Global modeling analysis of tropospheric ozone and its radiative forcing from biomass burning emissions in the twentieth century

This work evaluates the sensitivity of tropospheric ozone (O-3) and its radiative forcing (RF) from 1890 to 1990 to different biomass burning (BB) emissions using a global tropospheric climate-chemistry model (CCM) with a modified chemical mechanism for anthropogenic volatile organic compounds (AVOC). The use of the most efficient simplified chemical scheme among three chemical mechanisms with different degrees of complexity is acceptable for global scale simulations of the radiative effects of tropospheric O-3 changes in the CCM, since the differences in the results are small. The CCM model with simplified chemistry is implemented to study various aspects of the impact of BB emissions on tropospheric O-3 and its RF. The backward emission model results are in good agreement with the present-day observations for regions downwind of BB sources, while the forward emission model may reasonably produce the distributions of regional emissions in the preindustrial period. The global mean RF due to tropospheric O-3 increase from 1890 to 1990 is 0.41 W m(-2) on a global average. When no anthropogenic emissions in the preindustrial period are considered, this forcing reaches 0.47 W m(-2). We find that the global mean BB forcing due to tropospheric O-3 changes from 1890 to 1990 is 0.15 W m(-2) on a global average. The preindustrial BB emissions need to be represented realistically when evaluating controls on the emissions of trace gases and aerosols for a sustainable society, because there are significant open biomass burning emissions in the preindustrial period. The significant regional differences in the surface O-3 concentrations among three different BB data sets are found in the United States for 1890 and in Brazil for 1990. In these regions during the periods, the most common land uses in the forests are logging and conversion of primary or secondary forests to cattle pasture or shifting cultivation. Improvement in the data sets of historical land use changes and accurate representation of carbon dynamics are needed for improving the model calculation of biomass burning emissions.