Sewage, agricultural runoff, and atmospheric deposition have greatly increased the amount of nutrients (largely nitrogen (N) and phosphorus (P)) in surface water nationwide. Excess nutrients are associated with algal blooms and dissolved oxygen depletion in many water bodies, but linkages between nutrients and dissolved oxygen have been largely correlative. Biochemical oxygen demand (BOD) is a regulated water quality parameter that is aimed at describing the amount of oxygen consumed during the decomposition of organic matter. Despite the awareness that excess nutrients are linked to dissolved oxygen in rivers, few studies in the nutrient criteria literature discuss BOD measurements or how nutrients may impact BOD. Accordingly, I used factorial experiments to test the effect of inorganic nutrients (as N, P and N+P) and dissolved organic carbon on BOD measurements in Utah streams. The study was carried out from January through summer baseflow in 2011, allowing me to evaluate the effects of spatial and temporal variation of ambient nutrient concentration on oxygen demand. The study design included measurements in streams above and below nutrient point-sources (publicly owned treatment works) and several reference sites. I used classification and regression trees to identify thresholds of TN and TP that separate BOD response to nutrients into statistically distinct groups. My results show that seasonal variation affected BOD levels. As temperatures rose and water levels increased during peak runoff, I observed the highest BOD response to nutrient additions. I also found a significant correlation between BOD and ambient nutrient concentrations during that time period. I identified potential nutrient-related thresholds that could be used to assign numeric criteria that would protect designated uses. The threshold values I found for TN and TP were 0.56 mg/L and 0.09 mg/L, respectively. My results suggest that BOD may be sensitive to nutrient inputs and my experimental approach could be used as one line of evidence to support nutrient criteria related to aquatic life uses.

Syftet med den föreliggande studien var att undersöka huruvida arbetsrelaterade krav och arbetsrelaterade resurser kunde predicera utmattning hos förskolepersonal (N = 114). Studien genomfördes med en korrelationell design där de validerade enkäterna COPSOQ III och KUS-26 användes för att samla in data. Analysen genomfördes med tre hierarkiska multipla regressionsanalyser som visade att arbetsrelaterade krav och arbetsrelaterade resurser tillsammans kunde predicera utmattning. Arbetsrelaterade krav kunde predicera utmattning med ett positivt samband, medan arbetsrelaterade resurser inte på egen hand kunde predicera utmattning när de förekom i samma modell som arbetsrelaterade krav. Känslomässiga krav och kvantitativa krav var de typer av arbetsrelaterade krav som positivt kunde predicera utmattning. Socialt stöd från överordnad var den enda typen av resurs som kunde predicera utmattning med ett negativt samband. Sammanfattningsvis visade den föreliggande studien att arbetsrelaterade krav tycks vara en större riskfaktor än bristande arbetsrelaterade resurser när det kommer till utmattningsproblematik hos svensk förskolepersonal. / The aim of this study was to investigate whether job-demands and resources could predict exhaustion in Swedish preschool personnel (N = 114). The study was done using a quantitative method where the validated questionnaires COPSOQ III and KUS-26 were used to gather the data. Using 3 hierarchical multiple regression analyzes the present study showed that job-demands and resources could predict exhaustion. Job demands could positively predict exhaustion. However, job resources could not on its own predict exhaustion when occurring in the same model as job demands. The present study showed that emotional and quantitative demands were the types of demands that could positively predict exhaustion. Social support from supervisor was the only type of resource that could negatively predict exhaustion. In conclusion, the study showed that for Swedish preschool personnel, high job demands are a greater risk factors for exhaustion than lacking job resources.

Electric power systems are undergoing a paradigm shift where an increasing number of variable renewable energy resources such as wind and solar power are being introduced to all levels of existing power grids. At the same time consumers are gaining a more active role where self energy production and home automation solutions are no longer uncommon. This challenges traditional power systems which were designed to serve as a centralized top-down solution for providing electricity to consumers. Demand response has risen as a promising solution to cope with some of the challenges that this shift is creating. In this thesis, control and scheduling studies using demand response, and consumer load models adapted to environments similar to Sweden are proposed and evaluated. The studies use model predictive control approaches for the purpose of providing ancillary and financial services to electricity market actors using thermal flexibility from detached houses. The approaches are evaluated on use-cases using data from Sweden for the purpose of reducing power imbalances of a balance responsible player and congestion management for a system operator. Simulations show promising results for reducing power imbalances by up to 30% and managing daily congestion of 5-19 MW using demand response. Moreover, a consumer load model of an office building is proposed using a gray-box modeling approach combining physical understanding of buildings with empirical data. Furthermore, the proposed consumer load model along with a similar model for detached houses are packaged and made freely available as MATLAB applications for other researchers and stakeholders working with demand response. The applications allow the user to generate synthetic electricity load profiles for heterogeneous populations of detached houses and office buildings down to 1-min resolution. The aim of this thesis has been to summarize and discuss the main highlights of the included articles. The interested reader is encouraged to investigate further details in the second part of the thesis as they provide a more comprehensive account of the studies and models proposed. / <p>QC 20171011</p>

The housing market is one of the most important markets for many economic agents. Large differences in the local market across Sweden suggest regional heterogeneity, however. This study aims to answer if the price and income elasticities of demand for small houses vary between different types of Swedish municipalities. This answer is explored in the light of the central place theory and location theory to see if they follow a hierarchal structure across space. To test this empirically, the 290 municipalities were grouped based on the Swedish Association of Local Authority and Regions’ definitions and tested group-wise using a log-log fixed-effect average hedonic price model using data for 2013-2020. The main findings indicate some differences in the estimates of price and income elasticities between different types of municipalities, but mixing results whether they follow a hierarchal relationship. The conclusions changes depending on which scale one measure, which indicate how local the housing market is.

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Municipal water suppliers are increasingly faced with implementing programs to address temporary water shortages in the United States. Having reliable estimates for the effectiveness of these programs will help in water supply planning. This dissertation estimates the reductions in residential water-use for voluntary and mandatory water-use restrictions used in Virginia during the 2002 drought. These restrictions were evaluated using both a conventional approach (single-dummy variable for each) and non-conventional approach where program intensity was accounted for. Program intensity was measured by information dissemination for voluntary restrictions, and by information dissemination and enforcement efforts for mandatory restrictions. An unbalanced panel with data from 21 municipal water suppliers was used in the analysis. Under the conventional approach, voluntary restrictions had no significant effect on water-use and mandatory restrictions showed a small to moderate effect. However, program intensity was found to have a significant influence on the magnitude of the water-use reductions in the non-conventional approach. These reductions ranged from 0-7% for voluntary restrictions, and from 0-22% for mandatory restrictions. Moreover, these reductions followed a pattern of increasing program effectiveness with higher levels of information and enforcement. This result indicates that water supply planners need to give considerable attention to the manner in which drought management programs are implemented. Price was also found to have an important effect on residential water-use. A moderate price increase of $3 per 1000 gallons would be expected to reduce water-use by almost 15%. Thus combining mandatory restrictions (implemented at high intensity) with a moderate to high price increase could result in water-use savings approaching 40% based on estimates from this analysis. Other important findings included: a) consumers were responding to a mix of pure marginal price and fixed fees/previous block rates, b) apartment accounts were found to be included in most of the localities residential data and had a significant impact on water-use, and c) the income parameter was measuring more than a pure income effect. / Ph. D.

We study the benefits of resource flexibility, considering two different flexibility structures. First, we want to understand the impact of the firm's pricing strategy on its resource investment decision, considering a partially flexible resource. Secondly, we study the benefits of a flexible resource strategic approach, considering a resource flexibility structure that has not been studied in the previous literature. First, we study the capacity investment decision faced by a firm that offers two products/services and that is a price-setter for both products/services. The products offered by the firm are of varying levels (complexities), such that the resources that can be used to produce the higher level product can also be used to produce the lower level one. Although the firm needs to make its capacity investment decision under high demand uncertainty, it can utilize this limited (downward) resource flexibility, in addition to pricing, to more effectively match its supply with demand. Sample applications include a service company, whose technicians are of different capabilities, such that a higher level technician can perform all tasks performed by a lower level technician; a firm that owns a main plant, satisfying both end-product and intermediate-product demand, and a subsidiary, satisfying the intermediate-product demand only. We formulate this decision problem as a two-stage stochastic programming problem with recourse, and characterize the structural properties of the firm's optimal resource investment strategy when resource flexibility and pricing flexibility are considered in the investment decision. We show that the firm's optimal resource investment strategy follows a threshold policy. This structure allows us to understand the impact of coordinated decision-making, when the resource flexibility is taken into account in the investment decision, on the firm's optimal investment strategy, and establish the conditions under which the firm invests in the flexible resource. We also study the impact of demand correlation on the firm's optimal resource investment strategy, and show that it may be optimal for the firm to invest in both flexible and dedicated resources when product demand patterns are perfectly positively correlated. Our results offer managerial principles and insights on the firm's optimal resource investment strategy as well as extend the newsvendor problem with pricing, by allowing for multiple resources (suppliers), multiple products, and resource pooling. Secondly, we study the benefits of a delayed decision making strategy under demand uncertainty, considering a system that satisfies two demand streams with two capacitated and flexible resources. Resource flexibility allows the firm to delay its resource allocation decision to a time when partial information on demands is obtained and demand uncertainty is reduced. We characterize the structure of the firm's optimal delayed resource allocation strategy. This characterization allows us to study how the revenue benefits of the delayed resource allocation strategy depend on demand and capacity parameters, and the length of the selling season. Our study shows that the revenue benefits of this strategy can be significant, especially when demand rates of the different types are close, while resource capacities are much different. Based on our analysis, we provide guidelines on the utilization of such strategies. Finally, we incorporate the uncertainty in demand parameters into our models and study the effectiveness of several delayed capacity allocation mechanisms that utilize the resource flexibility. In particular, we consider that demand forecasts are uncertain at the start of the selling season and are updated using a Bayesian framework as early demand figures are observed. We propose several heuristic capacity allocation policies that are easy to implement as well as a heuristic procedure that relies on a stochastic dynamic programming formulation and perform a numerical study. Our study determines the conditions under which each policy is effective. / Ph. D.

Engine-triggered tasks are real-time tasks that are released when the crankshaft arrives at certain positions in its path of rotation. This makes the rate of release of these jobs a function of the crankshaft's angular speed and acceleration. In addition, several properties of the engine triggered tasks like the execution time and deadlines are dependent on the speed profile of the crankshaft. Such tasks are referred to as adaptive-variable rate (AVR) tasks. Existing methods to calculate the worst-case demand of AVR tasks are either inaccurate or computationally intractable. We propose a method to efficiently calculate the worst-case demand of AVR tasks by transforming the problem into a variant of the knapsack problem. We then propose a framework to systematically narrow down the search space associated with finding the worst-case demand of AVR tasks. Experimental results show that our approach is at least 10 times faster, with an average runtime improvement of 146 times for randomly generated task sets when compared to the state-of-the-art technique. / Master of Science / Real-time systems require temporal correctness along with accuracy. This notion of temporal correctness is achieved by specifying deadlines to each of the tasks. In order to ensure that all the deadlines are met, it is important to know the processor requirement, also known as demand, of a task over a given interval. For some tasks, the demand is not constant, instead it depends on several external factors. For such tasks, it becomes necessary to calculate the worst-case demand. Engine-triggered tasks are activated when the crankshaft in an engine is at certain points in its path of rotation. This makes their activation rate dependent on the angular speed and acceleration of the crankshaft. In addition, several properties of the engine triggered tasks like the execution time and deadlines are dependent on the speed profile of the crankshaft. Such tasks are referred to as adaptive-variable rate (AVR) tasks. Existing methods to calculate the worst-case demand of AVR tasks are either inaccurate or computationally intractable. We propose a method to efficiently calculate the worst-case demand of AVR tasks by transforming the problem into a variant of the knapsack problem. We then propose a framework to systematically narrow down the search space associated with finding the worst-case demand of AVR tasks. Experimental results show that our approach is at least 10 times faster, with an average runtime improvement of 146 times for randomly generated task sets when compared to the state-of-the-art technique.