Building-integrated carbon-capture (BICC) is an envisioned mechanism capable of absorbing carbon dioxide (CO2) from the air to be stored and then converted into useful carbon-based materials without negatively impacting the environment. This dissertation builds on the authors' previous work, in which building façades were treated as artificial leaves capable of providing shade to lower solar heat gain, while simultaneously capturing CO2 through the air filters attached to the building façades by attempting a different approach capable of capturing CO2 within buildings. This dissertation presents the author’s work on BICC, where buildings are envisioned as CO2 reservoirs or vacuums, into which mechanical systems introduce fresh air, and through human activities, the air within the building becomes enriched with CO2 before being pushed out back to the outer environment. The design of a carbon-capture mechanism will take advantage of the ventilation side of existing HVAC systems, through which BICC captures CO2 from the exhaust-enriched CO2 air. BICC will utilize existing opportunities and components within buildings represented in the high CO2 concentration in buildings, ventilation guidelines, mechanical equipment represented in air handling unit and air duct network, in addition to natural gas grid connectivity. BICC will capture CO2 through buildings' mechanical system, and the captured CO2 would then be converted into renewable methane to be injected into the existing natural gas pipeline network. This dissertation will investigate the potential of BICC to offset carbon emissions from multiple commercial building types and will present a utilization strategy for the captured carbon.

The rapid rate of urbanization coupled with continued population growth and anthropogenic activities has resulted in a myriad of urban climate related impacts across different cities around the world. Hot-arid cities are more vulnerable to induced urban heat effects due to the intense solar radiation during most of the year, leading to increased ambient air temperature and outdoor/indoor discomfort in Phoenix, Arizona. With the fast growth of the capital city of Arizona, the automobile-dependent planning of the city contributed negatively to the outdoor thermal comfort and to the people's daily social lives. One of the biggest challenges for hot-arid cities is to mitigate against the induced urban heat increase and improve the outdoor thermal. The objective of this study is to propose a pragmatic and useful framework that would improve the outdoor thermal comfort, by being able to evaluate and select minimally invasive urban heat mitigation strategies that could be applied to the existing urban settings in the hot-arid area of Phoenix. The study started with an evaluation of existing microclimate conditions by means of multiple field observations cross a North-South oriented urban block of buildings within Arizona State University’s Downtown campus in Phoenix. The collected data was evaluated and analyzed for a better understanding of the different local climates within the study area, then used to evaluate and partially validate a computational fluid dynamics model, ENVI-Met. Furthermore, three mitigation strategies were analyzed to the Urban Canopy Layer (UCL) level, an increase in the fraction of permeable materials in the ground surface, adding different configurations of high/low Leaf Area Density (LAD) trees, and replacing the trees configurations with fabric shading. All the strategies were compared and analyzed to determine the most impactful and effective mitigation strategies. The evaluated strategies have shown a substantial cooling effect from the High LAD trees scenarios. Also, the fabric shading strategies have shown a higher cooling effect than the Low LAD trees. Integrating the trees scenarios with the fabric shading had close cooling effect results in the High LAD trees scenarios. Finally, how to integrate these successful strategies into practical situations was addressed.

Passive cooling techniques, specifically passive downdraft cooling (PDC), have proven to be a solution that can address issues associated with air conditioning (AC). Globally, over 100 buildings have integrated PDC in its different forms, most of which use direct evaporative cooling. Even though all surveyed buildings were energy efficient and cost-effective and most surveyed buildings were thermally comfortable, application of PDC remains limited. This study aims to advance performance of the single stage passive downdraft evaporative cooling tower (PDECT), and expand its applicability beyond the hot dry conditions where it is typically used, by designing and testing a multi-stage passive and hybrid downdraft cooling tower (PHDCT). Experimental evaluation on half-scale prototypes of these towers was conducted in Tempe, Arizona, during the hot dry and hot humid days of Summer, 2017. Ambient air dry-bulb temperatures ranged between 73.0°F with 82.9 percent coincident relative humidity, and 123.4°F with 7.8 percent coincident relative humidity. Cooling systems in both towers were operated simultaneously to evaluate performance under identical conditions.



Results indicated that the hybrid tower outperformed the single stage tower under all ambient conditions and that towers site water consumption was at least 2 times lower than source water required by electric powered AC. Under hot dry conditions, the single stage tower produced average temperature drops of 35°F (5°F higher than what was reported in the literature), average air velocities of 200 fpm, and average cooling capacities of 4 tons. Furthermore, the hybrid tower produced average temperature drops of 45°F (50°F in certain operation modes), average air velocities of 160 fpm, and average cooling capacities exceeding 4 tons. Under hot humid conditions, temperature drops from the single stage tower were limited to the ambient air wet-bulb temperatures whereas drops continued beyond the wet-bulb in the hybrid tower, resulting in 60 percent decline in the former’s cooling capacity while maintaining the capacity of the latter. The outcomes from this study will act as an incentive for designers to consider incorporating PDC into their designs as a viable replacement/supplement to AC; thus, reducing the impact of the built environment on the natural environment.

City administrators and real-estate developers have been setting up rather aggressive energy efficiency targets. This, in turn, has led the building science research groups across the globe to focus on urban scale building performance studies and level of abstraction associated with the simulations of the same. The increasing maturity of the stakeholders towards energy efficiency and creating comfortable working environment has led researchers to develop methodologies and tools for addressing the policy driven interventions whether it’s urban level energy systems, buildings’ operational optimization or retrofit guidelines. Typically, these large-scale simulations are carried out by grouping buildings based on their design similarities i.e. standardization of the buildings. Such an approach does not necessarily lead to potential working inputs which can make decision-making effective. To address this, a novel approach is proposed in the present study.

The principle objective of this study is to propose, to define and evaluate the methodology to utilize machine learning algorithms in defining representative building archetypes for the Stock-level Building Energy Modeling (SBEM) which are based on operational parameter database. The study uses “Phoenix- climate” based CBECS-2012 survey microdata for analysis and validation.

Using the database, parameter correlations are studied to understand the relation between input parameters and the energy performance. Contrary to precedence, the study establishes that the energy performance is better explained by the non-linear models.

The non-linear behavior is explained by advanced learning algorithms. Based on these algorithms, the buildings at study are grouped into meaningful clusters. The cluster “mediod” (statistically the centroid, meaning building that can be represented as the centroid of the cluster) are established statistically to identify the level of abstraction that is acceptable for the whole building energy simulations and post that the retrofit decision-making. Further, the methodology is validated by conducting Monte-Carlo simulations on 13 key input simulation parameters. The sensitivity analysis of these 13 parameters is utilized to identify the optimum retrofits.

From the sample analysis, the envelope parameters are found to be more sensitive towards the EUI of the building and thus retrofit packages should also be directed to maximize the energy usage reduction.

The objective of this thesis is to investigate the various types of energy end-uses to be expected in future high efficiency single family residences. For this purpose, this study has analyzed monitored data from 14 houses in the 2013 Solar Decathlon competition, and segregates the energy consumption patterns in various residential end-uses (such as lights, refrigerators, washing machines, ...). The analysis was not straight-forward since these homes were operated according to schedules previously determined by the contest rules. The analysis approach allowed the isolation of the comfort energy use by the Heating, Venting and Cooling (HVAC) systems. HVAC are the biggest contributors to energy consumption during operation of a building, and therefore are a prime concern for energy performance during the building design and the operation. Both steady state and dynamic models of comfort energy use which take into account variations in indoor and outdoor temperatures, solar radiation and thermal mass of the building were explicitly considered. Steady State Inverse Models are frequently used for thermal analysis to evaluate HVAC energy performance. These are fast, accurate, offer great flexibility for mathematical modifications and can be applied to a variety of buildings. The results are presented as a horizontal study that compares energy consumption across homes to arrive at a generic rather than unique model - to be used in future discussions in the context of ultra efficient homes. It is suggested that similar analyses of the energy-use data that compare the performance of variety of ultra efficient technologies be conducted to provide more accurate indications of the consumption by end use for future single family residences. These can be used alongside the Residential Energy Consumption Survey (RECS) and the Leading Indicator for Remodeling Activity (LIRA) indices to assist in planning and policy making related to residential energy sector.

The need for alternative energy efficient building heating and cooling technologies has given rise to the development and widespread use of Ground Coupled Heat Pump (GCHP) systems. This dissertation looks at the feasibility of using GCHP systems as a viable economic alternative to traditional air source cooling systems (ASHP) for conditioning buildings in the hot, semi-arid climate of Phoenix, Arizona. Despite high initial costs, GCHPs are gaining a foothold in northern climates where heating dominates, in large part due to government incentives. However, due to issues associated with low ground heat exchanger (GHE) efficiency and thermally-induced soil deformations, GCHPs are typically not considered a viable option in hot climates with deep groundwater and low permeability soil. To evaluate the energy performance and technical feasibility of GCHPs in Phoenix, the DOE 5,500 sq.ft small office, commercial building prototype was simulated in EnergyPlus to determine the cooling and heating loads. Next, a commercial software program, Ground Loop Design (GLD), was used to design and simulate the annual energy performance of both vertical (V-GCHPs) and horizontal GCHPs (H-GCHPs). Life cycle costs (LCC) were evaluated using realistic market costs both under dry, as well as fully saturated soil conditions (meant as an upper performance limit achievable by ground modification techniques). This analysis included performing several sensitivity analyses and also investigating the effect of financial rebates. The range of annual energy savings from the GCHP system for space cooling and heating was around 38-40% compared to ASHPs for dry soil. Saturated soil condition significantly affects the length of the GHE. For V-GCHPs, there was about 26% decrease in the length of GHE, thereby reducing the initial cost by 18-19% and decreasing the payback period by 24-25%. Likewise, for H-GCHPs, the length of GHE was reduced by 25% resulting in 22% and 39-42 % reduction in the initial cost and payback period respectively. With federal incentives, H-GCHPs under saturated soil conditions have the least LCC and a good payback periods of 2.3-4.7 years. V-GCHPs systems were been found to have payback periods of over 25 years, making them unfeasible for Phoenix, AZ, for the type of building investigated.

The ability to design high performance buildings has acquired great importance in recent years due to numerous federal, societal and environmental initiatives. However, this endeavor is much more demanding in terms of designer expertise and time. It requires a whole new level of synergy between automated performance prediction with the human capabilities to perceive, evaluate and ultimately select a suitable solution. While performance prediction can be highly automated through the use of computers, performance evaluation cannot, unless it is with respect to a single criterion. The need to address multi-criteria requirements makes it more valuable for a designer to know the "latitude" or "degrees of freedom" he has in changing certain design variables while achieving preset criteria such as energy performance, life cycle cost, environmental impacts etc. This requirement can be met by a decision support framework based on near-optimal "satisficing" as opposed to purely optimal decision making techniques. Currently, such a comprehensive design framework is lacking, which is the basis for undertaking this research. The primary objective of this research is to facilitate a complementary relationship between designers and computers for Multi-Criterion Decision Making (MCDM) during high performance building design. It is based on the application of Monte Carlo approaches to create a database of solutions using deterministic whole building energy simulations, along with data mining methods to rank variable importance and reduce the multi-dimensionality of the problem. A novel interactive visualization approach is then proposed which uses regression based models to create dynamic interplays of how varying these important variables affect the multiple criteria, while providing a visual range or band of variation of the different design parameters. The MCDM process has been incorporated into an alternative methodology for high performance building design referred to as Visual Analytics based Decision Support Methodology [VADSM]. VADSM is envisioned to be most useful during the conceptual and early design performance modeling stages by providing a set of potential solutions that can be analyzed further for final design selection. The proposed methodology can be used for new building design synthesis as well as evaluation of retrofits and operational deficiencies in existing buildings.

With the desire of high standards of comfort, huge amount of energy is being consumed to maintain the indoor environment. In US building consumes 40% of the total primary energy while residential buildings consume about 21%. A large proportion of this consumption is due to cooling of buildings. Deteriorating environmental conditions due to excessive energy use suggest that we should look at passive designs and renewable energy opportunities to supply the required comfort. Phoenix gets about 300 days of clear sky every year. It also witnesses large temperature variations from night and day. The humidity ratio almost always stays below the 50% mark. With more than six months having outside temperatures more than 75 oF, night sky radiative cooling promise to be an attractive means to cool the buildings during summer. This technique can be useful for small commercial facilities or residential buildings. The roof ponds can be made more effective by covering them with Band Filters. These band filters block the solar heat gain and allow the water to cool down to lower temperatures. It also reduces the convection heat gain. This helps rood ponds maintain lower temperatures and provide more cooling then an exposed pond. 50 μm Polyethylene band filter is used in this study. Using this band filter, roof ponds can be made up to 10% more effective. About 45% of the energy required to cool a typical residential building in summer can be saved.

Due to the lack of understanding of soil thermal behavior, rules-of-thumb and generalized procedures are typically used to guide building professionals in the design of ground coupled heat pump systems. This is especially true when sizing the ground heat exchanger (GHE) loop. Unfortunately, these generalized procedures often encourage building engineers to adopt a conservative design approach resulting in the gross over-sizing of the GHE, thus drastically increasing their installation cost. This conservative design approach is particularly prevalent for buildings located in hot and arid climates, where the soils are often granular and where the water table tends to exist deep below the soil surface. These adverse soil conditions reduce the heat dissipation efficiency of the GHE and have hindered the adoption of ground coupled heat pump systems in such climates. During cooling mode operation, heat is extracted from the building and rejected into the ground via the GHE. Prolonged heat dissipation into the ground can result in a coupled flow of both heat and moisture, causing the moisture to migrate away from the GHE piping. This coupled flow phenomenon causes the soil near the GHE to dry out and results in the degradation of the GHE heat dissipation capacity. Although relatively simple techniques of backfilling the GHE have been used in practice to mitigate such coupled effects, methods of improving the thermal behavior of the backfill region around the GHE, especially in horizontal systems, have not been extensively studied. This thesis presents an experimental study of heat dissipation from a horizontal GHE, buried in two backfill materials: (1) dry sand, and (2) wax-sand composite mixture. The HYDRUS software was then used to numerically model the temperature profiles associated with the aforementioned backfill conditions, and the influence of the contact resistance at the GHE-backfill interface was studied. The modeling strategy developed in HYDRUS was proven to be adequate in predicting the thermal performance of GHE buried in dry sand. However, when predicting the GHE heat dissipation in the wax-sand backfill, significant discrepancies between model prediction and experimental results still exist even after calibrating the model by including a term for the contact resistance. Overall, the thermal properties of the backfill were determined to be a key determinant of the GHE heat dissipation capacity. In particular, the wax-sand backfill was estimated to dissipate 50-60% more heat than dry sand backfill.

A major problem faced by electric utilities is the need to meet electric loads during certain times of peak demand. One of the widely adopted and promising programs is demand response (DR) where building owners are encouraged, by way of financial incentives, to reduce their electric loads during a few hours of the day when the electric utility is likely to encounter peak loads. In this thesis, we investigate the effect of various DR measures and their resulting indoor occupant comfort implications, on two prototype commercial buildings in the hot and dry climate of Phoenix, AZ. The focus of this study is commercial buildings during peak hours and peak days. Two types of office buildings are modeled using a detailed building energy simulation program (EnergyPlus V6.0.0): medium size office building (53,600 sq. ft.) and large size office building (498,600 sq. ft.). The two prototype buildings selected are those advocated by the Department of Energy and adopted by ASHRAE in the framework of ongoing work on ASHRAE standard 90.1 which reflect 80% of the commercial buildings in the US. After due diligence, the peak time window is selected to be 12:00-18:00 PM (6 hour window). The days when utility companies require demand reduction mostly fall during hot summer days. Therefore, two days, the summer high-peak (15th July) and the mid-peak (29th June) days are selected to perform our investigations. The impact of building thermal mass as well as several other measures such as reducing lighting levels, increasing thermostat set points, adjusting supply air temperature, resetting chilled water temperature are studied using the EnergyPlus building energy simulation program. Subsequently the simulation results are summarized in tabular form so as to provide practical guidance and recommendations of which DR measures are appropriate for different levels of DR reductions and the associated percentage values of people dissatisfied (PPD). This type of tabular recommendations is of direct usefulness to the building owners and operators contemplating DR response. The methodology can be extended to other building types and climates as needed.