The regulated control of pollutants is essential to maintaining good air quality in urban areas. A major concern is the formation of tropospheric ozone, which can be especially harmful to those with lung conditions and has been linked to the occurrence of asthma. Ozone is formed through reactions of oxidized volatile organic compounds with nitrogen oxides, and the accurate modeling of the process is necessary for smart and effective regulations. Ambient measurements are important to understanding the mechanisms involved in tropospheric chemistry. This dissertation describes the characterization of a novel instrument for the ambient measurement of dinitrogen pentoxide, N2O5, and the results of several field studies. This is an important intermediate in the major nighttime loss pathway of nitrogen oxides. The understanding of this process requires correct modeling formation, as any nitrogen oxides not removed at night will result in increased ozone formation at sunrise. Calibration studies have been performed in order to quantify the loss of reactive species within the instrument, and the sampling flow and N2O5 detection have been well characterized. The results of the laboratory measurements are presented. Results are presented from the SHARP Field Study in Houston, TX in the spring of 2009. N2O5 measurements are compared to measurements of other species, including nitric acid and nitryl chloride, which were performed by other research groups. Mixing ratios exceeding 300 ppt were observed following ozone exceedance days, and a dependence of the concentration on both wind speed and direction was noticed. There was a strong correlation determined between N2O5 with HNO3 and ClNO2 indicating both a fast heterogeneous hydrolysis and N2O5 as the primary source of the species. Observed atmospheric lifetimes for N2O5 were short, ranging from several seconds to several minutes. We have also investigated the presence of N2O5 in College Station, TX. Low mixing ratios peaking at approximately 20 ppt were observed, with longer atmospheric lifetimes of up to several hours. The role of biogenic emissions in the NO3-N2O5 equilibrium is discussed.

This thesis characterizes the ambient fine organic carbon aerosol and investigates its sources through the development and deployment of new measurement techniques. The focus is on organic compounds that are soluble in water (WSOC), which comprise a large fraction of the organic aerosol, yet little has been known about its chemical nature. A method was developed for quantitative on-line measurements of WSOC by using a Particle-into-Liquid Sampler (PILS) to capture ambient particles into a flow of purified water, which is then forced through a liquid filter and the carbonaceous content quantified by a Total Organic Carbon (TOC) analyzer. This system allows for a continuous 6 minute (ground-based) or 3 s integrated measurement (airborne) with a limit of detection of 0.1 microgramsC/m3 and uncertainty of 10%. Furthermore, a new quantitative method was developed to group speciate the WSOC. In the first step, WSOC is separated by use of XAD-8 resin into its hydrophilic (WSOCxp) and hydrophobic (WSOCxr) fractions. This separation can be performed on-line by coupling the XAD-8 column with the PILS-TOC or off-line on WSOC extracted from integrated filter samples. If off-line, a second step involving size-exclusion chromatography (SEC) is used to chromatographically separate by organic functional groups the WSOCxp and recovered hydrophobic fraction (WSOCxrr). During this step, the WSOCxp is further separated into aliphatic acids with less than four carbons, neutrals, and bases. The WSOCxrr can be separated into acids and neutrals. Results showing the capabilities of the PILS-TOC both on the ground at the St. Louis Midwest Supersite and when airborne during the New England Air Quality Study/Intercontinental Transport and Chemical Transformation 2004 mission conducted in the northeastern U.S. will be presented. Ambient results from urban sites where a PILS-TOC was coupled with a XAD-8 column will be discussed. Data from the two-step speciation performed on samples collected from urban Atlanta summer and winter, and biomass burning in rural Georgia in a region of prescribed burning are presented. Finally, WSOC measurements obtained in Atlanta and its surrounding regions from both the speciation measurements and PILS-TOC will be used to investigate the sources of WSOC in the southeastern U.S.

This thesis presents ambient energy data obtained from a measurement campaign carried out at an automobile plant. At the automobile plant, ambient light, ambient temperature and ambient radio frequency were measured during the day time over two days. The measurement results showed that ambient light generated the highest DC power. For plant and operation managers at the automobile plant, the measurement data can be used in system design considerations for future energy harvesting wireless sensor nodes at the plant. In addition, wideband measurements obtained from a machine workshop are presented in this thesis. The power delay profile of the wireless channel was obtained by using a frequency domain channel sounding technique. The measurements were compared with an equivalent ray tracing model in order to validate the suitability of the commercial propagation software used in this work. Furthermore, a novel technique for mathematically recreating the time dispersion created by factory inventory in a radio frequency channel is discussed. As a wireless receiver design parameter, delay spread characterizes the amplitude and phase response of the radio channel. In wireless sensor devices, this becomes paramount, as it determines the complexity of the receiver. In reality, it is sometimes difficult to obtain full detail floor plans of factories for deterministic modelling or carry out spot measurements during building construction. As a result, radio provision may be suboptimal. The method presented in this thesis is based on 3-D fractal geometry. By employing the fractal overlaying algorithm presented, metallic objects can be placed on a floor plan so as to obtain similar radio frequency channel effects. The environment created using the fractal approach was used to estimate the amount of energy a harvesting device can accumulate in a University machine workshop space.

Atmospheric fine particulate matter (PM2.5), which is mostly formed in the atmosphere from precursor gases, contributes to numerous environmental and health concerns. Quantifying the ambient concentrations of PM2.5 and precursor gases can be challenging. Hence, many scientific questions about the formation, chemical composition, and gas/particle partitioning of PM2.5 remain unanswered. Ambient Ion Monitor - Ion Chromatography (AIM-IC) was characterized and utilized to measure the water-soluble composition of PM2.5 (dominated by pNH4+, pSO42-, and pNO3-) and associated precursor gases (dominated by NH3(g), SO2(g), and HNO3(g)) during two field campaigns. The AIM-IC detection limits for hourly sampling were determined to be 3 - 45 ng m-3. The response time for “sticky” gases was significantly improved with a nylon denuder membrane. A novel inlet configuration for the AIM-IC, which minimizes sampling inlet losses and carryover in sample analyses, was implemented. Measurements from the BAQS-Met 2007 campaign were utilized to assess the accuracy of the AURAMS model and investigate gas/particle partitioning in SW Ontario. Due to high sulphate levels, NH3(g) was the limiting chemical factor in the formation and gas/particle partitioning of PM2.5. The errors in the predictions of relative humidity and free ammonia were responsible for the poor agreement iii between modelled and measured pNO3- values. The AIM-IC measurements from the CalNex 2010 study were compared to the CMAQ model and utilized to investigate the gas/particle partitioning in Bakersfield, CA. Very high NH3(g) concentrations were observed, and the formation and partitioning of PM2.5 was limited by HNO3(g) and H2SO4. Evidence of rapid removal of HNO3(g) by interactions with super-micron dust particles, and possibly with the alkaline surface was found. CMAQ exhibited significant biases in the predicted concentrations of pSO42-, NH3(g) and HNO3(g).

Atmospheric fine particulate matter (PM2.5), which is mostly formed in the atmosphere from precursor gases, contributes to numerous environmental and health concerns. Quantifying the ambient concentrations of PM2.5 and precursor gases can be challenging. Hence, many scientific questions about the formation, chemical composition, and gas/particle partitioning of PM2.5 remain unanswered. Ambient Ion Monitor - Ion Chromatography (AIM-IC) was characterized and utilized to measure the water-soluble composition of PM2.5 (dominated by pNH4+, pSO42-, and pNO3-) and associated precursor gases (dominated by NH3(g), SO2(g), and HNO3(g)) during two field campaigns. The AIM-IC detection limits for hourly sampling were determined to be 3 - 45 ng m-3. The response time for “sticky” gases was significantly improved with a nylon denuder membrane. A novel inlet configuration for the AIM-IC, which minimizes sampling inlet losses and carryover in sample analyses, was implemented. Measurements from the BAQS-Met 2007 campaign were utilized to assess the accuracy of the AURAMS model and investigate gas/particle partitioning in SW Ontario. Due to high sulphate levels, NH3(g) was the limiting chemical factor in the formation and gas/particle partitioning of PM2.5. The errors in the predictions of relative humidity and free ammonia were responsible for the poor agreement iii between modelled and measured pNO3- values. The AIM-IC measurements from the CalNex 2010 study were compared to the CMAQ model and utilized to investigate the gas/particle partitioning in Bakersfield, CA. Very high NH3(g) concentrations were observed, and the formation and partitioning of PM2.5 was limited by HNO3(g) and H2SO4. Evidence of rapid removal of HNO3(g) by interactions with super-micron dust particles, and possibly with the alkaline surface was found. CMAQ exhibited significant biases in the predicted concentrations of pSO42-, NH3(g) and HNO3(g).