Given the rapid and intense changes occurring throughout South Asia, South East Asia, and East Asia, it is important to look at the impacts of all of the major causes of air pollution emissions. This includes both large and stable urban sources, newly formed and rapidly changing urban sources, intense fires due to land-use change, and linear-combinations of the above. Since all of these underlying causes have different physical and chemical properties, their impacts on the atmospheric lifetime, height, and hence long-range transport are not always the same. However, by using a unified inverse-modeling approach, a less biased profile is found. Furthermore, the end results are found to match very well against measurements from additional sources, even without the need for arbitrary scaling. The model is shown to match both the mean, and the variability of measurements, across multiple years, including under both normal and El-Nino conditions.
A preliminary examination of the results show that there are three significant findings. First, that there is a smaller amount of transported pollutants from urban sources in Asia to the global scale. Second, there is an increase in the amount of pollutants transported from urban areas in South Asia and Southeast Asia to other locations within Asia. Third, that there is an increase in fire sources and in the total amount transported, both within Asia and from Asia to the rest of the Northern Hemisphere. These factors are not only based on changes in the emissions, but also on dynamics and other non-linear physical processes occurring on both small and global scales.
The results also reveal an interesting way to move forward. The goal of being able to reproduce and understand the correct mean of the amount of mass transported long-range, may not be the best way to proceed. In fact, the model runs that most closely capture the annual mean, do far worse in capturing the extreme events, including those which lead to the transport of the vast majority of the pollution both within Asia, and from Asia to the rest of the Northern Hemisphere. This is likely due to the more extreme events being in part hard to reproduce due to atypical sources, as well as non-linear atmospheric in-situ chemical and physical processing. Hence, a method which allows us to better reproduce the extremes, may lead to an overall better ability to understand long range transport, and its impacts, especially when it is the seasonal extremes that have the largest impact on the people. The ability to differentiate local and long-range sources is also of importance in Asia, where the vast majority of countries are still developing, and are hence free to set or alter their air pollution and climate policies more readily, leading to a greater opportunity to form a best-case approach to mitigating air pollution. It is hoped that the approach provided here can help us to make critical decisions about total sources and impacts.