Building statistical associations to forecast ethylbenzene levels in European urban-traffic environments

Emission from road traffic has become the most important source of local air pollution in numerous European cities. Epidemiological research community has established consistent associations between traffic-related substances and various health outcomes. Nevertheless, the vast majority of urban areas are characterised by infrastructure's absence to routinely monitor chemical health stressors, such as ethylbenzene. This paper aims at developing and presenting a tractable approach to reliably – and inexpensively – predict ethylbenzene trends in EU urban environments. The establishment of empirical relationships between rarely monitored pollutants such as ethylbenzene and more frequently or usually monitored, such as benzene and CO respectively, may cover the infrastructure's absence and support decision-making. Multiple regression analysis is adopted and the resulting statistical associations are applied to EU cities with available data for validation purposes. The results demonstrate that this approach is capable of capturing ethylbenzene concentration trends and should be considered as complementary to air quality monitoring.

► Ethylbenzene is a substance of the complex chemical pollution mix from road traffic.
► Tractably forecast ethylbenzene trends in EU urban micro-environments.
► Strong associations between ethylbenzene, xylene, toluene, benzene, CO and NOx.
► Validation of the adopted models to depict their applicability in intensive traffic.
► Reliable relations for combined exposure assessment.