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Porous carbon-based materials are commonly used to remove various organic and inorganic pollutants from gaseous and liquid effluents and products. In this study, the adsorption of dioxins on both activated carbons and multi-walled carbon nanotube was internally compared, via series of bench scale experiments. A laboratory-scale dioxin generator was applied to generate PCDD/Fs with constant concentration (8.3 ng I-TEQ/Nm(3)). The results confirm that high-chlorinated congeners are more easily adsorbed on both activated carbons and carbon nanotubes than low-chlorinated congeners. Carbon nanotubes also achieved higher adsorption efficiency than activated carbons even though they have smaller BET-surface. Carbon nanotubes reached the total removal efficiency over 86.8 % to be compared with removal efficiencies of only 70.0 and 54.2 % for the two other activated carbons tested. In addition, because of different adsorption mechanisms, the removal efficiencies of carbon nanotubes dropped more slowly with time than was the case for activated carbons. It could be attributed to the abundant mesopores distributed in the surface of carbon nanotubes. They enhanced the pore filled process of dioxin molecules during adsorption. In addition, strong interactions between the two benzene rings of dioxin molecules and the hexagonal arrays of carbon atoms in the surface make carbon nanotubes have bigger adsorption capacity.

Light-absorbing particles (LAPs) deposited on snow can significantly reduce surface albedo and contribute to positive radiative forcing. This study firstly estimated and attributed the spatio-temporal variability in the radiative forcing (RF) of LAPs in snow over the northern hemisphere during the snow-covered period 2003–2018 by employing Moderate Resolution Imaging Spectroradiometer (MODIS) data, coupled with snow and atmospheric radiative transfer modelling. In general, the RF for the northern hemisphere shows a large spatial variability over the whole snow-covered areas and periods, with the highest value (12.7 W m−2) in northeastern China (NEC) and the lowest (1.9 W m−2) in Greenland (GRL). The concentration of LAPs in snow is the dominant contributor to spatial variability in RF in spring (~73%) while the joint spatial contributions of snow water equivalent (SWE) and solar irradiance (SI) are the most important (>50%) in winter. The average northern hemisphere RF gradually increases from 2.1 W m−2 in December to 4.1 W m−2 in May and the high-value area shifts gradually northwards from mid-altitude to high-latitude over the same period, which is primarily due to the seasonal variability of SI (~58%). More interestingly, our data reveal a significant decrease in RF over high-latitude Eurasia (HEUA) of −0.04 W m−2 a−1 and northeastern China (NEC) of −0.14 W m−2 a−1 from 2003 to 2018. By employing a sensitivity test, we find the concurrent decline in the concentration of LAPs in snow accounted for the primary responsibility for the decrease in RF over these two areas, which is further confirmed by in situ observations.

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