P. James McLellan

Models for predicting disinfection byproduct (DBP) formation in drinking waters: A chronological review

Disinfection for the supply of safe drinking water forms a variety of known and unknown byproducts through reactions between the disinfectants and natural organic matter. Chronic exposure to disinfection byproducts through the ingestion of drinking water, inhalation and dermal contact during regular indoor activities (e.g., showering, bathing, cooking) may pose cancer and non-cancer risks to human health. Since their discovery in drinking water in 1974, numerous studies have presented models to predict DBP formation in drinking water. To date, more than 48 scientific publications have reported 118 models to predict DBP formation in drinking waters. These models were developed through laboratory and field-scale experiments using raw, pretreated and synthetic waters. This paper aims to review DBP predictive models, analyze the model variables, assess the model advantages and limitations, and to determine their applicability to different water supply systems. The paper identifies the current challenges and future research needs to better control DBP formation. Finally, important directions for future research are recommended to protect human health and to follow the best management practices.

Uncertainty characterization approaches for risk assessment of DBPs in drinking water: a review.

The management of risk from disinfection by-products (DBPs) in drinking water has become a critical issue over the last three decades. The areas of concern for risk management studies include (i) human health risk from DBPs, (ii) disinfection performance, (iii) technical feasibility (maintenance, management and operation) of treatment and disinfection approaches, and (iv) cost. Human health risk assessment is typically considered to be the most important phase of the risk-based decision-making or risk management studies. The factors associated with health risk assessment and other attributes are generally prone to considerable uncertainty. Probabilistic and non-probabilistic approaches have both been employed to characterize uncertainties associated with risk assessment. The probabilistic approaches include sampling-based methods (typically Monte Carlo simulation and stratified sampling) and asymptotic (approximate) reliability analysis (first- and second-order reliability methods). Non-probabilistic approaches include interval analysis, fuzzy set theory and possibility theory. However, it is generally accepted that no single method is suitable for the entire spectrum of problems encountered in uncertainty analyses for risk assessment. Each method has its own set of advantages and limitations. In this paper, the feasibility and limitations of different uncertainty analysis approaches are outlined for risk management studies of drinking water supply systems. The findings assist in the selection of suitable approaches for uncertainty analysis in risk management studies associated with DBPs and human health risk.

Investigating effects of bromide ions on trihalomethanes and developing model for predicting bromodichloromethane in drinking water

Chlorination for drinking water can form brominated trihalomethanes (THMs) in the presence of bromide ions. Recent studies have reported that bromodichloromethane (BDCM) has a stronger association with stillbirths and neural tube defects than other THMs species. In this paper, the results of an experimental investigation into the factors forming THMs in the presence of bromide ions are presented. The experiments were conducted using synthetic water samples with different characteristics (e.g., pH, temperature, dissolve organic content). Different combinations of these characteristics were considered in the experimental program. The results showed that increased bromide ion concentrations led to increases in the formation of total THMs, with higher BDCM and dibromochloromethane (DBCM), and lower chloroform formation. By increasing the pH from 6 to 8.5, increased chloroform and decreased BDCM and DBCM formation were observed. Higher bromide ions to chlorine ratios increased BDCM and DBCM and decreased chloroform formation, while higher temperatures increased BDCM, DBCM and chloroform formation. In most cases, bromoform (CHBr(3)) concentrations were found to be below the detection limit. Significant factors influencing BDCM formation were identified using a statistical analysis. A model for BDCM formation was estimated from 44 experiments and statistical adequacy was assessed using appropriate diagnostics, including residual plots and an R(2) of 0.97. The model was validated using external data from 17 water supply systems in Newfoundland, Canada. The predictive performance of the model was found to be excellent, and the resulting model could be used to predict BDCM formation in drinking water and to perform risk-cost balance analyses for best management practices.

Dynamic modeling and optimal fed‐batch feeding strategies for a two‐phase partitioning bioreactor

A dynamic model for the degradation of phenol in a two-phase partitioning bioreactor has been developed based on mechanistic balances around the bioreactor. The key process characteristics including substrate transfer between the organic and aqueous phases, substrate inhibition, oxygen limitation, and cell entrainment were incorporated into the model. The model predictions were validated against existing experimental data obtained for a 2-L bioreactor, and good correlation was observed for the time frames of the simulations, as well as for trends in cell and substrate concentrations. Optimal fed-batch, phenol feeding strategies were then developed based on two approaches: (1) maximization of phenol consumption in a fixed time interval and (2) consumption of a fixed amount of phenol in minimal time. The optimal feeding policies, determined using the Iterative Dynamic Programming algorithm, provided substantial improvements in the amount of phenol consumed when compared to a typical experimental heuristic approach. For example, 45.73 g of phenol was predicted to be consumed in 50 h (not including lag phase) using the optimal feeding profile compared to 10.26 g of phenol consumed in the simulated experimental approach. Oxygen limitation was predicted to be a recurring operational challenge in the partitioning bioreactor, and had a strong impact on the optimization results.

Production of bio-synthetic natural gas in Canada.

Large-scale production of renewable synthetic natural gas from biomass (bioSNG) in Canada was assessed for its ability to mitigate energy security and climate change risks. The land area within 100 km of Canadas network of natural gas pipelines was estimated to be capable of producing 67-210 Mt of dry lignocellulosic biomass per year with minimal adverse impacts on food and fiber production. Biomass gasification and subsequent methanation and upgrading were estimated to yield 16,000-61,000 Mm(3) of pipeline-quality gas (equivalent to 16-63% of Canadas current gas use). Life-cycle greenhouse gas emissions of bioSNG-based electricity were calculated to be only 8.2-10% of the emissions from coal-fired power. Although predicted production costs (

Inhibition effects of ethanol concentration history and ethanol concentration change rate onZymomonas mobilis

17-21 GJ(-1)) were much higher than current energy prices, a value for low-carbon energy would narrow the price differential. A bioSNG sector could infuse Canadas rural economy with

Brief A passivity-based analysis for decentralized integral controllability

41-130 billion of investments and create 410,000-1,300,000 jobs while developing a nation-wide low-carbon energy system.

Feasibility study of a Great Lakes bioenergy system.

SummaryThe inhibition effects onZymomonas mobilis of ethanol concentration history (time-integrated exposure to ethanol) and ethanol concentration change rate have been investigated. It was found that the ethanol concentration history had no significant effect on the fermentative capability ofZ. mobilis, while the ethanol concentration change rate had a quite intense inhibitory effect.

Modelling of a continuous two-phase partitioning bioreactor for the degradation of xenobiotics

The property of decentralized integral controllability (DIC) is related to the concept of passivity in this note. A sufficient condition for DIC is proposed based on the passivity theorem and a computational method for testing DIC is presented.

Examination of sludge accumulation rates and sludge characteristics for a decentralized community wastewater treatment systems with individual primary clarifier tanks located in Wardsville (Ontario, Canada)

A bioenergy production and delivery system built around the Great Lakes St. Lawrence Seaway (GLSLS) transportation corridor was assessed for its ability to mitigate energy security and climate change risks. The land area within 100 km of the GLSLS and associated railway lines was estimated to be capable of producing at least 30 Mt(dry) yr(-1) of lignocellulosic biomass with minimal adverse impacts on food and fibre production. This was estimated to be sufficient to displace all of the coal-fired electricity in Ontario plus more than 620 million L of green diesel (equivalent to 5.3% of diesel consumption in GLSLS provinces). Lifecycle greenhouse gas emissions were 88% and 76% lower than coal-fired power and conventional diesel, respectively. Production costs of