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Progressive urban density affects city centers especially and results in growing congestion, lack of parking spaces, and increasing environmental costs of transportation, causing increased air pollutant emissions and noise. These phenomena reduce the attractiveness of the city and result in a degradation of the quality of life for its residents. In light of these phenomena, there is a clear need for intelligent management of urban space using new technologies that would be complementary to existing intelligent transportation systems. Expanding information resources obtained from mobile cameras will have a positive impact on increasing the efficiency of transportation management and use of limited space in city centers. It will also have an impact on reducing external transport costs and increasing the quality of logistics services provided in the city. The main aim of the paper is to develop a concept of a transport management system in cities using mobile vision systems mounted on unmanned aerial vehicles. The model will concern the cases of lane occupation by freight vehicles and the analysis of parking spaces in the city in order to improve their management. The results of the developed model will contribute to the automation of the parking space management process and increase the efficiency of the use of city parking space resources.

As the concern with global warming increases causing the need for CO2 reduction, renewable energy is of great interest as it has lower carbon footprint when compared to conventional sources (natural gas, coal, oil and nuclear). Solar energy has been drawing worldwide attention since it can transform sunlight directly into electricity with the use of photovoltaic (PV) cells. However, this technology has some drawbacks that need to be addressed including dust deposition on solar panels, also known as soiling. Soiling can decrease PV panel's efficiency thereby resulting in less energy production. The soiling rates are very site specific and depend on the geographic location of the panels and the climate in that area. The solar panels can be cleaned naturally (by rainfall, snow or wind) or mechanically washed. This thesis addresses the impact of solar panel soiling and washing on the energy production of solar PV plants located at the UNLV campus. The objectives of this project were (a) to evaluate whether rainfall alone, in the desert environment with low rainfall, is sufficient to clean up the solar panels, and, if possible, determine the minimum amount of rainfall necessary to clean up panels.; (b) to examine the efficiency loss caused by soiling using different methods of analyses and (c) to evaluate if panel washing is worthwhile given the cost and the efficiency gain that is obtained by washing. To calculate the efficiency of the panels, a model was developed to generate parameters that were not measured at the site. Panel efficiencies before and after rainfall events were compared to determine the minimum amount of rain necessary to clean the panels. It was found that at least 0.2 inches of rain was needed to partially restore clean-panel efficiency. In Las Vegas, the recurrence periods of different depths rainfall were calculated using data from the past 29 years. It was observed that the 50th percentile recurrence period of a rainfall event with depth of 0.2 inches or higher was approximately 52 days. Student Union: -0.0044%/day, CBC-C: -0.00099%/day, and Dayton Hall: -0.0034%/day The amount of efficiency lost during the dry intervals (periods between rainfall events) was analyzed in three different ways. The average efficiency loss per day during the dry periods varied from -0.000171 % to -0.00533 %, depending on the method used and the building where the panels were located. However, there were some limitations to the calculations. It was not possible to completely isolate the effects of only soiling on the efficiency of the panels. The rate of decline seemed to be also impacted by seasonal effects. To better evaluate the effect of washing, a professional company was hired to wash a set of solar panels located on UNLV's Student Union building. The panels were washed with water with a low concentration of TDS. The power output and the efficiency of those panels were analyzed from before and after the washing. There was a very small efficiency and power increase due to the washing. Therefore, it was concluded that washing in this area is not worthwhile, and that rainfall events in excess of 0.2 inches can adequately restore the efficiency of the panels. If there is a change in cost of energy, washing, water or a great increase in the efficiency of the solar panels, it would be necessary to reevaluate the analysis.

Abstract Building energy performance is often inadequate given design goals. While different types of assessment methods exist, they either do not consider design goals and/or are not general enough to integrate new and innovative energy concepts. Furthermore, existing assessment methods focus mostly on the building and system level while ignoring more detailed data. With the availability and affordability of more detailed measured data, the increased number of measured data points requires a structure to organize these data. This paper presents the Energy Performance Comparison Methodology (EPCM), which enables the identification of performance problems based on a comparison of measured data and simulated data representing design goals. The EPCM is based on an interlinked building object hierarchy that structures the detailed performance data from a spatial and mechanical perspective. This research is developed and tested on multiple case studies that provide real-life context and more generality compared to single case studies.

AbstractClimate change poses new and unique challenges that threaten lives and livelihoods. Given the increasing risks and looming uncertainty of climate change, increasing attention has been directed towards adaptation, or the strategies that enable humanity to persist and thrive through climate change the best it can. Though climate change is a global problem often discussed at the national scale, urban areas are increasingly seen as having a distinct role, and distinctive motivation and capacity, for adaptation. The 12 articles in this special issue explore ways of understanding and addressing climate change impacts on urban areas. Together they reveal young but rapidly growing scholarship on how to measure, and then overcome, challenges of climate change. Two key themes emerge in this issue: 1) that we must identify and then overcome current barriers to urban adaptation and 2) frameworks/metrics are necessary to identify and track adaptation progress in urban settings. Both of these themes point to the power of indicators and other quantitative information to inform priorities and illuminate the pathway forward for adaptation. As climate change is an entirely new challenge, careful measurement that enables investment by private and public parties is necessary to provide efficient outcomes that benefit the greatest number of people.

The effects of exogenous trehalose (Tre) on salt tolerance of pharmaceutical plant Catharanthus roseus and the physiological mechanisms were both investigated in this study. The results showed that the supplement of Tre in saline condition (250 mM NaCl) largely alleviated the inhibitory effects of salinity on plant growth, namely biomass accumulation and total leaf area per plant. In this saline condition, the decreased level of relative water content (RWC) and photosynthetic rate were also greatly rescued by exogenous Tre. This improved performance of plants under high salinity induced by Tre could be partly ascribed to its ability to decrease accumulation of sodium, and increase potassium in leaves. The exogenous Tre led to high levels of fructose, glucose, sucrose and Tre inside the salt-stressed plants during whole the three-week treatment. The major free amino acids such as proline, arginine, threonine and glutamate were also largely elevated in the first two-week course of treatment with Tre in saline solution. It was proposed here that Tre might act as signal to make the salt-stressed plants actively increase internal compatible solutes, including soluble sugars and free amino acids, to control water loss, leaf gas exchange and ionic flow at the onset of salt stress. The application of Tre in saline condition also promoted the accumulation of alkaloids. The regulatory role of Tre in improving salt tolerance was optimal with an exogenous concentration of 10 mM Tre. Larger concentrations of Tre were supra-optimum and adversely affected plant growth.

To understand the effects of physicochemical factors on nitrite transformation by microalgae, a lipid-rich Chlorella with high nitrite tolerance was cultured with 8 mmol/l sodium nitrite as sole nitrogen source under different conditions. The results showed that nitrite transformation was mainly dependent on the metabolic activities of algal cells rather than oxidation of nitrite by dissolved oxygen. Light intensity, temperature, pH, NaHCO3 concentrations, and initial cell densities had significant effects on the rate of nitrite transformation. Single-factor experiments revealed that the optimum conditions for nitrite transformation were light intensity: 300 μmol/m(2); temperature: 30°C; pH: 7-8; NaHCO3 concentration: 2.0 g/l; and initial cell density: 0.15 g/l; and the highest nitrite transformation rate of 1.36 mmol/l/d was achieved. There was a positive correlation between nitrite transformation rate and the growth of Chlorella. The relationship between nitrite transformation rate (mg/l/d) and biomass productivity (g/l/d) could be described by the regression equation y = 61.3x (R(2) = 0.9665), meaning that 61.3 mg N element was assimilated by 1.0 g dry biomass on average, which indicated that the nitrite transformation is a process of consuming nitrite as nitrogen source by Chlorella. The results demonstrated that the Chlorella suspension was able to assimilate nitrite efficiently, which implied the feasibility of using flue gas for mass production of Chlorella without preliminary removal of NOX.

Abstract With promising benefits such as traffic emission reduction, traffic congestion alleviation, and parking problem solving, Electric Vehicle (EV)-sharing systems have attracted large attentions in recent years. Different from other business modes, customers in sharing economy systems are usually price sensitive. Therefore, it is possible to shift the usage of shared EVs through a well-designed Dynamic Pricing Scheme (DPS), with the objective of maximizing the system operator's total profit. In this study, we propose a novel DPS for a large-scale EV-sharing network to address the EV unbalancing issue and satisfy the vehicle-grid-integration (VGI) service based on accurate station-level demand prediction. The proposed DPS is formulated as a complex optimization problem, which includes two Price Adjustment Level (PAL) decision variables for every origin-destination pair of stations. The two PALs are employed to affect the EV-sharing demand and travel time between each station pair, respectively. Physical and operational constraints from both EV demand and VGI service aspects are also included in the proposed model. Two case study are conducted to validate the effectiveness of the proposed method.

Abstract The central role of occupants for achieving energy savings in residential buildings is increasingly recognised. Simulation programmes able to take into account occupant behaviour are considered to be powerful tools for bridging the gap between the predicted and the actual energy consumption for new buildings. Nevertheless, the majority of residential buildings that will constitute the housing stock in 2050 have already been built today, therefore occupant behaviour and building simulation tools need to be fully exploited for supporting the renovation of existing housing stock. The aim of this paper is to explore the role of occupant behaviour modelling in supporting decision-makers dealing with the design of renovation strategies for residential buildings. An Italian multi-family public housing building is assumed as case study to estimate the influence of three dimensions linked with occupant behaviour – management of the thermostat, management of the heating system, variation of building characteristics – on energy heating consumption. The results show that, while the occupant behaviour influences the heating loads up to 1/3 in case of high level of building retrofit, the less the building is renovated, the higher is the behavioural impact in absolute terms of energy reduction. Therefore, in order to be effective, renovation strategies are required to design appropriate informative instruments at an early stage to support behaviour changes towards responsible energy consumption.