A DECADAL ANALYSIS AND SENSITIVITY STUDY USING MOPITT CO COLUMNS OVER ASIA

A global continental merged high-resolution (PBLH) dataset with good accuracy compared to radiosonde is generated via machine learning algorithms, covering the period from 2011 to 2021 with 3-hour and 0.25º resolution in space and time. The machine learning model takes parameters derived from the ERA5 reanalysis and GLDAS product as input, with PBLH biases between radiosonde and ERA5 as the learning targets. The merged PBLH is the sum of the predicted PBLH bias and the PBLH from ERA5.

Remotely sensed NO2 and surface NOx are combined with a mathematical method to estimate daily NOx emissions. The results identify new sources and improve existing estimates. The estimation is driven by three flexible factors: thermodynamics of combustion, chemical loss, and atmospheric transport. The thermodynamic term separates power, iron, and cement from coking, boilers, and aluminum. This work finds three causes for the extremes: emissions, UV radiation, and transport.

Four-year TROPOMI observations are used to derive tropospheric NO₂ emissions in two mega(cities) with high anthropogenic activity. Wind-assigned anomalies are calculated, and the emission rates and spatial patterns are estimated based on a machine learning algorithm. The results are in reasonable agreement with previous studies and the inventory. Our method is quite robust and can be used as a simple method to estimate the emissions of NO₂ as well as other gases in other regions.

We analyze global measurements of aerosol height from fires. A plume rise model reproduces measurements with a low bias in five regions, while a statistical model based on satellite measurements of trace gasses co-emitted from the fires reproduces measurements without bias in eight regions. We propose that the magnitude of the pollutants emitted may impact their height and subsequent downwind transport. Using satellite data allows better modeling of the global aerosol distribution.

Measured aerosol heights over the Maritime Continent are higher than previously thought, with 61 to 83 % of aerosols above the boundary layer. These aerosols should hence have a larger impact on the climate. The use of a plume rise model cannot match the measurements, unless the measured fire energy is increased by 0–60 %. Furthermore, the model is too spread, indicating the importance of including convection and aerosol–radiation interactions. Significant model improvements will be required.

This study highlights the importance of taking into account a simultaneous use of land use, fire and precipitation for understanding the impacts of fires on the atmospheric loading and distribution of aerosols in Southeast Asia over both space and time. Also, it highlights that there are significant advantages of using 8-day and monthly average values (instead of daily data) in order to better quantify the magnitude and timing of the inter- and intra-annual variance of Southeast Asian fires.

Measurements of size-resolved aerosols (0.25–18 μm) were conducted at three sites (urban, suburban and background sites) in southern China during monsoon season (May–June) in 2010 aqueous-phase reaction was the main formation pathway of droplet mode sulfate. New particle formation, chemical aging, and long-range transport from upwind urban or biomass burning regions were also found to be important in at least some of the sights on some of the sampling days.