Ultimate biodegradation and elimination of antibiotics in inherent tests

The biodegradation and elimination of antibiotics in municipal wastewater treatment plants is of particular concern because sewage is the main exposure route for antibiotics used in human medicine. The inherent biodegradability of 17 antibiotics was determined in a combined test design based on the Zahn-Wellens test (OECD 302 B, 1992) and the CO2-evolution test (OECD 301 B, 1992). CO2 Evolution test (Modified Sturm test). OECD Guideline for the Testing of Chemicals, Paris). Only benzylpenicillin sodium salt (Penicillin G) proved to be ultimately biodegradable, reaching ThCO2 degradation extents of 78-87%. Among the others, only amoxicillin, imipenem and nystatin showed certain ultimate biodegradation in few of the parallel flasks and can be regarded as partially biodegradable with formation of stable metabolites. The DOC-elimination of tetracycline-HCl showed a typical degradation curve starting with 18% and reaching the plateau phase at 80% after 21 days. Nevertheless, the CO2-evolution measured in parallel did not support the data, indicating that the time needed for reaching the adsorption equilibrium was underestimated. Several other antibiotics showed considerable DOC-elimination in the inherent test while only minor incidences of ultimate biodegradation were observed. The combination of CO2-evolution and DOC-elimination is a suitable instrument for assessing the behaviour of chemicals within one test. It enables one to assess both inherent ultimate biodegradability and DOC-elimination by sorption. The applicability of the test is limited to substances with a moderate toxicity.     

Rectification of prevailing visibility statistics

An investigation is made into the biases inherent in prevailing visibility observations and a method is proposed for removing these biases in order to rectify the visibility statistics for a station. Using these rectified statistics, the dependence of visibility on relative humidity is examined for five stations in or near New Jersey. The data are found to conform fairly well with a physical model.     

Intermittency and conditionally-averaged concentration fluctuation statistics in plumes

A semi-empirical Gaussian plume model is developed which predicts the intermittency factor, and the mean and variance of the non-zero time varying concentration in the plume from a point source. Wind tunnel data are used to verify the theory and to set the empirical constants. Conditionally averaged concentration fluctuation variance, which has zero concentrations removed, is only weakly dependent on source size, while intermittency caused by plume meandering is shown to be strongly dependent on source size. The resulting closed form predictions are presented in a form suitable for estimating risk of exposure to peak concentrations.     

The statistics of chemical trace concentrations in the steady state

The steady state probability distribution of chemical tracers in the atmosphere and in rain can be calculated from stochastic models, under explicit assumptions. We compare predictions from two such models, one based upon a linear stochastic equation in which random removal events … or storms … form a Poisson process, and the other based upon multiplicative random processes which produce a lognormal distribution. The two models predict different shapes for the resulting distributions of concentrations and fluxes of atmospheric tracers such as sulfates in ‘acid rain’. Consequently, estimates of the frequencies of extreme events, if based upon an assumed parametric form of a distribution function whose parameters are fitted by measurements of typical events, are model sensitive.To establish a preferred model for wet deposition, we have examined the statistics of sulfate deposition from the “European Network for the Study of Long Range Transport of Air Pollutants” (LRTAP), during the years 1973–1975. The shapes of the distributions of airborne sulfur species (SO₂+ SO₄²⁻), and of raincarried sulfate fluxes to the ground, are between those predicted by the two models.Our results are of operational significance to efforts directed to establishing national standards for rain quality.     

Concentration statistics for mixing-controlled reactive transport in random heterogeneous media

Uncertainty in the distribution of hydraulic parameters leads to uncertainty in flow and reactive transport. Traditional stochastic analysis of solute transport in heterogeneous media has focused on the ensemble mean of conservative-tracer concentration. Studies in the past years have shown that the mean concentration often is associated with a high variance. Because the range of possible concentration values is bounded, a high variance implies high probability weights on the extreme values. In certain cases of mixing-controlled reactive transport, concentrations of conservative tracers, denoted mixing ratios, can be mapped to those of constituents that react with each other upon mixing. This facilitates mapping entire statistical distributions from mixing ratios to reactive-constituent concentrations. In perturbative approximations, only the mean and variance of the mixing-ratio distribution are used. We demonstrate that the second-order perturbative approximation leads to erroneous or even physically impossible estimates of mean reactive-constituent concentrations when the variance of the mixing ratio is high and the relationship between the mixing ratio and the reactive-constituent concentrations strongly deviates from a quadratic function. The latter might be the case in biokinetic reactions or in equilibrium reactions with small equilibrium constant in comparison to the range of reactive-constituent concentrations. When only the mean and variance of the mixing ratio is known, we recommend assuming a distribution that meets the known bounds of the mixing ratio, such as the beta distribution, and mapping the assumed distribution of the mixing ratio to the distributions of the reactive constituents.     

Identification of odour sources in an industrial park from resident diaries statistics

A methodology based on social participation through the use of resident diaries was applied to evaluate the odour annoyance in the surroundings of an industrial park in Belgium during one year. The studied area covers about 8 km² and includes13 potential odour emitting facilities. The network involved 44 residents in the survey, among whom 19 were particularly considered for a detailed analysis. The questionnaire aimed at providing an odour rating twice-daily on a 6-level scale together with an odour type.The fact that the response rate corresponding to “no-odour” was high (79%) is particularly discussed. Some tests are proposed to check the plausibility of the answers, the coherence within clusters of residents and the individual performance of respondents to discriminate among odour ratings. The odour rose is presented as an attractive and visual tool, particularly suited in the case of multi-source areas, to map the different odour emissions, to point out the most worrying ones, to identify others creating less annoyance and possibly new unpredicted ones. The resident diary method has proven to be particularly useful, conjointly to other ones, to the case of multi-sources facilities in large areas, when the purpose is the assessment of the long-term evolution of odour annoyance.     

Effects of measurement uncertainty on air quality summary statistics

This paper examines the effects of measurement uncertainty on various summary statistics that are routinely used in air quality data analysis. Analytical approximations and computer simulation techniques are employed to illustrate and quantify how the uncertainty associated with an individual measurement results in an uncertainty for different summary statistics. Measurement uncertainty may be viewed as consisting of bias and imprecision. It is shown that even when there is no bias for individual measurements it is possible for imprecision alone to result in bias for certain commonly used summary statistics. Different types of statistics are shown to be less influenced by measurement imprecision and, consequently, a data set may be acceptable for some purpose but not for others. The desired precision of the summary statistic may be viewed as a guide in determining an acceptable level of imprecision for individual measurements.     

Calibration and error analysis of multiwavelength telephotometers

In preparation for the EPA-VISTTA summer 1979 field program, 12 multiwavelength telephotometers were tested and calibrated. A standard light source was used in the calibration process, and the linearity of the instruments was checked using neutral density filters. Calibration of the telephotometers was performed before and after this experiment to determine individual instrument response and drift. Results of the calibration indicated that the instruments had an average inherent error of approximately 1 per cent when operating in the contrast (or ratio) mode. The degree of error is less if a correction is made. In the absolute radiance mode, the instrument was estimated to have an average inherent error of approximately 10 per cent.Results of two of the telephotometer comparisons performed during the VISTTA program are shown to illustrate the problems of target selection and inhomogeneity. A comparison of the extinction coefficients determined from the telephotometers and the scattering coefficients measured by nephelometers showed reasonable agreement for the first example.A more comprehensive, side-by-side comparison showed that results from the two telephotometers agreed within 2 per cent in the ratio mode. However, the uncertainty in the extinction coefficient is between 10 and 15 per cent. This uncertainty can be reduced by eliminating the low contrast cases.     

Biodegradability of the antioxidant diaryl-p-phenylene diamine using a modified inherent biodegradation method at an environmentally relevant concentration

The chemical product diaryl-p-phenylene diamine (DAPD), produced by The Goodyear Tire & Rubber Company as POLYSTAY 100® (CAS 68953-84-4), is employed as an antidegradant in polymers used in tires and industrial rubber products. Previous evaluations pertaining to the ecological fate of DAPD indicated a lack of biodegradative activity in aquatic media. In order to further pursue the biodegradation potential of DAPD, it was deemed necessary to enhance the sensitivity of the aquatic biodegradation assay through (a) employment of a radiotracer of the test substance, and (b) optimisation of conditions for achieving maximal solubilisation of test material in the aquatic media of the incubation vessels. Test vessels were prepared according to the OECD ready biodegradability test guidelines, with DAPD added on silica gel at concentrations of 10 or 100 μg L⁻¹, together with a surfactant to aid solubilisation. After 63 d incubation up to 37% mineralisation was measured and up to 29% of the applied radioactivity was incorporated into cell biomass. Also, after 28 d no DAPD could be measured in solution by radio-TLC and HPLC–MS. These three results demonstrate that the antioxidant DAPD undergoes microbiologically mediated biodegradation and is highly unlikely to persist in the environment.     

Recommendations on statistics and benchmarks to assess photochemical model performance

Photochemical grid models are addressing an increasing variety of air quality related issues, yet procedures and metrics used to evaluate their performance remain inconsistent. This impacts the ability to place results in quantitative context relative to other models and applications, and to inform the user and affected community of model uncertainties and weaknesses. More consistent evaluations can serve to drive improvements in the modeling process as major weaknesses are identified and addressed. The large number of North American photochemical modeling studies published in the peer-reviewed literature over the past decade affords a rich data set from which to update previously established quantitative performance “benchmarks” for ozone and particulate matter (PM) concentrations. Here we exploit this information to develop new ozone and PM benchmarks (goals and criteria) for three well-established statistical metrics over spatial scales ranging from urban to regional and over temporal scales ranging from episodic to seasonal. We also recommend additional evaluation procedures, statistical metrics, and graphical methods for good practice. While we primarily address modeling and regulatory settings in the United States, these recommendations are relevant to any such applications of state-of-the-science photochemical models. Our primary objective is to promote quantitatively consistent evaluations across different applications, scales, models, model inputs, and configurations. The purpose of benchmarks is to understand how good or poor the results are relative to historical model applications of similar nature and to guide model performance improvements prior to using results for policy assessments. To that end, it also remains critical to evaluate all aspects of the model via diagnostic and dynamic methods. A second objective is to establish a means to assess model performance changes in the future. Statistical metrics and benchmarks need to be revisited periodically as model performance and the characteristics of air quality change in the future.

Implications: We address inconsistent procedures and metrics used to evaluate photochemical model performance, recommend a specific set of statistical metrics, and develop updated quantitative performance benchmarks for those metrics. We promote quantitatively consistent evaluations across different applications, scales, models, inputs, and configurations, thereby (1) improving the user’s ability to quantitatively place results in context and guide model improvements, and (2) better informing users, regulators, and stakeholders of model uncertainties and weaknesses prior to using results for policy assessments. While we primarily address U.S. modeling and regulatory settings, these recommendations are relevant to any such applications of state-of-the-science photochemical models.     

中国与欧盟环境保护投资统计的比较研究

从环境保护(简称环保)投资概念、环保投资统计口径、环保投资统计方法3个方面比较了中国环保投资统计和欧盟环保支出统计存在的差异,并评估了各自的环保投资规模与效益.并通过借鉴欧盟环保支出统计经验,得出完善中国环保投资统计工作的启示:明确界定环保投资内涵,逐步与国际概念接轨;规范环保投资统计制度,建立科学的统计方法;与国民经济统计相衔接,满足经济活动管理需求.     

The significance of the systematic error in rainfall measurement for assessing wet deposition

Deposited acidity in the U.K. and other countries is normally reported as the product of measured concentration and rainfall as measured in the standard type of network raingauge. Depending on its height above the ground surface and wind speed, the standard gauge systematically under registers rainfall. Hence real deposited acidity values can be larger by up to 20% and more than those reported.     

The bootstrap and the jackknife in ecotoxicology or nonparametric estimates of standard error

A recently invented statistical method, the bootstrap, is used to verify whether a hypothesis, developed from a limited data set, would be valid if all possible data would have been available, i.e. this statistical method allows generalization to chemicals of the same class not included in the original analysis. The validity of the relation, hypothesized by Neely, between the water solubility of an organic chemical and the ratio of the acute fish LC50 at two different time periods has been tested. The hypothesis has been shown correct by first fitting a linear model with a geometric mean (GM) functional regression, which takes into account errors in both the independent and dependent variables, to compare observed and predicted ratios; the generality of the model has been tested by computing the confidence limits of the correlation coefficient, of the slope and intercept of the GM regression model using the bootstrap. The results show that the correlation between predicted and observed data is statistically significant within one standard deviation, but sometimes it may not be significant at the 95% confidence limit. Neely's model is probably correct but it might have a systematic bias which makes the theoretical ratio somewhat higher than the observed ratio.     

Long-term aerosol particle flux observations part I: Uncertainties and time-average statistics

Long-term eddy covariance particle flux measurements for the size range starting from 10 nm were performed at a boreal forest site in Southern Finland. The large variability in turbulent flux estimates is inherent to the particle flux observations and thus long-term particle flux measurements enable to obtain statistically significant results by a suitable averaging. The particle flux random errors were estimated and a parameterisation for the integral time scale of turbulent flux was proposed. Application of flux errors for classification according to statistical significance of single flux values leads to systematically different deposition estimates on ensemble average basis. This must be avoided for determination of unbiased average deposition fluxes. The role of storage term in particle deposition evaluation was analysed. It was empirically determined that the method of storage term estimation discussed by [Finnigan, J., 2006. The storage term in eddy flux calculations. Agric. Forest Meteorol., 136, 108–113.] is not sensitive to the selection of the concentration averaging window in both ends of the flux averaging period. It is argued that the storage change in real atmospheric conditions results from boundary layer development as well as source–sink activity and therefore the filtering effect arising from averaging the concentration is of less importance. Diurnal, seasonal and annual variability of particle fluxes was analysed and it was observed that particle deposition rates are higher in winter. More detailed analysis of functional dependencies of particle deposition on environmental factors as well as dependence on size will be done in the second part of the paper.     

Selecting ozone exposure statistics for determining crop yield loss from air pollutants

Numerous ozone exposure statistics were calculated using hourly ozone data from crop yield loss experiments previously conducted for alfalfa, fresh market and processing tomatoes, cotton, and dry beans in an ambient ozone gradient near Los Angeles, California. Exposure statistics examined included peak (maximum daily hourly) and mean concentrations above specific threshold levels, and concentrations during specific time periods of the day. Peak and mean statistics weighted for ozone concentration and time period statistics weighted for hour of the day were also determined. Polynomial regression analysis was used to relate each of 163 ozone statistics to crop yield. Performance of the various statistics was rated by comparing residual mean square (RMS) values. The analyses demonstrated that no single statistic was best for all crop species. Ozone statistics with a threshold level performed well for most crops, but optimum threshold level was dependent upon crop species and varied with the particular statistics calculated. The data indicated that daily hours of exposure above a critical high-concentration threshold related well to crop yield for alfalfa, market tomatoes, and dry beans. The best statistic for cotton yield was an average of all daily peak ozone concentrations. Several different types of ozone statistics performed similarly for processing tomatoes. These analyses suggest that several ozone summary statistics should be examined in assessing the relationship of ambient ozone exposure to crop yield. Where no clear statistical preference is indicated among several statistics, those most biologically relevant should be selected.