DRY AND WET WEATHER FLOW NUTRIENT LOADS FROM A LOS ANGELES WATERSHED1

Effective watershed management requires an accurate assessment of the pollutant loads from the associated point and nonpoint sources. The importance of wet weather flow (WWF) pollutant loads is well known, but in semi‐arid regions where urbanization is significant the pollutant load in dry weather flow (DWF) may also be important. This research compares the relative contributions of potential contaminants discharged in DWF and WWF from the Ballona Creek Watershed in Los Angeles, California. Models to predict DWF and WWF loads of total suspended solids, biochemical oxygen demand, nitrate‐nitrogen, nitrite‐nitrogen, ammonia‐nitrogen, total Kjeldahl nitrogen, and total phosphorus from the Ballona Creek Watershed for six water years dating from 1991 to 1996 were developed. The contaminants studied were selected based on data availability and their potential importance in the degradation of Ballona Creek and Santa Monica Bay beneficial uses. Wet weather flow was found to contribute approximately 75 percent to 90 percent of the total annual flow volume discharged by the Ballona Creek Watershed. Pollutant loads are also predominantly due to WWF, but during the dry season, DWF is a more significant contributor. Wet weather flow accounts for 67 to 98 percent of the annual load of the constituents studied. During the dry season, however, the portion attributable to DWF increases to greater than 40 percent for all constituents except biochemical oxygen demand and total suspended solids. When individual catchments within the watershed are considered, the DWF pollutant load from the largest catchment is similar to the WWF pollutant load in two other major catchments. This research indicates WWF is the most significant source of nonpoint source pollution load on an annual basis, but management of the effects of the nonpoint source pollutant load should consider the seasonal importance of DWF.     

Long-term microphytoplankton variability patterns using multivariate analyses: ecological and management implications

Microphytoplankton data along the southern Tunisian coasts have been monitored weekly since 1995. This study used the data collected during the period 2000–2007 to determine the temporal variability patterns and to characterize the geographical structures of microphytoplankton populations. The methodological approach consisted in isolating the temporal variability common to all sampled sites and in analyzing the “residual” site-specific component. Multivariate ordination methods were used to determine the seasonal and interannual variability. The temporal pattern shared by all sites was highlighted and the seasonal cycle of the most frequent phytoplankton communities contrasted the diatoms winter-spring species to the dinoflagellates summer-fall species. Multitable comparison allowed the identification of three areas exhibiting similar phytoplankton population variability. The results, despite the coastal location of sampling sites, indicated that hydrodynamic and geomorphologic properties of the different areas as well as anthropogenic activities play a key role in the structure of the phytoplankton communities.     

Assessment of irrigation system sustainability using the Theil–Sen estimator of slope of time series

Agriculture, especially the irrigated sector, is the mainstay of Sudan’s economy as it accounts for 40 % of gross domestic product (GDP) and employs 70 % of the workforce. The economic viability of irrigated schemes is dependent on three factors: crop yield, water management and cropped area. The research question of this study was whether or not the current status of these factors can be sustained in order to maintain the economic viability of irrigation systems? To answer this question, a new (to the best of the author’s knowledge) approach was developed based on time series analysis, and on the Theil–Sen estimator of slope. The study defined sustainability conceptually as “the ability of an irrigation system to sustain crop yields using the optimum cropped area and water consumption to realize the economic viability of the irrigation system without a decline in soil quality and environment”. Time series datasets of crop yields, cropped area and irrigation water consumption are collected routinely by statistical departments. Any abrupt years in the development of trends were detected and related to their driving forces/causes, of which climatic conditions and marketing policies were found to be the most important. The simple approach developed proved its suitability for quantifying the progress of irrigated schemes’ towards sustainability development as tested under the conditions of Gezira irrigated scheme in Sudan—the largest singly managed irrigation scheme in the world. The scheme was found to be sustainable under the condition that the crop yield is considered as the top priority; otherwise, the sustainability of the scheme is jeopardized.     

Seaweeds as bioindicators of heavy metals off a hot spot area on the Egyptian Mediterranean Coast during 2008–2010

Concentrations of Cu, Zn, Cd, Pb, Ni, Co, Fe, Mn, and Hg were measured successively in water, sediments, and six macroalgal species belonging to three algal classes during 3 years (2008–2010) from Abu Qir Bay, Alexandria, Egypt: Chlorophyceae (Enteromorpha compressa, Ulva fasciata), Phaeophyceae (Padina boryana), and Rhodophyceae (Jania rubens, Hypnea musciformis, Pterocladia capillacea). The study aimed to assess the bioaccumulation potential of the seaweeds, as well as to evaluate the extent of heavy metal contamination in the selected study site. Metals were analyzed using atomic absorption spectrophotometry coupled with MH-10 hydride system. The obtained data showed that the highest mean concentrations of Cu, Zn, Fe, and Mn were recorded in E. compressa; Cd, Ni, and Hg exhibited their highest mean concentrations in P. boryana, while Pb and Co were found in J. rubens. Abundance of the heavy metals in the algal species was as follow: Fe?>?Mn?>?Zn?>?Pb?>?Ni?>?Co?>?Cu?>?Cd?>?Hg. E. compressa showed the maximum metal pollution index (MPI) which was 11.55. Bioconcentration factor (BCF) for the metals in algae was relatively high with a maximum value for Mn. The Tomlinson pollution load index (PLI) values for the recorded algal species were low, which ranged between 1.00 in P. boryana and 2.72 in E. compressa. Enrichment factors for sediments were low fluctuating between 0.43 for Hg to 2.33 for Mn. Accordingly, the green alga E. compressa, brown alga P. boryana, and red alga J. rubens can be nominated as bioindicators. Based on MPI and PLI indices, Abu Qir Bay in the present study is considered as low-contaminated area.     

Combined Municipal Solid Waste and biomass system optimization for district energy applications

Municipal Solid Waste (MSW) disposal has been a controversial issue in many countries over the past years, due to disagreement among the various stakeholders on the waste management policies and technologies to be adopted. One of the ways of treating/disposing MSW is energy recovery, as waste is considered to contain a considerable amount of bio-waste and therefore can lead to renewable energy production. The overall efficiency can be very high in the cases of co-generation or tri-generation. In this paper a model is presented, aiming to support decision makers in issues relating to Municipal Solid Waste energy recovery. The idea of using more fuel sources, including MSW and agricultural residue biomass that may exist in a rural area, is explored. The model aims at optimizing the system specifications, such as the capacity of the base-load Waste-to-Energy facility, the capacity of the peak-load biomass boiler and the location of the facility. Furthermore, it defines the quantity of each potential fuel source that should be used annually, in order to maximize the financial yield of the investment. The results of an energy tri-generation case study application at a rural area of Greece, using mixed MSW and biomass, indicate positive financial yield of investment. In addition, a sensitivity analysis is performed on the effect of the most important parameters of the model on the optimum solution, pinpointing the parameters of interest rate, investment cost and heating oil price, as those requiring the attention of the decision makers. Finally, the sensitivity analysis is enhanced by a stochastic analysis to determine the effect of the volatility of parameters on the robustness of the model and the solution obtained.     

Application of activated M/ZnO (M = Mn,Co, Ni,Cu, Ag) in photocatalytic degradation of diazo textile coloring dye

Activated ZnO powder has been prepared by procedures involving first its dissolution in nitric acid, then simultaneous treatment by adding NH₄OH and CO₂ bubbling leading to precipitation as Zn(OH)CO₃ (ZH) and further thermal decomposition of ZH at 400 °C. The gas evolution leads to formation of pores and increase in the specific surface area. Chemically activated M/ZnO powders doped with Mn, Co, Ni, Cu, and Ag have been obtained by the impregnation method. The samples have been characterized by ultraviolet-visible (UV-Vis) spectroscopy, diffuse reflectance (DR) UV-Vis, X-ray diffraction (XRD), single point Brunauer–Emmet–Teller (BET), scanning electron microscope (SEM), and X-ray photoelectron spectroscopy (XPS) methods. The experiments have shown that metal-doped activated ZnO powders possess higher photocatalytic activities in oxidative discoloration of model contaminant textile coloring dye Reactive Black 5 in slurry reactor compared to that of the pure ZnO. The XRD and XPS data have shown the presence of defects, nonstoichiometricity implying the formation of solid solutions. Copper-doped (1.5 wt%) activated ZnO (Cu²⁺ replaces Zn²⁺) is outstanding in its photocatalytic performance in discoloration of the dye due to the higher specific surface area and improved charge carrier separation.     

Rainwater toxicity and contamination study from São Paulo Metropolitan Region, Brazil

Wet deposition is an important process that removes pollutants from the atmosphere and transfers them to waters and soil. The goal of this study was to assess the biological effects of the atmospheric contamination of rainwater in the metropolitan area of São Paulo (MASP) using Daphnia similis, Ceriodaphnia dubia, and Vibrio fischeri. Experimental assays were carried out according to standard toxicity methodology. Twenty-three rainwater samples were collected from October 2007 to December 2008, at the Nuclear Research Institute (IPEN), in MASP. Major ions were determined by ionic chromatography, which showed NH₄ ⁺ and NO₃ ^? as prevalent ions. Ecotoxicological results confirmed toxic potential of rainwater, as all samples were toxic to D. similis and C. dubia. The V. fischeri luminescence reduction confirmed those negative effects of rainwater and percentage inhibition of relative luminescence ranged from 0.2 to 0.9 for 16 samples. Worse conditions were observed during the rainy season, suggesting convective rains are more effective in transferring contaminants and toxicity from atmosphere to surface.     

Implications of different population model structures for management of threatened plants

Population viability analysis (PVA) is a reliable tool for ranking management options for a range of species despite parameter uncertainty. No one has yet investigated whether this holds true for model uncertainty for species with complex life histories and for responses to multiple threats. We tested whether a range of model structures yielded similar rankings of management and threat scenarios for 2 plant species with complex postfire responses. We examined 2 contrasting species from different plant functional types: an obligate seeding shrub and a facultative resprouting shrub. We exposed each to altered fire regimes and an additional, species‐specific threat. Long‐term demographic data sets were used to construct an individual‐based model (IBM), a complex stage‐based model, and a simple matrix model that subsumes all life stages into 2 or 3 stages. Agreement across models was good under some scenarios and poor under others. Results from the simple and complex matrix models were more similar to each other than to the IBM. Results were robust across models when dominant threats are considered but were less so for smaller effects. Robustness also broke down as the scenarios deviated from baseline conditions, likely the result of a number of factors related to the complexity of the species’ life history and how it was represented in a model. Although PVA can be an invaluable tool for integrating data and understanding species’ responses to threats and management strategies, this is best achieved in the context of decision support for adaptive management alongside multiple lines of evidence and expert critique of model construction and output.