Support tools for land use policies based on high resolution regional air quality modelling

Air pollution is becoming a stringent issue, especially in large urban agglomerations like Bucharest, Romania. National and European air quality regulations are focusing on enforcing emission and immission limit values, but there is a poor correlation between air quality policies and land use policies, both critical to urban development. The objective of this study is to develop a methodological framework for including air quality data in policies concerning urban development and land use change. The novelty is given by the use of high-resolution regional air quality modelling data for key pollutants like PM₁₀, SO₂ and NO₂ with land use datasets. The study proposes a methodological framework based on the Urban Atlas Project’s land use classes and the WRF-Chem air quality model. Through overlay analysis of the air quality model output and land use datasets, it is possible to derive two major types of information: (1) the land use area and classes exposed to certain pollutant concentration intervals and (2) the variability of the exposed land use classes according to the air pollutants source – receptor dynamics. Results are presented in the form of applications of the methodological framework in two different case studies. The methodological framework could be used as a tool for practitioners to include and use the evidence from air pollution information in the spatial planning policies and practice. In the first case study, three PM₁₀ classes were set up in order to demonstrate the possibility to identify land use classes exposed to certain intervals of PM₁₀ concentrations and their extent. The second case study focuses on the land use classes and their extent exposed to SO₂ and NO₂ concentrations in two different meteorological scenarios during two days in September 2014. This approach could provide support for decision makers in the policy development process, resulting in more informed decisions regarding future destinations of different land categories taking into account air pollution data and indicators. This study also opens the way for future air quality satellite data (ESA Sentinel 5-P and 5), with resolutions similar to the air quality model outputs to be used in land use planning and policy development purposes.