Ozonation of oil sands process water removes naphthenic acids and toxicity

Naphthenic acids are naturally-occurring, aliphatic or alicyclic carboxylic acids found in petroleum. Water used to extract bitumen from the Athabasca oil sands becomes toxic to various organisms due to the presence of naphthenic acids released from the bitumen. Natural biodegradation was expected to be the most cost-effective method for reducing the toxicity of the oil sands process water (OSPW). However, naphthenic acids are poorly biodegraded in the holding ponds located on properties leased by the oil sands companies. In the present study, chemical oxidation using ozone was investigated as an option for mitigation of this toxicity. Ozonation of sediment-free OSPW was conducted using proprietary technology manufactured by Seair Diffusion Systems Inc. Ozonation for 50min generated a non-toxic effluent (based on the Microtox bioassay) and decreased the naphthenic acids concentration by approximately 70%. After 130min of ozonation, the residual naphthenic acids concentration was 2mgl(-1): <5% of the initial concentration in the filtered OSPW. Total organic carbon did not change with 130min of ozonation, whereas chemical oxygen demand decreased by approximately 50% and 5-d biochemical oxygen demand increased from an initial value of 2mgl(-1) to a final value of 15mgl(-1). GC-MS analysis showed that ozonation resulted in an overall decrease in the proportion of high molecular weight naphthenic acids (n> or = 22).     

Single-source impact analysis using three-dimensional air quality models

Isolating the effects of an individual emissions source on secondary air pollutants such as ozone and some components of particulate matter must incorporate complex nonlinear processes, be sensitive to small emissions perturbations, and account for impacts that may occur hundreds of kilometers away. The ability to evaluate these impacts is becoming increasingly important for efficient air quality management. Here, as part of a recent compliance enforcement action for a violation of the Clean Air Act and as an evaluation of ozone response to single-source emissions plumes, two three-dimensional regional photochemical air quality models are used to assess the impact on ozone from approximately 2000 to 3000 excess t/month of nitrogen oxides emitted from a single power plant in Ohio. Periods in May, July, and August are evaluated. Two sensitivity methods are applied: the "brute-force" (B-F) method and the decoupled direct method (DDM). Using DDM, maximum 1-hr averaged ozone concentrations are found to increase by up to 1.8, 1.3, and 2.2 ppbv during May, July, and August episodes, respectively, and concentration increases greater than 0.5 ppbv occur in Ohio, Pennsylvania, Maryland, New York, West Virginia, Virginia, and North and South Carolina. B-F results for the August episode show a maximum 1-hr averaged ozone concentration increase of 2.3 ppbv. Significant localized decreases are also simulated, with a maximum of 3.6 ppbv in Ohio during the August episode and decreases of 0.50 ppbv and greater in Ohio, Pennsylvania, Maryland, West Virginia, and Virginia. Maximum increases are compared with maximum decreases for the August period using second-order DDM and are found, in aggregate, to be greater in magnitude by 42%. When evaluated during hours when ozone concentrations exceed 0.060 ppm, the maximum increases in ozone are higher than decreases by 82%. The spatial extent of ozone increase in both cases is about triple that of reduction.     

Implementation of a windblown dust parameterization into MODELS-3/CMAQ: Application to episodic PM events in the US/Mexico border

Windblown dust is known to impede visibility, deteriorate air quality and modify the radiation budget. Arid and semiarid areas with unpaved and unvegetated land cover are particularly prone to windblown dust, which is often attributed to high particulate matter (PM) pollution in such areas. Yet, windblown dust is poorly represented in existing regulatory air quality models. In a study by the authors on modeling episodic high PM events along the US/Mexico border using the state-of-the-art CMAQ/MM5/SMOKE air quality modeling system [Choi, Y.-J., Hyde, P., Fernando, H.J.S., 2006. Modeling of episodic particulate matter events using a 3D air quality model with fine grid: applications to a pair of cities in the US/Mexico border. Atmospheric Environment 40, 5181–5201], some of the observed PM₁₀ NAAQS exceedances were inferred as due to windblown dust, but the modeling system was incapable of dealing with time-dependent episodic dust entrainment during high wind periods. In this paper, a time-dependent entrainment parameterization for windblown dust is implemented in the CMAQ/MM5/SMOKE modeling system with the hope of improving PM predictions. An approach for realizing windblown dust emission flux for each grid cell over the study domain on an hourly basis, which accounts for the influence of factors such as soil moisture content, atmospheric stability and wind speed, is presented in detail. Comparison of model predictions with observational data taken at a pair of US/Mexico border towns shows a clear improvement of model performance upon implementation of the dust emission flux parameterization.     

Characterizing effects of uncertainties in MSW composting process through a coupled fuzzy vertex and factorial-analysis approach

A coupled fuzzy vertex and factorial-analysis approach was developed in this study for systematically characterizing effects of uncertainties in a municipal solid waste composting process. A comprehensive composting process model was also embedded into the system framework and used to address substrate decomposition and biomass growth, as well as the interactions between moisture contents, temperatures, and oxygen concentrations. The applicability of the proposed method was verified through a custom-made pilot-scale composting system. Results from fuzzy simulation indicated that the fuzzy vertex method could effectively communicate implicit knowledge into dynamic simulations and thus provide valuable information for enhancing composting process control under uncertainty. The factorial analysis was effective in quantifying the proportion to which the uncertainty of each single or interactive effect of model parameters contributes to the overall uncertainty of the system outcomes. Thus, sensitive parameters that may lead to errors or unreasonable predictions can be determined. The proposed study system could not only be used in characterizing combined effects of uncertainties for composting processes, but was also applicable to many other environmental modelling systems.     

Characterization of food waste generators: a Hawaii case study

Information on food waste disposal and on recycling methods and recycled amounts is reported. Data were obtained from a mail and phone survey of all licensed food establishments in Hawaii conducted in 2004 and 2005. Of 8253 licensed food establishments, 5033 completed surveys. It was found that relationships exist between food establishment size (measured by the number of meals served per day or the number of employees) and the amount of food an establishment recycled; establishment type and recycling behavior; and establishment type and amount recycled. The amount of food waste recycled in the state of Hawaii was estimated to be 264,000 L/day and annual food waste generation was estimated to be 336,000 tonnes.     

Soils, climate change and the OECD

Some concepts of sustainability applied to soils are given in relation to the Organisation for Economic Co-operation and Development (OECD) Co-operative Research Programme 'Biological Resource Management for Sustainable Agricultural Systems'. The application of these concepts to climate change will be discussed in relation to seven high-profile papers published over the past 12 months. It is argued that multi-disciplinary (including social science) approaches are needed to address the issues. There is also a brief discussion on biomass energy in terms of soil sustainability and climate change.     

Modeling water and sediment contamination of Lake Pontchartrain following pump-out of Hurricane Katrina floodwater

Levee failure and overtopping as a result of Hurricane Katrina caused major flooding of New Orleans, Louisiana. Floodwaters, which were contaminated with heavy metals, organic chemicals, and fecal coliform bacteria (FCB), were pumped into neighboring Lake Pontchartrain during dewatering. The impact of levee failure on water and benthic sediment concentrations in the lake was investigated by applying a numerical water quality model coupled to a three-dimensional, numerical hydrodynamic model. The model was used to compute water and benthic sediment concentrations throughout the lake for lead, arsenic, benzo(a)pyrene (BaP), and 1,1-dichloro-2,2-bis(p-chlorophenyl)ethylene (DDE), and water concentrations for FCB. Computed concentrations resulting from actual pumped discharges with levee failure and overtopping were compared to computed concentrations resulting from pumped discharges without levee failure or overtopping, and concentrations from both sets of conditions were compared to ecological water and sediment quality screening guideline values. The model indicated that incremental increases above pre-Katrina benthic sediment concentrations are about a factor of 10 greater with dewatering of the floodwaters than with dewatering of storm water without flooding. However, these increases for the metals are small relative to pre-Katrina concentrations. The results showed that the ecological screening-level sediment quality guideline values were exceeded for BaP and DDE in areas near the south shoreline of the lake as a result of floodwater pump-out, whereas, this was not the case for storm water removal without flooding. The model showed that lake water column concentrations should be about the same during both dewatering conditions regardless of whether there is flooding or not.     

Seasonal Variation of Toxic Benzene Emissions in Petroleum Refinery

Petroleum refineries are largest chemical industries that are responsible for the emission of several pollutants into the atmosphere. Benzene is among the most important air pollutants that are emitted by petroleum refineries, since they are involved in almost every refinery process. Volatile organic compounds (VOCs) are a major group of air pollutants, which play a critical role in atmospheric chemistry. These contribute to toxic oxidants, which are harmful to ecosystem, human health and atmosphere. The variability of pollutants is an important factor in determining human exposure to these chemicals. The ambient air concentrations of benzene were measured in several sites around the Digboi petroleum refinery, near the city of Gowahati in northeast India, during winter and summer 2004. The seasonal and spatial variations of the ambient air concentrations of this benzene were investigated and analyzed. An estimation of the contribution of the refinery to the measured atmospheric levels of benzene was also performed. The ambient air mixing ratios of benzene in a large area outside the refinery was generally low, in ppbv range, much lower than the ambient air quality standards. This article presents the temporal and spatial variation of air pollution in and around petroleum refinery and showed that no health risk due to benzene is present in the areas adjacent to the refinery.     

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).     

Relation of waste generation and composition to socio-economic factors: a case study

To develop an effective waste management strategy for a given region, it is important to know the amount of waste generated and the composition of the waste stream. Past research has shown that the amount of waste generated is proportional to the population and the average mean living standards or the average income of the people. In addition, other factors may affect the amount and composition of waste. These are climate, living habits, level of education, religious and cultural beliefs, and social and public attitudes. This paper presents the findings of a study carried out in a suburban municipal area in Sri Lanka to determine the solid waste generation rate and waste composition based on field surveys and to determine the related socio-economic factors. A database was developed that included information on the quantity and composition of waste generated in a sample of households in the study area over a time period. The collected data was analysed to relate waste generation and composition data to various socio-economic factors. Over 400 sample households were selected for the study using a stratified random sampling methodology based on municipal wards and property values. A technique that considers both the number of households in a particular income group (property value range) and the standard deviation of property values within a given income group was used to determine the appropriate sample size for each municipal ward. Through category and regression analyses, the quantities of waste and waste composition were related to several socio-economic factors. The paper describes the basis for the sample selection, the methodology adopted for data collection, the socio-economic parameters used for the analysis, and the relationships developed from the analysis.