abstract: The world has been continuously urbanized and is currently accommodating more than half of the human population. Despite that cities cover only less than 3% of the Earth’s land surface area, they emerged as hotspots of anthropogenic activities. The drastic land use changes, complex three-dimensional urban terrain, and anthropogenic heat emissions alter the transport of mass, heat, and momentum, especially within the urban canopy layer. As a result, cities are confronting numerous environmental challenges such as exacerbated heat stress, frequent air pollution episodes, degraded water quality, increased energy consumption and water use, etc. Green infrastructure, in particular, the use of trees, has been proved as an effective means to improve urban environmental quality in existing research. However, quantitative evaluations of the efficacy of urban trees in regulating air quality and thermal environment are impeded by the limited temporal and spatial scales in field measurements and the deficiency in numerical models. This dissertation aims to advance the simulation of realistic functions of urban trees in both microscale and mesoscale numerical models, and to systematically evaluate the cooling capacity of urban trees under thermal extremes. A coupled large-eddy simulation–Lagrangian stochastic modeling framework is developed for the complex urban environment and is used to evaluate the impact of urban trees on traffic-emitted pollutants. Results show that the model is robust for capturing the dispersion of urban air pollutants and how strategically implemented urban trees can reduce vehicle-emitted pollution. To evaluate the impact of urban trees on the thermal environment, the radiative shading effect of trees are incorporated into the integrated Weather Research and Forecasting model. The mesoscale model is used to simulate shade trees over the contiguous United States, suggesting how the efficacy of urban trees depends on geographical and climatic conditions. The cooling capacity of urban trees and its response to thermal extremes are then quantified for major metropolitans in the United States based on remotely sensed data. It is found the nonlinear temperature dependence of the cooling capacity remarkably resembles the thermodynamic liquid-water–vapor equilibrium. The findings in this dissertation are informative to evaluating and implementing urban trees, and green infrastructure in large, as an important urban planning strategy to cope with emergent global environmental changes. / Dissertation/Thesis / Doctoral Dissertation Civil, Environmental and Sustainable Engineering 2019

<p>As Urban Air Mobility (UAM) is developed and brought into fruition via electric vertical takeoff and landing (eVTOL) vehicles, contingencies associated with this new distributed electric propulsion technology in metropolitan areas must be considered. On the state of knowledge on contingencies for eVTOL vehicles, these can be Epistemological Risks or Ontological Risks. Epistemological Risks include known-knowns (probabilistic risks) and known-unknowns (gaps in knowledge). Ontological Risks include, unknown-knowns (hidden knowledge), unknown-unknowns (fog of ignorance). As UAM operations at large scale do not have as much historical accidents data as General Aviation or Commercial Aviation, it is challenging to estimate its accident failure rate per 100,000 flight hours. While battery thermal runaway, battery energy uncertainty, software issues, and common mode power failures are some failure cases listed in this thesis, it is the undiscovered contingency (i.e., unknown-unknown) or unprepared contingency (i.e., unknown-known), along with other external factors, that can lead to an accident. UAM is expected to operate at 1500 feet AGL and at high frequencies over dense metropolitan areas. In an in-flight emergency at these altitudes, any startle response experienced by on-board or remote pilots can lead to longer response times. This study aims to create a framework for contingency planning and risk mitigation using a Reachable Ground Footprint model for eVTOL aircraft under 100% power failure scenarios in-flight. This framework utilizes all existing, public aerodrome infrastructures in metropolitan areas as potential contingency landing sites. Metrics such as Contingency Landing Assurance Percentage and Cruise Altitude Floor requirement are introduced to quantitatively measuring the safety of any UAM trip and provide recommendations on safe cruising altitudes. A demonstration case in the Chicago Metropolitan Area between DuPage Regional Airport and John H. Stroger Hospital Helipad is shown and discussed. Furthermore, aggregate analysis of 434 UAM trips in Chicago Metropolitan Area between Regional Airports, between Regional and Heliports, and between Heliports is performed, along with sensitivity studies involving wind and turn control restrictions. The results discuss variations in Cruise Altitude Floor, Flight Time, and Energy Consumption of these trips using an eVTOL vehicle.</p>

Rising concerns related to the effects of traffic congestion have led to the search for alternative transportation solutions. Advances in battery technology have resulted in an increase of electric vehicles (EVs), which serve to reduce the impact of many of the negative consequences of congestion, including pollution and the cost of wasted fuel. Furthermore, the energy-efficiency and quiet operation of electric motors have made feasible concepts such as Urban Air Mobility (UAM), in which electric aircraft transport passengers in dense urban areas prone to severe traffic slowdowns. Electrified transportation may be the solution needed to combat urban gridlock, but many logistical questions related to the design and operation of the resultant transportation networks remain to be answered. This research begins by examining the near-term effects of EV charging networks. Stationary plug-in methods have been the traditional approach to recharge electric ground vehicles; however, dynamic charging technologies that can charge vehicles while they are in motion have recently been introduced that have the potential to eliminate the inconvenience of long charging wait times and the high cost of large batteries. Using an agent-based model verified with traffic data, different network designs incorporating these dynamic chargers are evaluated based on the predicted benefit to EV drivers. A genetic optimization is designed to optimally locate the chargers. Heavily-used highways are found to be much more effective than arterial roads as locations for these chargers, even when installation cost is taken into consideration. This work also explores the potential long-term effects of electrified transportation on urban congestion by examining the implementation of a UAM system. Interdependencies between potential electric air vehicle ranges and speeds are explored in conjunction with desired network structure and size in three different regions of the United States. A method is developed to take all these considerations into account, thus allowing for the creation of a network optimized for UAM operations when vehicle or topological constraints are present. Because the optimization problem is NP-hard, five heuristic algorithms are developed to find potential solutions with acceptable computation times, and are found to be within 10% of the optimal value for the test cases explored. The results from this exploration are used in a second agent-based transportation model that analyzes operational parameters associated with UAM networks, such as service strategy and dispatch frequency, in addition to the considerations associated with network design. General trends between the effectiveness of UAM networks and the various factors explored are identified and presented.

No description available.

Outdoor air pollution is a major contributor to adverse health effects of citizens, in particular those living in urban environments. Air quality monitoring networks are set up to measure air quality in different environments in compliance with national and European legislation. Generally, only a few fixed monitoring sites are located within a city and thus cannot represent air pollutant concentrations in urban areas accurately enough to allow for a detailed human exposure assessment. Other approaches to derive detailed urban air pollutant concentration estimates exist, such as dispersion models and land-use regression (LUR) models. Low-cost portable air quality monitors are also emerging, which have the potential to add value to existing monitoring networks by providing measurements at greater spatial resolution and also to provide individual-level exposure assessment. The aim of this thesis is to demonstrate how measurements and modelling in combination allow detailed investigations of the variability of air pollutants in space and time in urban area, and in turn improve on the current exposure assessment methods. Three types of low-cost portable monitors measuring NO2, O3 (Aeroqual monitors) and PM2.5 (microPEM monitor) were evaluated against their respective reference instruments. The Aeroqual O3 monitor showed very good correlation (r2 > 0.9) with the respective reference instruments, but biases in the slope and intercept coefficients indicated that calibration of Aeroqual O3 monitor was needed. The Aeroqual NO2 monitor was subject to cross-sensitivity from O3, which, as demonstrated, can be effectively corrected by making O3 and NO2 measurements in tandem. Correlation between the microPEM monitor and its reference instrument was poor (r2 < 0.1) when PM2.5 concentrations were low (< 10 μg m-3), but significantly improved (r2 > 0.69) during periods with elevated PM2.5 concentrations. Relative humidity was not found to affect the raw results of PM2.5 measurements in a consistent manner. All three types of monitors cannot be used as equivalent or indicative methods instead of reference methods in studies that require quantification of absolute pollutant concentrations. However, the generally good correlations with reference instruments reassure their application in studies of relative trends of air pollution. Concentrations of PM2.5, ultrafine particles (UFP) and black carbon (BC) were quantified using portable monitors through a combination of mobile and static measurements in the city of Edinburgh, UK. The spatial variability of UFP and BC was large, of similar magnitude and about 3 times higher than the spatial variability of PM2.5. Elevated concentrations of UFP and BC were observed along streets with high traffic volumes whereas PM2.5 showed less variation between streets and a footpath without road traffic. Both BC and UFP significantly correlated with traffic counts, while no significant correlation between PM2.5 and traffic counts was observed. The relationships between UFP, NO2 and inorganic components of PM2.5 were further investigated through long-term measurements at roadside, urban background and rural sites. UFP moderately correlated with NOx (NO2 + NO) and showed varying relationships with NOx depending on the particle size distribution. Principal component analysis and air-mass back trajectory analysis revealed that PM2.5 concentrations were dominated by long-range transport of secondary inorganic aerosols, whereas UFP were mainly related to varying local emissions and meteorological conditions. These findings imply the need for different policies for managing human exposure to these different particle components: control of much BC and UFP appears to be manageable at local scale by restricting traffic emissions; however, abatement of PM2.5 requires a more strategic approach, in cooperation with other regions and countries on emissions control to curb long-range transport of PM2.5 precursors. A dispersion model (ADMS-Urban) was used to simulate high resolution NO2 and O3 concentrations in Edinburgh. The effects of different emission and meteorological input datasets on the resulting modelled NO2 concentrations were investigated. The modelled NO2 and O3 concentrations using the optimal model setup were validated against reference instrument and diffusion tube measurements. Temporal variability of NO2 was predicted well at locations that were not heavily influenced by local effects, such as road junctions and bus stops. Temporal variability of O3 was predicted better than for NO2. Long-term spatial variability of NO2 was found to correlate well with diffusion tube measurements, while modelled spatial variability of O3 in ADMS-Urban compared poorly with diffusion tube measurements. However, it was found that the O3 diffusion tube measurements may be subject to some unidentified biases affecting their accuracy. Land-use regression (LUR) models are widely used to estimate exposure to air pollution in urban areas. An appropriately sized and designed monitoring network is an important component for the development of a robust LUR model. Concentrations of NO2 were simulated by ADMS-Urban at ‘virtual’ monitoring sites in 54 different network designs of varying numbers and types of site, using a 25 km2 area including much of the Edinburgh city area. Separate LUR models were developed for each network. These LUR models were then used to estimate ambient NO2 concentrations at all residential addresses, which were evaluated against the ADMS-Urban modelled concentration at these addresses. The improvement in predictive capability of the LUR models was insignificant above ~30 monitoring sites, although more sites tended to yield more precise LUR models. Monitoring networks containing sites located within highly populated areas better estimated NO2 concentrations across all residential locations. LUR models constructed from networks containing more roadside sites better characterised the high end of residential NO2 concentrations but had increased errors when considering the whole range of concentrations. No particular composition of monitoring network resulted in good estimation simultaneously across all residential NO2 concentration and of the highest NO2 levels implying a lack of spatial contrast in LUR-modelled pollution surface compared with the dispersion model. Finally, the results from the measurement and modelling studies presented in thesis are synthesised in the context of current exposure assessment studies. Low-cost air-quality monitors currently do not possess and are unlikely in the near future to provide the robustness and accuracy to replace the existing routine monitoring network. Development of the low-cost air-quality should be aiming at upgrading them as the indicative method as defined in the data quality objective in the EU directive. The monitoring sites used to build LUR models should capture well the population distribution in the study area as opposed to capturing the greatest pollution contrast. The traditional methods of evaluating LUR models are also ineffective in characterising the models’ capability at estimating pollutant concentration at residential address. Given that the dispersion models are also subject to the availability and uncertainties in the input data, future air quality model development should endeavour to incorporate both dispersion and land-use regression models, where the uncertainty in the input data can be reduced by using LUR models built on actual measurements, and the limitation in the statistical modelling can be replaced by adopting the deterministic approach used in the dispersion model.

Abstract Combustion generated ultrafine particles have been found to be responsible for adverse effects on human health. New emission reduction technologies and fuels will change the composition of particle emissions. It is important to confirm that the new reduction technologies are designed to minimise the adverse health effects. In this doctoral thesis the potential health effects caused by traffic and industrially generated particles were studied using epidemiological, experimental and in silico studies. The effects of short-term changes in PM2.5 on the respiratory health of symptomatic children living near a steel works were studied to investigate whether specific sources of PM2.5 have the possible health effects. The PM2.5 emission sources were identified: long-range transport, a steel works, soil and street dust and a mechanical engineering works. Significant associations were not found between respiratory symptoms and PM2.5 or the sources markers. The deposition of traffic-related particles into the human respiratory system was computed using the lung deposition model. Particle size distribution was measured from diesel- and compressed natural gas (CNG)-fuelled busses and an off-road diesel engine under different combustion situations. The majority of the measured traffic-related particle numbers reach the alveolar region of the lungs. There were differences in the deposition of particles when different catalysts, engines or fuels were used. CNG or a diesel particulate filter (DPF) significantly reduced lung exposure to particles. Also physical activity, age and gender affected the deposition of particles. The diesel particles comprised compounds (carcinogenic PAHs, transition metals), which may have the ability to generate reactive oxygen. This study provides new knowledge how of the emission abatement technologies and fuels affects particle number and their composition, as well health hazards. Cleaner technology (CNG, DPF), emits significantly fewer particles in numbers, especially large particles, but they emit high amounts of small-size particles, which penetrate most easily to the deepest parts of the lungs. In addition, particles from engines with DPF include the largest variety of transition metals and other hazardous compounds compared to combustion systems having different emission after-treatment units. / Tiivistelmä Palamisprosesseista peräisin olevien ultrapienten hiukkasten on todettu olevan haitallisia ihmisen terveydelle. Uudet pako- ja savukaasujen puhdistusteknologiat ja polttoaineet vaikuttavat hiukkaspäästöihin ja niiden koostumukseen. Uusien menetelmien käytön tulee vähentää hiukkasten mahdollisia terveyshaittoja. Tässä väitöskirjassa tutkittiin liikenteestä ja teollisuudesta peräisin olevien hiukkasten mahdollisia terveyshaittoja käyttäen epidemiologista, kokeellista ja in silico- menetelmiä. Työssä tutkittiin PM2.5-hiukkasten lyhytaikaisvaihtelun yhteyttä terästehtaan läheisyydessä asuvien hengitystieoireisten lasten terveyteen ja päästölähteiden yhteyttä mahdollisiin terveysvaikutuksiin. Merkittäviä PM2.5-päästölähteitä olivat kaukokulkeuma, terästehdas, maaperä ja tiepöly sekä konepaja. Tutkimuksessa ei havaittu lasten hengitystieoireiden ja PM2.5:n tai päästölähteiden merkkiaineiden välillä merkittävää yhteyttä. Liikenneperäisten hiukkasten kulkeutumista ihmisen hengitysteihin tutkittiin keuhkodepositiomallilla. Diesel- ja maakaasukäyttöisten (CNG) bussien ja dieselkäyttöisen työkoneen hiukkaskokojakaumat mitattiin eri palamisolosuhteissa. Suurin osa mitatuista hiukkaslukumääristä kulkeutui keuhkojen alveolaaritasolle. Erilaisten katalysaattorien, moottoreiden tai polttoaineiden käytön seurauksena hiukkasten lukumääräpitoisuudet vaihtelivat ja siten hiukkasten kulkeutumisessa hengitysteihin oli eroja. CNG:n tai hiukkassuodattimen (DPF) käyttö vähensi merkittävästi hiukkaslukumääriä ja keuhkojen altistumista hiukkasille. Myös liikunta, ikä ja sukupuoli vaikuttivat hengitysteihin kulkeutuvien hiukkasten määriin. Dieselhiukkaset sisälsivät yhdisteitä (karsinogeeniset PAH:t, siirtymämetallit), jotka tuottavat hengitysteissä reaktiivisia happiradikaaleja. Tämä tutkimus antaa uutta tietoa päästövähennysmenetelmien ja polttoaineiden vaikutuksista hiukkasten lukumäärään ja koostumukseen sekä hiukkasten terveyshaitoihin. Puhtaamman teknologian käyttö (CNG, DPF) vähentää huomattavasti pakokaasun hiukkasten lukumäärää, etenkin suurten hiukkasten, mutta tuottaa silti suuria määriä pieniä hiukkasia, jotka kulkeutuvat helpommin keuhkojen syvimpiin osiin. Lisäksi moottoreiden hiukkaspäästöt käytettäessä hiukkassuodatinta, sisälsivät enemmän erilaisia siirtymämetalleja ja muita haitallisia aineita verrattuna polttoon, jossa käytettiin muita päästöjen jälkikäsittelymenetelmiä.

Chaque jour, 15% des Européens sont exposés à des niveaux moyens de bruit ou de polluants atmosphériquesdépassant les valeurs seuils fixées par la législation européenne. L’intensité de la pollution de chaque polluant et sarépartition à l’échelle d’une agglomération dépendent des capacités d’émission des sources, des phénomènes dedispersion, et de l’environnement urbain. Il en résulte une variabilité spatiale du niveau de multi-exposition qui resteencore largement méconnue. L’objectif de ce travail de thèse est d’identifier et de caractériser les situations de multiexpositionsur la ville de Besançon. Les niveaux sonores et les concentrations de plusieurs polluants atmosphériques denatures différentes (NO2, benzène, PM10 et PM2.5) ont été finement modélisés (2m x 2m). La compatibilité des modèlesa été maximisée par l’introduction d’inputs identiques dans les méthodologies de calcul Mithra-SIG pour le bruit, etCOPERT4/ADMS-urban pour les polluants. Dans un premier temps, l’impact de la définition du voisinage sur lesniveaux d’exposition a été exploré pour les deux pollutions. Douze indicateurs, présentant chacun une définitiondifférente de la zone d’exposition au voisinage du domicile, ont permis de quantifier les niveaux d'exposition autour des10865 bâtiments d’habitations bisontins. Les résultats obtenus mettent en évidence un impact significatif de ladéfinition de la zone d’exposition sur les niveaux. Les différentes définitions du voisinage conduisent à l'existence d'unbiais différentiel, dû à la prise en compte particulière des variables environnementales dans chacun des indicateurs. Cebiais se retrouve pour l'ensemble des polluants étudiés, bien que dans des proportions variables en fonction du polluant.Dans un second temps, l’étude des situations de multi-exposition bruit/NO2 a pu être réalisée. Les résultats obtenusindiquent l'existence d'une relation complexe et permettent de décrire les différentes situations de multi-expositionprésentes dans la ville. Ce travail de thèse constitue une des premières approches de ce type en France et permet demieux comprendre les relations existantes entre définition du voisinage, zones d'exposition, paramètresenvironnementaux et niveaux d'exposition. / Every day, 15% of the European population is exposed to average noise or air pollution levels exceeding theEuropean legal threshold. Levels and distribution of each pollutant across the city depend of individual sourcesemissions, dispersion phenomenon, and urban environment. Consequently, spatial variability of multi-exposure levelremains mostly unknown. The aim of this Ph. D. thesis is to identify and describe multi-exposure situations in the cityof Besançon. Environmental noise levels, and concentrations of several air pollutants (NO2, benzene, PM10 and PM2.5),have been modeled using a fine scale grid (2m x 2m). Model compatibility has been maximized by the use of commoninput into the calculation software Mithra-SIG (for noise) and COPERT4/ADMS-urban (for air pollutants). In a firsttime, impact of the neighborhood definition on exposure levels has been explored for both pollutions. Twelveindicators, each representing a different definition of the exposure area in the dwelling vicinity, have been used toquantify exposure levels around the 10 865 inhabitable building of Besançon. Obtained results show a significantimpact of the neighborhood definition on the exposure levels. Different neighborhood definitions lead to a differentialbias caused by a different accounting for environmental variables. This bias exists for all studied pollutant, but indifferent proportion depending on the pollutant. In a second time, situations of multi-exposure to noise and NO2 havebeen identified in the city. Results indicate a complex relation between pollutants and allow the description of severalmulti-exposure situations across the city. This work constitute one of the firsts approaches of this kind in France andallow a better understanding of the existing relations between neighborhood, exposure area, environmental parametersand exposure levels.

The thesis presents observations on the CO2 mixing ratio and the carbon isotopic ratio (13C/12C i.e. δ13) of atmospheric CO2 from the Indian region, for the period 2008 - 2011. An experimental system was established at the Centre for Earth Sciences, Indian Institute of Science, Bangalore. The experimental protocol involves collection of air samples, extraction of CO2 from the air samples collected, and finally the measurement of the CO2 mixing ratio and isotopic ratios of the extracted CO2 using pressure gauge readings and the dual inlet peripheral of the isotope ratio mass spectrometer, IRMS MAT 253. The isotopic ratios measured are scaled to VPDB and corrected for their N2O contribution. The experimental set up is calibrated with primary carbonate standards (NBS19) and an air CO2 reference mixture. The analytical precision (reproducibility of paired samples) obtained for the atmospheric CO2 measurement is ±7 µ mol.mol-1, ±0.05‰ and ±0.17‰ for the mixing ratio, δ 13C and δ 18Oof atmospheric CO2 respectively. The present study lays emphasis on the CO2 mixing ratio and the δ 13C of atmospheric CO2. There are very few atmospheric CO2 monitoring stations in India. There exists only one long-term monitoring station, Cabo de Rama, on the west coast of India. Of late, a few new stations for measuring atmospheric trace gases have been in operation, with the major focus being on remote locations. Urban stations in India have never been monitored before for both the mixing ratio and the δ13C of atmospheric CO2 together. Monitoring urban stations in India is crucial today as they have become prime emitters of CO2 due to industrial activity. The emission from the sources varies seasonally and is influenced by factors like the Indian monsoon. The Indian subcontinent is surrounded by the Arabian Sea, the Indian Ocean and the Bay of Bengal which act differentially in terms of CO2 uptake or release. There is also a differential transport of CO2 to and from the open ocean. Thus, understanding the spatial pattern of CO2 in the marine region close to the Indian subcontinent is essential to understand the oceanic uptake/release of CO2. As part of this thesis, an urban area was monitored during 2008 - 2011 and the marine region was observed during the southwest monsoon of 2009. The temporal variation of the CO2 mixing ratio and δ13C of atmospheric CO2 was observed over an urban station, Bangalore (12° 58′ N, 77° 38′ E, masl= 920 m), India. Since Bangalore is one of the developing urban cities in India, it is interesting to monitor Bangalore air to understand the impact of anthropogenic emissions on atmospheric CO2 variability. The region has four distinct seasons, dry summer (March – May), southwest monsoon (June – September), post monsoon (October – November) and winter (December – February). Thus, it is also an ideal location to identify the effect of different seasons on the contribution of CO2 from various sources. Air samples were collected from the Indian Institute of Science campus, Bangalore, during 2008 - 2011. Both the diurnal and seasonal variations of the mixing ratio and δ13C of CO2 were observed in Bangalore. On the diurnal scale, a higher mixing ratio with lighter carbon isotopes (negative value) of δ13C of CO2 was recorded in the air-CO2 analyzed during the early morning compared to the late afternoon samples. The observations suggest that coal combustion, biomass burning and car exhausts are possible sources for CO2 identified based on the Keeling plot method. The nocturnal boundary layer (NBL) is found to influence the buildup of CO2 concentration in the early morning. The presence of the NBL in the early morning prevents the mixing of locally produced air with the CO2 from the free atmosphere above. Thus, the free air contribution of CO2 is reduced during the early morning rather than in the afternoon. The effect of seasonal variability in the height of the NBL on the air CO2 mixing ratio and the 13C of atmospheric CO2 were documented in the present study. On a seasonal scale, the free air contribution of CO2 was found to be higher during the southwest monsoon and winter compared to the dry hot summer and post monsoon period. On a seasonal time scale, a sinusoidal pattern in both the mixing ratio and δ13C has been recorded in the observations. While compared with nearby CO2 monitoring stations like the coastal station, Cabo de Rama, and the Open Ocean station, Seychelles, maintained by CSIRO Australia and NOAA-CMDL respectively, Bangalore recorded higher amplitudes of seasonal variation. Seasonal scale variations have revealed an additional source i.e. emission from the cement industry along with other sources identified from diurnal variations. The emission of CO2 from these different sources is not constant; rather it was found to vary with different seasons. The enhanced biomass burning during the dry season drives the δ13C of atmospheric CO2 towards more negative values, while during the southwest monsoon; the increased biosphere cover pushes the δ13C value of atmospheric CO2 towards positive values. The effect of La Nina in 2011 is also prominent in the observation. The study also intends to identify the spatial variability of both the mixing ratio and δ 13C air-CO2 close to the urban station, Bangalore based on the simultaneous sampling of air from three locations, Bangalore and two coastal stations, Mangalore and Chennai, which are equidistant from Bangalore. Samples were collected during the southwest monsoon and winter of 2010 - 2011. The observations documented a similar source of CO2 for all the three stations irrespective of the season. The factor responsible for the variability in the mixing ratio and the δ 13C of air CO2 among these stations is the differential transport of air from the marine region and its mixing with locally produced air. To identify the variability of atmospheric CO2 over the marine region, the atmosphere over the Bay of Bengal was monitored during the southwest monsoon of 2009 as part of the Continental Tropical Convergence Zone (CTCZ) Cruise expedition. The ocean surface water was also monitored simultaneously for the δ18O of water and the δ13C of dissolved inorganic carbon measurement. The combined observations of both air and water have shown the transport of continental air to the marine region and its uptake by the ocean during the period. The variability of atmospheric-CO2 is also observed during special events like the solar eclipse. During the annular solar eclipse of 15th January, 2010 an unusually depleted source value was identified for Bangalore air. The role of the boundary layer and a change in photosynthesis were identified as possible factors affecting air CO2 composition. In conclusion, the thesis has provided the first observations on air CO2 variability from an urban station in India. The observations have identified the possible sources of CO2 and have demonstrated the role of climatic phenomena like the Atmospheric Boundary Layer, Indian Monsoon, and La Nina in controlling the behaviour of sources and sinks and thus affecting the air CO2 variability over land and ocean. The seasonal scale variation based on day-to-day variability in the afternoon samples has revealed the important contribution of emissions from the cement industry whose contribution was absent in the diurnal variability. Thus, it is evident from this study that the timing of air sampling is crucial while identifying the sources. The per capita emission of individual urban stations in India is different; thus, it is essential to monitor more urban stations to identify sources and their different contributions. In future, the simultaneous monitoring of both continental and marine air over both the Arabian Sea and the Bay of Bengal will enable us to understand the long range transport of atmospheric CO2. The long term monitoring of CO2 from the Indian region can give us a better perspective on the effect of the Indian monsoon on air CO2 variability and vice versa.