To quantitatively estimate and analyze the contribution of different aerosol types to radiative forcing, we thoroughly investigated their optical and radiative properties using the Aerosol Robotic Network (AERONET) data (2007-2018) over an urban-industrial (Lahore) and coastal (Karachi) cities located in Pakistan. The contribution of inferred aerosol types following the threshold applied for FMF500 versus SSA(440) and EANG(440-870) versus AANG(440-870) were found the highest for pure dust (PUD, 31.90%) followed by polluted continental (POC, 24.77%) types of aerosols, with moderate contribution was recorded for polluted dust (POD, 20.92%), organic carbon dominating (OCD, 11.85%), black carbon dominating (BCD, 8.77%) and the lowest for the non-absorbing (NOA, 1.79%) aerosol type. Seasonally, the mean (+/- SD) aerosol optical thickness at 440 nm (AOT(440)) was found maximum (0.73 +/- 0.36) for PUD type in summer and minimum for BCD (0.25 +/- 0.04) during spring at Karachi. However, the mean (+/- SD) AOT(440) varied from 0.85 +/- 0.25 during summer to 0.57 +/- 0.30 in winter at Lahore, with the highest contributions for POC (29.91%) and BCD (22.58%) and the lowest for NOA (5.85%) type of aerosols. Further, the intensive optical properties showed significant temporal and spectral changes and the complexity of inferred aerosol types over the study sites. The results are well substantiated with the air mass analysis obtained from the concentration weighted trajectory (CWT) model for different aerosol types. The Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART) model revealed the strong presence of BCD aerosol type led to a surface (BOA) and top of atmosphere (TOA) forcing of -70.12, -99.78 Wm(-2) and -9.60, -19.74 Wm(-2), with an annual heating rate of 2.10 and 2.54 Kday(-1), respectively, at Karachi and Lahore sites.

We use Aerosol Robotic Network (AERONET) observation data to empirically determine how natural and anthropogenic aerosol categories (i.e. mineral dust, biomass burning, and urban-industrial aerosols) affect light extinction, showing that their radiative forcing varies strongly with the surface albedo. Generally, the radiative forcing depends on the aerosol loading, but the efficiency varies with the aerosol type and aerosol-radiation-surface interactions. Desert dust, biomass burning and urban-industrial aerosols can exhibit dramatic shifts in radiative forcing at the top of the atmosphere, from cooling to warming, at surface albedos from below 0.5 to above 0.75. Based on the linear relationship between the radiative forcing efficiency and surface albedo for aeolian aerosols, using Moderate Resolution Imaging Spectroradiometer (MODIS) AOT (Aerosol Optical Thickness) and surface albedo data, we characterized a large Asian dust event during the spring of 2001, and demonstrate its immense spatially varying radiative forcing, ranging from about -84.0 to +69.3 W/m(2). For extensive Russian wildfires during the summer of 2010, strong radiative cooling forcing variability of biomass combustion aerosols is found, ranging from about -86.3 to +3.1 W/m(2). For a thick urban-industrial aerosol haze over northern India during the winter of 2017, a large range of about -85.0 to -0.3 W/m(2) is found. These wide ranges underscore the need to accurately define aerosol-radiation-surface interactions.

A two-step approach is proposed to derive component aerosol direct radiative forcing (ADRF) at the top of atmosphere (TOA) over global oceans from 60 degrees S to 60 degrees N for clear-sky condition by combining Terra CERES/MODIS-SSF shortwave (SW) flux and aerosol optical thickness (AOT) observations with the fractions of component AOTs from the GSFC/GOCART model. The derived global annual mean component ADRF is +0.08 +/- 0.17 W/m(2) for black carbon, -0.52 +/- 0.24 W/m(2) for organic carbon, -1.10 +/- 0.42 W/m(2) for sulfate, -0.99 +/- 0.37 W/m(2) for dust, -2.44 +/- 0.84 W/m(2) for sea salt, and -4.98 +/- 1.67 W/m(2) for total aerosols. The total ADRF has also been partitioned into anthropogenic and natural components with a value of -1.25 +/- 0.43 and -3.73 +/- 1.27 W/m(2), respectively. The major sources of error in the estimates have also been discussed. The analysis adds an alternative technique to narrow the large difference between current model-based and observation-based global estimates of component ADRF by combining the satellite measurement with the model simulation. (c) 2007 Elsevier Ltd. All rights reserved.