Indiana University-Purdue University Indianapolis (IUPUI) / This study looked at the time period of June through mid-October, 2013, based on the results of earlier studies that the strongest correlation between the PM2.5 and AOD data sets occurs during the summer and fall. Terra satellite data was used in this study due to availability of images for the geographic area of the state of Indiana during the time period of the study. PM2.5 measurements from 12 IDEM continuous monitoring sites, which were collected at noon local time, were compared with MODIS AOD data. Despite the limitations of useful data and smaller data sets, this study shows encouraging results, and illustrates that there is a relationship between remotely sensed MODIS AOD data and fine particulate matter (PM2.5) data collected from ground sensors within the geographic region of the state of Indiana. It is believed that this topic should be studied further and expanded upon.

Air quality has long been a major health concern for citizens around the world, and increased levels of exposure to fine particulate matter (PM2:5) has been definitively linked to serious health effects such as cardiovascular disease, respiratory illness, and increased mortality. PM2:5 is one of six attainment criteria pollutants used by the EPA, and is similarly regulated by many other governments worldwide. Unfortunately, the high cost and complexity of most current PM2:5 monitors results in a lack of detailed spatial and temporal resolution, which means that concerned individuals have little insight into their personal exposure levels. This is especially true regarding hyper-local variations and short-term pollution events associated with industrial activity, heavy fossil fuel use, or indoor activity such as cooking. Advances in sensor miniaturization, decreased fabrication costs, and rapidly expanding data connectivity have encouraged the development of small, inexpensive devices capable of estimating PM2:5 concentrations. This new class of sensors opens up new possibilities for personal exposure monitoring. It also creates new challenges related to calibrating and characterizing inexpensively manufactured sensors to provide the level of precision and accuracy needed to yield actionable information without significantly increasing device cost. This thesis addresses the following two primary questions: 1. Can an inexpensive air quality monitor based on mass-manufactured dust sensors be calibrated efficiently in order to achieve inter-device agreement in addition to agreement with professional and federally-endorsed particle monitors? 2. Can an inexpensive air quality monitor increase the confidence and capacity of individuals to understand and control their indoor air quality? In the following thesis, we describe the development of the Speck fine particulate monitor. The Speck processes data from a low-cost dust sensor using a Kalman filter with a piecewise sensing model. We have optimized the parameters for the algorithm through short-term co-location tests with professional HHPC-6 particle counters, and verified typical correlations between the Speck and HHPC-6 units of r2 > 0:90. To account for variations in sensitivity, we have developed a calibration procedure whereby fine particles are aerosolized within an open room or closed calibration chamber. This allows us to produce Specks for commercial distribution as well as the experiments presented herein. Drawing from previous pilot studies, we have distributed low-cost monitors through local library systems and community groups. Pre-deployment and post-deployment surveys characterize user perception of personal exposure and the effect of a low-cost fine particulate monitor on empowerment.

Excessive PM2.5 emissions in China threaten peoples’ health and cause massive economic burdens to society. Under pressure from the public, and the international community, China published PM2.5 standards for the first time in March 2012. Following the introduction of standards, several pilot cities began to build PM2.5 monitoring networks. This paper is designed to explore whether PM2.5 monitoring can be effectively undertaken and implemented in China and whether monitoring results can offer a technical basis to facilitate a significant reduction in actual PM2.5 emissions and protect public health. PM2.5 monitoring is essential in helping the government and public monitor pollution levels and supervise local compliance with PM2.5 standards. Key aspects to facilitate an effective monitoring process are discussed in the analysis. In addition, a case study – Lanzhou’s PM2.5 monitoring network – is provided to analyze and improve current PM2.5 monitoring practices at local levels, as well as suggest credible technical support to local authorities so as to cut PM2.5 emissions levels. Based on detailed analysis, the results suggest that PM2.5 monitoring can be successfully implemented in China by following several key principles – designing a representative PM2.5 monitoring network, applying QA/QC to ensure data quality, interpreting the data scientifically to understand real pollution levels, etc. In addition, this paper recommends three measures critical to realizing PM2.5 reduction goals: (1) emissions source control, (2) public participation to add input to the decision-making process and supervise local compliance with PM2.5 standards, and (3) non-governmental organization/international cooperation to improve local government and environmental agencies’ capacity with regards to environmental protection. Lessons derived from the case study can help improve PM2.5 monitoring performance not just in Lanzhou, but in cities that share similar monitoring issues across China. Scientific monitoring, together with the application of the above three measures, can more effectively curb PM2.5 emissions, improve air quality, and mitigate negative health effects associated with air pollution. / acase@tulane.edu

This research investigates the difference between indoor and outdoor residential fine particulate matter (PM2.5) and explores the feasibility of predicting residential PM2.5 infiltration for use in exposure assessments. Data were compiled from a previous study conducted in Seattle, Washington, USA and a new monitoring campaign was conducted in Victoria, British Columbia, Canada. Infiltration factors were then calculated from the indoor and outdoor monitoring data using a recursive mass balance model. A geographic information system (GIS) was created to collect data that could be used to predict residential PM2.5 infiltration. Spatial property assessment data (SPAD) were collected and formatted for both study areas, which provided detailed information on housing characteristics. Regression models were created based on SPAD and different meteorological and temporal variables. Results indicate that indoor PM2.5 is poorly correlated to outdoor PM2.5 due to indoor sources and significant variations in residential infiltration. A model based on a heating and non-heating season, and information on specific housing characteristics from SPAD was able to predict a large portion of the variation within residential infiltration. Such models hold promise for improving exposure assessment for ambient PM2.5.

Aerosol emissions from diesel combustion and other activities in rail yards can affect the health of urban populations. Fine particulate (PM[subscript 2.5]) concentrations near the Inman and Tilford rail yards in Atlanta, Georgia, are the highest measured in the state. The rail yard complex is surrounded by homes, schools, businesses and other industries. The impact of the aerosol emissions from these rail yards on local concentrations of PM[subscript 2.5] was quantified. Specifically, black carbon and PM[subscript 2.5] fuel-based emission factors from the rail yards were estimated by carbon balance using high time-resolution monitoring, a BC and PM[subscript 2.5] emissions inventory was estimated and dispersion modeling was applied to assess the impact of the rail yard activities on local air quality and the cost and benefits of upgrading locomotive engines with cleaner technologies was assessed. Further, baseline information that will allow a later evaluation of the improvement of local air quality as locomotives operating in the rail yards are upgraded was generated, and a composition profile of the rail yard aerosols was developed using chemical speciation techniques. These results found that activities from locomotives in the Inman and Tilford Rail yards lead to and an average emission factor of 6.0 ± 0.5 g of PM[subscript 2.5] per gallon of fuel and are responsible for increases in annual average concentrations of approximately 1.3 µg/m³ of PM[subscript 2.5] as far as 1 km from the perimeter of the rail yard complex. Approximately 11.7 tons of BC and 26 tons of PM[subscript 2.5] per year were emitted from the rail yards in 2011. The rail yards were found to be important sources of hydrocarbon-like organic aerosols (HOA) and black carbon from fuel (BCf). Upgrading the engines at the rail yards would decrease PM[subscript 2.5] emissions by about 9 t/year, reducing PM[subscript 2.5] concentrations around 0.5±0.1 µg/m³ as far as 1 km from the perimeter of the rail yard complex and producing monetized health benefits of approximately 24 million dollars per year.

Tropospheric fine particulate matter (PM) poses serious health risks and has a significant impact on global climate change. The measurement of various aspects of PM is challenging due to its complex chemical nature. This dissertation addresses various aspects of PM, including composition, measurement, and visibility. The U.S. Environmental Protection Agency (EPA) proposed a new secondary standard based on visibility in urban areas using 24-h averaged measurements of either light scatter or PM concentration. However shorter averaging times may better represent human perception of visibility. Data from two studies conducted in Lindon, UT, 2012, and Rubidoux, CA, 2003, were used to compare different techniques to estimate visibility, particularly the effect of relative humidity on visibility estimations. Particle composition was measured in Salt Lake City during January-February of 2009. One-hour averaged concentrations of several gas phase and particle phase inorganic species were measured. The results indicate ammonium nitrate averages 40% of the total PM2.5 mass in the absence of inversions and up to 69% during strong inversions. Also, the formation of ammonium nitrate is nitric acid limited, while the formation of ozone appears to be oxidant and volatile organic carbon (VOC) limited. Reduction of NOx will reduce ammonium nitrate secondary particle formation, however, a decrease in NOx may increase ozone concentration.Due to the complexity of PM it is poorly characterized. A large fraction of PM is composed of organic compounds, but these compounds are not regularly monitored due to limitations in current sampling techniques. The GC-MS Organic Aerosol Monitor (OAM) combines a collection device with thermal desorption, gas chromatography and mass spectrometry to quantitatively measure the carbonaceous components of PM on an hourly averaged basis. A compact GC and simple pre-concentrator were developed for the system to decouple separation from manual injection and enhance separation of environmentally-relevant polar organic compounds, such as levoglucosan. The GC-MS OAM is fully automated and has been successfully deployed in the field. It uses a chemically deactivated filter for collection followed by thermal desorption and GC-MS analysis. Laboratory tests show that detection limits range from 0.2 to 3 ng for many atmospherically relevant compounds. The GC-MS OAM was deployed in the field for semi-continuous measurement of the organic markers, levoglucosan, dehydroabietic acid, and several polycyclic aromatic hydrocarbons (PAHs) during winter (January to March), 2015 and 2016. Results illustrate the significance of this monitoring technique to more fully characterize the organic components of PM and identify sources of pollution.

Chronic respiratory diseases such as asthma and chronic bronchitis have significantly increased in prevalence in Africa over the past 10 years. Recent studies have demonstrated that exposure to air pollution may be associated with an increased risk of chronic respiratory diseases. However, such studies have predominantly been conducted in western societies or often used urbanicity as a proxy for exposure to air pollution. Therefore, we evaluated the association between PM2.5 exposure and asthma/chronic bronchitis in Senegal. A cross-sectional study was conducted for the time period of 3 October 2010 to 28 April 2011 using annual concentrations of PM2.5 measured via multiple satellite instruments, and asthma/chronic bronchitis, which was self-reported at baseline via a health survey questionnaire. We used mixed model logistic regression to evaluate the relationship between PM2.5 exposure and asthma/chronic bronchitis risk while adjusting for lifestyle factors, location, and other air pollutants. Sex was evaluated as an effect modifier. The adjusted association between PM2.5 and asthma/chronic bronchitis was 1.03 (95%CI: 0.99 – 1.06). In males the adjusted odds ratio was 1.09 (95%CI: 1.03-1.15), compared to females (aOR 1.01 (95%CI: 0.97 – 1.05). Our results suggest that increasing levels of exposure to PM2.5 puts individuals at a higher risk for chronic respiratory diseases, especially men. These findings have significant policy implications and should be built upon in future research.

This dissertation consists of three separate research projects. Each paper uses a different applied econometric technique to investigate problems related to air quality economics. The first chapter is a general introduction to all three studies. The second chapter explores adopting an environmentally-friendly public transportation system in Europe. The Bayesian econometric methods show that willingness to pay for a new public transportation system is primarily driven by improvements to public goods, such as air quality and greenhouse gas emission reduction. The third chapter uses the red tide-related stated experience and satellite imagery of chlorophyll-a concentration as well as field data of respiratory irritation. This chapter illustrates that ancillary scientific information can be efficiently combined with choice experimental data. The fourth chapter uses panel fixed-effect models to investigate the short-term effect of air pollution on students' cognitive performance in China. It is shown that PM2.5 has a significantly negative impact on students' exam performance. / Doctor of Philosophy / This dissertation consists of three separate research projects. The first chapter is a general introduction to all three chapters. The second chapter assesses residents' support for environmentally-friendly public transportation (EFPT) upgrades across Europe. We develop a novel Bayesian logit model to investigate residents' willingness to pay for local EFPT upgrades. We find evidence that WTP is primarily driven by expected improvements to public goods, such as air quality and greenhouse gas abatement, as opposed to private ridership benefits. WTP distributions are strongly positive in all nations suggesting implicit public support for EFPT in Europe. The third chapter presents a unique opportunity to validate stated experiences by Florida Gulf coast residents with red tide-related air toxins with satellite imagery of chlorophyll-a concentration, as well as field data on respiratory irritation at local beaches. We find that respondents are more likely to choose our proposed new harmful algal blooms forecast system when the chlorophyll-a concentration or respiratory irritation is higher at nearby coastal locations. Moreover, we illustrate that this ancillary scientific information can be efficiently combined with choice experimental data and consider this research a first step in a broader effort to directly link scientific data on environmental conditions with nonmarket economic outcomes. The fourth chapter investigates short-term exposure of air pollution on students' cognitive performance in a high-stakes exam: China's College English Test (CET). We use student fixed effects in the panel-data model to estimate the effect of air pollution on students' test scores. Our findings indicate a statistically significant negative effect of PM2.5 on exam performance and also show PM2.5 is equally harmful to listening and reading section, and maybe even more for writing section. We also find that short-term exposure causes negative cognitive effects, suggesting that temporary preventative measures could be effective in avoiding the negative effects of PM2.5.

Este trabalho teve como objetivo a identificação e quantificação das fontes do Material Particulado fino (MP2,5) da Região Metropolitana de Porto Alegre (RMPA), em especial, as fontes veiculares. Foram utilizadas amostras coletadas diariamente durante 24 horas, entre junho/2007 a fevereiro/2009 na Universidade Federal de Ciências da Saúde de Porto Alegre, próxima a vias de intenso tráfego. As amostras foram analisadas para determinação da concentração em massa, composição elementar e iônica do MP2,5. A concentração média do particulado fino durante o experimento foi de 13,4 µg m-3 e do Black Carbon foi de 3,8 µg m-3. Os elementos-traço S, K e Fe destacaram-se com concentrações mais elevadas. Através de Modelagem Receptora (Análise de Fatores AF e Fatoração de Matriz Positiva, Positive Matrix Factorization PMF), identificaram-se as possíveis fontes de MP2,5 da região. A utilização do PMF, modelo multivariado mais avançado, embora não tenha mostrado uma clara separação das fontes, possibilitou uma quantificação mais acurada das fontes identificadas. Por essa metodologia foram identificadas como fontes do MP2,5 as emissões veiculares, a ressuspensão do solo e as indústrias. Para ambos os modelos, a principal fonte identificada está relacionada com as emissões veiculares, respondendo por aproximadamente 50 % da massa do particulado fino. Dos resultados obtidos com o PMF, o solo tem uma pequena participação (2,5 %). A dificuldade na identificação das fontes pode ser atribuída a falta de medida de traçadores específicos dos combustíveis utilizados no setor de transporte e as limitações analíticas do sistema de Fluorescência de Raio-X, que possui baixos limites de detecção para importantes traçadores de fontes móveis e industriais como V, Ni, Cr, Se e Cu. / The aim of this work was to identify and quantify the sources of fine particles in the Metropolitan Region of Porto Alegre, specially the vehicular sources. PM2.5 samples collected daily for 24 hours between june/2007 to february/2009 at the Universidade Federal de Ciências da Saúde de Porto Alegre, near heavy traffic routes. The samples were analyzed for determination of mass concentration, elemental and ionic composition. The average concentration of fine particulate matter during the experiment was 13.4 µg m-3 and Black Carbon was 3.8 µg m-3. The trace elements S, K and Fe stood out with higher concentrations. Through Receptor Modeling (Factor Analysis AF and Positive Matrix Factorization PMF), identified the possible sources of PM2,5 in the region. Using the most advanced multivariate model PMF, although it has not shown a clear separation of sources, enabled a more accurate quantification of the identified sources. For this methodology have been identified as sources of PM2,5 vehicle emissions, ressuspension of soil and industries. For both models, the main source identified is related to vehicle emissions approximately 50 % of the mass of fine particulate was explained by vehicular emission (light- and heavy-duty fleet). In the results obtained with PMF, participation of the dust soil was small (2.5 %). The difficulty in identifying the sources can be attributed to lack of measurement of specific tracers of fuels used in the transport sector and the limitations of the analytical system by X-Ray Fluorescence, which has low detection limits for important tracers of industrial and mobile sources as V, Ni, Cr, Se and Cu.

Durante a montagem de uma resposta inflamatória, um estímulo reconhecido como um fator de perigo desencadeia a supressão de melatonina noturna pela pineal e a indução da produção em monócitos. A poluição atmosférica é um dos maiores fatores de risco à saúde da população urbana. Neste estudo in vivo, a exposição aguda aos poluentes do ar gera um estresse oxidativo pulmonar, deflagra uma resposta inflamatória a partir da ativação da via de sinalização do NF-κB, do aumento das moléculas de adesão PECAM e ICAM e da sintase de óxido nítrico induzida (iNOS), bem como de citocinas inflamatórias. A medida que o tempo de exposição à poluição progride, a concentração plasmática noturna da melatonina se reduz em 39 %, enquanto que a pulmonar aumenta 55%. Tanto as enzimas AA-NAT e ASMT envolvidas na biossíntese da melatonina, quanto as enzimas antioxidantes SOD, CAT e GPx tem suas expressões gênicas no pulmão duplicadas, bem como suas atividades aumentadas. Os mRNAs das enzimas antioxidantes SOD e CAT pulmonar foram reduzidos a partir do bloqueio dos receptores MT1 e MT2. Tais resultados fundamentam ações farmacológicas que protejam ou revertam os efeitos lesivos gerados pela poluição atmosférica através do eixo imune-pineal tendo a melatonina como um agente terapêutico. / During assembly of an inflammatory response a stimulation recognized as a risk factor triggers the suppression of nocturnal pineal melatonin and by inducing the production in immunocompetent cells. Air pollution is one of the major risk factors to health of the urban population. In this in vivo study, acute exposure to air pollutants generates a pulmonary oxidative stress triggers an inflammatory response from the signaling pathway of activation of NF-κB, the increase in adhesion molecules PECAM and ICAM and nitric oxide synthase induced (iNOS) as well as inflammatory cytokines. As time progresses exposure to pollution, nocturnal plasma melatonin concentration is reduced by 39%, while the lung increases by 55%. Both AA-NAT enzymes and ASMT involved in the biosynthesis of melatonin, as the antioxidant enzymes SOD, CAT and GPx has its gene expression in lung duplicate, as well as its increased activities. The mRNAs of antioxidant enzymes SOD and CAT lung were reduced from blocking the MT1 and MT2 receptors. These results support pharmacological actions to protect or reverse the harmful effects caused by air pollution through the immune-pineal axis taking melatonin as a therapeutic agent.