Impacts of terrestrial vegetation on surface ozone in China: from present to carbon neutrality

Despite many efforts to control anthropogenic sources, high ambient ozone (O3) concentrations remain a serious air pollution problem in China. Terrestrial vegetation can remove surface O3 through dry deposition but also enhance surface O3 through biogenic volatile organic compound (BVOC) emissions. However, the net impacts of terrestrial vegetation on surface O3 remains unclear. Here, we perform simulations using a chemistry-vegetation coupled model to assess the impacts of terrestrial vegetation on surface daily maximum 8 h average (MDA8) O3 in China through biogeochemical processes, including BVOC emissions and stomatal uptake. The results show that vegetation biogeochemical processes increase summer mean surface MDA8 O3 by 1.3 ppb in the present day in China, with 3.7 ppb from BVOC emissions but −2.7 ppb from stomatal uptake. However, the enhanced summer mean surface MDA8 O3 from vegetation biogeochemical processes decreases from 5.4 to 2.7 ppb in the North China Plain (NCP), from 7.2 to 0.8 ppb in the Yangtze River Delta (YRD), from 8.7 to 1.8 ppb in the Sichuan Basin (SCB) and from 4.2 to 0.4 ppb in the Pearl River Delta by the period of carbon neutrality. Our study highlights that carbon neutrality-driven emission reductions can greatly mitigate the enhanced surface O3 related to terrestrial vegetation, though there is still a positive impact of terrestrial vegetation on surface O3 in some hotspots, including the NCP and the SCB.


Introduction
Ozone (O 3 ) is a major component of photochemical smog.High O 3 concentrations at the ground level can cause large damage on public health and terrestrial ecosystems (Dang and Liao 2019, Dedoussi et al 2020, Unger et al 2020).Since the successive implementation of a series of air pollution prevention and control action plans by Chinese government, the concentrations of particulate matter are decreased remarkably, but O 3 pollution has shown a worsening trend (Fu et al 2019, Lu et al 2020).During the period 2013-2019, the annual O 3 assessment value (daily maximum 8 h sliding average 90% quantile concentration) in 74 key cities nationwide increased by 28.8%.
Meanwhile, the number of cities with annual O 3 assessment value exceeding the limits of the national secondary standard increased from 17 to 56 among 74 key cities (Zhang et al 2020).
O 3 is mainly produced from atmospheric nitrogen oxides (NOx) and volatile organic compounds (VOCs) through photochemical reactions under high light conditions (Tan et al 2021, Zhao et al 2023).The O 3 photochemical processes are highly nonlinear in response to its precursors (Xing et al 2011, Xie et al 2014, Liu et al 2022) and sensitive to meteorological parameters, including temperature and humidity (Kavassalis and Murphy 2017, Porter and Heald 2019, Lei et al 2022).The occurrence of extreme O 3 pollution events is not only attributed to the local production and elimination processes but also aggravated by regional transport (Gong et al 2020, Wang et al 2021b).Furthermore, surface O 3 is closely related to terrestrial ecosystem activities.On the one hand, biogenic VOC (BVOC) emissions from terrestrial vegetation are considered a major source of surface O 3 , particularly in regions with high O 3 concentrations, such as the Yangtze River Delta (YRD) and the Pearl River Delta (PRD) in China.In these regions, BVOC emissions from vegetation have been found to be equivalent to anthropogenic VOC emissions (Wu et al 2020, Li et al 2021, Wang et al 2021c).On the other hand, stomatal uptake is a vital sink for surface O 3 .In vegetated regions, stomatal uptake accounts for 30%-80% of O 3 dry deposition (Gerosa et al 2005, Zhang et al 2006, Fowler et al 2009, Ducker et al 2018).
The control of O 3 pollution is not simply achieved by reducing the precursors emissions, including NOx and VOCs.In fact, an inappropriate reduction ratio between these two can increase surface O 3 concentrations (Li et al 2019, Yang et al 2021).One of the challenges in controlling O 3 pollution is how to accurately determine the natural contribution from vegetation and accordingly set the reduction ratio for anthropogenic NOx and VOCs.Moreover, with China's goal of carbon neutrality by 2060, afforestation may be utilized to enhance carbon sequestration on land.Therefore, clarifying the impacts of terrestrial vegetation to surface O 3 in China is crucial for creating long-term effective strategies to control O 3 pollution, and has significant scientific and practical value for improving future air quality.
Although several studies have assessed the impacts of terrestrial vegetation on surface O 3 in China using the chemical transport model (Liu et al 2018, Ma et al 2019, Wu et al 2020, Wang et al 2021c, Cao et al 2022), there are several knowledge gaps remain to be filled.Previous studies mainly focused on the impacts of BVOC on surface O 3 , but the stomatal uptake was generally missing, despite being known as an important sink for surface O 3 .Furthermore, to the best of our knowledge, the joint impacts of BVOC emission and stomatal uptake on surface O 3 in China still remains unknown.This is because that the vegetation stomatal conductance in the current Wesely (1989) dry deposition scheme and MEGAN2.1 BVOC estimation scheme of chemical transport model lacks the ecological response to environmental variables, which induce large uncertainties (Sun et al 2022).For example, Kavassalis and Murphy (2017) found that the ecological-dependent stomatal conductance in dry deposition scheme is crucial for reproducing observed strong ozonehumidity correlation.Moreover, recent studies have found significant differences in the response of BVOC emission to drought simulated by the MEGAN2.1 scheme contrast to observation (Seco et al 2015, Jiang et al 2018), which is mainly related to the selection of soil moisture threshold points in this scheme (Huang et al 2015).To improve the model skill in simulating the O 3 dry deposition velocity and BVOC emissions, several scholars began to couple vegetation models with chemical transport models.For example, Lei et al (2020) and Lam et al (2023) have coupled the vegetation modules to the GEOS-Chem chemical transport model, which provide an important tool to quantify the interactions between atmospheric chemistry and terrestrial vegetation.
In this study, using a newly coupled atmospheric chemistry-vegetation model, which accounts for dry deposition and BVOC emissions through the photosynthesis-dependent schemes, we quantify the isolated and combined impacts of BVOC emissions and stomatal uptake on surface daily maximum 8 h average (MDA8) O 3 in China.Such study will provide an important scientific support for China to develop long-term effective measures for controlling O 3 pollution in the context of carbon neutrality.

Methods and materials
2.1.The GC-YIBs model GEOS-Chem is utilized as a global 3D atmospheric chemistry and transport model to simulate the concentrations of gaseous pollutants and aerosols by implementing a comprehensive HOx-NOx-VOC-O 3 -halogen-aerosol chemical mechanism (https:// geoschem.github.io/).In GEOS-Chem, the Fast-JX scheme is employed to calculate photolysis rates.The model of emissions of gases and aerosols from nature (MEGAN2.1) is used to calculate BVOC emissions (Guenther et al 2012).The resistance-in-series scheme is employed to estimate the dry deposition of gases (Wesely 1989).However, some recent studies revealed that the current schemes have large uncertainties in simulating BVOC emissions and O 3 dry deposition, which is mainly because these schemes fail to capture the response of BVOC emissions and dry deposition to eco-physiological process (Kavassalis and Murphy 2017, Jiang et al 2018, Silva and Heald 2018, Wang et al 2021a).
The Yale interactive terrestrial biosphere model (YIBs) as a vegetation model, is designed to simulate the changes of leaf area index (LAI) and tree height through carbon assimilation, respiration and allocation processes (Yue and Unger 2015).Following Farquhar and Spitters schemes, the YIBs model includes nine plant functional types (PFTs; figure S1) to calculate plant photosynthesis.The parameterization schemes of LAI and carbon allocation processes are consistent with the TRIFFID (Topdown Representation of Interactive Foliage and Flora Including Dynamics) vegetation model.The stomatal conductance at leaf level is estimated with the Ball and Berry model (Baldocchi et al 1987).The isoprene emission at leaf level is computed with the PS_BVOC  (Friedlingstein et al 2020).GC-YIBs is a newly developed atmospheric chemistry-vegetation model, which couples the YIBs model with the GEOS-Chem model (Lei et al 2020).In GC-YIBs, the YIBs model outputs photosynthesisdependent stomatal conductance and isoprene emissions to account for dry deposition and BVOC emissions in GEOS-Chem.In turn, the simulated surface O 3 concentration in GEOS-Chem is used as an input to affect the carbon cycle in the YIBs model.This two-way coupling between YIBs and GEOS-Chem improves the natural source and sink simulations of surface O 3 (Lei et al 2022) and allows for a comprehensive understanding of how atmospheric chemistry and terrestrial ecosystem are interconnected and affect each other.

Model simulations
In this study, the nested GC-YIBs model with a high horizontal resolution of 0.5 • × 0.625 • is driven by the MERRA2 meteorological reanalysis to assess the impacts of terrestrial vegetation on surface O 3 in China.The biomass burning emission is calculated using the Global Fire Emissions Database version 4.1 (GFED4.1)inventory (van der Werf et al 2017).The global anthropogenic emission inventory is provided by community emissions data system (CEDS) (McDuffie et al 2020).The 2017 anthropogenic emission in China is provided by the multiresolution emission inventory (MEIC) inventory (Zheng et al 2018).The 2060 anthropogenic emission associated with China's target of carbon neutrality is obtained from the dynamic projection for emissions in China (DPEC) model (Cheng et al 2021, Tong et al 2020).
With the GC-YIBs model, eight runs are designed to separate the impacts of terrestrial vegetation on O 3 through BVOC emission and stomatal uptake processes (table 1).These runs are divided into two main groups: 1. CTRL, NOB, NOS and NOBS simulations use anthropogenic emissions in 2017.CTRL is the control simulation with default setting.NOB, NOS and NOBS are sensitive simulations, which omit the impacts of BVOC, stomatal uptake and both BVOC and stomatal uptake on surface O 3 , respectively.2. CTRL_CN, NOB_CN, NOS_CN and NOBS_CN simulations are the same as CTRL, NOB, NOS and NOBS simulations, except that the former uses anthropogenic emissions in 2060 under ambitious carbon neutrality scenario.
All above simulations are performed from May to August in 2017, and the results of the last three months (JJA) are used to assess the impacts of terrestrial vegetation on surface O 3 in summer.The differences between CTRL and NOB, NOS and NOBS represent the impacts of BVOC emissions alone, stomatal uptake alone and jointly BVOC emissions and stomatal uptake on surface O 3 in China, respectively.The difference between CTRL_CN and CTRL indicates the changes of surface O 3 due to anthropogenic emission reductions under carbon neutrality scenario relative to present.The differences between CTRL_CN and NOB_CN, NOS_CN and NOBS_CN represent the impacts of BVOC emissions alone, stomatal uptake alone and joint BVOC emissions and stomatal uptake on surface O 3 in China under carbon neutrality scenario, respectively.

Validation data
In this study, we collected hourly O 3 concentrations at 1580 sites in summer 2017 from the observational network of the China Ministry of Ecology and Environment (www.cnemc.cn/).With the quality controls (observation available for at least 20 h per day and 87 d in summer), MDA8 O 3 concentrations at 955 sites in China are applied to validate the GEOS-Chem model.Similarly, we use satellite retrieval product of GOSIF (Li and Xiao 2019) as the benchmark gross primary productivity (GPP) to validate the YIBs model.

Evaluations of the GC-YIBs model
GC-YIBs is developed as a vital tool for examining the interaction between atmospheric chemistry and terrestrial vegetation.Here, we first validate the skill of the GC-YIBs model for reproducing observed surface O 3 and GPP in summer 2017 (figure 1).Observed MDA8 O 3 shows spatial heterogeneity with the maximums in the North China Plain (NCP, 34.5-41 • N, 112-118.5 • E), the YRD (29-34.5 • N, 116.5-122 • E) and the Sichuan Basin (SCB, 28.5-32 • N, 103.5-107 • E) (figure 1(a)).In these regions, the summer mean MDA8 O 3 reach up to 70 ppb, causing a serious threat to public health and terrestrial ecosystems.Compared to observations, the simulated MDA8 O 3 with the GC-YIBs model generally match the observed spatial pattern with a high correlation coefficient of 0.88 (figure 1(b)).Different from surface O 3 , satellite-based GPP increases from the northwest to the southeast of China, with the maximums in the SCB (figure 1(c)).Similarly, the simulated GPP from the GC-YIBs model also shows high consistent with observation and the correlation coefficient reaches 0.81 (figure 1(d)).The above evaluations provide a high confidence level in quantify the impacts of terrestrial vegetation on surface O 3 in China using the GC-YIBs model.

Impacts of vegetation on surface O 3 at present
Terrestrial vegetation plays an important role in regulating surface O 3 .With anthropogenic emissions in 2017, we quantify the impacts of terrestrial vegetation on summer mean surface O 3 driven by BVOC emissions and stomatal uptake (figure 2).Due to BVOC emissions from terrestrial vegetation, MDA8 O 3 shows a large enhancement with a regional average of 3.7 ppb (6.0%) in China (figures 2(a) and (b)).The largest enhancement of 12.9 ppb (17.5%) is found in the SCB, where the dense vegetation is observed.In addition, BVOC emissions increase MDA8 O 3 by 11.8 ppb (16.4%) in the YRD, 8.6 ppb (10.5%) in the NCP and 6.7 ppb (13.0%) in the PRD (21.5-24 • N, 112-115.5 • E).In contrast to BVOC emissions, stomatal uptake decreases MDA8 O 3 by 2.7 ppb (4.5%) averaged in China (figures 2(c) and (d)).Regionally, the decrease of MDA8 O 3 is mainly found in eastern China, while the decrease in western China is very small.Such spatial pattern well resembles the dry deposition velocity and stomatal conductance patterns (figure S2).Stomatal uptake and BVOC emissions have opposite contributions to surface O 3 , therefore, the net contribution of vegetation to surface O 3 is an important question.With the sensitivity experiment NOBS, we further assess the joint impacts of stomatal uptake and BVOC emissions on MDA8 O 3 in China (figures 2(e) and (f)).Generally, due to both stomatal uptake and BVOC emissions processes, MDA8 O 3 increases by 1.3 ppb (2.1%) averaged in China, suggesting that terrestrial vegetation plays a positive role in regulating surface O 3 .The largest enhancement of 8.7 ppb (11.8%) is found in the SCB, followed by 7.2 ppb (10.1%) in the YRD, 5.4 ppb (6.6%) in the NCP, and 4.2 ppb (8.1%) in the PRD.

Impacts of vegetation on surface O 3 under carbon neutrality
To mitigate climate change, China has pledged to achieve the target of carbon neutrality by the mid of 21st century.Following the China's target of carbon neutrality, the major precursors of O 3 decrease largely in future decades (Tong et al 2020).As the consequence, O 3 pollution in China is mitigated from this climate policy (figures 3(a) and (b)).Nationally, MDA8 O 3 decreases by 8.8 ppb (14.5%) from 2017 to 2060 under carbon neutrality scenario.Regionally, MDA8 O 3 shows large decreases of 19.5 ppb (23.9%) in the NCP, 27.3 ppb (40.0%) in the YRD, 22.7 ppb (30.8%) in the SCB and 22.8 ppb (44.3%) in the PRD.However, there are limited mitigation effects for O 3 pollution in western and northern China, where emission reductions are slight towards carbon neutrality.
Deep emission reductions associated with carbon neutrality influence not only surface O 3 , but also the role of terrestrial vegetation in O 3 pollution (figure 4).Compared to the present, the contributions of terrestrial vegetation to surface O 3 decrease in 2060 under carbon neutrality scenario.Due to BVOC emissions, the MDA8 O 3 averaged in China increases by only 1.7 ppb (3.3%) in 2060 under carbon neutrality scenario (figures 4(a) and (b)).Especially in the YRD and the SCB, the contributions of BVOC emissions to MDA8 O 3 decrease to 4.5 ppb and 5.3 ppb in 2060 under carbon neutrality scenario, respectively, which are less than half of that in the present.In contrast to BVOC emissions, there are limited changes (−2.1 vs. −2.7 ppb) in the contribution of stomatal uptake to surface MDA8 O 3 in 2060 relative to 2017 (figures 4(c) and (d) vs. figures 2(c) and (d)).Therefore, the net impacts of terrestrial vegetation on surface MDA8 O 3 become more smaller in 2060 under carbon neutrality relative to the present (figures 4(e) and (f) vs. figures 2(e) and (f)).For example, due to both BVOC emissions and stomatal uptake, the enhanced MDA8 O 3 of 1.3 ppb (2.1%) in 2017 shift to a decline of 0.38 ppb (0.74%) averaged in China in 2060 under carbon neutrality.Regionally, due to vegetation biogeochemical processes, the enhanced MDA8 O 3 decreases from 5.4 to 2.7 ppb in the NCP, from 7.2 to 0.8 ppb in the YRD, from 8.7 to 1.8 ppb in the SCB and from 4.2 to 0.4 ppb in the PRD.These findings seem to indicate that the contributions of terrestrial vegetation to surface O 3 maybe shift from positive to negative in the four key polluted regions due to further anthropogenic emission reductions.

Conclusion and discussion
In recent years, O 3 pollution still remains a severe environmental problem in China although two phases of clean air actions have been implemented by Chinese government since 2013 (Gong et al 2020, Li et al 2020, Lu et al 2020).The generation and dissipation of O 3 are not only related to anthropogenic emissions and meteorological parameters, but also influenced by vegetation processes, including BVOC emission and stomatal uptake (Lin et al 2020, Lei et al 2022).The control of O 3 pollution requires a clear understanding of the contribution of vegetation processes to O 3 source and sink, especially in the context of China's potential efforts to achieve carbon neutrality by 2060 through afforestation in the future.However, accurately quantifying the impact of vegetation processes on surface O 3 has always remained a challenge, mainly due to the significant uncertainty in the description of complex vegetation processes in current atmospheric chemical transport models (Wong et al 2019, Lei et al 2020, Lam et al 2023).In this study, using a newly coupled atmospheric chemistry-vegetation model, which accounts for dry deposition and BVOC emissions through the photosynthesis-dependent schemes, we conduct eight simulations to assess the net impacts of terrestrial vegetation on surface O 3 in China.The results show that vegetation biogeochemical processes, including both stomatal uptake and BVOC emissions can cause a large enhancement in surface O 3 in China, especially in the two key O 3 pollution regions of the SCB and the NCP by the present day.However, such enhancements tend to be alleviated by the period of carbon neutrality with deep cut of anthropogenic emissions.Our study reveals the negative O 3 pollution effects of terrestrial vegetation, providing important scientific values for future O 3 pollution control.
The spatial distribution of enhanced surface O 3 by BVOC emissions generally agrees on previous literatures (Lu et al 2019, Wu et al 2020, Cao et al 2022), with the maximums in the SCB, the YRD, and the NCP.Compared to an early study that reported that BVOC emissions increased summer mean surface O 3 by 8.6 ppb in China (Cao et al 2022), our study predicts a small enhancement of 3.7 ppb in summer mean surface O 3 in China.Such   discrepancy may be attributed to different schemes of BVOC emissions (PS_BVOC vs. MEGAN2.1)in O 3 simulations.Previous studies reported that the MEGAN2.1 scheme fails to capture the response of isoprene emissions to droughts because of the lack of eco-physiological process (Jiang et al 2018, Lei et al 2022).Moreover, Wang et al (2021a) implemented drought impacts in MEGAN2.1 and showed that the updated MEGAN2.1 scheme predicted lower BVOC emissions, resulting in lower surface O 3 concentrations.In order to reduce uncertainties, our study uses a photosynthesis-dependent BVOC scheme (PS_BVOC) to estimate the contribution of BVOC emissions to surface O 3 in China.
Some limitations are acknowledged here.(i) In our simulations under carbon neutrality scenario, we use only changing anthropogenic emissions but with meteorology fixed in 2017.A recent study showed that deep emission reductions associated with the target of carbon neutrality increased surface temperature by 0.2 K in eastern China (Yang et al 2023).Therefore, our simulations may underestimate surface O 3 concentrations under carbon neutrality scenario, because high air temperature can increase natural emissions (e.g.BVOC and soil NOx) (Lu et al 2021, Lei et al 2022)

Figure 3 .
Figure 3. Absolute (a) and relative (b) changes of summer mean MDA8 O3 with anthropogenic emissions under carbon neutrality relative to the present.

Table 1 .
Summary of eight simulations using the GC-YIBs model.Unger et al 2013).The YIBs model has been comprehensively evaluated using the multi-source datasets (Yue and Unger 2018).Beginning in 2020, the YIBs model became a participant in the 'Trends in the land carbon cycle (TRENDY)' multi-model ensemble project, which aims to estimate the global carbon budget and accelerate photochemical reactions(Pyrgou et al 2018, Wang et al 2022).(ii)Inthis study, we only consider biogeochemical processes, including stomatal uptake and BVOC emissions to assess the impacts of terrestrial vegetation on surface O 3 , mainly because the feedback of vegetation on meteorology is not coupled in the GEOS-Chem Y Lei et al model.Previous studies have showed that vegetation can decrease surface temperature and increase atmospheric relative humidity through transpiration (Mahmood et al 2014, Yu et al 2020).Therefore, the impacts of terrestrial vegetation on surface O 3 through both biogeochemical processes and meteorological feedbacks are worth to further investigate using a fully coupled chemistry-carbon-climate model in the future.Y Lei et al over the Yangtze River Delta region, China Atmos.Environ.186 113-28 Liu Y S et al 2022 Decadal changes in ozone in the lower boundary layer over Beijing, China Atmos.Environ.275 119018 Lu X et al 2021 The underappreciated role of agricultural soil nitrogen oxide emissions in ozone pollution regulation in North China Nat.Commun.12 Lu X, Zhang L, Chen Y F, Zhou M, Zheng B, Li K, Liu Y M, Lin J T, Yang Y, Li H M, Chen L, Dang R J, Xue D K, Li B J, Tang J P, Leung L R and Liao H 2022 North China Plain as a hot spot of ozone pollution exacerbated by extreme high temperatures Atmos.Chem.Phys.22 4705-19 Wang X L et al 2021b Sensitivities of ozone air pollution in the Beijing-Tianjin-hebei area to local and upwind precursor emissions using adjoint modeling Environ.Sci.Technol.Geddes J A, Tai A P K and Silva S J 2019 Importance of dry deposition parameterization choice in global simulations of surface ozone Atmos.Chem.Phys.19 14365-85 Wu K et al 2020 Estimation of biogenic VOC emissions and their corresponding impact on ozone and secondary organic aerosol formation in China Atmos.Res.231 104656 Xie M, Zhu K G, Wang T J, Yang H M, Zhuang B L, Li S, Li M G, Zhu X S and Ouyang Y 2014 Application of photochemical indicators to evaluate ozone nonlinear chemistry and pollution control countermeasure in China Atmos.Environ.99 466-73 Xing J, Wang S X, Jang C, Zhu Y and Hao J M 2011 Nonlinear response of ozone to precursor emission changes in China: a modeling study using response surface methodology Atmos.Chem.Phys.11 5027-44 Yang Y, Zeng L, Wang H, Wang P and Liao H 2023 Climate effects of future aerosol reductions for achieving carbon neutrality in China Sci.Bull.68 902-5 Yang Y, Zhao Y, Zhang L, Zhang J, Huang X, Zhao X F, Zhang Y, Xi M X and Lu Y 2021 Improvement of the satellite-derived NOx emissions on air quality modeling and its effect on ozone and secondary inorganic aerosol formation in the Yangtze River Delta, China Atmos.Chem.Phys.21 1191-209 Yu L X, Liu Y, Liu T X and Yan F Q 2020 Impact of recent vegetation greening on temperature and precipitation over China Agric.For.Meteorol.295 108197 Yue X and Unger N 2015 The Yale interactive terrestrial biosphere model version 1.0: description, evaluation and implementation into NASA GISS ModelE2 Geosci.Model Dev. 8 2399-417 Yue X and Unger N 2018 Fire air pollution reduces global terrestrial productivity Nat.Commun.9 5413 Zhang L M, Vet R, Brook J R and Legge A H 2006 Factors affecting stomatal uptake of ozone by different canopies and a comparison between dose and exposure Sci.Total Environ.370 117-32 Zhang Y H, Zheng J Y, Chen C H, He J J and Hu J L 2020 Blue Book on Prevention and Control of Atmospheric Ozone Pollution in China (available at: www.ep-serve.com/forepart/zxnr_index.do?oid=51478637&tid=26378242) (in Chinese) Zhao K H, Wu Y H, Huang J P, Gronoff G, Berkoff T A, Arend M and Moshary F 2023 Identification of the roles of urban plume and local chemical production in ozone episodes observed in long island sound during LISTOS 2018: implications for ozone control strategies Environ.Int.174 107887 Zheng B et al 2018 Trends in China's anthropogenic emissions since 2010 as the consequence of clean air actions Atmos.