Remote Sensing for Air Quality Impact Assessment

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Poor air quality is a threat to human health and ecosystems across many parts of the developed World (especially in Europe and North America) and is rapidly worsening in parts of the developing World (especially in Asia and parts of Africa). There is a large focus on understanding air pollution impacts on human health and how pollution concentrations (especially ozone and particulate matter or aerosol) contribute to premature deaths and increases in cardiovascular disease. However, air pollution also affects ecosystems, here impacts vary from effects on yield, biomass and biodiversity losses which can lead to reductions in crop and timber yields and changes in species composition of ecosystems. Impacts on vegetation biomass will also affect carbon sequestration (less carbon being held in living biomass leading to more carbon dioxide in the atmosphere) which will enhance climate change. Air pollution has also been found to affect the control that plants have over gas exchange resulting in increased transpiration which can in turn alter stream flow and hydrology. Even though these effects threaten food security, natural resources & biodiversity and the regulation of supporting biophysical systems our understanding of air pollution effects on ecosystems is far less advanced compared to that for human health, especially when considered at the global scale. This project seeks to redress that balance using novel approaches that will bring together state of the art advances in the interpretation of satellite data targeted towards helping evaluate global air quality models and improve their ability to make future predictions of air pollution impacts on ecosystems. The project will focus efforts by developing a data and modelling framework that provides a means of integrating different components (chemistry transport models, pollution impact models, satellite data of pollutant concentrations, land cover characteristics, surface monitoring data) that, when brought together, will advance our knowledge of air pollution impacts to vegetation. The project will target specific aspects of this integration to reduce key uncertainties in air pollution impact assessment and allow future advancements in both remote sensing and air quality disciplines to be more easily integrated in the future. These are i. incorporation of seasonal cycles of canopy architecture derived from satellite data into chemistry transport models; ii. use of satellite derived distributions of ozone, aerosol, photosynthetically active radiation and fluorescence to evaluate chemistry transport model outputs and; iii. inclusion of methods to simulate photosynthesis and fluorescence into chemistry transport models so that the combined action of aerosol and ozone on photosynthesis (and subsequent vegetation damage) can be more readily compared with satellite data observations.Finally, the project will culminate in an end user workshop to raise awareness of these new developments and their potential application to the broader scientific community concerned with understanding the influence of air pollution on atmospheric and terrestrial biosphere exchange processes. The project will also benefit a range of stakeholders with interest in air quality including i. national government through contribution to improving national scale modelling of air pollution; ii. European bodies involved in the UNECEs Convention on Long Range Transboundary Air Pollution who require estimates of pollution concentration and associated impacts to human health and vegetation across Europe; and iii. organisations such as UNEP active at the global level tasked with developing policies that can most effectively mitigate the most damaging effects of air pollution. Finally, the project will also benefit the Earth System Modelling community who are currently developing methods to improve our understanding of the effect of air pollution on atmosphere-biosphere exchange.