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Abstract: The total protein associated with bioaerosol particulate matter (PM) is generally measured as an all-inclusive indicator of airborne biological material, which may enhance the effects of allergens, allergic and asthmatic responses. To investigate the level and seasonal variations of biological loading, PM10 were collected in a metropolitan area of Hefei, central China from June 2008 to February 2009 and analyzed for total protein mass, trace elements, and water-soluble ions. The protein concentration in PM10 ranged from 2.08 to 36.71 μg m−3 with an average of 11.42 μg m−3. This was the highest value reported so far in the literature. The total protein was found to have a significant correlation with the air pollution index (API) and mean visibility (VV), indicating the potential influence of anthropogenic sources and/or crustal sources. The protein content displayed an obvious seasonal variation with respect to weather conditions. In the rainy season the level of protein was low, while in the dry season and foggy weather the level of protein was relatively high. A correlation analysis revealed that the relationship between total protein concentration and water-soluble ions K+ and in PM10 during the dry season is 0.92 and 0.66 (P < 0.05), respectively, suggesting that anthropogenic pollution and biomass burning are main contributors during this period. [Copyright &y& Elsevier]

This study presents the characterization of X CH4 (averaged-column dry air mole fraction) variability and trends using the near-infrared (NIR) solar spectra recorded by the ground-based high-resolution Fourier transform spectrometer (FTS) over Hefei, China. An annual increase of 10.55 ± 2.87 ppb yr −1 (0.56 ± 0.15% yr −1 ) in CH 4 concentrations was deduced from the three years’ worth of FTS measurements. Seasonal cycles and three typical diurnal variation modes were captured. The maximum CH 4 concentration occurred in late summer or early autumn, while the minimum CH 4 concentration occurred in winter. CH 4 concentrations in August were 30–55 ppb higher than those in January. In most cases, the diurnal variability exhibited an increasing trend in summer or early autumn, while it exhibited a decreasing trend or remained relatively constant in other seasons. We compared the FTS data with the GOSAT data and the GEOS-Chem model data. The average difference between the GOSAT and FTS data (GOSAT minus FTS) was 1.60 ppb (0.09%) ±13.0 ppb (0.70%), and between the smoothed GEOS-Chem model data and FTS data (GEOS-Chem minus FTS) was −8.09 ppb (0.45%) ±17.83 ppb (0.95%). The differences between GOSAT and FTS were season-independent; however, obvious season-dependent differences were observed between GEOS-Chem and FTS. The GOSAT and GEOS-Chem models could reproduce the seasonal cycle observed by FTS with correlation coefficients (r) of 0.77 and 0.86, respectively. [ABSTRACT FROM AUTHOR]