A43D 0191 N li it G h Ch i t C l d ithA43D-0191 Near explicit Gas phase Chemistry Coupled withA43D 0191 Near explicit Gas phase Chemistry Coupled withNear-explicit Gas-phase Chemistry Coupled withNear explicit Gas phase Chemistry Coupled with p p y pp p y pE t i A M h i L ki t Eth l (E85) E h t i FExtensive Aqueous Mechanism: Looking at Ethanol (E85) Exhaust in a FogExtensive Aqueous Mechanism: Looking at Ethanol (E85) Exhaust in a FogExtensive Aqueous Mechanism: Looking at Ethanol (E85) Exhaust in a FogExtensive Aqueous Mechanism: Looking at Ethanol (E85) Exhaust in a Fogq g ( ) g

Di L Gi b h M k Z J bDiana L Ginnebaugh Mark Z JacobsonDiana L. Ginnebaugh, Mark Z. JacobsonDiana L. Ginnebaugh, Mark Z. JacobsonDepartment of Civil and Environmental Engineering Atmosphere/Energy Stanford University moongdes@stanford edu and Jacobson@stanford eduDepartment of Civil and Environmental Engineering Atmosphere/Energy Stanford University moongdes@stanford edu and Jacobson@stanford eduDepartment of Civil and Environmental Engineering, Atmosphere/Energy, Stanford University, moongdes@stanford.edu and Jacobson@stanford.edup g g p gy y g @ @

Introduction Model Setup and Emissions DataBig Picture Results continuedIntroduction Model Setup and Emissions DataBig Picture Results, continuedIntroduction Model Setup and Emissions DataBig Picture esu ts, co t uedS th C t Ai B i (SCAB) b d lTh i d f th l i t t ti f l t i ti ti Ethanol impacts air pollution and climate change throughout its production • South Coast Air Basin (SCAB) - box modelThe increased use of ethanol in transportation fuels warrants an investigation Ethanol impacts air pollution and climate change throughout its production ( )

O CH CHOp gf it b i ll ti I i k lt and use Here we are only examining how the tailpipe emissions of flex G li hi l i i f 2020 (J b 2007) O3 CH3CHOof its consequences on urban air pollution. In our previous work, our results and use. Here, we are only examining how the tailpipe emissions of flex • Gasoline vehicle emissions for 2020 (Jacobson 2007) O3 CH3CHOof its consequences on urban air pollution. In our previous work, our results y g p p

f el ehicles sing ethanol (E85) ill impact rban air poll tion s ch as( )

suggest that E85’s effect on health through ozone formation becomes fuel vehicles using ethanol (E85) will impact urban air pollution, such as • 60% reduction from 2002 SCAB emissions to account for improved vehiclessuggest that E85 s effect on health through ozone formation becomes g ( ) p p ,t ti j t i f th t t l th l i t

• 60% reduction from 2002 SCAB emissions to account for improved vehicles

hi l i i ( b )increasingly more significant relative to gasoline at colder temperatures due to ozone concentrations – just one piece of the total ethanol picture.• E85 vehicle emissions (Jacobson 2007)increasingly more significant relative to gasoline at colder temperatures due to ozone concentrations just one piece of the total ethanol picture.

h f h l i d d f h h h l i d d E85 vehicle emissions (Jacobson 2007)the change in exhaust emission composition at lower temperatures even with Therefore these results are independent of what the ethanol is produced

B d 12 di i h i i d d 24 C % hthe change in exhaust emission composition at lower temperatures, even with Therefore, these results are independent of what the ethanol is produced

• Based on 12 studies with emissions data around 24 C - average % changeg p p

th k i t hi (Gi b h t l 2010) W t d from – corn sugar cane cellulosic materials – and how it is transported g gthe weaker winter sunshine (Ginnebaugh et al. 2010). We now extend our from – corn, sugar cane, cellulosic materials – and how it is transported. ( g )t d t i l d th i t f f th b i ll ti f li Fle F elstudy to include the impact of a fog on the urban air pollution from gasoline • Gasoline and E85 emissionsFlex Fuel study to include the impact of a fog on the urban air pollution from gasoline

d h h h i l h i ( ) d• Gasoline and E85 emissions

Select Species Gasoline Vehicles singand E85 exhaust We use the Master Chemical Mechanism (MCM 3 1) and speciated using Black (1995Select Species Gasoline Vehicles using and E85 exhaust. We use the Master Chemical Mechanism (MCM 3.1) and speciated using Black (1995-p(72 T t l) V hi l

gE85the Chemical Aqueous Phase Radical Mechanism (CAPRAM 3 0i) with the

p g (1997) d C t (2008) i t 70

(72 Total) Vehicles E85the Chemical Aqueous Phase Radical Mechanism (CAPRAM 3.0i) with the E85 1997) and Carter (2008) into 70 ( )

CO 782 000 821 100SMVGEAR II chemical ordinary differential solver to provide the speed E85 997) d C e ( ) o 7l il i i (

CO 782,000 821,100 SMVGEAR II chemical ordinary differential solver to provide the speed volatile organic species (see, ,

NO 6 890 4 823y p p

t i l t th li t d h i t t i h ff t Wvolatile organic species (see NO2 6,890 4,823 necessary to simulate the complicated chemistry to examine such effects. We Table 1)

NO2 6,890 ,8 3CH COOHy p y

fi t lid t t th d di l t i l th b iTable 1)NO 62,010 43,407 CH3COOH

C H OHfirst validate our gas-to-aqueous method, dissolutoinal growth, by comparing NO 62,010 43,407 3 C2H5OHfirst validate our gas to aqueous method, dissolutoinal growth, by comparing d l l i h h f h l ( ) h h d l i h • 48 hour model run 6 am toMethane 4 723 12 010 C2H5OH

model results with those from Barth et al (2003) We then use the model with • 48 hour model run – 6 am to Methane 4,723 12,010 model results with those from Barth et al. (2003). We then use the model with 6Ethylene 4 691 8 256

species-resolved tailpipe emissions data for E85 (15% gasoline 85% ethanol 6 amM d l V lid tiEthylene 4,691 8,256

species-resolved tailpipe emissions data for E85 (15% gasoline, 85% ethanol Model Validation Ethane 1 184 1 724fuel blend) and gasoline vehicles with a monodisperse fog to investigate the • Vehicle emissions profile

Model Validation Ethane 1,184 1,724 fuel blend) and gasoline vehicles with a monodisperse fog to investigate the • Vehicle emissions profilePropylene 3 109 801) g p g gchanges in air poll tion concentrations We incl de di rnal effects b

pPropylene 3,109 801 changes in air pollution concentrations. We include diurnal effects by • Based on the diurnal profile forDi l i l h (J b 2005) h f f h 1 3 Butadiene 477 51g p y

i i t d i• Based on the diurnal profile for • Dissolutional growth (Jacobson 2005) governs the transfer from gas phase 1,3 Butadiene 477 51

examining two day scenarios. urban vehicles from theDissolutional growth (Jacobson 2005) governs the transfer from gas phase

Benzene 3 035 819examining two day scenarios. urban vehicles from the to aqueous phase Benzene 3,035 819 Emissions Modelingto aqueous phase Toluene 7 226 1 738 Emissions Modeling

l i h lToluene 7,226 1,738

Clearinghouse Temporal• Barth et al (2003) model intercomparison had two cases both with M&P-Xylene 5 516 1 239Model Description

Clearinghouse Temporal All i (USEPA 2000)

• Barth et al. (2003) model intercomparison had two cases, both with M&P Xylene 5,516 1,239 Model Description Allocation (USEPA 2000)constant noon time photolysis: O-Xylene 2 021 396Model Description ( )constant noon-time photolysis: O Xylene 2,021 396 HCOOH

B k d i ip y

Methanol 215 5 110 HCOOH• Background emissions1) clear sky only

Methanol 215 5,110

G Ph Ch i l M h ic g ou d e ss o s1) clear-sky-only Ethanol 24 51 462Gas-Phase Chemical Mechanism: • Include point fugitive area

) y y Ethanol 24 51,462 Gas Phase Chemical Mechanism: • Include point, fugitive, area, 2) cloudy where the first 30 minutes are clear next 1 hour has a Formaldehyde 569 1 168The Master Chemical Mechanism (MCM 2002) is a large chemical

p gnon road non gasoline and on2) cloudy, where the first 30 minutes are clear, next 1 hour has a Formaldehyde 569 1,168

The Master Chemical Mechanism (MCM 2002) is a large chemical non-road non-gasoline and on-) y, ,di l d d th fi l 30 i t l Acetaldehyde 366 9 516 HOCH CHOmechanism describing the tropospheric degradation of 135 commonly emitted road non gasolinemonodisperse cloud, and the final 30 minutes are clear Acetaldehyde 366 9,516 HOCH2CHOmechanism describing the tropospheric degradation of 135 commonly-emitted Table 1: Select Species for Vehicle

road non-gasolineo od spe se c oud, a d e a 30 u es a e c ea HOCH2CHOg p p g yl til i h i l (VOC ) It d l d t L d U i it d

Table 1: Select Species for Vehicle d d i hd l ith th B th h i t if di l t i lvolatile organic chemicals (VOCs). It was developed at Leeds University and Emissions in the South Coast Air Basin • Constant day and night• ran our model with the Barth mechanism to verify our dissolutoinalvo e o g c c e c s (VOCs). w s deve oped eeds U ve s y d

i b i i l d d i h h l i ifi i f i ThEmissions in the South Coast Air Basin Constant day and nightran our model with the Barth mechanism to verify our dissolutoinal

h h dis being continuously updated with the latest scientific information. The in 2020 (tonnes/year)growth methodis being continuously updated with the latest scientific information. The in 2020 (tonnes/year)growth methodcurrent version (3 1) incorporates over 13 500 chemical reactions and over • Fog (approximately 50 fog events in Los Angeles in 2008)current version (3.1) incorporates over 13,500 chemical reactions and over • ran the same case with MCM-CAPRAM mechanism for comparison • Fog (approximately 50 fog events in Los Angeles in 2008)

Fi 3 Ti i i i b f G li d E85 i h f d4 600 speciesran the same case with MCM CAPRAM mechanism for comparison Figure 3: Time series concentration in ppb for Gasoline and E85 cases without a fog and 4,600 species. • From midnight to noon on the 2nd day

g pp f f gith f f id i ht t th 2nd dFrom midnight to noon on the 2 day with a fog from midnight to noon on the 2nd day

A Ph Ch i l M h i Li id W t C t t 3 10 7 l t / l if g f g y

Aqueous-Phase Chemical Mechanism: • Liquid Water Content = 3 x 10-7 vol water/vol airAqueous Phase Chemical Mechanism: q• Time series results shown in Figure 3 for select species

The Chemical Aqueous Phase Radical Mechanism (Herrmann et al 2005) • Droplet radius = 10 micronTime series results shown in Figure 3 for select species

The Chemical Aqueous Phase Radical Mechanism (Herrmann et al 2005) • Droplet radius = 10 micronO f i i i ll d i b d d i i hi h

q ( )treats aq eo s chemistr among 390 species and 829 reactions (incl ding 51 • Ozone – fog initially suppresses ozone production but ends up driving higher ozonetreats aqueous chemistry among 390 species and 829 reactions (including 51 • No reduction in photolysis for this baseline case

Ozone fog initially suppresses ozone production but ends up driving higher ozone i f h f h b d ff

q y g p ( gt h ti ) CAPRAM 3 0 h th h

No reduction in photolysis for this baseline case concentrations after the fog has burned offgas-to-aqueous phase reactions). CAPRAM 3.0 has the aqueous phase Si fil k d 2ggas to aqueous phase reactions). CAPRAM 3.0 has the aqueous phase

h i l i f 34 i 13 b li d di b li • Sine temperature profile peaked at 2 pm at ~75F • Acetaldehyde fog increases acetaldehyde concentrations during the fog but reduceschemical reactions for 34 species – 13 monocarboxylic and dicarboxylic Sine temperature profile, peaked at 2 pm at 75F • Acetaldehyde – fog increases acetaldehyde concentrations during the fog but reduces chemical reactions for 34 species 13 monocarboxylic and dicarboxylic the acetaldehyde peak in the afternoon

R ltacids 10 carbonyl compounds 5 alcohols 4 polyfunctional compounds 1 the acetaldehyde peak in the afternoonResultsacids, 10 carbonyl compounds, 5 alcohols, 4 polyfunctional compounds, 1 Resultsester and 1 heterocyclic compound and is the most extensive aqueous • Acetic Acid and Formic Acid – fog dramatically increases acetic and formic acidester and 1 heterocyclic compound , and is the most extensive aqueous Acetic Acid and Formic Acid fog dramatically increases acetic and formic acid

i f b h li d E85y p q

mechanism available (Pilling 2007) concentrations for both gasoline and E85 casesmechanism available (Pilling 2007). co ce o s o bo g so e d c ses( g )• Ethanol fog decreases ethanol concentrations which is not surprising because it• Ethanol – fog decreases ethanol concentrations, which is not surprising because it

Gear Solver: forms acetaldehyde and acetic acid in the presence of a fogGear Solver: forms acetaldehyde and acetic acid in the presence of a fogSMVGEAR II (J b 1994 1995 1998) i t i diSMVGEAR II (Jacobson 1994, 1995, 1998) is a sparse-matrix ordinary • Glycol Aldehyde – the fog causes a higher peak in glycol aldehyde concentrationsSMVGEAR II (Jacobson 1994, 1995, 1998) is a sparse matrix ordinary diff i l i (ODE) l I h f i i

Glycol Aldehyde the fog causes a higher peak in glycol aldehyde concentrationsdifferential equation (ODE) solver It was chosen for two main reasons – itdifferential equation (ODE) solver. It was chosen for two main reasons it

C l i d F t W kuses the Gear solution mechanism which is considered accurate and it uses a Conclusions and Future Workuses the Gear solution mechanism, which is considered accurate, and it uses a Conclusions and Future Worksparse matrix technique during matrix decomposition and backsubstitutionsparse-matrix technique during matrix decomposition and backsubstitution that dramatically decreases the run timesthat dramatically decreases the run times. F i th t ti f l k i ll t t i l diy Fog increases the concentrations of several key air pollutants, including ozone, g y p , g ,

i id f i id d l l ld h dacetic acid, formic acid, and glycol aldehyde.acetic acid, formic acid, and glycol aldehyde.

N i i i i H d l i d d dNext, sensitivities to pH, water content, droplet size, temperature, and reducedBarth, M. C., S. Sillman, et al. (2003). "Summary of the cloud chemistry modeling intercomparison: Photochemical box model simulation." Journal of Next, sensitivities to pH, water content, droplet size, temperature, and reduced ( ) y y g pGeophysical Research 108(D7): AAC5-1-AAC5-AAC5-19.

photolysis will be investigatedp y ( )

Black, F. (1995-1997). “Characterization of Alternative Fuel Vehicle Emissions Composition and Ozone Potential.” EPA No. RW89936763. Annual Reports to photolysis will be investigatedBlack, F. (1995 1997). Characterization of Alternative Fuel Vehicle Emissions Composition and Ozone Potential. EPA No. RW89936763. Annual Reports to the Department of Energy Fi 2 T D A O C i f G li d E85 i hthe Department of Energy.Carter W P L (2008) “Development of an Improved Chemical Speciation Database for Processing Emissions of Volatile Organic Compounds for Air Quality Figure 2: Two Day Average Ozone Concentration for Gasoline and E85 cases without Carter, W.P.L. (2008). Development of an Improved Chemical Speciation Database for Processing Emissions of Volatile Organic Compounds for Air Quality Models ” College of Engineering Center for Environmental Research and Technology (CE CERT) University of California Riverside The possibility that the use of E85 in our vehicles would increase ozone

g y g z ff d ith f f id i ht t th 2nd dModels. College of Engineering, Center for Environmental Research and Technology (CE-CERT), University of California, Riverside.

http:// engr cr ed / carter/emitdb/The possibility that the use of E85 in our vehicles would increase ozone a fog and with a fog from midnight to noon on the 2nd dayhttp://www.engr.ucr.edu/~carter/emitdb/

Gi b h D L J Li t l (2010) "E i i th t t d d f th l (E85) li i i i ll ti ith l l concentrations in some of our cities that are already dealing with high ozonef g f g f g y

Ginnebaugh, D. L., J. Liang, et al. (2010). "Examining the temperature dependence of ethanol (E85) versus gasoline emissions on air pollution with a largely-li i h i l h i " A h i i 44 1192 1199 • Modeled four 2-day scenarios: concentrations in some of our cities that are already dealing with high ozone

explicit chemical mechanism." Atmospheric Environment 44: 1192-1199. • Modeled four 2-day scenarios: y g gl l lik L A l i ll h th i f h ld b f thHerrmann, H.; Tilgner, A.; Barzaghi, P.; Majdik, Z.; Gligorovski, S.; Poulain, L. and Monod, A.; Towards a more detailed description of tropospheric aqueous

li flevels, like Los Angeles, especially when there is a fog, should be one of the

phase organic chemistry: CAPRAM 3.0., Atmospheric Environment 39 (23-24), 4351-4363, 2005 , http://projects.tropos.de/capram/ • Gasoline & E85 – no fog, g , p y g,

id i h d l i li f bi f lp g y p ( ) p p j p pJacobson, M. Z. and R. P. Turco (1994). "SMVGEAR: A Sparse-Matrix, Vectorized Gear Code for Atmospheric Models." Atmospheric Environment 28(2): 273-

Gasoline & E85 no fog considerations when developing policy for biofuels., ( ) p , p p ( )284. Gasoline & E85 fog from midnight to noon on the second da

considerations when developing policy for biofuels. 284.Jacobson M Z (1995) "Computation of Global Photochemistry with SMVGEAR II " Atmospheric Environment 29(18): 2541-2546 • Gasoline & E85 – fog from midnight to noon on the second dayJacobson, M. Z. (1995). Computation of Global Photochemistry with SMVGEAR II. Atmospheric Environment 29(18): 2541 2546. Jacobson M Z (1998) "Improvement of SMVGEAR II on Vector and Scalar Machines Through Absolute Error Tolerance Control " Atmospheric Environment

g g y

AcknowledgementsJacobson, M. Z. (1998). Improvement of SMVGEAR II on Vector and Scalar Machines Through Absolute Error Tolerance Control. Atmospheric Environment 32(4): 791 796 • pH was allowed to vary with reactions resulting avg pH = 2 1Figure 1: Clear sky and Cloudy Model Results Using the Barth Chemical Mechanism Acknowledgements32(4): 791-796.Jacobson M Z (2005) Fundamentals of Atmospheric Modeling New York Cambridge University Press

• pH was allowed to vary with reactions – resulting avg pH = 2.1 Figure 1: Clear sky and Cloudy Model Results Using the Barth Chemical Mechanism (B h SMVGEAR) d h MCM CAPRAM Ch i l M h i (MCM AcknowledgementsJacobson, M. Z. (2005). Fundamentals of Atmospheric Modeling. New York, Cambridge University Press.

J b M Z (2007) Eff t f th l (E85) li hi l d t lit i th U it d St t E i S i T h l 10 1021/ 062085

p y g g p(Barth-SMVGEAR) and the MCM-CAPRAM Chemical Mechanism (MCM-Jacobson, M.Z. (2007) Effects of ethanol (E85) versus gasoline vehicles on cancer and mortality in the United States, Environ. Sci. Technol., 10.1021/es062085v.

MCM (2002) M Ch i l M h i 3 1 U i i f L d h // l d k/MCM/h h • Average ozone concentration increased with fog but the(Barth SMVGEAR) and the MCM CAPRAM Chemical Mechanism (MCM

CAPRAM SMVGEAR) d t th f d l lt (i th ( lMCM (2002). Master Chemical Mechanims v. 3.1, University of Leeds. http://mcm.leeds.ac.uk/MCM/home.htt • Average ozone concentration increased with fog, but the CAPRAM-SMVGEAR) compared to the range of model results (in the grey (clear Thank you to NASA EPA and DOE for sponsoring this researchPilling, M. J. (2007). Representation of Chemical Detail in Atmospheric Models. Regional Climate Variability and its Impacts in The Mediterranean Area,

g g,diff b t li d E85 d d ( Fi 2)

) p g f ( g y (k ) d bl ( l d ) h di ) f B th t l (2003) Thank you to NASA, EPA and DOE for sponsoring this research.Springer Netherlands. 79: 207-218 difference between gasoline and E85 decreased (see Figure 2)sky) and blue (cloudy) shading) from Barth et al. (2003) difference between gasoline and E85 decreased (see Figure 2)y) ( y) g) f ( )