Matching Items (6)
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- All Subjects: Atmospheric science
- Creators: Herckes, Pierre
- Creators: Moustaoui, Mohamed
Description
This thesis outlines the development of a vector retrieval technique, based on data assimilation, for a coherent Doppler LIDAR (Light Detection and Ranging). A detailed analysis of the Optimal Interpolation (OI) technique for vector retrieval is presented. Through several modifications to the OI technique, it is shown that the modified technique results in significant improvement in velocity retrieval accuracy. These modifications include changes to innovation covariance portioning, covariance binning, and analysis increment calculation. It is observed that the modified technique is able to make retrievals with better accuracy, preserves local information better, and compares well with tower measurements. In order to study the error of representativeness and vector retrieval error, a lidar simulator was constructed. Using the lidar simulator a thorough sensitivity analysis of the lidar measurement process and vector retrieval is carried out. The error of representativeness as a function of scales of motion and sensitivity of vector retrieval to look angle is quantified. Using the modified OI technique, study of nocturnal flow in Owens' Valley, CA was carried out to identify and understand uncharacteristic events on the night of March 27th 2006. Observations from 1030 UTC to 1230 UTC (0230 hr local time to 0430 hr local time) on March 27 2006 are presented. Lidar observations show complex and uncharacteristic flows such as sudden bursts of westerly cross-valley wind mixing with the dominant up-valley wind. Model results from Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS®) and other in-situ instrumentations are used to corroborate and complement these observations. The modified OI technique is used to identify uncharacteristic and extreme flow events at a wind development site. Estimates of turbulence and shear from this technique are compared to tower measurements. A formulation for equivalent wind speed in the presence of variations in wind speed and direction, combined with shear is developed and used to determine wind energy content in presence of turbulence.
ContributorsChoukulkar, Aditya (Author) / Calhoun, Ronald (Thesis advisor) / Mahalov, Alex (Committee member) / Kostelich, Eric (Committee member) / Huang, Huei-Ping (Committee member) / Phelan, Patrick (Committee member) / Arizona State University (Publisher)
Created2013
Description
Americans spend upwards of 90% of their time indoors, hence indoor air quality (IAQ) and the impact of IAQ on human health is a major public health concern. IAQ can be negatively impacted by outdoor pollution infiltrating indoors, the emission of indoor pollutants, indoor atmospheric chemistry and poor ventilation. Energy saving measures like retrofits to seal the building envelope to prevent the leakage of heated or cooled air will impact IAQ. However, existing studies have been inconclusive as to whether increased energy efficiency is leading to detrimental IAQ. In this work, field campaigns were conducted in apartment homes in Phoenix, Arizona to evaluate IAQ as it relates to particulate matter (PM), carbonyls, and tobacco specific nitrosamines (TSNA).
To investigate the impacts of an energy efficiency retrofit on IAQ, indoor and outdoor air quality sampling was carried out at Sunnyslope Manor, a city-subsidized senior living apartment complex. Measured indoor formaldehyde levels before the building retrofit exceeded reference exposure limits, but in the long term follow-up sampling, indoor formaldehyde decreased for the entire study population by a statistically significant margin. Indoor PM levels were dominated by fine particles and showed a statistically significant decrease in the long term follow-up sampling within certain resident subpopulations (i.e. residents who reported smoking and residents who had lived longer at the apartment complex). Additionally, indoor glyoxal and methylglyoxal exceeded outdoor concentrations, with methylglyoxal being more prevalent pre-retrofit than glyoxal, suggesting different chemical pathways are involved. Indoor concentrations reported are larger than previous studies. TSNAs, specifically N'-nitrosonornicotine (NNN), 4-(methyl-nitrosamino)-4-(3-pyridyl)-butanal (NNA) and 4-(methylnitrosoamino)-1-(3-pyridyl)-1-butanone (NNK) were evaluated post-retrofit at Sunnyslope Manor. Of the units tested, 86% of the smoking units and 46% of the non-smoking units had traces of at least one of the nitrosamines.
To investigate the impacts of an energy efficiency retrofit on IAQ, indoor and outdoor air quality sampling was carried out at Sunnyslope Manor, a city-subsidized senior living apartment complex. Measured indoor formaldehyde levels before the building retrofit exceeded reference exposure limits, but in the long term follow-up sampling, indoor formaldehyde decreased for the entire study population by a statistically significant margin. Indoor PM levels were dominated by fine particles and showed a statistically significant decrease in the long term follow-up sampling within certain resident subpopulations (i.e. residents who reported smoking and residents who had lived longer at the apartment complex). Additionally, indoor glyoxal and methylglyoxal exceeded outdoor concentrations, with methylglyoxal being more prevalent pre-retrofit than glyoxal, suggesting different chemical pathways are involved. Indoor concentrations reported are larger than previous studies. TSNAs, specifically N'-nitrosonornicotine (NNN), 4-(methyl-nitrosamino)-4-(3-pyridyl)-butanal (NNA) and 4-(methylnitrosoamino)-1-(3-pyridyl)-1-butanone (NNK) were evaluated post-retrofit at Sunnyslope Manor. Of the units tested, 86% of the smoking units and 46% of the non-smoking units had traces of at least one of the nitrosamines.
ContributorsFrey, Sarah E (Author) / Herckes, Pierre (Thesis advisor) / Fraser, Matthew P (Thesis advisor) / Destaillats, Hugo (Committee member) / Chizmeshya, Andrew (Committee member) / Arizona State University (Publisher)
Created2014
Description
The role of environmental factors that influence atmospheric propagation of sound originating from freeway noise sources is studied with a combination of field experiments and numerical simulations. Acoustic propagation models are developed and adapted for refractive index depending upon meteorological conditions. A high-resolution multi-nested environmental forecasting model forced by coarse global analysis is applied to predict real meteorological profiles at fine scales. These profiles are then used as input for the acoustic models. Numerical methods for producing higher resolution acoustic refractive index fields are proposed. These include spatial and temporal nested meteorological simulations with vertical grid refinement. It is shown that vertical nesting can improve the prediction of finer structures in near-ground temperature and velocity profiles, such as morning temperature inversions and low level jet-like features. Accurate representation of these features is shown to be important for modeling sound refraction phenomena and for enabling accurate noise assessment. Comparisons are made using the acoustic model for predictions with profiles derived from meteorological simulations and from field experiment observations in Phoenix, Arizona. The challenges faced in simulating accurate meteorological profiles at high resolution for sound propagation applications are highlighted and areas for possible improvement are discussed.
A detailed evaluation of the environmental forecast is conducted by investigating the Surface Energy Balance (SEB) obtained from observations made with an eddy-covariance flux tower compared with SEB from simulations using several physical parameterizations of urban effects and planetary boundary layer schemes. Diurnal variation in SEB constituent fluxes are examined in relation to surface layer stability and modeled diagnostic variables. Improvement is found when adapting parameterizations for Phoenix with reduced errors in the SEB components. Finer model resolution (to 333 m) is seen to have insignificant ($<1\sigma$) influence on mean absolute percent difference of 30-minute diurnal mean SEB terms. A new method of representing inhomogeneous urban development density derived from observations of impervious surfaces with sub-grid scale resolution is then proposed for mesoscale applications. This method was implemented and evaluated within the environmental modeling framework. Finally, a new semi-implicit scheme based on Leapfrog and a fourth-order implicit time-filter is developed.
A detailed evaluation of the environmental forecast is conducted by investigating the Surface Energy Balance (SEB) obtained from observations made with an eddy-covariance flux tower compared with SEB from simulations using several physical parameterizations of urban effects and planetary boundary layer schemes. Diurnal variation in SEB constituent fluxes are examined in relation to surface layer stability and modeled diagnostic variables. Improvement is found when adapting parameterizations for Phoenix with reduced errors in the SEB components. Finer model resolution (to 333 m) is seen to have insignificant ($<1\sigma$) influence on mean absolute percent difference of 30-minute diurnal mean SEB terms. A new method of representing inhomogeneous urban development density derived from observations of impervious surfaces with sub-grid scale resolution is then proposed for mesoscale applications. This method was implemented and evaluated within the environmental modeling framework. Finally, a new semi-implicit scheme based on Leapfrog and a fourth-order implicit time-filter is developed.
ContributorsShaffer, Stephen R. (Author) / Moustaoui, Mohamed (Thesis advisor) / Mahalov, Alex (Committee member) / Fernando, Harindra J.S. (Committee member) / Ovenden, Nicholas C. (Committee member) / Huang, Huei-Ping (Committee member) / Calhoun, Ronald (Committee member) / Arizona State University (Publisher)
Created2014
Description
The atmosphere contains a substantial amount of water soluble organic material, yet despite years of efforts, little is known on the structure, composition and properties of this organic matter. Aqueous phase processing by fogs and clouds of the gas and particulate organic material is poorly understood despite the importance for air pollution and climate. On one hand, gas phase species can be processed by fog/cloud droplets to form lower volatility species, which upon droplet evaporation lead to new aerosol mass, while on the other hand larger nonvolatile material can be degraded by in cloud oxidation to smaller molecular weight compounds and eventually CO2.
In this work High Performance Size Exclusion Chromatography coupled with inline organic carbon detection (SEC-DOC), Diffusion-Ordered Nuclear Magnetic Resonance spectroscopy (DOSY-NMR) and Fluorescence Excitation-Emission Matrices (EEM) were used to characterize molecular weight distribution, functionality and optical properties of atmospheric organic matter. Fogs, aerosols and clouds were studied in a variety of environments including Central Valley of California (Fresno, Davis), Pennsylvania (Selinsgrove), British Columbia (Whistler) and three locations in Norway. The molecular weight distributions using SEC-DOC showed smaller molecular sizes for atmospheric organic matter compared to surface waters and a smaller material in fogs and clouds compared to aerosol particles, which is consistent with a substantial fraction of small volatile gases that partition into the aqueous phase. Both, cloud and aerosol samples presented a significant fraction (up to 21% of DOC) of biogenic nanoscale material. The results obtained by SEC-DOC were consistent with DOSY-NMR observations.
Cloud processing of organic matter has also been investigated by combining field observations (sample time series) with laboratory experiments under controlled conditions. Observations revealed no significant effect of aqueous phase chemistry on molecular weight distributions overall although during cloud events, substantial differences were apparent between organic material activated into clouds compared to interstitial material. Optical properties on the other hand showed significant changes including photobleaching and an increased humidification of atmospheric material by photochemical aging. Overall any changes to atmospheric organic matter during cloud processing were small in terms of bulk carbon properties, consistent with recent reports suggesting fogs and clouds are too dilute to substantially impact composition.
In this work High Performance Size Exclusion Chromatography coupled with inline organic carbon detection (SEC-DOC), Diffusion-Ordered Nuclear Magnetic Resonance spectroscopy (DOSY-NMR) and Fluorescence Excitation-Emission Matrices (EEM) were used to characterize molecular weight distribution, functionality and optical properties of atmospheric organic matter. Fogs, aerosols and clouds were studied in a variety of environments including Central Valley of California (Fresno, Davis), Pennsylvania (Selinsgrove), British Columbia (Whistler) and three locations in Norway. The molecular weight distributions using SEC-DOC showed smaller molecular sizes for atmospheric organic matter compared to surface waters and a smaller material in fogs and clouds compared to aerosol particles, which is consistent with a substantial fraction of small volatile gases that partition into the aqueous phase. Both, cloud and aerosol samples presented a significant fraction (up to 21% of DOC) of biogenic nanoscale material. The results obtained by SEC-DOC were consistent with DOSY-NMR observations.
Cloud processing of organic matter has also been investigated by combining field observations (sample time series) with laboratory experiments under controlled conditions. Observations revealed no significant effect of aqueous phase chemistry on molecular weight distributions overall although during cloud events, substantial differences were apparent between organic material activated into clouds compared to interstitial material. Optical properties on the other hand showed significant changes including photobleaching and an increased humidification of atmospheric material by photochemical aging. Overall any changes to atmospheric organic matter during cloud processing were small in terms of bulk carbon properties, consistent with recent reports suggesting fogs and clouds are too dilute to substantially impact composition.
ContributorsWang, Youliang (Author) / Herckes, Pierre (Thesis advisor) / Fraser, Matthew (Committee member) / Anbar, Ariel (Committee member) / Arizona State University (Publisher)
Created2014
Description
Earth-system models describe the interacting components of the climate system and
technological systems that affect society, such as communication infrastructures. Data
assimilation addresses the challenge of state specification by incorporating system
observations into the model estimates. In this research, a particular data
assimilation technique called the Local Ensemble Transform Kalman Filter (LETKF) is
applied to the ionosphere, which is a domain of practical interest due to its effects
on infrastructures that depend on satellite communication and remote sensing. This
dissertation consists of three main studies that propose strategies to improve space-
weather specification during ionospheric extreme events, but are generally applicable
to Earth-system models:
Topic I applies the LETKF to estimate ion density with an idealized model of
the ionosphere, given noisy synthetic observations of varying sparsity. Results show
that the LETKF yields accurate estimates of the ion density field and unobserved
components of neutral winds even when the observation density is spatially sparse
(2% of grid points) and there is large levels (40%) of Gaussian observation noise.
Topic II proposes a targeted observing strategy for data assimilation, which uses
the influence matrix diagnostic to target errors in chosen state variables. This
strategy is applied in observing system experiments, in which synthetic electron density
observations are assimilated with the LETKF into the Thermosphere-Ionosphere-
Electrodynamics Global Circulation Model (TIEGCM) during a geomagnetic storm.
Results show that assimilating targeted electron density observations yields on
average about 60%–80% reduction in electron density error within a 600 km radius of
the observed location, compared to 15% reduction obtained with randomly placed
vertical profiles.
Topic III proposes a methodology to account for systematic model bias arising
ifrom errors in parametrized solar and magnetospheric inputs. This strategy is ap-
plied with the TIEGCM during a geomagnetic storm, and is used to estimate the
spatiotemporal variations of bias in electron density predictions during the
transitionary phases of the geomagnetic storm. Results show that this strategy reduces
error in 1-hour predictions of electron density by about 35% and 30% in polar regions
during the main and relaxation phases of the geomagnetic storm, respectively.
technological systems that affect society, such as communication infrastructures. Data
assimilation addresses the challenge of state specification by incorporating system
observations into the model estimates. In this research, a particular data
assimilation technique called the Local Ensemble Transform Kalman Filter (LETKF) is
applied to the ionosphere, which is a domain of practical interest due to its effects
on infrastructures that depend on satellite communication and remote sensing. This
dissertation consists of three main studies that propose strategies to improve space-
weather specification during ionospheric extreme events, but are generally applicable
to Earth-system models:
Topic I applies the LETKF to estimate ion density with an idealized model of
the ionosphere, given noisy synthetic observations of varying sparsity. Results show
that the LETKF yields accurate estimates of the ion density field and unobserved
components of neutral winds even when the observation density is spatially sparse
(2% of grid points) and there is large levels (40%) of Gaussian observation noise.
Topic II proposes a targeted observing strategy for data assimilation, which uses
the influence matrix diagnostic to target errors in chosen state variables. This
strategy is applied in observing system experiments, in which synthetic electron density
observations are assimilated with the LETKF into the Thermosphere-Ionosphere-
Electrodynamics Global Circulation Model (TIEGCM) during a geomagnetic storm.
Results show that assimilating targeted electron density observations yields on
average about 60%–80% reduction in electron density error within a 600 km radius of
the observed location, compared to 15% reduction obtained with randomly placed
vertical profiles.
Topic III proposes a methodology to account for systematic model bias arising
ifrom errors in parametrized solar and magnetospheric inputs. This strategy is ap-
plied with the TIEGCM during a geomagnetic storm, and is used to estimate the
spatiotemporal variations of bias in electron density predictions during the
transitionary phases of the geomagnetic storm. Results show that this strategy reduces
error in 1-hour predictions of electron density by about 35% and 30% in polar regions
during the main and relaxation phases of the geomagnetic storm, respectively.
ContributorsDurazo, Juan, Ph.D (Author) / Kostelich, Eric J. (Thesis advisor) / Mahalov, Alex (Thesis advisor) / Tang, Wenbo (Committee member) / Moustaoui, Mohamed (Committee member) / Platte, Rodrigo (Committee member) / Arizona State University (Publisher)
Created2018
Description
Atmospheric particulate matter (PM) has a pronounced effect on our climate, and exposure to PM causes negative health outcomes and elevated mortality rates in urban populations. Reactions that occur in fog can form new secondary organic aerosol material from gas-phase species or primary organic aerosols. It is important to understand these reactions, as well as how organic material is scavenged and deposited, so that climate and health effects can be fully assessed. Stable carbon isotopes have been used widely in studying gas- and particle-phase atmospheric chemistry. However, the processing of organic matter by fog has not yet been studied, even though stable isotopes can be used to track all aspects of atmospheric processing, from particle formation, particle scavenging, reactions that form secondary organic aerosol material, and particle deposition. Here, carbon isotope analysis is used for the first time to assess the processing of carbonaceous particles by fog.
This work first compares carbon isotope measurements (δ13C) of particulate matter and fog from locations across the globe to assess how different primary aerosol sources are reflected in the atmosphere. Three field campaigns are then discussed that highlight different aspects of PM formation, composition, and processing. In Tempe, AZ, seasonal and size-dependent differences in the δ13C of total carbon and n-alkanes in PM were studied. δ13C was influenced by seasonal trends, including inversion, transport, population density, and photochemical activity. Variations in δ13C among particle size fractions were caused by sources that generate particles in different size modes.
An analysis of PM from urban and suburban sites in northeastern France shows how both fog and rain can cause measurable changes in the δ13C of PM. The δ13C of PM was consistent over time when no weather events occurred, but particles were isotopically depleted by up to 1.1‰ in the presence of fog due to preferential scavenging of larger isotopically enriched particles. Finally, the δ13C of the dissolved organic carbon in fog collected on the coast of Southern California is discussed. Here, temporal depletion of the δ13C of fog by up to 1.2‰ demonstrates its use in observing the scavenging and deposition of organic PM.
This work first compares carbon isotope measurements (δ13C) of particulate matter and fog from locations across the globe to assess how different primary aerosol sources are reflected in the atmosphere. Three field campaigns are then discussed that highlight different aspects of PM formation, composition, and processing. In Tempe, AZ, seasonal and size-dependent differences in the δ13C of total carbon and n-alkanes in PM were studied. δ13C was influenced by seasonal trends, including inversion, transport, population density, and photochemical activity. Variations in δ13C among particle size fractions were caused by sources that generate particles in different size modes.
An analysis of PM from urban and suburban sites in northeastern France shows how both fog and rain can cause measurable changes in the δ13C of PM. The δ13C of PM was consistent over time when no weather events occurred, but particles were isotopically depleted by up to 1.1‰ in the presence of fog due to preferential scavenging of larger isotopically enriched particles. Finally, the δ13C of the dissolved organic carbon in fog collected on the coast of Southern California is discussed. Here, temporal depletion of the δ13C of fog by up to 1.2‰ demonstrates its use in observing the scavenging and deposition of organic PM.
ContributorsNapolitano, Denise (Author) / Herckes, Pierre (Thesis advisor) / Fraser, Matthew (Committee member) / Shock, Everett (Committee member) / Arizona State University (Publisher)
Created2018