Editing IPCC:AR6/WGI/Chapter-6 (section)

== 6.5 Implications of Changing Climate on AQ ==

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Air pollutants can be impacted by climate change through physical changes affecting meterorological conditions, chemical changes affecting their lifetimes, and biological changes affecting their natural emissions ( [[#Kirtman--2013|Kirtman et al., 2013]] ). Changes in meteorology affect air quality directly through modifications of atmospheric transport patterns (e.g., occurrence and length of atmospheric blocking episodes, ventilation of the polluted boundary layer), extent of mixing layer and stratosphere–troposphere exchange (STE) for surface ozone ( [[#von%20Schneidemesser--2015|von Schneidemesser et al., 2015]] ), and through modifications of the rate of reactions that generate secondary species in the atmosphere. Changing precipitation patterns in a future climate also influence the wet removal efficiency, in particular for atmospheric aerosols ( [[#Hou--2018|Hou et al., 2018]] ). Processes at play in non-CO <sub>2</sub> biogeochemical feedbacks (Section 6.4.5) are also involved in the perturbation of atmospheric pollutants (Section 6.2.2).

This section relies on observational studies performed by analysing the correlation between specific meteorological conditions projected to occur more frequently in the future and surface pollutants, and global- and regional-scale modelling studies considering solely climate change in the future. We also assess the surface ozone and PM <sub>2.5</sub> changes based on CMIP6 models analysed in AerChemMIP, considering climate change in isolation with emissions in 2050 from SSP3-7.0 scenario (Section 6.7.1). Air quality being highly variable in space and time, the use of regional atmospheric chemistry models is necessary to characterize the effect of future climate on air quality properly. However, difficulties for such assessment arise from the need for long simulations that include complex chemistry–natural system interactions with high computational cost, in addition to the difficulty related to the regionalization of climate change ( [[IPCC:Wg1:Chapter:Chapter-10#10.3.1.2|Section 10.3.1.2]] ). Changes in the occurrence of weather patterns influencing air pollution (e.g., anticyclonic stagnation conditions, transport pathways from pollution sources, convection) due to climate change are assessed in Chapters 4 and 11.

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=== 6.5.1 Effect of Climate Change on Surface Ozone ===

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The AR5 assessed with ''high confidence'' that in unpolluted regions, higher water vapour abundances and temperatures in a warmer climate would enhance ozone chemical destruction, leading to lower baseline <sup>[[#footnote-000|5]]</sup> surface ozone levels ( [[#Kirtman--2013|Kirtman et al., 2013]] ). In polluted regions, AR5 assessed with ''medium confidence'' that higher surface temperatures will trigger regional feedbacks in chemistry and local emissions that will increase surface ozone and the intensity of surface ozone peaks.

The response of surface ozone to climate-induced Earth system changes is complex due to counteracting effects. Studies considering the individual effects of climate-driven changes in specific precursor emissions or processes show increases in surface ozone under warmer atmosphere for some processes. This is indeed the case for enhanced STE and stratospheric ozone recovery ( [[#Sekiya--2014|Sekiya and Sudo, 2014]] ; [[#Hess--2015|Hess et al., 2015]] ; [[#Banerjee--2016|Banerjee et al., 2016]] ; [[#Meul--2018|Meul et al., 2018]] ; [[#Morgenstern--2018|Morgenstern et al., 2018]] ; [[#Akritidis--2019|Akritidis et al., 2019]] ) or the increase of soil NO <sub>x</sub> emissions ( [[#Wu--2008|Wu et al., 2008]] ; [[#Romer--2018|Romer et al., 2018]] ), which can each lead to 1 to 2 ppb increase in surface ozone. Other processes, in particular deposition or those related to emissions from natural systems (Section 6.2.2) are expected to play a key role in future surface ozone and even the occurrence of pollution events (e.g., in the case of wildfires) but their effects are difficult to quantify in isolation.

Since the AR5, several studies have investigated the net effect of climate change on surface ozone, based on either global or regional model projections. A systematic and quantitative comparison of the ozone change, however, is difficult due to the variety of models with different complexities in the representation of natural emissions, chemical mechanisms and physical processes, as well as the surface ozone metrics applied for analysis. Ozone response to climate change has been shown to be particularly sensitive to model representation of processes like BVOC emissions, deposition, and isoprene chemistry (Squire et al. , 2015; Val Martin et al. , 2015; Schnell et al. , 2016; Pommier et al. , 2018) . More robust protocols are now used more commonly comprising, notably, longer simulations necessary to separate change from interannual variability (Barnes et al. , 2016; Lacressonnière et al. , 2016; Garcia-Menendez et al. , 2017) . However, the amplitude of climate change penalty on ozone over polluted regions may be different in high-resolution (regional- and urban-scale) models in comparison to coarse-resolution global models, because a number of controlling processes are resolution-dependent including for example, local emissions and sensitivity to the chemical regime (NMVOC limited versus NO <sub>x</sub> limited; [[#Lauwaet--2014|Lauwaet et al., 2014]] ; [[#Markakis--2014|Markakis et al., 2014]] , 2016).

Consistent with AR5 findings, global mean surface ozone concentration decreases range from 0.69 ± 0.16 ppb to 2.28 ± 0.24 ppb due to the dominating role of ozone destruction by water vapour in a four-member ensemble of CMIP6 ESM for surface warmings of 1.5°C–2.5°C (Figure 6.14). This decrease is driven by the ozone decrease over oceans, especially in the tropics (decrease of 1–5 ppb) and large parts of the continental unpolluted regions. The sensitivity of annual mean surface ozone to the level of surface warming over these remote areas varies spatially from –2 to –0.2 ppb <sup>o</sup> C <sup>–1</sup> (Supplementary Material Figure 6.SM.1).

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[[File:622b088318696710265aebab0c22e65c IPCC_AR6_WGI_Figure_6_14.png]]

'''Figure 6.14 |''' '''Multi-model annual mean change in surface O''' <sub>3</sub> '''(ppb) concentrations at different warming levels.''' Changes are shown for '''''(a)''''' 1.0°C, '''''(b)''''' 1.5°C, '''''(c)''''' 2.0°C and '''''(d)''''' 2.5°C increases in global mean surface air temperature. CMIP6 models include GFDL-ESM4, GISS-E2-1-G, MRI-ESM2-0 and UKESM1-0-LL. For each model, the change in surface O <sub>3</sub> is calculated as the difference between two AerChemMIP experiments – one with evolving future emissions and sea surface temperatures (SSTs) under the SSP3-7.0 scenario and the other with the same setup but with fixed present-day SSTs. The difference is calculated as a 20-year mean in surface O <sub>3</sub> around the year when the temperature threshold in each model is exceeded. The multi-model change in global annual mean surface O <sub>3</sub> concentrations with ± 1 ''standard deviation'' are shown within parentheses. Uncertainty is represented using the simple approach: no overlay indicates regions with high model agreement, three out of four models agree on sign of change; diagonal lines indicate regions with low model agreement, where three out of four models agree on sign of change. For more information on the simple approach, please refer to the Cross-Chapter Box Atlas.1. Further details on data sources and processing are available in the chapter data table (Table 6.SM.3).

Over ozone-producing regions of the world, such as in North America, Europe and Eastern Asia, AR5 and post-AR5 model studies project a general increase of surface ozone levels (climate change penalty on ozone) in a future warmer climate particularly during summer ( [[#Fu--2019|Fu and Tian, 2019]] ) . However, in current regional models, using more robust protocols, this increase of surface ozone, attributable to climate change, is of lower magnitude than in previous estimates ( [[#Lacressonnière--2016|Lacressonnière et al., 2016]] ; [[#Garcia-Menendez--2017|Garcia-Menendez et al., 2017]] ). Climate change enhances the efficiency of precursor emissions to generate surface ozone in polluted regions (Schnell et al. , 2016), and thus the magnitude of this effect will depend on the emissions considered in the study (present or future, and mitigated or not; Colette et al. , 2015; Fiore et al. , 2015) .

Considering anthropogenic emissions of precursors globally higher than the current emissions ( SSP3-7.0 in 2050; Figure 6.20), the CMIP6 ensemble confirms the surface ozone penalty due to climate change o ver regions close to anthropogenic pollution sources or close to natural emissions sources of ozone precursors (e.g., biomass-burning areas), with a penalty of a few ppb for the annual mean, proportional to warming levels (Figure 6.14). This rate ranges regionally from 0.2–2 ppb °C <sup>–1</sup> (Supplementary Material Figure 6.SM.1). The CMIP6 ESMs show this consistently for South East Asia (in line with [[#Hong--2019|Hong et al. (2019)]] and [[#Schnell--2016|Schnell et al. (2016)]] ) and for India (in line with [[#Pommier--2018|Pommier et al., 2018]] ) as well as in parts of Africa and South America, close to enhanced BVOC emissions (at least three out of four ESMs agree on the sign of change). The results are mixed in polluted regions of Europe and US because of lower anthropogenic precursor emissions which leads to a very low sensitivity of surface ozone to climate change (–0.5 ppb °C <sup>–1</sup> to 0.5 ppb °C <sup>–1</sup> ; Supplementary Material Figure 6.SM.1) and thus the ESMs can disagree on sign of changes for a given warming level. This heterogeneity in the results is also found in regional studies over North America (Gonzalez-Abraham et al. , 2015; Val Martin et al. , 2015; Schnell et al. , 2016; He et al. , 2018; Nolte et al. , 2018; Rieder et al. , 2018) or over Europe (Colette et al. , 2015; Lacressonnière et al. , 2016; Schnell et al. , 2016; Fortems-Cheiney et al. , 2017) .

Overall, warmer climate is expected to reduce surface ozone in unpolluted regions as a result of greater water vapour abundance accelerating ozone chemical loss ( ''high confidence'' ). Over regions with high anthropogenic and/or natural ozone precursor emissions, there is prevailing evidence that climate change will introduce a surface O <sub>3</sub> penalty increasing with increasing warming levels (with a magnitude ranging regionally from 0.2–2 ppb °C <sup>–1</sup> ) ( ''medium'' to ''high confidence'' ). Yet, there are uncertainties in processes affected in a warmer climate which can impact and modify future baseline and regional/local surface ozone levels. The response of surface ozone to future climate change through stratosphere–troposphere exchange, soil NO <sub>x</sub> emissions and wildfires is positive ( ''medium confidence'' ). In addition, there is ''low confidence'' in the magnitude of the effect of climate change on surface ozone through biosphere interactions (natural methane, non-methane BVOC emissions and ozone deposition) and lightning NO <sub>x</sub> emissions.

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=== 6.5.2 Impact of Climate Change on Particulate Matter ===

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Changes in concentration and chemistry of particulate matter (PM) in a changing climate depend in a complex manner on the response of the multiple interactions of changes in emissions, chemical processes, deposition and other factors (e.g., temperature, precipitation, circulation patterns). These changes are difficult to assess and, at the time of AR5, no confidence level was attached to the overall impact of climate change on PM <sub>2.5</sub> ( [[#Kirtman--2013|Kirtman et al., 2013]] ). Possible changes induced by climate change may concern both atmospheric concentration levels and chemical composition.

Higher temperatures increase the reaction rate of gaseous SO <sub>2</sub> to particulate sulphate conversion but also favour evaporation of particulate ammonium nitrate ( [[#Megaritis--2013|Megaritis et al., 2013]] ). Also, higher temperatures are expected to affect BVOC emissions (e.g., [[#Pacifico--2012|Pacifico et al., 2012]] ) that would influence SOA concentrations, although this effect has been questioned by more recent evidence ( [[#Wang--2018|]] [[#Wang--2018|]] [[#Wang--2018|B. Wang et al., 2018]] ; Z. [[#Zhao--2019|]] [[#Zhao--2019|]] [[#Zhao--2019|Zhao et al., 2019]] ). More generally, climate change will also affect dust concentration levels in the atmosphere (Section 6.2.2.4) and the occurrence of forest fires, both very large sources of aerosols to the global troposphere (Section 6.2.2.6).

Wet deposition constitutes the main sink for atmospheric PM ( [[#Allen--2016|]] [[#Allen--2016|Allen et al., 2016]] , 2019; [[#Xu--2018|Xu and Lamarque, 2018]] ). In particular, precipitation frequency has a higher effect on PM wet deposition than precipitation intensity ( [[#Hou--2018|Hou et al., 2018]] ). PM is also sensitive to wind speed and atmospheric stability conditions emphasizing the importance of stagnation episodes and low planetary boundary layer heights for increasing PM atmospheric concentrations ( [[#Porter--2015|Porter et al., 2015]] ).

At the global scale, depending on its magnitude, the warming leads either to a small increase in global mean PM concentration levels (about 0.21 µg m <sup>–3</sup> in 2100 for RCP8.5), mainly controlled by sulphate and organic aerosols or a small decrease (–0.06 µg m <sup>–3</sup> for RCP2.6, [[#Westervelt--2016|Westervelt et al. (2016)]] and [[#Xu--2018|Xu and Lamarque (2018)]] ). On the other hand, [[#Xu--2018|Xu and Lamarque (2018)]] and Allen et al. (2016, 2019) found an increase of aerosol burden and PM surface concentration throughout the 21st Century, attributed to a decrease in wet-removal flux despite the overall projected increase in global precipitation, on the ground of an expected shift of future precipitation towards more frequent heavy events. Based only on three models, the CMIP6 ensemble shows that for most land areas, there is low agreement between models on the sign of the effect of climate change on annual mean PM <sub>2.5</sub> (Supplementary Material Figure 6.SM.2).

Due to the typical atmospheric lifetime of PM in the atmosphere, of the order of a few days, most studies dealing with the future PM concentration levels have a regional character and concern mainly Europe (Megaritis et al. , 2013; Lacressonnière et al. , 2016, 2017; Lemaire et al. , 2016; Cholakian et al. , 2019), the USA (Penrod et al. , 2014; Fiore et al. , 2015; Gonzalez-Abraham et al. , 2015; Shen et al. , 2017; He et al. , 2018; Nolte et al. , 2018), Southern and Eastern Asia ( [[#Jiang--2013|Jiang et al., 2013]] ; [[#Nguyen--2019|Nguyen et al., 2019]] ) and India ( [[#Pommier--2018|Pommier et al., 2018]] ). No studies are available for other areas of the world.

Changes in the chemical composition of PM as a result of future climate change can also be an important issue for the effects of PM on human health and the environment, but only sparse data are available in the literature on this and the results are, as yet, inconclusive (Im et al. , 2012; Jiang et al. , 2013; Megaritis et al. , 2013; Gonzalez-Abraham et al. , 2015; Gao et al. , 2018; He et al. , 2018; Cholakian et al. , 2019).

Overall, there is ''medium confidence'' ( ''medium evidence'' , ''high agreement'' ) in a small effect, positive or negative, on PM global burden due to climate change.

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=== 6.5.3 Impact of Climate Change on Extreme Pollution ===

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Extreme air pollution is identified as the concentration of an air pollutant that is above a given threshhold value (high concentration or a high percentile) as the sensitivity of peak values to meteorological conditions can be different from sensitivity of the median or mean ( [[#Porter--2015|Porter et al., 2015]] ). The AR5 assessed with ''medium confidence'' that uniformly higher temperatures in polluted environments will trigger regional feedbacks in chemistry and local emissions that will increase peak ozone and PM pollution, but assessed ''low confidence'' in projecting changes in meteorological blocking associated with these extreme episodes.

Meteorological conditions, such as heatwaves, temperature inversions and atmospheric stagnation episodes favour air quality extremes and are influenced by changing climate ( [[#Fiore--2015|Fiore et al., 2015]] ). The body of literature on the connection between climate change and extreme anthropogenic pollution episodes is essentially based on correlation and regression applied to observation reanalysis but the metrics and methodologies differ making quantitative comparisons difficult. Many emission processes in the natural systems are sensitive to temperature, and bursts of emissions as a reponse to extreme weather, as in the case of wildfires in dry conditions ( [[#Bondur--2020|Bondur et al., 2020]] ; [[#Xie--2020|Xie et al., 2020]] ) can occur, which would then add to the risk of extreme air pollution but are not sufficiently constrained to be quantitatively assessed.

Since AR5, published studies provide augmented evidence for the connections between extreme ozone and PM pollution events and high temperatures, especially long-lasting heatwaves, whose frequency is increasing due to a warming climate ( [[#Lelieveld--2014|Lelieveld et al., 2014]] ; [[#Porter--2015|Porter et al., 2015]] ; [[#Hou--2016|Hou and Wu, 2016]] ; [[#Jing--2017|Jing et al., 2017]] ; [[#Schnell--2017|Schnell and Prather, 2017]] ; [[#Sun--2017|Sun et al., 2017]] ; H. [[#Zhang--2017|]] [[#Zhang--2017|Zhang et al., 2017]] ). However, the relationship between air pollution and individual meteorological parameters is exaggerated because of covariation on synoptic time scales ( [[#Fiore--2015|Fiore et al., 2015]] ). For example, heatwaves are often associated with clear skies and stagnation, making clear attribution to specific meteorological variables complicated. In Asia, future changes in winter conditions have also been shown to favour more particulate pollution ( [[#Cai--2017|Cai et al., 2017]] ; [[#Zou--2017|Zou et al., 2017]] ). The relationship between the occurrence of stagnation episodes and high concentrations of ozone and PM <sub>2.5</sub> has been shown to be regionally and metric dependant ( [[#Oswald--2015|Oswald et al., 2015]] ; [[#Sun--2017|Sun et al., 2017]] ; [[#Kerr--2018|Kerr and Waugh, 2018]] ; [[#Schnell--2018|Schnell et al., 2018]] ; [[#Garrido-Perez--2019|Garrido-Perez et al., 2019]] ).

The increase of frequency, duration and intensity of heatwaves is extremely likely on all continents for different future warming levels ( [[IPCC:Wg1:Chapter:Chapter-11#11.3.5|Section 11.3.5]] , Table 11.2). However, there is low confidence in projected changes in storm tracks, jets and blocking, and thus their influence on extreme temperatures in the mid-latitudes ( [[IPCC:Wg1:Chapter:Chapter-11#11.3.1|Section 11.3.1]] ).

In conclusion, there is still ''medium confidence'' that climate-driven changes in meterorological conditions, such as heatwaves or stagnations, will favour extreme air pollution episodes over highly polluted areas, however, the relationship between these meteorological conditions and high concentrations of ozone and PM <sub>2.5</sub> have been shown to be regionally and metric dependant.

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