Desorption of arsenic from drinking water distribution system solids

Previous work has shown that arsenic can accumulate in drinking water distribution system (DWDS) solids (Lytle et~al., 2004) when arsenic is present in the water. The release of arsenic back into the water through particulate transport and/or chemical release (e.g. desorption, dissolution) could result in elevated arsenic levels at the consumers' tap. The primary objective of this work was to examine the impact of pH and orthophosphate on the chemical release (i.e. desorption) of arsenic from nine DWDS solids collected from utilities located in the Midwest. Arsenic release comparisons were based on the examination of arsenic and other water quality parameters in leach water after contact with the solids over the course of 168~hours. Results showed that arsenic was released from solids and suggested that arsenic release was a result of desorption rather than dissolution. Arsenic release generally increased with increasing initial arsenic concentration in the solid and increasing pH levels (in the test range of 7 to 9). Finally, orthophosphate (3 and 5 mg PO₄/L) increased arsenic release at all pH values examined. Based on the study results, utilities with measurable levels of arsenic present in their water should be aware that some water quality changes can cause arsenic release in the DWDS potentially resulting in elevated levels at the consumer's tap.     

Coastal Flood Risk Analysis Using Landsat-7 ETM+ Imagery and SRTM DEM: A Case Study of Izmir, Turkey

The Intergovernmental Panel on Climate Change (IPCC) reports an acceleration of the global mean sea-level rise (MSLR) in the twentieth century in response to global climate change. If this acceleration remains constant, then some coastal areas are most likely to be inundated by the year 2100. The ability to identify the differential vulnerability of coastlines to future inundation hazards as result of global climate change is necessary for timely actions to be taken. Yildiz et al. (Journal of Mapping, 17, 1-75, 2003) reported that the local MSLR in the city of Izmir rose at a rate of 6.8 +/- 0.9 mm year(-1) between 1984 and 2002. In this study, the spatial distribution of the coastal inundation hazards of Izmir region was determined using not only land-use and land-cover (LULC) types derived from the maximum likelihood classification of Landsat-7 Enhanced Thematic Mapper Plus (ETM+) multi-spectral image set but also the classification of the digital elevation model (DEM) acquired by the shuttle radar topography mission (SRTM). Coastal areas with elevations of 2 and 5 m above mean sea-level vulnerable to inundation were found to cover 2.1 and 3.7% of the study region (6,107 km(2)), respectively. Our findings revealed that Menemen plain along Gediz river, and the settlements of Karsiyaka, Alacati, Aliaga, Candarli and Selcuk are at high risk in order of decreasing vulnerability to permanent and episodic inundation by 2100 under the high MSLR scenarios of 20 to 50 mm year(-1).     

Serial Correlation and Inter-annual Variability in Relation to the Statistical Power of Monitoring Schemes to Detect Trends in Fish Populations

We studied the effects of inter-annual variability and serial correlation on the statistical power of monitoring schemes to detect trends in biomass of bream (Abramis brama) in Lake Veluwemeer (The Netherlands). In order to distinguish between 'true' system variability and sampling variability we simulated the development of the bream population, using estimates for population structure and growth, and compared the resulting inter-annual variabilities and serial correlations with those from field data. In all cases the inter-annual variability in the field data was larger than in simulated data (e.g. for total biomass of all assessed bream sigma = 0.45 in field data, and sigma = 0.03-0.14 in simulated data) indicating that sampling variability decreased statistical power for detecting trends. Moreover, sampling variability obscured the inter-annual dependency (and thus the serial correlation) of biomass, which was expected because in this long-lived population biomass changes are buffered by the many year classes present. We did find the expected serial correlation in our simulation results and concluded that good survey data of long-lived fish populations should show low sampling variability and considerable inter-annual serial correlation. Since serial correlation decreases the power for detecting trends, this means that even when sampling variability would be greatly reduced, the number of sampling years to detect a change of 15%.year(-1) in bream populations (corresponding to a halving or doubling in a six-year period) would in most cases be more than six. This would imply that the six-year reporting periods that are required by the Water Framework Directive of the European Union are too short for the existing fish monitoring schemes.     

Distribution of PAHs in Surface Soils from Petroleum Handling Facilities in Calabar

The level of concentrations of polycyclic aromatic hydrocarbons (PAHs) in surface soils from petroleum handling facilities (kerosene tank, generating plant, petrol stations, mechanic workshops, leaking pipeline and air port fuel dump) from Calabar metropolis southeastern Nigeria was determined by gas chromatography/ mass spectrometry. The results show that total polycyclic aromatic hydrocarbons (PAHs) varied from 1.80 to 334.43 mg/kg with a mean of 50.31 mg/kg. The lowest value of 1.80 mg/kg was obtained from petrol station while the highest value of 334.43 mg/kg was obtained from facility characterised by petrol stations and mechanic workshops. The ratio of phenanthrene/anthracene and fluoranthene/pyrene, varied from 0.43 to 27.72 and from 0.14 to 17.76 respectively. These ratios indicate various sources for the PAH. The two to three ring PAHs are the most abundant. Based on the PAH ratios and content alone it is not possible to distinguish between contribution from motor vehicle exhaust, gasoline spillage, used engine oil or petroleum production. However, considering the area of the study, it is very likely that the major source of soil contamination is originating from petroleum product.     

The Distribution and Sources of Polycyclic Aromatic Hydrocarbons in Surface Sediments Along the Egyptian Mediterranean Coast

Coastal marine sediment samples were collected from 31 sampling stations along the Egyptian Mediterranean Sea coast. All sediment samples were analyzed to determine aliphatic and polycyclic aromatic hydrocarbons (PAHs) as well as total organic carbon (TOC) contents and grain size analysis. Total concentrations of 16 EPA-PAHs in the sediments were varied from 88 to 6338 ng g⁻¹ with an average value of 154 ng g⁻¹ (dry weight). However, the concentrations of total aliphatic were varied from 1.3 to 69.9 ng g⁻¹ with an average value of 15.6 ng g⁻¹ (dry weight). The highest contents of PAHs were found in the Eastern harbor (6338 ng g⁻¹), Manzala (5206 ng g⁻¹) and El-Jamil East (4895 ng g⁻¹) locations. Good correlations observed between a certain numbers of PAH concentrations allowed to identify its origin. The average total organic carbon (TOC) percent was varied from 0.91 to 4.54%. Higher concentration of total pyrolytic hydrocarbons (∑COMB) than total fossil hydrocarbons (∑PHE) declared that atmospheric fall-out is the significant source of PAHs to marine sediments of the Egyptian Mediterranean coast. The selected marked compounds, a principal component analysis (PCA) and special PAHs compound ratios (phenanthrene/anthracene vs fluoranthene/pyrene; ∑COMB/∑EPA-PAHs) suggest the pyrogenic origins, especially traffic exhausts, are the dominant sources of PAHs in most locations. Interferences of rather petrogenic and pyrolytic PAH contaminations were noticed in the harbors due to petroleum products deliveries and fuel combustion emissions from the ships staying alongside the quays.     

A Procedure for NEPA Assessment of Selenium Hazards Associated With Mining

This paper gives step-by-step instructions for assessing aquatic selenium hazards associated with mining. The procedure was developed to provide the U.S. Forest Service with a proactive capability for determining the risk of selenium pollution when it reviews mine permit applications in accordance with the National Environmental Policy Act (NEPA). The procedural framework is constructed in a decision-tree format in order to guide users through the various steps, provide a logical sequence for completing individual tasks, and identify key decision points. There are five major components designed to gather information on operational parameters of the proposed mine as well as key aspects of the physical, chemical, and biological environment surrounding it — geological assessment, mine operation assessment, hydrological assessment, biological assessment, and hazard assessment. Validation tests conducted at three mines where selenium pollution has occurred confirmed that the procedure will accurately predict ecological risks. In each case, it correctly identified and quantified selenium hazard, and indicated the steps needed to reduce this hazard to an acceptable level. By utilizing the procedure, NEPA workers can be confident in their ability to understand the risk of aquatic selenium pollution and take appropriate action. Although the procedure was developed for the Forest Service it should also be useful to other federal land management agencies that conduct NEPA assessments, as well as regulatory agencies responsible for issuing coal mining permits under the authority of the Surface Mining Control and Reclamation Act (SMCRA) and associated Section 401 water quality certification under the Clean Water Act. Mining companies will also benefit from the application of this procedure because priority selenium sources can be identified in relation to specific mine operating parameters. The procedure will reveal the point(s) at which there is a need to modify operating conditions to meet environmental quality goals. By recognizing concerns early in the NEPA process, it may be possible for a mining company to match operational parameters with environmental requirements, thereby increasing the likelihood that the permit application will be approved.     

Using Spatial Pattern to Quantify Relationship Between Samples, Surroundings, and Populations

The need for accurate carbon budgeting, climate change modelling, and sustainable resource management has lead to an increase in the number of large area forest monitoring programs. Large area forest monitoring programs often utilize field and remotely sensed data sources. Sampling, via field or photo plots, enables the collection of data with the desired level of categorical detail in a timely and efficient manner. When sampling, the aim is to collect representative detailed data enabling the statistical reporting upon the characteristics of larger areas. As a consequence, approaches for investigating how well sample data represent larger areas (i.e., the sample neighbourhood and the population) are desired. Presented in this communication is a quantitative approach for assessing the nature of sampled areas in relation to surrounding areas and the overall population of interest. Classified Landsat data is converted to forest/non-forest categories to provide a consistent and uniform data set over a 130,000 km² study region in central British Columbia, Canada. From this larger study area 322 2 × 2 km photo plots on a 20 × 20 km systematic grid are populated with composition and configuration information for comparison to non-sampled areas. Results indicate that typically, within the study area, the spatial pattern of forest within a photo plot is representative of the forest patterns found within primary and secondary neighbourhoods and over the entire population of the study. These methods have implications for understanding the nature of data used in monitoring programs worldwide. The ability to audit photo and field plot information promotes an increased understanding of the results developed from sampling and provides tools identifying locations of possible bias.     

Size and composition distributions of particulate matter emissions: part 1--light-duty gasoline vehicles

Size-resolved particulate matter (PM) emitted from light-duty gasoline vehicles (LDGVs) was characterized using filter-based samplers, cascade impactors, and scanning mobility particle size measurements in the summer 2002. Thirty LDGVs, with different engine and emissions control technologies (model years 1965-2003; odometer readings 1264-207,104 mi), were tested on a chassis dynamometer using the federal test procedure (FTP), the unified cycle (UC), and the correction cycle (CC). LDGV PM emissions were strongly correlated with vehicle age and emissions control technology. The oldest models had average ultrafine PM0.1 (0.056- to 0.1-microm aerodynamic diameter) and fine PM1.8 (< or =1.8-microm aerodynamic diameter) emission rates of 9.6 mg/km and 213 mg/km, respectively. The newest vehicles had PM0.1 and PM1.8 emissions of 51 microg/km and 371 microg/km, respectively. Light duty trucks and sport utility vehicles had PM0.1 and PM1.8 emissions nearly double the corresponding emission rates from passenger cars. Higher PM emissions were associated with cold starts and hard accelerations. The FTP driving cycle produced the lowest emissions, followed by the UC and the CC. PM mass distributions peaked between 0.1- and 0.18-microm particle diameter for all vehicles except those emitting visible smoke, which peaked between 0.18 and 0.32 microm. The majority of the PM was composed of carbonaceous material, with only trace amounts of water-soluble ions. Elemental carbon (EC) and organic matter (OM) had similar size distributions, but the EC/OM ratio in LDGV exhaust particles was a strong function of the adopted emissions control technology and of vehicle maintenance. Exhaust from LDGV classes with lower PM emissions generally had higher EC/OM ratios. LDGVs adopting newer technologies were characterized by the highest EC/OM ratios, whereas OM dominated PM emissions from older vehicles. Driving cycles with cold starts and hard accelerations produced higher EC/OM ratios in ultrafine particles.     

Ambient Aerosol and its Carbon Content in Gainesville, a Mid-Scale City in Florida

Ambient aerosols were collected during 2000–2001 in Gainesville, Florida, using a micro-orifice uniform deposit impactor (MOUDI) to study mass size distribution and carbon composition. A bimodal mass distribution was found in every sample with major peaks for aerosols ranging from 0.32 to 0.56 μm, and 3.2 to 5.6 μm in diameter. The two distributions represent the fine mode (<2.5 μm) and the coarse mode (>2.5 μm) of particle size. Averaged over all sites and seasons, coarse particles consisted of 15% carbon while fine particles consisted of 22% carbon. Considerable variation was noted between winter and summer seasons. Smoke from fireplaces in winter appeared to be an important factor for the carbon, especially the elemental carbon contribution. In summer, organic carbon was more abundant. The maximum secondary organic carbon was also found in this season (7.0 μg m⁻³), and the concentration is between those observed in urban areas (15–20 μg m⁻³) and in rural areas (4–5 μg m⁻³). However, unlike in large cities where photochemical activity of anthropogenic emissions are determinants of carbon composition, biogenic sources were likely the key factor in Gainesville. Other critical factors that affect the distribution, shape and concentration were precipitation, brushfire and wind.     

Pesticide Residues in Bovine Milk from a Predominantly Agricultural State of Haryana, India

One hundred forty seven samples of bovine milk were collected from 14 districts of Haryana, India during December 1998–February 1999 and analysed for the presence of organochlorine pesticide (OCPs) residues. ∑HCH, ∑DDT, ∑endosulfan and aldrin were detected in 100%, 97%, 43% and 12% samples and with mean values of 0.0292, 0.0367, 0.0022 and 0.0036 μg/ml, respectively. Eight percent samples exceeded the maximum residue limit (MRL) of 0.10 mg/kg as recommended by WHO for ∑HCH, 4% samples of 0.05 mg/kg for α-HCH, 5% samples of 0.01 mg/kg for γ-HCH, 26% samples of 0.02 mg/kg for β-HCH as recommended by PFAA and 24% samples of 0.05 mg/kg as recommended by FAO for ∑DDT. Concentrations of β-HCH and p,p′-DDE were more as compared to other isomers and metabolites of HCH and DDT.