Modeling and Control of Passive Chilled Beams with Underfloor Air Distribution of Ventilation in Office Buildings in Humid Climates

This dissertation presents the results of a study to determine the operational control, energy performance and comfort conditions associated with passive chilled beams for office buildings in a humid climate and to develop a method for the modeling of passive chilled beams with a ventilation system and underfloor air distribution (UFAD). For the analysis, a 606,900 ft2 commercial office building in ASHRAE climate zone 3A with passive chilled beams and a ventilation system with UFAD was selected as the case-study building. In the first step, measured data from the building was used to develop a calibrated whole-building energy analysis model in EnergyPlus 8.1. The energy model also implemented methods to model the controls found in a passive chilled beam system with underfloor air distribution. A simplified steady-state energy model was also developed for the validation of the EnergyPlus model and for energy use prediction. In the second step, two methods of optimization for the operational control strategies were tested: a simplified rule-based optimization and a model-based predictive control optimization. The influence of these two approaches to optimization on HVAC energy savings and thermal comfort were found to be within 2% of each other. Finally, summertime stratification measurements were taken in the offices and were combined with a CFD model of a single zone in Star CCM+ 9.04 to establish temperature and airflow profiles in the zones. These comfort studies were conducted for the cooling season only and showed that the thermostat setpoints are not fulfilled in the exterior zones in summer and chilled beam and ventilation system interact with each other and have an adverse effect on the overall system energy efficiency. The results of the research show that if properly controlled, a passive chilled beam system with a parallel ventilation system has the potential for HVAC savings of 14-24% over standard VAV systems in office buildings in humid climates. All of the HVAC energy savings come from fan and reheat energy. Energy savings are affected by latent loads and ventilation requirements in the zones and the potential for the use of an economizer. Indoor humidity levels are also higher with a passive chilled beam system than a standard VAV system. Independent control of the volume of air supplied by the ventilation system and the supply air temperature is necessary to achieve the predicted energy savings. Lastly, the summertime zone comfort studies reveal that the presence of the UFAD ventilation system hinders the natural downward plumes from the chilled beams and the presence of the chilled beam system inhibits stratification in the zones. Because of the lower ventilation flow rates associated with the chilled beams, there is significant increase in the temperatures in the supply plenums

The Ginninderra CH4 and CO2 release experiment: An evaluation of gas detection and quantification techniques

A methane (CH4) and carbon dioxide (CO2) release experiment was held from April to June 2015 at the Ginninderra Controlled Release Facility in Canberra, Australia. The experiment provided an opportunity to compare different emission quantification techniques against a simulated CH4 and CO2 point source release, where the actual release rates were unknown to the participants. Eight quantification techniques were assessed: three tracer ratio techniques (two mobile); backwards Lagrangian stochastic modelling; forwards Lagrangian stochastic modelling; Lagrangian stochastic (LS) footprint modelling; atmospheric tomography using point and using integrated line sensors. The majority of CH4 estimates were within 20% of the actual CH4 release rate (5.8 g/min), with the tracer ratio technique providing the closest estimate to both the CH4 and CO2 release rates (100 g/min). Once the release rate was known, the majority of revised estimates were within 10% of the actual release rate. The study illustrates the power of measuring the emission rate using multiple simultaneous methods and obtaining an ensemble median or mean. An ensemble approach to estimating the CH4 emission rate proved successful with the ensemble median estimate within 16% for the actual release rate for the blind release experiment and within 2% once the release rate was known. The release also provided an opportunity to assess the effectiveness of stationary and mobile ground and aerial CH4 detection technologies. Sensor detection limits and sampling rates were found to be significant limitations for CH4 and CO2 detection. A hyperspectral imager’s capacity to image the CH4 release from 100 m, and a Boreal CH4 laser sensor’s ability to track moving targets suggest the future possibility to map gas plumes using a single laser and mobile aerial reflector

High methylmercury in Arctic and subarctic ponds is related to nutrient levels in the warming eastern Canadian Arctic

Permafrost thaw ponds are ubiquitous in the eastern Canadian Arctic, yet little information exists on their potential as sources of methylmercury (MeHg) to freshwaters. They are microbially active and conducive to methylation of inorganic mercury, and are also affected by Arctic warming. This multiyear study investigated thaw ponds in a discontinuous permafrost region in the Subarctic taiga (Kuujjuarapik-Whapmagoostui, QC) and a continuous permafrost region in the Arctic tundra (Bylot Island, NU). MeHg concentrations in thaw ponds were well above levels measured in most freshwater ecosystems in the Canadian Arctic (>0.1 ng L−1). On Bylot, ice-wedge trough ponds showed significantly higher MeHg (0.3−2.2 ng L−1) than polygonal ponds (0.1−0.3 ng L−1) or lakes (<0.1 ng L−1). High MeHg was measured in the bottom waters of Subarctic thaw ponds near Kuujjuarapik (0.1−3.1 ng L−1). High water MeHg concentrations in thaw ponds were strongly correlated with variables associated with high inputs of organic matter (DOC, a320, Fe), nutrients (TP, TN), and microbial activity (dissolved CO2 and CH4). Thawing permafrost due to Arctic warming will continue to release nutrients and organic carbon into these systems and increase ponding in some regions, likely stimulating higher water concentrations of MeHg. Greater hydrological connectivity from permafrost thawing may potentially increase transport of MeHg from thaw ponds to neighboring aquatic ecosystems

Pyrosequencing of Bacterial Symbionts within Axinella corrugata Sponges: Diversity and Seasonal Variability

Background: Marine sponge species are of significant interest to many scientific fields including marine ecology, conservation biology, genetics, host-microbe symbiosis and pharmacology. One of the most intriguing aspects of the sponge ‘‘holobiont’’ system is the unique physiology, interaction with microbes from the marine environment and the development of a complex commensal microbial community. However, intraspecific variability and temporal stability of sponge-associated bacterial symbionts remain relatively unknown. Methodology/Principal Findings: We have characterized the bacterial symbiont community biodiversity of seven different individuals of the Caribbean reef sponge Axinella corrugata, from two different Florida reef locations during variable seasons using multiplex 454 pyrosequencing of 16 S rRNA amplicons. Over 265,512 high-quality 16 S rRNA sequences were generated and analyzed. Utilizing versatile bioinformatics methods and analytical software such as the QIIME and CloVR packages, we have identified 9,444 distinct bacterial operational taxonomic units (OTUs). Approximately 65,550 rRNA sequences (24%) could not be matched to bacteria at the class level, and may therefore represent novel taxa. Differentially abundant classes between seasonal Axinella communities included Gammaproteobacteria, Flavobacteria, Alphaproteobacteria, Cyanobacteria, Acidobacter and Nitrospira. Comparisons with a proximal outgroup sponge species (Amphimedon compressa), and the growing sponge symbiont literature, indicate that this study has identified approximately 330 A. corrugata-specific symbiotic OTUs, many of which are related to the sulfur-oxidizing Ectothiorhodospiraceae. This family appeared exclusively within A. corrugata, comprising \u3e34.5% of all sequenced amplicons. Other A. corrugata symbionts such as Deltaproteobacteria, Bdellovibrio, and Thiocystis among many others are described. Conclusions/Significance: Slight shifts in several bacterial taxa were observed between communities sampled during spring and fall seasons. New 16 S rDNA sequences and concomitant identifications greatly expand the microbial community profile for this model reef sponge, and will likely be useful as a baseline for any future comparisons regarding sponge microbial community dynamics

An Artificial Intelligence Dataset for Solar Energy Locations in India

Rapid development of renewable energy sources, particularly solar photovoltaics (PV), is critical to mitigate climate change. As a result, India has set ambitious goals to install 500 gigawatts of solar energy capacity by 2030. Given the large footprint projected to meet renewables energy targets, the potential for land use conflicts over environmental values is high. To expedite development of solar energy, land use planners will need access to up-to-date and accurate geo-spatial information of PV infrastructure. In this work, we developed a spatially explicit machine learning model to map utility-scale solar projects across India using freely available satellite imagery with a mean accuracy of 92%. Our model predictions were validated by human experts to obtain a dataset of 1363 solar PV farms. Using this dataset, we measure the solar footprint across India and quantified the degree of landcover modification associated with the development of PV infrastructure. Our analysis indicates that over 74% of solar development In India was built on landcover types that have natural ecosystem preservation, or agricultural value.Comment: Accepted for publication in Nature Scientific Dat