Neighborhood-Level Particle Pollution Assessment during the COVID-19 Pandemic via a Novel IoT Solution

In recent years, the concentration levels of various air pollutants have been constantly increasing, primarily due to the high vehicle flow. In 2020, however, severe lockdowns in Greece were imposed to reduce the spread of the COVID-19 pandemic, which led to a rapid reduction in the concentration levels of air pollutants such as PM2.5 and PM10 in the atmosphere. Initially, this paper seeks to identify the correlation between the concentration levels of PM10 and the traffic flow by acquiring data from low-cost IoT devices which were placed in Thessaloniki, Greece, from March to August 2020. The correlation and the linearity between the two parameters were further investigated by applying descriptive analytics, regression techniques, Pearson correlation, and independent T-testing. The obtained results indicate that the concentration levels of PM10 are strongly correlated to the vehicle flow. Therefore, the results hint that the decrease in the vehicle flow could result in improving the quality of environmental air. Finally, the acquired results point out that the temperature and humidity are weakly correlated with the concentration levels of PM10 present in the atmosphere.

Risk assessment of exposure to the Middle Eastern dust storms in Iran

The aims of this study were to i) assess the relationship between COVID-19 cases with PM10 concentration and ii) investigation premature deaths due to cardiovascular (M-CVD) and respiratory (M-RD) diseases in three classification levels (PM10<50 mu g m(-3) in normal days, 50-200 mu g m(-3) in dusty days, and >200 mu g m(-3) in MED storm), by using daily averages of PM10 concentrations. The number of M-CVD and M-RD were estimated by concentration-response model, per 10(5) people during 2017 to 2021. The results showed that 187, 183, 163, 215, and 206 days were observed with the PM10 concentrations lower than 50 mu g m(-3) during 2017 to 2021, and 178, 180, 200, 150, and 149 days were subtotal with exceeding PM10 from the WHO guideline (50 mu g m(-3)), respectively. A positive correlation (r(2)=0.33, p < 0.05) was found to be between the number of COVID-19 cases and PM10 mean concentrations (r = 0.589, p = 0.046). Our findings showed that the highest M-CVD and M-RD were among exposed people at dusty days (50 < PM10 <= 200 mu g m(-3)) in 2019. The total M-CVD and M-RD from 2017 to 2021 were 11.78 and 12.2, 18.25 and 17.4, 22.29 and 23.78, 10.33 and 7.6, 10.37 and 9.95 per 10(5) people, respectively which 31.48% of health effects were related to PM10 concentrations more than 200 mu g m(-3).

Role of air pollutants mediated oxidative stress in respiratory diseases.

Airborne particulate (PM) components from fossil fuel combustion can induce oxidative stress initiated by reactive oxygen species (ROS) that are strongly correlated with airway inflammation and asthma. A valid biomarker of airway inflammation is fractionated exhaled nitric oxide (FENO). The oxidative potential of PM2.5 can be evaluated with the dithiothreitol (DTT) dosage, which represents both ROS chemically produced and intracellular ROS of macrophages. This correlates with quality indicators of the internal environment and ventilation strategies such as dilution and removal of airborne contaminants.

Real-time detection of atmospheric fine particle mass concentration based on laser forward small angle scattering

The level of fine particulate air pollution exposure is positively correlated with the death rate of individuals infected with COVID-19. Monitoring is the first step to prevent fine particulate pollution. The instrument based on light scattering method to detect particle concentration has unparalleled advantages over other instruments due to its rapidity, real-time and low cost. Traditional light scattering instruments are limited by the light absorption and particle properties of particles, and their ability to monitor some particles with strong light absorption is greatly reduced. Moreover, when the measured environment is greatly different from the calibration environment, the measurement results often have large errors. In this research, an instrument is designed to detect the forward scattering of light from small angles of particles. It can monitor the number concentration of particles in the environment in real time in four particle size ranges (PM1, PM2.5, PM4 and PM10) and convert it into the mass concentration of particles. By using the simulated atmospheric smoke box and the standard instrument to conduct a field comparison experiment, the reliability and stability of the measurement results are verified. © 2021 SPIE.