Sampling techniques for the assessment of anthropogenic vapour and particulate mercury in the Brazilian Amazon atmosphere

A system, based on annular gold-coated denuders, was optimized and used in the atmospheric sampling of mercury in urban and rural sites of the Alta Floresta, a region in the Brazilian Amazon. Results showed that vapour phase mercury (Hgv) is dominant in samples collected in both sites. However, particulate mercury (Hg) may sometimes be significant at the urban site, with values representing up to 77% of the total Hg collected during sampling, but may also be insignificant at the same site, depending on the gold commercialization activity and, probably, on the meteorological conditions during the sampling period. The presence of mercury in both the vapour and particulate phases in the atmosphere of the urban site can explain the high mercury concentrations found in urban dust reported for some cities in the Amazon, and also the relatively high Hg concentrations found in soils adjacent to the urban centre of Alta Floresta. It appears that the urban dust of "garimpo" areas in the Amazon can act as an efficient adsorber of Hgv emitted by gold dealer operations during the purification process. Mercury emissions from gold dealer shops in the Amazon have been considered as a human health risk through the inhalation of Hg vapour. However, although true for indoor sites, the significant contribution of particulate phase Hg shown in this study in outdoor urban sites calls for a re-evaluation of the risk assessment estimates performed up to now in urban centres in the Amazon.     

Using slides to test for changes in crown defoliation assessment methods part II: Application of the image analysis system CROCO

We tested whether the semi-automatic program CROCO can replace visual assessments of slides to detect changes in defoliation assessment methods. We randomly selected a series of slides of 24 Norway spruce trees with 220 field assessments made between 1986 and 1995. The slides had been randomly arranged and assessed by three experts without knowledge of the tree number or the year when the slide was taken. Defoliation scores were computed with CROCO. Each tree had thus three different defoliation scores, field assessments, photo assessments and CROCO scores.CROCO scores were less correlated with the field assessments (Spearmans rank correlation: 0.67) than were the slide assessments with the field assessments (0.79–0.83). However, CROCO was not biased against the field scores, while slide assessments systematically underestimated defoliation.In a multi-variate mixed effect model none of the variables tree overlap, tree visibility and light conditions was significant in explaining differences between slide assessors and CROCO scores. The same model applied for the differences from the field scores yielded significant effects for poor light conditions (CROCO and all assessors), for crown overlap (CROCO and one assessor) and for visibility (one assessor). We conclude, therefore, that CROCO can be used to detect past and future changes in assessment methods without bias if poor quality photographs are avoided.     

The suitability of a single intertidal fish trap for the assessment of long-term trends in fish and epibenthic invertebrate populations

The suitability of a single intertidal fish trap for the assessment of long-term trends in fish and epibenthic invertebrate relies upon the assumption of an on-average constant sampling fraction from the study population. This assumption was examined by comparing trends over years in five different traps within the study area. For some species, like cod, the traps showed more or less parallel fluctuations. This is in agreement with the assumption. However, for other species, like mackerel, the assumption was invalidated by distinct trends over years.Publication no. 62 of the project Applied Scientific Research Netherlands Institute for Sea Research (BEWON)     

Monitoring and assessment of land use status by GIS

The objectives of this study were to assess land suitability andto monitor the spatial and temporal changes in land use types (LUTs)by using GIS. The study was conducted in an irrigated area of 920ha, located in the East Mediterranean region of Turkey. Archiveddata of LUTs were utilized. Data analysis was conducted by usingArcInfo and ArcView GIS softwares. The land characteristics werecompared with land requirements of present LUTs by taking intoaccount the land evaluation results. Three major soil series andtwelve different LUTs were identified. Corn and citrus were themost planted LUTs in the assessment period. Generated mapsdemonstrated how LUTs changed spatially and temporally. Most LUTswere clustered in certain areas indicating that farmer'sselection of LUTs was affected by their habits and neighbor'sbehavior. Land suitability assessment results indicated thatCanakci and Mursel soil series were found to be highly suitable forall LUTs while Arikli soil series was determined to be moderately suitablecitrus, vegetables and watermelon. Citrus plantationmaps overlaid on soil series maps demonstrated that the citrushas not been planted completely on suitable areas. Landsuitability assessment showed that citrus plantation in Arikliseries would result in 40% yield loss and 58% of land is notused at its potential.     

Signal-transfer modeling for regional assessment of forest responses to environmental changes in the southeastern United States

Stochastic transfer of information in a hierarchy of simulators is offered as a conceptual approach for assessing forest responses to changing climate and air quality across 13 southeastern states of the USA. This assessment approach combines geographic information system and Monte Carlo capabilities with several scales of computer modeling for southern pine species and eastern deciduous forests. Outputs, such as forest production, evapotranspiration and carbon pools, may be compared statistically for alternative equilibrium or transient scenarios providing a statistical basis for decision making in regional assessments. This revised version was published online in July 2006 with corrections to the Cover Date.     

Grain-size analysis of volcanic ash for the rapid assessment of respiratory health hazard

Volcanic ash has the potential to cause acute and chronic respiratory diseases if the particles are sufficiently fine to enter the respiratory system. Characterization of the grain-size distribution (GSD) of volcanic ash is, therefore, a critical first step in assessing its health hazard. Quantification of health-relevant size fractions is challenging without state-of-the-art technology, such as the laser diffractometer. Here, several methods for GSD characterization for health assessment are considered, the potential for low-cost measurements is investigated and the first database of health-pertinent GSD data is presented for a suite of ash samples from around the world. Methodologies for accurate measurement of the GSD of volcanic ash by laser diffraction are presented by experimental analysis of optimal refractive indices for different magmatic compositions. Techniques for representative sampling of small quantities of ash are also experimentally investigated. GSD results for health-pertinent fractions for a suite of 63 ash samples show that the fraction of respirable (<4 microm) material ranges from 0-17 vol%, with the variation reflecting factors such as the style of the eruption and the distance from the source. A strong correlation between the amount of <4 and <10 microm material is observed for all ash types. This relationship is stable at all distances from the volcano and with all eruption styles and can be applied to volcanic plume and ash fallout models. A weaker relationship between the <4 and <63 microm fractions provides a novel means of estimating the quantity of respirable material from data obtained by sieving.     

Analysis of spatio-temporal land cover changes for hydrological impact assessment within the Nyando River Basin of Kenya

The spatio-temporal changes in the land cover states of the Nyando Basin were investigated for auxiliary hydrological impact assessment. The predominant land cover types whose conversions could influence the hydrological response of the region were selected. Six Landsat images for 1973, 1986, and 2000 were processed to discern the changes based on a methodology that employs a hybrid of supervised and unsupervised classification schemes. The accuracy of the classifications were assessed using reference datasets processed in a GIS with the help of ground-based information obtained through participatory mapping techniques. To assess the possible hydrological effect of the detected changes during storm events, a physically based lumped approach for infiltration loss estimation was employed within five selected sub-basins. The results obtained indicated that forests in the basin declined by 20% while agricultural fields expanded by 16% during the entire period of study. Apparent from the land cover conversion matrices was that the majority of the forest decline was a consequence of agricultural expansion. The model results revealed decreased infiltration amounts by between 6% and 15%. The headwater regions with the vast deforestation were noted to be more vulnerable to the land cover change effects. Despite the haphazard land use patterns and uncertainties related to poor data quality for environmental monitoring and assessment, the study exposed the vast degradation and hence the need for sustainable land use planning for enhanced catchment management purposes.     

Multi-criteria decision analysis with probabilistic risk assessment for the management of contaminated ground water

Traditionally, environmental decision analysis in subsurface contamination scenarios is performed using cost–benefit analysis. In this paper, we discuss some of the limitations associated with cost–benefit analysis, especially its definition of risk, its definition of cost of risk, and its poor ability to communicate risk-related information. This paper presents an integrated approach for management of contaminated ground water resources using health risk assessment and economic analysis through a multi-criteria decision analysis framework. The methodology introduces several important concepts and definitions in decision analysis related to subsurface contamination. These are the trade-off between population risk and individual risk, the trade-off between the residual risk and the cost of risk reduction, and cost-effectiveness as a justification for remediation. The proposed decision analysis framework integrates probabilistic health risk assessment into a comprehensive, yet simple, cost-based multi-criteria decision analysis framework. The methodology focuses on developing decision criteria that provide insight into the common questions of the decision-maker that involve a number of remedial alternatives. The paper then explores three potential approaches for alternative ranking, a structured explicit decision analysis, a heuristic approach of importance of the order of criteria, and a fuzzy logic approach based on fuzzy dominance and similarity analysis. Using formal alternative ranking procedures, the methodology seeks to present a structured decision analysis framework that can be applied consistently across many different and complex remediation settings. A simple numerical example is presented to demonstrate the proposed methodology. The results showed the importance of using an integrated approach for decision-making considering both costs and risks. Future work should focus on the application of the methodology to a variety of complex field conditions to better evaluate the proposed methodology.     

Assessing the effects of land use changes on soil sensitivity to erosion in a highland ecosystem of semi-arid Turkey

There has been increasing concern in highlands of semiarid Turkey that conversion of these systems results in excessive soil erosion, ecosystem degradation, and loss of sustainable resources. An increasing rate of land use/cover changes especially in semiarid mountainous areas has resulted in important effects on physical and ecological processes, causing many regions to undergo accelerated environmental degradation in terms of soil erosion, mass movement and reservoir sedimentation. This paper, therefore, explores the impact of land use changes on land degradation in a linkage to the soil erodibility, RUSLE-K, in Cankiri–Indagi Mountain Pass, Turkey. The characterization of soil erodibility in this ecosystem is important from the standpoint of conserving fragile ecosystems and planning management practices. Five adjacent land uses (cropland, grassland, woodland, plantation, and recreational land) were selected for this research. Analysis of variance showed that soil properties and RUSLE-K statistically changed with land use changes and soils of the recreational land and cropland were more sensitive to water erosion than those of the woodland, grassland, and plantation. This was mainly due to the significant decreases in soil organic matter (SOM) and hydraulic conductivity (HC) in those lands. Additionally, soil samples randomly collected from the depths of 0–10 cm (D ₁) and 10–20 cm (D ₂) with irregular intervals in an area of 1,200 by 4,200 m sufficiently characterized not only the spatial distribution of soil organic matter (SOM), hydraulic conductivity (HC), clay (C), silt (Si), sand (S) and silt plus very fine sand (Si + VFS) but also the spatial distribution of RUSLE-K as an algebraically estimate of these parameters together with field assessment of soil structure to assess the dynamic relationships between soil properties and land use types. In this study, in order to perform the spatial analyses, the mean sampling intervals were 43, 50, 64, 78, 85 m for woodland, plantation, grassland, recreation, and cropland with the sample numbers of 56, 79, 72, 13, and 69, respectively, resulting in an average interval of 64 m for whole study area. Although nugget effect and nugget effect–sill ratio gave an idea about the sampling design adequacy, the better results are undoubtedly likely by both equi-probable spatial sampling and random sampling representative of all land uses.