Aerosol‐planetary boundary layer (PBL) interactions have been found to enhance air pollution in megacities in China. We show that black carbon (BC) aerosols play the key role in modifying the PBL meteorology and hence enhancing the haze pollution. With model simulations and data analysis from various field observations in December 2013, we demonstrate that BC induces heating in the PBL, particularly in the upper PBL, and the resulting decreased surface heat flux substantially depresses the development of PBL and consequently enhances the occurrences of extreme haze pollution episodes. We define this process as the “dome effect” of BC and suggest an urgent need for reducing BC emissions as an efficient way to mitigate the extreme haze pollution in megacities of China.

Light-absorbing organic carbon (i.e., brown carbon or BrC) in the atmospheric aerosol has significant contribution to light absorption and radiative forcing. However, the link between BrC optical properties and chemical composition remains poorly constrained. In this study, we combine spectrophotometric measurements and chemical analyses of BrC samples collected from July 2008 to June 2009 in urban Xi'an, Northwest China. Elevated BrC was observed in winter (5 times higher than in summer), largely due to increased emissions from wintertime domestic biomass burning. The light absorption coefficient of methanol-soluble BrC at 365 nm (on average approximately twice that of water-soluble BrC) was found to correlate strongly with both parent polycyclic aromatic hydrocarbons (parent-PAHs, 27 species) and their carbonyl oxygenated derivatives (carbonyl-OPAHs, 15 species) in all seasons ( r > 0.61). These measured parent-PAHs and carbonyl-OPAHs account for on average ∼1.7% of the overall absorption of methanol-soluble BrC, about 5 times higher than their mass fraction in total organic carbon (OC, ∼0.35%). The fractional solar absorption by BrC relative to element carbon (EC) in the ultraviolet range (300-400 nm) is significant during winter (42 ± 18% for water-soluble BrC and 76 ± 29% for methanol-soluble BrC), which may greatly affect the radiative balance and tropospheric photochemistry and therefore the climate and air quality.

The chromophores responsible for light absorption in atmospheric brown carbon (BrC) are not well characterized, which hinders our understanding of BrC chemistry, the links with optical properties, and accurate model representations of BrC to global climate and atmospheric oxidative capacity. In this study, the light absorption properties and chromophore composition of three BrC fractions of different polarities were characterized for urban aerosol collected in Xi'an and Beijing in winter 2013−2014. These three BrC fractions show large differences in light absorption and chromophore composition, but the chromophores responsible for light absorption are similar in Xi'an and Beijing. Water-insoluble BrC (WI-BrC) fraction dominates the total BrC absorption at 365 nm in both Xi'an (51 ± 5%) and Beijing (62 ± 13%), followed by a humic-like fraction (HULIS-BrC) and high-polarity water-soluble BrC. The major chromophores identified in HULIS-BrC are nitrophenols and carbonyl oxygenated polycyclic aromatic hydrocarbons (OPAHs) with 2−3 aromatic rings (in total 18 species), accounting for 10% and 14% of the light absorption of HULIS-BrC at 365 nm in Xi'an and Beijing, respectively. In comparison, the major chromophores identified in WI-BrC are PAHs and OPAHs with 4−6 aromatic rings (in total 16 species), contributing 6% and 8% of the light absorption of WI-BrC at 365 nm in Xi'an and Beijing, respectively.

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Abstract. Aerosol pollution in eastern China is an unfortunate consequence of the region's rapid economic and industrial growth. Here, sun photometer measurements from seven sites in the Yangtze River Delta (YRD) from 2011 to 2015 were used to characterize the climatology of aerosol microphysical and optical properties, calculate direct aerosol radiative forcing (DARF) and classify the aerosols based on size and absorption. Bimodal size distributions were found throughout the year, but larger volumes and effective radii of fine-mode particles occurred in June and September due to hygroscopic growth and/or cloud processing. Increases in the fine-mode particles in June and September caused AOD 440 nm > 1.00 at most sites, and annual mean AOD 440 nm values of 0.71-0.76 were found at the urban sites and 0.68 at the rural site. Unlike northern China, the AOD 440 nm was lower in July and August (∼ 0.40-0.60) than in January and February (0.71-0.89) due to particle dispersion associated with subtropical anticyclones in summer. Low volumes and large bandwidths of both fine-mode and coarsemode aerosol size distributions occurred in July and August because of biomass burning. Single-scattering albedos at 440 nm (SSA 440 nm ) from 0.91 to 0.94 indicated particles with relatively strong to moderate absorption. Strongly absorbing particles from biomass burning with a significant SSA wavelength dependence were found in July and August at most sites, while coarse particles in March to May were Published by Copernicus Publications on behalf of the European Geosciences Union. 406H. Che et al.: Aerosol optical properties and direct radiative forcing mineral dust. Absorbing aerosols were distributed more or less homogeneously throughout the region with absorption aerosol optical depths at 440 nm ∼ 0.04-0.06, but inter-site differences in the absorption Angström exponent indicate a degree of spatial heterogeneity in particle composition. The annual mean DARF was −93 ± 44 to −79 ± 39 W m −2 at the Earth's surface and ∼ −40 W m −2 at the top of the atmosphere (for the solar zenith angle range of 50 to 80 • ) under cloud-free conditions. The fine mode composed a major contribution of the absorbing particles in the classification scheme based on SSA, fine-mode fraction and extinction Angström exponent. This study contributes to our understanding of aerosols and regional climate/air quality, and the results will be useful for validating satellite retrievals and for improving climate models and remote sensing algorithms.

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