Promoting Pollution-Free Routes in Smart Cities Using Air Quality Sensor Networks.

Nowadays, citizens have a huge concern about the quality of life in their cities, especially regarding the level of pollution. Air quality level is of great importance, not only to plan our activities but also to take precautionary measures for our health. All levels of governments are concerned about it and have built their indexes to measure the air quality level in their countries, regions or cities. Taking into account the existing sensor infrastructure within smart cities, it makes possible to evaluate these indices and to know anywhere the level of pollution in real-time. In this scenario, the main objective of the current work is to foster citizens' awareness about pollution by offering pollution-free routes. To achieve this goal, a technology-agnostic methodology is presented, which allows for creating pollution-free routes across cities depending on the level of pollution in each zone. The current work includes an extensive study of existing air quality indices, and proposes and carries forward to deployment of the defined methodology in a big city, such as Madrid (Spain).

Impact of Lockdown on Air Quality in the Most Polluted Cities of India.

Background: COVID-19 has become a global pandemic, prompting lockdowns in practically every country. To prevent the spread of the disease, India has enforced a rigorous nationwide lockdown that commenced in March 2020. The lockdown imposed amid the pandemic ensured that most commercial activities and vehicle transportation ceased, resulting in a significant reduction in air pollution levels. Material and Methods: The value of air pollutants PM10, PM2.5, NO2, and SO2 from January to May 2020 was obtained from the Indian Central Pollution Control Board. Before lockdown and during lockdown, relative fluctuations in ambient concentrations of four air contaminants were investigated. The Box-Jenkins approach was used to estimate future air pollution data points using time series data analysis. Results: The PM10 level reduced by 61%, 30%, 68%, 37%, and 43% in the selected cities, respectively. Comparison of other pollutant concentrations before and after the lockdown also found a reduction in ambient pollutant concentrations, resulting in improved air quality. Inference of predicted model values to observed values revealed a significant increase in the concentrations of all pollutants. The percentage increases in AQImean from predicted to observed values were 206% in Ghaziabad, 148% in Delhi, 59% in Hyderabad, and 160% in Cochin. Conclusion: The strict lockdown has resulted in a significant drop in air pollutant levels. Upgrading present technologies could help keep pollution to a minimum of 37% under control. The findings would prompt the government to consider how to strictly reduce vehicle and industrial pollution to improve air quality and maintain improved public health.

Monitoring of air pollution levels related to Charilaos Trikoupis Bridge.

Charilaos Trikoupis bridge is the longest cable bridge in Europe that connects Western Greece with the rest of the country. In this study, six air pollution monitoring campaigns (including major regulated air pollutants) were carried out from 2013 to 2015 at both sides of the bridge, located in the urban areas of Rio and Antirrio respectively. Pollution data were statistically analyzed and air quality was characterized using US and European air quality indices. From the overall campaign, it was found that air pollution levels were below the respective regulatory thresholds, but once at the site of Antirrio (26.4 and 52.2µg/m3 for PM2.5 and ΡΜ10, respectively) during the 2nd winter period. Daily average PM10 and PM2.5 levels from two monitoring sites were well correlated to gaseous pollutant (CO, NO, NO2, NOx and SO2) levels, meteorological parameters and factor scores from Positive Matrix Factorization during the 3-year period. Moreover, the elemental composition of PM10 and PM2.5 was used for source apportionment. That analysis revealed that major emission sources were sulfates, mineral dust, biomass burning, sea salt, traffic and shipping emissions for PM10 and PM2.5, for both Rio and Antirrio. Seasonal variation indicates that sulfates, mineral dust and traffic emissions increased during the warm season of the year, while biomass burning become the dominant during the cold season. Overall, the contribution of the Charilaos Trikoupis bridge to the vicinity air pollution is very low. This is the result of the relatively low daily traffic volume (~10,000 vehicles per day), the respective traffic fleet composition (~81% of the traffic fleet are private vehicles) and the speed limit (80km/h) which does not favor traffic emissions. In addition, the strong and frequent winds further contribute to the rapid dispersion of the emitted pollutants.

A model-based framework for air quality indices and population risk evaluation, with an application to the analysis of Scottish air quality data.

The paper is devoted to the development of a statistical framework for air quality assessment at the country level and for the evaluation of the ambient population exposure and risk with respect to airborne pollutants. The framework is based on a multivariate space-time model and on aggregated indices defined at different levels of aggregation in space and time. The indices are evaluated, uncertainty included, by considering both the model outputs and the information on the population spatial distribution. The framework is applied to the analysis of air quality data for Scotland for 2009 referring to European and Scottish air quality legislation.