Filtering effect of wind flow turbulence on atmospheric pollutant dispersion

This paper presents a model for coupling the statistics of wind velocity distribution and atmospheric pollutant dispersion. The effect of wind velocity distribution is modeled as a three-dimensional finite-impulse response (3D-FIR) filter. A phase space representation of the 3D-FIR filter window is discussed. The resulting pollutant dispersion is the multiplication in the phase space of the 3-D Fourier transform of the pollutant concentration and the volume described by the filter window coefficients. The shape of the filter window in the phase space enables representing such effects as vortex shedding thermal currents, etc. The impact of spatial distribution of the sensors on the resulting pollutant spatial distribution and the 3-D FIR filter model employed also discuss. The case of a neutrally buoyant plume emitted from an elevated point source in a turbulent boundary layer considers. The results show that wind turbulence is an important factor in the pollutant dispersion and introduces expected random fluctuations in pollutant distribution and leads to spreading the distribution due to wind mixing.     

International Environmental Agreements: Design of Optimal Transfers Under Heterogeneity

International environmental agreements (IEAs) can coordinate abatement of transboundary pollutants. This paper investigates how heterogeneous countries facing a stock pollutant might structure such an agreement. In particular, we examine how an IEA might be implemented with a set of monetary transfers. The focus is on transfers that are time invariant, linear in emissions, and consistent with budget balance. There is a range of such schemes that would induce efficient emissions. We provide a simple and intuitive characterization of these penalties and describe how specific proposals might be chosen in order to facilitate compliance and implementation. Our proposals are illustrated with a simple example. We show that heterogeneity reduces the scope for penalty schemes to jointly satisfy desirable properties.     

A survey on the utility of the USEPA CADDIS stressor identification procedure

The Environmental Protection Agency (EPA) has made available on the worldwide web a systematic stream stressor identification procedure, the “Causal Analysis/Diagnosis Decision Information System” or CADDIS. We report here the results of a survey of regulators and scientists in 11 states who use CADDIS or another stressor identification procedure in their work. The 13 survey questions address guidelines as to what impairment scenarios to approach with stressor identification, what information is needed to perform stressor identification, and what the stakeholder role is in performing stressor identification. At the time of this survey (the summer of 2009), the EPA CADDIS website was less commonly used among the state regulators surveyed than the published EPA stressor identification document on which it is based. The respondents generally find the EPA stressor identification procedure useful and capable of being adapted to their individual needs. Survey respondents all use stressor identification in their Total Maximum Daily Load work, but also in a wide variety of other applications. All the “types of evidence” included in the CADDIS stressor identification procedure are used by the practitioners surveyed with the exception of the results of ecological simulation models. While the CADDIS documentation encourages the involvement of stakeholders in stressor identification, most respondents do not assemble stakeholder teams of local officials and citizens to participate in stressor analyses.     

Assessment of physicochemical parameters and prevalence of virulent and multiple-antibiotic-resistant <Emphasis Type="Italic">Escherichia coli</Emphasis> in treated effluent of two wastewater treatment plants and receiving aquatic <Emphasis Type="Italic">milieu</Emphasis> in Durban,South Africa

The poor operational status of some wastewater treatment plants often result in the discharge of inadequately treated effluent into receiving surface waters. This is of significant public health concern as there are many informal settlement dwellers (ISDs) that rely on these surface waters for their domestic use. This study investigated the treatment efficiency of two independent wastewater treatment plants (WWTPs) in Durban, South Africa and determined the impact of treated effluent discharge on the physicochemical and microbial quality of the receiving water bodies over a 6-month period. Presumptive Escherichia coli isolates were identified using biochemical tests and detection of the mdh gene via PCR. Six major virulence genes namely eae, hly, fliC, stx1, stx2, and rfbE were also detected via PCR while antibiotic resistance profiles of the isolates were determined using Kirby-Bauer disc diffusion assay. The physicochemical parameters of the wastewater samples ranged variously between 9 and 313.33 mg/L, 1.52 and 76.43 NTUs, and 6.30 and 7.87 for COD, turbidity, and pH respectively, while the E. coli counts ranged between 0 and 31.2?×?10³ CFU/ml. Of the 200 selected E. coli isolates, the hly gene was found in 28 %, fliC in 20 %, stx2 in 17 %, eae in 14 %, with stx1 and rfbE in only 4 % of the isolates. Notable resistance was observed toward trimethoprim (97 %), tetracycline (56 %), and ampicillin (52.5 %). These results further highlight the poor operational status of these WWTPs and outline the need for improved water quality monitoring and enforcement of stringent guidelines.     

Assessing regulatory violations of disinfection by-products in water distribution networks using a non-compliance potential index

Inactivating pathogens is essential to eradicate waterborne diseases. However, disinfection forms undesirable disinfection by-products (DBPs) in the presence of natural organic matter. Many regulations and guidelines exist to limit DBP exposure for eliminating possible health impacts such as bladder cancer, reproductive effects, and child development effects. In this paper, an index named non-compliance potential (NCP) index is proposed to evaluate regulatory violations by DBPs. The index can serve to evaluate water quality in distribution networks using the Bayesian Belief Network (BBN). BBN is a graphical model to represent contributing variables and their probabilistic relationships. Total trihalomethanes (TTHM), haloacetic acids (HAA5), and free residual chlorine (FRC) are selected as the variables to predict the NCP index. A methodology has been proposed to implement the index using either monitored data, empirical model results (e.g., multiple linear regression), and disinfectant kinetics through EPANET simulations. The index’s usefulness is demonstrated through two case studies on municipal distribution systems using both full-scale monitoring and modeled data. The proposed approach can be implemented for data-sparse conditions, making it especially useful for smaller municipal drinking water systems.