S1

Supporting Information for

Molecular Markers of Secondary Organic Aerosol in

Mumbai, India

Pingqing Fu1,2*, Shankar G. Aggarwal3,2, Jing Chen4,5, Jie Li1, Yele Sun1, Zifa Wang1, Huansheng Chen1, Hong Liao1,9, Aijun Ding6, G. S. Umarji7, R. S. Patil7, Qi Chen8,

and Kimitaka Kawamura2

1 State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China

2 Institute of Low Temperature Science, Hokkaido University, Sapporo 060-0819, Japan 3 CSIR-National Physical Laboratory, New Delhi 110012, India 4 SKLEG, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China 5 Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences,

Beijing 100101, China 6 Institute for Climate and Global Change Research & School of Atmospheric Sciences, Nanjing

University, Nanjing, 210093, China 7 Centre for Environmental Science and Engineering, Indian Institute of Technology Bombay,

Mumbai, 400076, India 8 State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of

Environmental Sciences and Engineering, Peking University, Beijing 100871, China 9 School of Environmental Science and Engineering, Nanjing University of Information Science &

Technology, Nanjing 210044, China

*Corresponding Author. Phone: +86-10-8201-3200; e-mail: fupingqing@mail.iap.ac.cn

This SI file contains thirteen pages with detailed methods, three tables (Tables S1-S3), four figures

(Figures S1-S4), and references.

S2

METHODS

OC, EC, and WSOC Measurements.

Organic carbon (OC) and elemental carbon (EC) were determined using a Sunset Lab carbon

analyzer, following the Interagency Monitoring of Protected Visual Environments (IMPROVE)

thermal evolution protocol and assuming carbonate carbon in the sample to be negligible (1). In

brief, an aliquot (Φ14 mm) of the quartz fiber filter was punched for each sample. The punched

filter was placed in a quartz boat inside the thermal desorption chamber of the analyzer, and then

stepwise heating was applied. Equivalent OC concentrations from field blanks were less than 5%

of the average OC concentrations of the actual samples. Analytical errors in triplicate analysis

were within 10%.

Water-soluble organic carbon (WSOC) was measured using a 2.0 cm disk of the filter

sample, which was extracted with Milli-Q water (7.0 ml) in a glass bottle using an ultrasonic bath

for 30 min. Particles in the extracts were removed using a disc filter. A 2 M HCl solution (0.1 ml)

was added to 5 ml of water extracts. After purging for 10 min with ultrapure air (80 ml min−1), 100

μl of solution were injected into a TOC analyzer (Shimadzu TOC-5000A). The analytical error

(repeatability) was estimated to be within 6% by the duplicate analyses (2).

Organic Species Analysis.

For each sample, a filter aliquot (ca. 6 cm2) was extracted with dichloromethane/methanol (2:1;

v/v) three times under ultrasonication. The solvent extracts were filtered through quartz wool

packed in a Pasteur pipette, concentrated by the use of a rotary evaporator, and then blown down

to dryness with pure nitrogen gas. The extracts were then reacted with 50 μl of N,O-bis-

(trimethylsilyl)trifluoroacetamide (BSTFA) with 1% trimethylsilyl chloride and 10 μl of pyridine

at 70°C for 3 h. After reaction, the derivatives were diluted with 140 μl of n-hexane containing

1.43 ng μl–1 of the internal standard (C13 n-alkane) prior to GC-MS injection (3).

GC-MS Analysis.

GC/MS analyses of the derivatized fraction were performed on a Hewlett-Packard model 6890 GC

coupled to a Hewlett-Packard model 5973 MSD. The GC was equipped with a split/splitless

injection and a DB-5ms fused silica capillary column (30 m × 0.25 mm i.d., 0.25 μm film

thickness). Helium was used as a carrier gas. GC oven temperature was programmed from 50°C (2

min) to 120°C at 30°C min–1 and then to 300°C at 6°C min–1 with a final isothermal hold at 300°C

for 20 min. The MS was operated in electron ionization (EI) mode at 70 eV and scanned from 50

S3

to 650 Da. Data were processed with Chemstation software. Individual compounds were identified

by comparison of mass spectra with those of authentic standards and literature data (4, 5). For the

quantification of 3-hydroxyglutaric, cis-pinonic, and pinic acids, their GC-MS response factors

were determined using authentic standards. β-Caryophyllinic acid was estimated using the

response factor of pinic acid. The toluene SOA tracer was estimated using the response factor of 3-

hydroxyglutaric acid. 2-Methylglyceric acid, 2-methyltetrols, C5-alkene triols, and 3-methyl-1, 2,

3-butanetricarboxylic acid were quantitatively determined by a capillary GC (Hewlett-Packard,

HP6890) equipped with a flame ionization detector (FID). The standard of meso-erythritol, a

surrogate compound generally used for the quantification of 2-methyltetrols (4), was quantitatively

determined by both GC-MS and GC-FID. Its relative standard deviation based on these two

methods was <5%. A field blank filter was treated as the real samples for quality assurance. Target

compounds were not detected in the blank. Recoveries for the authentic standards or surrogates

that were spiked onto pre-combusted quartz filters and analyzed as the samples (n = 3) were

generally better than 80%. Relative standard deviation of the concentrations based on duplicate

sample analysis was generally <10%. All the experiments were completed in March 2009.

Regional SOA Burden Modeling: NAQPMS.

A Nested Air Quality Prediction Modeling System (NAQPMS) (6), a fully modularized 3-D

chemical transport model derived from the Weather Research and Forecasting model, was used to

estimate the regional distribution of SOA in South Asia. The physical and chemical evolution of

reactive pollutants in the atmosphere is reproduced by solving the mass balance equation in

terrain-following coordinates. Secondary organic aerosols are currently treated by a bulk two-

product yield parameterization (7). For simulation of heterogeneous chemical processes, 12

species and 28 reactions involving dust, sea salt, sulfate, and black carbon are included. The

advection scheme uses accurate mass-conservative, peak-preserving algorithm (8). Natural

hydrocarbon emissions were derived from the Global Emissions Initiative (GEIA) (9). The

simulation periods were 2006–2007 with a six-month spin-up time. The basic integration time step

for NAQPMS was 5 minutes.

Regional SOA Burden Modeling: GEOS-Chem.

The GEOS-Chem global chemical transport model (v9-02, www.geos-chem.org) was applied here

at a 2° × 2.5° horizontal resolution and was driven by GEOS-5 assimilated meteorology with 47

vertical levels between the surface and ~0.01 hPa. The organic aerosol scheme includes POA,

SOA, and oceanic organic aerosol. Sources of POA include anthropogenic and biofuel emissions

S4

from Bond et al. (10) with seasonal variability (11) and year-specific monthly-mean biomass

burning from the Global Fire Emissions Database (GFED v3) (12). POA are treated as

semivolatile organic compounds (SVOC) that can remain in the particle phase after dilution (non-

volatile POA) or age in the gas phase to form SOA. SOA produced by the oxidation of

intermediate volatility organic compounds (IVOC) are also included (13). Biogenic and aromatic

SOA formation is simulated by gas-to-particle partitioning of SOA tracers formed by the oxidation

of volatile organic compound (VOC) precursors (14-16) with NOx dependent yields and a updated

lumping scheme (17). The emissions of biogenic precursors (i.e., isoprene and terpenes) are

calculated from the Model of Emissions of Gases and Aerosols from Nature (MEGAN v2.1) (18).

The emissions of aromatic precursors (i.e., benzene, toluene, and xylene) follow the Emission

Database for Global Atmospheric Research (EDGAR v2.0) and the emissions of CO from biofuel

and biomass burning (16). We also include oceanic POA sources with emissions estimated by

scaling to remotely-sensed chlorophyll-α concentrations (19, 20). We assumed that 50% of the

non-volatile POA from combustion sources and 100% of oceanic POA was hydrophobic, with an

e-folding conversion of 1.2 days from hydrophobic to hydrophilic (21). The simulated organic-

carbon concentrations were scaled by a factor of 1.4 for non-volatile POA and 2.1 for SOA formed

from SVOC to account for additional non-carbon mass to obtain the simulated OA mass

concentrations. SOA are treated as highly soluble (Henry’s law coefficient of 105 M atm–1) with an

80% scavenging efficiency.

S5

Table S1. Aerosol components in PM10 samples and major meteorological parameters.

Components Summer (n=14) Winter (n=10) min max mean std min max mean std

OC (µgC m–3) 3.3 6.1 4.5 0.91 11.9 23.2 15.3 3.3 EC (µgC m–3) 0.70 3.7 1.5 0.88 4.5 8.9 6.4 1.5 WSOC (µgC m–3) 1.2 2.7 1.7 0.43 3.5 9.5 6.0 2.0 WIOC (µgC m–3) 2.0 4.1 2.8 0.66 6.5 13.8 9.4 2.3 WIOC in OC (%) 55.0 77.9 63.0 5.7 44.3 74.8 61.4 8.5 Temperature (°C) 25.5 34.8 30.6 2.4 20.5 33.7 25.3 3.7 Relative humidity (%) 50.2 98.0 77.4 12.4 27.0 43.0 36.7 5.2

Isoprene SOA tracers (ng m–3) 2-methylglyceric acid (2-MGA) 0.10 0.83 0.30 0.22 0.30 2.8 1.2 0.80 ΣC5-alkene triols a 0.02 0.18 0.06 0.05 0.09 4.0 0.95 1.2 2-methylthreitol 0.04 0.40 0.21 0.12 0.34 0.94 0.56 0.16 2-methylerythritol 0.10 1.0 0.51 0.33 0.83 2.2 1.4 0.45 sum of 2-methyltetrols 0.14 1.4 0.72 0.45 1.2 3.1 2.0 0.59 subtotal 0.29 2.3 1.1 0.69 1.7 9.9 4.1 2.4

α/β-pinene SOA tracers (ng m–3) 3-hydroxyglutaric acid (3-HGA) 0.87 5.0 2.0 1.2 3.5 34 14 11 pinonic acid 2.7 17 5.5 3.9 1.0 3.0 1.9 0.73 HDCCA b 0.06 0.79 0.25 0.20 0.27 2.0 0.96 0.58 3-acetylglutaric acid 0.04 0.71 0.23 0.20 0.44 3.7 1.7 1.1 3-acetyladipic acid 0.05 0.36 0.14 0.09 0.46 3.8 1.4 1.2 3-isopropylglutaric acid 0.23 1.81 0.67 0.50 1.07 19 5.9 6.0 pinic acid 0.22 1.3 0.59 0.31 0.91 6.2 2.7 1.9 MBTCA c 0.01 0.19 0.06 0.06 0.06 1.2 0.49 0.37 subtotal 5.1 21 9.4 4.7 11 72 29 22

β-caryophyllene SOA tracer (ng m–3) β-caryophyllinic acid 0.21 1.4 0.69 0.28 3.2 11 5.6 2.9

Toluene SOA tracer (ng m–3) DHOPA d 0.008 0.21 0.05 0.055 0.06 1.9 0.62 0.55 sum of SOA tracers 5.8 24 11 5.3 17 89 40 27

Hydroxyacids (ng m–3) hydroxyacetic acid (glycolic acid) 1.2 5.4 2.8 1.2 4.5 37 16 10 3-hydroxybutyric acid 0.65 2.0 1.2 0.39 2.2 5.8 3.5 1.1 2-hydroxybenzoic acid (salicylic acid) 0.05 0.12 0.08 0.02 0.30 1.1 0.60 0.24 3-hydroxybenzoic acid 0.14 0.89 0.24 0.20 1.0 3.3 2.1 0.80 4-hydroxybenzoic acid 0.60 9.9 1.7 2.4 6.0 63 22 16 3,4-dihydroxybenzoic acid 0.73 3.0 1.6 0.63 5.7 26 10 5.8 subtotal 4.1 17 7.7 3.2 34 92 55 22

a C5-alkene triols: the sum of cis-2-methyl-1, 3, 4-trihydroxy-1-butene, trans-2-methyl-1, 3, 4-trihydroxy-1-butene, and 3-methyl-2, 3, 4-trihydroxy-1-butene.

b HDCCA: 3-(2-hydroxyethyl)-2, 2-dimethyl-cyclobutane carboxylic acid. c MBTCA: 3-methyl-1, 2, 3-butanetricarboxylic acid. d DHOPA: 2,3-dihydroxy-4-oxopentanoic acid.

S6

Table S2. Summary of organic carbon concentrations (ngC m–3) from different biogenic VOCs and their contributions in aerosol OC (%). Both SOC and SOA mass concentrations are estimated using the tracer-based method by Kleindienst et al. (22).

Components Summer (June 2006) Winter (February 2007) range mean std range mean std

Concentration (ngC m–3) Isoprene SOC 1.6–13 7.0 4.2 9.7–38 20 8.4 Monoterpene SOC 22–92 41 20 48–310 127 97 Sesquiterpene SOC 9.3–60 30 12 138–483 244 127 Toluene SOC 1.0–26 6.2 7.0 7.8–237 79 70 Subtotal 41–158 83 37 216–1030 470 290

Percentage in aerosol OC (%) Isoprene SOC 0.03–0.30 0.14 0.08 0.08–0.19 0.13 0.04 Monoterpene SOC 0.43–1.8 0.91 0.39 0.31–1.9 0.80 0.51 Sesquiterpene SOC 0.16–0.99 0.67 0.21 1.0–2.9 1.6 0.61 Toluene SOC 0.03–0.43 0.13 0.13 0.05–1.0 0.48 0.34 Subtotal 0.86–3.0 1.9 0.66 1.5–5.6 3.0 1.4

Mass concentration (ng m–3) Isoprene SOA 3.9–33 16 10 24–94 50 21 Monoterpene SOA 30–125 56 27 66–427 175 133 Sesquiterpene SOA 20–126 63 26 291–1020 515 269 Toluene SOA 2.0–52 12 14 15–468 156 137 Subtotal 71–291 147 65 415–1930 896 535

S7

Table S3. Averaged concentrations (μgC m−3) of biogenic SOC and their contributions in OC (%) measured in the Mumbai aerosols compared to those reported in other studies.

Location SOC (percentages in OC)

Sample period Reference Isoprene Monoterpenes β-Caryophyllene

I. Urban sites Mumbai, India 0.007 (0.14%) 0.041 (0.91%) 0.03 (0.67%) Jun 2006 This study Mumbai, India 0.02 (0.13) 0.13 (0.80%) 0.24 (1.6%) Feb 2007 This study Atlanta, US 0.86 (11%) 0.30 (4.0%) 0.01 (0.13%) May−Aug 2005 (23) Beijing, China 0.30 (1.8%) 0.13 (0.76%) 0.12 (0.7%) Aug 2007 (24) Beijing, China 0.92 (8.9%) 0.49 (4.7%) 0.21 (2.0%) Jul−Aug, 2008 (25) Hong Kong, China 0.19 (7.3%) 0.18 (7.0%) 0.17 (6.6%) Jul−Aug (clean) (26) Hong Kong, China 0.46 (4.6%) 2.5 (25%) 1.6 (16%) Jul−Aug (haze) (26) Cincinnati, US 0.93 (28%) 0.28 (8.6%) 0.16 (4.9%) May 2004 (27) Detroit, US 0.41(12%) 0.37(11%) 0.32 (9.4%) May 2004 (27) Riverside, CA 0.15 (3.8%) 0.19 (4.8%) 0.04 (1%) Aug 2005 (28) Urban site, Mexico 0.22 (2.5%) 0.21 (2.4%) 0.15 (1.7%) Mar, 2006 (29) Peripheral, Mexico 0.20 (4.1%) 0.24 (4.9%) 0.25 (5.1%) Mar, 2006 (29) II. Suburban/Rural/Mountain Sites Centerville, USA 1.78 (27%) 0.69 (11%) 0.02 (0.31%) May−Aug 2005 (23) Pensacola, USA 0.80 (14%) 0.50 (8.5%) 0.25 (4.3%) May−Aug 2005 (23) Yufa, China 0.41 (3.1%) 0.14 (1.1%) 0.17 (1.3%) Aug 2007 (24) Yufa, China 1.30 (14%) 0.52 (5.5%) 0.16 (1.7%) Jul−Aug 2008 (25) Bondville, US 0.49 (28%) 0.24 (14%) 0.11 (6.3%) May−Sept 2004 (27) Northbrook, IL 0.36 (15%) 0.24 (9.8%) 0.17 (6.9%) May−Sept 2004 (27) Wangqingsha, China 0.05 (2.6%) nd 0.02 (1.0%) Aug−Sept 2008 (30) Wangqingsha, China 0.02 (0.2%) 0.02 (0.2%) 0.02 (0.2%) Nov−Dec 2008 (30) Research Triangle Park 1.13 (31%) 0.73 (20%) 1.10 (30%) Jan−Dec 2003 (22) Research Triangle Park 0.38 (7.4%) 0.12 (2.3%) 0.002 (0.04%) Mar−Sept 2006 (31) Mt. Tai, China 0.84 (4.0%) 0.31 (1.5%) 0.78 (3.7%) Early June 2006 (3) Mt. Tai, China 0.60 (7.4%) 0.14 (1.7%) 0.17 (2.1%) Late June 2006 (3) Moshiri forest, Japan 0.54 (13%) 0.12 (2.8%) 0.03 (0.7%) Aug 2001 (32) III. Marine and the Polar Regions (ngC m−3) Bohai Sea to the Arctic 4.02 (1.8%) 0.27 (0.12%) 0.10 (0.05%) Jul−Sept 2003 (33) Alert, the Arctic 1.73 (0.7%) 7.67 (3.0%) 5.22 (2.1%) Feb−Jun 1991 (34) Arctic Ocean 23.0 (4.1%) 20.8 (3.7%) 0.73 (0.13%) Aug, 2009 (35)

S8

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Figure S1. Diurnal variations of ambient temperature and relative humidity recorded at the

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S9

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Figure S2. Diurnal variations of (a) organic carbon (OC), (b) elemental carbon (EC), (c) water

soluble organic carbon (WSOC), and (d) OC/EC ratios in Mumbai aerosols collected during June

2006 and February 2007. The open and black circles represent daytime and nighttime samples,

respectively.

S10

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Figure S3. Diurnal variations of hydroxyacids and levoglucosan in the Mumbai aerosols.

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Figure S4. Diurnal variations of α/β-pinene SOA tracers in the Mumbai aerosols.

S12

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