ASU Scholarship Showcase

Small and medium office buildings consume a significant parcel of the U.S. building stock energy consumption. Still, owners lack resources and experience to conduct detailed energy audits and retrofit analysis. We present an eight-steps framework for an energy retrofit assessment in small and medium office buildings. Through a bottom-up approach and a web-based retrofit toolkit tested on a case study in Arizona, this methodology was able to save about 50% of the total energy consumed by the case study building, depending on the adopted measures and invested capital. While the case study presented is a deep energy retrofit, the proposed framework is effective in guiding the decision-making process that precedes any energy retrofit, deep or light.

Commercial buildings’ consumption is driven by multiple factors that include occupancy, system and equipment efficiency, thermal heat transfer, equipment plug loads, maintenance and operational procedures, and outdoor and indoor temperatures. A modern building energy system can be viewed as a complex dynamical system that is interconnected and influenced by external and internal factors. Modern large scale sensor measures some physical signals to monitor real-time system behaviors. Such data has the potentials to detect anomalies, identify consumption patterns, and analyze peak loads. The paper proposes a novel method to detect hidden anomalies in commercial building energy consumption system. The framework is based on Hilbert-Huang transform and instantaneous frequency analysis. The objectives are to develop an automated data pre-processing system that can detect anomalies and provide solutions with real-time consumption database using Ensemble Empirical Mode Decomposition (EEMD) method. The finding of this paper will also include the comparisons of Empirical mode decomposition and Ensemble empirical mode decomposition of three important type of institutional buildings.

Sustainable fisheries management is key to restoring and maintaining ecological function and benefits to people, but it requires accurate information about patterns of resource use, particularly fishing pressure. In most coral reef fisheries and other data-poor contexts, obtaining such information is challenging and remains an impediment to effective management. We developed the most comprehensive regional view of shore-based fishing effort and catch published to date, to show detailed fishing patterns from across the main Hawaiian Islands (MHI). We reveal these regional patterns through fisher “creel” surveys conducted by local communities, state agencies, academics, and/or environmental organizations, at 18 sites, comprising >10,000 h of monitoring across a range of habitats and human influences throughout the MHI. All creel surveys included in this study except for one were previously published in some form (peer-reviewed articles or gray literature reports). Here, we synthesize these studies to document spatial patterns in nearshore fisheries catch, effort, catch rates (i.e., catch-per-unit-effort (CPUE)), and catch disposition (i.e., use of fish after catch is landed). This effort provides for a description of general regional patterns based on these location-specific studies. Line fishing was by far the dominant gear type employed. The most efficient gear (i.e., highest CPUE) was spear (0.64 kg h^-1), followed closely by net (0.61 kg h^-1), with CPUE for line (0.16 kg h^-1) substantially lower than the other two methods. Creel surveys also documented illegal fishing activity across the studied locations, although these activities were not consistent across sites. Overall, most of the catch was not sold, but rather retained for home consumption or given away to extended family, which suggests that cultural practices and food security may be stronger drivers of fishing effort than commercial exploitation for coral reef fisheries in Hawai‘i. Increased monitoring of spatial patterns in nearshore fisheries can inform targeted management, and can help communities develop a more informed understanding of the drivers of marine resource harvest and the state of the resources, in order to maintain these fisheries for food security, cultural practices, and ecological value.

There are many data mining and machine learning techniques to manage large sets of complex energy supply and demand data for building, organization and city. As the amount of data continues to grow, new data analysis methods are needed to address the increasing complexity. Using data from the energy loss between the supply (energy production sources) and demand (buildings and cities consumption), this paper proposes a Semi-Supervised Energy Model (SSEM) to analyse different loss factors for a building cluster. This is done by deep machine learning by training machines to semi-supervise the learning, understanding and manage the process of energy losses. Semi-Supervised Energy Model (SSEM) aims at understanding the demand-supply characteristics of a building cluster and utilizes the confident unlabelled data (loss factors) using deep machine learning techniques. The research findings involves sample data from one of the university campuses and presents the output, which provides an estimate of losses that can be reduced. The paper also provides a list of loss factors that contributes to the total losses and suggests a threshold value for each loss factor, which is determined through real time experiments. The conclusion of this paper provides a proposed energy model that can provide accurate numbers on energy demand, which in turn helps the suppliers to adopt such a model to optimize their supply strategies.

Three studies examined the symbolic and self-presentational meaning of low-water-use residential landscaping in a desert city in the southwestern United States. We hypothesized that owners' water-intensive or water-conserving landscape choices would be seen to convey very different characteristics. Data indicated that these two types of residential landscapes led to substantially different attributions about homeowners and also that potential homeowners could use landscapes to convey an array of characteristics to a social audience. In general, water-intensive landscapes led to more positive attributions than did water-conserving landscapes. The results support the idea that landscaping choice may be guided by self-presentational considerations, and that such considerations might influence the adoption of high- or low-water-use landscapes.

Conservation of marine resources is critical to the wellbeing of human communities. Coastal artisanal fishing communities are particularly reliant on marine resources for food and for their livelihoods. Management actions aimed at marine conservation may lead to unanticipated changes in human behavior that influence the ability of conservation programs to achieve their goals. We examine how marine conservation strategies may impact labor decisions that influence both the ecosystem and human livelihoods using simulation modeling. We consider two conservation strategies in the model: direct action through fisheries regulation enforcement, and indirect action through land conservation. Our results indicate that both strategies can increase the abundance of fish, and thus contribute to the maintenance of marine resources. However, our results also show that marine fisheries enforcement may negatively impact the livelihoods of human communities. Land conservation, on the other hand, potentially enhances the livelihood of the human populations. Thus, depending on management objectives, indirect or a combination of direct and indirect conservation strategies may be effective at achieving conservation and sustainability goals. These results highlight the importance of accounting for changes in human behavior resulting from management actions in conservation and management.

Smart growth policy and planning have tended to emphasize urban centers and regions, yet rural communities can also be important sites of innovation. Recent work demonstrated that these communities had surprisingly high levels of current and potential nonmotorized travel. Legislation in California mandates reductions in greenhouse gas emissions across all of the state's metropolitan planning organization (MPO) regions, including the heavily rural San Joaquin Valley. Advocates for rural communities are finding common cause with more traditional environmental organizations around the vision of investing in and enhancing extant rural places as an alternative to leapfrog patterns of urban and suburban sprawl. Because of existing patterns of extreme disparity and legion underserved unincorporated communities, analyses that can help integrate social equity within regional planning are needed to serve and empower rural residents. This paper presents the results of several new analyses of the social equity dimensions of regional transportation plans in the San Joaquin Valley. Activity-based travel model data were used to analyze equity, with a particular focus placed on eight disadvantaged unincorporated communities identified by community advocates to be important demonstration sites. The investigators showed how improvements to traditional equity analysis could enhance the consideration of equity in the planning process and compared the results developed by innovative techniques with those obtained by use of their traditional counterparts. The methods outlined here can make substantial contributions to reduce disparities in rural communities, which would likely be overlooked in typical regional equity analyses because of their small size, and offer lessons for MPOs serving rural areas across the country.

During the last 40 years evidence from systematic case study analysis and behavioral experiments have provided a comprehensive perspective on how communities can manage common resources in a sustainable way. The conventional theory based on selfish rational actors cannot explain empirical observations. A more comprehensive theoretical framework of human behavior is emerging that include concepts such as trust, conditional cooperation, other-regarding preferences, social norms, and reputation. The new behavioral perspective also demonstrates that behavioral responses depend on social and biophysical context.

Nitrogen availability and cell density each affects growth and cellular astaxanthin content of Haematococcus pluvialis, but possible combined effects of these two factors on the content and productivity of astaxanthin, especially under outdoor culture conditions, is less understood. In this study, the effects of the initial biomass densities IBDs of 0.1, 0.5, 0.8, 1.5, 2.7, 3.5, and 5.0 g L-1 DW and initial nitrogen concentrations of 0, 4.4, 8.8, and 17.6 mM nitrate on growth and cellular astaxanthin content of H. pluvialis Flotow K-0084 were investigated in outdoor glass column photobioreactors in a batch culture mode. A low IBD of 0.1 g L-1 DW led to photo-bleaching of the culture within 1-2 days. When the IBD was 0.5 g L-1 and above, the rate at which the increase in biomass density and the astaxanthin content on a per cell basis was higher at lower IBD. When the IBD was optimal (i.e., 0.8 g L-1), the maximum astaxanthin content of 3.8% of DW was obtained in the absence of nitrogen, whereas the maximum astaxanthin productivity of 16.0 mg L-1 d(-1) was obtained in the same IBD culture containing 4.4 mM nitrogen. The strategies for achieving maximum Haematococcus biomass productivity and for maximum cellular astaxanthin content are discussed.

Major progress has been made in the past decade towards understanding of the biosynthesis of red carotenoid astaxanthin and its roles in stress response while exploiting microalgae-based astaxanthin as a potent antioxidant for human health and as a coloring agent for aquaculture applications. In this review, astaxanthin-producing green microalgae are briefly summarized with Haematococcus pluvialis and Chlorella zofingiensis recognized to be the most popular astaxanthin-producers. Two distinct pathways for astaxanthin synthesis along with associated cellular, physiological, and biochemical changes are elucidated using H. pluvialis and C. zofingiensis as the model systems. Interactions between astaxanthin biosynthesis and photosynthesis, fatty acid biosynthesis and enzymatic defense systems are described in the context of multiple lines of defense mechanisms working in concert against photooxidative stress. Major pros and cons of mass cultivation of H. pluvialis and C. zofingiensis in phototrophic, heterotrophic, and mixotrophic culture modes are analyzed. Recent progress in genetic engineering of plants and microalgae for astaxanthin production is presented. Future advancement in microalgal astaxanthin research will depend largely on genome sequencing of H pluvialis and C. zofingiensis and genetic toolbox development. Continuous effort along the heterotrophic-phototrophic culture mode could lead to major expansion of the micro algal astaxanthin industry.