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

Built-up areas represent an artifiial impait to natural environment with large spatial variability and speiifi meihaniit radiationt thermal and ihemiial properties. Despite of inireasing horizontal resolution of numeriial weather prediition modelst the impait of loial built-up area on mesosynoptiv weather phenomena is still not well resolved. Therefore it is neiessary to use some of urban environment modelst whiih were designed to parameterize speiifi urban prosiessest not expliiitly resolved inside the grid box. In the thesis main urban iharaiteristiis are explained (impait on the struiture of boundary layert radiation and heat balanie of urban environment or urban heat island)t basii priniiples of urbanization appliiation in the numeriial weather model are desiribedt as well as different urban parameterizations available in numeriial model WRFe (Weather Reseaih and Feoreiasting). Number of validation experiments were performed for summer and winter episode in non-hydrostatii mode at 3t3 km resolutiont where different urban parametrizationst antropogenii heat adjustment and impait of mosaii land-use were tested. April 2018 Prague weather foreiast was verifiated in ionsideration of urban heat island.

Urbanization modifies the thermal characteristics of the land and makes way for a succession of transformations in the urban environmental system. This phenomenon, known as Urban Heat Island (UHI), is characterized by elevated temperatures in urban areas that negatively impact on the quality of life and environment in urban areas including, increased emissions of Green House Gases (GHGs) and rising energy consumption. These impacts add to global climate change and thus, mitigating UHI is essential to mitigating global climate change. One GHG, Carbon Dioxide (CO2), accounts for about half of the Earth’s anthropogenic GHG emissions. Terrestrial ecosystems can act as Carbon sinks (C sinks), i.e. natural vegetation reservoirs that absorb more C than they release. Thus, C sinks play an essential and critical function in lowering CO2. Furthermore, providing appropriate C sinks at both the building and urban scales can decrease UHI and contribute to reduction in energy consumption. This study used Landsat 8 imagery of the site, Al Bayt Stadium in Qatar, to investigate the effects of surface UHI by computing the Land Surface Temperature (LST) difference of the site---pre- and post-construction, as well as examine the correlation between natural vegetation abundance and temperature in ten locations within the site’s vicinity. Results show that minimum, maximum and mean LST of the case study area (2014 vs. 2020) decreased 2.80 oC, 5.5 oC and 2.3 oC, respectively, as well as a decreasing trend in the LST as a function of increasing C Sinks. These results demonstrate the importance of introducing C sinks to lower LST and mitigate UHI. Mitigating UHI also has a direct effect on Energy Consumption Balance (ECB). This equilibrium is achieved not only through the introduction of C sinks, but balancing C sinks with high albedo materials and natural ventilation.  Thus, this study also investigated the site’s various design aspects (e.g. cooling technology, structure and surface albedo materials, landscaping) and found that Al Bayt Stadium’s design successfully incorporates strategies to reduce energy consumption at both the urban (macro) and building (micro) scales.

In this study eddy covariance was used to measure sensible heat, latent heat, and carbon dioxide fluxes for the months of August, September, and October of 2009 within the roughness sublayer (RSL) of the urban center of Portland, OR. Vehicle traffic and solar radiation were also measured for the month of October. Flux measurements were compared with measurements from other urban areas as a test of reasonableness. CO₂ fluxes were nearly always positive and were strongly correlated with the weekday diurnal traffic cycle. CO₂ fluxes averaged 6.6 μmol/m^²s, which is less than other published measurements in urban areas. Sensible and latent heat fluxes followed the expected diurnal profile associated with solar radiation. Average sensible heat flux decreased as the season changed from summer to fall, moving from an average of 39 W/m^² in August to 12 W/m^² in October. A corresponding increase in latent heat flux was observed during this period, changing from an average of 10 W/m^² in August to 17 W/m^² in October. Heat flux behavior and amplitude was consistent with other urban measurements, though amplitude varies considerably from city to city. Stationarity was shown to positively influence measured CO₂ fluxes, but to have little effect on measured heat fluxes. Preliminary comparisons of October sensible heat and CO₂ fluxes to an inventory-based estimate of vehicle emissions indicate that eddy covariance measurements underestimate the true fluxes by 50%.

Cities are home to more than half of the world’s population, and this figure is set to continue to rise amidst ongoing global urbanization trends. Against this backdrop, urban development is increasingly confronted with multifaceted challenges. These range from public health emergencies, exemplified by the COVID-19 global pandemic, to the environmental hazards driven by climate change, including extreme heat waves and more frequent severe storms. Confronted with these substantial risks, the urgency of devising and implementing strategies for sustainable and resilient urban development has become paramount. Given this context, the work presented in this thesis aims to advance understanding of some critical urban sustainability challenges, and to develop models, tools, and sensing systems that can support progress towards a more sustainable and resilient urban future. The first part of the thesis focuses on the role and usage of urban parks during a global public health emergency. Urban parks became critical for maintaining the well-being of urban residents during the COVID-19 global pandemic. To examine the impact of COVID-19 on urban park usage, New York City (NYC) was selected as a case study, and SafeGraph mobility data, which was collected from a large sample of mobile phone users, was used to assess the change in park visits and travel distance to a park based on park type, the income level of the visitor’s census block group (visitor CBG) and that of the park census block group (park CBG). All analyses were adjusted for the impact of temperature on park visitation, and the research work was focused primarily on park visits made by NYC residents. Overall, for the eight most popular park types in NYC, namely – Community Park, Flagship Park, Jointly Operated Playground, Nature Area, Neighborhood Park, Playground, Recreation Field/Courts and Triangle/Plaza – visits dropped by 49.2% from 2019 to 2020. The peak reduction in visits occurred in April 2020. Visits to all park types, excluding Nature Areas, decreased from March to December 2020 as compared to 2019. Parks located in higher-income CBGs tended to have lower reductions in visits, with this pattern being primarily driven by visits to large parks, including Flagship Parks, Community Parks and Nature Areas. All types of parks saw significant decreases in distance traveled to visit the park, with the exception of the Jointly Operated Playground, Playground, and Nature Area park types. Visitors originating from lower-income CBGs traveled shorter distances to parks and had less reduction in travel distances compared to those from higher-income CBGs. Furthermore, both before and during the pandemic, people tended to travel a greater distance to parks located in high-income CBGs compared to those in low-income CBGs. Finally, multiple types of parks proved crucial destinations for NYC residents during the pandemic. These included Nature Areas to which the visits remained stable, along with Recreation Field/Courts which had relatively small decreases in visits especially for lower-income communities. Results from this particular research study can support future park planning by shedding light on the different users of certain park types before and during a global crisis, where access to green spaces can help alleviate the human well-being consequences associated with mitigating the crisis, including the type of “lockdown” or limited mobility policies implemented in 2020 during the COVID-19 global pandemic. The second part of the thesis investigates the role of urban greening and other land surface features in influencing the urban heat island effect in NYC. The urban heat island (UHI) effect describes the phenomenon whereby cities are generally warmer than surrounding rural areas. UHI effects can exacerbate extreme heat events, leading to an increase in heat-related illness and mortality. Here, the runoff coefficient was used as a numerical surrogate for urban greening, with lower runoff coefficients being associated with higher fractions of urban greening. Using a high-resolution landcover GIS dataset developed for New York City (NYC), which classified the city into more than 13 million land patches, the runoff coefficient of land use across the entire city was mapped down to a resolution of 30m×30m, along with five other variables including surface albedo, distance to water bodies, land surface elevation, building density and building height. Daytime land surface temperature (LST) in summer was used as a surrogate for the UHI effect in NYC, and the work investigated the relationship between the runoff coefficient and LST. The work also examined the relationship between LST and the variables of surface albedo, distance to a water body, land surface elevation, building density and building height. Results indicate that runoff coefficient can explain a large portion of variability related to urban LST, with lower runoff coefficients (more greenery) being associated with lower LST. Use of the five other variables improves the predictability of LST, although the influence each variable has on LST varies with urban setting and context. The research work presented in this part of the thesis also shows the disproportionately higher exposure to urban heat in lower-income communities in NYC. The findings can be used to develop strategies to mitigate UHI effects in NYC and other cities around the world. In the third part of the thesis, a wireless environmental sensing system is developed for monitoring urban green spaces, with demonstrated application for stormwater management. The monitoring of urban green spaces, including monitoring of soil conditions and soil health, is crucial for sustainable urban development and ecological resilience. Leveraging advances in wireless environmental sensing, a LoRaWAN-based system capable of measuring air temperature/humidity, soil temperature and moisture, and soil moisture dynamics is designed and deployed across seven diverse urban green spaces for a full year at Columbia University’s Morningside Campus in New York City. The data collected by this sensing network reveals notable variations in soil moisture across the seven monitored sites, which are influenced by a combination of vegetation type, soil conditions, and physical settings. Monitored lawns consistently showed higher soil moisture levels due to their slower draining soil type, underlying concrete structures, and lower canopy rainfall interception and transpiration loss, whereas one monitored tree pit site with a more rapidly draining soil type showed significantly lower soil moisture throughout the study period, despite having comparable physical settings with another monitored site. Seasonal trends indicated lower summer moisture in some monitored areas due to increased evaporation and transpiration under high temperatures, while others areas maintained higher soil moisture as a result of frequent irrigations. Models were developed to quantify soil moisture response to rainfall events. It was found that the increase in soil moisture at each monitored site was highly dependent on the rainfall depth and the initial soil moisture. Overall, the results show that a range of diverse green spaces can help retain and drain storms up to certain sizes of 30-50mm. However, proactively designed soil drainage systems are needed to handle extreme storm events above 50mm. The study highlights the effectiveness of LoRaWAN technology in urban environmental monitoring and provides valuable insights into how different urban green spaces can contribute to stormwater management. The findings presented in this portion of the thesis demonstrate the instrumental role that monitoring, data analysis and modeling can play in helping city planners and environmental managers optimize urban green spaces for ecological benefits and enhance urban resilience, including in the face of stressors such as climate change. Overall, with its data-driven, evidence-based insights, this work contributes to the understanding of the multifaceted urban sustainability challenges in a changing environment, including public health emergencies such as the COVID-19 global pandemic, and climate change induced environmental hazards such as extreme heat events and more frequent severe storms. Alongside deepening understanding, the developed quantitative models and sensing technologies presented in this thesis offer practical solutions to support urban development towards a more sustainable and resilient future.

Improvements for environmental monitoring and assessment were achieved to advance our understanding of sea-land interactions and nutrient cycling in a coastal bay.; The comprehensive assessment techniques for monitoring of water quality of a coastal bay can be diversified via an extensive investigation of the spatiotemporal nutrient patterns and the associated eco-hydrological trends in a coastal urban region. With this work, it is intended to thoroughly investigate the spatiotemporal nutrient patterns and associated eco-hydrological trends via a two part inquiry of the watershed and its adjacent coastal bay. The findings show that the onset of drought lags the crest of the evapotranspiration and precipitation curve during each year of drought. During the transition year, ET and precipitation appears to start to shift back into the analogous temporal pattern as the 2005 wet year. NDVI shows a flat receding tail for the September crest in 2005 due to the hurricane impact signifying that the hurricane event in October dampening the severity of the winter dry season in which alludes to relative system memory. The k-means model with 8 clusters is the optimal choice, in which cluster 2 at Lower Tampa Bay had the minimum values of total nitrogen (TN) concentrations, chlorophyll a (Chl-a) concentrations, and ocean color values in every season as well as the minimum concentration of total phosphorus (TP) in three consecutive seasons in 2008. Cluster 5, located in Middle Tampa Bay, displayed elevated TN concentrations, ocean color values, and Chl-a concentrations, suggesting that high colored dissolved organic matter values are linked with some nutrient sources. The data presented by the gravity modeling analysis indicate that the Alafia River Basin is the major contributor of nutrients in terms of both TP and TN values in all seasons. Such ecohydrological evaluation can be applied for supporting the LULC management of climatic vulnerable regions as well as further enrich the comprehensive assessment techniques for estimating and examining the multi-temporal impacts and dynamic influence of urban land use and land cover.

No description available.

As urbanization and global warming increase, an increasing importance is set on that urban planning processes take the possible effects of urban heat islands into account. In order to provide local city planners with site specific knowledge of the current situation in Stockholm, this study has explored the intra-urban heat island effect in Stockholm municipality by identifying major problem areas as well as addressing the statistical relationship between temperature and factors relating to land cover and urban planning strategies. Remotely sensed land surface temperature (LST) and the Swedish National Land Cover Database (NMD) have formed the data basis for the analyses that were carried out using GIS. The LST and land cover information have been extracted from randomly placed circle polygons in order to create a sample for the statistical analyses.  The results show that there exist differences in temperature within Stockholm municipality, both within the municipality as a whole and between various urban characters. In both cases, land cover is identified as an important, but not sole, factor to explain the differences. On land areas, artificial non-vegetated surfaces and forest is identified as the land cover classes of most relevance when it comes to the urban heat island effect. For both land cover classes, a strong correlation to LST is seen. Even though certain uncertainties and limitations are embedded in the data as well as in the method choices, the study can conclude in that the urban heat island effect is present in Stockholm municipality and that it can be derived from both land cover and urban characters. / I takt med att urbaniseringen och den globala uppvärmningen ökar kommer högre krav ställas på att stadsplaneringen tar hänsyn till de effekter som väntas uppstå kopplat till urbana värmeöar. I syfte att bistå lokala stadsplanerare med platsspecifik kunskap om den nuvarande situationen i Stockholm har den här studien utforskat intraurbana temperaturvariationer i Stockholms stad genom att identifiera de mest utsatta områdena samt genom att undersöka det statistiska sambandet mellan temperatur och faktorer kopplat till marktäcke och stadsutformning. Markens yttemperatur uppmätt från satellit och Nationella marktäckedata (NMD) har utgjort det främsta dataunderlaget för analyserna som genomförts med hjälp av GIS. Genom att extrahera information om yttemperatur och marktäcke från slumpmässigt placerade cirkelpolygoner kunde ett urval till de statistiska analyserna skapas.  Resultaten från studien visar att det finns skillnader i temperatur inom Stockholms stad, både inom kommunen som helhet och mellan olika stadsbyggnadskaraktärer. I båda fallen kan marktäcke identifieras som en viktig, men inte ensam, faktor till att förklara skillnaderna. På landområdena identifieras exploaterad mark och skog som de marktäcken med störst betydelse när det kommer till urbana värmeöar. För båda marktäckena ses i studien en stark korrelation till yttemperatur. Trots att vissa osäkerheter och begräsningar kan kopplas till både använd data och de metoder som använts kan slutsatsen att effekten från urbana värmeöar finns i Stockholms kommun dras. Dessutom kan konstateras att effekten kan härledas både till marktäcke och stadsbyggnadskaraktär.

För att bromsa effekterna av klimatförändringarna i urbana miljöer krävs det omfattande vetenskaplig forskning inom alla områden. Till en början för att öka medvetenheten om alla oklara frågor och aspekter av effekterna av ett förändrat klimat - och sedan som ett verktyg för att skapa holistiska lösningar som bör sträva efter att lösa en sammansättning av problem inom samma insats. Med denna studie vill vi belysa vikten i sammanhållen stadsuteckling för att lyckas med klimatanpassning. Både effekter av och orsaker till urbana värmeöar är något som träder fram över längre perioder av tid, samt påverkas av permanenta och storskaliga förändringar. Argument för implementeringen av insatser såsom alternativa sätt av mobilitet blir därmed mer realistiska och genomförbara genom att belysa vikten av en mer storskalig, övergripande och gemensam planering. / To cultivate efforts to curb the effects of climate change in urban spaces, a multitude of scientific research across all features is necessary. First, as a step to raise awareness to every obscure issue and aspect of the effects of a changing climate; and second as a tool to create holistic solutions which should strive to solve a compund of issues within the same action. With this thesis we want to illustrate the importance of a cohesive urban development to be able to succeed in climate change adaption. Both effects and causes of urban heat islands appear over time and are affected by permanent and grand changes in the urban environment. Therefore, arguments for the implementation of actions such as alternative ways to confront mobility become more realistic and achievable through illustrating the importance of a more holistic and united urban planning approach.

This study critically examines the (UHI) effect in urban and suburban neighbourhoods of Quito, Ecuador, over a 19-year period, focusing on the interplay between atmospheric pollution and urban/ suburban temperature. Utilizing Empirical Dynamic Modeling(EDM) and Convergent Cross-Mapping (CCM), this study dives into the nonlinear dynamics of environmental factors, a method that traditional linear models fail to address effectively.The results unveil a consistent and strong positive correlation across various neighbourhoods, with temperature fluctuations indicating a typical UHI effect. This is most noticeable in urbanized areas where the temperature is significantly higher due to dense infrastructure and reduced greenery, a pattern that diminishes as one moves towards the outskirts. Specifically, pollutants like PM2.5 exhibit a non-uniform positive correlation, suggesting their collective increase or decrease across different regions, whereas CO shows a very slight and inconsistent inverse relationship across locations. The causal analysis further substantiates a significant interaction between PM2.5 concentrations and temperature, with the data revealing a reciprocal predictive capacity between these variables. The CCM analysis, through its graphical representation of predictive skills, confirms the causal effect of PM2.5 on urban temperature, marking an essential contribution to understanding the UHI effect and its implications for urban environmental dynamics. This study provides a comprehensive overview of the UHI phenomenon, highlighting the intricate relationship between urbanization, atmospheric pollution, and climate. The findings emphasize the necessity for urban planning and policy to consider these complex interactions to mitigate the effects of climate change on urban environments.