Model Of Emissions Of Gases And Aerosols From Nature Research Articles

Brazilian Atmospheric Inventories – BRAIN: a comprehensive database of air quality in Brazil

Abstract. Developing air quality management systems to control the impacts of air pollution requires reliable data. However, current initiatives do not provide datasets with large spatial and temporal resolutions for developing air pollution policies in Brazil. Here, we introduce the Brazilian Atmospheric Inventories (BRAIN), the first comprehensive database of air quality and its drivers in Brazil. BRAIN encompasses hourly datasets of meteorology, emissions, and air quality. The emissions dataset includes vehicular emissions derived from the Brazilian Vehicular Emissions Inventory Software (BRAVES), industrial emissions produced with local data from the Brazilian environmental agencies, biomass burning emissions from FINN – Fire INventory from the National Center for Atmospheric Research (NCAR), and biogenic emissions from the Model of Emissions of Gases and Aerosols from Nature (MEGAN) (https://doi.org/10.57760/sciencedb.09858, Hoinaski et al., 2023a; https://doi.org/10.57760/sciencedb.09886, Hoinaski et al., 2023b). The meteorology dataset has been derived from the Weather Research and Forecasting Model (WRF) (https://doi.org/10.57760/sciencedb.09857, Hoinaski and Will, 2023a; https://doi.org/10.57760/sciencedb.09885, Hoinaski and Will, 2023c). The air quality dataset contains the surface concentration of 216 air pollutants produced from coupling meteorological and emissions datasets with the Community Multiscale Air Quality Modeling System (CMAQ) (https://doi.org/10.57760/sciencedb.09859, Hoinaski and Will, 2023b; https://doi.org/10.57760/sciencedb.09884, Hoinaski and Will, 2023d). We provide gridded data in two domains, one covering the Brazilian territory with 20×20 km spatial resolution and another covering southern Brazil with 4×4 km spatial resolution. This paper describes how the datasets were produced, their limitations, and their spatiotemporal features. To evaluate the quality of the database, we compare the air quality dataset with 244 air quality monitoring stations, providing the model's performance for each pollutant measured by the monitoring stations. We present a sample of the spatial variability of emissions, meteorology, and air quality in Brazil from 2019, revealing the hotspots of emissions and air pollution issues. By making BRAIN publicly available, we aim to provide the required data for developing air quality policies on municipal and state scales, especially for under-developed and data-scarce municipalities. We also envision that BRAIN has the potential to create new insights into and opportunities for air pollution research in Brazil.​​​​​​​

Sensitivity of the WRF-Chem v4.4 simulations of ozone and formaldehyde and their precursors to multiple bottom-up emission inventories over East Asia during the KORUS-AQ 2016 field campaign

Abstract. In this study, the WRF-Chem v4.4 model was utilized to evaluate the sensitivity of O3 simulations with three bottom-up emission inventories (EDGAR-HTAP v2 and v3 and KORUS v5) using surface and aircraft data in East Asia during the Korea-United States Air Quality (KORUS-AQ) campaign period in 2016. All emission inventories were found to reproduce the diurnal variations of O3 and its main precursor NO2 as compared to the surface monitor data. However, the spatial distributions of the daily maximum 8 h average (MDA8) O3 in the model do not completely align with the observations. The model MDA8 O3 had a negative (positive) bias north (south) of 30° N over China. All simulations underestimated the observed CO by 50 %–60 % over China and South Korea. In the Seoul Metropolitan Area (SMA), EDGAR-HTAP v2 and v3 and KORUS v5 simulated the vertical shapes and diurnal patterns of O3 and other precursors effectively, but the model underestimated the observed O3, CO, and HCHO concentrations. Notably, the model aromatic volatile organic compounds (VOCs) were significantly underestimated with the three bottom-up emission inventories, although the KORUS v5 shows improvements. The model isoprene estimations had a positive bias relative to the observations, suggesting that the Model of Emissions of Gases and Aerosols from Nature (MEGAN) version 2.04 overestimated isoprene emissions. Additional model simulations were conducted by doubling CO and VOC emissions over China and South Korea to investigate the causes of the model O3 biases and the effects of the long-range transport on the O3 over South Korea. The doubled CO and VOC emission simulations improved the model O3 simulations for the local-emission-dominant case but led to the model O3 overestimations for the transport-dominant case, which emphasizes the need for accurate representations of the local VOC emissions over South Korea.

Arctic Heatwaves Could Significantly Influence the Isoprene Emissions From Shrubs

AbstractWarming climate in the Arctic is leading to an increase in isoprene emission from ecosystems. We assessed the influence of temperature on isoprene emission from Arctic willows with laboratory and field measurements. Our findings indicate that the hourly temperature response curve of Salix spp., the dominant isoprene emitting shrub in the Arctic, aligns with that of temperate plants. In contrast, the isoprene capacity of willows exhibited a more substantial than expected response to the mean ambient temperature of the previous day, which is much stronger than the daily temperature response predicted by the current version of the Model of Emissions of Gases and Aerosols from Nature (MEGAN). With a modified algorithm from this study, MEGAN predicts 66% higher isoprene emissions for Arctic willows during an Arctic heatwave. However, despite these findings, we are still unable to fully explain the high temperature sensitivity of isoprene emissions from high latitude ecosystems.

Updating Biogenic Volatile Organic Compound (BVOC) Emissions With Locally Measured Emission Factors in South China and the Effect on Modeled Ozone and Secondary Organic Aerosol Production

AbstractBiogenic volatile organic compounds (BVOCs) emitted from terrestrial plants contribute substantially to ozone (O3) and secondary organic aerosol (SOA) formation in the troposphere. Accurate estimation of BVOC emissions is highly challengeable with a variety of uncertainties, one of which is the use of default emission factors (EFs) particularly for underrepresented regions without local data. In this study, locally measured BVOC‐EFs in south China, a subtropical region with abundant vegetation, were used to update regional BVOC emissions as estimated by the Model of Emissions of Gases and Aerosols from Nature (MEGAN). These EFs were recently determined in situ with characterized dynamic chambers for the emissions of isoprene, monoterpenes, and sesquiterpenes from tree species. The Community Multiscale Air Quality (CMAQ) model was then employed to see how much the regional O3 and SOA production is altered with the updated BVOC emissions. Results revealed lower BVOC emission estimates in south China when using the localized EFs than the MEGAN default ones, particularly for sesquiterpenes with a notable average reduction rate of approximately 40%. Using the updated BVOC emissions improved model O3 predictions in all seasons when compared to surface O3 monitoring, yet the lower BVOC emissions resulted in modeled O3 and SOA concentrations decreased by up to −6 ppb and −1.5 μg m−3, respectively, throughout south China. This study highlights the significance of localized EFs in refining emission estimates and air quality predictions in regions with a wealth of vegetation.

Assessment of isoprene and near-surface ozone sensitivities to water stress over the Euro-Mediterranean region

Abstract. Plants emit biogenic volatile organic compounds (BVOCs) in response to changes in environmental conditions (e.g. temperature, radiation, soil moisture). In the large family of BVOCs, isoprene is by far the strongest emitted compound and plays an important role in ozone chemistry, thus affecting both air quality and climate. In turn, climate change may alter isoprene emissions by increasing temperature as well as the occurrence and intensity of severe water stresses that alter plant functioning. The Model of Emissions of Gases and Aerosols from Nature (MEGAN) provides different parameterizations to account for the impact of water stress on isoprene emissions, which essentially reduces emissions in response to the effect of soil moisture deficit on plant productivity. By applying the regional climate–chemistry model RegCM4chem coupled to the Community Land Model CLM4.5 and MEGAN2.1, we thus performed sensitivity simulations to assess the effects of water stress on isoprene emissions and near-surface ozone levels over the Euro-Mediterranean region and across the drier and wetter summers over the 1992–2016 period using two different parameterizations of the impact of water stress implemented in the MEGAN model. Over the Euro-Mediterranean region and across the simulated summers, water stress reduces isoprene emissions on average by nearly 6 %. However, during the warmest and driest selected summers (e.g. 2003, 2010, 2015) and over large isoprene-source areas (e.g. the Balkans), decreases in isoprene emissions range from −20 % to −60 % and co-occur with negative anomalies in precipitation, soil moisture and plant productivity. Sustained decreases in isoprene emissions also occur after prolonged or repeated dry anomalies, as observed for the summers of 2010 and 2012. Although the decrease in isoprene emissions due to water stress may be important, it only reduces near-surface ozone levels by a few percent due to a dominant VOC-limited regime over southern Europe and the Mediterranean Basin. Overall, over the selected analysis region, compared to the old MEGAN parameterization, the new one leads to localized and 25 %–50 % smaller decreases in isoprene emissions and 3 %–8 % smaller reductions in near-surface ozone levels.

Emission characteristics of biogenic volatile organic compounds in a subtropical pristine forest of southern China

Emission characteristics of biogenic volatile organic compounds (BVOCs) from dominant tree species in the subtropical pristine forests of China are extremely limited. Here we conducted in situ field measurements of BVOCs emissions from representative mature evergreen trees by using dynamic branch enclosures at four altitude gradients (600–1690 m a.s.l.) in the Nanling Mountains of southern China. Composition characteristics as well as seasonal and altitudinal variations were analyzed. Standardized emission rates and canopy-scale emission factors were then calculated. Results showed that BVOCs emission intensities in the wet season were generally higher than those in the dry season. Monoterpenes were the dominant BVOCs emitted from most broad-leaved trees, accounting for over 70% of the total. Schima superba, Yushania basihirsuta and Altingia chinensis had relatively high emission intensities and secondary pollutant formation potentials. The localized emission factors of isoprene were comparable to the defaults in the Model of Emissions of Gases and Aerosols from Nature (MEGAN), while emission factors of monoterpenes and sesquiterpenes were 2 to 58 times of those in the model. Our results can be used to update the current BVOCs emission inventory in MEGAN, thereby reducing the uncertainties of BVOCs emission estimations in forested regions of southern China.

Intra- and interannual changes in isoprene emission from central Amazonia

Abstract. Isoprene emissions are a key component in biosphere–atmosphere interactions, and the most significant global source is the Amazon rainforest. However, intra- and interannual variations in biological and environmental factors that regulate isoprene emission from Amazonia are not well understood and, thereby, are poorly represented in models. Here, with datasets covering several years of measurements at the Amazon Tall Tower Observatory (ATTO) in central Amazonia, Brazil, we (1) quantified canopy profiles of isoprene mixing ratios across seasons of normal and anomalous years and related them to the main drivers of isoprene emission – solar radiation, temperature, and leaf phenology; (2) evaluated the effect of leaf age on the magnitude of the isoprene emission factor (Es) from different tree species and scaled up to canopy with intra- and interannual leaf age distribution derived by a phenocam; and (3) adapted the leaf age algorithm from the Model of Emissions of Gases and Aerosols from Nature (MEGAN) with observed changes in Es across leaf ages. Our results showed that the variability in isoprene mixing ratios was higher between seasons (max during the dry-to-wet transition seasons) than between years, with values from the extreme 2015 El Niño year not significantly higher than in normal years. In addition, model runs considering in situ observations of canopy Es and the modification on the leaf age algorithm with leaf-level observations of Es presented considerable improvements in the simulated isoprene flux. This shows that MEGAN estimates of isoprene emission can be improved when biological processes are mechanistically incorporated into the model.

Updated isoprene and terpene emission factors for the Interactive BVOC (iBVOC) emission scheme in the United Kingdom Earth System Model (UKESM1.0)

Abstract. Biogenic volatile organic compounds (BVOCs) influence atmospheric composition and climate, and their emissions are affected by changes in land use and land cover (LULC). Current Earth system models calculate BVOC emissions using parameterisations involving surface temperature, photosynthetic activity, CO2 and vegetation type and use emission factors (EFs) to represent the influence of vegetation on BVOC emissions. We present new EFs for the Interactive BVOC Emission Scheme (iBVOC) used in the United Kingdom Earth System Model (UKESM), based on those used by the Model of Emissions of Gases and Aerosols from Nature (MEGAN) v2.1 scheme. Our new EFs provide an alternative to the current EFs used in iBVOC, which are derived from older versions of MEGAN and the Organizing Carbon and Hydrology in Dynamic Ecosystem (ORCHIDEE) emission scheme. We show that current EFs used by iBVOC result in an overestimation of isoprene emissions from grasses, particularly C4 grasses, due to an oversimplification that incorporates the EF of shrubs (high isoprene emitters) into the EF for C3 and C4 grasses (low isoprene emitters). The current approach in iBVOCs assumes that C4 grasses are responsible for 40 % of total simulated isoprene emissions in the present day, which is much higher than other estimates of ∼ 0.3 %–10 %. Our new isoprene EFs substantially reduce the amount of isoprene emitted by C4 grasslands, in line with observational studies and other modelling approaches, while also improving the emissions from other known sources, such as tropical broadleaf trees. Similar results are found from the change to the terpene EF. With the new EFs, total global isoprene and terpene emissions are within the range suggested by the literature. While the existing model biases in the isoprene column are slightly exacerbated with the new EFs, other drivers of this bias are also noted. The disaggregation of shrub and grass EFs provides a more faithful description of the contribution of different vegetation types to BVOC emissions, which is critical for understanding BVOC emissions in the pre-industrial and under different future LULC scenarios, such as those involving wide-scale reforestation or deforestation. Our work highlights the importance of using updated and accurate EFs to improve the representation of BVOC emissions in Earth system models and provides a foundation for further improvements in this area.

Development of an ecophysiology module in the GEOS-Chem chemical transport model version 12.2.0 to represent biosphere–atmosphere fluxes relevant for ozone air quality

Abstract. 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 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-stomatal depositional and non-depositional processes relevant for O3 simulations. The 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 production (GPP) without O3 damage is 119 Pg C yr−1. O3-induced reduction in GPP is 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 317.9 Tg C yr−1, which is 31.2 Tg C yr−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.

Impacts of land cover changes on biogenic emission and its contribution to ozone and secondary organic aerosol in China

Abstract. The greening impacts on China from 2000 to 2017 led to an increase in vegetated areas and thus enhanced biogenic volatile organic compound (BVOC) emissions. BVOCs are regarded as important precursors for ozone (O3) and secondary organic aerosol (SOA). As a result, accurate estimation of BVOC emissions is critical to understand their impacts on air quality. In this study, the Model of Emissions of Gases and Aerosols from Nature (MEGAN) v2.1 was used to investigate the impact of different leaf area index (LAI) and land cover (LC) datasets on BVOC emissions in China in 2016, and the effects on O3 and SOA were evaluated based on the Community Multiscale Air Quality (CMAQ) modeling system. Three LAI satellite datasets of the Global LAnd Surface Satellite (GLASS), the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD15A2H version 6 (MOD15), and the Copernicus Global Land Service (CGLS), as well as three LC satellite datasets of the MODIS MCD12Q1 LC products, the Copernicus Climate Change Service (C3S) LC products, and the CGLS LC products, were used in five parallel experiments (cases: C1–C5). Results show that changing LAI and LC datasets of the model input has an impact on BVOC estimations. BVOC emissions in China ranged from 25.42 to 37.39 Tg in 2016 and were mainly concentrated in central and southeastern China. Changing the LC inputs for the MEGAN model has a more significant difference in BVOC estimates than using different LAI datasets. The combination of C3S LC and GLASS LAI performs better in the CMAQ model, indicating that it is the better choice for BVOC estimations in China. The highest contribution of BVOCs to O3 and SOA can reach 12 ppb and 9.8 µg m−3, respectively. Changing the MEGAN inputs further impacts the concentrations of O3 and SOA, especially changing LC datasets. The relative difference between MCD12Q1 LC and C3S LC is over 52 % and 140 % in O3 and biogenic SOA (BSOA) in central and eastern China. The BSOA difference is mainly attributed to the isoprene SOA (ISOA), a major contributor to BSOA. The relative differences in ISOA between different cases are up to 160 % in eastern China. Therefore, our results suggest that the uncertainties in MEGAN inputs should be fully considered in future O3 and SOA simulations.

The influence of vegetation drought stress on formaldehyde and ozone distributions over a central European city

To estimate the effect of vegetation stress and changes in biogenic volatile organic compound (BVOC) emissions on urban ozone (O3) levels we perform a systematic, observation-based analysis of the relationship between formaldehyde (HCHO) mixing ratios, meteorological parameters, measurement-based drought indicators and O3 over the central European city of Vienna, Austria. In addition, numerical models SURface EXternalisée (SURFEX), Model of Emissions of Gases and Aerosols from Nature (MEGAN) Vers.2.1 and 3 and MOdèle de Chimie A Grande Echelle (MOCAGE) are combined to estimate the soil moisture, the spatial distribution and drought response of isoprene emissions, and the resulting distribution of HCHO in the atmosphere. To analyse the effect of drought during spring and summer we contrast observations during dry and reference years. Our results show that the observed HCHO can be explained using the simulated isoprene emissions as well as observed and simulated vegetation drought responses. HCHO mixing ratios differ strongly between dry and reference seasons. Spring-time precipitation deficits facilitate reduced HCHO mixing ratios due to delayed and weakened plant growth. In consequence also O3 burdens are lowered due to reduced BVOC precursor emissions. These reductions occur despite radiation levels being higher than during the reference year, illustrating the strong potential of spring-time BVOC emissions to modulate urban O3 burdens. Conversely, during summer elevated O3 levels occur during local drought conditions. These are driven by advected isoprene originating from nearby forest areas, which are not affected by drought. Our results regarding elevated summer-time O3 burdens under vegetation heat and drought stress are in good agreement with previous work.

High emission rates and strong temperature response make boreal wetlands a large source of isoprene and terpenes

Abstract. Wetlands cover only 3 % of the global land surface area, but boreal wetlands are experiencing an unprecedented warming of four times the global average. These wetlands emit isoprene and terpenes (including monoterpenes (MT), sesquiterpenes (SQT), and diterpenes (DT)), which are climate-relevant highly reactive biogenic volatile organic compounds (BVOCs) with an exponential dependence on temperature. In this study, we present ecosystem-scale eddy covariance (EC) fluxes of isoprene, MT, SQT, and DT (hereafter referred to together as terpenes) at Siikaneva, a boreal fen in southern Finland, from the start to the peak of the growing season of 2021 (19 May 2021 to 28 June 2021). These are the first EC fluxes reported using the novel state-of-the-art Vocus proton transfer reaction mass spectrometer (Vocus-PTR) and the first-ever fluxes reported for DTs from a wetland. Isoprene was the dominant compound emitted by the wetland, followed by MTs, SQTs, and DTs, and they all exhibited a strong exponential temperature dependence. The Q10 values, the factor by which terpene emissions increases for every 10 ∘C rise in temperature, were up to five times higher than those used in most BVOC models. During the campaign, the air temperature peaked above 31 ∘C on 21–22 June 2021, which is abnormally high for boreal environments, and the maximum flux for all terpenes coincided with this period. We observed that terpene emissions were elevated after this abnormally “high-temperature stress period”, indicating that past temperatures alter emissions significantly. The standardized emission factor (EF) of the fen for isoprene (EFiso) was 11.1 ± 0.3 nmol m−2 s−1, which is at least two times higher than in previous studies and as high as the emission factors typical for broadleaf and other forests in the lower latitudes. We observed EFMT of 2.4 ± 0.1 nmol m−2 s−1, EFSQT of 1.3 ± 0.03 nmol m−2 s−1, higher than typical for needle leaf and broadleaf tree functional types, and EFDT of 0.011 ± 0.001 nmol m−2 s−1. We also compared the landscape average emissions to the model of emissions of gases and aerosols from nature (MEGAN) v2.1 and found that the emissions were underestimated by over 9 times for isoprene, over 300 times for MTs, and 800 times for SQTs. Our results show that due to very high EFs and high sensitivity to increasing temperatures, these high-latitude ecosystems can be a large source of terpenes to the atmosphere, and anthropogenic global warming could induce much higher BVOC emissions from wetlands in the future.

Optimizing the Isoprene Emission Model MEGAN With Satellite and Ground‐Based Observational Constraints

AbstractIsoprene is a hydrocarbon emitted in large quantities by terrestrial vegetation. It is a precursor to several air quality and climate pollutants including ozone. Emission rates vary with plant species and environmental conditions. This variability can be modeled using the Model of Emissions of Gases and Aerosols from Nature (MEGAN). MEGAN parameterizes isoprene emission rates as a vegetation‐specific standard rate which is modulated by scaling factors that depend on meteorological and environmental driving variables. Recent experiments have identified large uncertainties in the MEGAN temperature response parameterization, while the emission rates under standard conditions are poorly constrained in some regions due to a lack of representative measurements and uncertainties in landcover. In this study, we use Bayesian model‐data fusion to optimize the MEGAN temperature response and standard emission rates using satellite‐ and ground‐based observational constraints. Optimization of the standard emission rate with satellite constraints reduced model biases but was highly sensitive to model input errors and drought stress and was found to be inconsistent with ground‐based constraints at an Amazonian field site, reflecting large uncertainties in the satellite‐based emissions. Optimization of the temperature response with ground‐based constraints increased the temperature sensitivity of the model by a factor of five at an Amazonian field site but had no impact at a UK field site, demonstrating significant ecosystem‐dependent variability of the isoprene emission temperature sensitivity. Ground‐based measurements of isoprene across a wide range of ecosystems will be key for obtaining an accurate representation of isoprene emission temperature sensitivity in global biogeochemical models.

Evaluation of biogenic emissions from three different vegetation distributions in South Korea

Map of plant functional type (PFT) is one of key information in estimating the bottom-up biogenic emissions. This study investigated the performance of three different maps of PFT on biogenic emissions in South Korea: i) PFT map from the MODerate resolution Imaging Spectroradiometer (MODIS) satellite sensor onboard Terra-/Aqua-satellites (MPFT); ii) PFT map from the Environmental Geographic Information System (EGIS) provided by the Korean Ministry of Environment (EPFT); and iii) PFT map from the Forest Geographic Information System (FGIS) established by the Korea Forest Service (FPFT). These three different vegetation distributions were used as input information into the Model of Emissions of Gases and Aerosols from Nature (MEGAN) model. The biogenic emissions estimated by the MEGAN model simulations were then evaluated by comparisons between the Community Multi-scale Air Quality (CMAQ) simulated mixing ratios of biogenic species with ground- and aircraft-borne mixing ratios during the period of the Korea–United States Air Quality (KORUS-AQ) campaign. The analyses found that the simulation using the FPFT map, which has been regarded as ‘ground truth’, produced the best results in terms of several statistical metrics. For example, among the three experiments, the simulation with the FPFT map produced the best index of agreement (IOA) of 0.76 and the lowest normalized mean bias (NMB) of 5.61%, in comparison with ground-based isoprene observations. The simulations with the MPFT map also performed reasonably, showing low NMBs of −42.13% and −14.87% for the isoprene and the first-generation products of isoprene, respectively, in comparison with the DC-8 airborne observations. In addition, the applications of the MPFT map to the MEGAN modeling showed significant overestimations in the mixing ratios of biogenic species over the SoBaek (SB) mountain ranges. It was believed that this was due to the overestimated density of broadleaf deciduous temperate trees over the SB mountain ranges in the MPFT map. On the other hand, the EPFT map showed the worst performances, which might be related to crude classification of vegetation. This study also suggests two important possibilities. First, the current isoprene-related photochemistry appears to be highly uncertain, based on large underestimations of the first-generation products of isoprene, in comparison with observations. Second, the emission factors of monoterpenes in the MEGAN model may be too small, based on large underestimations of monoterpenes, in comparison with observations.

Modeling the biogenic isoprene emission and its impact on ozone pollution in Zhejiang province, China

Isoprene is the most abundantly emitted biogenic volatile organic compound (BVOC), which plays an essential role in producing tropospheric ozone (O3). However, the simulations of isoprene emissions have not been sufficiently verified over Yangtze River Delta (YRD), and few studies have specifically addressed its impact on O3 formation. In this study, we simulated the isoprene emissions in Zhejiang Province (ZJ), a region with the largest BVOC emission in YRD, in August 2020 using the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and the latest Moderate Resolution Imaging Spectroradiometer (MODIS) products, and investigated its contributions to O3 using the Weather Research and Forecasting (WRF)-Community Multiscale Air Quality (CMAQ) model. The model has a good performance on isoprene simulations over urban and suburban areas, with mean biases of −0.16–0.12 ppb, but underestimated the concentrations at forest sites (mainly due to bamboo). Regionally, the simulated formaldehyde concentrations over forests agree well with the satellite observations. In August 2020, the total isoprene emission in ZJ was 125.1 GgC, with higher emissions in western ZJ and relatively lower emissions in eastern coastal regions. The spatial pattern of isoprene concentrations is similar to its emissions, and the maximum daytime average concentrations are above 3.5 ppb. The spatial pattern of its contribution to daily maximum 8 h average O3 concentrations is significantly different from the emissions and concentrations, which shows a higher impact in northern ZJ (>6 ppb) and relatively lower impact in southern ZJ (1–3 ppb). The mean contribution over ZJ is 8.9 %, with daily variation in the range of 3.1 % to 13.4 %. For different cities, the monthly mean contribution is in the range of 4.6 % to 14.3 %, and the maximum daily contribution reaches about 25 %. These findings help understand the summertime O3 pollution in ZJ and the YRD region of China.

Modeling Isoprene Emission Response to Drought and Heatwaves Within MEGAN Using Evapotranspiration Data and by Coupling With the Community Land Model.

We introduce two new drought stress algorithms designed to simulate isoprene emission with the Model of Emissions of Gases and Aerosols from Nature (MEGAN) model. The two approaches include the representation of the impact of drought on isoprene emission with a simple empirical approach for offline MEGAN applications and a more process-based approach for online MEGAN in Community Land Model (CLM) simulations. The two versions differ in their implementation of leaf-temperature impacts of mild drought. For the online version of MEGAN that is coupled to CLM, the impact of drought on leaf temperature is simulated directly and the calculated leaf temperature is considered for the estimation of isoprene emission. For the offline version, we apply an empirical algorithm derived from whole-canopy flux measurements for simulating the impact of drought ranging from mild to severe stage. In addition, the offline approach adopts the ratio (f PET) of actual evapotranspiration to potential evapotranspiration to quantify the severity of drought instead of using soil moisture. We applied the two algorithms in the CLM-CAM-chem (the Community Atmosphere Model with Chemistry) model to simulate the impact of drought on isoprene emission and found that drought can decrease isoprene emission globally by 11% in 2012. We further compared the formaldehyde (HCHO) vertical column density simulated by CAM-chem to satellite HCHO observations. We found that the proposed drought algorithm can improve the match with the HCHO observations during droughts, but the performance of the drought algorithm is limited by the capacity of the model to capture the severity of drought.

A Modeling Approach for Quantifying Human-Beneficial Terpene Emission in the Forest: A Pilot Study Applying to a Recreational Forest in South Korea.

(1) Background: Recent economic developments in South Korea have shifted people’s interest in forests from provisioning to cultural services such as forest healing. Although policymakers have attempted to designate more forests for healing purposes, there are few established standards for carrying out such designations based on the quantified estimation. (2) Methods: We suggest a modeling approach to estimate and analyze the emission rate of human-beneficial terpenes. For this purpose, we adopted and modified the Model of Emissions of Gases and Aerosols from Nature (MEGAN), a commonly used biogenic volatile organic compounds (BVOCs) estimation model which was suitable for estimating the study site’s terpene emissions. We estimated the terpene emission rate for the whole year and analyzed the diurnal and seasonal patterns. (3) Results: The results from our model correspond well with other studies upon comparing temporal patterns and ranges of values. According to our study, the emission rate of terpenes varies significantly temporally and spatially. The model effectively predicted spatiotemporal patterns of terpene emission in the study site. (4) Conclusions: The modeling approach in our study is suitable for quantifying human-beneficial terpene emission and helping policymakers and forest managers plan the efficient therapeutic use of forests.

Modeling Biogenic Volatile Organic Compounds Emissions and Subsequent Impacts on Ozone Air Quality in the Sichuan Basin, Southwestern China

Biogenic volatile organic compounds (BVOCs) impact atmospheric oxidation capacity and regional air quality through various biogeochemistry processes. Accurate estimation of BVOC emissions is crucial for modeling the fate and transport of air pollutants in chemical transport models. Previous modeling characterizes the spatial variability of BVOCs while estimated BVOC emissions show large uncertainties, and the impacts of BVOC emissions on ozone (O3) air quality are not well understood. In this study, we estimate the BVOC emissions by model of emissions of gases and aerosols from nature (MEGAN) v2.1 and MEGAN v3.1 over the Sichuan Basin (SCB) situated in southwestern China for 2017. Further, the critical role of BVOC emissions on regional O3 pollution is illustrated with a CMAQ modeled O3 episode in summer 2017. Annual BVOC emissions over the SCB in 2017 are estimated to be 1.8 × 106 tons with isoprene emissions as high as 7.3 × 105 tons. Abundant BVOC emissions are depicted over the southern and southeastern SCB, in contrast to the relatively low emissions of BVOC over the Chengdu Plain and northeastern SCB. CMAQ simulations depict a strong influence of BVOC on ambient O3 formation over densely forested regions including southern SCB and Chongqing city, accounting for 10% of daily maximum hourly O3 concentration (DM1h O3) and 6% of daily maximum 8-h average O3 (MDA8h O3) concentrations in July 2017. Over the severe O3 episode in summer 2017, sensitivity experiments indicate that enhanced BVOC emissions contribute substantially to basin-wide O3 concentrations and elevate peak O3 levels by 36.5 and 31.2 μg/m3 for the southern SCB and Chengdu Plain, respectively. This work identifies robustly important effects of BVOC emissions on O3 exceedance events over the SCB and contributes insight into pursuing an O3 abatement strategy with full consideration of potential contributions from BVOC emissions.

Impact of Drought on Isoprene Fluxes Assessed Using Field Data, Satellite-Based GLEAM Soil Moisture and HCHO Observations from OMI

Biogenic volatile organic compounds (BVOCs), primarily emitted by terrestrial vegetation, are highly reactive and have large effects on the oxidizing potential of the troposphere, air quality and climate. In terms of global emissions, isoprene is the most important BVOC. Droughts bring about changes in the surface emission of biogenic hydrocarbons mainly because plants suffer water stress. Past studies report that the current parameterization in the state-of-the-art Model of Emissions of Gases and Aerosols from Nature (MEGAN) v2.1, which is a function of the soil water content and the permanent wilting point, fails at representing the strong reduction in isoprene emissions observed in field measurements conducted during a severe drought. Since the current algorithm was originally developed based on potted plants, in this study, we update the parameterization in the light of recent ecosystem-scale measurements of isoprene conducted during natural droughts in the central U.S. at the Missouri Ozarks AmeriFlux (MOFLUX) site. The updated parameterization results in stronger reductions in isoprene emissions. Evaluation using satellite formaldehyde (HCHO), a proxy for BVOC emissions, and a chemical-transport model, shows that the adjusted parameterization provides a better agreement between the modelled and observed HCHO temporal variability at local and regional scales in 2011–2012, even if it worsens the model agreement in a global, long-term evaluation. We discuss the limitations of the current parameterization, a function of highly uncertain soil properties such as porosity.

Modeling sensitivities of BVOCs to different versions of MEGAN emission schemes in WRF-Chem (v3.6) and its impacts over eastern China

Abstract. Biogenic volatile organic compounds (BVOCs) simulated by current air quality and climate models still have large uncertainties, which can influence atmospheric chemistry and secondary pollutant formation. These modeling sensitivities are primarily due to two sources. One originates from different treatments in the physical and chemical processes associated with the emission rates of BVOCs. The other is errors in the specification of vegetation types and their distribution over a specific region. In this study, the version of the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) updated by the University of Science and Technology of China (USTC version of WRF-Chem) from the public WRF-Chem(v3.6) is used. The modeling results over eastern China with different versions (v1.0, v2.0, v3.0) of the Model of Emissions of Gases and Aerosols from Nature (MEGAN) in WRF-Chem are examined or documented. Sensitivity experiments with these three versions of MEGAN and two vegetation datasets are conducted to investigate the difference of three MEGAN versions in modeling BVOCs and its dependence on the vegetation distributions. The experiments are also conducted for spring (April) and summer (July) to examine the seasonality of the modeling results. The results indicate that MEGAN v3.0 simulates the largest amount of biogenic isoprene emissions over eastern China. The different performance among MEGAN versions is primarily due to their different treatments of applying emission factors and vegetation types. In particular, the results highlight the importance of considering the sub-grid vegetation fraction in estimating BVOC emissions over eastern China, which has a large area of urbanization. Among all activity factors, the temperature-dependent factor dominates the seasonal change of activity factor in all three versions of MEGAN, while the different response to the leaf area index (LAI) change determines the difference among the three versions in seasonal variation of BVOC emissions. The simulated surface ozone concentration due to BVOCs can be significantly different (ranging from 1 to more than 10 ppbv in some regions) among the experiments with three versions of MEGAN, which is mainly due to their impacts on surface VOCs and NOx concentrations. Theoretically MEGAN v3.0 that is coupled with the land surface scheme and considers the sub-grid vegetation effect should overcome previous versions of MEGAN in WRF-Chem. However, considering uncertainties of retrievals and anthropogenic emissions over eastern China, it is still difficult to apply satellite retrievals of formaldehyde and/or limited sparse in situ observations to constrain the uncertain parameters or functions in BVOC emission schemes and their impacts on photochemistry and ozone production. More accurate vegetation distribution and measurements of biogenic emission fluxes and species concentrations are still needed to better evaluate and optimize models.