Hazards associated with air pollution motivate the search for technologies capable of monitoring individual exposure to gaseous pollutants and particulate matter (PM). A Low-cost Optical Particle Counter (OPC), costing less than 50 USD, is an example of such technologies. Currently, OPCs are widely used to measure the concentration of particle matter in ambient air. While these low-cost air quality sensors are widely available, the accuracy and precision of these devices is highly uncertain. Consequently, the purpose of this thesis is to present an analytical model of two generic, low-cost OPCs based on the Laws of Conservation of Mass, Momentum, and Energy. These models utilize Mie scattering theory and Computational Fluid Dynamics models to quantify uncertainty and accuracy in low-cost OPCs based first principles. Modeling results indicate that the measurement of forward-scattered light may dramatically increase the accuracy of low-cost OPCs. These results also indicate that careful attention must be placed on the design of sensor flow passages so as to most efficiently transport particles to the scattering volume where they may be detected. A combination of careful attention to photodetector placement in the forward scattering regime as well as efficient transport to the scattering volume may increase low-cost OPC accuracy by magnitudes of order.

Background: Air pollution has become a serious environmental issue. It is responsible for hundreds of fatalities each year and it poses a serious threat to human health and environment. It leads to global warming, greenhouse effect and it also causes respiratory problems like asthma, lung cancer etc. It is important to predict the quality of the air to regulate air pollution. Air quality index (AQI) is a measure of air quality which describes the level of air pollution. Machine learning algorithms can help in predicting the AQI. Linear regression, LASSO regression, ridge regression, and SVR algorithms were used to forecast the AQI.  Objectives: The main objective of the thesis is to build and train a models using machine learning algorithms and find out the most accurate model in predicting the AQI.  Methods: Literature Review and Experimentation were chosen as methods to answer the research questions. There are a number of research papers written on prediction of AQI and literature review helped us a lot in research and references. Experimentation is also used to find out the most accurate machine learning model in predicting the air quality. In the experimentation phase, four machine learning algorithms were trained with air quality data to create predictive models for fore- casting AQI.  Results: Algorithms like Logistic Regression, Ridge Regression, LASSO Regression, and SVR are selected through literature review. Upon experimentation and training the algorithm with "Air Quality Data in India (2015-2020)" data set has showed that Ridge regression has the least MAE and RMSE and the highest R- square, which shows that it has the highest performance in predicting the AQI.  Conclusions: Four models are built by training with machine learning algorithms like Logistic Regression, Ridge Regression, LASSO Regression, and SVR and "Air Quality Data in India (2015-2020)" data set. After experimentation, it was found that Ridge Regression and LASSO regression has the better performance in the prediction of AQI.

Nitrogen oxides, sulfur dioxide, ozone, light scattering and relative humidity were measured in the sphere of influence of the Radford Army Amnmunition Plant using an airborne platform. Data were obtained on twelve days between May and July 1980 and were used to map the upwind-downwind pollutant concentrations around the arsenal. Results of this investigation indicate that an airborne platform can be used successfully in characterizing pollutant parameters in the sphere of influence of an area source. Results also indicate the complexity of NO-NO₂-O₃ cycle when hydrocarbons and sulfur dioxide are present. Benefits of this type of study may prove useful for the technical and administrative decision making processes of regulatory agencies and munitions manufacturing personnel. / M. S.

In recent years, the celebration activities of various types of folk-custom festivals in Taiwan have already been getting more and more attention from civilians. Festivities throughout the whole island are traditionally accompanied by loud and brightly colored firework displays. Among these activities, the firework display during the Chinese Lantern Festival in Kaohsiung City is one of the largest festivals in Taiwan every year. Therefore, it is important to investigate the influences of firework displays on ambient air quality during the Chinese Lantern Festival in Kaohsiung City. Field measurement of ambient gaseous pollutants and particulate matter (PM) was conducted on February 9-12, 2009, the Chinese Lantern Festival, in Kaohsiung City. Moreover, three kinds of firework powders obtained from the same factory producing Kaohsiung Lantern Festival fireworks were burned in a combustion chamber to determine the physicochemical properties of firework aerosols. Metallic elements were analyzed with an inductively coupled plasma-atomic emission spectrometer (ICP-AES). Ionic species and carbonaceous contents in the PM samples were analyzed with an ion chromatography (IC) and an elemental analyzer (EA), respectively. Finally, the source identification and apportionment of PM were analyzed by principal component analysis (PCA), enrichment factor (EF), and receptor modeling (CMB). For inorganic gaseous pollutants, the concentration peaks of NO, NO2, O3, CO were observed during the firework periods, and the concentration peak of NO was approximately 8.8 times higher than those during the non-firework periods. This study further revealed that, even at nighttime, ambient O3 could be reduced dramatically during the firework periods, whenas NO2 concentration increased concurrently, due to titration effects resulting from the prompt reaction of NO with O3 to form NO2 and O2. For organic gaseous pollutants, the concentration peak of toluene during the firework periods was approximately 2.2-4.1 times higher than those during the non-firework periods. Several metallic elements of PM during the firework display periods were obviously higher than those during the non-firework periods. On February 10, the concentrations of Mg, K, Pb, and Sr in PM2.5 were 10 times higher than those during the non-firework periods. Besides, the Cl-/Na+ ratio was slightly smaller than 1 in Kaohsiung Harbor, but it was approximately 3 during the firework display periods since Cl- came form chlorine content in firework aerosols at this time. Moreover, OC/EC ratio increased up to 2.8. In addition to the analysis of gaseous pollutants and PM during the Chinese Lantern Festival in Kaohsiung City, this study burned firework powders in a self-designed combustion chamber to measure the physicochemical properties of firework aerosols. In the results, K, Mg, Cl-, OC were major contents (<10%) in the aerosols produced from the burning firework powders. Moreover, Cl-/Na+ and OC/EC ratio were 15.0~23.4 and 2.9~3.2, respectively. Consequently, Cl-/Na+ and OC/EC ratio can be used as two important indicators of firework displays. Results obtained from PCA and CMB receptor modeling showed that the major sources of aerosols during the firework display periods were firework displays, motor/diesel vehicle exhanst, soil dusts, and marine aerosols. Besides, the firework displays on February 10 contributed approximately 25.2% and 16.6% of PM10 at two sampling sites, respectively.

published_or_final_version / Environmental Management / Master / Master of Science in Environmental Management

According to World Health Organization, around 7 million people die every year due to diseases caused by air pollution. With the improvements in Internet of Things in the recent years, environmental sensing systems has started to gain importance. By using technologies like Cloud Computing, RFID, Wireless Sensor Networks, and open Application Programming Interfaces, it has become easier to collect data for visualization on different platforms. However, collected data need to be represented in an efficient way for better understanding and analysis, which requires design of data visualization tools. The GreenIoT initiative aims to provide open data with its infrastructure for sustainable city development in Uppsala. An environmental web application is presented within this thesis project, which visualizes the gathered environmental data to help municipality organizations to implement new policies for sustainable urban planning, and citizens to gain more knowledge to take sustainable decisions in their daily life. The application has been developed making use of the 4Dialog API, which is developed to provide data from a dedicated cloud storage for visualization purposes. According to the evaluation presented in this thesis, further development is needed to improve the performance to provide faster and more reliable service as well as the accessibility to promote openness and social inclusion. / Enligt World Health Organization dör 7 miljoner människor varje år på grund av sjukdomar orsakade av luftföroreningar. Med förbättringar inom Internet of Things under senare år, har betydelsen av system för miljösensorer. Genom att använda tekniker som molntjänster, RFID, trådlösa sensornätverk och öppna programmeringsgränssnitt, har det blivit enklare att samla in data för visualisering på olika plattformar. Men insamlad data behöver bli representerad på ett effektivt sätt för bättre förståelse och analys, vilket kräver utformande av verktyg för visualisering av data. Initiativet GreenIoT strävar mot att erbjuda öppen data med sin infrastruktur för hållbar stadsutveckling i Uppsala. I detta arbete presenteras en webb-tillämpning, som visualiserar den insamlade miljödatan för att hjälpa kommunen att implementera nya policies för hållbar stadsutveckling, och stimulera medborgare till att skaffa mer kunskap för att göra miljövänliga val i sin vardag. Tillämpningen har utvecklats med hjälp av 4Dialog API, som tillhandahåller data från lagring i molnet för visualiseringssyfte. Enligt den utvärdering som presenteras i denna rapport konstateras att vidare utveckling behövs för att förbättra dels prestanda för att erbjuda en snabbare och mer tillförlitlig service, och dels åtkomstmöjligheter för att främja öppenhet och social inkludering.

A graphical system was developed to represent airborne air quality monitoring data. The representations developed included three—dimensional spatial mapping, percentage and frequency distributions, and altitude—based scatter diagrams. Elementary statistical analyses and correlations of the measured parameters were also performed. Data gathered in eight flights to the Shenandoah National Park during the summer months of 1981 were analyzed. Sulfur dioxide levels were found to be in the 5 - 15 ppb range, nitrogen oxides were in the 4 — 10 ppb range, nitrous oxide was in the 2 - 5 ppb range, nitrogen dioxide was in the 2 - 5 ppb range, ozone was in the 35 - 70 ppb range and visual range was in the 5 — 90 mile range. The data representation system proved to be an easier and more useful method of displaying the data than the previously existing system. / Master of Science

published_or_final_version / Environmental Management / Master / Master of Science in Environmental Management

Among the most ubiquitous and persistent air quality problems facing urban areas are high concentrations of gas phase oxidants and fine particulate matter. Ozone and particulate matter concentrations in urban areas are significantly influenced by other factors in addition to local emissions, such as regional transport spanning distances as large as 1000 kilometers. Despite the importance of regional transport in meeting air quality standards, to date most analyses of regional transport have focused only on short duration episodes, or semi-quantitative assessments. The development and evaluation of seasonal, quantitative assessments of regional pollutant transport, based on modeling calculations and observational data is the topic of this dissertation. The observational data available through the Texas Air Quality Studies in 2000 and 2006 provide a unique opportunity to develop, evaluate, and improve methods for characterizing regional air pollutant transport. Measurements collected during these studies are used as the primary observational basis for characterizing regional ozone transport and to evaluate the performance of photochemical models. Results suggest that measurements (from aircraft and surface monitors) and the photochemical model provide consistent estimates of the magnitude of ozone transport. On this basis, photochemical modeling is used to determine potential impacts of regional ozone transport in Texas, under varying meteorological and photochemical conditions, as well as to characterize the dominant chemical and physical processes within urban plumes. While qualitative studies and limited quantitative analyses have been performed to assess regional ozone transport, this work includes the first detailed quantitative characterization of the importance of ozone transport over the course of an entire ozone season using both photochemical modeling and ambient data. Results demonstrate that urban plumes in Texas are capable of transporting significant amounts of ozone over distances spanning hundreds of kilometers. Furthermore, on a seasonal basis, there are a number of days characterized by high contributions from inter-city transport coinciding with high total ozone concentrations, suggesting that the role of inter-city transport will remain significant for many areas to demonstrate attainment of the NAAQS for ozone. Results also indicate that reductions in the impacts of inter-city transport are possible by decreases in emissions from source regions. / text

L’objectif de cette étude était d’obtenir un capteur à bas coût, fonctionnant à température ambiante, et permettant d’obtenir une information sur la concentration d’ammoniac d’une atmosphère, sans tenir compte de l’humidité. Cela implique une très faible sensibilité à l’humidité et une faible synergie entre l’eau et l’ammoniac.Au terme d’une étude sur la mise en forme de films hybrides hydrophiles, par un procédé « propre » dans l’eau, un capteur a été développé, par un assemblage en couche par couche de polyélectrolytes hydrophiles, la polyaniline et la phtalocyanine tétrasulfonée de cuivre : PANI/TsPcCu. Ce capteur présente une limite de détection d’ammoniac inférieure au ppm et une très faible sensibilité à l’eau, permettant de détecter l’ammoniac sans informations sur l’humidité de l’air.De nouveaux dispositifs, basés sur un mode de transduction breveté, ont été étudiés : les heterojonctions MSDIs (Molecular Semiconductor-Doped Insulator). Ces dispositifs sont formés de deux couches superposées, une sous-couche isolante de type n, F16PcCu ou le PTCDA, et une couche supérieure semi-conductrice de type p, Pc2Lu. L’importance de la jonction entre les deux matériaux, mais aussi de la jonction entre les électrodes et la sous-couche, a été démontrée à l’aide de mesures d’impédances. Les propriétés capteurs des dispositifs MSDI ont été étudiées par exposition à l’ammoniac sur une large gamme d’humidité. Ils présentent une très faible sensibilité à l’eau et permettent de détecter des concentrations d’ammoniac inférieures au ppm. Suite au développement d’un banc de mesures spécifique permettant l’affinage de fromages, celui-ci a pu être suivi par des mesures capteur avec un résistor de PcCo et par GC-MS. Ces mesures ont mis en évidence l’intérêt de tels capteurs pour suivre l’évolution de la maturation des fromages. / The aim of this study was to obtain a low cost sensor, working at room temperature, capable to obtain an information about the ammonia concentration without any information about the humidity. These characteristics imply a very low sensitivity to humidity and a low cross sensitivity between humidity and ammonia.After a study on material processing of hydrophilic films using water as solvent, a sensors has been developed by using layer by layer assembly of polyelectrolytes, such as polyaniline and the tetrasulfonated copper phthalocyanine: PANI/TsCuPc. This sensor is able to detect sub ppm ammonia concentration, with a very low cross sensitivity between ammonia and water which allow ammonia sensing without any information about the humidity.New devices based on a patented transduction method were studied: the MSDIs heterojunctions (Molecular Semiconductor-Doped Insulator). This kind of device is prepared with two different layers, a sub layer of an n-type insulator, F16CuPc or PTCDA, and an upper layer of a p-type semiconductor, LuPc2. The importance of the junction between both materials and between the sub layer and the electrodes were studied by using ammonia exposure on a large humidity range. They exhibit a very low sensitivity to humidity and allow sub ppm ammonia sensing whatever the humidity is.A specific workbench has been developed and tested in the laboratory, to follow cheese ripening by using CoPc gas sensors and gas chromatography. These measurements showed readiness to the use of the kind of gas sensors for the follow up of dairy products.