Simplified Methods for Statistical Interpretation of Monitoring Data

Statistical techniques are useful for interpretation of monitoring data for pollutants, process variables, etc. Simplified nomographical methods are presented for relating numbers of samples to confidence intervals for their mean values, and for determining the proportion of the population exceeding a specified concentration and confidence intervals for the proportion. A chart also is given for design of a sampling program for quality control. Illustrative frequency distribution data are given for hourly-averaged methane concentrations in air over three-week periods. They show trimodal lognormal distributions. These charts are applicable to lognormal distributions, as well as to normal distributions. They are convenient for many common problems.     

The Precision Associated with the Sampling Frequencies of Total Particulate at Indianapolis,Indiana

The frequency distribution of total suspended particulate matter for Indianapolis, Ind., was examined in order to determine the precision associated with any given sampling scheme. By assuming a basic log_e-normal distribution, a theoretical set of confidence intervals about the geometric mean was derived for random sampling. Verification of the log_e-normal distribution was made for particulate matter in Indianapolis. Application of the derived confidence intervals revealed that for a 30-day period 20 samples must be taken to ensure that the 90% confidence interval will be within 10% of the geometric mean. Analysis of the records for 19 sampling locations within Indianapolis revealed that only 2 sites possessed sufficient data to allow monthly climatological evaluation over the period 1968-1970.     

A Physical Explanation of the Lognormality of Pollutant Concentrations

Investigators In different environmental fields have reported that the concentrations of various measured substances have frequency distributions that are lognormal, or nearly so. That is, when the logarithms of the observed concentrations are plotted as a frequency distribution, the resulting distribution is approximately normal, or Gaussian, over much of the observed range. Examples include radionuclides in soil, pollutants in ambient air, Indoor air quality, trace metals In streams, metals in biological tissue, calcium In human remains. The ubiquity of the lognormal distribution in environmental processes is surprising and has not been adequately explained, since common processes in nature (for example, computation of the mean and the analysis of error) usually give rise to distributions that are normal rather than lognormal. This paper takes the first step toward explaining why lognormal distributions can arise naturally from certain physical processes that are analogous to those found in the environment. In this paper, these processes are treated mathematically, and the results are illustrated in a laboratory beaker experiment that Is simulated on the computer.     

A physical explanation of the lognormality of pollutant concentrations

Investigators in different environmental fields have reported that the concentrations of various measured substances have frequency distributions that are lognormal, or nearly so. That is, when the logarithms of the observed concentrations are plotted as a frequency distribution, the resulting distribution is approximately normal, or Gaussian, over much of the observed range. Examples include radionuclides in soil, pollutants in ambient air, indoor air quality, trace metals in streams, metals in biological tissue, calcium in human remains. The ubiquity of the lognormal distribution in environmental processes is surprising and has not been adequately explained, since common processes in nature (for example, computation of the mean and the analysis of error) usually give rise to distributions that are normal rather than lognormal. This paper takes the first step toward explaining why lognormal distributions can arise naturally from certain physical processes that are analogous to those found in the environment. In this paper, these processes are treated mathematically, and the results are illustrated in a laboratory beaker experiment that is simulated on the computer.     

Long-term assessment of the wet precipitation chemistry in Austria (1984-1999)

The aim of the present study was to determine the long-time trends in concentrations and depositions of major ions in wet precipitation samples collected at 11 sampling sites from the Austrian precipitation chemistry network in the period 1984-1999. The analytical results were treated by the use of least square linear regression method. It is shown that a serious decrease of sulfate (between 30% and 60% for the period) and hydrogen ion (between 60% and 102% for the period) concentrations and depositions is achieved at almost all sampling sites and in most of these cases the linear trend proves to be statistically significant. Nitrogen containing ions and base cations do not reveal a distinct trend of changing and in the majority of the sites the linear models are not adequate. In principle, an overall slight concentration and deposition decrease for these major ions is observed (up to 30% for the period of observation) but some substantial exceptions are also found (site Haunsberg or site Lobau). The changes in chloride concentration and deposition, too, do not indicate significant linear trend and, in general, are decreasing for the period of monitoring. In order to give some explanation of the exceptional behaviour of some of the major ions in several sites, an additional comparison with Austrian emission data (sulfur dioxide, nitrogen oxides, ammonium) and with data from five EMEP sites from neighbouring countries is performed. A significant West-East trend of acidity increase is found as well as a good correlation with the emission trends. Therefore, both transboundary and specific local factors could be substantial factors in the wet precipitation chemistry in the region.     

An air quality data analysis system for interrelating effects, standards, and needed source reductions: Part 13--Applying the EPA Proposed Guidelines for Carcinogen Risk Assessment to a set of asbestos lung cancer mortality data

The Clean Air Act Amendments of 1990 (CAAA-90) list 189 hazardous air pollutants (HAPs) for which "safe" ambient concentrations are to be determined. The primary purpose of this paper is to develop two mathematical models, lognormal and logarithmic, that effectively express excess lung cancer mortality as a function of asbestos concentration for an example set of data and also to suggest using these two models for additional HAPs. The secondary purpose of this paper is to calculate a "safe" asbestos concentration by first assuming a default linear extrapolation (to one excess death per million people, as specified for carcinogenic HAPs). The resulting "safe" concentration is an impossible-to-achieve 1/1000 of present background asbestos concentrations. A letter to the editor and a response in this Journal issue use additional asbestos data that suggest that the "safe" concentration should be about 730 times higher than first calculated here and that a default nonlinear extrapolation should be used instead, with the "safe" concentration proportional to the desired mortality level raised to the 0.39 power. These results suggest that the most important problem in setting a "safe" concentration for each carcinogenic HAP is to determine the correct nonlinear extrapolation to use for each HAP.     

Characterization of municipal waste in Kampala,Uganda

In Kampala, Uganda, about 28,000 tons of waste is collected and delivered to a landfill every month. Kampala Capital City Authority (KCCA) records show that this represents approximately 40% of the waste generated in the city. The remaining uncollected waste is normally dumped in unauthorized sites, causing health and environmental problems. However, the organic fraction of domestic waste can provide an opportunity to improve livelihoods and incomes through fertilizer and energy production. This study characterized the municipal waste generated in Kampala and delivered to Kiteezi landfill between July 2011 and June 2012, that is, covering the dry and wet months. On each sampling day, waste was randomly selected from five trucks, sorted and weighed into different physical fractions. Samples of the organic waste from each truck were analyzed for total solids, major nutrients, and energy content. During the wet months, the waste consisted of 88.5% organics, 3.8% soft plastics, 2.8% hard plastics, 2.2% paper, 0.9% glass, 0.7% textiles and leather, 0.2% metals, and 1.0% others. During the dry months, the waste consisted of 94.8% organics, 2.4% soft plastics, 1.0% hard plastics, 0.7% papers, 0.3% glass, 0.3% textile and leather, 0.1% metals, and 0.3% others. The organic waste on average had a moisture content of 71.1% and contained 1.89% nitrogen, 0.27% phosphorus, and 1.95% potassium. The waste had an average gross energy content of 17.3 MJ/kg. It was concluded that the organic waste generated can be a suitable source of some plant nutrients that are useful especially in urban agriculture.

Implications:?The result of the waste characterization in Kampala was found to be significantly different from that obtained for other Sub-Saharan African (SSA) cities, showing that studies assuming average values for the waste fractions are likely to result in erroneous results. Furthermore, no reduction in organic fraction of the waste was noticed when compared with a study done two decades ago in spite of greatly improved economic status of Kampala city, a finding that is not in agreement with several other similar studies done for other SSA cities.     

Fine organic aerosols collected in a humid,rural location (Great Smoky Mountains,Tennessee, USA): Chemical and temporal characteristics

Fine organic aerosols collected at the Great Smoky Mountain National Park, Tennessee (USA) during 15 July –25 August 1995 as part of the Southeastern Aerosol and Visibility Study (SEAVS) were chemically characterized. The water-soluble organic species (WSOS) often dominated over the solvent-soluble organic species (SSOS) at this remote, humid sampling site, contributing 76–98% of the total identified organic mass in 17 out of the 21 daytime samples analyzed. Nighttime samples tended to have slightly larger concentrations of total SSOS than the daytime, with nocturnal/diurnal organic mass ratios greater than 1.0 in 7 out of the 10 paired samples. However, for total WSOS mass, the nocturnal-to-diurnal ratios were less than 0.3 in 7 out of the 10 paired samples, reflecting much more substantial depletion and/or less production of the more polar organics during nighttime. Based on identified species, the organic-mass-to-organic-carbon (OM–OC) ratios at the SEAVS site are estimated as 2.0, 2.2, and 1.3 for the daytime total organics, WSOS, and SSOS, respectively. For the nighttime samples, the OM–OC ratio for total identified organics is estimated to be 1.8, slightly lower than the daytime ratio due to the smaller mass fraction of WSOS present at night.     

Statistical distributions of particulate matter and the error associated with sampling frequency

The distribution of particulate matter (PM) concentrations has an impact on human health effects and the setting of PM regulations. Since PM is commonly sampled on less than daily schedules, the magnitude of sampling errors needs to be determined. Daily PM data from Spokane, Washington were resampled to simulate common sampling schedules and the sampling error was computed for regulatory and distribution statistics. Probability density functions (pdf's) were fit to the annual daily data to determine the shape of the PM_2.5 and PM₈ concentration distributions and they were also fit to the less than daily sampling to determine if pdf's could be used to predict the daily high-concentration percentiles. There is an error when using a less than daily sampling schedule for all statistics. The error expressed as a percentage difference from the everyday sampling for the PM_2.5 mean was as large as 1.7, 3.4 and 7.7% and the 98th percentile error was as great as 8.8, 18 and 67% for 1-in-2 day, 1-in-3 day and 1-in-6 day sampling, respectively. For PM₈ the error in the mean was 2.5, 4.7 and 8.6% for and the error in the 99th percentile was 27, 18 and 46% for 1-in-2 day, 1-in-3 day, and 1-in-6 day sampling, respectively. The PM_2.5 and PM₈ concentration data were best fit by a three-parameter lognormal distribution and a generalized extreme value distribution, respectively. For PM_2.5 and PM₈, as the annual mean increased the mode concentration increased, but for PM₈ the shape of the distribution also flattened. Predicting the daily high percentiles from pdf's that were fit to the less than daily sampled data produced mixed results. For PM₈, the pdf's predicted high concentrations were closer to the daily percentiles than the actual less-than-daily sampling percentile while for PM_2.5 they were not.     

Mercury in European Blushers,Amanita rubescens,mushrooms and topsoils: Bioconcentration potential and intake assessment

Total mercury content has been determined in fruiting bodies of European Blushers and topsoils collected from 11 sites across Poland in 2006-2008. Mercury analysis was carried out using a validated analytical method and cold-vapour atomic absorption (CV-AAS). The European Blusher effectively accumulated mercury in fruiting bodies. The mean values of total mercury in caps of European Blushers from background (uncontaminated) areas were from 0.22 to 1.0 (0.067-3.2) and in stipes from 0.16 to 0.65 (0.071-2.7) μg/g dry weight. In topsoil beneath to fruiting bodies, the median Hg concentration at 10 sites in Northern Poland varied between 0.030 and 0.072 (0.0096–0.19) μg/g dw, and in one site in Southern Poland was 0.20 (0.079–0.34) μg/g dw. Data on Hg in European Blushers from different countries were reviewed. The mean concentrations of total Hg in caps of European Blushers from two “pristine” sites in northern part of Poland were ～1.0 μg/g dw. A meal made with 300–500 g of fresh caps of European Blushers collected at such sites (assuming 90% water content in caps) can result in Hg intake of 0.0003–0.0005 mg Hg/kg bm (assuming a 60 kg bm), which is a dose equipotent to a new provisional tolerable weekly intake (PTWI) value set for inorganic Hg.     

Biomonitoring of heavy metals and air quality in Cordoba City, Argentina, using transplanted lichens

The objective of the present study was to test the concentrations of some elements in the transplanted lichen Usnea amblyoclada transplanted in Córdoba, Argentina, and to investigate the relative air quality of the area as indicated by a Pollution Index. Analyses of Cu, Co. Pb, Fe, Ni, Mn, S and Zn in addition to analyses of physiological parameters were performed after the transplantation period. No significant differences were observed among the sampling stations for the physiological parameters, except the dry weight/fresh weight ratio. The concentration of most elements was similar to or lower than those found in non-polluted and even polluted areas. The significant correlation found between Cu, Pb and Zn with the content of hydroperoxy conjugated dienes suggests an important oxidative effect probably caused by these ions. The distribution patterns of the elements were quite similar, with maximum values around a cement plant and the metallurgical industries. The Pollution Index distribution pattern does not coincide with the elements distribution, due to the fact that the index values probably reflected the emissions of gaseous phytotoxic pollutants.     

Frequency distribution of dust concentration in Barbados as a function of averaging time

Two sets of daily-averaged dust concentration data from Barbados, West Indies, have been analyzed to determine the affect of averaging time, ranging from 1 to 7 days, on the dust concentration frequency distribution. On each of the time scales examined, the frequency distribution is characterized as a bimodal lognormal distribution. The major effects of increasing the averaging are a major reduction in the percentage of the samples represented by the lower of the two modes and a significant increase in the geometric mean concentration of that mode. Consequently, predictions of the distributions on a shorter time scale are likely to substantially underestimate the frequency of low concentration samples.     

Atmospheric lead concentration distribution in Northern Taiwan

Atmospheric lead concentrations were measured randomly, approximately once per week, at five traffic sites in northern Taiwan from September 1994 to May 1995. Three types of theoretical distributions, lognormal, Weibull and gamma were selected to fit the frequency distribution of the measured lead concentration. Four goodness-of-fit criteria were used to judge which theoretical distribution is the most appropriate to represent the frequency distributions of atmospheric lead.The results show that atmospheric lead concentrations in total suspended particulates fit the lognormal distribution reasonably well in northern Taiwan. The intervals of fitted theoretical cumulative frequency distributions (CFDs) can successfully contain the measured data when the population mean is estimated with a 95% confidence interval. In addition, atmospheric lead concentration exceeding a critical concentration is also predicted from the fitted theoretical CFDs.     

Measurements and modelling of the ozone deposition velocity to concrete tiles,including the effect of diffusion

A range of models were fitted to the experimental time-dependent curves for the deposition velocity of O₃ to concrete floor tile samples. The models included modified Langmuir isotherms assuming adsorption of O₃ on the material surfaces and models assuming direct reaction on and diffusion of O₃ into the material from the air. The best fit was obtained with a simple two-parameter model assuming direct reaction of O₃ with adsorbed surface water and direct diffusion of O₃ into the material from the air. However, models assuming an additional second-order reaction of O₃ with an adsorbed surface species with a given start mass gave improved curve fit in the first 500 min. Applying the best model to experimental data obtained over the whole air humidity range resulted in markedly lower equilibrium deposition velocities than those measured after 48 h. The modelling gave a deposition velocity minimum in the 50–70% relative air humidity range in agreement with observations. The deposition velocity minimum could be explained with a reduced constant for the reaction of O₃ with water or OH⁻ ions on the surface.     

An Air Quality Data Analysis System for Interrelating Effects,Standards, and Needed Source Reductions: Part 4. A Three-Parameter Averaging-Time Model

Urban air pollutant concentration data often tend to fit a two-parameter averaging-time model having three characteristics: (1) pollutant concentrations are (two-parameter) lognormally distributed for all averaging times; (2) median concentrations are proportional to averaging time raised to an exponent; and (3) maximum concentrations are approximately inversely proportional to averaging time raised to an exponent. Concentration data obtained near many isolated point sources and in some urban areas often do not fit a two-parameter lognormal distribution. An increment (either positive or negative) can be added to each such concentration in order to fit the data instead to a three-parameter lognormal distribution. This increment has been incorporated as the third parameter in a new three-parameter averaging-time model that can be used in both point-source and urban settings. Examples show how this new model can be used to analyze SO₂ concentration data obtained near a point source to determine the degree of emission reduction needed to achieve the national ambient air quality standards.     

The effects of scale and spatial heterogeneities on diffusion in volcanic breccias and basalts: Amchitka Island, Alaska

Knowledge of the factors that influence the diffusion of contaminants, such as the diffusivity and the connected porosity, is crucial to modeling the long-term fate and transport of contaminants in subsurface systems with small or negligible advective flow, such as in fractured crystalline rock. Fractured rock is naturally heterogeneous, and hence, understanding the diffusivity of a molecule through this material (or the formation factor of the medium) becomes a complex problem, with critical concerns about the scale of laboratory measurements and about the spatial variability of these measurements relative to the scale needed for fate and transport modeling. This study employed both electrical and tracer-based laboratory methods to investigate the effects of scale and pore system connectivity on the diffusivity for volcanic matrix rock derived from the study site, a former underground nuclear test site at Amchitka Island, Alaska. The results of these investigations indicate a relatively well-connected pore system with scale effects generally limited to approximately 6 cm lengths and well-correlated to observed heterogeneous features. An important conclusion resulting from this study, however, is that there is a potential for the estimated diffusivity to be misrepresented by an order of magnitude if multiple samples or longer sample lengths are not used. Given the relatively large number of measurements resulting from these investigations, an analysis of the probability density function (PDF) of the diffusivity was possible. The PDF of the diffusivity was shown to generally follow a normal distribution for individual geologic layers. However, when all of the geologic layers are considered together, the distribution of the subsurface as a whole was shown to follow a lognormal distribution due to the order of magnitude differences amongst the layers. An understanding of these distributions is essential for future stochastic modeling efforts.     

Estimation of sampling uncertainty for determination of pesticide residues in plant commodities

In order to provide residue data for refining the estimated sampling uncertainty, a coordinated research program was initiated for performing field studies on residues in individual items of leafy vegetables, small and large crops. The trials were carried out in 13 countries with 3 small fruits, 5 large crops, 2 medium/large crops and 3 leafy vegetables. The 25 pesticide active ingredients applied represented the dicarboximide (3), organophosphorus (8), synthetic pyrethroids (5), phthalimides (2), organochlorine (1) and other types of pesticides (6). In addition, 11 supervised field trials were performed in grapes and lettuce by the pesticide manufacturers, and their results were provided for evaluation. The studies represented actual agriculture practice around the world, and provide reliable data for estimation of sampling uncertainty. Based on the 12346 residue data, the best estimate for the relative sampling uncertainty for composite samples, assuming sample size of 10 for small crops and leafy vegetables and 5 for large crops, with 95% confidence limits in brackets are: small commodities: 0.25 (0.20–0.29); Brassica leafy vegetables: 0.20 (0.16–0.24); large commodities: 0.33 (0.29–0.38).     

On the Evaluation of Predictions from a Gaussian Plume Model

The performance of a CRSTER equivalent Gaussian plume model (CEQM) is examined using data from the EPRI Plume Model Validation study at the Klncaid, Illinois site. Four-way comparisons are made on the ordered statistics or the cumulative frequency distribution (CFD) of maximum hourly observed and predicted concentrations. Using the uniform random distribution and the lognormal random distribution as simple predictive schemes without any physical context, it Is found that the CEQM predicts a concentration CFD which matches the observed CFD significantly closer than the CFD predicted by the uniform random distribution. The two-parameter lognormal random distribution predicts the concentration CFD better than the CEQM over all concentration ranges; however, the CEQM fits the upper range of the concentration distribution better than the lognormal random distribution,, despite the fact that the predictions are generated using dispersion conditions entirely different from those of the observations. The nature of this ergodicity of distribution is probed by exercising CEQM using randomized input based on the observed frequency distributions of the Input parameters instead of feeding the hour-by-hour model input matched by time into CEQM as is customarily done. The exercise of the model by uncoupling the time linkage in model Input has no systematic effect on the predicted cumulative frequency distribution of concentrations. Only at the highest concentration range (99.5% or higher) do the two sets of predictions begin to diverge.     

Size distribution of large aerosol particles during AGASP-II: Absence of st. augustine eruptive particles in the Alaskan Arctic

Number distribution data for 0.1–45 μm diameter aerosol were obtained using optical counting and sizing probes flown over the Alaskan Arctic during the second Arctic Gas and Aerosol Sampling Program (AGASP-II), flights 201–203. Due to noise present in the lowest size channels of the optical probes, estimates of the H₂SO₄ component of Arctic haze were not attempted. Large particle (> 0.5 μm diameter) results are presented here. Large particle number and volume concentration were determined along with estimated mass, which was generally </ 0.1μg m⁻³. Lognormal fitting to > 0.3 μg m⁻³ mass loading sizedistributed aerosol data produced a means for comparing volume geometric median diameters (VGMD) for these higher-mass time intervals. These VGMDs showed that solid crustal particles previously observed during AGASP-II had VGMDs in the 1.2–1.6 μm range and that the shape of these fitted lognormal distributions was essentially constant. This result suggests very-long-range transport from a distant crustal source and, in conjunction with aerosol physical and chemical characterization data, argues against the presence of the Mt. Augustine eruptive particles during AGASP-II Alaskan Arctic sampling.     

R&D Activities,Operating Experience Discussed at Fabric Alternatives Forum

ABSTRACT

Previously reported volatile organic compounds (VOC) radiocarbon (¹⁴C) measurements for 1992 summertime Atlanta, GA, have been compared with chromatographic data and emissions inventory predictions. The chromatographic approach that was used provided a more comprehensive VOC characterization than typically achieved, and the emissions inventory was research-grade level (date-, site-, and time-specific). The comparisons are in general agreement that biogenic emissions contribute only modestly (<10%) to the VOC content of the particular ambient samples that were collected and measured. The choices of sampling site (near city-center) and times (early morning and late evening) are major influences on the results, which consequently should not be regarded as representing the average VOC biogenic impact for the Atlanta area.