Direct-Contact Air, Gravel, Ground Heat Exchanger in Air Treatment Systems for Cowshed Air Conditioning

This paper describes the analysis of the possibility of use of the direct-contact air, gravel, ground heat exchanger (acronym GAHE), patented at the Wroclaw University of Science and Technology, as a means of improving microclimate parameters in dairy cows’ barns. Different possibilities of introducing GAHE to the standard mechanical ventilation system of cowsheds have been proposed and investigated. Based on literature data, the required air parameters in the barns of dairy cows were determined and discussed. Computer simulations were carried out and the results obtained were compared to the baseline model. Year-round changes in microclimate parameters, especially air temperature, relative humidity, and THI index were investigated. The benefits of GAHE use were indicated. The possible increase in the minimum air volume of ventilation during the winter season and the decrease in the maximum values of this parameter in the summer were presented. Indications were made of the systems where the application of GAHE could be the most beneficial. A further research path has been proposed.

The comparison of vehicle headlamps

The aim of this article is the comparison of vehicle headlamps in terms of pedestrians' visibility at nighttime conditions. The study was designed to gain results, which could serve as a basis for the pedestrian-vehicle accident analysis in terms of visibility during night drive. For this study were used comparable vehicles (same vehicle type and model year) with different headlamps type. Three different headlamps (halogen, xenon and LED headlamps) were used for the analysis. Experiments were carried out under similar conditions (straight road, nighttime, no disturbing factors). During a series of static tests, the vehicle approached at predefined distances to the figurant - pedestrian standing on the right side of the roadway. For the luminance analysis were used Luminance Distribution Analyser LumiDISP - software for analysing the luminance conditions based on evaluation of image data from digital photos.

Sea surface salinity subfootprint variability from a global high-resolution model

Subfootprint variability (SFV) is variability at a spatial scale smaller than the footprint of a sat-ellite, and cannot be resolved by satellite observations. It is important to quantify and understand as it contributes to the error budget for satellite data. The purpose of this study is to estimate the SFV for sea surface salinity (SSS) satellite observations. This is done using a high-resolution (1/48°) numerical model, the MITgcm, from which one year of output has recently become availa-ble. SFV, defined as the weighted standard deviation of SSS within the satellite footprint, was computed from the model for a 2°X2° grid of points for the one model year. We present maps of SFV for 40 and 100 km footprint size, display histograms of its distribution for a range of foot-print sizes and quantify its seasonality. At 100 km (40 km) footprint size, SFV has a mode of 0.06 (0.04). It is found to vary strongly by location and season. It has larger values in western bound-ary and eastern equatorial regions, and a few other areas. SFV has strong variability throughout the year, with generally largest values in the fall season. We also quantify representation error, the degree of mismatch between random samples within a footprint and the footprint average. Our estimates of SFV and representation error can be used in understanding errors in satellite obser-vation of SSS.

PTICE U PROSTORNIM I VREMENSKIM MODELIMA USMENE LIRIKE

The paper shows how human experience of nature influences poetic of oral lyric, more precisely – formation of spatial and temporal models. The functions of birds in these models are determined by their characteristic of flying and singing. Birds have an important role in constructing cosmic notions (axis mundi, hierogamic union, celestial world and master of rain). As ambiguous, birds belong to tame and wild, human and inhuman world. They can easily cross the boundaries in both directions – they arrive from the other world in the human world, and fly away from the human world to the ulterior one. They connect different spheres by their flight or voice – sky and earth, earth and water, mountain, water and field. Birds can equally belong to the far away spaces and the space of home. They mark crucial moments, tem- poral boundaries and intervals within the temporal models, but they are most often associated with morning and magical clean time. On the other hand, the songs model year cycle by the motif of migration of birds. As a part of one’s own and alien world, birds are important part of notion of nature in oral lyric songs.

Assimilation of citizen science data in snowpack modeling using a new snow dataset: Community Snow Observations

In this study, we examine the effectiveness of incorporating citizen science snow depth measurements into the seasonal snow model chain through data assimilation. We also introduce the Community Snow Observations dataset, a citizen science based snow depth measuring campaign. Improvements to model performance are characterized and evaluated using remote sensing datasets, fieldwork, and SNOTEL datasets. After citizen science snow depth measurements were incorporated, improvements to model performance were found in 62 % to 78 % of the simulations, depending on model year. The results suggest that modest measurements from citizen scientists have the potential to improve efforts to model snowpack processes in high mountain environments, with implications for water resource management and process-based snow modeling.

Anticipating land-use impacts of self-driving vehicles in the Austin, Texas, region

This paper used an implementation of the land-use model SILO in Austin, Texas, over a 27-year period with an aim to understand the impacts of the full adoption of self-driving vehicles on the region’s residential land use. SILO was integrated with MATSim for the Austin region. Land-use and travel results were generated for a business-as-usual case (BAU) of 0% self-driving or “autonomous” vehicles (AVs) over the model timeframe versus a scenario in which households’ value of travel time savings (VTTS) was reduced by 50% to reflect the travel-burden reductions of no longer having to drive. A third scenario was also compared and examined against BAU to understand the impacts of rising vehicle occupancy (VO) and/or higher roadway capacities due to dynamic ride-sharing (DRS) options in shared AV (SAV) fleets. Results suggested an 8.1% increase in average work-trip times when VTTS fell by 50% and VO remained unaffected (the 100% AV scenario) and a 33.3% increase in the number of households with “extreme work-trips” (over 1 hour, each way) in the final model year (versus BAU of 0% AVs). When VO was raised to 2.0 and VTTS fell instead by 25% (the “Hi-DRS” SAV scenario), average work-trip times increased by 3.5% and the number of households with “extreme work-trips” increased by 16.4% in the final model year (versus BAU of 0% AVs). The model also predicted 5.3% fewer households and 19.1% more available, developable land in the city of Austin in the 100% AV scenario in the final model year relative to the BAU scenario’s final year, with 5.6% more households and 10.2% less developable land outside the city. In addition, the model results predicted 5.6% fewer households and 62.9% more available developable land in the city of Austin in the Hi-DRS SAV scenario in the final model year relative to the BAU scenario’s final year, with 6.2% more households and 9.9% less developable land outside the city.