Ground-level ozone (O3) is a familiar pollutant because it is associated with summer haze and smog alerts. The 2000-2008 weekday-weekend variations of ozone concentration were examined in relation to the Toronto weather conditions. The goal of this work is twofold: (1) To determine whether extreme ozone events were associated with specific weather conditions, (2) To determine whether the weekday-weekend effect of extreme ozone events could be detectable during the nine-year study period. The results show that in the study period, there were totally 313 days having extreme ground-level ozone events with ozone concentration ≥ 80 ppb, which is the current Ontario Ambient Air Quality Criterion for ozone concentration, in the four selected Toronto sites. Additionally, the weather condition mainly associated with these 313 days was the Dry Tropical one. This study also shows the phenomenon of the weekday-weekend effect of extreme ozone events in the past nine years in Toronto.

Ground-level ozone (O3) is a familiar pollutant because it is associated with summer haze and smog alerts. The 2000-2008 weekday-weekend variations of ozone concentration were examined in relation to the Toronto weather conditions. The goal of this work is twofold: (1) To determine whether extreme ozone events were associated with specific weather conditions, (2) To determine whether the weekday-weekend effect of extreme ozone events could be detectable during the nine-year study period. The results show that in the study period, there were totally 313 days having extreme ground-level ozone events with ozone concentration ≥ 80 ppb, which is the current Ontario Ambient Air Quality Criterion for ozone concentration, in the four selected Toronto sites. Additionally, the weather condition mainly associated with these 313 days was the Dry Tropical one. This study also shows the phenomenon of the weekday-weekend effect of extreme ozone events in the past nine years in Toronto.

Thesis (Ph.D.); Submitted to the University of California, Berkeley, CA (US); 1 Sep 2003. / Published through the Information Bridge: DOE Scientific and Technical Information. "LBNL--54222" Fine, James. USDOE. Assistant Secretary for Fossil Energy. Office of Natural Gas and Petroleum Technology through the National Petroleum Technology Office (US) 09/01/2003. Report is also available in paper and microfiche from NTIS.

In urban areas, emissions of nitrogen oxide radicals (NOx ≡ NO + NO2) to the atmosphere from anthropogenic activities such as fossil fuel combustion contribute to poor air quality through the production of ozone and particulate matter. Soils are also a significant global source of NOx, but at downind forest environments the deposition of transported reactive nitrogen can be much more important than local emissions. Data from a government monitoring network in the Toronto area from 2000-2007 was used to explore the impact of long-term trends in NO2 and other ozone precursors on local ozone levels. Non-linear chemistry and the influence of meteorology explained why reductions in precursor levels during this period did not lead to significant improvements in ozone. Data from this network was also used to investigate the ability of a satellite-borne spectrometer to represent spatial patterns of ground-level NO2 in the same region. Selection biases, resulting from the need to discard satellite data on cloudy days, were shown to affect locations differently and were most severe at a receptor site. The sum of all reactive nitrogen oxides including NOx is known as NOy. A custom-built instrument for high precision and time resolution measurements of reactive nitrogen oxides was tested under various lab and field conditions, and used in field work where direct biosphere-atmosphere exchange of NOy was measured by eddy covariance above two comparable North American mixed forests (Haliburton Forest Wildlife Reserve and the University of Michigan Biological Station). While these forests were found to be small net sources of NOx, they were subject to elevated rates of NOy deposition overall, driven by the transport of polluted air from upwind source regions. Wet deposition measurements were used to show that dry deposition contributed a significant fraction of total deposition during the observation periods.

In urban areas, emissions of nitrogen oxide radicals (NOx ≡ NO + NO2) to the atmosphere from anthropogenic activities such as fossil fuel combustion contribute to poor air quality through the production of ozone and particulate matter. Soils are also a significant global source of NOx, but at downind forest environments the deposition of transported reactive nitrogen can be much more important than local emissions. Data from a government monitoring network in the Toronto area from 2000-2007 was used to explore the impact of long-term trends in NO2 and other ozone precursors on local ozone levels. Non-linear chemistry and the influence of meteorology explained why reductions in precursor levels during this period did not lead to significant improvements in ozone. Data from this network was also used to investigate the ability of a satellite-borne spectrometer to represent spatial patterns of ground-level NO2 in the same region. Selection biases, resulting from the need to discard satellite data on cloudy days, were shown to affect locations differently and were most severe at a receptor site. The sum of all reactive nitrogen oxides including NOx is known as NOy. A custom-built instrument for high precision and time resolution measurements of reactive nitrogen oxides was tested under various lab and field conditions, and used in field work where direct biosphere-atmosphere exchange of NOy was measured by eddy covariance above two comparable North American mixed forests (Haliburton Forest Wildlife Reserve and the University of Michigan Biological Station). While these forests were found to be small net sources of NOx, they were subject to elevated rates of NOy deposition overall, driven by the transport of polluted air from upwind source regions. Wet deposition measurements were used to show that dry deposition contributed a significant fraction of total deposition during the observation periods.

Ground-level ozone is harmful to the human respiratory system, as well as the environment. The national EPA 8-hour ozone standard for ground-level ozone was reduced from 85 parts per billion (ppb) to 75 ppb in 2008, and trends from previous years show that some of the counties in Central Florida could be in danger of violation. Violation means "non attainment" status; in which the county is ordered by EPA to develop specific implementation plans to reduce its emissions. The objective of this study was to compile an emissions inventory of volatile organic compounds (VOCs) and nitrogen oxides (NOx) from nonroad equipment in Osceola, Seminole, and Orange Counties (OSO) in Central Florida, and to develop possible action steps to reduce those emissions. This is important because VOC and NOx emissions are precursors to ground-level ozone. Thus, compiling emissions inventories is important to identify high VOC and NOx emitters. Mobile and point sources have long been the highest emitters of VOC and NOx and have therefore been targeted and monitored since the Clean Air Act of 1970, but the nonroad sources (such as construction and lawn equipment) have only been regulated since the 1990s. Using the NONROAD and NMIM modeling programs, the highest nonroad emitters of VOC for Central Florida were found to be lawn/garden equipment, and boating equipment, emitting a combined percentage of 77% of the total nonroad mobile source VOC. Construction equipment contributed 67% of the total nonroad mobile source emissions of NOx in Central Florida. The components of these categories were also analyzed to find the largest individual sources of VOC and NOx. Of the individual sources, lawn mowers and outboard boat engines were found to be the largest sources of VOCs. Of the NOx sources, all the construction equipment components had a relatively similar level of NOx emissions. Next, action steps were developed to reduce emissions, focusing on the high emitters, along with an estimated cost and feasibility for each measure. Of these steps, implementing a ban on leafblowers, and reducing use of lawn mowers, edgers, trimmers, etc. seemed to be the most effective for reducing VOCs. Although these are effective measures, the cost and feasibility of both pose challenges. The best action step for reducing NOx emissions in construction equipment seemed to be by simply reducing idling of equipment on job sites. This also poses challenges in feasibility and enforcement by management. Further, constant on/off cycles could result in decreasing the useful life of the older construction equipment. Finally, a survey was conducted with various construction managers and companies to find out the typical equipment and quantity needed for land clearing/grubbing, as well as the typical use, idling time, and total project time for each piece of equipment on a 10-acre site, under various conditions. The purpose of the study was to develop a rough estimate for the average amount of VOC and NOx emissions that will be produced per acre of land clearing activities, and to estimate the emissions reductions and cost savings if idling of the equipment was reduced.

Effective pollution mitigation is the key to successful air quality management. Although states invest millions of dollars to predict future air quality, the regulatory modeling and analysis process to inform pollution control strategy remains uncertain. Traditionally deterministic ‘bright-line’ tests are applied to evaluate the sufficiency of a control strategy to attain an air quality standard. A critical part of regulatory attainment demonstration is the prediction of future pollutant levels using photochemical air quality models. However, because models are uncertain, they yield a false sense of precision that pollutant response to emission controls is perfectly known and may eventually mislead the selection of control policies. These uncertainties in turn affect the health impact assessment of air pollution control strategies. This thesis explores beyond the conventional practice of deterministic attainment demonstration and presents novel approaches to yield probabilistic representations of pollutant response to emission controls by accounting for uncertainties in regional air quality planning. Computationally-efficient methods are developed and validated to characterize uncertainty in the prediction of secondary pollutant (ozone and particulate matter) sensitivities to precursor emissions in the presence of uncertainties in model assumptions and input parameters. We also introduce impact factors that enable identification of model inputs and scenarios that strongly influence pollutant concentrations and sensitivity to precursor emissions. We demonstrate how these probabilistic approaches could be applied to determine the likelihood that any control measure will yield regulatory attainment, or could be extended to evaluate probabilistic health benefits of emission controls, considering uncertainties in both air quality models and epidemiological concentration–response relationships. Finally, ground-level observations for pollutant (ozone) and precursor concentrations (oxides of nitrogen) have been used to adjust probabilistic estimates of pollutant sensitivities based on the performance of simulations in reliably reproducing ambient measurements. Various observational metrics have been explored for better scientific understanding of how sensitivity estimates vary with measurement constraints. Future work could extend these methods to incorporate additional modeling uncertainties and alternate observational metrics, and explore the responsiveness of future air quality to project trends in emissions and climate change.

Viena didžiausių problemų, atsirandančių dėl oro taršos miestų ore, yra tarša, sukelta fotocheminių oksidantų, tarp jų, ir priežemio ozono. Darbo tikslas: nustatyti priežemio ozono koncentracijos sklaidą Kauno mieste ir jos ryšį su meteorologinėmis sąlygomis. Tyrimai buvo vykdomi 2006 - 2009 metais. Darbo objektas - Kauno miestas. Visoje miesto teritorijoje priežemio ozono koncentracija buvo matuota 10 skirtingų matavimo vietų. Ozono koncentracijai nustatyti buvo naudotas „Aeroqual 300 Series” ozono matuoklis. Priežemio ozono koncentracija buvo matuota vidudienį nuo 12 iki 14 ir vakare nuo 17 iki 19 valandos. Kiekvienoje vietoje buvo atlikta nuo 4 - 6 matavimų, kiekvieno sezono metu. Tyrimų metu nustatyta, kad priežemio ozono koncentracijos pasiskirstymas kiekvieno sezono metu yra skirtingas. Didžiausia vidutinė sezoninė priežemio ozono koncentracija buvo nustatyta pavasario - vasaros sezonų metu (72 g/m3), o mažiausia žiemos sezono metu (7 g/m3). 2009 m. pavasario sezono metu Vileikos g., prie GMF nustatyta didžiausia vienkartinė priežemio ozono koncentracija (128 g/m3). Buvo vertintas priežemio ozono koncentracijos ryšys su meteorologinėmis sąlygomis ir azoto oksidų (NOx) koncentracija. Gauti rezultatai parodė, statistiškai reikšmingą teigiamą ryšį tarp ozono koncentracijos ir temperatūros (r = 0,73; p = 0,00) ir NO2 koncentracijos (r = 0,48; p = 0,03). Tai rodo, kad didėjant temperatūrai ir NO2 koncentracijai, didėja ir priežemio ozono koncentracija. Tarp priežemio... [toliau žr. visą tekstą] / One of the major problems resulting from air pollution of the urban area, is the pollution caused by photochemical oxidants, among their, ground level ozone. The aim of this work was to assess distribution of ground level ozone concentration in Kaunas and its relationship to meteorological situation. Measurements was carried out in 2006 - 2009. Object of work has been selected Kaunas city. Throughout the city area ground level ozone concentration was measured by a sampling scheme for the 10 different measurement points. For determinate of ground level ozone concentration, we used ozone quality monitor „Aeroqual 300 Series“. Ground level ozone concentration was measured at midday from 12 to 14 and in the evening from 17 to 19 hours. Each site was carried out from 4 - 6 measurements. Study rezults revealed, that ground level ozone concentration distribution of each season is different. The maximum average ozone concentration was found in spring - summer season (72 g/m3), and the lowest in winter season (7 g/m3). The higher ground level ozone concentration episode (128 g/m3) was stated in spring season in 2009 year. Relationship between ground level ozone concentration and meteorological situations and nitrogen oxides (NOx) concentration was evaluated. The results showed statistically significant positive relationship between ozone concentration and temperature (r = 0,73; p = 0,00) and NO2 concentration (r = 0,48; p = 0,03). Between ground level ozone concentration and wind... [to full text]

La pollution atmosphérique constitue un risque environnemental majeur dont les effets néfastes sur la santé et sur l’environnement sont déjà clairement démontrés. Toutefois, la mesure d’exposition des populations aux polluants tels que les particules fines et l’ozone troposphérique demeure approximative en raison de la faible densité des stations d’échantillonnage de ces polluants. Peu d’études ont considéré la variation spatiale intra-urbaine dans la modélisation spatiale des concentrations de polluants. Certaines études ont cependant combiné interpolation spatiale et corrélation avec des facteurs locaux. De plus, l’effet du régime météorologique (par exemple l’occurrence d’une inversion de température) sur l’amplitude de ces corrélations n’est pas pris en compte. Cette thèse a donc pour objectif d’évaluer de nouvelles manières de caractériser la distribution spatiale et temporelle des particules fines (PM2.5) et de l’ozone troposphérique (O3) à l’échelle intra-urbaine. Plus particulièrement, nous avons développé un modèle de géostatistique multivariable appelée krigeage avec dérive externe (KED, kriging with external drift) basé sur l’intégration de variables auxiliaires dans le processus d’estimation journalière des PM2.5 et de l’O3. Le krigeage constitue une forme d’interpolation spatiale des données de stations de mesures éparses, alors que la dérive externe mise sur des corrélations entre des conditions locales (axes de transport routier, espaces verts, etc.) et la concentration des polluants atmosphériques. Afin de prendre en compte les variations temporelles, notamment celles reliées aux conditions météorologiques, ces modèles ont été développés par groupes basés sur des conditions synoptiques et six classes d’états établies selon la température, le vent, l’humidité relative et les précipitations, d’après des données météorologiques journalières. Les résultats montrent que l’intégration des variables auxiliaires telles que la densité de la végétation et les zones des activités industrielles locales dans le KED expliquent en partie les variations intra-urbaines des PM2.5 de l’île de Montréal, mais que cet apport est variable selon la classe météorologique. Ainsi, lorsque les corrélations sont très faibles, une interpolation spatiale simple, comme la méthode IDW (inverse distance weighting) est plus exacte que l’interpolation multivariable, alors que pour d’autres conditions synoptiques le KED produit les prédictions les plus certaines. Nous avons pour cette raison proposé un modèle d’interpolation hybride (KED-IDW) s’adaptant aux conditions météorologiques. Nous avons également montré, particulièrement dans le cas de l’O3, que le krigeage avec dérive externe améliore les résultats obtenus par krigeage ordinaire (sans variables auxiliaires). Cette thèse a aussi permis d’évaluer l’apport d’un modèle spatio-temporel (BME, bayesian maximum entropy) dans l’estimation de l’effet à court terme de l’exposition à l’O3 sur les décès à Montréal. Les résultats suggèrent que ce modèle spatio-temporel dans les conditions développées (par ex. basé sur les données de 12 stations de mesures, pour un territoire de 1 310 km2) n’apporte pas de gains significatifs dans l’estimation de l’effet de l’exposition. Dans l’ensemble, cette thèse contribue au progrès de modélisation spatiale empirique des polluants atmosphériques en se fondant notamment sur l’adaptation aux conditions météorologiques et par l’ajout de certains facteurs météorologiques comme prédicteurs. Dans ce contexte, cette thèse ouvre une voie prometteuse pour l’amélioration des estimations de polluants atmosphériques à l’échelle intra-urbaine et de la capacité à évaluer les risques à la santé de la population par une meilleure caractérisation de l’exposition. Mots-clés : pollution de l’air, particules fines, ozone troposphérique, santé, géostatistique, krigeage avec dérive externe, environnement urbain. / Air pollution is a major environmental hazard with clearly demonstrable adverse effects on health and the environment. However, the measurement of populations’ exposure to pollutants such as particulate matter and ground-level ozone remains approximate due to the low density of sampling stations for these pollutants. Moreover, intra-urban spatial variation in the spatial modeling of pollutant concentrations has received little research attention. If anything, some studies have combined spatial interpolation and correlation with local factors; however, they do so without examining the effect of the weather regime (e.g., a temperature inversion) on the magnitude of these correlations. In order to overcome these shortcomings, this dissertation aims to evaluate new ways of characterizing the spatial and temporal distribution of fine particles (PM2.5) and ground-level ozone (O3) at the intra-urban scale. In particular, we developed a multivariable geostatistical model called “kriging with external drift” (KED) based on the integration of auxiliary variables into the process of estimating daily PM2.5 and O3 concentrations. Kriging is a form of spatial interpolation of data from measurement stations that are dispersed, while external drift is based on correlations between local conditions (road transport arteries, green spaces, etc.) and the concentration of atmospheric pollutants. In order to take account of temporal variations, especially those related to weather conditions, we designed these models around six synoptic weather classes based on daily meteorological data (such as temperature, wind, relative humidity and precipitation). v The results show that the integration of auxiliary variables (such as vegetation density and local industrial activity areas) in KED partly explains the intra-urban variations of PM2.5 on the island of Montreal, but that this contribution is variable depending on the weather conditions. Thus, when the correlations are very low, a simple spatial interpolation (such as the inverse distance weighting (IDW) method) is more accurate than multivariable interpolation, whereas for other synoptic conditions KED produces the most certain predictions. For this reason, we proposed a hybrid interpolation model (KED-IDW) that can adapt to different weather conditions. We have also shown, particularly in the case of O3, that KED improves the results obtained from ordinary kriging (without auxiliary variables). This dissertation also allowed to evaluate the contribution of a spatial-temporal model—BME (bayesian maximum entropy)—in the estimation of the short-term effect of exposure to O3 on deaths in Montreal. The results suggest that this spatio-temporal model under the determined conditions (e.g., based on data from 12 measurement stations, for a territory of 1 310 km2) does not offer significant improvements to the estimation of the effect of exposure. Overall, this dissertation contributes to the advancement of the empirical spatial modeling of air pollutants, namely by taking into account the adaptation to weather conditions as well as certain predictive meteorological factors. In this context, the dissertation opens up a promising path for improving the estimation of air pollution at the intra-urban scale and the capacity to assess population health risks through better characterization of exposure.