Microenvironmental characteristics important for personal exposures to aldehydes in Sacramento,CA, and Milwaukee,WI

Oxygenated additives in gasoline are designed to decrease the ozone-forming hydrocarbons and total air toxics, yet they can increase the emissions of aldehydes and thus increase human exposure to these toxic compounds. This paper describes a study conducted to characterize targeted aldehydes in microenvironments in Sacramento, CA, and Milwaukee, WI, and to improve our understanding of the impact of the urban environment on human exposure to air toxics. Data were obtained from microenvironmental concentration measurements, integrated, 24-h personal measurements, indoor and outdoor pollutant monitors at the participants' residences, from ambient pollutant monitors at fixed-site locations in each city, and from real-time diaries and questionnaires completed by the technicians and participants. As part of this study, a model to predict personal exposures based on individual time/activity data was developed for comparison to measured concentrations. Predicted concentrations were generally within 25% of the measured concentrations. The microenvironments that people encounter daily provide for widely varying exposures to aldehydes. The activities that occur in those microenvironments can modulate the aldehyde concentrations dramatically, especially for environments such as “indoor at home.” By considering personal activity, location (microenvironment), duration in the microenvironment, and a knowledge of the general concentrations of aldehydes in the various microenvironments, a simple model can do a reasonably good job of predicting the time-averaged personal exposures to aldehydes, even in the absence of monitoring data. Although concentrations of aldehydes measured indoors at the participants' homes tracked well with personal exposure, there were instances where personal exposures and indoor concentrations differed significantly. Key to the ability to predict exposure based on time/activity data is the quality and completeness of the microenvironmental characterizations for the chemicals of interest. Consistent with many earlier studies, personal exposures are difficult to predict using data from regional outdoor monitors.     

Parameter evaluation and model validation of ozone exposure assessment using Harvard Southern California Chronic Ozone Exposure Study data

To examine factors influencing long-term ozone (O3) exposures by children living in urban communities, the authors analyzed longitudinal data on personal, indoor, and outdoor O3 concentrations, as well as related housing and other questionnaire information collected in the one-year-long Harvard Southern California Chronic Ozone Exposure Study. Of 224 children contained in the original data set, 160 children were found to have longitudinal measurements of O3 concentrations in at least six months of 12 months of the study period. Data for these children were randomly split into two equal sets: one for model development and the other for model validation. Mixed models with various variance-covariance structures were developed to evaluate statistically important predictors for chronic personal ozone exposures. Model predictions were then validated against the field measurements using an empirical best-linear unbiased prediction technique. The results of model fitting showed that the most important predictors for personal ozone exposure include indoor O3 concentration, central ambient O3 concentration, outdoor O3 concentration, season, gender, outdoor time, house fan usage, and the presence of a gas range in the house. Hierarchical models of personal O3 concentrations indicate the following levels of explanatory power for each of the predictive models: indoor and outdoor O3 concentrations plus questionnaire variables, central and indoor O3 concentrations plus questionnaire variables, indoor O3 concentrations plus questionnaire variables, central O3 concentrations plus questionnaire variables, and questionnaire data alone on time activity and housing characteristics. These results provide important information on key predictors of chronic human exposures to ambient O3 for children and offer insights into how to reliably and cost-effectively predict personal O3 exposures in the future. Furthermore, the techniques and findings derived from this study also have strong implications for selecting the most reliable and cost-effective exposure study design and modeling approaches for other ambient pollutants, such as fine particulate matter and selected urban air toxics.     

How to bend down the environmental Kuznets curve: the significance of biomass energy

Sources of renewable energy have received wide attention in the literature because of serious threats to the environment. However, some renewable resources, including biomass energy role is debatable in the energy economics literature. This empirical work focuses to analyze the role of biomass energy in carbon dioxide (CO₂) emissions using the framework of the environmental Kuznets curve (EKC) in Pakistan over the period from 1980 to 2015. The bound testing approach suggests there is cointegration among study variables. The study uses an auto-regressive distributed lag model (ARDL) with a structural break in the series. To summarize the findings of the study, it can be inferred that biomass energy increase CO₂ emissions. In addition, biomass energy helps to form a U-shaped relationship between income and CO₂ emissions that support the EKC hypothesis. Also, the feedback hypothesis is found between biomass energy and CO₂ emissions. The findings would guide policymaker with practical guidelines to formulate policies to utilize a high amount of biomass energy in a sustainable manner.

     

The influence of biomass energy consumption on CO<Subscript>2</Subscript> emissions: a wavelet coherence approach

In terms of today, one may argue, throughout observations from energy literature papers, that (i) one of the main contributors of the global warming is carbon dioxide emissions, (ii) the fossil fuel energy usage greatly contributes to the carbon dioxide emissions, and (iii) the simulations from energy models attract the attention of policy makers to renewable energy as alternative energy source to mitigate the carbon dioxide emissions. Although there appears to be intensive renewable energy works in the related literature regarding renewables’ efficiency/impact on environmental quality, a researcher might still need to follow further studies to review the significance of renewables in the environment since (i) the existing seminal papers employ time series models and/or panel data models or some other statistical observation to detect the role of renewables in the environment and (ii) existing papers consider mostly aggregated renewable energy source rather than examining the major component(s) of aggregated renewables. This paper attempted to examine clearly the impact of biomass on carbon dioxide emissions in detail through time series and frequency analyses. Hence, the paper follows wavelet coherence analyses. The data covers the US monthly observations ranging from 1984:1 to 2015 for the variables of total energy carbon dioxide emissions, biomass energy consumption, coal consumption, petroleum consumption, and natural gas consumption. The paper thus, throughout wavelet coherence and wavelet partial coherence analyses, observes frequency properties as well as time series properties of relevant variables to reveal the possible significant influence of biomass usage on the emissions in the USA in both the short-term and the long-term cycles. The paper also reveals, finally, that the biomass consumption mitigates CO₂ emissions in the long run cycles after the year 2005 in the USA.     

Foliar injury, leaf gas exchange and biomass responses of black cherry (Prunus serotina Ehrh.) half-sibling families to ozone exposure

Open pollinated families of black cherry seedlings were studied to determine genotypic differences in foliar ozone injury and leaf gas exchange in 1994 and growth response following three growing seasons. An O(3)-sensitive half-sibling family (R-12) and an O(3)-tolerant half-sibling family (MO-7) planted in natural soil were studied along with generic nursery stock (NS) seedlings. Ozone exposure treatments were provided through open top chambers and consisted of 50, 75, and 97% of ambient ozone, and open plots from May 9 to August 26, 1994. Ambient ozone concentrations reached an hourly peak of 88 ppb with 7-hour averages ranging from 39 to 46 ppb. Seedlings in the 50 and 75% of ambient chambers were never exposed to greater than 80 ppb O(3). Visible foliar ozone injury (stipple) was significantly higher for R-12 seedlings than MO-7 seedlings and increased with increasing ozone exposures. For the chamber treatments averaged over all families, there was no significant difference in stomatal conductance and net photosynthetic rates, but there was a significant decrease in root biomass, and a significant decrease in root/shoot ratio between the 50 and 97% of ambient chambers. Stomatal conductance and net photosynthetic rates were significantly different between families with R-12 seedlings generally greater than MO-7 seedlings. The R-12 seedlings had a 7.5 mmol m(-2) increase in ozone uptake compared to MO-7, and at the same cumulative O(3) exposure R-12 exhibited 40.9% stippled leaf area, whereas MO-7 had 9.2% stippled leaf area. Significant differences were observed in stem volume growth and total final biomass between the open-top chambers and open plots. Although R-12 had the most severe foliar ozone injury, this family had significantly greater stem volume growth and total final biomass than MO-7 and NS seedlings. Root:shoot ratio was not significantly different between MO-7 and R-12 seedlings.     

A time series analysis of environmental and metrological factors impact on cutaneous leishmaniasis incidence in an endemic area of Dehloran,Iran

The aim of this study was to investigate the relationship between the environmental and metrological variables and cutaneous leishmaniasis (CL) transmission and its prediction in a region susceptible to this disease prevalence using a time series model. The accurate locations of 4437 CL diagnosed from 2011 to 2015 were obtained to be used in the time series model. Temperature, number of days with temperature over 30 °C, and number of earthquake were related to CL incidence using the Seasonal Auto-correlated Integrated Moving Average (SARIMA) model according to the Box-Jenkins method. In addition, the relationship between land use and surface soil type in 500- and 1000-m radius around the CL patients were investigated. The SARIMA models showed significant associations between environmental and meteorological variables and CL incidence adjusted for seasonality and auto-correlation. The result indicated that there are need more robust preventive programs in earthquake-prone areas with high temperature and inceptisol soil type than other areas. In addition, the region with these characteristics should be considered as high-risk areas for CL prevalence.     

Relating meteorological variables and trends in motor vehicle emissions to monthly urban carbon monoxide concentrations

A model which quantifies the relationship between the monthly time series for CO emissions, the monthly time series in ambient CO concentration, and meteorologically driven dispersion was developed. Fifteen cities representing a wide range of geographical and climatic conditions were selected. An eight-year time series (1984–1991 inclusive) of monthly averaged data were examined in each city. A new method of handling missing ambient concentration values which is designed to calculate city-wide average concentrations that follow the trend seen at individual monitor sites is presented. This method is general and can be used in other applications involving missing data. The model uses emissions estimates along with two meteorological variables (wind speed and mixing height) to estimate monthly averages of ambient air pollution concentrations. The model is shown to have a wide range of applicability; it works equally well for a wide range of cities that have very different temporal CO distributions. The model is suited for assessing long-term trends in ambient air pollutants and can also be used for estimating seasonal variations in concentration, estimation of trends in emissions, and for filling in gaps in the ambient concentration record.     

Parameter Evaluation and Model Validation of Ozone Exposure Assessment Using Harvard Southern California Chronic Ozone Exposure Study Data

Abstract

To examine factors influencing long‐term ozone (O₃) exposures by children living in urban communities, the authors analyzed longitudinal data on personal, indoor, and outdoor O₃ concentrations, as well as related housing and other questionnaire information collected in the one‐year‐long Harvard Southern California Chronic Ozone Exposure Study. Of 224 children contained in the original data set, 160 children were found to have longitudinal measurements of O₃ concentrations in at least six months of 12 months of the study period. Data for these children were randomly split into two equal sets: one for model development and the other for model validation. Mixed models with various variance‐covariance structures were developed to evaluate statistically important predictors for chronic personal ozone exposures. Model predictions were then validated against the field measurements using an empirical best‐linear unbiased prediction technique.The results of model fitting showed that the most important predictors for personal ozone exposure include indoor O₃ concentration, central ambient O₃ concentration, outdoor O₃ concentration, season, gender, outdoor time, house fan usage, and the presence of a gas range in the house. Hierarchical models of personal O₃ concentrations indicate the following levels of explanatory power for each of the predictive models: indoor and outdoor O₃ concentrations plus questionnaire variables, central and indoor O₃ concentrations plus questionnaire variables, indoor O₃ concentrations plus questionnaire variables, central O₃ concentrations plus questionnaire variables, and questionnaire data alone on time activity and housing characteristics. These results provide important information on key predictors of chronic human exposures to ambient O₃ for children and offer insights into how to reliably and cost‐effectively predict personal O₃ exposures in the future. Furthermore, the techniques and findings derived from this study also have strong implications for selecting the most reliable and cost‐effective exposure study design and modeling approaches for other ambient pollutants, such as fine particulate matter and selected urban air toxics.     

Simulation of 1-year-old Populus tremuloides response to ozone stress at Ithaca, USA, and Suwon, Republic of Korea

The growth of 1-year-old aspen was simulated using TREGRO, a computer simulation model of individual tree growth, to assess potential effects of ozone (O3). TREGRO was parameterized using information from a field experiment conducted at Ithaca, NY, USA; the model was then applied using environmental information from Suwon, Korea, where O3 exposures of aspen had not been conducted. In the parameterization at Ithaca, the simulated and measured total biomass differed by about 3% and the differences between measured and simulated biomass gain of leaf, shoot, and root were 15.4, 8.3, and 4.4%, respectively. Simulating growth at Suwon required adjustment in growth rates to match measured growth due to the different weather conditions at the two cities. The assimilated carbon was evenly distributed to each tissue (foliage, branch, stem, coarse, fine roots) in Suwon, whereas it was mainly allocated to vigorous stem growth in Ithaca. The vigorous growth under Suwon conditions resulted in less total non-structural carbon and perhaps trees more vulnerable to O3 stress. Although the ambient O3 in Suwon (1.2 ppm.h of sum of the hourly concentrations greater than 0.06 ppm [SUM06]) was lower than that in Ithaca (2.1 ppm.h of SUM06), a reduction of 8% of total assimilated carbon was found compared to simulation without O3. Severe effects on root growth at elevated O3 (1.7 times ambient) were predicted; however, the effects on leaf growth would not be as severe.     

Responses of bean (Phaseolus vulgaris L. cv. Pros) to chronic ozone exposure at two levels of atmospheric ammonia

Plants of bean (Phaseolus vulgaris cv. Pros) were exposed to a range of O3 concentrations up to 70 nl litre(-1) for 9 h day(-1) in the presence (45 nl litre(-1)) and absence (21 nl litre(-1)) of enhanced NH3 in 12 open-top chambers. Treatment effects on visible injury, growth and yield were assessed after 49 (intermediate harvest) and 62 days of exposure (final harvest). The proportion of leaves with visible injury at final harvest increased with increasing concentrations of O3. Enhanced NH3 did not cause any symptoms and did not affect injury by O3. The estimated seasonal mean concentration corresponding with 5% injury was circa 23 nl litre(-1) O3. Biomass production and green pod yield decreased with increasing concentrations of O3 and were generally stimulated by enhanced NH3 at both harvests. Adverse effects of O3 on biomass and pod yield did not depend on the NH3 level. Relative yield response to increasing 9-h daily mean O3 concentrations was nonlinear and yield losses of 5 and 10% were calculated to occur at seasonal daytime mean concentrations of 27 and 33 nl litre(-1) O3, respectively. Linear regression showed that the Accumulated exposures Over a Threshold of 30 (AOT30) and 40 nl litre(-1) (AOT40) O3 performed equally well. The estimated accumulated O3 exposures corresponding with a yield loss of 5% were 1600 nl litre(-1) h for AOT30 and 400 nl litre(-1) h for AOT40. The results are discussed in relation to the long-term critical level that is used as a guideline to protect crops against adverse effects by O3.     

Characterizing relationships between personal exposures to VOCs and socioeconomic,demographic, behavioral variables

Socioeconomic and demographic factors have been found to significantly affect time-activity patterns in population cohorts that can subsequently influence personal exposures to air pollutants. This study investigates relationships between personal exposures to eight VOCs (benzene, toluene, ethylbenzene, o-xylene, m-,p-xylene, chloroform, 1,4-dichlorobenzene, and tetrachloroethene) and socioeconomic, demographic, time-activity pattern factors using data collected from the 1999–2000 National Health and Nutrition Examination Survey (NHANES) VOC study. Socio-demographic factors (such as race/ethnicity and family income) were generally found to significantly influence personal exposures to the three chlorinated compounds. This was mainly due to the associations paired by race/ethnicity and urban residence, race/ethnicity and use of air freshener in car, family income and use of dry-cleaner, which can in turn affect exposures to chloroform, 1,4-dichlorobenzene, and tetrachloroethene, respectively. For BTEX, the traffic-related compounds, housing characteristics (leaving home windows open and having an attached garage) and personal activities related to the uses of fuels or solvent-related products played more significant roles in influencing exposures. Significant differences in BTEX exposures were also commonly found in relation to gender, due to associated significant differences in time spent at work/school and outdoors. The coupling of Classification and Regression Tree (CART) and Bootstrap Aggregating (Bagging) techniques were used as effective tools for characterizing robust sets of significant VOC exposure factors presented above, which conventional statistical approaches could not accomplish. Identification of these significant VOC exposure factors can be used to generate hypotheses for future investigations about possible significant VOC exposure sources and pathways in the general U.S. population.     

The effect of ozone on below-ground carbon allocation in wheat

Short-term (14)CO(2) pulse and chase experiments were conducted in order to investigate the effect of ozone on below-ground carbon allocation in spring wheat seedlings (Triticum aestivum L. 'ANZA'). Wheat seedlings were grown in a sand-hydroponic system and exposed to either high ozone (38-40 ppm-h) or low ozone (23-31 ppm-h) for 21 days in a series of replicated experiments. Following the ozone exposures, the plants were pulsed with (14)CO(2) and allocation of (14)C-labeled photosynthate was measured in the plant and growth media. Soluble root exudates were measured, without disturbing the plant roots, 24 h after the (14)CO(2) pulse. Shoot biomass was reduced by 17% for the high ozone and 9% for the low ozone exposures, relative to control treatments. Root biomass was reduced by 9% for the high ozone exposures, but was not significantly different than the controls for the low ozone. The amount of (14)C activity in the shoot and root tissue 24 h after the (14)CO(2) pulse, normalized to tissue weight, total (14)CO(2) uptake, or the total (14)C retention in each plant, was not affected by either high or low ozone exposures. The amount of (14)C activity measured in the growth media solution surrounding the roots increased 9% for the high ozone exposures, and after normalizing to root size or root (14)C activity, the growth media solution (14)C activity increased 29 and 40%, respectively. Total respiration of (14)CO(2) from the ozone-treated plants decreased, but the decrease was not statistically significant. Our results suggest that soluble root exudation of (14)C activity to the surrounding rhizosphere increases in response to ozone. Increased root exudation to the rhizosphere in response to ozone is contrary to reports of decreased carbon allocation below ground and suggests that rhizosphere microbial activity may be initially stimulated by plant exposure to ozone.     

Economic complexity,ICT, biomass energy consumption,and environmental degradation: evidence from Iran

Economic complexity, biomass energy consumption, and information communication technology (ICT) have diverse impacts on energy consumption and carbon dioxide (CO₂) emissions. Nevertheless, analysis of these variable effects is not addressed in the previous literature; the antiqueness of this article is stuffing this gap. This study assessed the relationship between gross domestic product (GDP) per capita, biomass consumption, economic complexity index (ECI), ICT, and CO₂ emissions in Iran in 1994–2018. The autoregressive distributed lag (ARDL) model and the quantile regression (QR) econometric technique were used to investigate the factors affecting CO₂ emissions in the tails of the conditional distribution. The share of each influential factor was predicted through the variance decomposition analysis (VD) for the next 10 years. The empirical results showed a long-run relationship between the variables. So, the variables of biomass consumption, ECI, and ICT improve the quality of the environment in Iran by reducing CO₂ emissions, and the per capita GDP variable increases CO₂ emissions. Results suggest no evidence indicating the presence of environmental Kuznets curve (EKC); however, QR demonstrated the existence of EKCs in the lower quantiles of the conditional distribution. The ECI will have the most share to change the CO₂ emissions in the future. The income threshold should be determined at the turning point of the EKC to increase economic development. Moreover, investing in increasing biomass consumption is vital. Policymakers also need to consider strict added value for the export of products.

     

Characterisation of urban inhalation exposures to benzene,formaldehyde and acetaldehyde in the European Union

BACKGROUND, AIM AND SCOPE: All across Europe, people live and work in indoor environments. On average, people spend around 90% of their time indoors (homes, workplaces, cars and public transport means, etc.) and are exposed to a complex mixture of pollutants at concentration levels that are often several times higher than outdoors. These pollutants are emitted by different sources indoors and outdoors and include volatile organic compounds (VOCs), carbonyls (aldehydes and ketones) and other chemical substances often adsorbed on particles. Moreover, legal obligations opposed by legislations, such as the European Union's General Product Safety Directive (GPSD) and Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH), increasingly require detailed understanding of where and how chemical substances are used throughout their life-cycle and require better characterisation of their emissions and exposure. This information is essential to be able to control emissions from sources aiming at a reduction of adverse health effects. Scientifically sound human risk assessment procedures based on qualitative and quantitative human exposure information allows a better characterisation of population exposures to chemical substances. In this context, the current paper compares inhalation exposures to three health-based EU priority substances, i.e. benzene, formaldehyde and acetaldehyde. MATERIALS AND METHODS: Distributions of urban population inhalation exposures, indoor and outdoor concentrations were created on the basis of measured AIRMEX data in 12 European cities and compared to results from existing European population exposure studies published within the scientific literature. By pooling all EU city personal exposure, indoor and outdoor concentration means, representative EU city cumulative frequency distributions were created. Population exposures were modelled with a microenvironment model using the time spent and concentrations in four microenvironments, i.e. indoors at home and at work, outdoors at work and in transit, as input parameters. Pooled EU city inhalation exposures were compared to modelled population exposures. The contributions of these microenvironments to the total daily inhalation exposure of formaldehyde, benzene and acetaldehyde were estimated. Inhalation exposures were compared to the EU annual ambient benzene air quality guideline (5 microg/m3-to be met by 2010) and the recommended (based on the INDEX project) 30-min average formaldehyde limit value (30 microg/m3). RESULTS: Indoor inhalation exposure contributions are much higher compared to the outdoor or in-transit microenvironment contributions, accounting for almost 99% in the case of formaldehyde. The highest in-transit exposure contribution was found for benzene; 29.4% of the total inhalation exposure contribution. Comparing the pooled AIRMEX EU city inhalation exposures with the modelled exposures, benzene, formaldehyde and acetaldehyde exposures are 5.1, 17.3 and 11.8 microg/m3 vs. 5.1, 20.1 and 10.2 microg/m3, respectively. Together with the fact that a dominating fraction of time is spent indoors (>90%), the total inhalation exposure is mostly driven by the time spent indoors. DISCUSSION: The approach used in this paper faced three challenges concerning exposure and time-activity data, comparability and scarce or missing in-transit data inducing careful interpretation of the results. The results obtained by AIRMEX underline that many European urban populations are still exposed to elevated levels of benzene and formaldehyde in the inhaled air. It is still likely that the annual ambient benzene air quality guideline of 5 microg/m3 in the EU and recommended formaldehyde 30-min average limit value of 30 microg/m3 are exceeded by a substantial part of populations living in urban areas. Considering multimedia and multi-pathway exposure to acetaldehyde, the biggest exposure contribution was found to be related to dietary behaviour rather than to inhalation. CONCLUSIONS: In the present study, inhalation exposures of urban populations were assessed on the basis of novel and existing exposure data. The indoor residential microenvironment contributed most to the total daily urban population inhalation exposure. The results presented in this paper suggest that a significant part of the populations living in European cities exceed the annual ambient benzene air quality guideline of 5 microg/m3 in the EU and recommended (INDEX project) formaldehyde 30-min average limit value of 30 microg/m3. RECOMMENDATIONS AND PERSPECTIVES: To reduce exposures and consequent health effects, adequate measures must be taken to diminish emissions from sources such as materials and products that especially emit benzene and formaldehyde in indoor air. In parallel, measures can be taken aiming at reducing the outdoor pollution contribution indoors. Besides emission reduction, mechanisms to effectively monitor and manage the indoor air quality should be established. These mechanisms could be developed by setting up appropriate EU indoor air guidelines.     

Ethnicity,housing and personal factors as determinants of VOC exposures

Previous studies investigating effects of personal, demographic, housing and other factors on exposures to volatile organic compounds (VOC) have focused on mean or median exposures, and generally not the high exposures that are of great interest. This paper identifies determinants of personal VOC exposures on a quantile-specific basis using a nationally representative sample. The NHANES 1999–2000 VOC dataset was merged with personal, demographic, housing, smoking and occupation variables. Bivariate analyses tested for differences in geometric means and quantiles across levels of potential exposure determinants. Multivariate sample-weighted ordinary least-squares (OLS) and quantile regression (QR) models were then used to adjust for covariates. We identify a number of exposure determinants, most of which varied by exposure quantile. The most striking finding was the much higher exposures experienced by Hispanics and Blacks for aromatic VOCs (BTEX: benzene, toluene, ethylbenzene and xylenes), methyl tert-butyl ether (MTBE), and 1,4-dichlorobenzene (DCB). Exposure to gasoline, paints or glues, and having a machine-related occupation also were associated with extremely high BTEX and MTBE exposures. Additional determinants included the presence of attached garages and open windows, which affected exposures of BTEX (especially at lower quantiles) and MTBE (especially at higher quantiles). Smoking also increased BTEX exposures. DCB was associated with air freshener use, and PERC with dry-cleaned clothing. After adjusting for demographic, personal and housing factors, age and gender were not significant predictors of exposure. The use of QR in conjunction with OLS yields a more complete picture of exposure determinants, and identifies subpopulations and heterogeneous exposure groups in which some individuals experience very elevated exposures and which are not well represented by changes in the mean. The high exposures of Hispanics and Blacks are perplexing and disturbing, and they warrant further investigation.     

Improved computational model (AQUIFAS) for activated sludge, integrated fixed-film activated sludge, and moving-bed biofilm reactor systems, Part I: Semi-empirical model development

Research was undertaken to develop a model for activated sludge, integrated fixed-film activated sludge (IFAS), and moving-bed biofilm reactor (MBBR) systems. The model can operate with up to 12 cells (reactors) in series, with biofilm media incorporated to one or more cells, except the anaerobic cells. The process configuration can be any combination of anaerobic, anoxic, aerobic, post-anoxic with or without supplemental carbon, and reaeration; it can also include any combination of step feed and recycles, including recycles for mixed liquor, return activated sludge, nitrates, and membrane bioreactors. This paper presents the structure of the model. The model embeds a biofilm model into a multicell activated sludge model. The biofilm flux rates for organics, nutrients, and biomass can be computed by two methods--a semi-empirical model of the biofilm that is relatively simpler, or a diffusional model that is computationally intensive. The values of the kinetic parameters for the model were measured using pilot-scale activated sludge, IFAS, and MBBR systems. For the semiempirical version, a series of Monod equations were developed for chemical oxygen demand, ammonium-nitrogen, and oxidized-nitrogen fluxes to the biofilm. Within the equations, a second Monod expression is used to simulate the effect of changes in biofilm thickness and fraction nitrifiers in the biofilm. The biofilm flux model is then linked to the activated sludge model. The diffusional model and the verification of the models are presented in subsequent papers (Sen and Randall, 2008a, 2008b). The model can be used to quantify the amount of media and surface area required to achieve nitrification, identify the best locations for the media, and optimize the dissolved oxygen levels and nitrate recycle rates. Some of the advanced features include the ability to apply different media types and fill fractions in cells; quantify nitrification, denitrification, and biomass production in the biofilm and mixed liquor suspended solids; and perform dynamic simulations.     

Estimating contribution of wildland fires to ambient ozone levels in National Parks in the Sierra Nevada, California

Data from four continuous ozone and weather monitoring sites operated by the National Park Service in Sierra Nevada, California, are used to develop an ozone forecasting model and to estimate the contribution of wildland fires on ambient ozone levels. The analyses of weather and ozone data pointed to the transport of ozone precursors from the Central Valley as an important source of pollution in these National Parks. Comparisons of forecasted and observed values demonstrated that accurate forecasts of next-day hourly ozone levels may be achieved by using a time series model with historic averages, expected local weather and modeled PM values as explanatory variables. Results on fire smoke influence indicated occurrence of significant increases in average ozone levels with increasing fire activity. The overall effect on diurnal ozone values, however, was small when compared with the amount of variability attributed to sources other than fire.     

Workplace and Environmental Air Contaminant Concentrations Measured by Open Path Fourier Transform Infrared Spectroscopy: A Statistical Process Control Technique to Detect Changes from Normal Operating Conditions

Open path Fourier transform infrared (OP-FTIR) spectroscopy is a new air monitoring technique that can be used to measure concentrations of air contaminants in real or near-real time. OP-FTIR spectroscopy has been used to monitor workplace gas and vapor exposures, emissions from hazardous waste sites, and to track emissions along fence lines. This paper discusses a statistical process control technique that can be used with air monitoring data collected with an OP-FTIR spectrometer to detect departures from normal operating conditions in the workplace or along a fence line. Time series data, produced by plotting consecutive air sample concentrations in time, were analyzed. Autocorrelation in the time series data was removed by fitting dynamic models. Control charts were used with the residuals of the model fit data to determine if departures from defined normal operating conditions could be rapidly detected. Shewhart and exponentially weighted moving average (EWMA) control charts were evaluated for use with data collected under different room air flow and mixing conditions.

Under rapidly changing conditions the Shewhart control chart was able to detect a leak in a simulated process area. The EWMA control chart was found to be more sensitive to drifts and slowly changing concentrations in air monitoring data. The time series and statistical process control techniques were also applied to data obtained during a field study at a chemical plant. A production area of an acrylonitrile, 1,3-butadiene, and styrene (ABS) polymer process was monitored in near-real time. Decision logics based on the time series and statistical process control technique introduced suggest several applications in workplace and environmental monitoring. These applications might include signaling of an alarm or warning, increasing levels of worker respiratory protection, or evacuation of a community, when gas and vapor concentrations are determined to be out-of-control.     

Phytoremediation of Cadmium-Contaminated Soils by Rorippa globosa Using Two-Phase Planting (5 pp)

Background Phytoextraction of contaminated soils by heavy metals can provide a great promise of commercial development. Although there are more than 400 species of hyperaccumulators found in the world, phytoremediation technology is rarely applied in field practice for remedying contaminated soils, partially due to low biomass and long growth duration for most of discovered hyperaccumulating plants. In order to enhance the metal-removing efficiency in a year, the two-phase planting countermeasure of phytoextraction by harvesting anthesis biomass was investigated on the basis of the newly found Cd-hyperaccumulator Rorippa globosa (Turcz.) Thell. with 107.0 and 150.1 mg/kg of the Cd accumulation in stems and leaves, respectively, when soil Cd added was concentrated to 25.0 mg/kg. Methods The field pot-culture experiment was used to observe the distribution property of R. globosa aboveground biomass and to examine characteristics of accumulating Cd by the plant at different growth stages. The concentration of Cd in plants and soils was determined using atomic absorption spectrophotometry (AAS). Results and Discussion The results indicated that the total dry stem and leaf biomass of R. globosa harvested at the flowering phase was up to 92.3% of that at its full maturity and the concentration of Cd in stems and leaves harvested at the flowering phase was up to 73.8% and 87.7% of that at the mature phase, respectively. The Cd-removing ratio by shoots of R. globosa harvested at the flowering phase was up to 71.4% of that at the mature phase. It was also found, by observing the growth duration of R. globosa, that the frostless period at the experiment site was twice as long as the growth time from the seedling-transplanted phase to the flowering phase of the hyperaccumulator. Conclusion R. globosa could be transplanted into contaminated soils twice in one year by harvesting the hyperaccumulator at its flowering phase based on climatic conditions of the site and traits of the plant growth. In this sense, the extraction efficiency of Cd in shoots of R. globosa increased 42.8% compared to that of at its single maturity when the plant was transplanted into contaminated soils after it had been harvested at its flowering phase and the plant accumulated Cd from soil at the same extraction ratio at its second flowering phase. Thus, the method of anthesis biomass regulation by the two-phase planting is very significant to increase the Cd-removing efficiency by phytoremediation used in practice over the course of a year. Recommendation and Outlook As for some hyperaccumulators that the growth duration from the seedling-transplanted phase to the flowering phase are short and the concentrations of heavy metals accumulated in their shoots at the flowering phase are high, the efficiency of phytoremediation can greatly be improved using the method of the two-phase planting.