Baiyu Zhang

Screening of biosurfactant producers from petroleum hydrocarbon contaminated sources in cold marine environments

An overview of literature about isolating biosurfactant producers from marine sources indicated no such producers have been reported form North Atlantic Canada. Water and sediment samples were taken from petroleum hydrocarbon contaminated coastal and offshore areas in this region. Either n-hexadecane or diesel was used as the sole carbon source for the screening. A modified colony-based oil drop collapsing test was used to cover sessile biosurfactant producers. Fifty-five biosurfactant producers belong to genera of Alcanivorax, Exiguobacterium, Halomonas, Rhodococcus, Bacillus, Acinetobacter, Pseudomonas, and Streptomyces were isolated. The first three genera were established after 1980s with interesting characteristics and limited relevant publications. Some of the 55 isolated strains were found with properties such as greatly reducing surface tension, stabilizing emulsion and producing flocculant. Isolates P6-4P and P1-5P were selected to demonstrate the performance of biosurfactant production, and were found to reduce the surface tension of water to as low as 28 dynes/cm.

Naphthalene degradation in seawater by UV irradiation: The effects of fluence rate, salinity, temperature and initial concentration

A large amount of oil pollution at sea is produced by the operational discharge of oily wastewater. The removal of polycyclic aromatic hydrocarbons (PAHs) from such sources using UV irradiation has become attractive, yet the photolysis mechanism in seawater has remained unclear. This study examines the photodegradation kinetics of naphthalene in natural seawater through a full factorial design of experiments (DOE). The effects of fluence rate, salinity, temperature and initial concentration are investigated. Results show that fluence rate, temperature and the interaction between temperature and initial concentration are the most influential factors. An increase in fluence rate can linearly promote the photodegradation process. Salinity increasingly impedes the removal of naphthalene because of the existence of free-radical scavengers and photon competitors. The results will help understand the photolysis mechanism of PAHs and develop more effective methods for treating oily seawater generated from offshore industries.

CCEM: A City-cluster Energy Systems Planning Model

Abstract An understanding of complex interactions among energy, environmental, and economic activities is important for making decisions to support sustainable economic development and environmental protection. Energy models at global, national, and provincial levels are effective tools used for examining these interactions. However, these models are inadequate for a city-cluster jurisdiction such as the Toronto-Niagara Region (TNR), Canada, which has unique economic and energy characteristics. The objective of this study is to develop a City-cluster Energy Systems Planning Model (CCEM) and apply it to the TNR as a case study. It is demonstrated that the model can be effectively used for supporting energy planning, environmental management, and greenhouse gas (GHG) reduction in a city-cluster jurisdiction.

Offshore produced water management: A review of current practice and challenges in harsh/Arctic environments

Increasing offshore oil and gas exploration and development in harsh/Arctic environments require more effective offshore produced water management, as these environments are much more sensitive to changes in water quality than more temperate climates. However, the number and scope of studies of offshore produced water management in harsh/Arctic environments are limited. This paper reviews the current state of offshore produced water management, impacts, and policies, as well as the vulnerability, implications and operational challenges in harsh/Arctic environments. The findings show that the primary contaminant(s) of concern are contained in both the dissolved oil and the dispersed oil. The application of emerging technologies that can tackle this issue is significantly limited by the challenges of offshore operations in harsh/Arctic environments. Therefore, there is a need to develop more efficient and suitable management systems since more stringent policies are being implemented due to the increased vulnerability of harsh/Arctic environments.

Adsorption of Cu and Zn onto Mn/Fe oxides and organic materials in the extractable fractions of river surficial sediments.

The roles of the extractable components (Mn oxides, Fe oxides, and organic materials) of surficial sediments in controlling metals adsorption were investigated. Cu and Zn adsorptions were conducted before and after the surficial sediments extracted with hydroxylamine hydrochloride, an oxalate solution, and H 2 O 2 , respectively. The extraction removed target components with extraction efficiencies from 63 to 98%. Nonlinear regression analyses of Cu and Zn adsorptions based on the assumption of additive Langmuir adsorption isotherm were employed to estimate the relative contributions of sediment components to Cu and Zn adsorptions. The results indicate that the greatest contribution to total Cu and Zn adsorption to the surficial sediments on a molar basis was from Mn oxides in the extractable fractions. Both Cu and Zn adsorption capacities of Mn oxides exceeded those of Fe oxides by approximately one order of magnitude, fewer roles were attributed to the adsorption of organic material (OM), and the estimated contribution of the residual fraction to total Cu and Zn adsorption was insignificant. These information implied that the roles of metal oxides (Fe and Mn oxides) in the extractable form of the surficial sediments, especially Mn oxides, was the most important component in controlling heavy metal transportation in aquatic environments.

Process simulation and dynamic control for marine oily wastewater treatment using UV irradiation

UV irradiation and advanced oxidation processes have been recently regarded as promising solutions in removing polycyclic aromatic hydrocarbons (PAHs) from marine oily wastewater. However, such treatment methods are generally not sufficiently understood in terms of reaction mechanisms, process simulation and process control. These deficiencies can drastically hinder their application in shipping and offshore petroleum industries which produce bilge/ballast water and produced water as the main streams of marine oily wastewater. In this study, the factorial design of experiment was carried out to investigate the degradation mechanism of a typical PAH, namely naphthalene, under UV irradiation in seawater. Based on the experimental results, a three-layer feed-forward artificial neural network simulation model was developed to simulate the treatment process and to forecast the removal performance. A simulation-based dynamic mixed integer nonlinear programming (SDMINP) approach was then proposed to intelligently control the treatment process by integrating the developed simulation model, genetic algorithm and multi-stage programming. The applicability and effectiveness of the developed approach were further tested though a case study. The experimental results showed that the influences of fluence rate and temperature on the removal of naphthalene were greater than those of salinity and initial concentration. The developed simulation model could well predict the UV-induced removal process under varying conditions. The case study suggested that the SDMINP approach, with the aid of the multi-stage control strategy, was able to significantly reduce treatment cost when comparing to the traditional single-stage process optimization. The developed approach and its concept/framework have high potential of applicability in other environmental fields where a treatment process is involved and experimentation and modeling are used for process simulation and control.

Modeling of UV-Induced Photodegradation of Naphthalene in Marine Oily Wastewater by Artificial Neural Networks

In this study, an artificial neural networks (ANN) model was developed to predict the removal of a polycyclic aromatic hydrocarbon (PAH), namely, naphthalene from marine oily wastewater by using UV irradiation. The removal rate was used as model output and simulated as a function of five independent input variables, including fluence rate, salinity, temperature, initial concentration and reaction time. The configuration of the ANN model was optimized as a three-layer feed-forward Levenberg–Marquardt backpropagation network with log-sigmoid and linear transfer functions at the hidden (12 hidden neurons) and output layers, respectively. By considering goodness-of-fit and cross validated predictability, the ANN model was trained to provide good overall agreement with experimental results with a slope of 0.97 and a correlation of determination (R2) of 0.943. Sensitivity analysis revealed that fluence rate and temperature were the most influential variables, followed by reaction time, salinity and initial concentration. The findings of this study showed that neural network modeling could effectively predict the behavior of the photo-induced PAH degradation process.

A hybrid fuzzy stochastic analytical hierarchy process (FSAHP) approach for evaluating ballast water treatment technologies

BackgroundEnvironmental decisions can be complex because of the inherent trade-offs among environmental, social, ecological, and economic factors. This paper presents a novel hybrid fuzzy stochastic analytical hierarchy process (FSAHP) approach to aid decision making by incorporating fuzzy and stochastic uncertainty into the traditional analytic hierarchy process (AHP). A case study related to ballast water management is used to demonstrate the applicability of the proposed approach. Nine experts from government ministries and academic institutions are invited to evaluate five treatment technologies (i.e., heat treatment, ultraviolet, ozone, ultrasound, and biocide) based on a number of criteria such as efficacy, capital cost, and human risk.ResultsThe experts’ preferences over the set of alternatives are represented as linguistic terms instead of numerical values. The beta-PERT distribution is adopted to approximate the probability density functions of the values of their inputs. Statistical analysis indicates that ultraviolet has the highest score (0.22–0.24) in most replications and its overlap with the second-best alternative is statistically negligible. Ozone, ultrasound, and heat treatment are mostly found as the second-, third-, and fourth-best alternatives with considerable overlaps that may be reduced if more experts are involved.ConclusionsAs compared with the traditional AHP, the proposed FSAHP approach can not only take into account linguistic information but also capture the uncertainty associated with insufficient information and biased opinions in group decision-making problems.

Offshore oil spill response practices and emerging challenges

Offshore oil spills are of tremendous concern due to their potential impact on economic and ecological systems. A number of major oil spills triggered worldwide consciousness of oil spill preparedness and response. Challenges remain in diverse aspects such as oil spill monitoring, analysis, assessment, contingency planning, response, cleanup, and decision support. This article provides a comprehensive review of the current situations and impacts of offshore oil spills, as well as the policies and technologies in offshore oil spill response and countermeasures. Correspondingly, new strategies and a decision support framework are recommended for improving the capacities and effectiveness of oil spill response and countermeasures. In addition, the emerging challenges in cold and harsh environments are reviewed with recommendations due to increasing risk of oil spills in the northern regions from the expansion of the Arctic Passage.

IFMEP: an interval fuzzy multiobjective environmental planning model for urban systems

Abstract As a complex system, the urban environment usually presents multiobjective, uncertain, and dynamic characteristics, which leads to difficulties in urban environmental planning. In this study, an interval fuzzy multiobjective programming method is proposed for tackling such problems and the associated solution algorithm is also discussed. Based on the proposed method, an interval fuzzy multiobjective environment planning model is further developed with specific focus on urban systems. The proposed approach allows uncertainties and comprehensive interaction of system components to be effectively communicated into the optimisation process. Furthermore, using scenario analysis and interactive solution processes, stakeholder preferences are efficiently integrated, promoting feasibility and robustness of decisions. The developed model was tested by a real-world case study in Kunming City, China. An analysis of the results shows that the proposed approach is an effective means for urban environmental planning.