A dynamic compartment model for assessing the transfer of radionuclide deposited onto flooded rice-fields

A dynamic compartment model has been studied to estimate the transfer of radionuclides deposited onto flooded rice-fields after an accidental release. In the model, a surface water compartment and a direct shoot-base absorption from the surface water to the rice-plant, which are major features discriminating the present model from the existing model, has been introduced to account for the flooded condition of rice-fields. The model has been applied to the deposition experiments of 137Cs on rice-fields that were performed at three different times to simulate the deposition before transplanting (May 2) and during the growth of the rice (June 1 and August 12), respectively. In the case of the deposition of May 2, the root-uptake is the most predominant process for transferring 137Cs to the rice-body and grain. When the radionuclide is applied just after transplanting (June 1), the activity of the body is controlled by the shoot-base absorption and the activity of the grain by the root-uptake. The deposition just before ear-emergence (August 12) shows that the shoot-base absorption contributes entirely to the increase of both the activities of the body and grain. The model prediction agrees within one or two factors with the experimental results obtained for a respective deposition experiment.     

Odor and gas release from anaerobic treatment lagoons for swine manure

Odor and gas release from anaerobic lagoons for treating swine waste affect air quality in neighboring communities but rates of release are not well documented. A buoyant convective flux chamber (BCFC) was used to determine the effect of lagoon loading rate on measured odor and gas releases from two primary lagoons at a simulated wind speed of 1.0 m s(-1). Concentrations of ammonia (NH3), hydrogen sulfide (H2S), carbon dioxide (CO2), sulfur dioxide (SO2), and nitric oxide (NO) in 50-L air samples were measured. A panel of human subjects, whose sensitivity was verified with a certified reference odorant, evaluated odor concentration, intensity, and hedonic tone. Geometric mean odor concentrations of BCFC inlet and outlet samples and of downwind berm samples were 168 +/- 44 (mean +/- 95% confidence interval), 262 +/- 60, and 114 +/- 38 OU(E) m(-3) (OU(E), European odor unit, equivalent to 123 microg n-butanol), respectively. The overall geometric mean odor release was 2.3 +/- 1.5 OU(E) s(-1) m(-2) (1.5 +/- 0.9 OU s(-1) m(-2)). The live mass specific geometric mean odor release was 13.5 OU(E) s(-1) AU(-1) (animal unit = 500 kg live body mass). Overall mean NH3, H2S, CO2 and SO2 releases were 101 +/- 24, 5.7 +/- 2.0, 852 +/- 307, and 0.5 +/- 0.4 microg s(-1) m(-2), respectively. Nitric oxide was not detected. Odor concentrations were directly proportional to H2S and CO2 concentrations and odor intensity, and inversely proportional to hedonic tone and SO2 concentration (P < 0.05). Releases of NH3, H2S, and CO2 were directly proportional (P < 0.05) to volatile solids loading rate (VSLR).     

Improvement of thermal hydrolysis rate of dichloroacetic acid using alcohol

Dichloroacetic acid (DCAA) is produced during the oxidation of trichloroethylene. It is also produced in drinking water treatment as a disinfection by-product. DCAA is a problem material, because of its toxicity. The objective of this research is to find the final products and the reaction pathway of the DCAA decomposition by hydrolysis, and to increase the hydrolysis rate. The removal of both chlorine atoms in DCAA structure was achieved with hydrolysis at around 75 degrees C, and the final products were oxalic acid and glycolic acid. The reaction pathway was the production of oxalic acid and glycolic acid from two glyoxylic acid molecules by Cannizzaro reaction after the glyoxylic acid production from dechlorination of DCAA with hydrolysis. The hydrolysis rate of DCAA was increased with the use of 90% ethanol solution as solvent. The activation energy of DCAA was about 80 kJ/mol in it, while it was around 105 kJ/mol in water.     

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(R~2), 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.     

MINIMIZING THE IMPACT OF URBANIZATION ON LONG TERM RUNOFF1

Increasing concern about the problems caused by urban sprawl has encouraged development and implementation of smart growth approaches to land use management. One of the goals of smart growth is water resources protection, in particular minimizing the runoff impact of urbanization. To investigate the magnitude of the potential benefits of land use planning for water resources protection, possible runoff impacts of historical and projected urbanization were estimated for two watersheds in Indiana and Michigan using a long term hydrological impact analysis model. An optimization component allowed selection of land use change placements that minimize runoff increase. Optimizing land use change placement would have reduced runoff increase by as much as 4.9 percent from 1973 to 1997 in the Indiana study watershed. For nonsprawl and sprawl scenarios in the Michigan watershed for 1978 to 2040, optimizing land use change placement would have reduced runoff increase by 12.3 percent and 20.5 percent, respectively. The work presented here illustrates both an approach to assessing the magnitude of the impact of smart growth and the significant potential scale of smart growth in moderating runoff changes that result from urbanization. The results of this study have significant implications for urban planning.     

Process evaluation for optimization of EDTA use and recovery for heavy metal removal from a contaminated soil

This study aimed to establish an optimized, closed loop application of ethylenediaminetetraacetic acid (EDTA) in heavy metal removals from a contaminated soil through integrating EDTA recovery/regeneration and metal precipitation processes in the treatment train. Three divalent heavy metals were investigated, namely, Pb, Cd, and Ni. The extractability of the metals by EDTA followed the decreasing order of CdPb>Ni. The first part of this study was to search for the optimal use of the fresh EDTA in removing these heavy metals from the contaminated soil. The second part of this study was devoted to the recovery/regeneration of the spent EDTA which followed the sequential processes involving (1) complex destabilization by adding ferric ion (Fe(III)) to liberate Pb, Cd, and Ni, (2) precipitation of the liberated Pb, Cd, and Ni in phosphate (PO4(3-)) forms, and (3) precipitation of the excess Fe(III) which eventually produced free EDTA for reuse. The process variables were dosages of Fe(III) and PO4(3-), pH and reaction times. Laborious trial experiments would be needed in searching for the optimum conditions for the above processes. To expedite this exercise, a geochemical equilibrium model, MINTEQA2, was used to find the thermodynamically favorable conditions for recoveries of both EDTA and heavy metals. This was then followed by experimental examination of the process kinetics to observe for the optimal reaction time for each thermodynamically favorable process. This study revealed that 2 h of reaction time each for the complex destabilization reaction and the metal phosphate precipitation reaction was sufficient to achieve equilibrium. With the optimized process condition identified in this study, a total of 95%, 89% and 90% of the extracted Pb, Cd and Ni, respectively, could be precipitated from the spent EDTA solution, with 84% EDTA recovery. The reused EDTA maintained more than 90% of its preceding extraction power in each cycle of reuse.     

Reductive dechlorination of 1,2,4-trichlorobenzene with palladized nanoscale Fe(zero-valent) particles supported on chitosan and silica

In this study, nanoscale Pd-Fe particles, with diameters less than 100 nm, were synthesized and dispersed over the chitosan and silica supports. Three different Pd-Fe particles were synthesized, namely 0.1% Pd-Fe, 0.5% Pd-Fe and 1.0% Pd-Fe. SEM images confirmed that the Pd-Fe particles were dispersed over the surface of the supports while SEM-EDX confirmed evenly distribution of Pd over Fe(zero-valent). alpha-Fe(zero-valent) crystallites were identified by means of XRD and observed in TEM. Reductive dechlorinations of 1,2,4-trichlorobenzene (1,2,4-TCB) with the nanoscale Pd-Fe/chitosan and Pd-Fe/silica were carried out in the batch experiment system. Disappearance of the parent species and formation of the reaction intermediates and end product were monitored at discrete times. The results show that the nano-scale Pd-Fe particles were able to completely dechlorinate the chlorinated benzenes within a very short timescale. Complete dechlorinations of 1,2,4-TCB to benzene were achieved within 60 min with the 1.0% Pd-Fe/chitosan and within 100 min with the 1.0% Pd-Fe/silica. Reaction rates were observed to increase with increasing Pd content of the Pd-Fe/support. The reactions apparently followed pseudo-first-order kinetics with respect to the 1,2,4-TCB transformation. A kinetic model is constructed to fit the experimental results for the reactions, enabling identification of the major and minor dechlorination pathways of 1,2,4-TCB. The model suggests that the 1,2,4-TCB transformation mainly followed the primary pathway of direct reductive dechlorination to benzene and secondary pathway of sequential hydrogenolysis to 1,2-dichlorobenzene (1,2-DCB) and then chlorobenzene (CB) or benzene.     

Quality assured measurements of animal building emissions: gas concentrations

Comprehensive field studies were initiated in 2002 to measure emissions of ammonia (NH3), hydrogen sulfide (H2S), carbon dioxide (CO2), methane (CH4), nonmethane hydrocarbons (NMHC), particulate matter <10 microm in diameter, and total suspended particulate from swine and poultry production buildings in the United States. This paper focuses on the quasicontinuous gas concentration measurement at multiple locations among paired barns in seven states. Documented principles, used in air pollution monitoring at industrial sources, were applied in developing quality assurance (QA) project plans for these studies. Air was sampled from multiple locations with each gas analyzed with one high quality commercial gas analyzer that was located in an environmentally controlled on-farm instrument shelter. A nominal 4 L/min gas sampling system was designed and constructed with Teflon wetted surfaces, bypass pumping, and sample line flow and pressure sensors. Three-way solenoids were used to automatically switch between multiple gas sampling lines with > or =10 min sampling intervals. Inside and outside gas sampling probes were between 10 and 115 m away from the analyzers. Analyzers used chemiluminescence, fluorescence, photoacoustic infrared, and photoionization detectors for NH3, H2S, CO2, CH4, and NMHC, respectively. Data were collected using personal computer-based data acquisition hardware and software. This paper discusses the methodology of gas concentration measurements and the unique challenges that livestock barns pose for achieving desired accuracy and precision, data representativeness, comparability and completeness, and instrument calibration and maintenance.