Statistical determination of the optimal sample size of secondary effluent BOD5 and SS

A statistical technique is presented for determining the optimal sample size required to estimate the true geometric mean with an allowable error at a desired level of confidence. Attention is focused on its application in the monitoring of secondary effluent BOD₅ and SS. It is concluded that continuous monitoring of effluent BOD₅ or SS throughout the year may generate much more data than are required for practical purposes. This statistical method may be used by operators or regulatory agencies to formulate cost-effective monitoring schemes. Records of the sample size data of secondary effluent BOD₅ and SS across Canada are also discussed.     

Serial batch leaching procedure for characterization of coal fly ash

Although many leaching methods have been used for various purposes by research groups, industries, and regulators, there is still a need for a simple but comprehensive approach to leaching coal utilization by-products and other granular materials in order to estimate potential release of heavy metals when these materials are exposed to natural fluids. A serial batch characterization method has been developed at the National Energy Technology Laboratory that can be completed in 2–3 days to serve as a screening tool. The procedure provides an estimate of cumulative metals release under varying pH conditions, and leaching the sample at increasing liquid/solid ratios can indicate the rate at which this process will occur. This method was applied to eight fly ashes, adapted to the acidic or alkaline nature of the ash. The leachates were analyzed for 30 elements. The test was run in quadruplicate, and the relative standard deviation (RSD) was used as a measure of method reproducibility. RSD values are between 0.02 and 0.70, with the majority of the RSD values less than 0.3. The serial batch leaching procedure was developed as a simple, relatively quick, yet comprehensive method of estimating the risk of heavy metal release from fly ash when it is exposed to natural fluids, such as acid rain or groundwater. Tests on a random selection of coal fly ashes have shown it to be a reasonably precise method for estimating the availability and long-term release of cations from fly ash.     

Function Approximation and Documentation of Sampling Data Using Artificial Neural Networks

Biodiversity studies in ecology often begin with the fitting and documentation of sampling data. This study is conducted to make function approximation on sampling data and to document the sampling information using artificial neural network algorithms, based on the invertebrate data sampled in the irrigated rice field.Three types of sampling data, i.e., the curve species richness vs. the sample size, the curve rarefaction, and the curve mean abundance of newly sampled species vs.the sample size, are fitted and documented using BP (Backpropagation) network and RBF (Radial Basis Function) network. As the comparisons, The Arrhenius model, and rarefaction model, and power function are tested for their ability to fit these data. The results show that the BP network and RBF network fit the data better than these models with smaller errors.BP network and RBF network can fit non-linear functions (sampling data) with specified accuracy and don't require mathematical assumptions. In addition to the interpolation, BP network is used to extrapolate the functions and the asymptote of the sampling data can be drawn. BP network cost a longer time to train the network and the results are always less stable compared to the RBF network. RBF network require more neurons to fit functions and generally it may not be used to extrapolate the functions. The mathematical function for sampling data can be exactly fitted using artificial neural network algorithms by adjusting the desired accuracy and maximum iterations. The total numbers of functional species of invertebrates in the tropical irrigated rice field are extrapolated as 140 to 149 using trained BP network, which are similar to the observed richness.     

Probabilistic Modelling of Cattle Farm Distribution in Australia

A probabilistic Bayesian method called weights of evidence (WofE) was used to develop a synthetic dataset of cattle farm locations at a national scale across Australia. The synthetic dataset was required for the modelling of livestock movements with a view to assessing biosecurity implications. The WofE method is based on the analysis of spatial relationships between evidential patterns with respect to an event, such as the actual location of a farm. The evidential patterns of cattle farms were derived from maps of land use, land tenure, drainage systems, roads, settlements and long-term averaged rainfall. These evidential patterns were used for delineating and ranking land areas suitable for cattle farming. For each evidential pattern statistics such as a positive weight, a negative weight and a contrast were calculated for estimating the degree of correlation between the evidential patterns and known farm locations. The integrated evidential patterns of known farms were then used for estimating posterior probabilities and splitting land into five different classes according to its suitability for farming.

Soil Gas Volatile Organic Compound Concentration Contours for Locating Vadose Zone Nonaqueous Phase Liquid Contamination

Diffusion of VOC from cylindrical vadose zone domains contaminatedwith distributed nonaqueous phase liquid is examined in the steadystate approximation. The effects of first-order biodegradation and ofan extended underlying pool of LNAPL floating on the water table belowthe cylindrical domain are explored by means of an orthogonal functionsapproach. The distribution of VOC in the vadose zone above a floatingcircular LNAPL pool of finite size is explored by a numerical method.The results provide information useful in estimating the spacing anddepth at which soil gas samples should be taken in order to detect thepresence of such source areas. Comparison of model results with soilgas VOC measurements at various depths also provides insight into theextent to which natural biodegradation of the VOCs is taking place.     

A method to combine non-probability sample data with probability sample data in estimating spatial means of environmental variables

In estimating spatial means of environmental variables of a region from datacollected by convenience or purposive sampling, validity of the results canbe ensured by collecting additional data through probability sampling. Theprecision of the estimator that uses the probability sample can beincreased by interpolating the values at the nonprobability sample points tothe probability sample points, and using these interpolated values as anauxiliary variable in the difference or regression estimator. Theseestimators are (approximately) unbiased, even when the nonprobability sampleis severely biased such as in preferential samples. The gain in precisioncompared to the estimator in combination with Simple Random Samplingis controlled by the correlation between the target variable andinterpolated variable. This correlation is determined by the size (density)and spatial coverage of the nonprobability sample, and the spatialcontinuity of the target variable. In a case study the average ratio of thevariances of the simple regression estimator and estimator was 0.68for preferential samples of size 150 with moderate spatial clustering, and0.80 for preferential samples of similar size with strong spatialclustering. In the latter case the simple regression estimator wassubstantially more precise than the simple difference estimator.     

Assessing Spatial, Temporal, and Analytical Variation of Groundwater Chemistry in a Large Nuclear Complex, USA

Statistical analyses were applied at the Hanford Site, USA, to assess groundwater contamination problems that included (1) determining local backgrounds to ascertain whether a facility is affecting the groundwater quality and (2) determining a ‘pre-Hanford' groundwater background to allow formulation of background-based cleanup standards. The primary purpose of this paper is to extend the random effects models for (1) assessing the spatial, temporal, and analytical variability of groundwater background measurements; (2) demonstrating that the usual variance estimate s ², which ignores the variance components, is a biased estimator; (3) providing formulas for calculating the amount of bias; and (4) recommending monitoring strategies to reduce the uncertainty in estimating the average background concentrations. A case study is provided. Results indicate that (1) without considering spatial and temporal variability, there is a high probability of false positives, resulting in unnecessary remediation and/or monitoring expenses; (2) the most effective way to reduce the uncertainty in estimating the average background, and enhance the power of the statistical tests in general, is to increase the number of background wells; and (3) background for a specific constituent should be considered as a statistical distribution, not as a single value or threshold. The methods and the related analysis of variance tables discussed in this paper can be used as diagnostic tools in documenting the extent of inherent spatial and/or temporal variation and to help select an appropriate statistical method for testing purposes.     

Estimating means and variances: The comparative efficiency of composite and grab samples

This paper compares the efficiencies of two sampling techniques for estimating a population mean and variance. One procedure, called grab sampling, consists of collecting and analyzing one sample per period. The second procedure, called composite sampling, collectsn samples per period which are then pooled and analyzed as a single sample. We review the well known fact that composite sampling provides a superior estimate of the mean. However, it is somewhat surprising that composite sampling does not always generate a more efficient estimate of the variance. For populations with platykurtic distributions, grab sampling gives a more efficient estimate of the variance, whereas composite sampling is better for leptokurtic distributions. These conditions on kurtosis can be related to peakedness and skewness. For example, a necessary condition for composite sampling to provide a more efficient estimate of the variance is that the population density function evaluated at the mean (i.e.f()) be greater than . If , then a grab sample is more efficient. In spite of this result, however, composite sampling does provide a smaller estimate of standard error than does grab sampling in the context of estimating population means.     

Comparison between electrofishing and snorkeling surveys to describe fish assemblages in Laurentian streams

We evaluated the relative performance of electrofishing and visual surveys (snorkeling) for estimating the abundance of combinations of fish species and size classes in rivers. We also assessed the effect of environmental conditions on potential differences between the results obtained using these two sampling methods. Sampling sites were distributed in the Laurentian region of Québec. Both methods were used while sections were blocked. Three snorkelers swam the river sections upstream while identifying and counting fish of each species and size classes. Three-pass electrofishing was performed in the same sites and abundances were estimated with a maximum likelihood depletion model. Greater abundances of fish were observed by snorkeling than by electrofishing at all sites. Snorkeling species richness was higher or equal to electrofishing richness in, respectively, 60 % and 40 % of sampled sites. Differences in the fish communities observed by both sampling methods were not related to environmental conditions. The results of our work are therefore contrary to that of most published studies that suggested the use of electrofishing over visual surveys. This study highlights that conclusions derived from previous work on sampling gear comparisons may not be generalisable; rather survey methods might benefit from being selected based on fish community composition.     

A feasible method to assess inaccuracy caused by patchiness in water quality monitoring

Patchiness is a typical property of water quality in lakes. However, in conventional water quality monitoring, patchiness is usually too expensive to take into account, due to the high number of required samples. This study examines a feasible methodology developed for estimating the representativeness of discrete chlorophyll a measurements. Four spatially extensive data sets were collected from the Enonselkä basin of Lake Vesijärvi in Southern Finland, using a flow trough system with a fluorometer in a moving boat. Data sets were used to estimate (1) the spatial representativeness of discrete sampling; (2) the effect of varying sample size on the detected mean chlorophyll a concentration and on the observed proportion of variance. Spatial representativeness was assessed using semivariogram analysis. Results indicate that the spatial representativeness of discrete sampling can remain undesirably low. Furthermore, in monitoring programs involving just one or only a few samples, there is a significant risk of obtaining a false estimate for the mean value and variance of chlorophyll a concentration over the whole monitoring area.     

A low-cost towed video camera system for underwater surveys: comparative performance with standard methodology

Technological advances in the field of underwater video have led to an exponential increase in the use of drifting cameras (DC) and remotely operated vehicles (ROVs) to monitor the diversity, abundance, and size structure of marine life. Main advantages of DCs relative to ROVs are their lower costs and the much simpler logistics required to operate them. This study compares the performance of a new low-cost DC system equipped with a novel measuring device with that of a standard DC bearing an array of laser pointers. The new DC, which can be operated from a small boat, carries a pair of parallel steel “whiskers” that are dragged on the seabed within the field of view of the camera, providing a scale for measuring and estimating the density of benthic biota. An experiment conducted using an array of objects of known sizes laid on the bottom showed that its performance in terms of both size and density estimation was similar to that of the standard technique based on laser pointers. Measurement errors had a negligible negative bias (??2.3%) and a standard deviation that ranged between 13 and 8% for objects from 25 to 110 mm in size. The whiskers offered a simplified method for density estimation that avoids the need to calculate the width of the field of view, thus reducing the video processing time by around 60% with respect to the standard method. Briefly, the new system offers an efficient low-cost alternative for benthic ecology studies conducted on soft or non-irregular bottoms.     

What do qualitative rapid assessment collections of macroinvertebrates represent? A comparison with extensive quantitative sampling

It is a fundamental tenet of Rapid Biological Assessments (RBA) that the samples collected reflect the community from which they are drawn. As with any biological sampling, RBA collections are subject to sampling error resulting in the omission of some taxa. The aim of this study is to compare the composition of RBA samples with an estimate of community structure based on extensive quantitative sampling. We used logistic regression to explore the relationships between the frequency of a taxon being collected in an RBA sample and its biological and ecological traits, namely its abundance, distribution, body size and habit. RBA samples and quantitative estimates of community structure were made in riffles in the Kangaroo and Nepean Rivers, New South Wales, Australia. Single RBA samples may collect up to 63% of the taxa that are collected by extensive quantitative sampling at a site. The frequency of a taxon being recorded in an RBA sample was significantly and positively related to all traits tested indicating a bias in the collection methods towards large, abundant and widely distributed taxa. Accordingly, taxa missed by RBA sampling were generally small, narrowly distributed or rare. These findings enhance our understanding of what RBA samples represent, and the bias and source of errors associated with RBA sampling. This study also quantifies the utility of RBA methods for biodiversity assessment.     

Optimum Methods of Inactivation of Strongyloides stercoralis Larvae from Reclaimed Wastewater

Strongyloidiasis presents a major health hazard when reusing wastewater. Albendazol with a concentration of 4 mg/l, a contact time of 45 min, pH 1.2 and pH 10.2, killed the larva. The larva was also killed with a 0.03% concentration of iodine and a detention time of 30 min or a 0.04% concentration of iodine and a contact time of 10 min. The required detention time to inactivate larva in water was found to be 17 days. The minimum revealed residual chlorine to kill the larvae was 4 mg/l with 120 min of detention time, and a minimum contact time was found to be 80 min with a residual of 23 mg/l. Many methods are available to inactivate the Strongyloides stercoralis, which could be acids, alkaline chemicals, larvicidal chemicals, super chlorination, or just detention time. The best method must be determined according to the prevailing specific environmental site and the feasibility of the selected method(s).     

Reliability of differing densities of sample grids used for the monitoring of forest condition in Europe

Concern about the possible deterioration of forest health led to the establishment in the 1980s of inventories of forest condition throughout Europe. International standardisation of the programmes was sought and a number of recommendations were made concerning sampling and assessment procedures. One of the most important rulings was that the assessment should be made on a systematic grid, the minimum density of which was 16×16 km. However, many countries adopted denser sampling grids, with 4×4 km being used in several countries and 1×1 km being used in the Netherlands. With five or more years of monitoring completed, there is a growing belief that a rapid and irreversible decline in forest health is not occurring. Consequently, some countries/regions are seeking to reduce their annual investment in forest health monitoring.The precision of national/regional estimates of forest health can be directly related to the sample size. As the sample size decreases, so also does the precision of the estimates. This is illustrated using data collected in Switzerland in 1992 and using grid densities of 4×4 km, 8×8 km, 12×12 km and 16×16 km. The value of the data is dependent on the sample size and the degree to which it is broken down (by region or species). The loss of precision associated with most subdivisions at the 8×8 km grid level remains acceptable, but a sharp deterioration in the precision occurs at the 12×12 km and 16×16 km grid levels. This has considerable implications for the interpretation of the inventories from those countries using a 16×16 km grid. In Switzerland, a reduction from the current 4×4 km grid to an 8×8 km grid (i.e. 75% reduction in sample size) would have relatively little impact on the overall results from the annual inventories of forest health.     

Even sampling designs generation by charges repulsion simulation

Evenly distributed sampling design is generally considered as an efficient sampling design. It is widely used in sampling for the environmental survey. In this paper, we present a novel method for generating N evenly distributed samples within a given irregular polygon via simulating the movements of some ideal homogeneous point charges. Initially, charges are randomly put into the sampling region; then, they are freed and held orderly; and after enough runs, the charges will finally reach a stable state with all of them having a zero resultant force and velocity; and so they distribute evenly within the region. Their layout can thus be considered as an evenly distributed sampling design. The main advantages of this method are: (1) it is easy to understand and implement; (2) it is efficient in both running and generating better designs. Analysis and experimental results indicate that this method is an efficient and robust method for generating even sampling designs for 2D polygonal sampling region.     

Potential Applications for Pyrolysis-GC/MS in Bioremediation

Preliminary data are presented from a set of experiments designed to promote the use of pyrolysis-GC/MS in bioremediation. Studies were designed to aid researchers in developing a pyrolysis-GC/MS method and identifying how the method could help characterize bioremediation, particularly in organic soils. Since sample size affects the results of pyrolytic analyses, the first experiment demonstrated how an appropriate sample size might be selected for pyrolysis-GC/MS testing. In order to show how quantitative results can be obtained from pyrolysis-GC/MS, a second experiment determined the 'goodness of fit' for a standard curve relating the chromatographic area under a pyrogram to actual mass units. The third experiment investigated ways in which pyrolysis-GC/MS analyses could improve our understanding of bioremediation in organic soils contaminated with crude oil. Experimental results confirmed that differences in analyte mass affect the extent of pyrolytic cracking. In pyrograms of the test soil, the ratio of toluene to total product showed that for a sample mass between 1.8 and 2.0 mg, variability in the cracking pattern was minimized. Unlike deviations outside this range, small deviations within the range did not appreciably effect the toluene ratio. A standard curve was prepared for pyrolytic analyses by plotting the total chromatographic area of all pyrolysis products versus the mass of organic material pyrolyzed. These data were fit with a straight line having an 'R²' of 0.73. Based on a bench scale bioremediation experiment, preliminary pyrolysis-GC/MS results were used to predict that compounds derived from lignin and carbohydrates would be degraded faster in uncontaminated than contaminated soils. Appreciable degradation of both compounds, however, occurred in contaminated soils. In addition, results suggested that using pyrolysis-GC/MS to quantify the sum of all n-alkanes and the ratio of odd to even chain n-alkanes could help researchers distinguish between the degradation of petroleum and non-petroleum hydrocarbons in contaminated and uncontaminated soils.     

For What Applications Can Probability and Non-Probability Sampling Be Used?

Almost any type of sample has some utilitywhen estimating population quantities. The focus inthis paper is to indicate what type or combination oftypes of sampling can be used in various situationsranging from a sample designed to establishcause-effect or legal challenge to one involving asimple subjective judgment. Several of these methodshave little or no utility in the scientific area buteven in the best of circumstances, particularlycomplex ones, both probabilistic and non-probabilisticprocedures have to be used because of lack ofknowledge and cost. We illustrate this with a marbledmurrelet example.     

Use of Australian cladocerans to generate life-cycle toxicity data

Cladocerans (or water-fleas) are important animals in freshwater exosystems. They are widely used in toxicity tests because of their small size, ease of culture, and sensitivity to chemicals. They are particularly suited to life-cycle tests because newly-hatched young can produce offspring in less than one week. Most data are available for European and North American species, and may be not be appropriate to Australian conditions. In the present study, eight Australian cladocerans were evaluated in three-brood life-cycle tests over ten days or less. Species were evaluated by duration of life cycle, ease of handling, numbers of young produced in three broods, and stability in laboratory culture.Ceriodaphnia cfdubia was the best test species. The greatest number of young, the highest survival rate and the shortest time to produce three broods were achieved in filtered Sydney mains water, aged in the presence of fish, using blended trout pellets and alfalfa as food.     

Determining subsampling effort for the development of a rapid bioassessment protocol using benthic macroinvertebrates in streams of Southeastern Brazil

The purpose of this study was to establish a subsampling procedure for benthic macroinvertebrates to aid in the development of a multimetric index to assess the biological condition of streams. Data from six streams that are considered minimally impaired were used. Subsampling was done using a device divided into 24 quadrats. The sediment from each quadrat was sorted, and all organisms were removed and identified. Richness metrics were the most affected by subsample size. Relative-abundance metrics were the most stable, proving that the sample was well distributed throughout the tray and abundance proportions were maintained. The results showed that the macroinvertebrate assemblage present in the six quadrats was similar to that present in the full sample. These analyses indicated that six quadrats, randomly designated, with a minimum of 200 collected specimens could be used in place of the full sample. In routine water management, managing time and costs are a major challenge; therefore, this type of simplification is absolutely necessary to ensure that a biomonitoring tool is useful for practical applications.     

三重四极杆质谱技术测定固体废弃物中多氯联苯

以二氯甲烷为萃取剂,采用快速溶剂萃取、凝胶渗透色谱净化、三重四极杆质谱技术测定固体废弃物中7种多氯联苯单体,选择十氯联苯为内标物,2,4,5,6-四氯间二甲苯为替代物。质谱采用MRM扫描,优化了目标物质保留时间、母离子和子离子质量数及碰撞能量等参数。方法在0.050 mg/L～2.00 mg/L范围内线性良好,7种多氯联苯单体的检出限为0.194 ng/g～0.355 ng/g(以称取30 g样品、定容至2.0 mL计),标准样品回收率多在60%～105%之间,空白加标样品测定值的相对标准偏差在8.6%～13.0%之间。