Performance assessment of NOVA SDS011 low-cost PM sensor in various microenvironments.

Over the last 10 years, as a possible alternative to the conventional approach to air quality monitoring, real-time monitoring systems that use low-cost sensors and sensor platforms have been frequently applied. Generally, the long-term characteristics of low-cost PM sensors and monitoring have not been thoroughly documented except for a few widely used sensors and monitors. This article addresses the laboratory and field validation of three low-cost PM monitors of the same type that use the NOVA SDS011 PM sensor module over a 1-year period. In outdoor environments, we co-located low-cost PM monitors with GRIMM EDM180 monitors at the National Air Quality Monitoring stations. In indoor environments, we co-located them with a Turnkey Osiris PM monitor. Several performance aspects of the PM monitors were examined: operational data coverage, linearity of response, accuracy, precision, and inter-sensor variability. The obtained results show that inter-monitor R values were typically higher than 0.95 regardless of the environment. The tested monitors demonstrate high linearity in comparison with PM10 and PM2.5 concentrations measured in outdoor air with reference-equivalent instrumentation with R2 values ranging from 0.52 up to 0.83. In addition, very good agreement (R2 values ranging from 0.93 up to 0.97) with the gravimetric PM10 and PM2.5 method is obtained in the indoor environment (30 < RH < 70%). High RH (over 70%) negatively affected the PM monitors' response, especially in the case of PM10 concentrations (high overestimation).

Modelling Voluntary General Population Vaccination Strategies during COVID-19 Outbreak: Influence of Disease Prevalence.

A novel statistical model based on a two-layer, contact and information, graph is suggested in order to study the influence of disease prevalence on voluntary general population vaccination during the COVID-19 outbreak. Details about the structure and number of susceptible, infectious, and recovered/vaccinated individuals from the contact layer are simultaneously transferred to the information layer. The ever-growing wealth of information that is becoming available about the COVID virus was modelled at each individual level by a simplified proxy predictor of the amount of disease spread. Each informed individual, a node in a heterogeneous graph, makes a decision about vaccination "motivated" by their benefit. The obtained results showed that disease information type, global or local, has a significant impact on an individual vaccination decision. A number of different scenarios were investigated. The scenarios showed that in the case of the stronger impact of globally broadcasted disease information, individuals tend to vaccinate in larger numbers at the same time when the infection has already spread within the population. If individuals make vaccination decisions based on locally available information, the vaccination rate is uniformly spread during infection outbreak duration. Prioritising elderly population vaccination leads to an increased number of infected cases and a higher reduction in mortality. The developed model accuracy allows the precise targeting of vaccination order depending on the individuals' number of social contacts. Precisely targeted vaccination, combined with pre-existing immunity, and public health measures can limit the infection to isolated hotspots inside the population, as well as significantly delay and lower the infection peak.

On the use of small and cheaper sensors and devices for indicative citizen-based monitoring of respirable particulate matter.

Respirable particulate matter present in outdoor and indoor environments is a health hazard. The particle concentrations can quickly change, with steep gradients on short temporal and spatial scales, and their chemical composition and physical properties vary considerably. Existing networks of aerosol particle measurements consist of limited number of monitoring stations, and mostly aim at assessment of compliance with air quality legislation regulating mass of particles of varying sizes. These networks can now be supplemented using small portable devices with low-cost sensors for assessment of particle mass that may provide higher temporal and spatial resolution if we understand the capabilities and characteristics of the data they provide. This paper overviews typical currently available devices and their characteristics. In addition it is presented original results of measurement and modelling in the aim of one low-cost PM monitor validation.