Observations on the suitability of the aethalometer for vehicular and workplace monitoring

A field study was undertaken to evaluate the suitability of the aethalometer, an instrument capable of performing near-real-time measurement of low-level (10-1,000 ng/m3) airborne combustion products, for vehicular and workplace monitoring. Several technical limitations were identified: (1) there was no ready means for external calibration of optical measurements; (2) airflow rates were unstable; (3) effective range of concentrations was limited; and (4) the aethalometer demonstrated sensitivity to movement and vibration. Unless addressed, these limitations will restrict future uses of the aethalometer for vehicular and workplace monitoring.     

Photosynthesis, chlorophyll integrity, and spectral reflectance in lichens exposed to air pollution

The major objective of the present study was to identify the relationship of physiologial parameters of the photosynthetic system with the elemental content of the lichen Ramalina lacera (With.) J.R. Laund. Thalli of R. lacera were collected in an unpolluted site and transplanted in a national park and an industrial region in Israel for 8 mo. Analyses of photosynthetic activity, chlorophyll integrity, spectral reflectance, and amount of 11 metals were performed after this period of exposure. The normalized difference vegetation index (NDVI), indicative of the spectral reflectance response of the thallus, correlated with photosynthetic rate and chlorophyll and K content and correlated inversely with amounts of Ba, Cr, Cu, and Ni. The NDVI appears to enable the detection of early signs of pollutant-induced stress before changes in other physiological parameters become apparent. Elevated amounts of Cr, Cu, Fe, Mn, Ni, and Zn in lichens transplanted to an industrial area and the correlation of Mn and Ni, Mn and V, Ni and V, Fe and Mn, Fe and V, and Fe and Zn point for the greater part to metal processing in a steel smelter. Correlations of Cr and Ni, Cu and Ni, Zn and Cu, Cu and Mn, and Zn and Ni could be related to metal processing in the industrial area but indicate also vehicular activity as a possible originator.     

An analysis of occupational stair accident patterns

This report describes an analysis of existing occupational injury data concerning stairway-related falls. Injury data based on reports obtained from the Ohio and California workers' compensation agencies were analyzed to identify common stair injury patterns. Frequency tabulations are provided for the following factors: (a) location (indoors vs. outdoors, on vs. off employer's premises, site category); (b) task (ascending vs. descending, body movement on the stair, task being attempted); and (c) events (precipitating actions and conditions). One of the most outstanding findings is that 92 % of the injuries occurred when the worker was descending the stair, i.e., 636 of the 688 cases in which direction of travel was indicated. Additionally, injury records from the New York and Ohio workers' compensation agencies were used to rank industries in terms of combined frequency and severity rates of stairway-related injuries.     

Work-related deaths in Washington State, 1998-2002

INTRODUCTION: In Washington State, 87 workers are killed each year, on average, while in work status. To understand these incidents and to assist in focusing on and development of potential prevention measures, they must be well characterized. METHODS: Work-related fatalities between the years 1998 and 2002 are described by the demographics of the victims, types of incidents, the victims' occupations, and industries and location in which they worked. RESULTS: Motor vehicle- and machinery-related incidents accounted for nearly 33% and 14% of the incidents, respectively. Agriculture, forestry, fishing, hunting, and mining (n=87), and construction (n=83) had the most fatalities. Fatality rates per 100,000 workers for these industries were 25.7 and 8.7, respectively, compared to the state-wide average of 3.1 fatalities/100,000 workers. DISCUSSION: These data indicate numerous areas for prevention of work-related traumatic injuries and fatalities.     

Consumer-resource body-size relationships in natural food webs

It has been suggested that differences in body size between consumer and resource species may have important implications for interaction strengths, population dynamics, and eventually food web structure, function, and evolution. Still, the general distribution of consumer-'resource body-size ratios in real ecosystems, and whether they vary systematically among habitats or broad taxonomic groups, is poorly understood. Using a unique global database on consumer and resource body sizes, we show that the mean body-size ratios of aquatic herbivorous and detritivorous consumers are several orders of magnitude larger than those of carnivorous predators. Carnivorous predator-prey body-size ratios vary across different habitats and predator and prey types (invertebrates, ectotherm, and endotherm vertebrates). Predator-prey body-size ratios are on average significantly higher (1) in freshwater habitats than in marine or terrestrial habitats, (2) for vertebrate than for invertebrate predators, and (3) for invertebrate than for ectotherm vertebrate prey. If recent studies that relate body-size ratios to interaction strengths are general, our results suggest that mean consumer-resource interaction strengths may vary systematically across different habitat categories and consumer types.     

Trace metal content in inhalable particulate matter (PM<Subscript>2.5–10</Subscript> and PM<Subscript>2.5</Subscript>) collected from historical mine waste deposits using a laboratory-based approach

Mine wastes and tailings are considered hazardous to human health because of their potential to generate large quantities of highly toxic emissions of particulate matter (PM). Human exposure to As and other trace metals in PM may occur via inhalation of airborne particulates or through ingestion of contaminated dust. This study describes a laboratory-based method for extracting PM_2.5–10 (coarse) and PM_2.5 (fine) particles from As-rich mine waste samples collected from an historical gold mining region in regional, Victoria, Australia. We also report on the trace metal and metalloid content of the coarse and fine fraction, with an emphasis on As as an element of potential concern. Laser diffraction analysis showed that the proportions of coarse and fine particles in the bulk samples ranged between 3.4–26.6 and 0.6–7.6 %, respectively. Arsenic concentrations were greater in the fine fraction (1680–26,100 mg kg^?1) compared with the coarse fraction (1210–22,000 mg kg^?1), and Co, Fe, Mn, Ni, Sb and Zn were found to be present in the fine fraction at levels around twice those occurring in the coarse. These results are of particular concern given that fine particles can accumulate in the human respiratory system. Our study demonstrates that mine wastes may be an important source of metal-enriched PM for mining communities.     

Intercomparison of Satellite Remote Sensing‐Based Flood Inundation Mapping Techniques

The objective of this study was to determine the accuracy of five different digital image processing techniques to map flood inundation extent with Landsat 8–Operational Land Imager satellite imagery. The May 2016 flooding event in the Hempstead region of the Brazos River, Texas is used as a case study for this first comprehensive comparison of classification techniques of its kind. Five flood water classification techniques (i.e., supervised classification, unsupervised classification, delta‐cue change detection, Normalized Difference Water Index [NDWI], modified NDWI [MNDWI]) were implemented to characterize flooded regions. To identify flood water obscured by cloud cover, a digital elevation model (DEM)–based approach was employed. Classified floods were compared using an Advanced Fitness Index to a “reference flood map” created based on manual digitization, as well as other data sources, using the same satellite image. Supervised classification yielded the highest accuracy of 86.4%, while unsupervised, MNDWI, and NDWI closely followed at 79.6%, 77.3%, and 77.1%, respectively. Delta‐cue change detection yielded the lowest accuracy with 70.1%. Thus, supervised classification is recommended for flood water classification and inundation map generation under these settings. The DEM‐based approach used to identify cloud‐obscured flood water pixels was found reliable and easy to apply. It is therefore recommended for regions with relatively flat topography.