Seasonal and influent characteristic effects on hydrogen sulfide generation at a water reclamation plant.

Correlations between sulfide generation and seasonal influent wastewater characteristics were identified based on a long-term monitoring program in summer and winter at a water reclamation plant. During summer, the emission rates of hydrogen sulfide (H2S) from the liquid treatment processes increased substantially compared to those during winter due to the increased wastewater temperature. The open tanks/clarifiers were the least significant H2S emission contributors throughout the year. For solids-handling processes, the H2S emission rates did not change during the year due to similar sludge characteristics in the different seasons. The fate of sulfide in liquid treatment processes was investigated as an alternative to estimation of H2S emissions. H2S emission from the wet well and screens was proven to be robustly associated with the wastewater temperature, flow rate, 5-day biochemical oxygen demand and total Kjeldahl nitrogen levels. However, the correlation between influent parameters and H2S emission from aerated grit chambers was not statistically significant.

ATP as a marker for surface contamination of biological origin in schools and as a potential approach to the measurement of cleaning effectiveness.

To address the need for a quantitative approach to the measurement of cleaning effectiveness, related to biologically derived surface contamination, three commercially available adenosine triphosphate (ATP) test systems were used to collect multiple samples measured in relative light units (RLUs) from 27 elementary schools in the southwestern United States before and after a standardized cleaning protocol. The database consisted of 6480 ATP measurements from four critical surfaces (student desktops, cafeteria tabletops, and restroom sinks and stall doors). Data was assessed according to ranges of ATP values before and after cleaning. Results showed the potential for such data to provide the basis for a standardized approach to the measurement of cleaning effectiveness, based on detection and quantification of pollutant loads of biological origin, across critical surfaces in school building environments. It is anticipated that verification of this data in school buildings across different geographic and climatic regions will lead to the establishment of "acceptable" ranges of ATP values that can be used as a practice-based approach to improving cleaning practices and contributing to healthier school environments.

Case study of odor and indoor air quality assessment in the dewatering building at the Stickney Water Reclamation Plant.

Indoor air quality (IAQ) and odors were determined using sampling/monitoring, measurement, and modeling methods in a large dewatering building at a very large water reclamation plant. The ultimate goal was to determine control strategies to reduce the sensory impacts on the workforce and achieve odor reduction within the building. Study approaches included: (1) investigation of air mixing by using CO(2) as an indicator, (2) measurement of airflow capacity of ventilation fans, (3) measurement of odors and odorants, (4) development of statistical and IAQ models, and (5) recommendation of control strategies. The results showed that air quality in the building complies with occupational safety and health guidelines; however, nuisance odors that can increase stress and productivity loss still persist. Excess roof fan capacity induced odor dispersion to the upper levels. Lack of a local air exhaust system of sufficient capacity and optimum design was found to be the contributor to occasional less than adequate indoor air quality and odors. Overall, air ventilation rate in the building has less effect on persistence of odors in the building. Odor/odorant emission rates from centrifuge drops were approximately 100 times higher than those from the open conveyors. Based on measurements and modeling, the key control strategies recommended include increasing local air exhaust system capacity and relocation of exhaust hoods closer to the centrifuge drops.

Odor emission rate estimation of indoor industrial sources using a modified inverse modeling method.

Odor emission rates are commonly measured in the laboratory or occasionally estimated with inverse modeling techniques. A modified inverse modeling approach is used to estimate source emission rates inside of a postdigestion centrifuge building of a water reclamation plant. Conventionally, inverse modeling methods divide an indoor environment in zones on the basis of structural design and estimate source emission rates using models that assume homogeneous distribution of agent concentrations within a zone and experimentally determined link functions to simulate airflows among zones. The modified approach segregates zones as a function of agent distribution rather than building design and identifies near and far fields. Near-field agent concentrations do not satisfy the assumption of homogeneous odor concentrations; far-field concentrations satisfy this assumption and are the only ones used to estimate emission rates. The predictive ability of the modified inverse modeling approach was validated with measured emission rate values; the difference between corresponding estimated and measured odor emission rates is not statistically significant. Similarly, the difference between measured and estimated hydrogen sulfide emission rates is also not statistically significant. The modified inverse modeling approach is easy to perform because it uses odor and odorant field measurements instead of complex chamber emission rate measurements.

Comparison of two dynamic measurement methods of odor and odorant emission rates from freshly dewatered biosolids.

Odor and odorant emission rates from freshly dewatered biosolids in a dewatering building of a Water Reclamation Plant (WRP) are measured using the EPA flux chamber and wind tunnel methods. Experimental results are compared statistically to test whether the two methods result in similar emission rates when experiments are performed under field conditions. To the best of our knowledge the literature is void of studies comparing the two methods indoors. In this paper the two methods are compared indoors where the wind velocity and air exchange rate are pertinent field conditions and can be measured. The difference between emission rates of odor and hydrogen sulfide measured with the two methods is not statistically significant (P values: 0.505 for odor, 0.130 for H(2)S). It is concluded that both methods can be used to estimate source emissions but selection of the most effective or efficient method depends on prevailing environmental conditions. The wind tunnel is appropriate for outdoor environments where wind effects on source emissions are more pronounced than indoors. The EPA flux chamber depends on the air exchange rate of the chamber, which simulates corresponding conditions of the indoor environment under investigation and is recommended for estimation of indoor pollution sources.

Modeling daily variation of trihalomethane compounds in drinking water system, Houston, Texas.

Total trihalomethanes (TTHM) concentrations vary widely and periodically between 70 and 130 ppb. Data from the National Environmental Services Laboratory, Houston, Texas indicate that pH and free residual chlorine contribute minimally to the wide variability of TTHM levels. Temperature variation in drinking fluctuates from 11 to 27 degrees C. The objective of this research is to formulate a model that delineates more clearly the daily variations of the most prevalent volatile trihalomethane by-products: chloroform (CHCl3), bromodichloromethane (CHBr2Cl), and bromoform (CHBr3) levels from drinking water. This model simulates the daily fluctuation of THM at a single location and at any time during the day as a function of the water temperature and the average concentration of TTHM, which can be estimated. The hypothesis of this study is that observed daily fluctuations of TTHM, CHCl3, CHCl2Br, CHClBr2, and CHBr3 are periodic. This hypothesis is tested using autocorrelation functions and it is shown that for the series of pH the correlation coefficient is maximal at zero lags, rapidly decreases to zero, and increases again between 4- and 6-h period. Such pattern suggests random fluctuation unrelated to time. However, the series of free residual chlorine, temperature, TTHM, CHCl3, CHCl2Br, CHClBr2, and CHBr3 suggest a different pattern. The correlation coefficient increases when the time-shift approaches 24 h. These repetitions in fluctuation of content over a 24-h period are statistically significant. The model formulated in this study provides insights in TTHM variation and is a necessary tool to reduce the error when estimating potential risk from exposure to trihalomethane compounds in drinking water system. In general, calculation of potential risk by using a value measured early morning or late afternoon concentrations were found minimal lead to an underestimation of the population risk.

Modeling brominated trihalomethane compounds in drinking water at a treatment plant in Beaumont, Texas.

The premise of this study is that the presence of bromide has a substantial effect on both the speciation and total formation of trihalomethane (THM). Consequently, models of water containing substantial bromide concentrations require refinement because they are only calibrated with raw water with high humic acid content. This study investigates and reports efforts on such refinement. The objectives of work reported in this paper are to formulate and validate a new correlative model that is based on physical principles and incorporates high levels of bromide that affect THM formation using raw water rich in both humic and fulvic acid. Two types of THM precursors are considered in the model discussed in this paper: (1) activated aromatic groups, which are more reactive with chlorine than with bromine, and (2) aliphatic groups, which are more reactive with bromine than with chlorine. Aliphatic and aromatic carbons are incorporated in the model by the inclusion of pertinent variables such as C/N and Br/Cl2 in the algorithm. The model also includes NH4+. This variable affects chlorine consumption that, in turn, potentially affects THM formation. For the first time ever, organic carbon to organic nitrogen and bromide to chlorine ratios is also used as variables potentially affecting THM formation when treating drinking water. The THM model formulated in this paper is an empirical model based on scientific principles and not simply a regression equation. The formulated model is pronounced valid based on a validation effort that employs a portion of an EPA database that was not used for model formulation.

Modeling spatial variation of brominates trihalomethane in a water distribution system of Ontario, Canada.

Conventional approaches to characterize and model the formation of trihalomethanes (THM) species in the distribution system use either residence time or water temperature. A significant deviation of THM levels were observed at the beginning and the end of a selected distribution system in Ontario, which may be because the consumption rate of residual chlorine is not constant in the distribution system. The approach developed in this study incorporates water temperature and proceeds with a trend and decomposition modeling method to incorporate the traveled distance and to explain the seasonal THM variation in the distribution system. The model has been tested and verified using a database from the Bettravia distribution system in Ontario, Canada. The deviations at the extremes of the distribution system were minimized due to the modeling technique used to develop the model and by including more factors that affect THM formation in the distribution system. The agreement between predicted and measured THM values at the beginning and the end of the distribution system is pronounced. The model presented in this paper is a robust tool that may be used by SDWAA to evaluate regulatory options and justify potential regulations regarding THM levels of the drinking water distribution system.

The indoor environmental index and its relationship with symptoms of office building occupants.

An index for indoor environmental quality, the Indoor Environmental Index (IEI), was developed. This study aggregates the Indoor Air Pollution Index, an index found in the literature, and a new index: the Indoor Discomfort Index. The average of these two indices is the IEI, which is calculated using concentrations of eight pollutants and two comfort variables measured in 100 office buildings in the United States. The database used was developed for the U.S. Environmental Protection Agency Building Assessment Survey Evaluation study. A symptom index also is developed to denote persistent occupant symptoms. The IEI and the symptom index are used to investigate the relationship between indoor environmental quality and symptoms. Two simple linear regression models were formulated; these models explain 67 and 79% of the variation in the average symptom index, with the variation of the average IEI depending on the method of averaging used in the construction of the models. In addition, a conceptual explanation is provided for the empirical or regression models formulated. The IEI and the associated models relating indoor environmental quality with the office occupant symptom index may be used as management tools, as illustrated with an example.

Estimating effects of moisture damage repairs on students' health-a long-term intervention study.

Health symptom questionnaire responses were collected from upper secondary and high school students (n=245) before comprehensive repairs of moisture damage in the school. The questionnaire study was repeated 1 year (n=227), 3 years (n=256), and 5 years (n=233) after the repairs. The data were analyzed both in cross-sectional design including all respondents, and longitudinally including paired observations of those individuals who had responded both before and after the repairs. In addition, the effect of intervention on health symptoms was analyzed using generalized estimating equations (GEEs), taking into account within-subject correlation between repeated measurements. Compared to the situation before the repairs, the situation after the repairs was significantly improved in most of the 20 symptoms studied among the cross-sectional study populations. However, improvement was not so clear in the paired analysis and GEE analysis among the students who responded to three repeated questionnaires. The results indicate that the repairs succeeded in the sense that new cases of symptomatic students were no longer expected. However, the reversibility of symptoms among the group of exposed individuals may need to be considered separately.

Chapter three: methodology of exposure modeling.

In this chapter, the concept of exposure assessment and its evolution is introduced, and evaluated by critically appraising the pertinent literature as it applies to exposures to Particulate Matter (PM). Exposure measurement or estimation methodologies and models are reviewed. Three exposure/measurement methodologies are assessed. Estimation methods focus on source evaluation and attribution, sources include those outdoors and indoors as well as in occupational and in-transit environments. Fate and transport models and their inputs are addressed to estimate concentrations outdoors and indoors; source attribution techniques help focus on the contributing sources. Activity pattern techniques are also reviewed and their use in exposure models to estimate inhalation exposure to PM is presented. Deterministic, regression and other stochastic models of exposure to PM are reviewed and evaluated. Strengths, limitations, assumptions and affirmations of the use of exposure assessment as an integral component of risk assessment and risk management are discussed in the conclusions and discussions section of this work.

Modeling exposure to particulate matter.

Exposure assessment, a component of risk assessment, links sources of pollution with health effects. Exposure models are scientific tools used to gain insights into the processes affecting exposure assessment. The purpose of this paper is to review the process and methodology of estimating inhalation exposure to particulate matter (PM) using various types of models. Three types of models are discussed in the paper. Indirect type of models are physical models that employ inventories of outdoor and indoor sources and their emission rates to identify major sources contributing to exposure to PM, and use fate and transport and indoor air quality models to estimate PM concentrations at receptor sites. PM concentrations and time spent by a subject at each receptor site are input variables to the conventional exposure model that estimates the desired exposure levels. Direct type models use measured exposure or exposure concentrations in conjunction with information obtained from questionnaires to formulate exposure regression models. Stochastic models use exposure measurements, estimates can also be used, to formulate exposure population distributions and investigate associated uncertainty and variability. Since models developed using databases from western countries are not necessarily applicable in developing countries, the difference in requirements among western and developing countries is highlighted in the paper. Employment of exposure modeling methods in developing countries requires development of local information. Such information includes local outdoor and indoor source inventories, local or regional meteorological conditions, adjustment of indoor models to reflect local building construction conditions, and use of questionnaires to obtain local time budget and activity patterns of the subject population.