Editing IPCC:AR6/WGI/Chapter-12 (section)

=== 12.3.7 Other Climatic Impact-drivers ===

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==== 12.3.7.1 Air Pollution Weather ====

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Although future air pollution will be strongly driven by air quality policies, anthropogenically-driven changes to temperature, humidity, precipitation and synoptic patterns have the potential to affect the emissions, production, concentration and transport of particulate matter (e.g., from dust, fires, pollen) and gaseous pollutants such as sulphur dioxide, tropospheric ozone and nitrogen dioxide (Section 6.5) with resulting impacts on human health, agriculture and ecosystems ( [[#Ren--2011|Ren et al., 2011]] ; [[#Fiore--2015|Fiore et al., 2015]] ; [[#Kinney--2015a|Kinney et al., 2015a]] ; [[#Tian--2016|Tian et al., 2016]] ; [[#Orru--2017|Orru et al., 2017]] ; [[#Emberson--2018|Emberson et al., 2018]] ; [[#Hayes--2020|Hayes et al., 2020]] ). Information about conditions leading to poor air quality is also important for visibility in natural parks and tourist locations ( [[#Yue--2013|Yue et al., 2013]] ; [[#Val%20Martin--2015|Val Martin et al., 2015]] ), as well as the efficiency of solar photovoltaic panels ( [[#Sweerts--2019|Sweerts et al., 2019]] ). Relevant information about conditions favouring air pollution includes tracking warmer conditions that accelerate ozone formation ( [[#Peel--2013|Peel et al., 2013]] ; [[#Schnell--2016|Schnell et al., 2016]] ) and the frequency and duration of stagnant air events ( [[#Horton--2014|Horton et al., 2014]] ; [[#Fann--2015|Fann et al., 2015]] ; [[#Lelieveld--2015|Lelieveld et al., 2015]] ; [[#Vautard--2018|Vautard et al., 2018]] ), although no regional index has proven sufficient to capture regional changes or acute events ( [[#Kerr--2018|Kerr and Waugh, 2018]] ; [[#Schnell--2018|Schnell et al., 2018]] ). By contrast, precipitation and moister air tend to reduce pollution (Section 6.5).

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==== 12.3.7.2 Atmospheric Carbon Dioxide at Surface ====

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Carbon dioxide (CO <sub>2</sub> ) is a well-mixed greenhouse gas with global repercussions on Earth’s energy balance; however, atmospheric CO <sub>2</sub> concentration changes at the land surface also affect plant functions within ecosystems and agriculture (see also Chapter 5). High CO <sub>2</sub> concentration can increase photosynthesis rates and primary production within natural ecosystems ( [[#Norby--2010|Norby et al., 2010]] ; [[#Ratliff--2015|Ratliff et al., 2015]] ; [[#Zhu--2016|Zhu et al., 2016]] ) and agricultural crops ( [[#Hatfield--2011|Hatfield et al., 2011]] ; [[#Leakey--2012|Leakey et al., 2012]] ; [[#Bell--2013|Bell et al., 2013]] ; [[#Glenn--2014|Glenn et al., 2014]] ; [[#Nagelkerken--2015|Nagelkerken and Connell, 2015]] ; [[#Behrenfeld--2016|Behrenfeld et al., 2016]] ; [[#Deryng--2016|Deryng et al., 2016]] ; [[#Kimball--2016|Kimball, 2016]] ). High CO <sub>2</sub> concentration affects total biomass and plant sugar content important to bioenergy production ( [[#Schaeffer--2012|Schaeffer et al., 2012]] ), but also helps some pests and weeds flourish ( [[#Hamilton--2005|Hamilton et al., 2005]] ; [[#Wolfe--2008|Wolfe et al., 2008]] ; [[#Valerio--2013|Valerio et al., 2013]] ; [[#Korres--2016|Korres et al., 2016]] ; [[#Stinson--2016|Stinson et al., 2016]] ; [[#Ramesh--2017|Ramesh et al., 2017]] ), while potentially shifting the effectiveness of herbicides ( [[#Varanasi--2016|Varanasi et al., 2016]] ; [[#Refatti--2019|Refatti et al., 2019]] ). Higher CO <sub>2</sub> concentration reduces transpiration losses during drought conditions ( [[#Cammarano--2016|Cammarano et al., 2016]] ; [[#Deryng--2016|Deryng et al., 2016]] ; [[#Swann--2016|Swann et al., 2016]] ; [[#Durand--2018|Durand et al., 2018]] ), which also changes the energy balance within the plant canopy ( [[#Webber--2017|Webber et al., 2017]] ). Higher CO <sub>2</sub> reduces the nutritional density of crops and forage lands ( [[#Loladze--2014|Loladze, 2014]] ; [[#Müller--2014|Müller et al., 2014]] ; [[#Myers--2014|Myers et al., 2014]] , 2017; X. [[#Li--2016|]] [[#Li--2016|]] [[#Li--2016|Li et al., 2016]] ; [[#Lee--2017|]] [[#Lee--2017|M.A. Lee et al., 2017]] ; [[#Smith--2018|Smith and Myers, 2018]] ; [[#Zhu--2018|Zhu et al., 2018]] ; [[#Beach--2019|Beach et al., 2019]] ) and can increase the production of toxins ( [[#Ziska--2007|Ziska et al., 2007]] ) and allergenic pollen ( [[#Schmidt--2016|Schmidt, 2016]] ).

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==== 12.3.7.3 Radiation at Surface ====

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Changes in surface solar and longwave radiation fluxes alter photosynthesis rates and potential evapotranspiration for natural ecosystems and food, fibre and energy crops ( [[#Mäkinen--2018|Mäkinen et al., 2018]] ); changes in radiation fluxes can also shift solar energy resources ( [[#Schaeffer--2012|Schaeffer et al., 2012]] ; [[#Jerez--2015|Jerez et al., 2015]] ; [[#Wild--2015|Wild et al., 2015]] ; [[#Fant--2016|Fant et al., 2016]] ; [[#Craig--2018|Craig et al., 2018]] ). Plants and aquatic systems particularly respond to changes in photosynthetically active radiation (PAR) and the fraction of diffuse radiation ( [[#Proctor--2018|Proctor et al., 2018]] ; [[#Ren--2018|Ren et al., 2018]] ; [[#Ryu--2018|Ryu et al., 2018]] ). Increases in ultraviolet radiation can also detrimentally affect ecosystems and human health ( [[#Barnes--2019|Barnes et al., 2019]] ).

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==== 12.3.7.4 Additional Relevant Climatic Impact-drivers ====

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Additional CIDs may be relevant for regional studies but are not the focus of assessment in this Report. For example, information about changes in the frequency and seasonal timing of fog helps anticipate airport delays and cool beach days, and is also important for water delivery and retention in coastal ecological and agricultural systems ( [[#Torregrosa--2014|Torregrosa et al., 2014]] ).

Threats to many sectoral assets and associated systems may also be compounded when multiple hazards occur simultaneously in the same place, affect multiple regions at the same time, or occur in a sequence that may amplify overall impact ( [[IPCC:Wg1:Chapter:Chapter-11#11.8|Section 11.8]] ; [[#IPCC--2012|IPCC, 2012]] ; [[#Clarke--2018|Clarke et al., 2018]] ; [[#Zscheischler--2018|Zscheischler et al., 2018]] ; [[#Raymond--2020|Raymond et al., 2020]] ). There is emerging literature on many connected extremes and their associated hazards (e.g., climatic conditions that could drive multi-breadbasket failures; [[#Trnka--2019|Trnka et al., 2019]] ; [[#Kornhuber--2020|Kornhuber et al., 2020]] ), but a full accounting is not practical here especially considering the many possible CID combinations and the need to assess how exposed systems would be vulnerable to compound CIDs (assessed in WGII). Table 12.2 is once again instructive here in considering hazard-related storylines, as the multiple CIDs affecting a given sectoral asset (assessing across a row of Table 12.2) point to potentially dangerous hazard combinations. Similarly, change in a single CID has the potential to affect multiple sectoral assets (assessing down a column of Table 12.2) in a manner with broader systemic implications (AR6 WGII).

'''Recent literature defines CID indices to represent trends and thresholds that influence sectoral assets, albeit with considerable variation owing to the unique characteristics of regional and sectoral assets. Indices include direct information about the CID’s profile (magnitude, frequency, duration, timing, spatial extent) or utilize atmospheric conditions as a proxy for CIDs that are more difficult to directly observe or simulate. Each sector is affected by multiple CIDs, and each CID affects multiple sectors. Assets within the same sector may require different or tailored indices even for the same CID. These indices may be defined to capture graduated thresholds associated with tipping points or inflection points in a particular sectoral vulnerability, with commonalities in the types of processes these thresholds represent even as their precise magnitude may vary by specific sectoral system and asset.'''

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