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Aim:  To characterize the microbial community structure and bamA gene diversity involved in anaerobic degradation of toluene and benzoate under denitrifying conditions. Methods and Results:  Nitrate‐reducing enrichment cultures were established on either toluene, benzoate or without additional substrate. Bacterial community structures were characterized by 16S rRNA gene–based PCR‐DGGE analysis. bamA gene diversity was analysed using DGGE and cloning methods. The results showed that bamA gene related to bamA of Thauera chlorobenzoica was dominant in toluene and benzoate cultures. However, a greater diversity of sequences was obtained in benzoate cultures. Low diversity of bamA gene was observed, and some similarities of bamA were also found between active cultures and backgrounds, suggesting that potential natural attenuation of aromatic compounds might occur. Conclusions:  The combined analysis of 16S rRNA and bamA genes suggests that the species related to genera Thauera dominated toluene‐ and benzoate‐degrading cultures. The combination of multiple methods (DGGE and cloning) provides a more complete picture of bamA gene diversity. Significance and Impact of the Study:  To our knowledge, this is the first report of bamA gene in denitrifying enrichments using DGGE and cloning analysis.

Abstract. Aerosol hygroscopicity and cloud condensation nuclei (CCN) activity under clean conditions and polluted events are investigated based on size-resolved CCN and aerosol chemical composition observations during the Aerosol-CCN-Cloud Closure Experiment (AC3Exp) campaign conducted at Xianghe, China in summer 2013. About 14–22% of aerosol particles during the campaign are of externally mixed CCN-inactive particles that cannot serve as CCN under atmospheric typical supersaturation (SS) of ∼0.4%. A high sensitivity of Maximum activation fractions (MAF) to SS under polluted conditions has been observed. The pollutants can cause a maximum MAF decrease of 25–30% (at SS = 0.08%). Hygroscopicity parameter kappa (κ) are about 16–35% lower under polluted conditions than under clean conditions for particles in accumulation size range (80–180 nm); however, for particles in nucleation or Aitken size range (30–60 nm), κ is slightly higher under polluted conditions. A non-parallel observation (NPO) CCN closure study shows low correlation coefficient between estimated and observed CCN number concentrations (NCCN). About 30–40% uncertainties in NCCN prediction are associated with the changes of particle composition. A case study shows that CCN activation ratio (AR) increased with the increase of condensation nuclei (CN) number concentrations (NCN) in relatively clean days. In the case, AR exhibited good correlation with κchem, which is calculated from chemical volume fractions, due to particles mainly composed of soluble inorganics. On the contrary, AR declined with increase of NCN during polluted events when particles composed mostly of organics. Meanwhile, AR is closely related to f44, which is the fraction of total organic mass signal at m/z 44 and closely associated with particle organic oxidation level. Our study highlights the importance of aerosols chemical composition on determining the activation properties of aerosol particles, underlining the importance of long-term observation of CCN under different atmospheric environments, especially those with heavy pollution and high CN number concentrations.

The wavelength dependence of the retardation induced by a photoelastic modulator (PEM) is a central issue in multichannel modulator-based spectroscopic ellipsometry and reflectance difference spectroscopy (RDS), where the optical signal is detected simultaneously at different wavelengths. Here we present a refined analysis of the modulator crystal's retardation and its effect on the signal quality. Two retardation correction schemes that take into account the actual wavelength dependence of the stress-optic coefficient are introduced. It is demonstrated experimentally that both methods provide a better correction than the procedure currently used in multichannel RDS. We define quality factors to evaluate the actual performance of the multichannel detection system as compared with a wavelength adaptive single-channel experiment. These quality factors thus provide a useful guideline for choosing the appropriate PEM retardation or reference wavelength in a multichannel experiment.