Urban air quality monitoring at high spatial resolution by diffusive sampling.

15 Luglio 2019

High spatial resolution monitoring using diffusive samplers allows studying the urban pollutant distribution, thus enabling deeper investigation of their generation and diffusion mechanisms. Nevertheless, such a monitoring campaign has a certain cost.

Aim of the note is to suggest how to realize a monitoring campaign of urban pollution by diffusive sampling at high spatial resolution.

A practical example comes from the RESOLUTION project whose results are reported in the publication “Evaluation of the best compromise between urban air quality monitoring by diffusive sampling and resource requirements“. Four European capital cities (Dublin, Madrid, Paris and Rome) were monitored six times, each time for seven days. Benzene, toluene, ethylbenzene, xylenes (BTEX) and NO2 concentrations were measured at 146 sites in Dublin, 293 in Madrid, 339 in Paris and 290 in Rome for a total number of 6300 VOC samples and as many NO2. Multiscale grids have been drawn which ranged in mesh size from 500 m to 2 km.

Isoconcentration map of the overall urban BTEX distribution
during the first sampling campaign in Rome

How to do it

1) Design the sampling grid

The extent of attendance of each site must be taken into account: greater width of the mesh in the less frequented areas and less in the busier areas; the smaller meshes is therefore to be destined to the areas with greater density of resident and greater number of shopping centers or other meeting points, bearing in mind that the population spends, on average, 10% of the time outside for travel, expenses and leisure time commitments, 30% of the time indoors for work, the remaining 60% at home.

2) The samplers must be exposed and withdrawn as soon as possible, ensuring the maximum contemporary exposure of all samplers, therefore a number of suitable and prepared positioning staff must be provided.

3) Once recovered, the samples must be shipped immediately to the laboratories responsible for the analyses.

4) Collect meteorological data: they are important both for make corrections to the value of the scope of radiello sampling in relation to temperature, and to assess the effects of the prevailing wind direction in polluting mapping.

5) To obtain the maps of isoconcentration levels, use the most suitable statistical interpolation models. We suggest geostatistical interpolation techniques.