Biomedical subjects

George B Arhonditsis

Publications and source records attributed to George B Arhonditsis.

7 recordsLinked to original sources

PubMed2006

Evaluation of the current state of mechanistic aquatic biogeochemical modeling: citation analysis and future perspectives.

We examined the factors that determine the citations of 153 mechanistic aquatic biogeochemical modeling papers published from 1990 to 2002. Our analysis provides overwhelming evidence that ocean modeling is a dynamic area of the current modeling practice. Models developed to gain insight into the ocean carbon cycle/marine biogeochemistry are most highly cited, the produced knowledge is exported to other cognitive disciplines, and oceanic modelers are less reluctant to embrace technical advances (e.g., assimilation schemes) and more critically increase model complexity. Contrary to our predictions, model application for environmental management issues on a local scale seems to have languished; the pertinent papers comprise a smaller portion of the published modeling literature and receive lower citations. Given the critical planning information that these models aim to provide, we hypothesize that the latter finding probably stems from conceptual weaknesses, methodological omissions, and an evident lack of haste from modelers to adopt new ideas in their repertoire when addressing environmental management issues. We also highlight the lack of significant association between citation frequency and model complexity, model performance, implementation of conventional methodological steps during model development (e.g., validation, sensitivity analysis), number of authors, and country of affiliation. While these results cast doubt on the rationale of the current modeling practice, the fact that the Fasham et al. (1990) paper has received over 400 citations probably dictates what should be done from the modeling community to meet the practical need for attractive and powerful modeling tools.

Chemistry↗

PubMed2005

A daily time series analysis of stream water phosphorus concentrations along an urban to forest gradient.

During a 1-year period, we sampled stream water total phosphorus (TP) concentrations daily and soluble reactive phosphorus (SRP) concentrations weekly in four Seattle area streams spanning a gradient of forested to urban-dominated land cover. The objective of this study was to develop time series models describing stream water phosphorus concentration dependence on seasonal variation in stream base flows, short-term flow fluctuations, antecedent flow conditions, and rainfall. Stream water SRP concentrations varied on average by +/- 18% or +/- 5.7 microg/L from one week to another, whereas TP varied +/- 48% or +/- 32.5 microg/L from one week to another. On average, SRP constituted about 47% of TP. Stream water SRP concentrations followed a simple sine-wave annual cycle with high concentrations during the low-flow summer period and low concentrations during the high-flow winter period in three of the four study sites. These trends are probably due to seasonal variation in the relative contributions of groundwater and subsurface flows to stream flow. In forested Issaquah Creek, SRP concentrations were relatively constant throughout the year except during the fall, when a major salmon spawning run occurred in the stream and SRP concentrations increased markedly. Stream water SRP concentrations were statistically unrelated to short-term flow fluctuations, antecedent flow conditions, or rainfall in each of the study streams. Stream water TP concentrations are highly variable and strongly influenced by short-term flow fluctuations. Each of the processes assessed had statistically significant correlations with TP concentrations, with seasonal base flow being the strongest, followed by antecedent flow conditions, short-term flow fluctuations, and rainfall. Times series models for each individual stream were able to predict approximately 70% of the variability in the SRP annual cycle in three of the four streams (r2 = 0.57-0.81), whereas individual TP models explained approximately 50% of the annual cycle in all streams (r2 = 0.39-0.59). Overall, time series models for SRP and TP dynamics explained 82% and 76% of the variability for these variables, respectively. Our results indicate that SRP, the most biologically available and therefore most important phosphorus fraction, has simpler and easier-to-predict seasonal and weekly dynamics.

Animals↗

PubMed2005

Non-point-source impacts on stream nutrient concentrations along a forest to urban gradient.

We conducted statistical analyses of a 10-year record of stream nutrient and sediment concentrations for 17 streams in the greater Seattle region to determine the impact of urban non-point-source pollutants on stream water quality. These catchments are dominated by either urban (22-87%) or forest (6-73%) land cover, with no major nutrient point sources. Stream water phosphorus concentrations were moderately strongly (r2=0.58) correlated with catchment land-cover type, whereas nitrogen concentrations were weakly (r2=0.19) and nonsignificantly (at alpha<0.05) correlated with land cover. The most urban streams had, on average, 95% higher total phosphorus (TP) and 122% higher soluble reactive phosphorus (SRP) and 71% higher turbidity than the most forested streams. Nitrate (NO3), ammonium (NH4), and total suspended solids (TSS) concentrations did not vary significantly with land cover. These results suggest that urbanization markedly increased stream phosphorus concentrations and modestly increased nitrogen concentrations. However, nutrient concentrations in Seattle region urban streams are significantly less than those previously reported for agricultural area streams.

Cities↗

PubMed2004

Modeling the formation of chlorination by-products in river waters with different quality.

Water chlorination results in formation of a variety of organic compounds, known as chlorination by-products (CBPs), mainly trihalomethanes (THMs) and haloacetic acids (HAAs). Factors affecting their concentrations have been found to be organic matter content of water, pH, temperature, chlorine dose, contact time and bromide concentration, but the mechanisms of their formation are still under investigation. Within this scope, chlorination experiments have been conducted with river waters from Lesvos island, Greece, with different water quality regarding bromide concentration and organic matter content. The factors studied were pH, time and chlorine dose. The determination of CBPs was carried out by gas chromatography techniques. Statistical analysis of the results was focused on the development of multiple regression models for predicting the concentrations of total trihalomethanes and total HAAs based on the use of pH, reaction time and chlorine dose. The developed models, although providing satisfactory estimations of the concentrations of the CBPs, showed lower correlation coefficients than the multiple regression models developed for THMs only during previous study. It seems that the different water quality characteristics of the two river waters in the present study is responsible for this phenomenon. The results indicate that under these conditions the formation of THMs and HAAs in water has a more stochastic character, which is difficult to be described by the conventional regression techniques.

Bromides↗

PubMed2004

Patterns and mechanisms of phytoplankton variability in Lake Washington (USA).

Temporal variability in lake phytoplankton is controlled largely by a complex interplay between hydrodynamic and chemical factors, and food web interactions. We explored mechanisms underlying phytoplankton interannual variability in Lake Washington (USA), using a 25-yr time series of water quality data (1975-1999). Time-series analysis and PCA were used to decompose chlorophyll data into modes of variability. We found that phytoplankton dynamics in Lake Washington were characterized by four seasonal modes, each of which was associated with different ecological processes. The first mode coincided with the period when the system was light limited (January-March) and phytoplankton patterns were driven by the amount of available solar radiation. The second mode (April-June) coincided with the peak of the spring bloom and the subsequent decline of phytoplankton biomass, and was largely controlled by total phosphorus levels and grazing pressure from cladoceran zooplankton. Evidence of co-dependence and tight relationship between phytoplankton and cladoceran dynamics were also found from July to October when a large portion of the phosphorus supply in the mixed layer was provided by zooplankton excretion. The fourth mode (November-December) was associated with the transition to thermal and chemical homogeneity and the winter phytoplankton minima (2-2.5 microg/l). Finally, we examined the effects of meteorological forcing and large-scale oceanic climate fluctuations (ENSO and PDO) on phytoplankton dynamics and assessed the significance of their role on the interannual variability in the lake.

Animals↗

PubMed2002

Quantitative assessment of trihalomethane formation using simulations of reaction kinetics.

A modelling procedure with a time discretisation of 1 min is developed in order to study and simulate the kinetics of formation of total trihalomethanes (TTHM) in water treatment plants. This methodology was applied on two significant processing units of Athens (Galatsi Treatment Plant-GTP, Menidi Treatment Plant-MTP). The fundamental concept of the model was based on the representation of the water treatment plant as a mixed flow reactor, where the formation of TTHM was predicated on a generalised reaction of total halogens with an organic precursor. Differential rates of reactants and products were expressed in terms of the reaction stoichiometry. Volatilisation, flocculation, coagulation and sedimentation processes were also incorporated in the model in order to assess their distinct role. The most appropriate coefficient set was sought and it was found that a stoichiometric ratio of 0.5 for total halogen, 0.6 for organic substrate and 0.2 for TTHM (or 2.5:3:1) resulted in the best fit between simulated and experimental data. The present modelling approach should be considered as a promising methodological basis towards the realistic reproduction of the dynamics of water treatment plants and the development of reliable numerical tools for the accurate prediction of THM formation.

Disinfectants↗

PubMed2002

Multiple regression models: a methodology for evaluating trihalomethane concentrations in drinking water from raw water characteristics.

The presence of trihalomethanes (THMs) in drinking water has attracted the attention of both researchers and professionals, because of the harmful effects of these substances on human health. A multiple regression model was developed to estimate THM concentrations in finished drinking water, using data from the Menidi Treatment Plant of Athens. A number of routinely measured characteristics--including chlorine dose, chlorophyll a, temperature, pH and bromide--of raw water, were used to generate a reliable methodology for predicting both total THM and individual species concentrations. Seasonality effects were also considered during the analysis. In general, these models were found to give acceptable fits, estimating accurately lows and highs over the annual cycle.

Forecasting↗