ALBERT

Description: Limited information about exposure to volatile organic compounds (VOCs) in primary schools in Vietnam is available. In this study, we aimed to characterize indoor VOCs in four primary schools situated in Ho Chi Minh City, a metropolis in the south of Vietnam and assess health risks linked to the students’ exposure to VOCs. Indoor and outdoor air samples were collected in the schools and analyzed for volatile composition using gas chromatography coupled with mass spectrometry. Different classes of VOCs, including aromatic hydrocarbons, alkanes, aldehydes, esters, cyclic terpenes, and chlorinated hydrocarbons, were identified and quantified in classrooms of the schools. The results showed that the concentrations of the VOCs differed significantly among the schools and between ground-floor and first floor classrooms. In addition, VOC profiles differed considerably between air-conditioned and non-air-conditioned classrooms. Limonene, a compound associated with fragrance products, was the most abundant VOC, with the median (range) concentration of 26.12 (10.29, 50.08) μg/m3. The concentrations of the compounds examined in the study were in general found to be higher indoors compared with outdoors, signifying indoor emission sources. Potential harmful effects are expected as a result of exposure to benzene, ethylbenzene, naphthalene, 1,4-dichlorobenzene and tetrachloroethylene in the investigated schools. Further research is needed to fully assess the health risks to students, teachers, and staff in these educational environments.

Description: Smart home automation is expected to improve living standards with the evolution of internet of things (IoT) that facilitate the remote control of residential appliances. There are, however, several factors that require attention for broader successful consumer adoption. This paper focusses on three key barriers: (i) different underlying technologies requiring an integrated voice-based control for ease of use, (ii) lack of trust due to security and privacy concerns, and (iii) unawareness of the use of machine intelligence by users for exploiting the full potential of smartness. Voice-controlled home environments are possible with cloud-based solutions that are being deployed commercially. However, there are drawbacks due to non-standard voice channels and commands with delays in meeting the required response time for real-time services. Adoption is also required to meet with the expected goals of simplicity, security, and integration. To address these barriers, we propose a model integrating IoT services and wireless technologies for developing a secure smart home automation with a voice-controlled artificial intelligence system. We demonstrate the model’s application in a variety of practical use cases, by implementing a secure and smart voice-based system for an integrated control of several home devices seamlessly.

Description: Global climatic changes have been observed for all natural biomes, with the greatest impact in the permafrost zone. The short series of direct observations of air temperature and precipitation from meteorological stations for this territory make it difficult to use them in studies of the impact of climate change on forest and forest-tundra ecosystems, but only longer series of gridded data expand the temporal-spatial resolution of this analysis. We compared local and gridded air temperature, precipitation and vapor pressure deficit (VPD) data, analyzed the trends of their changes over the last century for three sites in the permafrost zone (YAK and TAY in Russia, and CAN in Canada), and estimated the effect of their variability on oxygen isotopes in the tree-ring cellulose (δ18Ocell) of three different species (Larix cajanderi Mayr, Larix gmelinii Rupr. Rupr and Piceaglauca (Moench) Voss). Climate trend analysis showed strong changes after the 1980s, and even more pronounced from 2000 to 2020. We revealed that δ18Ocell-YAK showed mixed signals of the July temperature (r = 0.49; p = 0.001), precipitation (r = −0.37; p = 0.02) and vapor pressure deficit (VPD) (r = 0.31; p = 0.02), while δ18Ocell-CAN captured longer March–May (r = 0.37, p = 0.001) and July (r = 0.32, p 〈 0.05) temperature signals as well as spring VPD (r = 0.54, p = 0.001). The δ18Ocell-TAY showed a significant correlation with air temperature in July (r = 0.23, p = 0.04) and VPD in March (r = −0.26, p = 0.03). The obtained eco-hydrological relationships indicate the importance of temperature and moisture to varying degrees, which can be explained by site- and species-specific differences.

Description: The direct aerosol-radiative effects in the WRF-Chem model account for scattering/absorption of solar radiation due to aerosols, while aerosol–cloud interactions result in modifying wet scavenging of the ambient concentrations as an indirect aerosol effect. In this study, impact of aerosol on meteorological parameters, PM10 and ozone concentrations are analysed which revealed (i) that a net decrease in shortwave and longwave radiation by direct feedback results in decrease in temperature up to 0.05 K, (ii) that a net increase due to longwave and shortwave radiation when both direct and indirect effects are taken together results in an increase in temperature up to 0.25 K (where the mean of temperature is 33.5 °C and standard deviation 2.13 °C), (iii) a marginal increase in boundary layer height of 50 m with increase in temperature with feedbacks, (iv) overall net increase in radiation by direct and indirect effect together result in an increase in PM10 concentration up to 12 μg m−3 (with PM10 mean as 84.5 μg m−3 and standard deviation 28 μg m−3) and an increase in ozone concentration up to 3 μg m−3 (with ozone mean as 29.65 μg m−3 and standard deviation 5.2 μg m−3) mainly due to net increase in temperature. Furthermore, impact of sensitivity of different aerosol mechanisms on PM10 concentrations was scrutinized for two different mechanisms that revealed underestimation by both of the mechanisms with MOSAIC scheme, showing less fractional bias than MADE/SORGAM. For the dust storm period, MOSAIC scheme simulated higher mass concentrations than MADE/SORGAM scheme and performed well for dust-storm days while closely capturing the peaks of high dust concentrations. This study is one of the first few to demonstrate the impact of both direct and indirect aerosol feedback on local meteorology and air quality using a meteorology–chemistry modelling framework; the WRF-Chem model in a tropical urban airshed in India located in semi-arid climatic zone. It is inferred that semi-arid climatic conditions behave in a vastly different manner than other climatic zones for direct and indirect radiative feedback effects.

Description: With cities reinforcing greener ways of urban mobility, encouraging urban cycling helps to reduce the number of motorized vehicles on the streets. However, that also leads to a significant increase in the number of bicycles in urban areas, making the question of planning the cycling infrastructure an important topic. In this paper, we introduce a new method for analyzing the demand for bicycle parking facilities in urban areas based on object detection of social media images. We use a subset of the YFCC100m dataset, a collection of posts from the social media platform Flickr, and utilize a state-of-the-art object detection algorithm to detect and classify moving and parked bicycles in the city of Dresden, Germany. We were able to retrieve the vast majority of bicycles while generating few false positives and classify them as either moving or stationary. We then conducted a case study in which we compare areas with a high density of parked bicycles with the number of currently available parking spots in the same areas and identify potential locations where new bicycle parking facilities can be introduced. With the results of the case study, we show that our approach is a useful additional data source for urban bicycle infrastructure planning because it provides information that is otherwise hard to obtain.

Description: Building typification is of theoretical interest and practical significance in map generalization. It aims to transform an initial set of buildings to a subset, while maintaining the essential distribution characteristics and important individual buildings. This study focuses on buildings located in residential suburban or rural areas and generalizes them to medium or small scale, for which the typification process can be viewed as point-similar object selection that generates exemplars in local building clusters. From this view, we propose a novel building typification approach using affinity propagation exemplar-based clustering. Based on a sparse graph constructed on the input building set, the proposed approach considers all buildings as potential cluster exemplars and keeps passing messages between those objects; thus, high-quality representative objects (i.e., exemplars) of the initial building set can be obtained and further outputted as the typified result. Experiments with real-life building data show that the proposed method is superior to the two existing representative methods in maintaining the overall distribution characteristics. Meanwhile, the importance of each individual building and the constraints of the road network can be embedded flexibly in this method, which gives some advantages in terms of preserving important buildings and the local structural distribution along the road, etc.

Description: The long-term sustainability of fractures within rocks determines whether it is reasonable to utilize such formations as potential EGS reservoirs. Representative for reservoirs in Variscan metamorphic rocks, three long-term (one month each) fracture permeability experiments on saw-cut slate core samples from the Hahnenklee well (Harz Mountains, Germany) were performed. The purpose was to investigate fracture permeability evolution at temperatures up to 90 °C using both deionized water (DI) and a 0.5 M NaCl solution as the pore fluid. Flow with DI resulted in a fracture permeability decline that is more pronounced at 90 °C, but permeability slightly increased with the NaCl fluid. Microstructural observations and analyses of the effluent composition suggest that fracture permeability evolution is governed by an interplay of free-face dissolution and pressure solution. It is concluded that newly introduced fractures may be subject to a certain permeability reduction due to pressure solution that is unlikely to be mitigated. However, long-term fracture permeability may be sustainable or even increase by free-face dissolution when the injection fluid possesses a certain (NaCl) salinity.

Description: A census of endangered plant populations is critical to determining their size, spatial distribution, and geographical extent. Traditional, on-the-ground methods for collecting census data are labor-intensive, time-consuming, and expensive. Use of drone imagery coupled with application of rapidly advancing deep learning technology could greatly reduce the effort and cost of collecting and analyzing population-level data across relatively large areas. We used a customization of the YOLOv5 object detection model to identify and count individual dwarf bear poppy (Arctomecon humilis) plants in drone imagery obtained at 40 m altitude. We compared human-based and model-based detection at 40 m on n = 11 test plots for two areas that differed in image quality. The model out-performed human visual poppy detection for precision and recall, and was 1100× faster at inference/evaluation on the test plots. Model inference precision was 0.83, and recall was 0.74, while human evaluation resulted in precision of 0.67, and recall of 0.71. Both model and human performance were better in the area with higher-quality imagery, suggesting that image quality is a primary factor limiting model performance. Evaluation of drone-based census imagery from the 255 ha Webb Hill population with our customized YOLOv5 model was completed in

Description: The scarcity of surface water resources in the dry season in the Kilinochchi district increases the demand for freshwater. Therefore, the main objective of this study is to delineate potential groundwater zones in Kilinochchi, Sri Lanka, using integrated remote sensing (RS), geographic information systems (GIS) and the analytical hierarchy process (AHP). Groundwater potential zones are demarcated for the Kilinochchi district by overlaying thematic layers: geology, geomorphology, land use/land cover, soil types, drainage density, slope, lineament, and rainfall. The thematic layers were integrated into a geographic information system, and a weighted overlay analysis was carried out to delineate groundwater zones. Thus the resultant map is categorized into five different potential zones: very low (59.12 km2), low (207.78 km2), moderate (309.89 km2), high (507.74 km2), and very high (111.26 km2). The groundwater potential map was validated with the existing seventy-nine wells, which indicated a good prediction accuracy of 81.8%. This suggests that the results obtained by integrating RS-GIS and AHP are well-matched with the existing well water depth. The AHP approach based on RS-GIS was a handy and efficient technique for assessing potential groundwater zones. This research will help policymakers better manage the Kilinochchi district’s groundwater resources and give scope for further research into groundwater exploration in the area.

Description: Collophane is difficult to upgrade by reverse flotation of quartz with amine collector alone due to its low grade, complex structure, fine dissemination grain size, etc. This investigation was conducted to explore the synergistic effect of dibutyl phthalate (DBP) as a surfactant with cetyltrimethyl ammonium bromide (CTAB) as the collector on the separation of quartz from collophane by means of micro-flotation tests, surface tension and aggregate size measurements, and froth water mass fraction/recovery characterization. It was found that DBP reduced the surface tension of the reagent solution and enhanced the collision probability between bubbles and quartz particles by increasing the size of aggregates through increased hydrophobic interaction between the quartz particles and DBP droplets. The addition of DBP reduced the entrainment of fine collophane particles as a result of improved defoaming and increased the flotation recovery of quartz without resulting in any flotation of collophane at dosages lower than 200 mg/L. Flotation test results with the binary artificial mineral mixture showed that DBP improved the P2O5 recovery, SiO2 rejection, and P2O5 grade by up to 7%, 12%, and 1%, respectively.