Steps towards fast, fine, reliable satellite-based multi-species emission constraint

Human activities and climate change have profoundly changed emissions of air pollutants and greenhouse gases into the atmosphere. As countries move towards carbon neutrality and clean air, targeted emission control has become more important than ever to ensure rapid, deep and cost-effective emission mitigation. This ambition requires timely, high-resolution and accurate emission tracking, raising an unprecedented challenge to conventional emission inventories based on socioeconomic statistics and observation-based emission constraints that are subject to the resolution and coverage of observation data. In the advent of multi-satellite, multi-instrument, multi-species measurements of atmospheric constituents, together with rapid advancement of big Earth data and artificial intelligence techniques, a new paradigm of observation-based emission inversion becomes possible by strategically combining these sets of knowledge to guide a physics-based model framework in a computationally light manner. In this talk, starting from nitrogen oxides, we will present several scientific and methodological progresses to illustrate the emerging opportunity of this new paradigm for fast, fine, reliable satellite-based multi-species emission constraint, aiming to establish a comprehensive dataset to timely and accurately track air pollutants and greenhouse gases at fine scales.