Daily average monitoring data for PM10, PM2.5 and PM1.0 and meteorological parameters at Chengdu from 2009 to 2011 are analyzed using statistical methods to replicate the effect of urban air pollution in Chengdu metropolitan region of the Sichuan Basin. The temporal distribution of, and correlation between, PM10, PM2.5 and PM1.0 particles are analyzed. Additionally, the relationships between particulate matter (PM) and certain meteorological parameters are studied. The results show that variations in the average mass concentrations of PM10, PM2.5 and PM1.0 generally have the same V-shaped distributions (except for April), with peak/trough values for PM average mass concentrations appearing in January/September, respectively. From 2009 to 2011, the inter-annual average mass concentrations of PM10, PM2.5 and PM1.0 fall year on year. The correlation coefficients of daily concentrations of PM10 with PM2.5, PM10 with PM1.0, and PM2.5 with PM1.0 were high, reaching 0.91, 0.83 and 0.98, respectively. In addition, the average ratios of PM2.5/PM10, PM1.0/PM10 and PM1.0/PM2.5 were 85%, 78% and 92%, respectively. From this, fine PM is determined to be the principal pollutant in the Chengdu region. Except for averaged air pressure values, negative correlations exist between other meteorological parameters and PM. Temperature and air pressure influenced the transport and accumulation of PM by

SUMMARYThe apparent intensity of hyaluronan (HA) staining in tissue sections can vary as a function of fixation techniques. We examined the histochemical distribution of HA in normal human skin using an HA-specific binding peptide derived from bovine nasal cartilage. The HA, particularly in the dermis, was best preserved in sections fixed in 10% acidformalin with 70% ethanol. In contrast, sections fixed in the routine 10% neutral-buffered formalin had a much weaker intensity of HA staining. Furthermore, acid-formalin/ethanolfixed sections retained much of their apparent HA after incubation with saline, in contrast to the neutral formalin-fixed sections, in which most of the stainable HA was lost. Such marked differences in staining intensity were not observed in slides stained with Alcian blue, a procedure pressumed to stain HA as well as other glycosaminoglycans. Staining using the HA binding peptide was entirely absent when sections were first preincubated in hyaluronidase, whereas similar Alcian blue-stained sections retained most of their staining intensity. Caution should be exercised in evaluating the distribution of HA in tissues using the HA binding peptide, particularly when different fixation techniques among several laboratories are being compared. In addition, the ability to evaluate the HA content of tissues using Alcian blue staining should be reconsidered. The sulfated glycosaminolglycans of the "ground substance" appear to be the predominant substrates for Alcian blue.

The quality of the Ku-band scatterometer-derived winds is known to be degraded by the presence of rain. Little work has been done in characterizing the impact of rain on C-band scatterometer winds, such as those from the Advanced Scatterometer (ASCAT) onboard Metop-A. In this paper, the rain impact on the ASCAT operational level 2 quality control (QC) and retrieved winds is investigated using the European Centre for Medium-range Weather Forecasts (ECMWF) model winds, the Tropical Rainfall Measuring Mission's (TRMM) Microwave Imager (TMI) rain data, and tropical buoy wind and precipitation data as reference. In contrast to Ku-band, it is shown that C-band is much less affected by direct rain effects, such as ocean splash, but effects of increased wind variability appear to dominate ASCAT wind retrieval. ECMWF winds do not well resolve the airflow under rainy conditions. ASCAT winds do but also show artifacts in both the wind speed and wind direction distributions for high rain rates (RRs). The operational QC proves to be effective in screening these artifacts but at the expense of many valuable winds. An image-processing method, known as singularity analysis, is proposed in this paper to complement the current QC, and its potential is illustrated. QC at higher resolution is also expected to result in improved screening of high RRs.Index Terms-Geophysical inverse problems, image processing, microwave measurements, quality control, remote sensing.

The assessment and validation of the quality of satellite scatterometer vector winds is challenging under increased subcell wind variability conditions, since reference wind sources such as buoy winds or model output represent very different spatial scales from those resolved by scatterometers (i.e., increased representativeness error). In this paper, moored buoy wind time series are used to assess the correlation between subcell wind variability and several Advanced Scatterometer (ASCAT)‐derived parameters, such as the wind‐inversion residual, the backscatter measurement variability factor, and the singularity exponents derived from an image processing technique, called singularity analysis. It is proven that all three ASCAT parameters are sensitive to the subcell wind variability and complementary in flagging the most variable winds, which is useful for further application. A triple collocation (TC) analysis of ASCAT, buoy, and the European Centre for Medium‐range Weather Forecasting (ECMWF) model output is then performed to assess the quality of each wind data source under different variability conditions. A novel approach is used to compute the representativeness errors, a key ingredient for the TC analysis. The experimental results show that the estimated errors of each wind source increase as the subcell wind variability increases. When temporally averaged buoy winds are used instead of 10 min buoy winds, the TC analysis results in smaller buoy wind errors (notably at increased wind variability conditions) while ASCAT and ECMWF errors do not significantly change, further validating the proposed TC approach. It is concluded that at 25 km resolution, ASCAT provides the best quality winds in general.