Two key air pollutants that affect asthma are ozone and particle pollution. Studies show a direct relationship between the number of deaths and hospitalizations for asthma and increases of particulate matter in the air, including dust, soot, fly ash, diesel exhaust particles, smoke, and sulfate aerosols. Cars are found to be a primary contributor to this problem. However, patient awareness of the link is limited. This chapter begins with a general discussion of vehicular dependency or ‘car culture’, and then focuses on the discussion of the effects of air pollution on asthma in the Netherlands. I argue that international organizations and patient organizations have not tended to put pressure on air-control, pollution-control or environmental standards agencies, or the actual polluters. While changes in air quality and the release of greenhouse gases are tied to practices like the massive corporate support for the ongoing use of motor vehicles and the increased prominence of ‘car culture’ globally, patient organizations seem more focused on treating the symptoms rather than addressing the ultimate causes of the disease. Consequently, I argue that to fully address the issue of asthma the international health organizations as well as national health ministries, patient organizations, and the general public must recognize the direct link between vehicular dependency and asthma. The chapter concludes with a recommendation for raising environmental health awareness by explicitly linking the vehicular dependency to the state of poor respiratory health. Strategic policy in the Netherlands then should explicitly link the present pattern of auto mobility to public health. https://onlinelibrary.wiley.com/doi/book/10.1002/9781118786949 LinkedIn: https://www.linkedin.com/in/helenkopnina/
MULTIFILE
AIOSAT - Autonomous Indoor & Outdoor Safety Tracking System
MULTIFILE
In safety science and practice, there have been various safety models, each of them reflecting a particular approach to safety management and accident causality. The large variety of models suggested in literature and applied in practice serve the communication of diverse perspectives towards safety and the need to consider contextual factors, but it does not allow the establishment of a common language within and across organisations and industry sectors. Considering the potential benefits of talking a lingua franca when it comes to safety and inspired by the Standard Model used in particle physics and recent suggestions from relevant studies, we thought of exploring the possibility to introduce a Standard Safety Model (STASAM). As a first step, we focused on four representative safety and accident models widely used, discussed and debated: the Swiss Cheese Model, AcciMap, Functional Resonance Analysis Method (FRAM) and Systems-Theoretic Accident Model and Processes (STAMP). We reviewed literature which compares the particular models, and we listed the strengths and weaknesses of each as a means to set the grounds for the STASAM. The combinations of these models with a focus to host their advantages and avoiding their disadvantages led to a three-level STASAM. The concept STASAM was used in two random incident investigation reports to assess its applicability and visualisation against the original models. The results of the application along with the STASAM concept were reviewed by three safety professionals and three safety researchers. The comments received were in the positive direction and indicated the potential of establishing an inclusive and commonly accepted safety/accident model. The next research phase will be the additional review of the STASAM and its pilot application to a variety of safety events and systems as a means to test its reliability and strengthen its validity.
Size measurement plays an essential role for micro-/nanoparticle characterization and property evaluation. Due to high costs, complex operation or resolution limit, conventional characterization techniques cannot satisfy the growing demand of routine size measurements in various industry sectors and research departments, e.g., pharmaceuticals, nanomaterials and food industry etc. Together with start-up SeeNano and other partners, we will develop a portable compact device to measure particle size based on particle-impact electrochemical sensing technology. The main task in this project is to extend the measurement range for particles with diameters ranging from 20 nm to 20 um and to validate this technology with realistic samples from various application areas. In this project a new electrode chip will be designed and fabricated. It will result in a workable prototype including new UMEs (ultra-micro electrode), showing that particle sizing can be achieved on a compact portable device with full measuring range. Following experimental testing with calibrated particles, a reliable calibration model will be built up for full range measurement. In a further step, samples from partners or potential customers will be tested on the device to evaluate the application feasibility. The results will be validated by high-resolution and mainstream sizing techniques such as scanning electron microscopy (SEM), dynamic light scattering (DLS) and Coulter counter.
Nano and micro polymeric particles (NMPs) are a point of concern by environmentalists and toxicologist for the past years. Their presence has been detected in many environmental bodies and even in more recently human blood as well. One of the most common paths these particles take to enter living organisms is via water consumption. However, despite the efforts of different academic and other knowledge groups, there is no consensus about standards methods which can be used to qualifying and quantifying these particles, especially the submicrometric ones. Many different techniques have been proposed like field flow fractionation (FFF) followed by multi angle laser scattering (MALS), pyrolysis-GC and scanning electron microscopy (SEM). Additionally, the sampling collection and preparation is also considered a difficult step, as such particles are mostly present in very low concentration. Nanocatcher proposes the use of submerged drones as a sampling collection tool to monitor the presence of submicrometric polymeric particles in water bodies. The sample collections will be done using special membrane systems specially designed for the drone. After collected, the samples will be analysed using FFF+MALS, SEM and Py-GC. If proven successful, the use of submerged drones can strongly facilitate sampling and mapping of submicrometric polymeric particles in water bodies and will provide an extensive and comprehensive map of the presence of these particles in such environment.
