In Situ Determination of the Rate of Unassisted Degradation of Saturated-Zone Hydrocarbon Contamination

Abstract

A method to measure the in situ degradation rate of dissolved hydrocarbon contamination has been developed and applied at two locations at a field site. The method uses the rates of downward diffusion of oxygen and upward diffusion of carbon dioxide through the unsaturated zone, as calculated from vertical soil-gas concentration gradients, combined with stoichiometry to obtain two degradation rates in hydrocarbon mass per water table surface area per time. Values of 0.385 gram per m² per day and 0.52 gram per m² per day (based upon oxygen data) and 0.056 gram per m² per day and 0.12 gram per m² per day (based upon carbon dioxide data) were calculated at a field site with dissolved fuel contamination. This result of lower values from ground-air carbon dioxide concentrations is consistent with a significant fraction of the carbon dioxide produced being lost to the aqueous phase. Based upon a single-stage equilibrium phase-transfer model, gas/water volume ratios of 0.02 and 0.2 for the capillary fringe were calculated. Groundwater carbon dioxide fugacities and soil-gas carbon dioxide concentrations were used at the two locations and a third to determine whether the source of elevated soil carbon dioxide concentrations were unsaturated-zone hydrocarbon degradation or a saturated-zone process. This technique has potential applicability in setting risk-based remedial criteria and in allowing inclusion of the contribution of in situ degradation in remedial design. This can result in major remedial cost savings.     

Neural Network Model for Predicting Peak Photochemical Pollutant Levels

ABSTRACT

In this paper, an attempt is made for the 24-hr prediction of photochemical pollutant levels using a neural network model. For this purpose, a model is developed that relates peak pollutant concentrations to meteorological and emission variables and indexes. The analysis is based on measurements of O₃ and NO₂ from the city of Athens. The meteorological variables are selected to cover atmospheric processes that determine the fate of the airborne pollutants while special care is taken to ensure the availability of the required input data from routine observations or forecasts. The comparison between model predictions and actual observations shows a good agreement. In addition, a series of sensitivity tests is performed in order to evaluate the sensitivity of the model to the uncertainty in meteorological variables. Model forecasts are generally rather insensitive to small perturbations in most of the input meteorological data, while they are relatively more sensitive in changes in wind speed and direction.     

Adapting a geographical information system-based water resource management to the needs of the Romanian water authorities

Background, aim, and scope

The need for global and integrated approaches to water resources management, both from the quantitative and the qualitative point of view, has long been recognized. Water quality management is a major issue for sustainable development and a mandatory task with respect to the implementation of the European Water Framework Directive as well as the Swiss legislation. However, data modelling to develop relational databases and subsequent geographic information system (GIS)-based water management instruments are a rather recent and not that widespread trend. The publication of overall guidelines for data modelling along with the EU Water Framework Directive is an important milestone in this area. Improving overall water quality requires better and more easily accessible data, but also the possibility to link data to simulation models. Models are to be used to derive indicators that will in turn support decision-making processes. For this whole chain to become effective at a river basin scale, all its components have to become part of the current daily practice of the local water administration. Any system, tool, or instrument that is not designed to meet, first of all, the fundamental needs of its primary end-users has almost no chance to be successful in the longer term.

Materials and methods

Although based on a pre-existing water resources management system developed in Switzerland, the methodological approach applied to develop a GIS-based water quality management system adapted to the Romanian context followed a set of well-defined steps: the first and very important step is the assessment of needs (on the basis of a careful analysis of the various activities and missions of the water administration and other relevant stakeholders in water management related issues). On that basis, a conceptual data model (CDM) can be developed, to be later on turned into a physical database. Finally, the specifically requested additional functionalities (i.e. functionalities not provided by classical commercial GIS software), also identified during the assessment of needs, are developed. This methodology was applied, on an experimental basin, in the Ialomita River basin.

Results

The results obtained from this action-research project consist of a set of tangible elements, among which (1) a conceptual data model adapted to the Romanian specificities regarding water resources management (needs, data availability, etc.), (2) a related spatial relational database (objects and attributes in tables, links, etc.), that can be used to store the data collected, among others, by the water administration, and later on exploited with geographical information systems, (3) a toolbar (in the ESRI environment) offering the requested data processing and visualizing functionalities. Lessons learned from this whole process can be considered as additional, although less tangible, results.

Discussion

The applied methodology is fairly classical and did not come up with revolutionary results. Actually, the interesting aspects of this work are, on the one hand, and obviously, the fact that it produced tools matching the needs of the local (if not national) water administration (i.e. with a good chance of being effectively used in the day-to-day practice), and, on the other hand, the adaptations and adjustments that were needed both at the staff level and in technical terms.

Conclusions

This research showed that a GIS-based water management system needs to be backed by some basic data management tools that form the necessary support upon which a GIS can be deployed. The main lesson gained is that technology transfer has to pay much attention to the differences in existing situations and backgrounds in general, and therefore must be able to show much flexibility. The fact that the original objectives could be adapted to meet the real needs of the local end-users is considered as a major aspect in achieving a successful adaptation and development of water resources management tools. Time needed to setup things in real life was probably the most underestimated aspect in this technology transfer process.

Recommendations and perspectives

The whole material produced (conceptual data model, database and GIS tools) was disseminated among all river basin authorities in Romania on the behalf of the national water administration (ANAR). The fact that further developments, for example, to address water quantity issues more precisely, as envisaged by ANAR, can be seen as an indication that this project succeeded in providing an appropriate input to improve water quality in Romania on the long term.

     

Receptor Model Applied to Patterns in Space (RMAPS)

Abstract

The physical and mathematical bases of a new receptor model based on spatially intensive data are presented. The model apportions the average concentration of a species as measured at many sites among several spatially distinct sources and can be applied to primary or secondary species. In the latter case, no assumptions concerning transformation or deposition rates are required. The methodology is a combination of the empirical orthogonal function approach that is well known in meteorology and the self-modeling multivariate modeling approach that has long been applied in chemometrics and multivariate receptor modeling of air quality data. A simple, geometrical example of the modeling approach is given.     

Analysis and Simulation of Wintertime Light Scattering by the Urban Aerosol in Dallas-Fort Worth

ABSTRACT

Wintertime atmospheric light scattering in Dallas, TX, was estimated through the use of aerosol models. Input data for the aerosol models were provided by measurements of aerosol chemistry, physical particle size distributions, and distributions of particulate sulfur by particle size, and by predictions by an atmospheric simulation model. Light scattering measurements provided a basis for testing the aerosol models. The SCAPE thermodynamic equilibrium model was used to estimate the amount of liquid water associated with particles and the ELSIE Mie scattering model was applied to estimate the resulting light scattering. The calculations were based on aerosol properties measured in Dallas during December 1994 and February 1995, and changes in scattering due to hypothetical changes in the aerosol were predicted. The predicted light scattering was compared to scattering measured by an Optec nephelom-eter; agreement was within 20% in every case.     

Assuring the quality of data in the pesticide residue laboratory

Abstract

The importance of quality control procedures to the collection of pesticide residue data is discussed. The equipment requirements of an adequate, safe pesticide residue laboratory are presented. Equipment maintenance, personnel training, and preservation of samples is also reviewed. Appropriate objectives for an intra‐laboratory quality control program are outlined.     

The Development of a Sampling System for the Determination of Odor Emission Rates from Areal Surfaces: Part II. Mathematical Model

Abstract

An improved design for an odor emission hood was examined in the laboratory using ammonia emission from a water surface. The experimental ammonia convective mass transfer coefficients from a diluted ammonia solution were determined at velocities of 0.3 m/s to 0.8 m/s using the odor emission hood. The theoretical ammonia convective mass transfer coefficients were also predicted by boundary layer theory under laminar flow conditions. It was found that experimental data were only 10% below theoretical predictions at an air velocity of 0.3 m/s to 0.6 m/s. The maximum velocity was limited to 0.6 m/s by the geometric size, shape and aerodynamic stability of the hood. At 0.33 m/s, the smallest variation of mass transfer coefficients was measured. The odor emission rate was found to be a function of air velocity to the power 0.5 in accordance with boundary layer theory. An odor sampling system based upon the odor emission hood provides a way to quantify the potential odor emission strength in sewage treatment plants, for odor dispersion modeling and odor control.     

Review of Recent Ecotoxicological Studies on Cladocerans

Cladocerans have been widely used as the bioassay organisms in evaluating the impact of different toxic substances. Literature survey during the last 10 years revealed that cladoceran ecotoxicological research has been in an exponential phase constituting nearly 10% of publications on this group. Many studies have considered typically planktonic taxa such as Daphnia magna, D. pulex, Moina macrocopa, M. micrura and Ceriodaphania dubia. Experimental data on toxicity tests, to a lesser extent, are also available for littoral-benthic genera such as Simocephalus, Macrothrix and Alona. Most toxicity tests are limited to the derivation of median lethal concentrations of various durations but mostly at 24 or 48 h. Studies related to the evaluation of changes in the life history variables of cladocerans as a result of sublethal exposure to toxic substances are not many, but gaining importance. The common toxic substances used in the cladoceran toxicity tests appear to be heavy metals, pesticides and a few natural toxins such as cyanotoxins. We review here the effect of different toxic substances on cladocerans based on both the field and the laboratory studies from an ecotoxicology point of view. Suggestions for the future cladoceran ecotoxicology are also commented on.     

Development of Probabilistic Emission Inventories of Air Toxics for Jacksonville,Florida

Abstract

Probabilistic emission inventories were developed for 1,3-butadiene, mercury (Hg), arsenic (As), benzene, formaldehyde, and lead for Jacksonville, FL. To quantify inter-unit variability in empirical emission factor data, the Maximum Likelihood Estimation (MLE) method or the Method of Matching Moments was used to fit parametric distributions. For data sets that contain nondetected measurements, a method based upon MLE was used for parameter estimation. To quantify the uncertainty in urban air toxic emission factors, parametric bootstrap simulation and empirical bootstrap simulation were applied to uncensored and censored data, respectively. The probabilistic emission inventories were developed based on the product of the uncertainties in the emission factors and in the activity factors. The uncertainties in the urban air toxics emission inventories range from as small as –25 to +30% for Hg to as large as –83 to +243% for As. The key sources of uncertainty in the emission inventory for each toxic are identified based upon sensitivity analysis. Typically, uncertainty in the inventory of a given pollutant can be attributed primarily to a small number of source categories. Priorities for improving the inventories and for refining the probabilistic analysis are discussed.     

Comportement du metoxuron dans le sol

Abstract

The depressive effect of metoxuron which is sometimes observed on nitrifying bacteria, evolves with time to become harmless a month later, under laboratory conditions.

This phenomenon is explained by the present work carried out with two different soils, freshly sampled or airdried.

Metoxuron disappeared very quickly in the soil; the kinetics of disappearance were similar for the two soils studied.

This phenomenon, which results from a biological degradation, was not modified by supplying soil with ammoniacal nitrogen.     

ORP as slurry oxidation index and model modification in wet desulfurization system

ABSTRACT

Due to wet desulfurization system lacks effective control indicators for the oxidation process, so the sulfite oxidation in the slurry and the quality of gypsum become unstable. In this paper actual desulfurization system operation data are used to improve the ORP semi-empirical formula obtained in the laboratory. It was concluded that the ORP was mainly affected by the concentration of sulfite and pH during the operation of the actual desulfurization system, the dissolved oxygen was less affected by the small concentration change during operation. It is verified that the model can correct the ORP measurement value by using other conventional measurement data from the power plant. The results can provide theoretical support for adding ORP as a control index to optimize the oxidation process.     

Weekday vs. Weekend Ambient Ozone Concentrations: Discussion and Hypotheses with Focus on Northern California

Abstract

Since the early 1970s, researchers and data analysts have reported differences between weekday and weekend ozone concentrations, with higher ozone concentrations occurring on Sundays in some locations. At that time, the phenomenon was referred to as the “Sunday effect.” In the late 1980s, additional papers focused on weekday/weekend differences in air quality in the South Coast (Los Angeles) Air Basin.

Analyses of ozone concentrations measured at a number of locations in northern California reveal that average ozone concentrations are frequently higher on weekends than on weekdays. Violations of the California 0.09 ppm 1-hour air quality standard for ozone also occur in disproportionately greater frequency on weekends. We hypothesize that this phenomenon is based largely on the differences between weekday and weekend emission patterns. We believe that the observed differences may provide information regarding which pollutant reduction strategy, NO_x or ROG control, may be more effective in reducing ambient ozone concentrations. For the northern California region, the presence of higher weekend ozone concentrations suggests the need for ROG control is greater than for NO_x control. If both NO_x and ROG are to be controlled, it is important to understand the interdependence of the two pollutants in forming ozone. With the current uncertainty and debate regarding official vehicular emission inventories, this phenomenon emphasizes the importance of using observation-based data to examine ambient pollution and emission relationships. This natural experiment of varying emissions provides an interesting test case for sophisticated air pollution model performance and evaluation.

Using a Bay Area emission inventory and an estimate of its change from weekday to weekend, combined with a generic Empirical Kinetic Modeling Approach (EKMA) diagram, we demonstrate the weekend effect. In addition, changes in the Bay Area emission inventory from 1980 to 1990, when combined with the EKMA diagram, also show why the weekend effect is more evident in the 1990s.

It is our hypothesis that the presence of the weekend effect, positive or negative, combined with changes in emission changes, provides a simple clue to whether an area is NO_xor ROG limited with respect to ozone formation.     

Assessing background particulate contamination in an historic building – surface lead loading and contamination

ABSTRACT

Investigation of suspect surface contamination in a building may require comparative sampling across different zones to provide meaningful information with regard to contaminant sources, pathways and/or extent of dispersal. However, evaluation of the data using traditional null hypothesis significance testing (NHST) based upon the mean may result in misleading inference when encountering erratic distributions typical of environmental contaminant data. Sampling data (n = 90) for lead content in surface dust collected throughout a historic building with suspect contamination from uncontrolled disturbance to lead coatings were evaluated using traditional NHST and randomization/permutation inference; the latter metric was the maximum difference in frequency of detection (Δfd _max), to directly calculate the probability of the observed differences. In the examples for lead in surface dust presented herein, areas with “lower” mean concentration and/or no significant difference via NHST actually represented “greater contamination,” as Δfd _max indicated a greater probability of encountering lead at higher concentrations. Resulting conclusions with regard to sources and pathways contradicted those generated from traditional NHST, and underscore the need to recognize differences in applicability of different inference approaches, depending upon the distribution of the data and the particular problem. This is particularly relevant for forensic purposes.     

Using Continuous PM2.5 Monitoring Data to Report an Air Quality Index

Abstract

As stated in 40 CFR 58, Appendix G (2000), statistical linear regression models can be applied to relate PM_2.5 continuous monitoring (CM) measurements with federal reference method (FRM) measurements, collocated or otherwise, for the purpose of reporting the air quality index (AQI). The CM measurements can then be transformed via the model to remove any bias relative to FRM measurements. The resulting FRM-like modeled measurements may be used to provide more timely reporting of a metropolitan statistical area’s (MSA’s) AQI.¹ Of considerable importance is the quality of the model used to relate the CM and FRM measurements. The use of a poor model could result in misleading AQI reporting in the form of incorrectly claiming either good or bad air quality.

This paper describes a measure of adequacy for deciding whether a statistical linear regression model that relates FRM and continuous PM_2.5 measurements is sufficient for use in AQI reporting. The approach is the U.S. Environmental Protection Agency’s (EPA’s) data quality objectives (DQO) process, a seven-step strategic planning approach to determine the most appropriate data type, quality, quantity, and synthesis for a given activity.² The chosen measure of model adequacy is r², the square of the correlation coefficient between FRM measurements and their modeled counterparts. The paper concludes by developing regression models that meet this desired level of adequacy for the MSAs of Greensboro/Winston-Salem/High Point, NC; and Davenport/Moline/Rock Island, IA/IL. In both cases, a log transformation of the data appeared most appropriate. For the data from the Greens-boro/Winston-Salem/High Point MSA, a simple linear regression model of the FRM and CM measurements had an r² of 0.96, based on 227 paired observations. For the data from the Davenport/Moline/Rock Island MSA, due to seasonal differences between CM and FRM measurements, the simple linear regression model had to be expanded to include a temperature dependency, resulting in an r² of 0.86, based on 214 paired observations.     

Assessing Sorbents for Mercury Control in Coal-Combustion Flue Gas

Abstract

Sorbent injection for Hg control is one of the most promising technologies for reducing Hg emissions from power-generation facilities, particularly units that do not require wet scrubbers for SO₂ control. Since 1992, EPRI has been assessing the performance of Hg sorbents in pilot-scale systems installed at full-scale facilities. The initial tests were conducted on a 5000-acfm (142-m³/min) pilot baghouse. Screening potential sorbents at this scale required substantial resources for installation and operation and did not provide an opportunity to characterize sor-bents over a wide temperature range.

Data collected in the laboratory and in field tests indicate that sorbents are affected by flue gas composition and temperature. Tests carried out in actual flue gas at a number of power plants also have shown that sorbent performance can be site-specific. In addition, data collected at a field site often are different from data collected in the laboratory, with simulated flue gas mixed to match the major components in the site’s gas. To effectively estimate the costs of Hg sorbent systems at different plants, a measure of sorbent performance in the respective flue gases must be obtained. However, injection testing at multiple facilities with large pilot systems is not practical.

Over the past five years, fixed-bed characterization testing, modeling studies, and bench-scale injection testing have been undertaken to develop a low-cost technique to characterize sorbent performance in actual flue gas and subsequently to project normalized costs for Hg removal prior to full-scale demonstration. This article describes the techniques used and summarizes field-testing results from two plants burning Powder River Basin (PRB) coal for commercial activated carbon and several other sorbent types. Full-scale projections based on the results and data collected on larger-scale systems also are included.     

Nouvelles informations relatives aux variations temporaires de l'activite nitrifiante d'un sol evaluee au laboratoire. incidences d'un apport de matieres organiques

Abstract

The results reported in this paper confirm the seasonal influence on soil nitrifying activity estimated in the laboratory. The variations of this activity depend on different factors: climatic conditions, soil nature, occurence of plants, characteristics of the organic matter added to the soil.

A fresh organic matter (straw, for example) leads to reduced nitrifying activity immediately after its incorporation; its depressive action disappears after a month under laboratory condi‐tions. A decomposed organic matter, as a manure, produces no effect.

This work also shows the seasonal variations of the mineral nitrogen immobilization after addition of a fresh organic matter.     

Ion movements in the nervous system of the American cockroach,periplaneta Americana (L.), influenced by toxaphene

Abstract

The effect of toxaphene upon ion fluxes of the central nervous system (CNS) of the cockroach, Periplaneta americana (L.), was studied in vitro. The CNS, divided into three sections (brain, thoracic, and abdominal), was exposed to 10 M toxaphene in saline containing ²⁴Na⁺, ⁴²K⁺, ³⁶Cl^‐, or ⁴⁵Ca⁺⁺. Uptake and efflux of these ions were evaluated. Toxaphene was responsible for significant increases in the internal levels of ⁴²K⁺ and ⁴⁵Ca⁺⁺, but had little affect upon Na or ³⁶Cl^‐ movements. The resulting concentration changes of the ions may be involved in the neural activity observed with toxaphene poisoning. Of the three CNS sections, significant changes were more numerous and occurred earlier in abdominal sections.     

Diagnostics for Determining Influential Species in the Chemical Mass Balance Receptor Model

ABSTRACT

The chemical mass balance (CMB) model can be applied to estimate the amount of airborne particulate matter (PM) coming from various sources given the ambient chemical composition of the particles measured at the receptor and the chemical composition of the source emissions. Of considerable practical importance is the identification of those chemical species that have a large effect on either the source contributions or errors estimated by the CMB model. This paper details a study of a number of influential diagnostics for application of the CMB software. Some of the diagnostics studied are standard regression diagnostics based on single-row deletion diagnostics. A number of new diagnostics were developed specifically for the CMB application, based on the pseudo-inverse of the source composition matrix and called nondeletion diagnostics to distinguish them from the standard deletion diagnostics. Simulated data sets were generated to compare the diagnostics and their response to controlled amounts of random error.

A particular diagnostic called a modified pseudoinverse matrix (MPIN), developed for this study, was found to be the best choice for CMB model application. The MPIN diagnostic contains virtually all the information present in both deletion and nondeletion diagnostics. Since the MPIN diagnostic requires only the source profiles, it can be used to identify influential species in advance without sampling the ambient data and to improve CMB results through possible remedial actions for the influential species. Specific recommendations are given for interpretation and use of the MPIN diagnostic with the CMB model software. Elements with normalized MPIN absolute values of 1 to 0.5 are associated with influential elements. Noninfluential elements have normalized MPIN absolute values of 0.3 or less. Elements with absolute values between 0.3 and 0.5 are ambiguous but should generally be considered noninfluential.