Assessment of heavy metal enrichment in the offshore fine-grained sediments of the Caspian Sea

Sampling of the offshore seabed sediments of southwestern part of the Caspian Sea was carried out by gravity corer in order to study heavy metal concentration and the physicochemical factors controlling their distribution in the fine-grained fraction. The grain size distribution, amount, and type of clay minerals, total organic carbon (TOC) content, and Eh–pH of the sediments were determined. The average concentrations of the heavy metals in ppm are Mn (563), Cu (207.5), Sr (187), Zn (94), Pb (26.3), Ni (14.5), Co (11.5), Cd (2.56), and Ag (1.04) in their order of abundances. Co and Zn mostly indicate increase in silt-size fraction of the sediments suggesting their probable detrital provenance but the Mn, Ni, Cu, Sr, Pb, Cd, and Ag concentrations show a similar trend to distribution of the clay-size fraction. The concentrations of Mn, Co, and Cd increase with increase in the TOC content but the Cu, Pb, Ni, Ag, and Sr concentrations decrease with increase of the TOC content. The amounts of Zn, Cu, Sr, Pb, Cd, and Ag increase with increase in the CaCO₃ content. The calculated enrichment factor indicates that the sediments are very strong to extremely enriched in Ag, significantly enriched in Cu and Cd, and depleted to mineral for Pb, Sr, Co, Ni, and Zn. Variations of the Cu, Sr, Cd, Ag, and Pb concentrations are similar to the clay and CaCO₃ distributions.     

The use of sensory perception indicators for improving the characterization and modelling of total petroleum hydrocarbon (TPH) grade in soils

This paper proposes a multistep approach for creating a 3D stochastic model of total petroleum hydrocarbon (TPH) grade in potentially polluted soils of a deactivated oil storage site by using chemical analysis results as primary or hard data and classes of sensory perception variables as secondary or soft data. First, the statistical relationship between the sensory perception variables (e.g. colour, odour and oil–water reaction) and TPH grade is analysed, after which the sensory perception variable exhibiting the highest correlation is selected (oil–water reaction in this case study). The probabilities of cells belonging to classes of oil–water reaction are then estimated for the entire soil volume using indicator kriging. Next, local histograms of TPH grade for each grid cell are computed, combining the probabilities of belonging to a specific sensory perception indicator class and conditional to the simulated values of TPH grade. Finally, simulated images of TPH grade are generated by using the P-field simulation algorithm, utilising the local histograms of TPH grade for each grid cell. The set of simulated TPH values allows several calculations to be performed, such as average values, local uncertainties and the probability of the TPH grade of the soil exceeding a specific threshold value.     

An Approach to Reaeration Coefficient Modeling in Local Surface Water Quality Monitoring

Reaeration coefficient (k ₂) for River Atuwara, Ogun State, Nigeria was calculated from dissolved oxygen and biochemical oxygen demand data collected over period of 3 months covering the two prevailing climatic seasons in the country. Both the Akaike and Bayesian information criteria were used in the selection and analysis of ten models to identify the most suitable reaeration coefficient (k ₂) model for Atuwara River. Models that passed the confidence limit were subjected to model evaluation using measures of agreement between observed and predicted data such as percent bias, Nash–Sutcliffe efficiency, and root mean square observation standard deviation ratio. The used approach yield better results than empirical models developed for local conditions while it is also useful in conserving scarce resources.     

Effects of northeast monsoon on trace metal distribution in the South China Sea off Peninsular Malaysia

Concentrations of trace metals in the South China Sea (SCS) were determined off the coast of Terengganu during the months of May and November 2007. The concentrations of dissolved and particulate metals were in the range of 0.019–0.194 μg/L and 50–365 μg/g, respectively, for cadmium (Cd), 0.05–0.45 μg/L and 38–3,570 μg/g for chromium (Cr), 0.05–3.54 μg/L and 21–1,947 μg/g for manganese (Mn), and 0.03–0.49 μg/L and 2–56,982 μg/g for lead (Pb). The order of mean log K _D found was Cd?>?Cr?>?Pb?>?Mn. The study suggests that the primary sources of these metals are discharges from the rivers which drain into the SCS, in particular the Dungun River, which flows in close proximity to agricultural areas and petrochemical industries. During the northeast monsoon, levels of particulate metals in the bottom water samples near the shore were found to be much higher than during the dry season, the probable result of re-suspension of the metals from the bottom sediments.     

Assessing environmentally significant effects: a better strength-of-evidence than a single P value?

Interpreting a P value from a traditional nil hypothesis test as a strength-of-evidence for the existence of an environmentally important difference between two populations of continuous variables (e.g. a chemical concentration) has become commonplace. Yet, there is substantial literature, in many disciplines, that faults this practice. In particular, the hypothesis tested is virtually guaranteed to be false, with the result that P depends far too heavily on the number of samples collected (the ‘sample size’). The end result is a swinging burden-of-proof (permissive at low sample size but precautionary at large sample size). We propose that these tests be reinterpreted as direction detectors (as has been proposed by others, starting from 1960) and that the test’s procedure be performed simultaneously with two types of equivalence tests (one testing that the difference that does exist is contained within an interval of indifference, the other testing that it is beyond that interval—also known as bioequivalence testing). This gives rise to a strength-of-evidence procedure that lends itself to a simple confidence interval interpretation. It is accompanied by a strength-of-evidence matrix that has many desirable features: not only a strong/moderate/dubious/weak categorisation of the results, but also recommendations about the desirability of collecting further data to strengthen findings.     

Impact of rapid urbanisation and industrialisation on river sediment metal contamination

This study aimed at evidencing contaminant inputs from a rapidly growing population and the accompanying anthropogenic activities to river sediments. The Fez metropolitan area and its impacts on the Sebou's sediments (the main Moroccan river) were chosen as a case study. The Fez agglomeration is surrounded by the river Fez, receiving the wastewaters of this developing city and then flowing into the Sebou. The sediment cores from the Fez and Sebou Rivers were extracted and analysed for major elements, butyltins and toxic metals. Normalised enrichment factors and geoaccumulation index were calculated. Toxicity risk was assessed by two sets of sediment quality guideline (SQG) indices. A moderate level of contamination by butyltins was observed, with monobutyltin being the dominant species across all sites and depths. The lowest level of metal pollution was identified in the Sebou's sediments in upstream of Fez city, whilst the Fez' sediments were heavily polluted and exhibited bottom-up accumulation trends, which is a clear signature of recent inputs from the untreated wastewaters of Fez city. Consequently, the sediments of Fez and Sebou at the downstream of the confluence were found to be potentially toxic, according to the SQG levels. This finding is concerned with aquatic organisms, as well as to the riverside population, which is certainly exposed to these pollutants through the daily use of water. This study suggests that although Morocco has adopted environmental regulations aiming at restricting pollutant discharges into the natural ecosystems, such regulations are neither well respected by the main polluters nor efficiently enforced by the authorities.     

Microbial contamination of dental unit waterlines and effect on quality of indoor air

The microbiological quality in dental unit waterlines (DUWLs) is considered to be important because patients and dental staff with suppressed immune systems are regularly exposed to water and aerosols generated from dental units (DUs). Opportunistic pathogens like Pseudomonas, Legionella, Candida, and Aspergillus can be present in DUWLs, while during consultations, bioaerosols can be dispersed in the air, thus resulting in effects on microbiological quality of indoor air. This present study represents microbiological air and water quality in dental offices (DOs) and also concerns the relationship between the quality of DO air and dental unit water. This study aimed to assess both the microbial quality of dental unit water and the indoor air in 20 DOs and to survey the effect on the quality of the indoor air with the existing microorganisms in dental unit water. Fourteen out of 20 (70 %) DUWLs were found to be contaminated with a high number of aerobic mesophilic heterotrophic bacteria. In terms of bacterial air contamination levels, in 90 % of DOs, a medium level (<500 colony-forming units (CFU)/m³) of contamination was determined, while in terms of microfungal air contamination, in all DOs, a low level (<100 CFU/m³) of contamination was determined. Potential infection or allergen agents, such as Pseudomonas, Micrococcus, Staphylococcus, Alternaria, Cladosporium, Penicillium, Aspergillus, and Paecilomyces were isolated from water and air samples. This study’s determination of contamination sources and evaluation of microbial load in DOs could contribute to the development of quality control methods in the future.     

Using process-based models to filter out natural variability in observed concentrations of nitrogen and phosphorus in river water

Advances in process-based modelling of loads of nitrogen and phosphorus carried by rivers have created new possibilities to interpret time series of water quality data. We examined how model runs with constant anthropogenic forcing can be used to estimate and filter out weather-driven variation in observational data and, thereby, draw attention to other features of such data. An assessment of measured and modelled nutrient concentrations at the outlets of 45 Swedish rivers provided promising results for total nitrogen. In particular, joint analyses of observational data and outputs from the catchment model S-HYPE strengthened the evidence that downward trends in nitrogen were due to mitigation measures in agriculture. Evaluation of modelled and observed total phosphorus concentrations revealed considerable bias in the collection or chemical analysis of water samples and also identified weaknesses in the model outputs. Together, our results highlight the need for more efficient two-way communication between environmental modelling and monitoring.