Effects of ozone-vegetation interactions on meteorology and air quality in China using a two-way coupled land- atmosphere model

Correspondence to: Steve H.L. Yim (yimsteve@gmail.com) & Amos P.K. Tai (amostai@cuhk.edu.hk) 15 Abstract. Tropospheric ozone (O3) is one of the most important air pollutants in China and is projected to continue to increase in the near future. O3 and vegetation closely interact with each other and such interactions may not only affect plant physiology (e.g., stomatal conductance and photosynthesis) but also influence the overlying meteorology and air quality through modifying leaf stomatal behaviors. Previous studies have highlighted China as a hotspot in terms of O3 pollution and O3 damage to vegetation. 20 Yet, few studies have investigated the effects of O3-vegetation interactions on meteorology and air quality in China, especially in the light of recent severe O3 pollution. In this study, a two-way coupled land-atmosphere model was applied to simulate O3 damage to vegetation and the subsequent effects on meteorology and air quality in China. Our results reveal that O3 causes up to 16% enhancement in stomatal resistance, whereby large increases are found in Henan, Hebei and Shandong provinces. O3 25 damage causes a more than 20% reduction in photosynthesis rate, and at least 5% and 20% decrease in leaf area index (LAI) and gross primary production (GPP), respectively, and hotspot areas appear in the northeastern and southern China. The associated reduction in transpiration causes a 5–30 W m decrease (increase) in latent heat (sensible heat) flux, which induces a 3% reduction in surface relative humidity, 0.2–0.8 K increase in surface air temperature, and 40–120 m increase in boundary layer height in China. 30 We also found that the meteorological changes further induce a 2–6 ppb increase in O3 concentration in northern and south-central China mainly due to enhanced isoprene emission following increased air temperature, demonstrating that O3-vegetation interactions can lead to a strong positive feedback that can amplify O3 pollution in China. Our findings emphasize the importance of considering the effects of O3 damage and O3-vegetation interactions in air quality simulations, with ramifications for both air 35 quality and forest management.


Introduction
Tropospheric ozone (O3) is a secondary air pollutant, which is mainly formed from the photochemical can not only reduce gross primary production (GPP) of natural vegetation as well as crop yields (Ainsworth et al., 2012;Lombardozzi et al., 2012;Tai e al., 2014;Feng et al., 2015;Yue et al., 2017;Li et al., 2018), but also decrease transpiration , decrease runoff (Li et al., 2016) on larger scales and therefore affect the global carbon and water cycle (Lombardozzi et al., 2015).

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Vegetation can in turn modulate O3 concentration through influencing the sources and sinks of O3. Dry deposition of O3 onto vegetation is a major sink for O3, mainly via stomatal uptake. Stomata are the pores on plant leaves; they control water exiting and carbon entering the leaf interior and hence influence the water and carbon exchange between the land and atmosphere. When vegetation is exposed to enhanced 55 O3 levels, cellular and tissue damage can result in a decrease in photosynthesis rate, thus altering CO2 assimilation. Stomata conductance may decrease subsequently in response to O3 exposure, thus reducing the dry-depositional sink of O3 (Sadiq et al., 2017;Zhou et al., 2018), but some studies also suggest that O3 exposure can cause stomata to respond more sluggishly to changing environmental conditions, such as drought, with complex overall effects on stomatal behaviors and dry deposition (e.g., Huntingford et 60 al., 2018). Vegetation also affects the sources of O3; the most abundant biogenic VOC (BVOC) species emitted by vegetation is isoprene (C5H8), which is a major precursor for O3 formation in polluted, high-NOx environments, but removes O3 by ozonolysis or by sequestering NOx in more pristine, low-NOx regions (Hollaway et al., 2017). Isoprene production is known to be highly coupled with photosynthesis and by extension to stomatal conductance (Arneth et al., 2007). Moreover, transpiration, which is more reasonable. Lombardozzi et al (2012) modified the stomata conductance and photosynthetic rate separately based on the cumulative uptake of O3 into leaves and has shown a better representation of plant responses to O3 exposure. Efforts have been made to investigate the effects of O3 exposure on land biosphere based on the above O3 damage schemes. For example, based on an off-line process-based vegetation model, Yue and Unger (2014) found that O3 damage decrease GPP by 4-8% on average in the 90 eastern US and leads to significant decreases of 11-17% in east coast hot spots. Using the offline CLM model, Lombardozzi et al. (2015) estimated that the present O3 exposure reduces GPP and transpiration globally by 8-12% and 2.0-2.4%, respectively.
Several modeling studies conducted so far have demonstrated the importance of considering the 95 interactions and feedbacks between atmosphere and biosphere. By dynamically coupling O3 and LAI but without considering the meteorological feedbacks of O3-vegetation interactions to O3, Zhou et al. (2018) found that O3-induced damage on LAI can lead to changes in O3 concentrations by -1.8 to +3 ppb in boreal summer. By considering the interactions between atmospheric chemistry with biosphere in a twoway coupling model, Lei et al. (2020) quantified the damaging effects of O3 on vegetation and found a 100 global reduction of annual GPP by 1.5-3.6 %, with regional extremes of 10.9-14.1 % in the eastern US and eastern China. Based on the CESM model with fully interactive atmospheric chemistry, biogeochemical and biogeophysical cycles, Sadiq et al. (2017) estimated that surface O3 is 4-6 ppb higher in Europe, North America and China in simulations with O3-vegetation coupling comparing the surface O3 concentrations without O3-vegetation coupling. Based on modified WRF-Chem model, Li et al (2016, 105 2018) investigated the effect of O3 exposure on hydroclimate and crop productivity in the US, and highlighted O3 damage effects on meteorological fields and surface energy balance as well as the crop yields, but the feedbacks of changing meteorology onto surface O3 were not investigated. Arnold et al (2018) examined the global climate response to O3 exposure and found O3 damage on vegetation can induce widespread surface warming and changes in clouds, which could be critical on regional scales.

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Although the interactions between O3 and vegetation are critical to our environment, adequate representation of O3-vegetation interactions is still missing in most atmospheric models used for climate and atmospheric chemistry simulations, at least in part due to incomplete coupling capacities with land surface or biospheric model components at high resolutions, and in part due to limited observations to optimize O3 damage schemes for wider regional applicability.

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With the rapid urbanization and industrialization in the recent decades, China has experienced increasingly severe O3 pollution, which is expected to continue to worsen in the near future. O3 concentration in China has been observed to exceed ambient air quality standard by 100-200% (Wang et al., 2017) with the maximum 8-hour mean concentration of O3 (MDA8 O3) increasing by 4.6% per 120 year from 2015 to 2017 (Silver et al., 2018). Lu et al. (2018) showed that urban surface O3 in China during 2013-2017 was significantly higher than that in other regions around the world, and thus vegetation exposure to O3 is also higher in China. Li et al. (2018) also revealed the increasing trend of O3 in megacity clusters of China during 2013-2017, which is closely related with meteorology, anthropogenic emissions and PM2.5 concentrations. Global-scale studies have highlighted China as a 125 hotspot of O3 pollution and damage to vegetation compared with other regions (Sadiq et al., 2017;Arnold et al., 2018;Lei et al., 2020). However, a comprehensive study of how O3 affects meteorology and air quality through O3-vegetation interactions in China at high spatial resolutions, especially under the severe O3 pollution during 2014-2017, is still limited but highly warranted.
This study, therefore, first adopted and implemented a semi-mechanistic O3 damage scheme in a widely used regional atmosphere-land modeling framework and hence used it to simulate and assess the impacts of O3-vegetation interactions on boundary-layer meteorology and air quality in China at a high spatial resolution. Specifically, O3-induced damage to vegetation, changes in meteorology in China due to O3vegetation coupling, and the subsequent feedback effects onto O3 concentration itself are examined, 135 which is crucial to fully understand the O3-vegetation interactions and the following impacts on climate, biosphere, and air quality in areas with both high O3 concentrations and high vegetation coverage.

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The Weather Research and Forecasting (WRF) model is a state-of-the-art mesoscale nonhydrostatic meteorological model. An atmospheric chemistry module that includes various gas-phase chemistry and aerosol mechanisms has been implemented into and fully coupled with WRF to create the WRF-Chem model (Grell et al., 2005;Fast et al., 2006). In WRF-Chem, both the air quality and meteorological 145 components use the same transport scheme, model grid, subgrid-scale transport physics and time step.
WRF-Chem has been widely used in previous air quality studies (e.g., Li et al., 2016;Li et al., 2018;Liu et al., 2018;. In this study, we applied our revised WRF-Chem model based on version 3.8.1 to simulate meteorological fields and O3 concentration over China. For the land surface component within WRF, we used Noah-MP, which will be described in the next subsection. Noah-MP is a land surface model that uses multiple options for key land-atmosphere interaction processes (Niu et al., 2011). Noah-MP contains a separate vegetation canopy defined by a canopy top and bottom, crown radius, and leaves with prescribed dimensions, orientation, density, and radiometric properties. The canopy employs a two-stream radiation transfer approach along with shading effects necessary to achieve proper surface energy and water transfer processes (Dickinson, 1983). Noah-MP is 180 capable of distinguishing between C3 and C4 photosynthesis pathways and defines vegetation-specific parameters for plant photosynthesis and respiration.
Noah-MP is available for prognostic vegetation growth that combines a Ball-Berry photosynthesis-based stomatal resistance (Farquhar et al., 1980;Ball et al., 1987) that allocates carbon to various parts of 185 vegetation (leaf, stem, wood and root) and soil carbon pools (fast and slow). GPP, leaf area index (LAI) and canopy height are then predicted downstream from photosynthesis. The dynamic LAI and canopy height calculation will further affect surface energy fluxes, which will then affect the boundary-layer meteorology when coupling with the atmosphere model in WRF-Chem.

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In this study, the O3 concentration simulated by the chemical module of the WRF-Chem model was also dynamically passed onto the Noah-MP land surface model at every time step to modify the photosynthesis and stomatal conductance due to O3 damage. The land surface variables simulated by Noah-MP were also dynamically passed back onto the atmospheric components, thus allowing immediate, two-way feedback effects onto meteorological fields, O3 and other atmospheric chemical 195 constituents. In this way, land surface processes, atmospheric dynamics, and atmospheric chemistry in the WRF-Chem model were fully coupled.

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In Noah-MP, the Farquhar model (Farquhar et al., 1980) was used to calculate photosynthetic rate, whereas Ball-Berry model was used to calculate stomatal conductance (Ball et al., 1987). The photosynthesis rate, A (μmol CO2 m −2 s −1 ), is calculated separately for sunlit and shaded leaves and is limited by either one of three limiting factors and can be calculated as where Wc is the Rubisco-limited photosynthesis rate, Wj is the light-limited photosynthesis rate, and We is the export-limited photosynthesis rate. Igs is the growing season index with values ranging from 0 to 1.
Stomatal conductance (gs) is computed based on the photosynthesis rate from the Farquhar model as where gs is the leaf stomatal conductance (μmol m −2 s −1 ); rs is the leaf stomatal resistance (s m 2 μmol −1 ); m is an empirical parameter that relates stomatal conductance and photosynthesis with values ranging 215 from 5 to 9; A is the photosynthesis rate as described above; cs is the CO2 partial pressure at the leaf surface (Pa); es is the vapor pressure at the leaf surface (Pa); ei is the saturation vapor pressure inside the leaf (Pa); Patm is the atmospheric pressure (Pa); and b is the minimum stomatal conductance.
As mentioned above, following Lombardozzi et al. (2015), an O3 damage scheme was implemented in 220 Noah-MP embedded in WRF-Chem model version 3.8.1. The photosynthesis rate and stomatal conductance are modified independently using two sets of O3 impact factors, 3 and 3 , respectively, which are then multiplied to the initial A and gs calculated by the Farquhar-Ball-Berry model, respectively. Lombardozzi et al. (2012) found that independently modifying stomatal conductance and photosynthesis can improve the model prediction of plant response to O3 damage. The two damage factors are calculated 225 based on the cumulative uptake of O3 (CUO), which integrates the O3 flux inside leaves through the stomata throughout the growing season. The CUO (mmol m −2 ) is calculated as Where [O3] is the surface O3 concentration (nmol m -3 ); 3 = 1.61 is the ratio of leaf resistance to O3 to leaf resistance to water (Uddling et al., 2012); rs is the stomatal resistance, ra is the aerodynamic resistance and rb is the boundary-layer resistance (s m −1 ); ∆t is the model time step (s). CUO is only accumulated when LAI is larger than 0.4 and O3 flux is larger than a threshold value of 0.8 nmol O3 m −2 s −1 to consider the detoxification effect of plants to O3 damage.

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The two damage factors have linear relationships with CUO and can be calculated as follows: where 3 is the O3 damage factor for photosynthesis and 3 is the O3 damage factor for stomatal conductance; ap, bp, ac, and bc are empirical slopes and intercepts of three different plant groups (broadleaf trees, needleleaf trees, and grasses or crops) from Lombardozzi et al. (2015). The values of these slopes and intercepts are shown in Table 1. The original photosynthesis and stomatal conductance 245 are then multiplied with the two damage factors, respectively to get the modified photosynthesis and stomatal conductance under O3 exposure.

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Two sets of experiments were conducted in this study. We performed a control simulation (simu_withoutO3) without O3 damage on vegetation and a production simulation (simu_withO3)   compared. These years were selected based on the high O3 concentrations that were pointed out in previous studies (Li et al., 2018;Lu et al., 2018;Silver et al., 2018). JJA was selected because of the most severe O3 pollution in this season and because it is the active growing season of plants.

Model evaluation
290 Table 3 shows the city-averaged evaluation results of meteorological variables. The information of the major cities used for evaluation is shown in Table S2. From

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The correlation coefficient of air pollutants ranges from 0.14 (PM10) to 0.66 (O3). Detailed evaluation results for each city are shown in Table S7

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In response to the PSN reductions, LAI and GPP also decrease. More than 0.4 reductions in LAI are found in central and northern China (Figure 3e), corresponding to more than 20% reductions in LAI; in other regions, 5-15% reductions in LAI are observed. More than 0.8 g C m −2 day −1 reductions in GPP are found generally in China. Similar to Figure 3c, we find that GPP decreases by ~20% in northeastern and southern China and decreases by more than 40% in other regions (Figure 3i). Based on offline models 380 without considering atmosphere-biosphere coupling, O3 damage was found to decrease GPP at most by 11-17% in the East Coast hotspots of the US (Yue and Unger, 2014). Using the offline CLM model, Lombardozzi et al. (2015) estimated that the present O3 exposure reduces GPP globally by 8-12%. Based on RegCM-CHEM4 regional climate model coupled with YIBs terrestrial biosphere model, Xie et al.
(2019) revealed that O3 damage induces a significant reduction (12.1±4.4%) in the GPP, up to 35% in 385 summer over China (Table S13). Comparing our results with previous studies, our results are broadly consistent with Xie et al. (2019) but the magnitude is larger than the studies conducted by Yue and Unger (2014) and Lombardozzi et al. (2015). Differences or uncertainties may arise from the different model settings. It appears that offline models as used by Yue and Unger (2014) and Lombardozzi et al. (2015) generally found smaller damage than studies with two-way coupling between the atmosphere and 390 biosphere as used by Xie et al. (2019) and our work; this could be due to the existence of positive biosphere-atmosphere feedbacks that potentially worsen O3 damage, as will be discussed in subsequent sections. Different O3 damage schemes employed in the models may also be a source of differences, although we note that both this work and Lombardozzi et al. (2015) used the same scheme, so the differences appear to arise more likely from the effect of coupling and other model settings than from the 395 schemes alone.
The spatial distribution of dominant vegetation types in China are shown in Figure 4, where we can see that the croplands dominant in eastern China and especially in southern China suffer the greatest GPP reductions, indicating that crop yields in China would also be heavily affected by O3 damage.

Changes in meteorology due to O3-vegetation coupling
Through interacting with vegetation, O3 has the potential to further affect the meteorological environment in China via modifying, e.g., surface heat fluxes, temperature, humidity, and boundary layer height. The 435 distribution of meteorological variables from simulations with and without O3 damage is thus compared and analyzed in this section.   Figure 7 shows the distribution and the changes in surface relative humidity, temperature and planetary boundary layer height (PBLH) in response to O3 damage. Reductions in transpiration rate can directly cause reductions in relative humidity. As shown in Figure 7b, relative humidity has at least 3% absolute reductions. Values of relative humidity decrease more in northern China than in southern China. Similar to the changes in TR (Figure 5b), larger reductions in relative humidity (3-9%) are found over Henan, changes in transpiration rate drive the increases in temperature and contribute to PBLH growth. As presented in Figure 7e and Figure 7h, the distribution and hotspot areas of the changes in temperature and PBLH are similar to those in relative humidity. Generally, northern China has larger increases of temperature and PBLH compared with other regions. Generally, temperature increases by 0.2-0.8 K and

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PBLH increases by 40-120 m for northern China. The hotspot areas experience at least 0.6 K increases in temperature, and 80 m increases in PBLH.
As shown in Table S13, our results are comparable with results from a regional simulation conducted by Li et al. (2016), which showed that O3 damage decreases LH flux by 10-27 W m −2 and O3 damage 470 increases temperature by 0.6 C-2.0 C in the US. However, in their study, Li et al. (2016) assumed that O3 damage to plants happens when O3 concentration is over a threshold of 20 ppb to imitate a weaker detoxifying effect of plants, instead of the 40 ppb threshold that was commonly used in other previous studies using the same ozone damage scheme (e.g., Lombardozzi et al., 2015;this study). Considering the severe O3 air pollution in China, we resorted to use the more universal O3 threshold of 40 ppb used 475 by other studies to represent a more conventional detoxifying effect, instead of lowering the threshold value that would cause much larger changes in the surface fluxes and meteorological fields. Using a twoway coupling model and the same O3 damage scheme, Arnold et al. (2018) revealed that O3 causes less than 8 W m −2 changes in surface heat fluxes regionally, which is smaller than the changes of surface heat fluxes in our study. One possible reason is that the simulated changes in O3 and aerosol in Arnold et al.

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(2018) did not feedback onto radiation and climate simulation or affect LAI.   Reduced dry deposition due to stomatal closure and reduced LAI, as well as increased isoprene emission, are all found to be the drivers for the overall positive O3 feedback. Reductions in dry deposition velocity, following closely the corresponding reductions in transpiration rate as both processes are modulated by 515 stomatal regulation, contribute in part to the O3 enhancement. Figure 9 shows the spatial distribution of isoprene emission and its changes due to O3 damage. We observe general increases in isoprene emission in eastern China, mainly due to increased surface temperature (Figs. 7e and 7f) that is more than enough to offset reduced isoprene caused by reduced LAI (Figs 4e and 4f). All in all, O3 damage on vegetation can further enhance O3 levels via an overall positive effect, due to not only the associated reductions in 520 dry deposition velocity, but also the reductions in transpiration, LH flux and the resulting rise in surface temperature.

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CO2 m −2 s −1 ) are found in northeastern and southern China. Following reduced photosynthesis, LAI shows relatively small reductions (5-15%), while GPP shows more than 20% reductions (1.6 g C m −2 day −1 ). Changes in transpiration rate are due to both changes in stomatal resistance and changes in LAI.
With the increases in stomatal resistance and decreases in LAI, transpiration deceases from 0.2 to 1.0 mm day -1 in eastern China with the largest reductions occur in northern China. We also found that the 555 distribution of changes in transpiration is consistent more with the distribution of stomatal resistance than with those of LAI, indicating the dominance of the former in contributing to the overall transpiration rate.
With O3 damage, the LH fluxes decrease by more than 4 W m −2 on average, with hotspot areas appearing in Shandong, Anhui and Jiangsu provinces, in which the decreases can be up to 30 W m −2 following 560 mostly the decreases in transpiration rate. SH fluxes increase in similar areas at comparable magnitudes (10-25 W m −2 ). The decreases in LH and the increases in SH cause the increases in temperature and PBLH. We found that northern China has larger decreases in relative humidity, temperature and PBLH compared with other regions. Generally, relative humidity shows at least 4% relative reductions, temperature increases by 0.2-0.8 K, and PBLH increases by 40-120 m for northern China. This indicates 565 that O3-vegetation interactions will cause a shift in the energy balance toward a state where available net radiation is dissipated more by SH flux than LH flux, with ramifications for surface temperature. This represents an additional pathway whereby anthropogenic O3 pollution can worsen warming, in addition to O3 being a greenhouse gas itself and O3-induced plant damage diminishing the global net carbon sink (e.g., Sitch et al., 2007;Lombardozzi et al., 2015).

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O3 induces changes in vegetation, surface fluxes and meteorology, and in turn affects its own concentration. In this study, we found in China reduced dry deposition velocity mostly due to enhanced stomatal conductance, enhanced isoprene emissions mostly due to enhanced surface temperature, and the corresponding increases in O3 concentration. O3 concentration increases the most (up to 6%) in Hebei, vegetation interactions can lead to a strong positive feedback that can amplify O3 pollution in China, in agreement with the suggestions by previous studies focusing on a global scale (Sadiq et al., 2017;Zhou et al., 2018;Gong et al., 2020). We also found that fully considering the positive O3-vegetation feedbacks, especially when meteorological changes are also accounted for, generates greater damage on vegetation 580 productivity than found by studies that only considered "offline" O3 damage on plants without feedbacks (Yue and Unger, 2014;Lombardozzi et al., 2015).
Uncertainty may arise from the O3 scheme employed in this study even through this scheme has considered the decoupling between photosynthesis and stomatal conductance. Because our method 585 following Lombardozzi et al. (2015) groups all the vegetation types into only three groups, which is maybe rough to investigate O3 damage effect on local scale. Moreover, the value of CUO is heavily rely on the O3 threshold, which may affect the calculation of O3 damage. We employed the universal threshold (40 ppb) in our study instead of the smaller threshold (20 ppb) used by Li et al. (2016) considering the severe O3 pollution and the overestimation of O3 by WRF-Chem in our study. However, for different 590 plant types, their detoxify to O3 may varied. Zhou et al. (2018) pointed out that the work of Lombardozzi et al. (2015) treat tropical and temperate plants equivalently, which may lead to possible biases. Detailed studies of investigating the plants responses to O3 and regional based CUO threshold should be conducted for more accurate simulation results for high resolution regional studies. Another uncertainty may from the ignorance of the direct effect of O3 on isoprene emission, which may slightly 595 weaken the positive O3 feedback mechanism as pointed out by Gong et al., 2020. But the feedback of isoprene emission is quite uncertain, which needs a lot of further studies. Drought stress that may affect the O3-vegetation coupling is also a major uncertainty in this study and a future direction for scholars to work on. Previous studies also indicate the importance of aerosol on O3 concentration in China recently , the O3, aerosol and vegetation interactions on climate and air quality therefore should 600 also be investigated in the future. Despite these uncertainties, our study provides detailed and comprehensive results that the O3-vegetation impacts will adversely affect plant growth and crop production, contribute to global warming, worsen the severe O3 air pollution in China, and identifies the hotspot areas in the country. Our findings clearly pinpoint the need to consider the O3 damage effects in both air quality studies and climate change studies.