Field evaluation of digital optical method to quantify the visual opacity of plumes

Visual Determination of the Opacity of Emissions from Stationary Sources (Method 9) is a reference method established by U.S. Environmental Protection Agency (EPA) to quantify plume opacity. However, Method 9 relies on observations from humans, which introduces subjectivity. In addition, it is expensive to teach and certify personnel to evaluate plume opacity on a semiannual basis. In this study, field tests were completed during a "smoke school" and a 4-month monitoring program of plumes emitted from stationary sources with a Method 9 qualified observer to evaluate the use of digital photography and two computer algorithms as an alternative to Method 9. This Digital Optical Method (DOM) improves objectivity, costs less to implement than Method 9, and provides archival photographic records of the plumes. Results from "smoke school" tests indicate that DOM passed six of eight tests when the sun was located in the 140 degrees sector behind one of the three cameras, with the individual opacity errors of 15% or less and average opacity errors of 7.5% or less. DOM also passed seven of the eight tests when the sun was located in the 216 degrees sector behind another camera. However, DOM passed only one of the eight tests when the sun was located in the 116 degrees sector in front of the third camera. Certification to read plume opacity by a "smoke reader" for 6 months requires that the "smoke reader" pass one of the smoke school tests during smoke school. The average opacity errors and percentage of observations with individual opacity errors above 15% for the results obtained with DOM were lower than those obtained by the smoke school trainees with the sun was located behind the camera, whereas they were higher than the smoke school trainee results with the sun located in front of the camera. In addition, the difference between plume opacity values obtained by DOM and a Method 9 qualified observer, as measured in the field for two industrial sources, were 2.2%. These encouraging results demonstrate that DOM is able to meet Method 9 requirements under a wide variety of field conditions and, therefore, has potential to be used as an alternative to Method 9.     

Iron isotopic fractionation in industrial emissions and urban aerosols

A study on tropospheric aerosols involving Fe particles with an industrial origin is tackled here. Aerosols were collected at the largest exhausts of a major European steel metallurgy plant and around its near urban environment. A combination of bulk and individual particle analysis performed by SEM–EDX provides the chemical composition of Fe-bearing aerosols emitted within the factory process (hematite, magnetite and agglomerates of these oxides with sylvite (KCl), calcite (CaCO₃) and graphite carbon). Fe isotopic compositions of those emissions fall within the range (0.08‰ < δ⁵⁶Fe < +0.80‰) of enriched ores processed by the manufacturer (−0.16‰ < δ⁵⁶Fe < +1.19‰). No significant evolution of Fe fractionation during steelworks processes is observed. At the industrial source, Fe is mainly present as oxide particles, to some extent in 3–4 μm aggregates. In the close urban area, 5 km away from the steel plant, individual particle analysis of collected aerosols presents, in addition to the industrial particle type, aluminosilicates and related natural particles (gypsum, quartz, calcite and reacted sea salt). The Fe isotopic composition (δ⁵⁶Fe = 0.14 ± 0.11‰) measured in the close urban environment of the steel metallurgy plant appears coherent with an external mixing of industrial and continental Fe-containing tropospheric aerosols, as evidenced by individual particle chemical analysis. Our isotopic data provide a first estimation of an anthropogenic source term as part of the study of photochemically promoted dissolution processes and related Fe fractionations in tropospheric aerosols.     

Laboratory investigation of flux reduction from dense non-aqueous phase liquid (DNAPL) partial source zone remediation by enhanced dissolution

This study investigated the benefits of partial removal of dense nonaqueous phase liquid (DNAPL) source zones using enhanced dissolution in eight laboratory scale experiments. The benefits were assessed by characterizing the relationship between reductions in DNAPL mass and the corresponding reduction in contaminant mass flux. Four flushing agents were evaluated in eight controlled laboratory experiments to examine the effects of displacement fluid property contrasts and associated override and underride on contaminant flux reduction (R(j)) vs. mass reduction (R(m)) relationships (R(j)(R(m))): 1) 50% ethanol/50% water (less dense than water), 2) 40% ethyl-lactate/60% water (more dense than water), 3) 18% ethanol/26% ethyl-lactate/56% water (neutrally buoyant), and 4) 2% Tween-80 surfactant (also neutrally buoyant). For each DNAPL architecture evaluated, replicate experiments were conducted where source zone dissolution was conducted with a single flushing event to remove most of the DNAPL from the system, and with multiple shorter-duration floods to determine the path of the R(j)(R(m)) relationship. All of the single-flushing experiments exhibited similar R(j)(R(m)) relationships indicating that override and underride effects associated with cosolvents did not significantly affect the remediation performance of the agents. The R(j)(R(m)) relationship of the multiple injection experiments for the cosolvents with a density contrast with water tended to be less desirable in the sense that there was less R(j) for a given R(m). UTCHEM simulations supported the observations from the laboratory experiments and demonstrated the capability of this model to predict R(j)(R(m)) relationships for non-uniformly distributed NAPL sources.     

Effect of Watershed Subdivision and Filter Width on SWAT Simulation of a Coastal Plain Watershed1

Cho, Jaepil, Richard R. Lowrance, David D. Bosch, Timothy C. Strickland, Younggu Her, and George Vellidis, 2010. Effect of Watershed Subdivision and Filter Width on SWAT Simulation of a Coastal Plain Watershed. Journal of the American Water Resources Association (JAWRA) 46(3):586-602. DOI: 10.1111/j.1752-1688.2010.00436.x Abstract: The Soil and Water Assessment Tool (SWAT) does not fully simulate riparian buffers, but has a simple filter function that is responsive to filter strip width (FILTERW). The objectives of this study were to (1) evaluate SWAT hydrology and water quality response to changes in watershed subdivision levels and different FILTERW configurations and (2) provide guidance for selecting appropriate watershed subdivision for model runs that include the riparian buffer feature through the FILTERW parameter. Watershed subdivision level is controlled by the critical source area (CSA) which defines the minimum drainage area required to form the origin of a stream. SWAT was calibrated on a 15.7 km² subdrainage within the Little River Experimental Watershed, Georgia. The calibrated parameter set was applied to 32 watershed configurations consisting of four FILTERW representations for each of eight CSA levels. Streamflow predictions were stable regardless of watershed subdivision and FILTERW configuration. Predicted sediment and nutrient loads from upland areas decreased as CSA increased when spatial variations of riparian buffers are considered. Sediment and nutrient yield at the watershed outlet was responsive to different combinations of CSA and FILTERW depending on selected in-stream processes. CSA ranges which provide stable sediment and nutrient yields at the watershed outlet was suggested for avoiding significant modifications in selected parameter set.     

Comparison of the removal efficiency of endocrine disrupting compounds in pilot scale sewage treatment processes

The removal efficiency of endocrine disrupting compounds from effluents using pilot scale sewage treatment processes, including various treatment technologies, such as membrane bioreactors (MBR), nanofiltration (NF) and reverse osmosis (RO) for the purpose of water reuse, were estimated and compared. The calculated estrogenic activity, expressed in ng-EEQ/l, based on the concentration detected by GC/MS, and relative potencies for each target compound were compared to those measured using the E-screen assay. The removal efficiencies for nonylphenol, was within the range of 55-83% in effluents. High removal efficiencies of approximately >70% based on the detection limits were obtained for bisphenol A, E1, EE2 and genistein with each treatment processes, with the exception of E1 ( approximately 64%) using the MBR process. The measured EEQ values for the effluents from the MBR, NF and RO processes also indicated low estrogenic activities of 0.65, 0.23 and 0.05 ng-EEQ/l, respectively. These were markedly reduced values compared with the value of 1.2 ng-EEQ/l in influent. Consequently, the removals of EDCs in terms of the EEQ value from the biological and chemical determinations were sufficiently achieved by the treatment process applied in this study, especially in the cases of the NF and RO treatments.     

Prediction of effluent concentration in a wastewater treatment plant using machine learning models

Of growing amount of food waste, the integrated food waste and waste water treatment was regarded as one of the efficient modeling method. However, the load of food waste to the conventional waste treatment process might lead to the high concentration of total nitrogen (T-N) impact on the effluent water quality. The objective of this study is to establish two machine learning models—artificial neural networks (ANNs) and support vector machines (SVMs), in order to predict 1-day interval T-N concentration of effluent from a wastewater treatment plant in Ulsan, Korea. Daily water quality data and meteorological data were used and the performance of both models was evaluated in terms of the coefficient of determination (R²), Nash–Sutcliff efficiency (NSE), relative efficiency criteria (d_rel). Additionally, Latin-Hypercube one-factor-at-a-time (LH-OAT) and a pattern search algorithm were applied to sensitivity analysis and model parameter optimization, respectively. Results showed that both models could be effectively applied to the 1-day interval prediction of T-N concentration of effluent. SVM model showed a higher prediction accuracy in the training stage and similar result in the validation stage. However, the sensitivity analysis demonstrated that the ANN model was a superior model for 1-day interval T-N concentration prediction in terms of the cause-and-effect relationship between T-N concentration and modeling input values to integrated food waste and waste water treatment. This study suggested the efficient and robust nonlinear time-series modeling method for an early prediction of the water quality of integrated food waste and waste water treatment process.     

3D QSAR studies of dioxins and dioxin-like compounds using CoMFA and CoMSIA

In the present study we have performed comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) on structurally diverse ligands of Ah (dioxin) receptor to explore the physico-chemical requirements for binding. All CoMFA and CoMSIA models have given q(2) value of more than 0.5 and r(2) value of more than 0.84. The predictive ability of the models was validated by an external test set, which gave satisfactory predictive r(2) values. Best predictions were obtained with CoMFA model of combined modified training set (q(2) = 0.631, r(2) = 0.900), giving predictive residual value = 0.02 log unit for the test compound. Addition of CoMSIA study has elucidated the role of hydrophobicity and hydrogen bonding along with the effect of steric and electrostatic properties revealed by CoMFA. We have suggested a model comprises of four structurally different compounds, which offers a good predictability for various ligands. Our QSAR model is consistent with all previously established QSAR models with less structurally diverse ligands.     

Case study analysis of the financial impact of catastrophic safety events

Several catastrophic events in the process industry have caused extensive damage to life and property and have forever changed the process safety landscape. Despite the commitment from the industry, incidents still occur with similar root causes, impacting major companies in various ways. This work examines the financial impact of such incidents on the stability and future of affected companies in different industries. Several devastating incidents were analyzed to evaluate the direct impact in the short- and long-term and to discuss factors influencing the ability of affected companies to withstand the consequence of catastrophic events.     

Measurement of Particulate Bound Mercury,Gaseous Elemental Mercury,and Reactive Gaseous Mercury Concentrations by Using an Ambient Air Mercury Collection System

In this investigation, the concentrations of gaseous elemental mercury (GEM), reactive gaseous mercury (RGM) and particulate bound mercury (PBM) in ambient air were measured at the Hung Kuang (traffic) sampling site during September 27 to October 6, 2014. An ambient air mercury collection system (AAMCS) was utilized to measure simultaneously PBM, GEM, and RGM concentrations in ambient air. The results thus obtained demonstrate that the mean concentrations of PBM, GEM, and RGM were 38.57 ± 11.4 (pg/m³), 17.67 ± 5.56 (ng/m³) and 10.78 ± 2.8 (pg/m³), respectively, at this traffic-sampling site. The mean GEM/PBM and GEM/RGM concentration ratios were 458 and 1639, respectively. The results obtained herein demonstrate that AAMCS can be utilized to collect three phases of mercury simultaneously. The mean PBM, GEM, and RGM concentrations herein were compared with others found in Asia, America, Europe and Antarctica. The mean PBM, GEM, and RGM concentrations were found to be lowest in Asia and Antarctica. The mean PBM concentration in Europe was approximately eight times that in this investigation. The mean GEM and RGM concentrations in this study were 1.21 and 170 times those found in the United States.