Spatial clustering in air quality data accuracy: assessment of low-cost sensors in Lisbon using a novel correlation-distance index - Sina Ataee; Myriam Lopes; Maria Isabel Nunes; Sónia Gouveia; Mohammad Vahidi Borji; Helder Relvas (Air Quality, Atmosphere & Health, 2026)
Effective air quality monitoring is essential for ensuring urban environmental comfort and protecting public health, especially within smart-city frameworks. In Lisbon, the performance of low-cost NO₂ and PM 10 sensors was assessed using a novel Correlation-Distance Index (CDI) coupled with Principal Component Analysis (PCA) weighting, alongside a demographic-weighted spatial association technique, benchmarked against reference monitoring stations. The analysis began by quantifying the inverse relationship between sensor–sensor correlation and Euclidean distance. This metric was then refined through the integration of PCA-derived weights and local population density, resulting in a composite CDI-PCA score assigned to each sensor. Spatial clustering of these scores identified zones of underperforming sensors, particularly in densely populated downtown and western neighborhoods. When these clusters were compared with census-block population data, there was a statistically significant association between CDI patterns and population density (χ²=406.5, p

Impact of traffic emissions on air quality in Cabo Verde - Sandra M. Freire; Helder Relvas; Myriam Lopes (Environmental Monitoring and Assessment, 2020)

Application of the DPSIR framework to air quality approaches - Helder Relvas; Ana Isabel Miranda (Air Quality, Atmosphere & Health, 2018)

Air quality assessment in Algiers city - Dalila Belhout; Rabah Kerbachi; Helder Relvas; Ana Isabel Miranda (Air Quality, Atmosphere & Health, 2018)

Optimal air quality policies and health: a multi-objective nonlinear approach - Helder Relvas; Ana Isabel Miranda; Claudio Carnevale; Giuseppe Maffeis; Enrico Turrini; Marialuisa Volta (Environmental Science and Pollution Research, 2017)