Workplace aerosol mass concentration measurement using optical particle counters

Direct-reading aerosol measurement usually uses the optical properties of airborne particles to detect and measure particle concentration. In the case of occupational hygiene, mass concentration measurement is often required. Two aerosol monitoring methods are based on the principle of light scattering: optical particle counting (OPC) and photometry. The former analyses the light scattered by a single particle, the latter by a cloud of particles. Both methods need calibration to transform the quantity of scattered light detected into particle concentration. Photometers are simpler to use and can be directly calibrated to measure mass concentration. However, their response varies not only with aerosol concentration but also with particle size distribution, which frequently contributes to biased measurement. Optical particle counters directly measure the particle number concentration and particle size that allows assessment of the particle mass provided the particles are spherical and of known density. An integrating algorithm is used to calculate the mass concentration of any conventional health-related aerosol fraction. The concentrations calculated thus have been compared with simultaneous measurements by conventional gravimetric sampling to check the possibility of field OPC calibration with real workplace aerosols with a view to further monitoring particle mass concentration. Aerosol concentrations were measured in the food industry using the OPC GRIMM? 1.108 and the CIP 10-Inhalable and CIP 10-Respirable (ARELCO?) aerosol samplers while meat sausages were being brushed and coated with calcium carbonate. Previously, the original OPC inlet had been adapted to sample inhalable aerosol. A mixed aerosol of calcium carbonate and fungi spores was present in the workplace. The OPC particle-size distribution and an estimated average particle density of both aerosol components were used to calculate the mass concentration. The inhalable and respirable aerosol fractions calculated from the OPC data are closely correlated with the results of the particle size-selective sampling using the CIP 10. Furthermore, the OPC data allow calculation of the thoracic fraction of workplace aerosol (not measured by sampling), which is interesting in the presence of allergenic particles like fungi spores. The results also show that the modified COP inlet adequately samples inhalable aerosol in the range of workplace particle-size distribution.     

Lead traceability along soil-melliferous flora-bee family-apiary products chain

Indirect measures were considered to study the lead transfer along the soil-melliferous flora-bee family-apiary products food chain. The concentrations of total and bioavailable lead in the soil were first investigated. Next, the lead level in different organs of melliferous flora and subsequently in the bee family and apiary products was measured. The results indicate a decrease in contamination as follows: honeybees > drones > propolis > wax > bee larvae > honey > royal jelly. The statistical analysis highlights the "lead pollution bioindicator" role of honeybees, honey and propolis. The risk factor parameter allows the prediction of the most impacted month and the least impacted of the melliferous season.     

Spatial modelling of the probability of obtaining a detectable concentration of ammonia in Moreton Bay, Australia

Ammonia is an important water quality variable, which in excess, can be detrimental to waterways and their ecosystems. In the Ecosystem Health Monitoring Program in South-east Queensland ammonia is monitored monthly, however, often more than 50% of the ammonia observations in Moreton Bay are below detection limit, making it difficult to draw useful inferences. In this paper a clipped Gaussian random field is used to spatially model and map the probability of detectable concentration of ammonia. The methodology is applied to the Moreton Bay samples collected in February 2005. The results suggest that for this month the oceanic impacted areas have higher probability of detectable ammonia concentration than the areas closer to the main sources of anthropogenic inputs.     

Selecting Variables for Habitat Suitability of <Emphasis Type="Italic">Asellus</Emphasis> (Crustacea,Isopoda) by Applying Input Variable Contribution Methods to Artificial Neural Network Models

This study aimed to compare different methods to analyse the contribution of individual river characteristics to predict the abundance of Asellus (Crustacea, Isopoda). Six methods which provide the relative contribution and/or the contribution profile of the input variables of artificial neural network models were therefore compared: (1) the ‘partial derivatives’ method; (2) the ‘weights’ method; (3) the ‘perturb’ method; (4) the ‘profile’ method; (5) the ‘classical stepwise’ method; (6) the ‘improved stepwise’ method. Consequently, the key variables which affect the habitat preferences of Asellus could be identified. To evaluate the performance of the artificial neural network model, the model predictions were compared with the results of a multiple linear regression analysis. The dataset consisted of 179 samples, collected over a 3-year period in the Zwalm catchment in Flanders, Belgium. Twenty-four environmental variables as well as the log-transformed abundance of Asellus were used in this study. The different contribution methods seemed to give similar results concerning the order of importance of the input variables. Nevertheless, their diverse computation led to differences in sensitivity and stability of the methods and the derived outcomes on the habitat preferences. From an ecological point of view, the environmental variables describing the stream type (width, depth, stream order and distance to mouth) were the most significant variables for Asellus in the Zwalm catchment during the period 2000–2002 for all applied methods. Indirectly, one can conclude that the water quality is not the limiting factor for the survival of Asellus in the Zwalm catchment.     

Mapping afforestation and deforestation from 1974 to 2012 using Landsat time-series stacks in Yulin District, a key region of the Three-North Shelter region, China

The Three-North Shelter Forest Program is the largest afforestation reconstruction project in the world. Remote sensing is a crucial tool to map land use and land cover change, but it is still challenging to accurately quantify the change in forest extent from time-series satellite images. In this paper, 30 Landsat MSS/TM/ETM+ epochs from 1974 to 2012 were collected, and the high-quality ground surface reflectance (GSR) time-series images were processed by integrating the 6S atmosphere transfer model and a relative reflectance normalization algorithm. Subsequently, we developed a vegetation change tracking method to reconstruct the forest change history (afforestation and deforestation) from the time-series Landsat GSR images based on the integrated forest z-score (IFZ) model by Huang et al. (2009a), which was improved by multi-phenological IFZ models and the smoothing processing of IFZ data for afforestation mapping. The mapping result showed a large increase in the extent of forest, from 380,394 ha (14.8 % of total district area) in 1974 to 1,128,380 ha (43.9 %) in 2010. Finally, the land cover and forest change map was validated with an overall accuracy of 89.1 % and a kappa coefficient of 0.858. The forest change time was also successfully retrieved, with 22.2 % and 86.5 % of the change pixels attributed to the correct epoch and within three epochs, respectively. The results confirmed a great achievement of the ecological revegetation projects in Yulin district over the last 40 years and also illustrated the potential of the time-series of Landsat images for detecting forest changes and estimating tree age for the artificial forest in a semi-arid zone strongly influenced by human activities.     

Temporal and spatial variations of nutrients in the Ten Mile Creek of South Florida, USA and effects on phytoplankton biomass

Water quality throughout south Florida has been a major concern for many years. Nutrient enrichment in the Indian River Lagoon (IRL) is a major surface water issue and is suggested as a possible cause of symptoms of ecological degradation. In 2005-06, water samples were collected weekly from seven sites along Ten Mile Creek (TMC), which drains into the Indian River Lagoon, to investigate and analyze spatial and temporal fluctuations of nutrients nitrogen (N) and phosphorus (P). The objective of this study was to understand the relationships among chlorophyll a concentration, nutrient enrichment and hydrological parameters in the surface water body.High median concentrations of total P (TP, 0.272 mg L(-1)), PO4-P (0.122 mg L(-1)), and dissolved total P (DTP, 0.179 mg L(-1)); and total N (TN, 0.988 mg L(-1)), NO3(-)-N (0.104 mg L(-1)), NH4+-N (0.103 mg L(-1)), and total Kjeldahl N (TKN, 0.829 mg L(-1)), were measured in TMC. The concentrations of TP, PO4-P, DTP, TN, NO3(-)-N, NH4+-N, and TKN were higher in summer and fall than in winter and spring. However, chlorophyll a and pheophytin concentrations during this period in TMC varied in the range of 0.000-60.7 and 0.000-17.4 microg L(-1), with their median values of 3.54 and 3.02 microg L(-1), respectively. The greatest mean chlorophyll a (10.3 microg L(-1)) and pheophytin (5.71 microg L(-1)) concentrations occurred in spring, while the lowest chlorophyll a (1.49 microg L(-1)) and pheophytin (1.97 mug L(-1)) in fall. High concentrations of PO4-P (>0.16 mg L(-1)), DTP (>0.24 mg L(-1)), NO3(-)-N (>0.15 mg L(-1)), NH4+-N (>0.12 mg L(-1)), and TKN (>0.96 mg L(-1)), occurred in the upstream of TMC, while high concentrations of chlorophyll a (>6.8 mug L(-l)) and pheophytin (>3.9 microg L(-l)) were detected in the downstream of TMC. The highest chlorophyll a (11.8 mug L(-l)) and pheophytin (6.06 microg L(-l)) concentrations, however, were associated with static and open water conditions. Hydrological parameters (total dissolved solid, electrical conductivity, salinity, pH, and water temperature) were positively correlated with chlorophyll a and pheophytin concentrations (P < 0.01) and these factors overshadowed the relationships between N and P concentrations and chlorophyll a under field conditions. Principal component analysis and the ratios of DIN/DP and TN/TP in the water suggest that N is the limiting nutrient factor for phytoplankton growth in the TMC and elevated N relative to P is beneficial to the growth of phytoplankton, which is supported by laboratory culture experiments under controlled conditions.     

Magnesium hydroxide bulk and colloid-associated 152Eu in an alkaline environment: colloid characterisation and sorption properties in the presence and absence of carbonate

The distribution of 152Eu between magnesium hydroxide bulk, colloids and solution has been assessed under alkaline conditions, such as those in nuclear fuel storage ponds. The colloidal phase has been characterised by two complementary methods: coupled ultrafiltration-ICP-AES and scanning electron microscopy. The quantity and the size distribution of the colloidal phase is strongly ionic strength-dependent. A decrease of the quantity of colloids, in particular the larger size ranges, has been observed with increasing ionic strength. Small colloids (1 kDa-10 kDa fraction) are predominant at all ionic strengths. The morphology of colloids, observed by field-emission gun scanning electron microscopy, appears to change from hexagonal prismatic (characteristic to the mineral) to spherical (energetically more favourable) as size decreases. The distribution of 152Eu between the solid and liquid/colloidal phases has been investigated at carbonate concentrations ranging from 0 to 10(-2) M by coupled ultrafiltration and gamma-spectrometry. Mg(OH)2 bulk appears to be a very strong sorbent for 152Eu, since complete sorption onto the bulk happens for carbonate concentrations as high as 10(-3) M. Scavenging of 152Eu by Mg(OH)2 colloids is negligible in the presence of Mg(OH)2 bulk. The distribution of 152Eu between liquid and colloidal phases has been investigated in the absence of bulk at various carbonate concentrations. A significant uptake of 152Eu by the colloids in solution has been observed, which decreases with increasing carbonate concentration. 152Eu appears to be mainly associated to the smallest colloids (1 kDa-10 kDa fraction). There is a strong correlation between the sorption properties and the surface area of the colloids.     

Development and Parameterization of a Rain- and Fire-driven Model for Exploring Elephant Effects in African Savannas

We describe the development and parameterization of a grid-based model of African savanna vegetation processes. The model was developed with the objective of exploring elephant effects on the diversity of savanna species and structure, and in this formulation concentrates on the relative cover of grass and woody plants, the vertical structure of the woody plant community, and the distribution of these over space. Grid cells are linked by seed dispersal and fire, and environmental variability is included in the form of stochastic rainfall and fire events. The model was parameterized from an extensive review of the African savanna literature; when available, parameter values varied widely. The most plausible set of parameters produced long-term coexistence between woody plants and grass, with the tree–grass balance being more sensitive to changes in parameters influencing demographic processes and drought incidence and response, while less sensitive to fire regime. There was considerable diversity in the woody structure of savanna systems within the range of uncertainty in tree growth rate parameters. Thus, given the paucity of height growth data regarding woody plant species in southern African savannas, managers of natural areas should be cognizant of different tree species growth and damage response attributes when considering whether to act on perceived elephant threats to vegetation.