The measurements covered the
following time periods: Gandhi College: 4/2006–3/2010; Kanpur:
1/2001–4/2012; Karachi: 9/2006–8/2011; Lahore: 4/2007–10/2011. Figure 1
shows the locations of these sites overlaid in the annual mean AOD map from
MODIS Terra. In the IGP there are large local emissions of aerosols from
various sources: heavy particulate pollution from industrial sources, strong
vehicular emissions, use of fossil fuels, and widespread biomass and
agricultural crop residue burning. In addition, the IGP is strongly affected
by seasonal (pre-monsoon) mineral dust transported mainly from the Thar
Desert

Annual mean AOD from MODIS Terra, with our AERONET study sites
overlaid in the map. Source of MODIS data:

Figure 2 shows the monthly mean AOD and SSA at 440 nm for our study sites. It is noted that this data set includes all AOD values (from the inversion data set) without the AOD threshold of 0.2 that we applied for refractive indices and also for SSA shown in the lower plot. This figure then further illustrates that the AOD levels are typically high and why our selected set of refractive indices was not very different to the “full” Level 2. The relative fractions of Level 2 data out of our selected set from Level 1.5, for refractive indices, were about 60, 97, 85, and 88 % for Karachi, Lahore, Kanpur, and Gandhi College, respectively.

Monthly mean AOD and SSA at 440 nm for our selected AERONET sites. Annual means are indicated by a symbol after December.

Since the main details of the methodology are comprehensively described
elsewhere, particularly in

The AERONET-retrieved imaginary refractive indices at four wavelengths form the basis for retrieving the fractions of absorbing components, including BrC.

The retrieval initially populates the fine mode with BC and BrC and the
coarse mode with dust components (hematite and goethite). However, in some
cases, in order to reach a realistic fit with the AERONET-retrieved imaginary
indices, some of the fine mode has to additionally include iron oxides
(hematite and goethite), and likewise some of the coarse mode can include
carbonaceous aerosols. The average imaginary index of the three longest
wavelengths (670, 870, 1020 nm), at red and near-infrared and hereinafter
referred to by

Imaginary indices at 440 nm and RNIR (average of 670, 870, and 1020 nm) assumed for each component in the
retrieval of

Number of AERONET observations for each month for the four sites. Data were collected for Karachi from September 2006 to August 2011, for Lahore from April 2007 to October 2011, for Kanpur from January 2001 to April 2012, and for Gandhi College from April 2006 to March 2010. Monthly data in parentheses were not included in the study due to the low number of observations.

There is a significant seasonality in both components of carbonaceous
aerosols, particularly in BC, the largest fractions occurring in the winter
and late fall seasons. This BC seasonality agrees well with the seasonal
pattern that has been obtained by the surface measurements in the IGP

Boxplot of monthly imaginary indices: average of the imaginary index
at 670, 870, and 1020 nm (

Monthly averages of imaginary indices and the retrieved fraction of
carbonaceous aerosols:

The radiative transfer calculations were performed by using the libRadtran
package

Size distributions and refractive indices were then used for calculating the
aerosol optical properties for the non-BrC mixture, which was done by
utilizing the spheroid aerosol model by

Figure 5 shows our simulated radiative effects by BrC in the lowest panel,
while the upper and middle panels include relevant parameters to interpret
these results. The difference in AOD at 440 nm (in blue) and at RNIR
(average of 670–1020, in red) between the simulations with and without BrC
is shown in the upper panel. The middle panel shows similar results for SSA,
which are particularly relevant quantities now to understand whether the
overall effect is warming or cooling when BrC is added in. It is emphasized
that while brown carbon is absorbing at the shortest wavelengths, determined
by the measurement at 440 nm in our case, it is almost purely scattering at
RNIR wavelengths. Therefore, when BrC is included, there are typically two
spectrally competing effects taking place, warming at the shortest and
cooling at the longer wavelengths. And we can detect these effects also in
the middle panel of Fig. 5. In principle, the scattering coefficient at RNIR
increases when BrC is added, while the absorption coefficient remains close
to a constant. Therefore, SSA (

The relative strength of these spectrally separated cooling and warming
effects will eventually determine whether the overall spectrally integrated
shortwave direct effect is cooling or warming. And the strength of both these
effects, in turn, depends on the relative fractions of the other components
present. In our version of absorbing components by

Monthly DRE (W m

As can be seen from Table 1, BC has the largest imaginary index at RNIR wavelengths, and therefore the most sensitive change towards cooling at RNIR takes place when BrC is added to the mixture of relatively large amounts of black carbon. These changes in the imaginary index, with and without BrC, essentially determine the SSA patterns we see in the middle panel of Fig. 5. Therefore, it is useful and clarifying to further interpret our BrC DRE results by focusing next on these changes. Figure 6 shows the change in imaginary index (based on volume averaging), both at 440 nm and RNIR range, if BrC is added in. The scale of both the BC and BrC volume fractions in this figure was determined by the range retrieved for our IGP sites (in the middle panel of Fig. 4). It is evident that including BrC results in an increase of the imaginary index difference at 440 nm, which is a strong function of the BrC volume fraction but depends only slightly on the BC fraction (shown by the solid isolines of the figure). At RNIR range the behavior is quite different: at low enough BC fractions, BrC can result in an increase in the imaginary index; however, most often the opposite is true (shown by the color bar and dotted isolines of the figure). Moreover, this decrease in the imaginary index with increasing BrC volume fraction depends also relatively strongly on the BC volume fraction. This means that for a given BrC fraction, the larger the volume fraction of BC, the stronger the cooling effect at RNIR wavelengths.

Our estimated values for the DRE of BrC shown in Fig. 5, and the corresponding changes in SSA (in the middle panels), are best understood with the help of Fig. 6 and there by the behavior at RNIR in particular. Therefore, this figure includes additionally the retrieved monthly averaged volume fractions of BC and BrC for 2 months, April and November, selected here to roughly represent the periods of the strongest warming and cooling. The name of the site is indicated next to the month of April; thus, the other end of the line corresponds to November. As can be seen from the middle panel of Fig. 5, the largest positive SSA difference at RNIR, when BrC is included, is in Gandhi College in November, which consistently corresponds to the case of the most negative change of the RNIR imaginary index in Fig. 6. This is then also the case of the strongest overall cooling by BrC. The spectral SSA changes due to the BrC, which are illustrated in the middle panel of Fig. 5, mainly determine whether overall cooling or warming takes place. However, the actual magnitude of these spectral cooling and warming contributions, in turn, are also substantially influenced by the absolute BrC fractions in AOD, which are shown in the upper panel of Fig. 5. It is evident that the large values of BrC optical depths at the end of the year in Gandhi College, in addition to the large increase of SSA at RNIR wavelengths, also strongly contribute to the considerable DRE of BrC. Brown carbon causes cooling in the other sites as well during this time of the year, when BC fractions are at their highest. On the other hand, the warming takes place typically in the spring season in all the sites, when BC fractions are lower but BrC fractions are at relatively high levels (shown in Figs. 4 and 6). To summarize, the common pattern is the warming by BrC in the spring season and cooling in the late fall and winter (except for Karachi where cooling takes place only in November–December), and this change of sign in the radiative effect by BrC is due to the different relative fractions of BC during the spring and late fall seasons.

Upper panel: monthly averages of the difference in AOD at 440 nm (blue) and at RNIR (red) between simulations with and without BrC. Middle panel: corresponding cases for SSA. Lower panel: monthly average DRE of BrC. Corresponding annual averages are given by the symbol after December.

Difference between the imaginary index with and without BrC included at 440 nm (solid isolines) and at RNIR wavelengths (by color bar and dotted isolines) as a function of BC and BrC volume fractions. Monthly mean values of BC and BrC volume fractions are shown for each site by symbols and lines for 2 months: April with the name of the site next to it and November at the other end of the line.

The annually averaged DRE of BrC is slightly positive for Karachi, while Lahore and Kanpur have slight cooling by BrC. The annually averaged negative forcing in Gandhi College is somewhat more profound due to the strongest cooling in the November–December period. The strongest cooling is due to the highest total BrC concentrations and thus AOD corresponding to the BrC during this period, as can be seen from the upper panel of Fig. 5.

Finally, Table 3 gives monthly DRE values for the following cases of included
aerosol types: total aerosols, BrC, BC and additionally the case with all
aerosols except for BrC (“non-BrC”). One can conclude, for example, that
during April–May the relative magnitude of warming by BrC is about 5–7 %
of total aerosol cooling, except for Gandhi College, where it is as high as
20 % in April due to the strong BC absorption and thus small overall
cooling. On the other hand, the importance of accounting properly for the
spectral BrC effect in the DRE of carbonaceous aerosols (BrC

As discussed above, whether the spectrally integrated SW direct radiative
effect by BrC results in cooling or warming is determined by the relative
strength of two opposing effects, warming at shorter wavelengths and cooling
at the RNIR range. Thus it is crucial to properly take both of these spectral
effects into account, which is often true for total aerosol DRE calculations
as well. However, it has also been common to estimate the optical properties
at mid-visible only and then apply some simple approximations and assumptions
to account for spectral dependence in direct radiative effect calculations

Direct radiative effect in Kanpur based on two spectral ranges of Kato bands: (1) all Kato bands and (2) Kato band no. 10 (center wavelength at 544.8 nm), but scaled to account for the full SW range. Upper panel: for BC; middle panel: for BrC; lower panel: for total aerosol.

It is evident that a single wavelength approach can produce a rather stable
estimate for the BC radiative effect; the relative error is within

The importance of light-absorbing organic aerosols has become evident in
recent years. It is important to understand and take into account the effects
of BrC not only for the aerosol radiative forcing, but also for surface UV
radiation levels and remote sensing from satellite in the UV wavelengths.
However, there are relatively few measurement-based estimates for the direct
radiative effect of BrC so far. In those earlier studies, the
AERONET-measured AAOD and AAE have been exploited, while this is the first
time that the DRE of BrC is estimated by exploiting the AERONET-retrieved
imaginary indices. With AAOD and AAE information only, there is little
information about the aerosol size, and thus the separation of dust and BrC
absorption becomes unclear, while arguably with the use of imaginary indices

We estimated the DRE of BrC as a difference of two radiative transfer runs:
the case for all aerosols and without BrC. We estimated the DRE of BC and
total aerosol similarly and, in that context, it became evident that the role
of BrC is not insignificant and, moreover, it is crucial to properly account
for its spectral radiative effect. The DRE of BrC can reach magnitudes of
10 % relative to BC, so it is not negligible in the DRE of absorbing
carbonaceous (BC

This study was supported by the Academy of Finland (project number 264242).Edited by: E. Gerasopoulos