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Photochemical Modeling of the Ozark Isoprene Volcano: MEGAN, BEIS, and Their Impacts on Air Quality Predictions Annmarie G. Carlton†,* and Kirk R. Baker‡ † ‡
Department of Environmental Sciences, Rutgers University, New Brunswick, New Jersey 08901, United States Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, United States
bS Supporting Information ABSTRACT: 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, CMAQMEGAN 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.
’ INTRODUCTION Globally, emissions of biogenic volatile organic compounds (BVOCs) are several times greater than all anthropogenic VOC emissions combined.1,2 In the continental U.S., BVOCs comprise approximately 7580% of the 2005 national VOC emission inventory.3 Highly reactive BVOCs affect regional and urban air quality by contributing to secondary pollutants such as ozone and particulate matter (PM).46 Contributions of BVOCs to secondary organic carbon (SOC) are also substantial 710 and an important consideration for climate simulations.7,11 Air quality predictions (e.g., ozone) are highly sensitive to BVOC emissions, in particular isoprene.1214 As a consequence, uncertainty in their estimates can hinder development of effective control strategies to manage air quality.15 Despite the abundance and importance of BVOCs, considerable uncertainty persists because accurate emission algorithms remain elusive for even the most highly emitted and well-studied BVOCs, namely isoprene and monoterpenes.16 Other biogenic emissions such as oxygenated VOCs (oVOCs) and sesquiterpenes are also substantial 1719 and can exert an influence on air quality.8 However these emissions are even less well characterized due to a lack of consistent and widespread observations. Terrestrial biogenic emissions for regional and global scale photochemical models are often developed from the MEGAN 1 r 2011 American Chemical Society
or BEIS 14 emission models. MEGAN and BEIS employ different land use categories, emission factors, and algorithms based on plant type, leaf area index, temperature, and photosynthetically activate radiation (PAR). Predicted isoprene emissions can differ between the two models by more than a factor of 2.20 When applied in a photochemical model, differences in the relative mix of reactive BVOCs could lead to changes in the predominance of particular pathways during oxidative gas-phase chemistry and potentially give rise to different predictions of secondary air pollutants such as ozone and PM2.5. MEGAN and BEIS emissions have been assessed individually with independent techniques. For example, BEIS emissions have been directly estimated using eddy covariance and above canopy flux measurements.21 Widespread evaluation of estimated MEGAN isoprene emissions has been performed using OMI satellite-derived formaldehyde columns coupled with inverse modeling (GEOSCHEM).22 BEIS emissions, as implemented in a regional-scale photochemical model, have been evaluated with measurements of Received: January 6, 2011 Accepted: April 14, 2011 Revised: April 13, 2011 Published: April 26, 2011 4438
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Figure 1. Field study and nearby network monitoring locations used in the evaluation (left), core field study locations in southern Missouri shown at right.
isoprene and ozone.15,23 Warneke et al. (2010) compare MEGAN and BEIS with the Lagrangian particle transport model FLEXPART and found predictions of BVOCs using MEGAN emissions tended to be higher than observations, whereas predictions based on BEIS emissions were typically lower than measured values. Because of the implications for air quality predictions arising from large differences in BVOCs, it is critical that MEGAN and BEIS be applied and evaluated in a 3D photochemical transport model that includes representation of the chemical and physical processes that transform BVOCs to secondary pollutants. Such a comparison, coupled with a detailed evaluation of the applied meteorology is essential because it provides insight as to which biogenic model performs better and might be more appropriate for climate simulations and regional regulatory modeling for development of air quality management plans (e.g., state implementation plans, SIPs). In this work, we quantify how MEGAN and BEIS emission estimates differ for BVOCs, oVOCs and the overall reactivity 24 of biogenic emissions in the model domain. Further, we evaluate how well the Community Multiscale Air Quality (CMAQ) photochemical model predicts BVOCs, ozone, formaldehyde, and secondary organic carbon (SOC) when each emissions model is employed. Predictions are compared with surface and aloft measurements made during a July 1998 intensive field campaign in the Ozarks (OZIE),23 a high BVOC emitting region. Additionally, field study measurements of temperature and solar radiation are evaluated to gauge how well the modeling system characterizes these important meteorological variables that drive biogenic emissions and influence photolytic chemistry.12,25 Prognostic meteorological model estimates of solar radiation in addition to satellite estimates of solar radiation are used as input to BEIS and MEGAN to determine how photosensitive each biogenic model is and how improved PAR estimates translate to ambient BVOC and air quality estimates from the photochemical model.
’ METHODS Photochemical Modeling. The Community Multiscale Air Quality (CMAQ) model v4.7.1 (www.cmaq-model.org) is a 3D Eulerian one-atmosphere photochemical transport model 26,27
used to estimate air quality. CMAQ is applied with the AERO5 aerosol module, which includes ISORROPIA inorganic chemistry 28 and a secondary organic aerosol module.10 CMAQv4.7.1 is applied with sulfur and organic oxidation aqueous phase chemistry 29 and the carbon-bond 2005 (CB05) gas-phase chemistry module.30 All model simulations are applied from June 15 to July 31, 1998, with a Lambert projection centered at (97, 40) and true latitudes at 33 and 45. A domain covering the continental United States with 36 km square sized grid cells provided hourly boundary conditions to a smaller domain covering Missouri, Illinois, Indiana, Kentucky, and northern Arkansas using 12 km square sized grid cells (Figure S1 of the Supporting Information). The vertical atmosphere up to 50 mb is resolved with 34 layers with most resolution in the boundary layer. The first 15 days of the simulation are excluded from the analyses and only predictions from the 12 km model domain are evaluated. Meteorology. Prognostic meteorological inputs are generated with version 3.1 of the Weather Research and Forecasting model (WRF), Advanced Research WRF (ARW) core.31 Important selected physics options include Pleim-Xiu land surface model, Asymmetric Convective Model version 2 planetary boundary layer scheme, KainFritsh cumulus parametrization, Morrison double moment microphysics, RRTMG longwave, and RRTMG shortwave radiation scheme.32 3D analyses nudging for temperature and moisture are applied above the boundary layer only. Analysis nudging for the wind is applied above and below the boundary layer. The WRF model was initialized using the North American Regional Reanalysis (www.emc.ncep.noaa.gov/mmb/ rreanl). In addition to using WRF estimated solar radiation, satellite estimates of PAR are converted to total shortwave downward radiation and used in combination with WRF estimated temperatures to drive both biogenic models. Satellite PAR estimates are taken from the GEWEX Continental Scale International Project and GEWEX Americas Prediction Project Surface Radiation Budget data.33 Satellite radiation is provided for the continental United States at a 0.5 by 0.5 degree resolution (http:// www.atmos.umd.edu/∼srb/gcip/cgi-bin/historic.cgi). Missing hours are replaced by hourly radiation estimates averaged over all valid hours during July of 1998. 4439
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Table 1. Daily Average Domain Total Emissions (TPD) of MEGAN and BEIS Emissions of VOCs and oVOCS CB05
species
description
BEIS
MEGAN
CB05
WRF
SATELLITE
WRF
SATELLITE
SOLRAD
SOLRAD
SOLRAD
SOLRAD
kOH (cm3 molec.1 s 1)
ALD2
acetaldehyde
752
752
1667
1464
k = 5.6 1012 exp(270/T)
ALDX
propionaldehyde
207
207
1107
990
k = 5.1 1012 exp(270/T)
CH4
methane
560
466
and higher aldehydes CO
carbon monoxide
6756
6756
12 198
ETH
ethene
1199
1199
3120
10 907
k = 2.45 1012 exp(1775/T) k = 1.44 1013 þ 3.43 1033[M]
a
2790
ko = 1.0 1028(T/300)4.5
ETHA
ethane
248
248
41
36
k¥= 8.8 1012(T/300)0.85 k = 8.7 1012 exp(1020/T)
ETOH
ethanol
1652
1652
1408
1251
k = 6.9 1012 exp(230/T)
FORM
formaldehyde
960
960
603
539
k = 9.0 1012
IOLE
internal olefin carbon
2072
2072
754
675
k = 1.0 1011 exp(550/T)
ISOP
isoprene
31 191
27 386
76 254
56 460
k = 2.54 1011 exp(407.6/T)
MEOH
methanol
4518
3955
19 936
16 496
k = 7.3 1012 exp(620/T)
NO
nitric oxide
1899
1854
1228
1228
ko = 7.0 1031(T/300)2.6 k¥= 3.6 1011(T/300)0.1
NVOL
nonvolative VOC
OLE
terminal olefin carbon
PAR
paraffin carbon
SESQb TERP
bond (RCdCR)
648
648
321
287
not applicable
1379
1376
1660
1484
k = 3.2 1011
4879
4874
4329
4008
k = 8.1 1013
sesquiterpene
1489
1489
1508
1334
not applicable
terpene
5711
5711
8730
8303
k = 1.5 1011 exp(449/T)
bond (RCdC) bond (CC)
a
Units are cm6 molec.2 s1 b Sesquiterpenes do not affect the gas-phase chemistry of CB05 as implemented in CMAQ4.7.1
Emissions. Anthropogenic emission inputs are based on the 2001 National Emission Inventory (NEI) version 2.34 All emissions were processed using the Sparse Matrix Operator Kernel Emissions (SMOKE) Modeling System.35 Anthropogenic emissions are not adjusted or projected from 2001 to 1998 given the remote location of the field study. Daily hour-specific biogenic emissions based on 1998 meteorology are generated using BEISv3.14 and MEGANv2.04. The BEIS and MEGAN models are used to create gridded, hourly emissions of CO, VOCs, oVOCs, and NOx from vegetation and soils for the U.S., Mexico, and Canada.1,14,36 Both models use meteorological inputs including hourly temperature and shortwave downward radiation, which is internally converted to PAR. BEIS uses vegetation speciation data from the Biogenic Emissions Landuse Database version 3,37 which provides data on the 230 vegetation classes at 1 km resolution over most of North America. MEGAN is applied with version 2.1 of vegetation-based emission factor maps. Field Study and Sampling. The OZIE field study was designed to provide an observational database to evaluate biogenic emissions models used in regional photochemical modeling applications for ozone estimation. Field study measurements were primarily made at 3 locations in southern Missouri, one location in southern Illinois, and one location in southern Indiana 23 (Figure 1). Each of the 3 locations in Missouri consisted of 3 to 5 distinct measurement sites. Surface measurements were made of total nonmethane organic carbon (TNMOC) and speciated VOCs including isoprene, R-pinene, and β-pinene. Some sites measured additional species including
formaldehyde and ozone. Meteorological measurements are also available at these locations for solar radiation, wind speed, wind direction, and temperature. Aloft measurements of isoprene and speciated VOCs were made at one site in southern Missouri using a balloon. Additionally, a roving balloon took measurements at different locations throughout the study period (Figure 1). Aircraft measurements of ozone, isoprene, TNMOC, and formaldehyde were made in the mid boundary layer near the surface measurement sites periodically during the field study.23 Special field study observations are supplemented with routine measurements of other pollutants in the general region of the OZIE experiment. Ozone observations are taken from the AIRS database and speciated PM2.5, namely organic carbon (OC) and elemental carbon (EC), are obtained from the CASTNET and IMPROVE monitor networks. A total of 4 sites within the modeling domain measuring 24 h average speciated PM2.5 (1 in 3 day sampling schedule) are included in the analysis. Semiempirical observational estimates of secondary organic carbon (SOC) are derived using an EC tracer approach.38
’ RESULTS AND DISCUSSION Emissions and VOC Reactivity. Spatial plots of monthly total BVOCs and nitric oxides are shown in Figure S2 of the Supporting Information and hourly emissions of BVOCs are shown in Figure S3 of the Supporting Information. Spatial patterns of the gridded MEGAN and BEIS isoprene, monoterpene and sesquiterpene emissions are qualitatively similar throughout the 4440
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Figure 2. Biases in temperature (top) and shortwave downward radiation (bottom) as compared to field study measurements made during OZIE. Lower and upper edges of the box represent the 25th and 75th percentiles, whiskers extend to 10th and 90th percentiles.
model domain. These similarities arise because the same meteorology and underlying vegetative and land use data was used to drive each model. However, differences in underlying emission algorithms and species mapping result in quantitative estimates of BVOC and oVOC emissions that diverge substantially (Table 1, Figure S3 of the Supporting Information). Daily average (model domain total) emission estimates using 2 different sources of solar radiation are shown for both models in Table 1. The average daily emission flux of total carbon to the atmosphere differs 3040 TonsCarbon day1 km2 between MEGAN and BEIS (for GEWEX and WRF solar radiation respectively), which can have implications for biogeochemical cycling (carbon budget) calculations. Isoprene emissions differ by a factor of ∼2, similar to findings by Warneke et al., (2010) and Hogrefe et al., (2011). MEGAN also estimates higher emission fluxes for monoterpenes, sesquiterpenes, and methane. BEIS does not predict methane emissions. In these simulations, differences in biogenic methane predictions do not affect air quality predictions because CMAQ v4.7.1 employs a spatially and temporally constant methane mixing ratio (i.e., 1.85 ppm). Emissions of many oVOCs are also substantially different. Regardless of solar radiation input, MEGAN emissions of methanol are more than 4 times higher than BEIS estimates. Emissions mapped to the CB05 species ALDX (propionaldehyde and higher aldehydes) are more than 5 times higher with MEGAN, while emissions mapped to IOLE (indicating internal olefins (RCdCR)) are more than 3 times higher with BEIS. These
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species and their model surrogates are rarely measured, making a straightforward determination of which model performs better for oVOC species difficult. The large differences in BVOC and oVOC emissions can affect the VOC reactivity, a critical factor in determining NOx and/or VOC sensitivity for ozone production. MEGAN predicted VOC reactivity (i.e., ∑([VOC]kOHVOC) for BVOC emissions, averaged over all days for the model domain is 2.1 (WRF solar radiation) to 1.8 (GEWEX solar radiation) times greater than predicted using BEIS, when applied to the CB05 gasphase chemical mechanism. Meteorology and Gas-Phase Surface Measurements. Consideration of meteorology predictions is an essential part of evaluating biogenic emissions. WRF-predicted temperature and solar radiation are consistently higher than surface measurements during the OZIE study (Figure 2). These positive biases in WRF suggest that MEGAN and BEIS predicted emissions would be less if the meteorological inputs were corrected. Indeed, MEGAN BVOC predictions are reduced (∼25% averaged over the whole domain for the modeling period) when WRF solar radiation is replaced with the GEWEX satellite product (Table 1 and Figure S3 of the Supporting Information), which compares more favorably to OZIE surface measurements (Figure 2). CMAQ predictions using MEGAN emissions (CMAQ-MEGAN) generated with the GEWEX estimates of PAR compare better with surface level measurements, most notably for isoprene (Figure 3). Residual overprediction of isoprene by the CMAQMEGAN modeling system, with improved solar radiation estimates, may arise in part from the positive bias in temperature (Figure 2). In contrast, BEIS emission estimates demonstrate little photosensitivity when solar radiation estimates are improved and underprediction of isoprene by CMAQ-BEIS worsens (Figure 3). Evaluation of CMAQ predicted monoterpenes is not straightforward. The CB05 gas-phase chemical mechanism, used in these CMAQ simulations, describes all monoterpenes as a single species. During the OZIE field campaign R- and β-pinene, which typically account for 5070% of monoterpenes,18 were measured. CMAQ monoterpene predictions should therefore be ∼1.42 times higher than the measured sum of R- and β-pinene. In this context, CMAQ-MEGAN performs reasonably well (Figure 3). CMAQ-BEIS predictions exhibit a negative bias, even before acknowledging that the model should be higher than the sum of measured values. CMAQ-MEGAN exhibits a large positive bias compared to surface formaldehyde measurements, 29 ppb (WRF solar radiation) and 14 ppb (GEWEX solar radiation) (Table S1 of the Supporting Information and Figure 3). This may be partially explained by the isoprene overprediction, but olefins, methanol, aldehydes, and other species also react to form formaldehyde in the CB05 gas-phase chemical mechanism 30 and the accuracy of the predicted mixing ratios for those species is unknown. CMAQ-BEIS agrees better with surface formaldehyde measurements (Table S1 of the Supporting Information). CMAQ predictions of ozone are similar near field study sites regardless if MEGAN or BEIS is employed, possibly because the area is NOx-limited for ozone production (Figure S4 of the Supporting Information). However, localized differences did arise throughout the model domain for afternoon (noon to 5:00 pm) ozone predictions (Figure S5 of the Supporting Information). Upper Air Measurement Evaluation. Accurate characterization of species’ vertical profiles in atmospheric models is critical to adequately describing long-range transport and scattering 4441
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Figure 3. Evaluation of model predicted isoprene (top row), monoterpenes (2nd row), formaldehyde (3rd row), and ozone (bottom row) at the surface when MEGAN and BEIS are employed to generate biogenic emissions. WRF-SOLRAD indicates WRF estimated solar radiation and SATELLITE SOLRAD indicates GEWEX product solar radiation. 4442
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Figure 4. Evaluation of aloft model predictions using satellite radiation for biogenic models. Balloon isoprene measurements made over grassland (top left) and aircraft measurements are over a forest canopy: isoprene (top right), formaldehyde (bottom left), and ozone (bottom right). Lower and upper edges of each box represent the 25th and 75th percentiles, whiskers extend to 10th and 90th percentiles.
effects that are altitude dependent. Balloon measurements, made over grassy clearings at multiple locations during afternoon hours, indicate that CMAQ predicted isoprene is higher and more variable than aloft measurements when either MEGAN or BEIS is employed (Figure 4, Table S1 of the Supporting Information). However the balloon isoprene measurements may be biased low due to losses on the cartridge monitors.39 CMAQ isoprene predictions compare well with the aircraft measurements (taken during late morning and afternoon hours) in the mid-boundary layer over forest canopy when MEGAN is employed but are biased low when BEIS is used to generate biogenic emissions. Contrary to comparisons at the surface, CMAQ-BEIS predictions of formaldehyde aloft are less than
observations, while CMAQ-MEGAN estimates compare favorably to aircraft measurements (Table S1 of the Supporting Information). Similar to the surface evaluation, CMAQ simulations with either biogenic model yield ozone predictions that are similar, though aloft ozone predictions are consistently biased low compared to measurements (Figure 4). Surface PM Evaluation. Large differences in MEGAN and BEIS BVOC emissions lead to large differences in CMAQpredicted SOC (Figure S6 of the Supporting Information). The OZIE study was designed to investigate biogenic emissions and potential effects on ozone, not PM. To evaluate which biogenic model leads to better SOC predictions by CMAQ, observationally estimated SOC from OC and EC measurements 4443
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Environmental Science & Technology at IMPROVE and CASTNET monitors in the general study area are used. CMAQ-BEIS underestimates SOC in the model domain at all locations on every monitoring day. Even with positive biases in precursor predictions, CMAQ-MEGAN underpredicts SOC as well, except for a few occasions at sites nearest the field study area: northern Arkansas (Upper Buffalo) and western Kentucky (Mammoth Cave). The higher CMAQMEGAN SOC predictions arise from higher estimates of the isoprene, monoterpene, and sesquiterpene precursors. Daily composition of SOC relative to VOC precursor and formation pathway is similar at all monitoring locations when employing MEGAN or BEIS except at Bondville. Without speciated SOC measurements (e.g. refs 40 and 41), it is difficult to determine if the similarity in relative proportion of individual precursor contribution to SOC by both modeling systems are coincidental or an accurate reflection of the relative mix of VOC contribution to SOC in the study area’s atmosphere. Past U.S. field studies in biogenically dominated areas did not focus on biogenic contributions to PM (e.g., OZIE,23 SOS 42). As a consequence, existing data sets are insufficient to fully understand biosphere contribution to and influence on condensed-phase atmospheric chemistry. It is critical that future field studies to investigate biogenic emissions or biosphere/atmosphere interactions include concurrent surface and aloft measurements of trace gases and speciated PM.
’ ASSOCIATED CONTENT
bS
Supporting Information. Table of aggregate CMAQ model performance metrics, figures of photochemical model domains, spacial patterns, total biogenic emissions, and additional figures. This material is available free of charge via the Internet at http://pubs.acs.org.
’ AUTHOR INFORMATION Corresponding Author
*E-mail:
[email protected].
’ ACKNOWLEDGMENT The authors gratefully acknowledge helpful contributions from Allan Beidler, James Beidler, Chris Allen, Lara Reynolds, Rob Gilliam, Marc Houyoux, Rich Mason, Christine Wiedinmyer, George Pouliot, Mike Koerber, and the OZIE participants. ’ REFERENCES (1) Guenther, A.; Karl, T.; Harley, P.; Wiedinmyer, C.; Palmer, P. I.; Geron, C. Estimates of global terrestrial isoprene emissions using MEGAN (model of emissions of gases and aerosols from nature). Atmos. Chem. Phys. 2006, 6, 3181–3210. (2) Rypdal, K.; Rive, N.; Berntsen, T.; Fagerli, H.; Klimont, Z.; Mideksa, T. K.; Fuglestvedt, J. S. Climate and air quality-driven scenarios of ozone and aerosol precursor abatement. Environ. Sci. Pol. 2009, 12, 855–869. (3) United States Environmental Protection Agency, National Emissions Inventory, http://www.epa.gov/ttnchie1/net/2005inventory. html. (4) Chameides, W. L.; Lindsay, R. W.; Richardson, J.; Kiang, C. S. The role of biogenic hydrocarbons in urban photochemical smogAtlanta as a case-study. Science 1988, 241, 1473–1475.
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