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The newly developed offline land ecosystem model Terrestrial Ecosystem Model in R (TEMIR) version 1.0 is described here. This version of the model simulates plant ecophysiological (e.g., photosynthetic and stomatal) responses to varying meteorological conditions and concentrations of CO 2 and ground-level ozone (O 3) based on prescribed meteorological and atmospheric chemical inputs from various sources. Driven by the same meteorological data used in the GEOS-Chem chemical transport model, this allows asynchronously coupled experiments with GEOS-Chem simulations with unique coherency for investigating biosphere–atmosphere chemical interactions. TEMIR agrees well with FLUXNET site-level gross primary productivity (GPP) in terms of both the diurnal and monthly cycles (correlation coefficients R2>0.85 and R2>0.8 , respectively) for most plant functional types (PFTs). Grass and shrub PFTs have larger biases due to generic model representations. The model performs best when driven by local site-level meteorology rather than reanalyzed gridded meteorology. Simulation using gridded meteorology agrees well for annual GPP in seasonality and spatial distribution with a global average of 134 Pg C yr -1. Application of Monin–Obukhov similarity theory to infer canopy conditions from gridded meteorology does not improve model performance, predicting an increase of + 7 % in global GPP. Present-day O 3 concentrations simulated by GEOS-Chem and an O 3 damage scheme at high sensitivity show a 2 % reduction in global GPP with prominent reductions of up to 15 % in eastern China and the eastern USA. Regional correlations are generally unchanged when O 3 is present and biases are reduced, especially for regions with high O 3 damage. An increase in atmospheric CO 2 concentration of 20 ppmv from the level in 2000 to the level in 2010 modestly decreases O 3 damage due to reduced stomatal uptake, consistent with ecophysiological understanding. Our work showcases the utility of this version of TEMIR for evaluating biogeophysical responses of vegetation to changes in atmospheric composition and meteorological conditions. [ABSTRACT FROM AUTHOR]

Agriculture and food systems play important roles shaping atmospheric chemistry and air quality, most dominantly via the release of reactive nitrogen (Nr) compounds, but also via agricultural burning, energy use, and cropland and pastureland expansion. In this opinion, we first succinctly review our current understanding of agricultural and food-system emissions of Nr and other atmospherically relevant compounds, their fates and impacts on air quality, human health and terrestrial ecosystems, and how such emissions can be potentially mitigated through better cropland management, livestock management and whole food-system transformation. With that, we highlight important knowledge gaps that warrant more extensive research, and argue that we scientists need to provide a more detailed, process-based understanding of the impacts of agriculture and food systems on atmospheric chemistry, especially as the importance of emissions from other fossil fuel-intensive sectors is fading in the face of regulatory measures worldwide. Such knowledge is necessary to guide food-system transformation in technologically feasible, economically viable, socially inclusive, and environmentally responsible manners, and essential to help society achieve multiple Sustainable Development Goals (SDGs), especially to ensure food security for the people, protect human and ecosystem health, improve farmers' livelihood, and ultimately help communities achieve socioeconomic and environmental sustainability. [ABSTRACT FROM AUTHOR]

Surface ozone (O 3) is well known for posing significant threats to both human health and crop production worldwide. However, a multidecadal assessment of the impacts of O 3 on public health and crop yields in China is lacking due to insufficient long-term continuous O 3 observations. In this study, we used a machine learning (ML) algorithm to correct the biases of O 3 concentrations simulated by a chemical transport model from 1981–2019 by integrating multi-source datasets. The ML-enabled bias correction offers improved performance in reproducing observed O 3 concentrations and thus further improves our estimates of the impacts of O 3 on human health and crop yields. The warm-season trends of increasing O 3 in Beijing–Tianjin–Hebei and its surroundings (BTHs) as well as in the Yangtze River Delta (YRD), Sichuan Basin (SCB), and Pearl River Delta (PRD) regions are 0.32, 0.63, 0.84, and 0.81 µ g m -3 yr -1 from 1981 to 2019, respectively. In more recent years, O 3 concentrations experienced more fluctuations in the four major regions. Our results show that only BTHs have a perceptible increasing trend of 0.81 µ g m -3 yr -1 during 2013–2019. Using accumulated O 3 over a threshold of 40 ppb (AOT40-China) exposure–yield response relationships, the estimated relative yield losses (RYLs) for wheat, rice, soybean, and maize are 17.6 %, 13.8 %, 11.3 %, and 7.3 % in 1981, increasing to 24.2 %, 17.5 %, 16.3 %, and 9.8 % in 2019, with an increasing rate of +0.03 % yr -1 , +0.04 % yr -1 , +0.27 % yr -1 , and +0.13 % yr -1 , respectively. The estimated annual all-cause premature deaths induced by O 3 increased from ∼55900 in 1981 to ∼162000 in 2019 with an increasing trend of ∼2980 deaths per year. The annual premature deaths related to respiratory and cardiovascular disease are ∼34200 and ∼40300 in 1998 and ∼26500 and ∼79000 in 2019, having a rate of change of -546 and +1770 deaths per year during 1998–2019, respectively. Our study, for the first time, used ML to provide a robust dataset of O 3 concentrations over the past 4 decades in China, enabling a long-term evaluation of O 3 -induced crop losses and health impacts. These findings are expected to fill the gap of the long-term O 3 trend and impact assessment in China. [ABSTRACT FROM AUTHOR]

Surficial enhanced rock weathering (ERW) is a land-based carbon dioxide removal (CDR) strategy that involves applying crushed silicate rock (e.g., basalt) to agricultural soils. However, unintended biogeochemical interactions with the nitrogen cycle may arise through ERW increasing soil pH as basalt grains undergo dissolution that may reinforce, counteract, or even offset the climate benefits from carbon sequestration. Increases in soil pH could drive changes in the soil emissions of key non-CO 2 greenhouse gases, e.g., nitrous oxide (N 2 O), and trace gases, e.g., nitric oxide (NO) and ammonia (NH 3), that affect air quality and crop and human health. We present the development and implementation of a new improved nitrogen cycling scheme for the Community Land Model v5 (CLM5), the land component of the Community Earth System Model, allowing evaluation of ERW effects on soil gas emissions. We base the new parameterizations on datasets derived from soil pH responses of N 2 O, NO, and NH 3 in ERW field trial and mesocosm experiments with crushed basalt. These new capabilities involve the direct implementation of routines within the CLM5 N cycle framework, along with asynchronous coupling of soil pH changes estimated through an ERW model. We successfully validated simulated "control" (i.e., no ERW) seasonal cycles of soil N 2 O, NO, and NH 3 emissions against a wide range of global emission inventories. We benchmark simulated mitigation of soil N 2 O fluxes in response to ERW against a subset of data from ERW field trials in the US Corn Belt. Using the new scheme, we provide a specific example of the effect of large-scale ERW deployment with croplands on soil nitrogen fluxes across five key regions with high potential for CDR with ERW (North America, Brazil, Europe, India, and China). Across these regions, ERW implementation led to marked reductions in N 2 O and NO (both 18 %), with moderate increases in NH 3 (2 %). While further developments are still required in our implementations when additional ERW data become available, our improved N cycle scheme within CLM5 has utility for investigating the potential of ERW point-source and regional effects of soil N 2 O, NO, and NH 3 fluxes in response to current and future climates. This framework also provides the basis for assessing the implications of ERW for air quality given the role of NO in tropospheric ozone formation, as well as both NO and NH 3 in inorganic aerosol formation. [ABSTRACT FROM AUTHOR]

Surface ozone (O3) is well known to pose significant threats to both human health and crop production worldwide. However, a multi-decadal assessment of O3 impacts on public health and crop yields in China is lacking due to insufficient long-term continuous O3 observations. In this study, we used a machine learning (ML) algorithm to correct the biases of O3 concentrations simulated by the chemical transport model from 1981–2019 by integrating multi-source datasets. The ML-enabled bias correction offers improved performance in reproducing observed O3 concentrations, and thus further improves our estimates of O3 impacts on human health and crop yields. Our results show that a warm-season increasing trend of O3 in Beijing-Tianjin-Hebei and its surroundings (BTHs), Yangtze River Delta (YRD), Sichuan Basin (SCB) and Pearl River Delta (PRD) regions are 0.32 μg m–3 yr–1, 0.63 μg m–3 yr–1, 0.84 μg m–3 yr–1, and 0.81 μg m–3 yr–1 from 1981 to 2019, respectively. In more recent years, O3 concentrations experience more fluctuations in the four major regions. Our results show that only BTHs have a perceptible increasing trend of 0.81 μg m–3 yr–1 during 2013–2019. Meteorological factors play important roles in modulating the interannual variability of surface O3, wherein synoptic systems (e.g., high-pressure system, Western Pacific subtropical high, tropical cyclone) are closely related to the spatiotemporal distribution of regional O3 via influencing regional weather conditions and transport processes. The estimated annual all-cause premature deaths induced by O3 increased from ~55,900 in 1981 to ~162,000 in 2019 with an increasing trend of ~2,980 deaths yr–1. The annual premature deaths related to respiratory and cardiovascular disease are ~34,200 and ~40,300 in 1998, and ~26,500 and ~79,000 in 2019, having a rate of change of –546 and +1,770 deaths yr–1 during 1998–2019, respectively. The estimated annual crop relative yield loss (RYL) for wheat, rice, soybean, and maize is 3.3 %, 5.5 %, 10.6 %, and 2.6 % in 1981, and increases to 5.9 %, 6.8 %, 15.1 %, and 4.1 % in 2019, respectively. The average annual crop RYL from 1981 to 2019 for wheat, rice, soybean, and maize range between 1.1–7.2 %, 2.7–9.4 %, 6.3–24.8 %, and 0.8–7.4 %, respectively, using different concentration-based metrics. Our study, for the first time, used ML to provide a robust dataset of O3 concentrations over the past four decades in China, enabling a long-term evaluation of O3-induced crop losses and health impacts. These findings are expected to fill the gap in the long-term O3 trend and impact assessment in China. [ABSTRACT FROM AUTHOR]

Ground-level ozone (O3) is a major air pollutant that adversely affects human health and ecosystem productivity. Removal of tropospheric O3 by plant stomatal uptake can in turn cause damage to plant tissues with ramifications for ecosystem and crop health. In many atmospheric and land surface models, the functionality of stomata opening is represented by a bulk stomatal conductance, which is often semi-empirically parameterized and highly fitted to historical observations. A lack of mechanistic linkage to ecophysiological processes such as photosynthesis may render models inadequate to represent plant-mediated responses of atmospheric chemistry to long-term changes in CO2 , climate, and short-lived air pollutant concentrations. A new ecophysiology module was thus developed to mechanistically simulate land - atmosphere exchange of important gas species in GEOS-Chem, a chemical transport model widely used in atmospheric chemistry studies. The implementation not only allows for dry deposition to be coupled with plant ecophysiology but also enables plant and crop productivity and functions to respond dynamically to atmospheric chemical changes. We conduct simulations to evaluate the effects of the ecophysiology module on simulated dry deposition velocity and concentration of surface O3 against an observation-derived dataset known as SynFlux. Our estimated stomatal conductance and dry deposition velocity of O3 are close to SynFlux with root-mean-squared errors (RMSEs) below 0.3 cms-1 across different plant functional types (PFTs), despite an overall positive bias in surface O3 concentration (by up to 16 ppbv). Representing ecophysiology was found to reduce the simulated biases in deposition fluxes from the prior model but worsen the positive biases in simulated O3 concentrations. The increase in positive concentration biases is mostly attributable to the ecophysiology-based stomatal conductance being generally smaller (and closer to SynFlux values) than that estimated by the prior semi-empirical formulation, calling for further improvements in non-stomatal depositional and non-depositional processes relevant for O3 simulations. The estimated global O3 deposition flux is 864 TgO3yr-1 with GEOS-Chem, and the new module decreases this estimate by 92 TgO3yr-1. Estimated global gross primary production (GPP) without O3 damage is 119 PgCyr-1. O3 -induced reduction in GPP is 4.2 PgCyr-1 (3.5 %). An elevated CO2 scenario (580 ppm) yields higher global GPP (+ 16.8 %) and lower global O3 depositional sink (- 3.3 %). Global isoprene emission simulated with a photosynthesis-based scheme is 317.9 TgCyr-1 , which is 31.2 TgCyr-1 (- 8.9 %) less than that calculated using the MEGAN (Model of Emissions of Gases and Aerosols from Nature) emission algorithm. This new model development dynamically represents the two-way interactions between vegetation and air pollutants and thus provides a unique capability in evaluating vegetation-mediated processes and feedbacks that can shape atmospheric chemistry and air quality, as well as pollutant impacts on vegetation health, especially for any timescales shorter than the multidecadal timescale. [ABSTRACT FROM AUTHOR]

Surficial enhanced rock weathering (ERW) is a land-based carbon dioxide removal (CDR) strategy that involves applying crushed silicate rock (e.g., basalt) to agricultural soils. However, unintended biogeochemical interactions with the nitrogen cycle may arise through ERW increasing soil pH as basalt grains undergo dissolution that may reinforce, counteract, or even offset the climate benefits from carbon sequestration. Increases in soil pH could drive changes in the soil emissions of key non-CO2 greenhouse gases, e.g., nitrous oxide (N2O), and trace gases, e.g., nitric oxide (NO) and ammonia (NH3) that affect air quality, and crop and human health. We present the development and implementation of a new improved nitrogen cycling scheme for the land surface model Community Land Model v5 (CLM5), the land component of the Community Earth System Model, allowing evaluation of ERW effects on soil gas emissions. We base the new parameterizations on datasets derived from soil pH responses of N2O, NO and NH3 of ERW field trial and mesocosm experiments with crushed basalt. We successfully validated simulated 'control' (i.e., no ERW) seasonal cycles of soil N2O, NO and NH3 emissions against a wide range of global emission inventories. We benchmark simulated mitigation of soil N2O fluxes in response to ERW against a sub-set of data from ERW field trials in the U.S. Corn Belt. Using the new scheme, we provide a specific example of the effect of large-scale ERW deployment with croplands on soil nitrogen fluxes across five key regions with high potential for CDR with ERW (North America, Brazil, Europe, India, and China). Across these regions, ERW implementation led to marked reductions in N2O and NO (both 18%) with moderate increases in NH3 (2%). Our improved N-cycle scheme within CLM5 has utility for investigating the potential of ERW point-source and regional effects of soil N2O, NO and NH3 fluxes in response to current and future climates. This framework also provides the basis for assessing the implications of ERW for air quality given the role of NO in tropospheric ozone formation, and both NO and NH3 in inorganic aerosol formation. [ABSTRACT FROM AUTHOR]

Ground-level ozone (O3) is a major air pollutant that adversely affects human health and agricultural productivity. Removal of air pollutants including tropospheric O3 from the atmosphere by vegetation is controlled mostly by the process of dry deposition, an important component of which is plant stomatal uptake that can in turn cause damage to plant tissues with ramifications for ecosystem and crop health. In many atmospheric and land surface models, the openness of plant stomata is represented by a bulk stomatal conductance, which is often semi-empirically parameterized, and highly fitted to historical observations. A lack of mechanistic linkage to ecophysiological processes such as photosynthesis may render models insufficient to represent plant-mediated responses of atmospheric chemistry to long-term changes in CO2, climate and short-lived air pollutant concentrations. A new ecophysiology module was thus developed to mechanistically simulate land−atmosphere exchange of important gas species in GEOS-Chem, a chemical transport model widely used in atmospheric chemistry studies. We adopted the formulations from the Joint UK Land Environmental Simulator (JULES) to couple photosynthesis rate, bulk stomatal conductance and isoprene emission rate dynamically. The implementation not only allows dry deposition to be coupled with plant ecophysiology, but also enables plant and crop productivity and functions to respond dynamically to atmospheric chemical changes. The research questions of this study include: 1) how the new ecophysiology module compares with the prior, semi-empirical parameterization in terms of simulating concentration and dry deposition velocity of O3 with respect to site measurement-based estimates; and 2) whether the ecophysiology module simulates vegetation productivity, dry deposition, isoprene emission rate and O3–vegetation interactions reasonably under a present-day and an elevated CO2 concentration. We conduct simulations to evaluate the effects of the ecophysiology module on simulated dry deposition velocity and concentration of surface O3 against an observation-derived dataset known as SynFlux. Our estimated dry deposition velocity of O3 is close to SynFlux dry deposition velocity with root-mean-squared errors (RMSE) ranging from 0.1 to 0.2 cm s–1 across different plant functional types (PFTs), despite an overall positive bias in surface O3 concentration (by up to 16 ppbv). Representing ecophysiology was found to reduce the simulated biases in deposition fluxes from the prior model, but worsen the positive biases in simulated O3 concentrations. The increase in positive concentration biases is mostly attributable to the ecophysiology-based stomatal conductance being generally smaller (and closer to SynFlux values) than that estimated by the prior semi-empirical formulation, calling for further improvements in non-depositional processes relevant for O3 simulations. Estimated global O3 deposition flux is 864 Tg O3 yr–1 with GEOS-Chem, and the new module decreases this estimate by 92 Tg O3 yr–1. Estimated global gross primary product (GPP) is 119 Pg C yr–1, with an O3-induced damage of 4.2 Pg C yr–1 (3.5 %). An elevated CO2 scenario (580 ppm) yields higher global GPP (+16.8 %) and lower global O3 depositional sink (–3.3 %). Global isoprene emission simulated with a photosynthesis-based scheme is 318 Tg C yr–1, which is 31 Tg C yr−1 (−8.9 %) less than that calculated using the MEGAN emission algorithm. This new model development dynamically represents the two-way interactions between vegetation and air pollutants, and thus provides a unique capability in evaluating pollutant impacts on vegetation health and feedback processes that can shape atmospheric chemistry and air quality especially for any timescales shorter than the multidecadal timescale. [ABSTRACT FROM AUTHOR]

While substantial progress has been made to improve our understanding of biogenic isoprene emissions under unstressed conditions, there remain large uncertainties in isoprene emissions under stressed conditions. Here we use the US Drought Monitor (USDM) as a weekly drought severity index and tropospheric columns of formaldehyde (HCHO), the key product of isoprene oxidation, retrieved from the Ozone Monitoring Instrument (OMI) to derive top-down constraints on the response of summertime isoprene emissions to drought stress in the Southeast U.S. (SE US), a region of high isoprene emissions and prone to drought. OMI HCHO column density is found to be 5.3% (mild drought) - 19.8% (severe drought) higher than that in no-drought conditions. A global chemical transport model, GEOS-Chem, with the MEGAN2.1 emission algorithm can simulate this direction of change, but the simulated increases at the corresponding drought levels are 1.4-2.0 times of OMI HCHO, suggesting the need for a drought24 stress algorithm in the model. By minimizing the model-to-OMI differences in HCHO to temperature sensitivity under different drought levels, we derived a top-down drought stress factor (γd_OMI) in GEOS-Chem that parameterizes using water stress and temperature. The algorithm led to an 8.6% (mild drought) - 20.7% (severe drought) reduction in isoprene emissions in the SE US relative to the simulation without it. With γd_OMI the model predicts a non-uniform trend of increase in isoprene emissions with drought severity that is consistent with OMI HCHO and a single site's isoprene flux measurements. Compared with a previous drought stress algorithm derived from the latter, the satellite30 based drought stress factor performs better in capturing the regional scale drought-isoprene responses as indicated by the close-to-zero mean bias between OMI and simulated HCHO columns under different drought conditions. The drought stress algorithm also reduces the model's high bias in organic aerosols (OA) simulations by 6.60% (mild drought) to 11.71% (severe drought) over the SE US compared to the no-stress simulation. The simulated ozone response to the drought stress factor displays a spatial disparity due to the isoprene suppressing effect on oxidants, with an <1 ppb increase in O3 in high-isoprene regions and a 1-3 ppbv decrease in O3 in low-isoprene regions. This study demonstrates the unique value of exploiting long-term satellite observations 36 to develop empirical stress algorithms on biogenic emissions where in situ flux measurements are limited. [ABSTRACT FROM AUTHOR]