Field evaluation of resistivity sensors for in situ moisture measurement in a bioreactor landfill

The ability of resistance-based sensors to measure in situ waste moisture content in a landfill was examined. One hundred and thirty-five resistance-based sensors were installed in a leachate recirculation well field at a bioreactor landfill in Florida, US. The performance of these sensors was studied for a period of over 6 years. The sensors were found to respond to an increase in moisture resulting from leachate recirculation. It was observed that 78% of sensors worked successfully in the field during the study period. The initial spatial average moisture content determined by the sensor readings (using a laboratory-derived calibration) was 42.8% compared to 23% from gravimetric readings. Eighteen sensors (13%) showed that they were saturated before liquid addition, and no change in moisture content was observed in these sensors during the study period. Laboratory-derived calibration methods resulted in an over-estimation of moisture content. An alternate field-calibration method, where wetted sensor output was assumed equal to the average of gravimetric measurements for wet samples, was evaluated. The final spatial average moisture contents were 64.2% and 44.4% for the laboratory-derived and field-derived calibration methodologies, respectively, compared to 45% measured gravimetrically from excavated waste samples. When moisture content was determined using a mass balance approach, the result was 34.6%. The results suggest that when appropriately calibrated, resistivity-based sensors can be used to obtain a reasonably accurate estimate of local moisture content. However, caution should be taken to extend the moisture content values that are representative of waste surrounding the sensors to estimate the overall moisture content on the landfill-wide scale.     

Formulation of a landfill pollution potential index to compare pollution potential of uncontrolled landfills

Generally speaking, landfilling is one of the prominent methods of waste disposal around the globe, but some under-developed and developing countries still continue to practice uncontrolled open dumping of waste. These uncontrolled landfills pose a relatively high threat to the various elements of the environment in comparison with the conventional engineered landfills that are used in many developed countries. However, some closed, un-engineered landfills do exist in developing countries. This paper presents a novel approach to compare the pollution potential of uncontrolled landfills using an index. The landfill pollution potential index (LPPI) has been developed using the Delphi technique and is an aggregation of six pollution indices that have already been developed for the quantification of different environmental elements. The LPPI is an increasing scale index, in which a higher index value indicates a higher pollution threat. The LPPI of a landfill in Delhi was calculated and the high LPPI value indicates that the respective landfill poses a significant threat to the environment. The LPPI can be used as an aid to diagnose a landfill's pollution potential relative to other landfills and therefore also to rank remediation investments.     

Lower Leg Injury Reference Values and Risk Curves from Survival Analysis for Male and Female Dummies: Meta-analysis of Postmortem Human Subject Tests

Objective: Derive lower leg injury risk functions using survival analysis and determine injury reference values (IRV) applicable to human mid-size male and small-size female anthropometries by conducting a meta-analysis of experimental data from different studies under axial impact loading to the foot–ankle–leg complex.

Methods: Specimen-specific dynamic peak force, age, total body mass, and injury data were obtained from tests conducted by applying the external load to the dorsal surface of the foot of postmortem human subject (PMHS) foot–ankle–leg preparations. Calcaneus and/or tibia injuries, alone or in combination and with/without involvement of adjacent articular complexes, were included in the injury group. Injury and noninjury tests were included. Maximum axial loads recorded by a load cell attached to the proximal end of the preparation were used. Data were analyzed by treating force as the primary variable. Age was considered as the covariate. Data were censored based on the number of tests conducted on each specimen and whether it remained intact or sustained injury; that is, right, left, and interval censoring. The best fits from different distributions were based on the Akaike information criterion; mean and plus and minus 95% confidence intervals were obtained; and normalized confidence interval sizes (quality indices) were determined at 5, 10, 25, and 50% risk levels. The normalization was based on the mean curve. Using human-equivalent age as 45 years, data were normalized and risk curves were developed for the 50th and 5th percentile human size of the dummies.

Results: Out of the available 114 tests (76 fracture and 38 no injury) from 5 groups of experiments, survival analysis was carried out using 3 groups consisting of 62 tests (35 fracture and 27 no injury). Peak forces associated with 4 specific risk levels at 25, 45, and 65 years of age are given along with probability curves (mean and plus and minus 95% confidence intervals) for PMHS and normalized data applicable to male and female dummies. Quality indices increased (less tightness-of-fit) with decreasing age and risk level for all age groups and these data are given for all chosen risk levels.

Conclusions: These PMHS-based probability distributions at different ages using information from different groups of researchers constituting the largest body of data can be used as human tolerances to lower leg injury from axial loading. Decreasing quality indices (increasing index value) at lower probabilities suggest the need for additional tests. The anthropometry-specific mid-size male and small-size female mean human risk curves along with plus and minus 95% confidence intervals from survival analysis and associated IRV data can be used as a first step in studies aimed at advancing occupant safety in automotive and other environments.     

Effect of commercial pesticides on plant growth-promoting activities of Burkholderia sp. strain L2 isolated from rhizosphere of Lycopersicon esculentum cultivated in agricultural soil

The in vitro study was carried out to examine the toxicity of four commercially used pesticides (phorate, mancozeb, chlorpyrifos, and endosulfan) at the recommended dose (1X) and higher field doses (1.5X, 2X, 2.5X, and 3X) on plant growth-promoting activities of Burkholderia sp. strain L2, isolated from pesticide-treated rhizosphere of Lycopersicon esculentum. At the recommended dose, level of toxicity of all the pesticides to phosphate solubilization activity and indole-3-acetic acid (IAA) production was less detrimental as compared to exceeding doses. At maximum dose rate of each pesticide, the percentage decrease in phosphate solubilization and IAA production over control was found in order of chlorpyrifos < mancozeb < endosulfan < phorate. Present study proves that Burkholderia sp. strain L2 could be used as a potential microbial inoculant in the agricultural soil having persistent pesticide residues.     

Physiologically based pharmacokinetic modeling of perfluoroalkyl substances in the human body

Currently, there are limited data on the levels of perfluoroalkyl substances other than perfluorooctane sulfonic acid and perfluorooctanoic acid in the human body. Most of this information has been extracted from biological monitoring of plasma while the occurrence of perfluoroalkyl substances in other human tissues is rarely studied. The objective of the present study was to develop a physiologically based pharmacokinetic model to assess the concentration of perfluoroalkyl substances in human tissues, based on an existing model previously validated for perfluorooctane sulfonic acid and perfluorooctanoic acid. Experimental data on concentrations of perfluoroalkyl substances in human tissues from individuals in Tarragona County (Catalonia, Spain) were used to estimate the values of some distribution and elimination parameters needed for the simulation. No significant correlations were found between these parameters and the chain lengths. The model was finally validated for five perfluoroalkyl substances.     

Water quality modelling of the river Yamuna (India) using QUAL2E-UNCAS

This paper describes the utility of QUAL2E as a modelling package in the evaluation of a water quality improvement programme. In this study, QUAL2E was applied to determine the pollution loads in the river Yamuna during its course through the national capital territory of Delhi, India. The study aimed at examining the influence of different scenarios on river water quality. Four different pollution scenarios were analysed besides the 'business as usual' situation. The study revealed that it was necessary to treat the discharge from drains to the river Yamuna and diversion of a substantial load to the Agra canal for further treatment was also essential. It was also established through this study that maintaining a flow rate of more than 10 m(3)/s in the river could also help preserve the river's water quality. To clearly display the model outcomes and demarcate polluted zones in the river stretch, model results were interfaced with a Geographical Information System (GIS) to produce cartographic outputs. In addition, uncertainty analysis in the form of first-order error analysis and Monte Carlo analysis was performed, to realise the effect of each model parameter on DO and BOD predictions. The uncertainty analysis gave satisfactory results on simulated data.