3 research outputs found

    Land cover change in low-warming scenarios may enhance the climate role of secondary organic aerosols

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    Most socioeconomic pathways compatible with the aims of the Paris Agreement include large changes to land use and land cover. The associated vegetation changes can interact with the atmosphere and climate through numerous mechanisms. One of these is emissions of biogenic volatile organic compounds (BVOCs), which may lead to the formation of secondary organic aerosols (SOAs) and atmospheric chemistry changes. Here, we use a modeling framework to explore potential future global and regional changes in SOA and tropospheric ozone following idealized, large-scale vegetation perturbations, and their resulting radiative forcing (RF). Guided by projections in low-warming scenarios, we modify crop and forest cover, separately, and in concurrence with changes in anthropogenic emissions and CO2 level. We estimate that increasing global forest cover by 30% gives a 37% higher global SOA burden, with a resulting forcing of −0.13 W m−2. The effect on tropospheric ozone is relatively small. Large SOA burden changes of up to 48% are simulated for South America and Sub-Saharan Africa. Conversely, increasing crop cover at the expense of tropical forest, yields similar changes but of opposite sign. The magnitude of these changes is strongly affected by the concurrent evolution of anthropogenic emissions. Our land cover perturbations are representative of energy crop expansion and afforestation, two key mitigation measures in 1.5 °C compatible scenarios. Our results hence indicate that depending on the role of these two in the underlying mitigation strategies, scenarios with similar long-term global temperature levels could lead to opposite effects on SOA. Combined with the complexity of factors that control SOA, this highlights the importance of including BVOC effects in further studies and assessments of climate and air quality mitigation involving the land surface

    A machine learning examination of hydroxyl radical differences among model simulations for CCMI-1

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    The hydroxyl radical (OH) plays critical roles within the troposphere, such as determining the lifetime of methane (CH ), yet is challenging to model due to its fast cycling and dependence on a multitude of sources and sinks. As a result, the reasons for variations in OH and the resulting methane lifetime (τCH ), both between models and in time, are difficult to diagnose. We apply a neural network (NN) approach to address this issue within a group of models that participated in the Chemistry-Climate Model Initiative (CCMI). Analysis of the historical specified dynamics simulations performed for CCMI indicates that the primary drivers of τCH differences among 10 models are the flux of UV light to the troposphere (indicated by the photolysis frequency JO1D), the mixing ratio of tropospheric ozone (O3), the abundance of nitrogen oxides (NO = NO C NO ), and details of the various chemical mechanisms that drive OH. Water vapour, carbon monoxide (CO), the ratio of NO V NO , and formaldehyde (HCHO) explain moderate differences in τCH , while isoprene, methane, the photolysis frequency of NO by visible light (JNO ), overhead ozone column, and temperature account for little to no model variation in τCH . We also apply the NNs to analysis of temporal trends in OH from 1980 to 2015. All models that participated in the specified dynamics historical simulation for CCMI demonstrate a decline in τCH during the analysed timeframe. The significant contributors to this trend, in order of importance, are tropospheric O3, JO1D, NO , and H2O, with CO also causing substantial interannual variability in OH burden. Finally, the identified trends in τCH are compared to calculated trends in the tropospheric mean OH concentration from previous work, based on analysis of observations. The comparison reveals a robust result for the effect of rising water vapour on OH and τCH , imparting an increasing and decreasing trend of about 0.5 % decade-1, respectively. The responses due to NO , ozone column, and temperature are also in reasonably good agreement between the two studies. 4 4 4 x 2 x 4 2 2 4 4 x 4 4
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