[1] The incision of rivers in bedrock is thought to be an important factor that influences the evolution of relief in tectonically active orogens. At present, there are at least six competing models for incision of bedrock rivers, but these models have received little quantitative testing. We statistically evaluate these models using observations from the Clearwater River in northwestern Washington State, which crosses the actively rising forearc high of the Cascadia margin. A previous study has used fluvial terraces along the Clearwater to estimate bedrock incision rates over the last $150 kyr. They show that incision rates have been steady over the long-term (>50 kyr), consistent with other evidence based on isotopic cooling ages, for steady long-term (>1 Myr) erosion rates. The steady state character of the river allows us to use the relatively simple time-invariant solutions for the various incision models and also to estimate long-term sediment discharge along the river, which is a critical variable for some incision models. An interesting feature of the Clearwater River is that it has a downstream decrease in the rate of incision, from $0.9 mm/yr in the headwater to <0.1 mm/yr at the coast. None of the incision models, including the shear stress model, successfully accounts for this relationship. This result may be due to the simple way in which these models are used, commonly without consideration for the distribution of discharge with time, and the variable capacity of the river channel to contain peak flows along its course. We suggest some general improvements for the incision models, and also guidelines for selecting those rivers that will allow good discrimination between competing models.

Climate controls landscape evolution, but quantitative signatures of climatic drivers have yet to be found in topography on a broad scale. Here we describe how a topographic signature of typhoon rainfall is recorded in the meandering of incising mountain rivers in the western North Pacific. Spatially averaged river sinuosity generated from digital elevation data peaks in the typhoon-dominated subtropics, where extreme rainfall and flood events are common, and decreases toward the equatorial tropics and mid-latitudes, where such extremes are rare. Once climatic trends are removed, the primary control on sinuosity is rock weakness. Our results indicate that the weakness of bedrock channel walls and their weakening by heavy rainfall together modulate rates of meander propagation and sinuosity development in incising rivers.

A prior study in New York City observed that airborne concentrations of three metals found in steel – iron, manganese, and chromium – are more than 100 times higher in the subway system than in aboveground air. To investigate the potential for health effects of exposure at these levels, we conducted a pilot study of subway workers comparing personal exposures to steel dust with biomarkers of metal exposure, oxidative stress, and DNA damage in blood and urine samples. Workers wore a personal air sampler operating at 4 L/m for one to three work shifts with blood and urine samples collected at the end of the final shift. We found that PM2.5 exposures varied among subway workers on the basis of job title and job activity. The subway workers’ mean time-weighted PM2.5 exposure was 52 µg/m3, with a median of 27 µg/m3, and a range of 6–469 µg/m3. The observed concentrations of PM2.5, iron, manganese, and chromium fell well below occupational standards. Biomarker concentrations among the 39 subway workers were compared with a group of 11 bus drivers, and a group of 25 suburban office workers. Concentrations of DNA–protein crosslinks and chromium in plasma were significantly higher in subway workers than in bus drivers, but no significant difference was observed for these biomarkers between subway workers and office workers. Urinary isoprostane concentrations were significantly correlated with the number of years working in the subway system, and were detected at higher, though not significantly higher, concentrations in subway workers than in bus drivers or office workers. At the group level, there was no consistent pattern of biomarker concentrations among subway workers significantly exceeding those of the bus drivers and office workers. At the individual level, steel dust exposure was not correlated with any of the biomarkers measured.

The aim of this research is to provide a detailed characterization of spatial patterns and temporal trends in the regional and local dust source areas within the desert of the Alashan Prefecture (Inner Mongolia, China). This problem was approached through multi‐scale remote sensing analysis of vegetation changes. The primary requirements for this regional analysis are high spatial and spectral resolution data, accurate spectral calibration and good temporal resolution with a suitable temporal baseline. Landsat analysis and field validation along with the low spatial resolution classifications from MODIS and AVHRR are combined to provide a reliable characterization of the different potential dust‐producing sources. The representation of intra‐annual and inter‐annual Normalized Difference Vegetation Index (NDVI) trend to assess land cover discrimination for mapping potential dust source using MODIS and AVHRR at larger scale is enhanced by Landsat Spectral Mixing Analysis (SMA). The combined methodology is to determine the extent to which Landsat can distinguish important soils types in order to better understand how soil reflectance behaves at seasonal and inter‐annual timescales. As a final result mapping soil surface properties using SMA is representative of responses of different land and soil cover previously identified by NDVI trend. The results could be used in dust emission models even if they are not reflecting aggregate formation, soil stability or particle coatings showing to be critical for accurately represent dust source over different regional and local emitting areas. Copyright © 2012 John Wiley & Sons, Ltd.