Older people are often over-represented in morbidity and mortality statistics associated with hot and cold weather, despite remaining mostly indoors. The study “Improving thermal environment of housing for older Australians” focused on assessing the relationships between the indoor environment, building characteristics, thermal comfort and perceived health/wellbeing of older South Australians over a study period that included the warmest summer on record. Our findings showed that indoor temperatures in some of the houses reached above 35 °C. With concerns about energy costs, occupants often use adaptive behaviours to achieve thermal comfort instead of using cooling (or heating), although feeling less satisfied with the thermal environment and perceiving health/wellbeing to worsen at above 28 °C (and below 15 °C). Symptoms experienced during hot weather included tiredness, shortness of breath, sleeplessness and dizziness, with coughs and colds, painful joints, shortness of breath and influenza experienced during cold weather. To express the influence of temperature and humidity on perceived health/wellbeing, a Temperature Humidity Health Index (THHI) was developed for this cohort. A health/wellbeing perception of “very good” is achieved between an 18.4 °C and 24.3 °C indoor operative temperature and a 55% relative humidity. The evidence from this research is used to inform guidelines about maintaining home environments to be conducive to the health/wellbeing of older people. Original publication at MDPI: https://doi.org/10.3390/atmos13010096 © 2022 by the authors. Licensee MDPI.
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Ageing brings about physiological changes that affect people’s thermal sensitivity and thermoregulation. The majority of older Australians prefer to age in place and modifications to the home environment are often required to accommodate the occupants as they age and possibly become frail. However, modifications to aid thermal comfort are not always considered. Using a qualitative approach this study aims to understand the thermal qualities of the existing living environment of older South Australians, their strategies for keeping cool in hot weather and warm in cold weather and to identify existing problems related to planning and house design, and the use of heating and cooling. Data were gathered via seven focus group sessions with 49 older people living in three climate zones in South Australia. The sessions yielded four main themes, namely ‘personal factors’, ‘feeling’, ‘knowing’ and ‘doing’. These themes can be used as a basis to develop information and guidelines for older people in dealing with hot and cold weather. Original publication at MDPI: https://doi.org/10.3390/ijerph16060935 © 2018 by the authors. Licensee MDPI.
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Machine learning models have proven to be reliable methods in classification tasks. However, little research has been conducted on the classification of dwelling characteristics based on smart meter and weather data before. Gaining insights into dwelling characteristics, which comprise of the type of heating system used, the number of inhabitants, and the number of solar panels installed, can be helpful in creating or improving the policies to create new dwellings at nearly zero-energy standard. This paper compares different supervised machine learning algorithms, namely Logistic Regression, Support Vector Machine, K-Nearest Neighbor, and Long-short term memory, and methods used to correctly implement these algorithms. These methods include data pre-processing, model validation, and evaluation. Smart meter data, which was used to train several machine learning algorithms, was provided by Groene Mient. The models that were generated by the algorithms were compared on their performance. The results showed that the Long-short term memory performed the best with 96% accuracy. Cross Validation was used to validate the models, where 80% of the data was used for training purposes and 20% was used for testing purposes. Evaluation metrics were used to produce classification reports, which indicates that the Long-short term memory outperforms the compared models on the evaluation metrics for this specific problem.
Recent research by the renowned Royal Institution of Chartered Surveyors (RICS) shows that more than 2/3 of all CO2 is emitted during the building process and less than 1/3 during use to heat the building and the tap water. Lightweight, local and biobased materials such as biocomposites to replace concrete and fossil based cladding are in the framework of climate change, a necessity for future building. Using plant fiber in polymer composites is especially interesting for construction since natural fibers exhibit comparative good mechanical properties with small specific weight, which defines the potential for lightweight constructions. The use of renewable resources, will affect the ecosystem favorably and the production costs of construction materials could also decrease. However, one disadvantage of natural fibers in plastics is their hydrophilic properties. In construction the materials need to meet special requirements like the resistance against fluctuating weather conditions (Ticoalu et al., 2010). In contrast to synthetic fibers, the natural ones are more moisture- and UV-radiation-sensitive. That may lead to degradation of these materials and a decreasing in quality of products. (Lopez et al., 2006; Mokhothu und John, 2017) Tanatex and NPSP have approached CoE BBE/Avans to assist in a study where fibres impregnated with the (modified) Tanatex products will be used for reinforcement of thermoset biopolymers. The influence of the different Tanatex products on the moisture absorption of natural/cellulosic fibers and the adhesion on the fibers on main composite matrix will be measured. The effect of Tantex products can optimize the bonding reaction between the resin and the fibers in the (bio) composite and result to improved strength and physico-chemical properties of the biocomposite materials. (word count: 270)
Horticulture crops and plants use only a limited part of the solar spectrum for their growth, the photosynthetically active radiation (PAR); even within PAR, different spectral regions have different functionality for plant growth, and so different light spectra are used to influence different properties of the plant, such as leaves, fruiting, longer stems and other plant properties. Artificial lighting, typically with LEDs, has been used to provide these specified spectra per plant, defined by their light recipe. This light is called steering light. While the natural sunlight provides a much more sustainable and abundant form of energy, however, the solar spectrum is not tuned towards specific plant needs. In this project, we capitalize on recent breakthroughs in nanoscience to optimally shape the solar spectrum, and produce a spectrally selective steering light, i.e. convert the energy of the entire solar spectrum into a spectrum most useful for agriculture and plant growth to utilize the sustainable solar energy to its fullest, and save on artificial lighting and electricity. We will take advantage of the developed light recipes and create a sustainable alternative to LED steering light, using nanomaterials to optimally shape the natural sunlight spectrum, while maintaining the increased yields. As a proof of concept, we are targeting the compactness of ornamental plants and seek to steer the plants’ growth to reduce leaf extension and thus be more valuable. To realize this project the Peter Schall group at the UvA leads this effort together with the university spinout, SolarFoil, whose expertise lies in the development of spectral conversion layers for horticulture. Renolit - a plastic manufacturer and Chemtrix, expert in flow synthesis, provide expertise and technical support to scale the foil, while Ludvig-Svensson, a pioneer in greenhouse climate screens, provides the desired light specifications and tests the foil in a controlled setting.
E-cycling intelligence is a research project directly connected to the PhD-research of Joost de Kruijf at the Utrecht University. Within the program the effects of the introduction of e-bikes in daily commuting are being investigated. Using a large-scale incentive program targeting on behavioral change among car-oriented commuters the next four specific components are being :- Modal shift to e-cycling- Well-being and travel satisfaction of e-bikes vs. car- Weather circumstances and e-cycling- Behavioral intention to e-bike vs. actual behavior Using a combination of three surveys (baseline, one month and half a year) and continuous GPS-measurement on the behavior of more than 800 participants makes this research unique. In collaboration with the TU/e the GPS-dataset is being translated into relevant information on modal shift on different trip purposes offering a new range of possibilities to analyses behavioral change. Knowledge on every of the four topics in the project is translated scientific paper. The expected end of the project is July 2021.With the research not new insights are being gained, the Breda University of Applied Sciences also develops a scientific network of cycling related researchers together with a network of cycling engaged road authorities.
