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![Does School Participatory Budgeting Increase Students’ Political Efficacy? Bandura’s “Sources,” Civic Pedagogy, and Education for Democracy](https://d1rbsgppyrdqq4.cloudfront.net/s3fs-public/styles/width_400/public/2021-07/screen-shot-2021-07-20-at-6.10.57-pm.png?versionId=01Z5qqwcTKc.eJFlSZubPdwl2jx84EzA&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASBVQ3ZQ42ZLA5CUJ/20240530/us-west-2/s3/aws4_request&X-Amz-Date=20240530T153632Z&X-Amz-SignedHeaders=host&X-Amz-Expires=120&X-Amz-Signature=5f99bae7fb5dd3b681870c13120e61e01f2fbbb4305bfafd85e96b7324580249&itok=Q5ViBtvN)
Does school participatory budgeting (SPB) increase students’ political efficacy? SPB, which is implemented in thousands of schools around the world, is a democratic process of deliberation and decision-making in which students determine how to spend a portion of the school’s budget. We examined the impact of SPB on political efficacy in one middle school in Arizona. Our participants’ (n = 28) responses on survey items designed to measure self-perceived growth in political efficacy indicated a large effect size (Cohen’s d = 1.46), suggesting that SPB is an effective approach to civic pedagogy, with promising prospects for developing students’ political efficacy.
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Engineered pavements cover a large fraction of cities and offer significant potential for urban heat island mitigation. Though rapidly increasing research efforts have been devoted to the study of pavement materials, thermal interactions between buildings and the ambient environment are mostly neglected. In this study, numerical models featuring a realistic representation of building-environment thermal interactions, were applied to quantify the effect of pavements on the urban thermal environment at multiple scales. It was found that performance of pavements inside the canyon was largely determined by the canyon geometry. In a high-density residential area, modifying pavements had insignificant effect on the wall temperature and building energy consumption. At a regional scale, various pavement types were also found to have a limited cooling effect on land surface temperature and 2-m air temperature for metropolitan Phoenix. In the context of global climate change, the effect of pavement was evaluated in terms of the equivalent CO2 emission. Equivalent CO2 emission offset by reflective pavements in urban canyons was only about 13.9e46.6% of that without building canopies, depending on the canyon geometry. This study revealed the importance of building-environment thermal interactions in determining thermal conditions inside the urban canopy.
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Trees serve as a natural umbrella to mitigate insolation absorbed by features of the urban environment, especially building structures and pavements. For a desert community, trees are a particularly valuable asset because they contribute to energy conservation efforts, improve home values, allow for cost savings, and promote enhanced health and well-being. The main obstacle in creating a sustainable urban community in a desert city with trees is the scarceness and cost of irrigation water. Thus, strategically located and arranged desert trees with the fewest tree numbers possible potentially translate into significant energy, water and long-term cost savings as well as conservation, economic, and health benefits. The objective of this dissertation is to achieve this research goal with integrated methods from both theoretical and empirical perspectives.
This dissertation includes three main parts. The first part proposes a spatial optimization method to optimize the tree locations with the objective to maximize shade coverage on building facades and open structures and minimize shade coverage on building rooftops in a 3-dimensional environment. Second, an outdoor urban physical scale model with field measurement is presented to understand the cooling and locational benefits of tree shade. The third part implements a microclimate numerical simulation model to analyze how the specific tree locations and arrangements influence outdoor microclimates and improve human thermal comfort. These three parts of the dissertation attempt to fill the research gap of how to strategically locate trees at the building to neighborhood scale, and quantifying the impact of such arrangements.
Results highlight the significance of arranging residential shade trees across different geographical scales. In both the building and neighborhood scales, research results recommend that trees should be arranged in the central part of the building south front yard. More cooling benefits are provided to the building structures and outdoor microclimates with a cluster tree arrangement without canopy overlap; however, if residents are interested in creating a better outdoor thermal environment, open space between trees is needed to enhance the wind environment for better human thermal comfort. Considering the rapid urbanization process, limited water resources supply, and the severe heat stress in the urban areas, judicious design and planning of trees is of increasing importance for improving the life quality and sustaining the urban environment.
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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.
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Studies on urban heat island (UHI) have been more than a century after the phenomenon was first discovered in the early 1800s. UHI emerges as the source of many urban environmental problems and exacerbates the living environment in cities. Under the challenges of increasing urbanization and future climate changes, there is a pressing need for sustainable adaptation/mitigation strategies for UHI effects, one popular option being the use of reflective materials. While it is introduced as an effective method to reduce temperature and energy consumption in cities, its impacts on environmental sustainability and large-scale non-local effect are inadequately explored. This paper provides a synthetic overview of potential environmental impacts of reflective materials at a variety of scales, ranging from energy load on a single building to regional hydroclimate. The review shows that mitigation potential of reflective materials depends on a set of factors, including building characteristics, urban environment, meteorological and geographical conditions, to name a few. Precaution needs to be exercised by city planners and policy makers for large-scale deployment of reflective materials before their environmental impacts, especially on regional hydroclimates, are better understood. In general, it is recommended that optimal strategy for UHI needs to be determined on a city-by-city basis, rather than adopting a “one-solution-fits-all” strategy.
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Land surface energy balance in a built environment is widely modelled using urban canopy models with representation of building arrays as big street canyons. Modification of this simplified geometric representation, however, leads to challenging numerical difficulties in improving physical parameterization schemes that are deterministic in nature. In this paper, we develop a stochastic algorithm to estimate view factors between canyon facets in the presence of shade trees based on Monte Carlo simulation, where an analytical formulation is inhibited by the complex geometry. The model is validated against analytical solutions of benchmark radiative problems as well as field measurements in real street canyons. In conjunction with the matrix method resolving infinite number of reflections, the proposed model is capable of predicting the radiative exchange inside the street canyon with good accuracy. Modeling of transient evolution of thermal filed inside the street canyon using the proposed method demonstrate the potential of shade trees in mitigating canyon surface temperatures as well as saving of building energy use. This new numerical framework also deepens our insight into the fundamental physics of radiative heat transfer and surface energy balance for urban climate modeling.
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Urban environmental measurements and observational statistics should reflect the properties generated over an adjacent area of adequate length where homogeneity is usually assumed. The determination of this characteristic source area that gives sufficient representation of the horizontal coverage of a sensing instrument or the fetch of transported quantities is of critical importance to guide the design and implementation of urban landscape planning strategies. In this study, we aim to unify two different methods for estimating source areas, viz. the statistical correlation method commonly used by geographers for landscape fragmentation and the mechanistic footprint model by meteorologists for atmospheric measurements. Good agreement was found in the intercomparison of the estimate of source areas by the two methods, based on 2-m air temperature measurement collected using a network of weather stations. The results can be extended to shed new lights on urban planning strategies, such as the use of urban vegetation for heat mitigation. In general, a sizable patch of landscape is required in order to play an effective role in regulating the local environment, proportional to the height at which stakeholders’ interest is mainly concerned.
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The sensitivity of Earth’s wetlands to observed shifts in global precipitation and temperature patterns and their ability to produce large quantities of methane gas are key global change questions. We present a microwave satellite-based approach for mapping fractional surface water (FW) globally at 25-km resolution. The approach employs a land cover-supported, atmospherically-corrected dynamic mixture model applied to 20+ years (1992–2013) of combined, daily, passive/active microwave remote sensing data. The resulting product, known as Surface Water Microwave Product Series (SWAMPS), shows strong microwave sensitivity to sub-grid scale open water and inundated wetlands comprising open plant canopies. SWAMPS’ FW compares favorably (R2 = 91%–94%) with higher-resolution, global-scale maps of open water from MODIS and SRTM-MOD44W. Correspondence of SWAMPS with open water and wetland products from satellite SAR in Alaska and the Amazon deteriorates when exposed wetlands or inundated forests captured by the SAR products were added to the open water fraction reflecting SWAMPS’ inability to detect water underneath the soil surface or beneath closed forest canopies. Except for a brief period of drying during the first 4 years of observation, the inundation extent for the global domain excluding the coast was largely stable. Regionally, inundation in North America is advancing while inundation is on the retreat in Tropical Africa and North Eurasia. SWAMPS provides a consistent and long-term global record of daily FW dynamics, with documented accuracies suitable for hydrologic assessment and global change-related investigations.
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A warming climate is altering land-atmosphere exchanges of carbon, with a potential for increased vegetation productivity as well as the mobilization of permafrost soil carbon stores. Here we investigate land-atmosphere carbon dioxide (CO2) cycling through analysis of net ecosystem productivity (NEP) and its component fluxes of gross primary productivity (GPP) and ecosystem respiration (ER) and soil carbon residence time, simulated by a set of land surface models (LSMs) over a region spanning the drainage basin of Northern Eurasia. The retrospective simulations cover the period 1960–2009 at 0.5° resolution, which is a scale common among many global carbon and climate model simulations. Model performance benchmarks were drawn from comparisons against both observed CO2 fluxes derived from site-based eddy covariance measurements as well as regional-scale GPP estimates based on satellite remote-sensing data.
The site-based comparisons depict a tendency for overestimates in GPP and ER for several of the models, particularly at the two sites to the south. For several models the spatial pattern in GPP explains less than half the variance in the MODIS MOD17 GPP product. Across the models NEP increases by as little as 0.01 to as much as 0.79 g C m-2 yr-2, equivalent to 3 to 340 % of the respective model means, over the analysis period. For the multimodel average the increase is 135 % of the mean from the first to last 10 years of record (1960–1969 vs. 2000–2009), with a weakening CO2 sink over the latter decades. Vegetation net primary productivity increased by 8 to 30 % from the first to last 10 years, contributing to soil carbon storage gains. The range in regional mean NEP among the group is twice the multimodel mean, indicative of the uncertainty in CO2 sink strength.
The models simulate that inputs to the soil carbon pool exceeded losses, resulting in a net soil carbon gain amid a decrease in residence time. Our analysis points to improvements in model elements controlling vegetation productivity and soil respiration as being needed for reducing uncertainty in land-atmosphere CO2 exchange. These advances will require collection of new field data on vegetation and soil dynamics, the development of benchmarking data sets from measurements and remote-sensing observations, and investments in future model development and intercomparison studies.