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Abstract For 118 million residential housing units in the U.S., there is currently a gap between the potential energy savings that can be achieved through the use of existing energy efficiency technologies, and the actual level of energy savings realized, particularly for the 37% of housing units that are considered residential rental properties. Additional quantifiable benefits are needed beyond energy savings to help further motivate residential property owners to invest in energy efficiency upgrades. This research focuses on assessing the adoption of energy efficient upgrades in U.S. residential housing and the impact on rental prices. Ten U.S. cities are chosen for analysis; these cities vary in size across multiple climate zones, and represent a diverse set of housing market conditions. Data was collected for over 159,000 rental property listings, their characteristics, and their energy efficiency measures listed in rental housing postings across each city. Following an extensive data quality control process, over thirty different types energy efficient features were identified. The level of adoption was determined for each city, ranging from 5.3% to 21.6%. Efficient lighting and appliances were among the most common, with many features doubling as energy efficient and other desirable aesthetic or comfort improvements. Then using propensity score matching and conditional mean comparison methods, the relative impact on rent charged in each city was calculated, which ranged from a 6% to 14.1% increase in rent for properties with energy efficient features, demonstrating a positive economic impact of these features, particularly for property owners. This was further subdivided into five types of energy efficiency upgrade and three housing types. Single family homes generally demanded higher premiums with energy efficient features, however there was not a consistent pattern across the types of efficient upgrades. The results of this work demonstrate that investment in energy efficient technologies has quantifiable benefits for rental property owners in the U.S. beyond just energy savings. This methodology and results can also be used in other cities and by property owners, utility companies, or others, ultimately encouraging further investment and positive economic impact in residential energy efficiency and in turn improving energy and resource conservation in the building sector.

Different species within the same community may exhibit distinct phenological responses to climate change, so it is necessary to study species differences in the green-up date among abundant species within a wide area, and a suitable phenology model should be introduced to explain the associated climate-driven mechanism. Although various models have been developed, very few studies have aimed to compare their efficiency and robustness, and the relative contributions of climate driving factors have not been sufficiently examined. We analyzed phenology data for 12 species across 17 stations in Inner Mongolia and found that essential spatiotemporal and interspecies differences existed in the green-up date. Five process-based models were established for each species and their performance was comprehensively evaluated. The two-phase models (sequential model, parallel model, unified model and unified model combined with precipitation driving) generally performed better than the one-phase model (thermal time model), and the model considering precipitation performed the best, which indicates that it is necessary to introduce the chilling effect and precipitation driving effect to improve the model accuracy in arid environments. We proposed a method to estimate the contribution rates of various climate driving factors, and significant differences in the relative demand for the various climate driving factors among different species were clearly revealed. The results indicated that for natural vegetation in Inner Mongolia, the need for the chilling and temperature driving is relatively high, and the precipitation driving is very important for herbaceous vegetation, which leads to considerable spatial and interspecies differences in green-up date. We demonstrated the feasibility of quantitatively evaluating the contributions of different climate driving factors with a process-based model, and the contradiction in phenological changes among different studies may eventually be clarified.

The development of advanced computational models for improving the accuracy of streamflow forecasting could save time and cost for sustainable water resource management. In this study, a locally weighted learning (LWL) algorithm is combined with the Additive Regression (AR), Bagging (BG), Dagging (DG), Random Subspace (RS), and Rotation Forest (RF) ensemble techniques for the streamflow forecasting in the Jhelum Catchment, Pakistan. To build the models, we grouped the initial parameters into four different scenarios (M1–M4) of input data with a five-fold cross-validation (I–V) approach. To evaluate the accuracy of the developed ensemble models, previous lagged values of streamflow were used as inputs whereas the cross-validation technique and periodicity input were used to examine prediction accuracy on the basis of root correlation coefficient (R), root mean squared error (RMSE), mean absolute error (MAE), relative absolute error (RAE), and root relative squared error (RRSE). The results showed that the incorporation of periodicity (i.e., MN) as an additional input variable considerably improved both the training performance and predictive performance of the models. A comparison between the results obtained from the input combinations III and IV revealed a significant performance improvement. The cross-validation revealed that the dataset M3 provided more accurate results compared to the other datasets. While all the ensemble models successfully outperformed the standalone LWL model, the ensemble LWL-AR model was identified as the best model. Our study demonstrated that the ensemble modeling approach is a robust and promising alternative to the single forecasting of streamflow that should be further investigated with different datasets from other regions around the world.

We present the first calculations to follow the evolution of all stable isotopes (and their abundant radioactive progenitors) in a finely zoned stellar model computed from the onset of central hydrogen burning through explosion as a Type II supernova. The calculations were performed for a 15 solar mass Pop I star using the most recently available set of experimental and theoretical nuclear data, revised opacity tables, and taking into account mass loss due to stellar winds. We find the approximately solar production of proton-rich isotopes above a mass number of A=120 due to the gamma-process. We also find a weak s-process, which along with the gamma-process and explosive helium and carbon burning, produces nearly solar abundances of almost all nuclei from A=60 to 85. A few modifications of the abundances of heavy nuclei above mass 90 by the s-process are also noted and discussed. New weak rates lead to significant alteration of the properties of the presupernova core. 10 pages, 4 figures, Nuclear Astrophysics X Workshop proceedings

Abstract Large-scale cultivation of microalgal biomass in open systems can benefit from the low cost of using natural sunlight, as opposed to artificial light, but may encounter problems with photoinhibition, high evaporation rates, potential contamination and high energy demand. Wavelength selective luminescent solar concentrator (LSC) panels can solve some of these problems when incorporated into low-cost sheltered structures for algal biomass production that concurrently produce their own electricity by harnessing select portions of solar energy, not used for algal growth. The LSC panels in this study contained a fluorescent dye, Lumogen Red 305, which transmits blue and red wavelengths used for photosynthesis with high efficiency, while absorbing the green wavelengths and re-emitting them as red wavelengths. The fluorescently generated red wavelengths are either transmitted to boost algal growth, or waveguided and captured by photovoltaic cells to be converted into electricity. We found that different strains of microalgae (currently used commercially) grew equally well under the altered spectral conditions created by the luminescent panels, compared to growth under the full solar spectrum. Thus this technology presents a new approach wherein algae can be grown under protected, controlled conditions, while the cost of operations is offset by the structure's internal electrical production, without any loss to algal growth rate or achievable biomass density.

Summary Monitoring of microbial corrosion is always difficult because of the sessile nature of bacteria and the lack of meaningful correlation between routine bacteria counts and bacterial activity. This problem is further aggravated in a large oilfield water system because of size and sampling difficulties. This paper discusses some monitoring techniques currently used in the oil industry, their limitations, and possible areas for improvement. These improved techniques are in use or will be implemented in the Aramco systems. Introduction Microbial corrosion has caused some failures in seawater injection systems. Whether or not microbial corrosion represents a major corrosion mechanism in the oilfield water system is a controversial question. However, it has certainly become a major concern in recent years. There are two approaches in dealing with microbial corrosion problems in a large oilfield water system. One approach is to start treating the system with bactericide in conjunction with regular scraping when the system is commissioned. The other is to treat the system only when an impending microbial-related problem is clearly defined. in either case, monitoring of microbial corrosion is essential. The first approach is more or less a precautionary measure. The treatment and selection of bactericides is usually based on past experience and laboratory evaluation tests. While the treatment is being implemented, a reliable monitoring program could assess the effectiveness of the current program of microbial corrosion control. In the second case, monitoring of microbial corrosion is even more important. it would provide timely information toward implementation of a treatment program before the system could get out of control. The industry's awareness of microbial corrosion has been indicated by the number of papers published in recent years on this subject. These articles cover a wide spectrum of interest from fundamental corrosion mechanisms to case studies, detection methods, control measures, etc. Although it is not clear to what extent microorganisms are responsible for the observed field corrosion failures, the general consensus still favors early establishment of a routine microbial corrosion monitoring program. The best approach seems to he the establishment of solid baseline data for the system after which any significant future deviation can be interpreted as a sign of a potential problem. The following sections describe the current methods used for routine monitoring, specifically for Aramco's large oilfield water systems. The limitations of these methods, the difficulties encountered, and some suggested studies for modification and improvement are discussed also. Current Monitoring Methods The methods currently used by Aramco can be categorized as (l) cell counts in water, (2) metal surface examination, (3) scraping solids analysis, (4) water quality analysis, and (5) evaluation of current bactericide treatment. Cell Counts in Water. These are used to detect bacterial organisms and their concentrations. it is recognized that confirmation of free-flowing bacteria in the water does not automatically mean trouble. However, if bacteria counts demonstrate a definite increase across the system, or over a period of time, the odds are that bacteria are active and working on the metal somewhere in the system. Cell counts routinely monitored include sulfate-reducing bacteria (SRB), general aerobic bacteria (OAB), iron bacteria, and others. SRB are widely recognized to he primarily responsible for bacteria-induced corrosion in an anaerobic environment. Depending on the nature of the sample to be tested and the types of problems encountered (or expected) in the field, one or several different enumeration techniques are employed. For field work, the method generally used by Aramco is culturing of samples in liquid growth media specifically designed for detecting a certain group of organisms. These laboratory media are prepared using the appropriate field water as a base, with addition of general growth nutrients for the organisms. The use of field water to prepare the media provides a water composition similar to that in which the bacteria originated. The media are supplemented with other ingredients to create an environment conducive to growth of certain bacteria (e.g., certain reducing agents have to he added into the SRB media). The media then are dispensed into serum vials at exactly 9 mL [9 cm3] each and sealed with rubber stoppers and aluminum seals. JPT P. 1171

An experimental study on the flow and heat transfer in open vertical enclosures, representing elevator shafts, warehouses, and atriums, due to a building fire is carried out, using a scale model. Smoke and hot gases are injected into the enclosure at a lower opening and the resulting downstream flow and temperature fields are studied. The inlet temperature and flow rate of the hot gases are varied over wide ranges to simulate the flow due to fire in multi-leveled buildings with vertical open shafts or atriums under natural ventilation. The conditions at the outlet, which is located on the same wall as the inlet, are also monitored to determine the effects of entrainment into the flow and heat transfer to the walls. Typical values of the operating conditions have been investigated, ranging from high buoyancy levels, for which the flow stays close to the vertical wall of the enclosure, to much lower levels, at which the flow enters the enclosure with a significant flow velocity and spreads outward very quickly. With increasing temperature at the inlet, the buoyancy effect is larger, resulting in higher velocities and shorter time to reach the top. The measured temperature at the outlet depends on heat transfer to the walls as well as on the flow velocity. Detailed measurements of the velocity and temperature fields have also been taken. It is found that a wall plume is generated which conveys the hot fluid rapidly along the vertical wall containing the inlet and the outlet. A recirculating flow arises away from this wall and this flow affects the heat transfer and flow in the wall plume. This feature, in turn, affects the entrainment into the flow, decay of the temperature level and the evolution of mean flow. Therefore, horizontally uniform conditions cannot be assumed here, as employed in several studies of tall enclosures. The wall plume has to be modeled in this case, considering the entrainment into the boundary layer flow and the effect of the recirculating flow.

The cover of a disposal cell is an important element in the long-term stability of a reclaimed uranium tailings site. The cover is generally comprised of a radon barrier, filter, and surface erosion barrier. A study is conducted to investigate the drainage and erosion potential between the filter and radon barrier layer in response to surface water flows over a layer of riprap. A cover system is physically modeled in a hydraulics laboratory. The experimental program evaluated the interstitial velocity potential through four filters, the erosion and sediment transport potential from the radon barrier, and the filter drainage rate after passage of the surface runoff hydrograph. The results indicated that the use of traditional filter criteria to bed riprap is extremely conservative and restricts drainage. The grain size of the filter materials should be increased to enhance drainage when placed on flat (\IS\N ≤\N 5%) slopes. A relationship is presented for estimating the drainage velocity potential through a filter layer as a function of slope and gradation. A new filter criteria should be developed for overtopping flow conditions.

Abstract Electricity markets in Europe become increasingly interconnected due to new grid connections and market coupling regulations. This paper examines the interdependencies between the Swiss electricity market and those of neighbouring countries. The Swiss market serves as a good example for a smaller electricity market which is increasingly affected by developments in the large neighbouring countries. To study these cross-border effects, especially those on Swiss electricity prices, we apply two different methodologies, an econometric and a Nash-Cournot equilibrium model. The analyses show that the Swiss electricity price correlates strongly with the German electricity price in the summer, but tends to follow the French electricity price in the winter. Another finding is that gas prices and the electricity load of neighbouring countries have a significant influence on prices. In particular, the load of France and Italy is driving up Swiss prices in the winter, while the German electricity demand and renewable energy generation have a larger influence on Swiss prices in the summer.