Overview
What this section contains
The Data Analysis section gathers the tools for exploring the air-quality data of the city of Catania: the measurements from the monitoring stations and the concentration fields computed by the model over the urban grid. The aim is to observe the spatio-temporal behaviour of the pollutants (NO2, O3, PM10, PM2.5, SO2), relate it to the processes that govern it (photochemistry, volcanic activity of Mt. Etna) and provide the theoretical and statistical background needed to interpret it.
Alongside the exploration tools the section holds two reference pages: the meaning of the quantities that recur across the site, and the regulatory and health reference values against which concentrations are compared. They exist to make the rest readable: a number without its unit, its averaging period and something to compare it with does not yet say anything.
Available tools and how to use them
WebGIS
Interactive map of the domain: monitoring stations and cells of the computational grid. It is the entry point of the analysis: you browse the map, select a cell (or a station) and from there open the time trends of the chosen point.
Time trends
Mean and maximum concentrations for the cell selected in the webGIS. You choose the time basis (annual, monthly or daily) with the dedicated buttons; at the bottom you can compute the NO2/O3 photochemical anticorrelation over a date range, with the Pearson coefficient by hour and month.
Monitoring data
The series measured by the air-quality monitoring stations: time coverage, measured pollutants and data quality. These are the reference observed data for the comparison with the model.
Correlation with volcanic activity
Analysis of the influence of Mt. Etna's degassing (in particular SO2 and particulate matter) on the measured concentrations, with bibliographic references and links to the data sources (ARPA Sicilia).
The quantities involved
What each quantity used across the site actually is: gaseous pollutants, particulate matter and its division by size, meteorological variables (including boundary layer height), land descriptors and satellite measurements, with their units and why they matter.
Reference and limit values
The values against which concentrations are compared: European limits, the Italian decree and the WHO guidelines, each with its averaging period, permitted exceedances and legal nature. Filterable by species, reference and statistic; the map colour scales are derived from them.
Leighton cycle
The equations of the NO–NO2–O3 chemical system (Leighton reaction and photolysis) that explain the observed and expected anticorrelation among the photochemical pollutants.
Statistical background
The meaning of the Pearson correlation coefficient and of the p-value, with an interactive animation showing how they change as r and the sample size vary.
Presentation of results
Summary and presentation of the analysis results.
Technologies to store, read and process the data
- Storage. Data live in a PostgreSQL/PostGIS database: the model output over the urban grid in the hourly-concentration table (per-cell arrays), the hourly station measurements, the pre-computed daily/monthly/annual aggregates and the geometry of the grid cells.
- Reading. Pages query the database through PHP endpoints that return JSON; for the larger series the loading is asynchronous (AJAX) and windowed in time, so as not to download large amounts of data at once.
- Processing and visualisation. Charts are rendered client-side with ECharts, ECharts-GL and Three.js (2D, 3D and WebGL); formulas are typeset with KaTeX. The cartographic component is served by the webGIS stack (QGIS Server, Lizmap, MapProxy, Redis on nginx).
Scientific bibliography
- Aiuppa, A., Bellomo, S., D'Alessandro, W., Ferm, M. & Valenza, M. (2003). Influence of volcanic passive degassing on air quality in the Mt. Etna area. WIT Transactions on Ecology and the Environment, 66. witpress.com
- Queißer, M. et al. (2019). TROPOMI enables high resolution SO2 flux observations from Mt. Etna, Italy, and beyond. Scientific Reports, 9, 957. doi:10.1038/s41598-018-37807-w
- Wasserstein, R.L. & Lazar, N.A. (2016). The ASA Statement on p-Values: Context, Process, and Purpose. The American Statistician, 70(2), 129–133. doi:10.1080/00031305.2016.1154108
- Núñez-Alonso, D., Pérez-Arribas, L.V., Manzoor, S. & Cáceres, J.O. (2019). Statistical Tools for Air Pollution Assessment: Multivariate and Spatial Analysis Studies in the Madrid Region. Journal of Analytical Methods in Chemistry, 2019, 9753927. doi:10.1155/2019/9753927
Keywords: analysis, data, air quality, webGIS, Catania