Understanding 2000-2018 trends in tropospheric ozone burden by tagging ozone molecules with their precursor emission source in a global chemistry climate model
Authors: Nalam Aditya , Lupascu Aura , Ansari Tabish , Butler Tim 
Published: March 2024

Tropospheric ozone (trop-O3) is a major pollutant at the surface and an important greenhouse gas at upper layers of troposphere. Major sources of trop-O3 are: transport from the stratosphere; and photochemical production within the troposphere involving reactions of ozone precursors: oxides of nitrogen (NO and NO2, collectively NOx) and reactive carbon species (RC), including methane.
In the past few decades, there have been several clean air measures taken by developed countries that have led to decreasing emissions from NH high latitude regions. However, the emissions from developing countries situated in the tropical and mid-latitude regions have been increasing, resulting in an overall equatorward shift in emissions. Zhang et al. 2016 find that this equatorward redistribution of ozone precursor emission is the dominant factor that has led to increase in global tropospheric ozone burden (TOB), due to larger convection of ozone and it&#8217;s precursors at the tropics from surface to the free troposphere where ozone lifetime is longer.
While several previous studies perform sensitivity simulations to understand the impact of changing precursor emissions on TOB trends, we use a source attribution technique (known as tagging/labelling) to quantify the absolute and relative contribution of various emission sectors to the global TOB. We perform simulation using CESM 1.2.2- CAM4-Chem are performed for a global study of trop-O3 source attribution (summarized in Butler et al. 2018) for the 2000-2018 period. Here, we modify the default chemical mechanism to output the ozone and its tags attributed to the source region/sector of its emitted precursors. For example, an NO molecule originating from biogenic source would be called NO_BIO, and all the other chemical species emanating from NO_BIO (NO2, NO3, O3 etc.) will hold the tag &#8220;BIO&#8221;. Two simulations are performed for tagging trop-O3 with its NOx and RC precursor emission sources separately. We specify separate tag identities for emissions from anthropogenic, biogenic, biomass burning, and aircraft sources. Additional tags are specified for lightning NOx in the NOx-tagged simulation, and for methane in the VOC-tagged simulation. Here, all surface-based anthropogenic emissions hold tags representing the geographical location (Europe, North America, East Asia, South Asia, Middle East etc.) at which the emissions occur.
Using these &#8220;tagged&#8221; simulations, we address the following questions:

What is the contribution of precursor emissions from various regions/sectors to the global TOB and its trend?
How does the ozone production efficiency of ozone precursor emissions respond to the trends in these precursor emissions during the 2000-2018 period?
How do contributions of different ozone precursors to the TOB contrast with their contribution to the trends in lower and upper tropospheric ozone, area-weighted mean surface O3 and population weighted O3?

The design of our simulations and several prominent results will be presented in our PICO.
Zhang et al. 2016: Tropospheric ozone change from 1980 to 2010 dominated by equatorward redistribution of emissions.
Butler et al. 2018: TOAST 1.0: Tropospheric Ozone Attribution of Sources with Tagging for CESM 1.2.2