The delayed neutron emission rates of U-235 and Pu-239 samples were measured accurately from a thermal fission reaction. A Monte Carlo calculation using the Geant4 code was used to demonstrate the neutron energy independence of the detector used in the counting station. A set of highly purified actinide samples (U-235 and Pu-239) was irradiated in these experiments by using the Texas A&M University Nuclear Science Center Reactor. A fast pneumatic transfer system, an integrated computer control system, and a graphite-moderated counting system were constructed to perform all these experiments. The calculated values for the five-group U-235 delayed neutron parameters and the six-group Pu-239 delayed neutron parameters were compared with the values recommended by Keepin et al. (1957) and Waldo et al. (1981). These new values differ slightly from literature values. The graphite-moderated counting station and the computerized pneumatic system are now operational for further delayed neutron measurement.

There are many U.S. health-related standards for ozone that aim to limit exposure to ozone. The potential for ozone emission from electrically connected air cleaners is well- known and has led to standards and regulations for portable indoor air cleaning devices, which emit ozone at measured rates of 0.056 – 13.4 mg/hr. However, there is evidence that some in-duct air cleaners may actually emit more ozone than portable air cleaners, despite being exempt from most regulations due to the lack of a suitable test method for measuring ozone generation. To explore if in-duct cleaners actually do emit ozone, I investigated seven commercially available residential in-duct air cleaning devices. These devices used one of two broad technologies as means of air cleaning: UV light or electrical corona. The lowest measured emission rates came from two air cleaners that utilized UV light technology and were 0.309 ± 1.7 mg/hr, which was likely below the detection limit of the apparatus and method, and 4.29± 1.5 mg/hr. Three of the air cleaners tested, also with UV lamps, were of the same brand and model yet exhibited differing emission rates, ranging from 7.44± 1.6 mg/hr to 15.8± 2.6 mg/hr. These three air cleaners were classified as medium emitters and also utilized UV light technology. The high median measured emission rates were measured from both an air cleaner utilizing electrical corona technology, 30.2 ± 4.0 mg/hr, and UV light technology, 29.4 ± 3.9 mg/hr. These experimental results confirm that some in-duct air cleaners are able to generate more ozone than some portable air cleaners and also suggest potential health risks to the indoor environment. / text

With the continued population growth and the blurring of the urban and rural interface, air quality impacts associated with agricultural particle-producing processes are becoming increasingly important. There is a lack of emission rate data from these source types and no prescribed measurement technique available to the agricultural and regulatory communities. One technique that has shown promise is combining field measurements with inverse modeling. This approach was used herein to examine particulate emissions from an almond harvesting operation, a cotton ginning facility, and comparative emissions from conservation versus conventional tillage practices. EPAapproved models ISCST3 and AERMOD were used with AirMetrics samplers. With error representing the standard deviation for all values, for ISCST3, the almond harvesting operation found PM10 emissions for shaking were 3.4 kilograms per hectare; PM2.5, PM10, and TSP emissions for sweeping were 0.81 ± 0.76, 4.8 ± 3.7, and 7.5 ± 5.1 kg ha-1, respectively; PM2.5, PM10, and TSP emissions for pickup were 1.7 ± 1.5, 6.1 ± iii 1.9, and 10.3 ± 3.8 kg ha-1, respectively. Using AERMOD, the almond harvesting operation found PM10 emissions for shaking were 4.4 kg ha-1; PM2.5, PM10, and TSP emissions for sweeping were 1.3 ± 1.5, 8.3 ± 9.4, and 27.0 ± 41.2 kg ha-1, respectively; PM2.5, PM10, and TSP emissions for pickup were 2.7 ± 1.3, 15.7 ± 14.1, and 42.3 ± 20.7 kg ha-1, respectively. PM2.5, PM10, and TSP emissions from the cotton gin were determined to be 1.7 ± 1.4, 14.3 ± 17.0, and 27.9 ± 41.1 g s-1 using ISCST3 and 0.9 ± 0.9, 10.5 ± 18.8, and 43.0 ± 79.9 g s-1 using AERMOD, respectively. ISCST3 emission rates for the combined tillage operations for PM2.5, PM10, and TSP were 0.15 ± 0.24, 0.44 ± 0.17, and 1.4 kg acre-1, while AERMOD rates were 0.17 ± 0.27, 0.66 ± 0.25, and 2.1 kg acre-1, respectively. ISCST3 emissions for the conventional tillage operations for PM2.5, PM10, and TSP were 0.47 ± 2.1, 1.1 ± 0.23, and 3.4 kg acre-1, and the AERMOD rates were 0.18 ± 0.26, 1.2 ± 0.24, and 5.1 kg acre-1, respectively.

Heavy-duty diesel vehicle (HDDV) operations are a major source of pollutant emissions in major metropolitan areas. Accurate estimation of heavy-duty diesel vehicle emissions is essential in air quality planning efforts because highway and non-road heavy-duty diesel emissions account for a significant fraction of the oxides of nitrogen (NOx) and particulate matter (PM) emissions inventories. Yet, major modeling deficiencies in the current MOBILE6 modeling approach for heavy-duty diesel vehicles have been widely recognized for more than ten years. While the most recent MOBILE6.2 model integrates marginal improvements to various internal conversion and correction factors, fundamental flaws inherent in the modeling approach still remain. The major effort of this research is to develop a new heavy-duty vehicle load-based modal emission rate model that overcomes some of the limitations of existing models and emission rates prediction methods. This model is part of the proposed Heavy-Duty Diesel Vehicle Modal Emission Modeling (HDDV-MEM) which was developed by Georgia Institute of Technology. HDDV-MEM first predicts second-by-second engine power demand as a function of vehicle operating conditions and then applies brake-specific emission rates to these activity predictions. To provide better estimates of microscopic level, this modeling approach is designed to predict second-by-second emissions from onroad vehicle operations. This research statistically analyzes the database provided by EPA and yields a model for prediction emissions at microscopic level based on engine power demand and driving mode. Research results will enhance the explaining ability of engine power demand on emissions and the importance of simulating engine power in real world applications. The modeling approach provides a significant improvement in HDDV emissions modeling compared to the current average speed cycle-based emissions models.

The Canadian livestock industry generates 150 million tonnes of manure annually and the majority of this manure is land applied. This practice allows the manure nutrients to be recycled to the soil crop system while improving soil fertility. However, land application of manure has the potential to negatively impact soil, water, and air quality if not managed properly. Microbial processes transform the manure nutrients into forms that are susceptible to leaching or volatilization. Balancing the nutrient loss dynamics from fertilized soil is very difficult because the nutrient transformations are affected by the soil environment such as air and water content, pH, and labile carbon content. All of these soil environmental factors can be influenced by manure application practices such as application rate, timing, and manure placement. Knowledge of how these management practices affect the soil environment can help producers make management decisions that reduce the likelihood of soil, water, and air contamination from manure application.<p> Very few data exist on how manure application practices affect odour emissions after spreading. Therefore, the efficiency of subsurface application in reducing odours from manure spreading for both solid and liquid manure was assessed. Flux chambers and dynamic dilution olfactometry were used to measure odour emissions from five livestock manure species applied at three application rates using surface and subsurface application methods. The results indicated that odour concentrations from injected plots were up to 66% (37% on average) lower than concentrations from broadcast applications. Injection seemed to have a larger impact on reducing odours from solid manure than liquid manure, mainly due to efficient manure coverage from solid manure injection. Odours measured immediately after solid manure applications were also 37% lower than from liquid manure applications. In general, odours from both manure types increased with higher application rates, but there was little difference in the odours among low, mid, and high application rates. The specific odour rate (odour emission rate per kg N applied) decreased with application rate due to the reduced surface area available for volatilization of compounds with higher application rates. Based on these results, injection of manure is an effective way to reduce the odour emissions immediately after spreading, particularly for solid manure. However, other factors associated with manure injection, such as the increased power requirement and soil disturbance must be considered when evaluating the overall impact of manure injection versus surface application.<p> The odour data collected in this study described how management practices affected odours immediately after spreading. Knowledge of how these practices affect the emission rate trend over time is required to apply dispersion models to optimize the minimum separation distances for manure spreading activities. The model parameters for an existing volatilization model were determined from field and literature data and the resulting model allowed the effects of application mode (surface vs. subsurface) and manure type (liquid vs. solid) on odour emissions for 48 hours after application to be simulated. The effects of injection depth and a coverage factor on emissions were also simulated. The modeled peak fluxes from liquid manure applications were higher than those for solid manure applications, but the extended duration of odour emissions from solid manure resulted in higher cumulative losses from solid manure applications. While the application rate had no effect on the initial odour flux, higher application rates resulted in higher peak fluxes, higher overall emissions, and longer odour durations for both manure types and application methods. Modest injection depths were shown to reduce odours from both liquid and solid manure applications compared to surface spreading. The percent reductions in cumulative odours due to injection were estimated assuming typical coverage factors. The general predictions of the model developed in this study agree reasonably well with odour emission rate trends reported in literature. Future work should focus on better estimation of the model parameters and the variation of effective diffusivity with time and soil conditions.<p> Greenhouse gas (GHG) emissions from agricultural activities such as land application of livestock manure cannot be ignored when assessing overall emissions from anthropogenic sources. Like odour emissions, the magnitude of the GHG emissions will be influenced by management practices such as manure placement during land application. The GHG fluxes resulting from the surface and subsurface application of liquid and solid manure were also compared within 24 hours of application using a static chamber and gas chromatography. The results showed that carbon dioxide equivalent (CO2-e) fluxes were approximately three times higher from the injected plots than the surface plots for both solid and liquid manure. The elevated CO2-e fluxes were mainly due to a pronounced increase in N2O fluxes which was likely caused by increased denitrification rates. The CO2-e fluxes from the liquid manure applications were also approximately three times higher than the CO2-e fluxes from the solid manure applications, probably due to higher levels of ammonium available for nitrification and subsequent denitrification. The CH4 fluxes were generally low and the treatments had no effect. The measured specific fluxes (total flux per kg N applied) remained relatively constant with application rate, indicating that, in this study, GHG emissions from manure applications were approximately proportional to the amount of land applied manure.<p> While the data from this study showed that manure type and placement influenced short-term nitrous oxide (N2O) emissions, manure management practices (particularly slurry injection or solid manure incorporation) have the potential to influence long-term emissions by changing the magnitude and pattern of the nitrogen cycle in the soil-plant system. Management practices also impact the magnitude of other nitrogen losses (ammonia volatilization, nitrate leaching) which affect indirect N2O emissions. A model that simulates the environmental conditions and nutrient transformations after manure application may allow a more reliable prediction of the effect of management practices on total GHG emissions. Numerous process-based models have been used to estimate N2O emissions as influenced by agricultural practices in Canada. However, these models do not account for enhanced denitrification that potentially exists after slurry injection or manure incorporation, resulting in an underestimation of N2O emissions. A simple mass balance of nitrogen after application to land showed that enhanced denitrification can increase total N2O-N emissions by a factor of 5. By accounting for the increased microbial activity, slower oxygen diffusion and higher water filled pore space that exists after manure injection, models may better estimate N2O emissions from manure application practices.

The Canadian livestock industry generates 150 million tonnes of manure annually and the majority of this manure is land applied. This practice allows the manure nutrients to be recycled to the soil crop system while improving soil fertility. However, land application of manure has the potential to negatively impact soil, water, and air quality if not managed properly. Microbial processes transform the manure nutrients into forms that are susceptible to leaching or volatilization. Balancing the nutrient loss dynamics from fertilized soil is very difficult because the nutrient transformations are affected by the soil environment such as air and water content, pH, and labile carbon content. All of these soil environmental factors can be influenced by manure application practices such as application rate, timing, and manure placement. Knowledge of how these management practices affect the soil environment can help producers make management decisions that reduce the likelihood of soil, water, and air contamination from manure application.<p> Very few data exist on how manure application practices affect odour emissions after spreading. Therefore, the efficiency of subsurface application in reducing odours from manure spreading for both solid and liquid manure was assessed. Flux chambers and dynamic dilution olfactometry were used to measure odour emissions from five livestock manure species applied at three application rates using surface and subsurface application methods. The results indicated that odour concentrations from injected plots were up to 66% (37% on average) lower than concentrations from broadcast applications. Injection seemed to have a larger impact on reducing odours from solid manure than liquid manure, mainly due to efficient manure coverage from solid manure injection. Odours measured immediately after solid manure applications were also 37% lower than from liquid manure applications. In general, odours from both manure types increased with higher application rates, but there was little difference in the odours among low, mid, and high application rates. The specific odour rate (odour emission rate per kg N applied) decreased with application rate due to the reduced surface area available for volatilization of compounds with higher application rates. Based on these results, injection of manure is an effective way to reduce the odour emissions immediately after spreading, particularly for solid manure. However, other factors associated with manure injection, such as the increased power requirement and soil disturbance must be considered when evaluating the overall impact of manure injection versus surface application.<p> The odour data collected in this study described how management practices affected odours immediately after spreading. Knowledge of how these practices affect the emission rate trend over time is required to apply dispersion models to optimize the minimum separation distances for manure spreading activities. The model parameters for an existing volatilization model were determined from field and literature data and the resulting model allowed the effects of application mode (surface vs. subsurface) and manure type (liquid vs. solid) on odour emissions for 48 hours after application to be simulated. The effects of injection depth and a coverage factor on emissions were also simulated. The modeled peak fluxes from liquid manure applications were higher than those for solid manure applications, but the extended duration of odour emissions from solid manure resulted in higher cumulative losses from solid manure applications. While the application rate had no effect on the initial odour flux, higher application rates resulted in higher peak fluxes, higher overall emissions, and longer odour durations for both manure types and application methods. Modest injection depths were shown to reduce odours from both liquid and solid manure applications compared to surface spreading. The percent reductions in cumulative odours due to injection were estimated assuming typical coverage factors. The general predictions of the model developed in this study agree reasonably well with odour emission rate trends reported in literature. Future work should focus on better estimation of the model parameters and the variation of effective diffusivity with time and soil conditions.<p> Greenhouse gas (GHG) emissions from agricultural activities such as land application of livestock manure cannot be ignored when assessing overall emissions from anthropogenic sources. Like odour emissions, the magnitude of the GHG emissions will be influenced by management practices such as manure placement during land application. The GHG fluxes resulting from the surface and subsurface application of liquid and solid manure were also compared within 24 hours of application using a static chamber and gas chromatography. The results showed that carbon dioxide equivalent (CO2-e) fluxes were approximately three times higher from the injected plots than the surface plots for both solid and liquid manure. The elevated CO2-e fluxes were mainly due to a pronounced increase in N2O fluxes which was likely caused by increased denitrification rates. The CO2-e fluxes from the liquid manure applications were also approximately three times higher than the CO2-e fluxes from the solid manure applications, probably due to higher levels of ammonium available for nitrification and subsequent denitrification. The CH4 fluxes were generally low and the treatments had no effect. The measured specific fluxes (total flux per kg N applied) remained relatively constant with application rate, indicating that, in this study, GHG emissions from manure applications were approximately proportional to the amount of land applied manure.<p> While the data from this study showed that manure type and placement influenced short-term nitrous oxide (N2O) emissions, manure management practices (particularly slurry injection or solid manure incorporation) have the potential to influence long-term emissions by changing the magnitude and pattern of the nitrogen cycle in the soil-plant system. Management practices also impact the magnitude of other nitrogen losses (ammonia volatilization, nitrate leaching) which affect indirect N2O emissions. A model that simulates the environmental conditions and nutrient transformations after manure application may allow a more reliable prediction of the effect of management practices on total GHG emissions. Numerous process-based models have been used to estimate N2O emissions as influenced by agricultural practices in Canada. However, these models do not account for enhanced denitrification that potentially exists after slurry injection or manure incorporation, resulting in an underestimation of N2O emissions. A simple mass balance of nitrogen after application to land showed that enhanced denitrification can increase total N2O-N emissions by a factor of 5. By accounting for the increased microbial activity, slower oxygen diffusion and higher water filled pore space that exists after manure injection, models may better estimate N2O emissions from manure application practices.

Air emissions from animal feeding operations have become a growing concern. Much work has been done to study occupational exposures and the exhaust concentrations associated with animal facilities; however little information has been provided about air quality around the houses. Ammonia (NH3 ), ethanol (EtOH), nitrous oxide (N2O), carbon dioxide (CO2), and particulate matter (PM 2.5 and PM10) emissions were monitored in two different buildings for laying hens in northern Utah. Over the six-month sampling period, the observed average temperatures for the west and east fan banks of the high-rise building were 21.2±4 and 19.4±1.3°C, respectively, and the average inside relative humidities during the same period were 43.7±7.2 and 48.4±7.9%, respectively. Furthermore, the observed average temperatures for the west and east fan banks of the manure-belt building were 20.6±4.4 and 17.9±2.7°C, respectively, and the average percent inside relative humidities during the same period were 44.4 ±7.6 and 49.3±7.4%, respectively. The ventilation rates ranged from 0.80 m3 h-1 bird-1 to 4.80 m3 h-1 bird -1 with an average of 2.02 m3 h -1 bird -1 for the high-rise barn and from 0.80 m3 h-1 bird -1 to 6.0 m3 h-1 bird-1 with an average of 2.20 m3 h-1 bird-1 for the manure-belt building over the sampling period of September, October, November, and December 2008 and January 2009. Average NH3 emission factors were 72±17 g d-1 AU-1 for the high-rise system and 9.1±7 g d-1 AU-1 for the manure-belt (1 AU is equal to 500 kg of animal live weight). The NH3 emission reduction factor for the manure-belt technique compared to the high-rise technique was 87%. Ammonia levels outside the house appeared to be less than 1 ppm. No significant emissions were registered for N2O, H2S, and EtOH, which were consistently close to zero for both techniques. The carbon dioxide (CO2) emission factor from the high-rise building was 104±11 g day-1 AU-1 and from the manure-belt building, 105±20 g day-1 AU-1. PM emissions were greater from the manure-belt system in comparison with the high-rise system, showing mean values of 165 vs. 114 g day-1 AU-1 for PM 2.5, 1,987 vs. 1,863 g day-1 AU-1for PM10 and 4,460 vs. 3,462 g day-1 AU-1 for TSP respectively. None of the 24-h PM 2.5 measurements collected from both management techniques exceeded the U.S. EPA 24-hr National Ambient Air Quality Standard (NAAQS) of 35 μg/m 3.

No description available.

Στα πλαίσια της εργασίας θα ασχοληθούμε με την μεθοδολογία υπολογισμού των ρυθμών εκπομπής αέριων ρύπων στα αστικά κέντρα της Ελλάδας. Οι πήγες της ατμοσφαιρικής ρύπανσης διακρίνονται σε σημειακές, επιφανειακές, ανθρωπογενείς και φυσικές. Στο πρώτο στάδιο θα γίνει καταγραφή και κατηγοριοποίηση των διαφόρων πηγών για τις Ελληνικές συνθήκες με βάση την διεθνή βιβλιογραφία. Οι μέθοδοι προσδιορισμού των ρυθμών εκπομπής θα διερευνηθούν. Συνήθως οι υπολογισμοί απαιτούν δυο ειδών παραμέτρους: την ένταση μιας δραστηριότητας (π.χ πόσα χιλιόμετρα διανύονται σε μια περιοχή από τα αυτοκίνητα μιας ορισμένης κατηγορίας σε μια περιοχή), και τον ρυθμό εκπομπής ανά μονάδα της δραστηριότητας (π.χ εκπομπές οξειδίων του αζώτου ανά χιλιόμετρο). Ανάλογα με την πηγή οι μέθοδοι μπορεί να είναι πιο πολύπλοκοι ή να απαιτούν την γνώση μεταβλητών που δεν είναι εύκολο να βρεθούν. Οι διαφορετικές προσεγγίσεις θα συγκριθούν τόσο με βάση την ακρίβεια τους όσο και με την δυνατότητα εφαρμογής τους στην Ελλάδα. Το τελικό αποτέλεσμα της εργασίας θα είναι μια αναλυτική μεθοδολογία υπολογισμού των εκπομπών ρύπων σε μια Ελληνική πόλη και συγκεκριμένα στην πόλη της Πάτρας, όπου θα μελετηθεί η εκπομπή αέριων ρύπων από τα επιβατικά πλοία τα οποία χρησιμοποιούν το λιμάνι της Πάτρας. Η παρούσα εργασία θα στοχεύσει στον προσδιορισμό της συγκέντρωσης αέριων ρύπων (σωματιδίων PM) στο αστικό κέντρο της Πάτρας, λαμβάνοντας ως πηγή ρύπων τα επιβατικά πλοία που παραμένουν στο Λιμάνι της Πάτρας. Η συγκέντρωση των αέριων ρύπων τέλος, θα υπολογισθεί με χρήση της Gaussian Plume Formula [JS Seinfeld and SN Pandis: “Atmospheric Chemistry and Physics: From Air Pollution to Climate Change”, 2nd edition, John Willey & Sons, INC]. / -

Engineering directly impacts current and future regulatory policy decisions. The foundation of air pollution control and air pollution dispersion modeling lies in the math, chemistry, and physics of the environment. Therefore, regulatory decision making must rely upon sound science and engineering as the core of appropriate policy making (objective analysis in lieu of subjective opinion). This research evaluated particulate matter and ammonia concentration data as well as two modeling methods, a backward Lagrangian stochastic model and a Gaussian plume dispersion model. This analysis assessed the uncertainty surrounding each sampling procedure in order to gain a better understanding of the uncertainty in the final emission rate calculation (a basis for federal regulation), and it assessed the differences between emission rates generated using two different dispersion models. First, this research evaluated the uncertainty encompassing the gravimetric sampling of particulate matter and the passive ammonia sampling technique at an animal feeding operation. Future research will be to further determine the wind velocity profile as well as determining the vertical temperature gradient during the modeling time period. This information will help quantify the uncertainty of the meteorological model inputs into the dispersion model, which will aid in understanding the propagated uncertainty in the dispersion modeling outputs. Next, an evaluation of the emission rates generated by both the Industrial Source Complex (Gaussian) model and the WindTrax (backward-Lagrangian stochastic) model revealed that the calculated emission concentrations from each model using the average emission rate generated by the model are extremely close in value. However, the average emission rates calculated by the models vary by a factor of 10. This is extremely troubling. In conclusion, current and future sources are regulated based on emission rate data from previous time periods. Emission factors are published for regulation of various sources, and these emission factors are derived based upon back-calculated model emission rates and site management practices. Thus, this factor of 10 ratio in the emission rates could prove troubling in terms of regulation if the model that the emission rate is back-calculated from is not used as the model to predict a future downwind pollutant concentration.