Assessing the intra-urban variability of nitrogen oxides and ozone across a highly heterogeneous urban area.

High-resolution air quality maps are critical towards assessing and understanding exposures to elevated air pollution in dense urban areas. However, these surfaces are rarely available in low- and middle-income countries that suffer from some of the highest air pollution levels worldwide. In this study, we make use of land use regressions (LURs) to generate annual and seasonal, high-resolution nitrogen dioxide (NO2), nitrogen oxides (NOx), and ozone (O3) exposure surfaces for the Greater Beirut Area (GBA) in Lebanon. NO2, NOx and O3 concentrations were monitored using passive samplers that were deployed at 55 pre-defined monitoring locations. The average annual concentrations of NO2, NOx, and O3 across the GBA were 36.0, 89.7, and 26.9 ppb, respectively. Overall, the performance of the generated models was appropriate, with low biases, high model robustness, and acceptable R2 values that ranged between 0.66 and 0.73 for NO2, 0.56 and 0.60 for NOx, and 0.54 and 0.65 for O3. Traffic-related emissions as well as the operation of a fossil-fuel power plant were found to be the main contributors to the measured NO2 and NOx levels in the GBA, whereas they acted as sinks for O3 concentrations. No seasonally significant differences were found for the NO2 and NOx pollution surfaces; as their seasonal and annual models were largely similar (Pearson's r > 0.85 for both pollutants). On the other hand, seasonal O3 pollution surfaces were significantly different. The model results showed that around 99% of the population of the GBA were exposed to NO2 levels that exceeded the World Health Organization defined annual standard.