Biogenic Emission Inventory System Research Articles

High-Resolution Modeling of Summertime Biogenic Isoprene Emissions in New York City.

As cities strive for ambitious increases in tree canopy cover and reductions in anthropogenic volatile organic compound (AVOC) emissions, accurate assessments of the impacts of biogenic VOCs (BVOCs) on air quality become more important. In this study, we aim to quantify the impact of future urban greening on ozone production. BVOC emissions in dense urban areas are often coarsely represented in regional models. We set up a high-resolution (30 m) MEGAN (The Model of Emissions of Gases and Aerosols from Nature version 3.2) to estimate summertime biogenic isoprene emissions in the New York City metro area (NYC-MEGAN). Coupling an observation-constrained box model with NYC-MEGAN isoprene emissions successfully reproduced the observed isoprene concentrations in the city core. We then estimated future isoprene emissions from likely urban greening scenarios and evaluated the potential impact on future ozone production. NYC-MEGAN predicts up to twice as much isoprene emissions in NYC as the coarse-resolution (1.33 km) Biogenic Emission Inventory System version 3.61 (BEIS) on hot summer days. We find that BVOCs drive ozone production on hot summer days, even in the city core, despite large AVOC emissions. If high isoprene emitting species (e.g., oak trees) are planted, future isoprene emissions could increase by 1.4-2.2 times in the city core, which would result in 8-19 ppbv increases in peak ozone on ozone exceedance days with current NOx concentrations. We recommend planting non- or low-isoprene emitting trees in cities with high NOx concentrations to avoid an increase in the frequency and severity of future ozone exceedance events.

Comparison between Spatially Resolved Airborne Flux Measurements and Emission Inventories of Volatile Organic Compounds in Los Angeles.

Los Angeles is a major hotspot for ozone and particulate matter air pollution in the United States. Ozone and PM2.5 in this region have not improved substantially for the past decade, despite a reduction in vehicular emissions of their precursors, NOx and volatile organic compounds (VOCs). This reduction in "traditional" sources has made the current emission mixture of air pollutant precursors more uncertain. To map and quantify emissions of a wide range of VOCs in this urban area, we performed airborne eddy covariance measurements with wavelet analysis. VOC fluxes measured include tracers for source categories, such as traffic, vegetation, and volatile chemical products (VCPs). Mass fluxes were dominated by oxygenated VOCs, with ethanol contributing ∼29% of the total. In terms of OH reactivity and aerosol formation potential, terpenoids contributed more than half. Observed fluxes were compared with two commonly used emission inventories: the California Air Resources Board inventory and the combination of the Biogenic Emission Inventory System with the Fuel-based Inventory of Vehicle Emissions combined with Volatile Chemical Products (FIVE-VCP). The comparison shows mismatches regarding the amount, spatial distribution, and weekend effects of observed VOC emissions with the inventories. The agreement was best for typical transportation related VOCs, while discrepancies were larger for biogenic and VCP-related VOCs.

Direct observations of NOx emissions over the San Joaquin Valley using airborne flux measurements during RECAP-CA 2021 field campaign

Abstract. Nitrogen oxides (NOx) are principle components of air pollution and serve as important ozone precursors. As the San Joaquin Valley (SJV) experiences some of the worst air quality in the United States, reducing NOx emissions is a pressing need, yet quantifying current emissions is complicated due to a mixture of mobile and agriculture sources. We performed airborne eddy covariance flux measurements during the Re-Evaluating the Chemistry of Air Pollutants in California (RECAP-CA) field campaign in June 2021. Combining footprint calculations and land cover statistics, we disaggregate the observed fluxes into component fluxes characterized by three different land cover types. On average, we find emissions of 0.95 mg N m−2 h−1 over highways, 0.43 mg N m−2 h−1 over urban areas, and 0.30 mg N m−2 h−1 over croplands. The calculated NOx emissions using flux observations are utilized to evaluate anthropogenic emissions inventories and soil NOx emissions schemes. We show that two anthropogenic inventories for mobile sources, EMFAC (EMission FACtors) and FIVE (Fuel-based Inventory for Vehicle Emissions), yield strong agreement with emissions derived from measured fluxes over urban regions. Three soil NOx schemes, including the MEGAN v3 (Model of Emissions of Gases and Aerosols from Nature), BEIS v3.14 (Biogenic Emission Inventory System), and BDISNP (Berkeley–Dalhousie–Iowa Soil NO Parameterization), show substantial underestimates over the study domain. Compared to the cultivated soil NOx emissions derived from measured fluxes, MEGAN and BEIS are lower by more than 1 order of magnitude, and BDISNP is lower by a factor of 2.2. Despite the low bias, observed soil NOx emissions and BDISNP present a similar spatial pattern and temperature dependence. We conclude that soil NOx is a key feature of the NOx emissions in the SJV and that a biogeochemical-process-based model of these emissions is needed to simulate emissions for modeling air quality in the region.

Improving ozone simulations in the Great Lakes Region: The role of emissions, chemistry, and dry deposition

The Great Lakes Region of the US continues experiencing exceedances of the ozone (O3) standards, despite years of emissions controls. In part, this is due to interactions between emissions from surrounding large cities (e.g., Chicago) and meteorology, which is heavily influenced by the presence of the Great Lakes. These complex meteorology-emissions interactions pose a challenge to fully capture O3 dynamics, particularly near shores of the lakes, where high O3 levels are often experienced. In a simulation with the Community Multiscale Air Quality (CMAQ) model, using inputs as typically constructed, the model tends to be biased high. A literature review indicated that NOx emissions from mobile sources, possibly overestimated in the 2011 National Emission Inventory (NEI), or the version of the Carbon Bond chemical mechanism used in CMAQ could be responsible for high biases of O3. As such, a series of sensitivity tests was conducted to identify potential causes for this bias, including emissions biases (e.g., biogenic VOCs, anthropogenic NOx), chemical mechanism choice, and O3 dry deposition to fresh water, for high O3 periods in July 2011. The base model/emissions configuration used the following: Carbon Bond mechanism CB05, biogenic emissions using Biogenic Emission Inventory System (BEIS), and anthropogenic emissions from the 2011 National Emissions Inventory (NEI). Meteorological inputs were developed using the Weather Research and Forecasting (WRF) model (version 3.8.1). Simulated daily maximum 8-h average O3 without and with a cutoff of 60 ppb (referred to as MDA8 O3 and elevated MDA8 O3 hereafter, respectively) were evaluated against measurements. The evaluation showed a high bias in MDA8 O3 across the domain, particularly at coastal sites (by ∼6 ppb), while elevated MDA8 O3 (i.e., greater than 60 ppb) was biased low, with exceptions centered along the shore of Lake Michigan. Using the CB6 chemical mechanism or 50% reduction of NOx emissions from on-road mobile sources led to substantial domain-wide decreases in O3 from the base case, and the model performance improved, particularly along the Lake Michigan shoreline and for the western domain. However, elevated MDA8 O3 was more biased against measurements, compared to the model performance in the base case, except at a few sites along the shoreline. Using the Model of Emissions of Gases and Aerosols from Nature (MEGAN) instead of BEIS to estimate biogenic emissions, or increasing dry deposition of O3 to fresh water by a factor of ten (which is unrealistic), had minor impacts on simulated O3 over land. But, combining MEGAN with CB6 resulted in improved elevated MDA8 O3 simulation along the western coast of Lake Michigan. Finally, using CB6 combined with a 30% reduction of on-road mobile NOx emissions and MEGAN led to the best performance. Two companion papers investigate how meteorological modeling can be improved. Together, the recommended modeling system could serve as a starting point for future O3 modeling in the region.

Implementation of different big-leaf canopy reduction functions in the Biogenic Emission Inventory System (BEIS) and their impact on concentrations of oxidized nitrogen species in northern Europe

Canopy reduction describes NO2 flux reduction at leaf stomata. We implemented the big-leaf reduction approaches of Wang et al. (1998) and Yienger and Levy (1995) in the Biogenic Emission Inventory System (BEIS) and compared them with the BEIS standard approach. The different reduction functions lead to a reduction of 17 Gg N or 27 Gg N respectively of nitrogen emission in comparison to the standard approach which reduces the nitrogen flux by about 1 Gg N in the three summer months of 2012. These are significant differences to the standard approach. The concentration reduction of oxidized reactive nitrogen in the model area shows also a significant reduction. While concentration reduction in central europe is low, in more rural regions of Europe, concentration changes are considerably higher. The calculated concentrations of NO2 show a significant improvement of the model performance when compared to EMEP observations in central Europe. This study favors the implementation and use of canopy reduction factors, especially the parameterization of Wang et al. (1998), for regional and global emission models for reasons of model physical correctness and improved model results.

The Variability of Ozone Sensitivity to Anthropogenic Emissions with Biogenic Emissions Modeled by MEGAN and BEIS3

In this study, we examined how modeled ozone concentrations respond to changes in anthropogenic emissions when different modeled emissions of biogenic volatile organic compounds (BVOCs) are used. With biogenic emissions estimated by the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and the Biogenic Emissions Inventory System Version 3 (BEIS3), the Community Multi-scale Air Quality with the High-order Direct Decouple Method (CMAQ-HDDM) simulations were conducted to acquire sensitivity coefficients. For the case study, we chose 17–26 August 2007, when the Southern Korean peninsula experienced region-wide ozone standard exceedances. The results show that modeled local sensitivities of ozone to anthropogenic emissions in certain NOx-saturated places can differ significantly depending on the method used to estimate BVOC emission, with an opposite trend of ozone changes alongside NOx reductions often shown in model runs using MEGAN and BEIS3. Findings of increased ozone concentrations with one model and decreased ozone concentrations with the other model implies that estimating BVOCs emissions is an important element in predicting variability in ozone concentration and determining the responses of ozone concentrations to emission changes, a discovery that may lead to different policy decisions related to air quality improvement. Quantitatively, areas in the 3-km modeling domain that experienced daily maximum one-hour ozone concentrations greater than 120 ppb (MDA1O3) showed differences of over 20 ppb in MDA1O3 values between model runs with MEGAN and BEIS3. For selected monitoring sites, the maximum difference in relative daily maximum eight-hour ozone concentrations (MDA8O3) response between the methods to model BVOCs was 4.2 ppb in MDA8O3 when we adopted a method similar to the Relative Reduction Factor used by the US Environmental Protection Agency (EPA).

Improved MEGAN predictions of biogenic isoprene in the contiguous United States

Isoprene emitted from biogenic sources significantly contributes to ozone and secondary organic aerosol formation in the troposphere. The Model of Emissions of Gases and Aerosols from Nature (MEGAN) has been widely used to estimate isoprene emissions from local to global scales. However, previous studies have shown that MEGAN significantly over-predicts isoprene emissions in the contiguous United States (US). In this study, ambient isoprene concentrations in the US were simulated by the Community Multiscale Air Quality (CMAQ) model (v5.0.1) using biogenic emissions estimated by MEGAN v2.10 with several different gridded isoprene emission factor (EF) fields. Best isoprene predictions were obtained with the EF field based on the Biogenic Emissions Landcover Database v4 (BELD4) from US EPA for its Biogenic Emission Inventory System (BEIS) model v3.61 (MEGAN-BEIS361). A seven-month simulation (April to October 2011) of isoprene emissions with MEGAN-BEIS361 and ambient concentrations using CMAQ shows that observed spatial and temporal variations (both diurnal and seasonal) of isoprene concentrations can be well predicted at most non-urban monitors using isoprene emission estimation from the MEGAN-BEIS361 without significant biases. The predicted monthly average vertical column density of formaldehyde (HCHO), a reactive volatile organic compound with significant contributions from isoprene oxidation, generally agree with the spatial distribution of HCHO column density derived using satellite data collected by the Ozone Monitoring Instrument (OMI), although summer month vertical column densities in the southeast US were overestimated, which suggests that isoprene emission might still be overestimated in that region. The agreement between observation and prediction may be further improved if more accurate PAR values, such as those derived from satellite-based observations, were used in modeling the biogenic emissions.

Evaluation of improved land use and canopy representation in BEIS v3.61 with biogenic VOC measurements in California

Abstract. Biogenic volatile organic compounds (BVOC) participate in reactions that can lead to secondarily formed ozone and particulate matter (PM) impacting air quality and climate. BVOC emissions are important inputs to chemical transport models applied on local to global scales but considerable uncertainty remains in the representation of canopy parameterizations and emission algorithms from different vegetation species. The Biogenic Emission Inventory System (BEIS) has been used to support both scientific and regulatory model assessments for ozone and PM. Here we describe a new version of BEIS which includes updated input vegetation data and canopy model formulation for estimating leaf temperature and vegetation data on estimated BVOC. The Biogenic Emission Landuse Database (BELD) was revised to incorporate land use data from the Moderate Resolution Imaging Spectroradiometer (MODIS) land product and 2006 National Land Cover Database (NLCD) land coverage. Vegetation species data are based on the US Forest Service (USFS) Forest Inventory and Analysis (FIA) version 5.1 for 2002–2013 and US Department of Agriculture (USDA) 2007 census of agriculture data. This update results in generally higher BVOC emissions throughout California compared with the previous version of BEIS. Baseline and updated BVOC emission estimates are used in Community Multiscale Air Quality (CMAQ) Model simulations with 4 km grid resolution and evaluated with measurements of isoprene and monoterpenes taken during multiple field campaigns in northern California. The updated canopy model coupled with improved land use and vegetation representation resulted in better agreement between CMAQ isoprene and monoterpene estimates compared with these observations.

Constraining NOx emissions using satellite NO2 measurements during 2013 DISCOVER-AQ Texas campaign

Reliable emission inventories are key to precisely model air pollutant concentrations. The relatively large reduction in NOx emissions that is well corroborated by satellite and in-situ observations over southeast Texas has resulted in discrepancies between observations and regional model simulations based on the National Emission Inventory (NEI) provided every three years in U.S. In this study, a Bayesian inversion of OMI tropospheric NO2 is conducted to update anthropogenic sources of NEI-2011 and soil-biogenic sources from BEIS3 (Biogenic Emission Inventory System version 3) over southeast Texas and west Louisiana during the 2013 DISCOVER-AQ Texas campaign. Results reveal that influences of the a priori profile used in OMI NO2 retrieval play a significant role in inconsistencies between model and satellite observations, which should be mitigated. A posteriori emissions are produced using the regional Community Multiscale Air Quality (CMAQ) model associated with Decoupled Direct Method (DDM) sensitivity analysis. The inverse estimate suggests a reduction in area (44%), mobile (30%), and point sources (60%) in high NOx areas (ENOx> 0.2 mol/s), and an increase in soil (∼52%) and area emissions (37%) in low NOx regions (ENOx< 0.02 mol/s). The reductions in anthropogenic sources in high NOx regions are attributed to both uncertainty of the priori and emissions policies, while increases in area and soil-biogenic emissions more likely resulted from under-estimation of ships emissions, and the Yienger- Levy scheme used in BEIS respectively. In order to validate the accuracy of updated NOx emissions, CMAQ simulation was performed and results were evaluated with independent surface NO2 measurements. Comparing to surface monitoring sites, we find improvements (before and after inverse modeling) for MB (1.95, −0.30 ppbv), MAB (3.65, 2.60 ppbv), RMSE (6.13, 4.37 ppbv), correlation (0.68, 0.69), and IOA (0.76, 0.82). The largest improvement is seen for morning time surface NO2 for which RMSE and MB are reduced considerably by ∼60% (5.05 to 2.07 ppbv) and 109% (3.49 to −0.3 ppbv). However, under-prediction of model NO2 in Houston on 09/25–09/26 likely resulting from unprecedented local NOx sources from the Houston Ship Channel (HSC) becomes more evident. Overall, results show that use of OMI tropospheric NO2 columns can substantially reduce the uncertainty of bottom-up emissions for a regional study which should be extended to larger domains (e.g. entire U.S. or North America).

Impact of sulfur dioxide oxidation by Stabilized Criegee Intermediate on sulfate

We revise the Carbon Bond chemical mechanism to explicitly represent three Stabilized Criegee Intermediates (SCIs) and their subsequent reactions with sulfur dioxide, water monomer, and water dimer, and incorporate the reactions into the Community Multiscale Air Quality model. The reaction of sulfur dioxide with SCI produces sulfuric acid which partitions into sulfate. We examine the impact of sulfur dioxide oxidation by SCI on sulfate using two different measured rate constants for the reaction of sulfur dioxide and SCI. When we use the higher rate constant and emissions estimates from the Biogenic Emissions Inventory System, it enhances monthly mean sulfate in summer by ∼20% in biogenically active areas. Enhancements are driven primarily by SCI produced from the reactions of biogenically derived alkenes and ozone. The use of the lower rate constant only marginally enhances sulfate since it is 65 times lower than the higher rate constant. We performed several sensitivity analyses to investigate the impacts of uncertain biogenic emissions and SCI loss rates. When we use the higher rate constant and emissions estimates from the Model of Emissions of Gases and Aerosols from Nature, it enhances monthly mean sulfate by ∼75%. A simulation using the lowest reported rate constant for the reaction of SCI and water indicated the maximum enhancement of sulfate from this chemistry was up to 4 μg/m3 over a 24-h period in some locations in the Southeastern U.S. Predictions without the SCI reaction are lower than observed sulfate while predictions with the SCI reaction improve the agreements with observations.

자연배출량이 수도권 고농도 오존 사례에 미치는 영향범위 추정: 2004년과 2007년 6월 사례를 중심으로

Biogenic Volatile Organic Compound (BVOC) emissions are estimated with BEIS3.12 (Biogenic Emissions Inventory System version 3.12) over the Seoul Metropolitan Area (SMA) and then used in CMAQ (Community Multiscale Air Quality) simulations for two high ozone episodes in 2004 and 2007 June. The first- and second-order sensitivity coefficients of ozone to BVOC emissions are estimated with High-order Decoupled Direct Method (HDDM) simulation in order to estimate the influence of BVOC emissions on ozone using the Zero-Out Contribution (ZOC) approach. ZOC analysis shows that relative contribution of BVOC emissions on daily maximum 1-hr ozone is as high as 30% for high ozone days above 100 ppb. However simulated isoprene concentrations were over-estimated by a factor of 2 when compared to the observations at the PAMS (Photochemical Air Monitoring Station) for the 2007 episode. When assumed that actual BVOC emissions are 50% less than estimated, the ZOC of BVOC emissions on daily maximum ozone drops by more than 10 ppb for the episode. The result indicates that uncertainty in BVOC emissions may have significant impact on high ozone prediction in the SMA.

Photochemical Modeling of the Ozark Isoprene Volcano: MEGAN, BEIS, and Their Impacts on Air Quality Predictions

Biogenic volatile organic compounds (BVOCs) contribute substantially to atmospheric carbon, exerting influence on air quality and climate. Two widely used models, the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and the Biogenic Emission Inventory System (BEIS) are employed to generate emissions for application in the CMAQ air quality model. Predictions of isoprene, monoterpenes, ozone, formaldehyde, and secondary organic carbon (SOC) are compared to surface and aloft measurements made during an intensive study in the Ozarks, a large isoprene emitting region. MEGAN and BEIS predict spatially similar emissions but magnitudes differ. The total VOC reactivity of the emissions, as developed for the CB05 gas-phase chemical mechanism, is a factor of 2 different between the models. Isoprene estimates by CMAQ-MEGAN are higher and more variable than surface and aloft measurements, whereas CMAQ-BEIS predictions are lower. CMAQ ozone predictions are similar and compare well with measurements using either MEGAN or BEIS. However, CMAQ-MEGAN overpredicts formaldehyde. CMAQ-BEIS SOC predictions are lower than observational estimates for every sample. CMAQ-MEGAN underpredicts SOC ∼ 80% of the time, despite overprediction of precursor VOCs. CMAQ-MEGAN isoprene predictions improve when prognostically predicted solar radiation is replaced with the GEWEX satellite product. CMAQ-BEIS does not exhibit similar photosensitivity.

Impact of Biogenic Emission Uncertainties on the Simulated Response of Ozone and Fine Particulate Matter to Anthropogenic Emission Reductions

ABSTRACT The role of emissions of volatile organic compounds and nitric oxide from biogenic sources is becoming increasingly important in regulatory air quality modeling as levels of anthropogenic emissions continue to decrease and stricter health-based air quality standards are being adopted. However, considerable uncertainties still exist in the current estimation methodologies for biogenic emissions. The impact of these uncertainties on ozone and fine particulate matter (PM2.5) levels for the eastern United States was studied, focusing on biogenic emissions estimates from two commonly used biogenic emission models, the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and the Biogenic Emissions Inventory System (BEIS). Photochemical grid modeling simulations were performed for two scenarios: one reflecting present day conditions and the other reflecting a hypothetical future year with reductions in emissions of anthropogenic oxides of nitrogen (NOx). For ozone, the use of MEGAN emissions resulted in a higher ozone response to hypothetical anthropogenic NOx emission reductions compared with BEIS. Applying the current U.S. Environmental Protection Agency guidance on regulatory air quality modeling in conjunction with typical maximum ozone concentrations, the differences in estimated future year ozone design values (DVF) stemming from differences in biogenic emissions estimates were on the order of 4 parts per billion (ppb), corresponding to approximately 5% of the daily maximum 8-hr ozone National Ambient Air Quality Standard (NAAQS) of 75 ppb. For PM2.5, the differences were 0.1–0.25 μg/m3 in the summer total organic mass component of DVFs, corresponding to approximately 1–2% of the value of the annual PM2.5 NAAQS of 15 μg/m3. Spatial variations in the ozone and PM2.5 differences also reveal that the impacts of different biogenic emission estimates on ozone and PM2.5 levels are dependent on ambient levels of anthropogenic emissions. IMPLICATIONS The findings presented in this study demonstrate that uncertainties in biogenic emission estimates due to different emission models can have a significant effect on the model estimates of ozone and PM2.5 concentrations; specifically, the changes in these concentrations due to reductions in anthropogenic emissions considered in regulatory modeling scenarios. These results point to the need for further research aimed at improving biogenic emission estimates as well as better characterizing their dependency on environmental factors and the fate of these emissions once released into the atmosphere.

A mechanistic modeling system for estimating large scale emissions and transport of pollen and co-allergens.

Allergic airway diseases represent a complex health problem which can be exacerbated by the synergistic action of pollen particles and air pollutants such as ozone. Understanding human exposures to aeroallergens requires accurate estimates of the spatial distribution of airborne pollen levels as well as of various air pollutants at different times. However, currently there are no established methods for estimating allergenic pollen emissions and concentrations over large geographic areas such as the United States. A mechanistic modeling system for describing pollen emissions and transport over extensive domains has been developed by adapting components of existing regional scale air quality models and vegetation databases. First, components of the Biogenic Emissions Inventory System (BEIS) were adapted to predict pollen emission patterns. Subsequently, the transport module of the Community Multiscale Air Quality (CMAQ) modeling system was modified to incorporate description of pollen transport. The combined model, CMAQ-pollen, allows for simultaneous prediction of multiple air pollutants and pollen levels in a single model simulation, and uses consistent assumptions related to the transport of multiple chemicals and pollen species. Application case studies for evaluating the combined modeling system included the simulation of birch and ragweed pollen levels for the year 2002, during their corresponding peak pollination periods (April for birch and September for ragweed). The model simulations were driven by previously evaluated meteorological model outputs and emissions inventories for the eastern United States for the simulation period. A semi-quantitative evaluation of CMAQ-pollen was performed using tree and ragweed pollen counts in Newark, NJ for the same time periods. The peak birch pollen concentrations were predicted to occur within two days of the peak measurements, while the temporal patterns closely followed the measured profiles of overall tree pollen. For the case of ragweed pollen, the model was able to capture the patterns observed during September 2002, but did not predict an early peak; this can be associated with a wider species pollination window and inadequate spatial information in current land cover databases. An additional sensitivity simulation was performed to comparatively evaluate the dispersion patterns predicted by CMAQ-pollen with those predicted by the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model, which is used extensively in aerobiological studies. The CMAQ estimated concentration plumes matched the equivalent pollen scenario modeled with HYSPLIT. The novel pollen modeling approach presented here allows simultaneous estimation of multiple airborne allergens and other air pollutants, and is being developed as a central component of an integrated population exposure modeling system, the Modeling Environment for Total Risk studies (MENTOR) for multiple, co-occurring contaminants that include aeroallergens and irritants.

남한지역 자연 배출량 산정 및 대기질 모사를 이용한 평가

BEIS2 (Biogenic Emissions Inventory System version 2) and BEIS3.12 (BEIS version 3.12) were used to estimate hourly biogenic emissions over South Korea using a set of vegetation and meteorological data simulated with the MM5 (Mesoscale Model version 5). Two biogenic emission models utilized different emission factors and showed different responses to solar radiations, resulting in about <TEX>$10{\sim}20%$</TEX> difference in the nationwide isoprene emission estimates. Among the 11-vegetation classes, it was found that mixed forest and deciduous forest are the most important vegetation classes producing isoprene emissions over South Korea comprising <TEX>${\sim}90%$</TEX> of the total. The simulated isoprene concentrations over Seoul metropolitan area show that diurnal and daily variations match relatively well with the PAMS (Photochemical Air Monitoring Station) measurements during the period of June 3<TEX>${\sim}$</TEX>June 10, 2004. Compared to BEIS2, BEIS3.12 yielded <TEX>${\sim}35%$</TEX> higher isoprene concentrations during daytime and presented better matches to the high peaks observed over the Seoul area. This study showed that the importance of vegetation data and emission factors to estimate biogenic emissions. Thus, it is expected to improve domestic vegetation categories and emission factors in order to better represent biogenic emissions over South Korea.

Monoterpene and Sesquiterpene Emission Estimates for the United States

Biogenic volatile organic compounds (BVOC) contribute significantly to the formation of ozone and secondary organic aerosol (SOA). The Model of Emissions of Gases and Aerosols from Nature (MEGANv2.02) is used to estimate emissions of isoprene, monoterpenes (MT), and sesquiterpenes (SQT) across the United States. Compared to the Biogenic Emission Inventory System (BEIS3.0), MEGANv2.02 estimates higher isoprene but lower MT emissions for July 2001 and January 2002. A sensitivity study of SQT and MT emission factors and algorithm parameters was conducted by assigning values to four plant functional types (PFTs) using both recent measurements and literature values. The standard deviations of the emissions factors within these PFTs were two to four times the averages because of the variation in experimental basal emissions rate data. More recently published SQT and MT basal emission rates are generally lower than those reported in the literature through 2004. With the new emissions factors, monthly average SQT emission rates for the contiguous United States are equal to 16% of the MT emissions during July and 9% of the emissions during January. The SQT emissions distribution is strongly influenced by the grass and crop PFT, for which SQT emissions data are quite limited.

Estimation of vegetative mercury emissions in China

Vegetative mercury emissions were estimated within the framework of Biogenic Emission Inventory System (BEIS3 V3.11). In this estimation, the 19 categories of U.S. Geological Survey landcover data were incorporated to generate the vegetation-specific mercury emissions in a 81-km Lambert Conformal model grid covering the total Chinese continent. The surface temperature and cloud-corrected solar radiation from a Mesoscale Meteorological model (MM5) were retrieved and used for calculating the diurnal variation. The implemented emission factors were either evaluated from the measured mercury flux data for forest, agriculture and water, or assumed for other land fields without available flux data. Annual simulations using the MM5 data were performed to investigate the seasonal emission variation. From the sensitivity analysis using two sets of emission factors, the vegetative mercury emissions in China domain were estimated to range from a lower limit of 79 x 10(3) kg/year to an upper limit of 177 x 10(3) kg/year. The modeled vegetative emissions were mainly generated from the eastern and southern China. Using the estimated data, it is shown that mercury emissions from vegetation are comparable to that from anthropogenic sources during summer. However, the vegetative emissions decrease greatly during winter, leaving anthropogenic sources as the major sources of emission.

Relationships among canopy scale energy fluxes and isoprene flux derived from long-term, seasonal eddy covariance measurements over a hardwood forest

The flux of isoprene, one of the more reactive biogenic volatile organic compounds, was measured using eddy covariance techniques on a continuous basis during the 2000–2002 growing seasons at a mixed hardwood forest in northern lower MI. Daytime fluxes of isoprene and both sensible ( H) and latent heat flux (LE) were linearly correlated with a positive slope on a daily basis, but the slopes of these relationships varied from one day to the next. Under drought conditions and longer time periods, LE fluxes were suppressed yet isoprene emissions were enhanced; thus, the slope of the isoprene to LE relationship was increased. For example, seasonally averaged LE fluxes were reduced in 2000 as a result of reduced rainfall, and average isoprene fluxes were 1.5 times greater in 2000 compared to years 2001 and 2002. The strong daily correlation between isoprene fluxes and associated energy fluxes is an important relationship that should be accurately reflected in canopy models used for estimating biogenic emissions. In addition, in cases where land surface model output includes latent heat fluxes, the latent heat fluxes may be used as a surrogate for above canopy light and temperature to provide a simple estimate of isoprene emissions. Observed isoprene fluxes are compared to the Biogenic Emission Inventory System (BEIS3) biogenic emission model and to a canopy scale biogenic emission model (WSU-BEIS) that includes a leaf energy budget and accounts for vertical changes in light and temperature through the canopy. Comparison of the emission models with observations showed that the fractional gross errors in isoprene flux estimates were approximately 37% for both models in 2001 and 2002, but increased to approximately 62% in 2000 when less rain occurred and LE fluxes were reduced. The BEIS3 model does not treat sensible or latent heat flux, but the simple scaling and leaf energy budget used in WSU-BEIS yields estimates of LE within approximately 50% of observations. Estimates of sensible heat flux with WSU-BEIS were larger than observed and indicate that the simple scaling approach may not be capable of treating all of the dynamics of canopy energy transfer accurately. Nonetheless, the strong relationships observed between isoprene flux and the energy flux terms provide a basis for testing these and other canopy models used for estimates of biogenic emissions.

Development of a processor in BEIS3 for estimating vegetative mercury emission in the continental United States

We have developed a regression-based processor for estimating vegetative mercury emission within the framework of Biogenic Emission Inventory System Version 3.11 (BEIS3 V3.11). In this development, we incorporated the 230 categories of USGS landcover data to generate the vegetation-specific mercury emission in a 36-km Lambert Conformal model grid covering the continental United States (CONUS). The surface temperature and cloud-corrected solar radiation from a Mesoscale Meteorological model (MM5) were retrieved and used for calculating the diurnal variation. The implemented emission factors were either evaluated from the measured mercury flux data for selected tree species, wetland and water, or assumed for the tree species without available flux data. Annual simulations using the 2001 USEPA MM5 data were performed to investigate the seasonal emission variation. From our sensitivity analysis using three sets of emission factors, we estimated that the vegetative mercury emission in the CONUS domain ranges from a lower limit of 31 ton yr −1 to an upper limit of 140 ton yr −1, with the best estimate at 44 ton yr −1. The modeled vegetative emission was mainly contributed from southeast US. Using the best estimate data, it is shown that mercury emission from vegetation is comparable to that from anthropogenic sources in summer (nearly half of the total emission). However, the vegetative emission decreases greatly in winter, leaving anthropogenic sources as the major emission source (>90% in winter months). Modeling assessment indicates that including vegetative emission (44 ton yr −1) can force an increase of ambient mercury concentration of up to 0.2 ng m −3 in summer midday, but has little impact on dry deposition of mercury. Additional emission factors can be implemented in the model once further mercury flux data become available.

Estimation of biogenic volatile organic compounds emissions in subtropical island—Taiwan

Elevated tropospheric ozone is harmful to human health and plants. It is formed through the photochemical reactions involving volatile organic compounds (VOCs) and nitrogen oxides (NO x ). The elevated ozone episodes occur mainly in summer months in the United States, while the high-ozone episodes frequently occur during the fall in Taiwan. The unique landscape of Taiwan produces tremendous amounts of biogenic VOCs in the mountain regions that are adjacent to concentrated urban areas. The urban areas, in turn, generate prodigious amounts of anthropogenic emissions. Biogenic VOC emissions have direct influence on tropospheric ozone formation. To explore the air quality problems in Taiwan, this study attempts to develop a biogenic VOC emission model suitable for air quality applications in Taiwan. The emission model is based on the Biogenic Emissions Inventory System Version 2 and coupled with a detailed Taiwan land use database. The 1999 total Taiwan biogenic VOC emissions were estimated at 214,000 metric tons. The emissions of isoprene, monoterpenes, and other VOCs were about 37.2%, 30.4%, and 32.4% of total biogenic VOC emissions, respectively. The annual total biogenic VOC emission per unit area was more than two times the value of that in any European country, implying that detailed emissions estimates in any size of region will benefit the global biogenic emission inventories.