MAL2

With rapidly expanding economic and industrial developments and tremendous increases in energy consumption, China and India are facing serious aerosol pollution, posing great threat to human health. Aerosols also modulate the climate and ecosystems via aerosol-cloud-radiation interactions. Yet, the poor understanding of aerosol pollution in Asia and its interactions with climate impedes the design and implementation of effective pollution control measures. Combining atmospheric modeling and observations, we demonstrated that the aerosol interactions with radiation and clouds contributed in important ways to intensification of the aerosol enhancements in North China. We manifested also how assimilation of PM_2.5 in winter haze periods can improve model predictions and that these improved predictions can reduce significantly the uncertainties in health impacts and estimates of aerosol radiative forcing. It was also demonstrated that the conditions of the ocean temperature in fall can be effectively used to predict the severity of Indian winter haze, which provides useful implications for pollution control at least a season in advance.

How to cite: Gao, M.: Aerosol-weather-climate interactions in highly polluted regions, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7317, https://doi.org/10.5194/egusphere-egu21-7317, 2021.

Methane is a potent greenhouse gas with concentrations that are rising in the atmosphere in unexpected ways. Because of its radiative efficiency and because its lifetime in the atmosphere is only around a decade, reducing atmospheric methane concentration is a major component of most pathways designed to meet climate targets. Over the past two decades, observations indicate that there have been substantial changes in the emissions and removal of methane. Yet, years later, we still do not definitively know why methane concentrations plateaued in the 2000s, increased globally after 2007 and then continued to increase at an even faster rate after 2014. This limited understanding impacts our ability to carry out targeted emissions reductions. Here, I discuss two areas of my work in addressing gaps in our knowledge. First, I discuss how high-resolution modeling can extract information from satellite data to quantify long-term changes in emissions and the underlying drivers of these changes. I show that Brazil is a unique example where major sources such as wetlands and cattle are geographically distinct and thus satellite data can be used to examine changes from particular processes. I show how in the absence of this separation, which is the case for many other parts of world, additional information such as isotopic ratios can be used to contribute to the partitioning of methane emissions into underlying sources. I also discuss the limitations in current capability to effectively use isotopic ratio measurements. I show how field experiments and simple models can be used to derive global distributions in the isotopic signatures of major sources such as wetlands, providing more consistency against observations. I discuss how incorrect assumptions about source signature distributions have a major impact on our ability to interpret atmospheric isotopic ratio measurements and that this may be one reason why we have not been able to conclusively interpret the recent atmospheric methane record.

How to cite: Ganesan, A.: Interpreting changes in atmospheric methane using satellite and isotopic ratio measurements, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2998, https://doi.org/10.5194/egusphere-egu21-2998, 2021.

When scientific or policy-relevant questions involve atmospheric chemistry, one often hears "nonlinear" being invoked, but the precise nature of the nonlinearity is never delineated, and we are left with the fuzzy impression that nonlinear problems are difficult, with no simple answer.  I have even seen it used to avoid including indirect greenhouse gases in the Kyoto Protocol.  For differentiable systems, nonlinear behavior can be expressed through a Taylor expansion whereby any of the 2^nd order terms (x², y² or xy) are the first nonlinear parts.  In this lecture I explore a range of scientific discoveries or developments in atmospheric chemistry where the nonlinear nature was critical to understanding the problem.  I select a set of problems worked on by many colleagues and myself over the last four decades.  These include:  multiple solutions in stratospheric chemistry; catastrophic depletion of ozone; numerical methods for tracer transport; our developing understanding of methane; chemical feedbacks and indirect greenhouse gases; and finally the rich heterogeneity of gases that drives tropospheric chemistry. I hope to convince you that by recognizing the nonlinear nature of atmospheric chemistry and understanding when it is important and when it is not, we can advance the field.   

How to cite: Prather, M.: The Nonlinear Nature of Atmospheric Chemistry, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8934, https://doi.org/10.5194/egusphere-egu21-8934, 2021.

The human development of our planet has a variety of negative impacts on the composition of its atmosphere at every scale – locally, regionally, and even globally. One of these dramatic changes has been the increase in the mass concentrations of sub-micrometer particles by one to sometimes two orders of magnitude over populated areas in the Northern Hemisphere. These atmospheric aerosols can cause serious health problems, reduce visibility, contribute to acidic deposition and material damage, but are also cooling the planet by reflecting sunlight back to space. Atmospheric chemistry occurs within a fabric of complicated atmospheric dynamics and physics. This interplay often results in nonlinear and often counterintuitive changes of the system when anthropogenic emissions change. A major goal of our research has been to gain a predictive understanding of the physical and chemical processes that govern the dynamics, size, and chemical composition of atmospheric aerosols.

To illustrate the advances in the experimental techniques and theoretical tools in atmospheric aerosol science, we will go back to the beginning of the 21^st century and we will revisit the design a particulate matter control strategy for the Eastern US based on the data, knowledge, and tools available at that time. We will then look at the effects of the parts of this control strategy that have been materialized and their effects on public health using the current understanding. Finally, we will look forward in ways of further improving air quality in the US and Europe.

How to cite: Pandis, S.: Back to the Future: Reducing Atmospheric Particulate Matter Levels to Improve Human Health, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-565, https://doi.org/10.5194/egusphere-egu21-565, 2021.