OPTIMAL LONG-TERM SCHEDULING OF STORMWATER DRAINAGE REHABILITATION1

ABSTRACT: A mathematical model is developed to optimally schedule long-term stormwater infrastructure rehabilitation activities. The model is capable of considering multiple rehabilitation projects and is driven by overall cost eensiderations. Rehabilitation activities are scheduled based on perceived reliabilities and future deterioration expected within the specified planning horizon. Future growth within the stormwater drainage basin is incorporated using chance constraints that limit the likelihood that a stormwater discharge exceeds system conveyance capacity. Model structure and development are discussed, and a hypothetical example using a drainage network is presented.     

Analysis of Products Generated from the Thermal and Catalytic Degradation of Pure and Waste Polyolefins using Py-GC/MS

The possibility of transforming waste plastics into valuable hydrocarbons via catalytic cracking and reforming is attracting increasing interest. Pyrolysis coupled with Gas Chromatographic separation and Mass Spectrometry detection (Py-GC/MS) has been used in this work to study the product selectivity of various catalysts in the conversion of pure and residual polyethylene samples into hydrocarbon products. Five acid solids of comparable aluminium contents but different textural and acid properties were tested as catalysts, including three zeolites (standard ZSM-5, nanocrystalline n-ZSM-5 and Beta) and two mesostructured solids (Al-MCM-41 and Al-SBA-15). Thermal cracking of the pure and residual polymers generated a similar range of products to each other, with a high proportion of linear paraffins and olefins of varying lengths. The presence of zeolitic materials resulted in complete elimination of heavy linear products, an increase in the light hydrocarbon fraction and a marked selectivity towards the formation of single-ring aromatic species, particularly benzene, toluene and xylene. Aromatic formation was particularly notable with the small crystal size n-ZSM-5 (aromatic selectivity up to 53.9%) and less marked in the case of standard ZSM-5 (up to 36.4%) and Beta zeolite (up to 35.0%). Mesostructured catalysts like Al-MCM-41 and Al-SBA-15 favoured the production of light C₂–C₅ hydrocarbons (up to 57.9%) while the formation of aromatic products was significantly lower than with zeolitic materials. The paper examines the extent and the causes for this product selectivity and discusses its connection with the acid and textural properties of each catalyst. It was also observed that, under the experimental conditions employed, the products generated were not significantly affected by the nature and origin of the polymers employed.     

Superoxide production by marine microalgae

A survey was conducted for production of the reactive oxygen species superoxide by 37 species (65 strains) of microalgae including dinoflagellates, raphidophytes, chlorophytes, prasinophytes, eustigmatophytes and prymnesiophytes. Ichthyotoxic raphidophyte species of Chattonella were found to produce the highest environmental levels of superoxide (177×10⁴ total chemiluminescence units). However, ichthyotoxic dinoflagellates (Karenia, Alexandrium) and the prymnesiophyte Prymnesium were also found to produce significant levels of superoxide (4×10⁴, 3×10⁴ and 5×10⁴ chemiluminescence units, respectively), equivalent to that of other raphidophyte species of Heterosigma and Fibrocapsa (6×10⁴ and 2×10⁴, respectively). A direct relationship between cell size and superoxide production was observed (r²=0.94), with larger cells producing more superoxide per cell. Chattonella produced the most superoxide per cell (expressed as cellular chemiluminescence units), followed by the dinoflagellate species Karenia, Alexandrium, Takayama and Gymnodinium. Small cells, such as the raphidophyte Heterosigma and the prymnesiophyte Prymnesium produced very little superoxide per cell (cellular chemiluminescence units), but potentially could still produce high total levels of superoxide if present at high biomass levels. Species commonly used as aquaculture bivalve feeds such as Dunaliella, Tetraselmis, Nannochloropsis and Pavlova produced negligible levels of superoxide, even at high biomass. We speculate that superoxide, while not the sole ichthyotoxic principle, may play a wider role in algal toxicity than previously considered, and propose a broad classification of microalgae based upon superoxide production.Communicated by M.S. Johnson, Crawley     

Radionuclide and chemical concentrations in mineral waters at Saratoga Springs, New York

A project to characterize the radionuclide and chemical components in natural spring waters in the vicinity of Saratoga Springs, New York (USA) has been completed. As a result of the measured radionuclide and chemical content, eight springs were labeled as mineral waters, whereas three springs contained very low concentrations of these components. The mineral waters were highly enriched in alkaline and alkaline-earth elements, as well as chloride ions. Three isotopes of radium ((224)Ra, (226)Ra, (228)Ra) were detected in the mineral waters and reached concentrations of 1, 20, and 2 Bq/L, respectively. Overall, the (226)Ra isotope constituted about 80% of the total radioactivity measured in the water samples. Dissolved uranium concentrations in the mineral waters were very low (mean approximately 50 mBq/L).     

Prediction of potential areas of species distributions based on presence-only data

We introduce a methodology to infer zones of high potential for the habitat of a species, useful for management of biodiversity, conservation, biogeography, ecology, or sustainable use. Inference is based on a set of sites where the presence of the species has been reported. Each site is associated with covariate values, measured on discrete scales. We compute the predictive probability that the species is present at each node of a regular grid. Possible spatial bias for sites of presence is accounted for. Since the resulting posterior distribution does not have a closed form, a Markov chain Monte Carlo (MCMC) algorithm is implemented. However, we also describe an approximation to the posterior distribution, which avoids MCMC. Relevant features of the approach are that specific notions of data acquisition such as sampling intensity and detectability are accounted for, and that available a priori information regarding areas of distribution of the species is incorporated in a clear-cut way. These concepts, arising in the presence-only context, are not addressed in alternative methods. We also consider an uncertainty map, which measures the variability for the predictive probability at each node on the grid. A simulation study is carried out to test and compare our approach with other standard methods. Two case studies are also presented.     

Expanding Kenya's protected areas under the Convention on Biological Diversity to maximize coverage of plant diversity

Biodiversity is highly valuable and critically threatened by anthropogenic degradation of the natural environment. In response, governments have pledged enhanced protected‐area coverage, which requires scarce biological data to identify conservation priorities. To assist this effort, we mapped conservation priorities in Kenya based on maximizing alpha (species richness) and beta diversity (species turnover) of plant communities while minimizing economic costs. We used plant‐cover percentages from vegetation surveys of over 2000 plots to build separate models for each type of diversity. Opportunity and management costs were based on literature data and interviews with conservation organizations. Species richness was predicted to be highest in a belt from Lake Turkana through Mount Kenya and in a belt parallel to the coast, and species turnover was predicted to be highest in western Kenya and along the coast. Our results suggest the expanding reserve network should focus on the coast and northeastern provinces of Kenya, where new biological surveys would also fill biological data gaps. Meeting the Convention on Biological Diversity target of 17% terrestrial coverage by 2020 would increase representation of Kenya's plant communities by 75%. However, this would require about 50 times more funds than Kenya has received thus far from the Global Environment Facility.     

Elimination of pharmaceutical pollutants by solar photoelectro-Fenton process in a pilot plant

Environmental Science and Pollution Research - In this study, the simultaneous degradation of antibiotics (ampicillin, sulfamethazine, and tetracycline; and non-steroidal anti-inflammatories...