Measurement of gaseous and particulate formaldehyde in the Yangtze River Delta, China

Journal Pre-proof Measurement of gaseous and particulate formaldehyde in the Yangtze River Delta, China Rongjuan Xu, Xin Li, Huabin Dong, Zhijun Wu, Shiyi Chen, Xin Fang, Jie Gao, Song Guo, Min Hu, Dongqing Li, Yuechen Liu, Ying Liu, Shengrong Lou, Keding Lu, Xiangxinyue Meng, Hongli Wang, Limin Zeng, Taomou Zong, Jianlin Hu, Mindong Chen, Min Shao, Yuanhang Zhang PII:

S1352-2310(19)30753-8

DOI:

https://doi.org/10.1016/j.atmosenv.2019.117114

Reference:

AEA 117114

To appear in:

Atmospheric Environment

Received Date: 5 August 2019 Revised Date:

30 October 2019

Accepted Date: 2 November 2019

Please cite this article as: Xu, R., Li, X., Dong, H., Wu, Z., Chen, S., Fang, X., Gao, J., Guo, S., Hu, M., Li, D., Liu, Y., Liu, Y., Lou, S., Lu, K., Meng, X., Wang, H., Zeng, L., Zong, T., Hu, J., Chen, M., Shao, M., Zhang, Y., Measurement of gaseous and particulate formaldehyde in the Yangtze River Delta, China, Atmospheric Environment (2019), doi: https://doi.org/10.1016/j.atmosenv.2019.117114. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Ltd.

1

Measurement of gaseous and particulate formaldehyde in the

2

Yangtze River Delta, China

3

Rongjuan Xua,c, Xin Lia,b,c,*, Huabin Donga,c, Zhijun Wua,c, Shiyi Chena,c, Xin Fanga,c,

4

Jie Gaod,e, Song Guoa,c, Min Hua,c, Dongqing Lia,c, Yuechen Liua,c, Ying Liua,c,

5

Shengrong Loud, Keding Lua,c, Xiangxinyue Menga,c, Hongli Wangd, Limin Zenga,c,

6

Taomou Zonga,c, Jianlin Hub, Mindong Chenb, Min Shaoa,c,f, and Yuanhang Zhanga,c

7

8

a

9

Environmental Sciences and Engineering, Peking University, 100871 Beijing, China P. R.

State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of

10

b

11

University of Information Science & Technology, Nanjing, 210044, China P. R.

12

c

13

China P. R.

14

d

15

Pollution Complex, Shanghai Academy of Environmental Sciences, 200233 Shanghai, China P. R.

16

e

17

R.

18

f

19

*Correspondence: Xin Li ([email protected])， Tel and fax: +86-10-62758382

Collaborative Innovation Centre of Atmospheric Environment and Equipment Technology, Nanjing

International Joint Laboratory for Regional Pollution Control, Ministry of Education, Beijing, 100816,

State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air

School of Environmental and Chemical Engineering, Shanghai University, 200444 Shanghai, China P.

Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China P. R.

1

20

Abstract

21

Formaldehyde (HCHO) is one of the most important intermediate products of

22

atmospheric photochemical reactions and is also a radical source that promotes ozone

23

formation. Given its high solubility, HCHO is likely to exist in particulate form. In

24

this work, gaseous HCHO (HCHOg) and particulate HCHO (HCHOp) were separated

25

and collected by a rotating wet annular denude (RWAD) and an aerosol growth

26

chamber–coil aerosol cooler (AC). The collected HCHO from the RWAD and AC are

27

measured by two online Hantzsch method-based formaldehyde analyzers. The

28

comprehensive campaign was held in the Yangtze River Delta of China from 15 May

29

to 18 June 2018, which is during the harvest season. Several biomass burning events

30

were identified by using acetonitrile as a tracer. During the period influenced by

31

biomass burning, the mixing ratios of HCHOg and HCHOp were respectively 122%

32

and 231% higher than those during other time periods. The enhancement ratio of

33

HCHOg to acetonitrile obtained from this work generally agrees with those from the

34

existing literature. Biomass burning contributed 14.8% to HCHOg, but the abundant

35

freshly discharged precursors it emitted greatly promoted the secondary production of

36

HCHOg. We suggest that the high concentration of HCHOp during the biomass

37

burning period was from uptake of HCHOg by aerosols during their transportation; the

38

liquid state particles are conducive to HCHOg uptake. High relative humidity, a low

39

particle rebound fraction f, as well as low temperatures may result in higher uptake

40

coefficient values.

41

Keywords: Biomass burning, HCHO, uptake, particle, liquid state, YRD 2

42

1 Introduction

43

Formaldehyde (HCHO) is one of the most abundant carbonyl compounds, and it

44

serves an important role in tropospheric atmospheric photochemical process (Hellén

45

et al., 2004). Hydroperoxy radicals (HO2) produced by HCHO photolysis react with

46

nitric oxide (NO) to generate hydroxyl radicals (OH). Therefore, the presence of

47

HCHO increases the cyclic efficiency of OH-HO2 and converts more NO to nitrogen

48

dioxide (NO2), thereby promoting the generation of ground-level ozone (O3)

49

(Chatfield et al., 2010; Toda et al., 2012; Xiaoyan et al., 2010). Exposure to high

50

levels of HCHO is carcinogenic and genotoxic, which is a considerable concern

51

(Alicke et al., 2002).

52

Photooxidation of various volatile organic compounds (VOCs) is the main source of

53

HCHO (Possanzini et al., 2002), although it can be emitted by some anthropogenic

54

sources, such as combustion engines and biomass burning, and by vegetation in small

55

amounts (Kesselmeier et al., 1997). Previous studies have been conducted to

56

determine the sources of HCHO. The ratio of HCHO to acetaldehyde (CH3CHO)

57

effectively indicates the contribution of photochemical oxidation of hydrocarbons

58

discharged by biogenic sources to HCHO (Shepson et al., 1991). In rural or remote

59

areas, the HCHO/CH3CHO ratio generally varies between 3 and 10, while the ratio is

60

lower than 3 in urban areas (Cerón et al., 2007; Jacob and Wofsy, 1988). To obtain

61

more specific results, several methods have been applied to quantify the primary and

62

secondary sources of HCHO. Harrison et al. (2006) adopted a method based on the

63

emission ratios of HCHO to the primary source tracer (CO) and determined that 3

64

vehicle exhaust contributed 26% of the HCHO. A multi-linear regression method is

65

based on the primary and secondary HCHO sources being linearly related to the

66

change in tracers, which is appropriate for identifying several primary sources.

67

Generally, CO, acetylene, and toluene are chosen to be the tracers of primary sources,

68

and O3, glyoxal, and peroxyacetyl nitrates (PAN) are chose to be the tracers of

69

secondary sources (Li et al., 2010). De Gouw et al. (2005, 2008) proposed the

70

photochemical age method based on parameterization of atmospheric reactions. Yuan

71

et al. (2012b) analyzed the ambient HCHO in Beijing with this method and found that

72

primary and secondary sources contributed 22% and 28% of the HCHO, respectively.

73

The photochemical age method takes into account the effect of photochemical

74

reactions; however, it is based on many assumptions and approximations that are not

75

completely reasonable in the real atmosphere.

76

Biomass burning is one of the major sources of HCHO, not only as the primary

77

emission source but as a source that emits precursors of secondary HCHO production

78

(Kesselmeier et al., 1997). Acetonitrile is usually used as a tracer to identify biomass

79

burning events. In rural areas, firewood use for cooking is gradually being replaced by

80

natural gas, but open crop residue burning after harvests and firewood for winter

81

heating are generally still being used. Muller and Stavrakou (2005) estimated that

82

global emissions of HCHO from biomass burning are about 2.9 Tg yr-1, accounting

83

for 70% of the total direct emissions of HCHO (4.1 Tg yr-1). In the Chengdu–

84

Chongqing Region, biomass burning contributed most (> 30%) to the ambient HCHO

85

in the winter (Li et al., 2014a, b). 4

86

Except to participate in VOC oxidation to form secondary organic aerosols (SOAs),

87

HCHO generally contributes to the generation of SOAs by heterogeneous uptake of

88

particles. Researchers observed hydroxymethanesulfonic acid in aerosols, which is a

89

product of the aqueous reaction between dissolved SO2 and HCHO (Dixon and Aasen,

90

1999; Scheinhardt et al., 2014). In recent experimental studies, the reactive uptake of

91

HCHO happened on mineral dust particles, while the uptake coefficient (~10-6–10-9)

92

was too low to make a difference to SOA formation (Sassine et al., 2010; Xu et al.,

93

2011). Some studies considered (NH4)2SO4 as seeds in laboratory experiments, and

94

several of them acquired high uptake coefficients (~10-2–10-3). The experiments were

95

carried out either under highly acidic conditions (> 50 wt% H2SO4) (Jayne et al., 1996)

96

or at ultralow temperatures (Iraci and Tolbert, 1997), which is not possible in the

97

troposphere. Research on measuring the particulate HCHO (HCHOp) with

98

impregnated filters went on simultaneously. Nevertheless, some studies reported that

99

HCHOp was insignificant relative to gaseous HCHO (HCHOg), which only occupied

100

10-3 to 10-4 of the HCHOg (Deandrade et al., 1995; Odabasi and Seyfioglu, 2005).

101

Unfortunately, using impregnated filters can create negative errors from the

102

destruction of equilibrium and oxidation, leading to huge measuring errors. In contrast,

103

some studies adopted a denuder to remove the HCHOg first, then sampled HCHOp

104

with filters or particle collectors, acquiring higher ratios of HCHOp/HCHOg (5% in a

105

forest in Japan, and 15% in Mexico City) (Andraca-Ayala and Ruiz-Suarez, 2005;

106

Toda et al., 2014). In China, a lack of online sampling and measurement of HCHOp

107

results in little knowledge on the influence of HCHO on SOA formation. 5

108

For this study, a campaign was held in the Yangtze River Delta (YRD) during harvest

109

time. We used a rotating wet annular denude and an aerosol growth chamber–coil

110

aerosol cooler to separate the HCHOg and HCHOp and measured them via two online

111

Hantzsch method-based formaldehyde analyzers. The YRD is a very important

112

agricultural production base and is a typical region with large-scale open burning

113

(Kudo et al., 2014; Xue et al., 2014). We discuss the influence of biomass burning and

114

other environmental elements on HCHOg and HCHOp herein.

115

2 Methods

116

2.1 Simultaneous measurement of gaseous and particulate HCHO by the gas and

117

aerosol collector–Hantzsch system

118

The simultaneous measurement of HCHOg and HCHOp is achieved by using a

119

personally built gas and aerosol collector (GAC)–Hantzsch system. It consists of a

120

rotating wet annular denuder (RWAD), a steam jet aerosol collector (SJAC), and two

121

commercialized HCHO analyzers (AL4021, AeroLaser GmbH, Germany). The

122

combination of the RWAD and SJAC being called a GAC was introduced by Dong et

123

al. (2012) for measurements of water soluble gases and particulate ions; a detailed

124

description on the principles and design of the GAC can be found therein. The

125

AL4021 instrument and its earlier version, AL4001, based on the Hantzsch technique,

126

have been described and validated in many studies as a well-suited method for HCHO

127

measurement (e.g., Kaiser et al., 2014; Wisthaler et al., 2008). Therefore, we only

128

provide a brief description of the GAC–Hantzsch system herein, instead focusing on

129

its modification for HCHOg and HCHOp measurements. 6

130 131

Fig. 1. Flow diagram of the analytical system. RWAD: rotating wet annular denude. SJAC:

132

steam jet aerosol collector. PP: peristaltic pumps. HD: heating rod. LP: liquid pump. SB:

133

safety bottle. FA: flow-limiting valve. AP: air pump. 3SV-1, 2: three-way solenoid valves.

134

Figure 1 shows the schematic setup of the GAC–Hantzsch system. Ambient air is

135

sampled into the RWAD at a flow rate of 8 L min−1. A stripping solution of 0.055 mol

136

L−1 H2SO4 is continuously pumped through the RWAD at a flow rate of 1.5 ml min−1,

137

forming a uniform liquid film on the RWAD inner surface. While HCHO molecules in

138

the sampled air diffuse to the surface and are captured by the stripping solution,

139

aerosols—due to their higher inertia—pass through the RWAD and reach the SJAC.

140

The SJAC consists of an aerosol growth chamber, a coil aerosol cooler, and an

141

impactor aerosol trapper. The aerosol growth chamber is filled with H2SO4 steam

142

generated from 0.055 mol L−1 H2SO4 solution (i.e., the stripping solution) at 120 °C,

143

which creates supersaturated conditions for capturing aerosols. HCHO and possibly

144

HCHO polymers in the captured aerosols will be dissolved in the stripping solution as

145

HCHO polymers readily decomposes at 60 °C (Kiernan, 2000). The captured aerosols 7

146

are then developed into droplets as they are passed through the coil aerosol cooler and

147

are finally collected by the impactor aerosol trapper. Both the coil aerosol cooler and

148

the impactor aerosol trapper are maintained at 10 °C by a water bath. The collected

149

droplets must be filtered as some parts of aerosols are not soluble in stripping solution.

150

The formed HCHO solutions on gas and aerosol channels are pumped into AL4021-1

151

and AL4021-2, respectively, and are continuously mixed with a Hantzsch reagent (5.6

152

mol L−1 ammonium acetate, 0.16 mol L−1 acetic acid, and 0.02 mol L−1 acetyl

153

acetone). In a continuous flow reactor held at 70 °C, HCHO reacts with the

154

Hantzsch reagent, thereby forming the 3,5-dacetyl-1,4-dihydrolutidine dye. The dye

155

solution is then illuminated by a UV-LED light producing radiation at 410 nm. The

156

emitted fluorescence signal is detected by a photomultiplier (PMT) at 510 nm.

157

Because of the long transmission pipeline, the hysteresis existed during sampling and

158

measuring HCHOg and HCHOp. When HCHOg and HCHOp solved in stripping

159

solution, the concentration was running-averaged with the flowing solution. We

160

switched the ambient air to zero air into the system, and the time needed for HCHOg

161

and HCHOp signal to decrease to 10% of the original value was defined the time

162

resolution (Li et al., 2014). They were 18 and 16 min for HCHOg and HCHOp during

163

this campaign, respectively. The signal hysteresis time of system equaled the time

164

resolution, which was considered in data processing and analysis. Since the

165

concentrations of the HCHO solution from the gas and the aerosol channel typically

166

differ by an order of magnitude, the high voltage applied on the PMT of the two

167

AL4021 instruments is adjusted accordingly to ensure good detection sensitivity for 8

168

each channel. A background signal of AL4021 is acquired every 6 h for 30 min by

169

pumping the stripping solution instead of the HCHO solution into the instrument. The

170

sensitivity of the instrument is calibrated using liquid HCHO standards. The

171

calibration is performed at four concentration levels of liquid HCHO standards. The

172

concentrations correspond to gas phase HCHO mixing ratios of 2 ppb, 5 ppb, 10 ppb,

173

and 30 ppb for the gas channel and to aerosol concentrations of 1 µg m−3, 4 µg m−3, 8

174

µg m−3, and 20 µg m−3 for the aerosol channel.

175

The collection efficiency of the RWAD for HCHOg (

176

factors, i.e., the liquid flow rate of the stripping solution inside the RWAD (Fl), the

177

H2SO4 concentration of the stripping solution (

178

(Fa). By passing a gaseous HCHO standard (≈35 ppb) through the RWAD and

179

measuring its concentration change, the collection efficiency can be calculated using

180

Equation 1: = 100% ×

181

and

) is mainly influenced by three

), and the air sampling flow rate

,

(1)

182

where

is the HCHO concentration in the gas flow entering and exiting the

183

RWAD, respectively. The HCHOg standard was prepared by a Gas Dilution Calibrator

184

(Sabio Gas Dilution Calibrator, Model 4010, Sabio, USA), in which an HCHO

185

Dynacalr® Permeation Tube (Type HE89, VICI Metronics Inc., USA) was kept at 70 °

186

C, and the permeated HCHO gas was diluted by a constant pure nitrogen flow of 20 L

187

min−1. The HCHOg concentration in the inflow and outflow of the RWAD was

188

measured by an AL4021 monitor. Figure 2 (a, b, c) shows the collection efficiencies

189

determined under different conditions. Among the three major influential factors, the 9

190 191

stripping solution flow rate has the least effect on the collection efficiency (Fig. 2a). is stable at around 96.5% once Fl is larger than 1.5 ml min−1 when

and Fa

192

are set to be 0.055 mol L−1 (the concentration of stripping solution in Hantzsch

193

method) and 20 L min−1, respectively. An increase of

194

mol L−1 results in a strong increase of

195

Fa are set to be 1.5 ml min−1 and 20 L min−1; a further increase of

196

contribute much to the improvement of

197

components due to the high corrosivity of H2SO4. The effect of the sampling flow is

198

two-fold. On the one hand, a higher sampling flow is preferred for reducing losses of

199

HCHO and aerosols along the sampling line; on the other hand, the higher the Fa, the

200

lower the residence time of the sampled air inside the RWAD and, thus, the smaller

201

the HCHO collection efficiency. As shown in Fig. 2 (c),

202

0.055 mol L−1 and 1.5 ml min−1, and

203

larger than 8 L min−1. Given the above results, we determined the optimal operational

204

conditions for the GAC–Hantzsch system as an Fl of 1.5 ml min−1,

205

mol L−1, and Fa of 8 L min−1. The HCHO collection efficiency under these conditions

206

is around 99.99%.

from 0.005 to 0.055

by 8% (Fig. 2b), in the meantime, Fl and does not

but could be harmful to the GAC

and Fa are set to be

starts decreasing from 99.99% when Fa is

10

of 0.055

207 208

Fig. 2. Characterization of critical parameters and possible interferences for the

209

GAC-Hantzsch system. Collection efficiency of RWAD versus (a) flow rate (

210

mol L−1, Fa = 20 L min−1), (b) H2SO4 concentration (Fl = 1.5 ml min−1, Fa = 20 L min−1), and

211

(c) air flow (

212

AL4021-2 (for HCHOp). (d) Measurement of a mixture of (NH4)2SO4 aerosols and HCHO gas

213

by the GAC–Hantzsch system. (e) Measurement with a HEPA filter in front of the sampling

214

line.

215

The collection efficiency for aerosols by the GAC (

216

al. (2012), and values larger than 99.5% were determined. In addition, losses of

217

aerosols on the wet surface of the RWAD were found to be less than 10% for those

218

with diameters larger than 100–120 nm. When using H2SO4 as a stripping solution, it

219

creates a more acidic environment in the RWAD, which could probably cause

220

additional uptake of HCHO by aerosols in the sampled air. This probability was

221

investigated by measuring a mixture of (NH4)2SO4 aerosols and HCHO gas by the

222

GAC–Hantzsch system. 1 L min−1 (NH4)2SO4 aerosols with pure nitrogen at about

223

500 ug/m−3generated by aerosol generator was mixed with 7 L min−1 HCHO gas at 35

= 0.055

= 0.055 mol L−1, Fl = 1.5 ml min−1); The signal of formaldehyde analyzer

11

) was investigated by Dong et

224

ppb, and went though the RWAD in less than 0.2 sec. The experiment was conducted

225

in the room temperature at 298K and RH was 50%. As shown in Fig. 2 (d), the

226

readout signal of AL4021-2 on the aerosol channel during the mixture measurement is

227

similar to those measuring zero air. Therefore, it is unlikely that uptake of HCHO by

228

aerosols is happening in the RWAD. In order to verify that the particulate HCHO

229

measurement is not influenced by possible penetration of gaseous HCHO or gas

230

leakage on the system, measurements with a HEPA filter installed in front of the

231

sampling line were performed regularly when the ambient HCHO was at high levels.

232

Figure 2 (e) clearly shows that the aerosol channel measures the same signal as that

233

for zero air when ambient aerosols were removed by the HEPA filter.

234

We define the limits of detection of the GAC–Hantzsch system for HCHO as three

235

times the concentration variation during zero air measurement. The determined value

236

is 0.05 ppb and 0.01 µg m−3 for gaseous and particulate HCHO, respectively. The

237

measurement uncertainty mainly stems from the calibration of the AL4021 monitor,

238

which is around 5% (Kaiser et al., 2014).

239

2.2 Field observations

240

Field measurements of trace gases and aerosols were performed in May–June of 2018

241

at the Jiangsu provincial Taizhou weather radar station (32.558ºN, 119.994°E),

242

which is located about 130 km away from the Shanghai–Nanjing channel and is

243

mainly composed of petrochemicals. The Taizhou site is surrounded by farmlands but

244

is about 150 m from the Qiyang Expressway to the north and 250 m from the Taizhen

245

Expressway to the east. The downtown area is located around 12 km to the northeast. 12

246

During the campaign, fundamental meteorological parameters and trace gases were

247

measured simultaneously.

248

An automatic online GC-MSD/FID system was used to measure VOCs, which was

249

developed by Peking University (Wang et al., 2014; Yuan et al., 2012a). This system

250

includes a custom-built cryogen-free cooling device creating an ultra-low temperature

251

of -165 °C, a two-channel sampling and pre-concentration system, and a commercial

252

GC-MSD/FID. The air sample in two-channel were dehydrated by dewatering traps

253

and pre-concentrated by the cooling device, respectively. After that, VOCs were rapid

254

heated then desorbed, and enter FID and MSD respectively. FID detector mainly

255

measures C2–C4 hydrocarbons, and C5–C11 hydrocarbons and OVOCs were

256

detected by MS detector. The time resolution is one hour, and the sampling time

257

occurs from the 3rd to the 8th minute of every hour. Two sets of standard gases were

258

used to calibrate the system: 56 NMHCs, including 28 alkanes, 13 alkenes and

259

alkynes, and 15 aromatics, and the EPA TO-15 standards, including additional

260

OVOCs and halocarbons. The precisions of the VOC measurements ranged from 0.8%

261

to 6.1%, and detection limits varied from 30 ppt to 50 ppt for different species.

262

Detailed information about this system and quality control procedures can be found in

263

Yuan et al. (2012a) and Wang et al. (2014).

264

A commercial PTR-QiTOF (IONICON Analytik Inc.) was employed herein are

265

similar to those described previously in Huang et al. (2019). It is used to measure

266

VOCs, especially OVOCs in the atmosphere with high sensitivity and fast response.

267

During this campaign, the sensitivity of the PTR-QiTOF was in the range of 13

268

1000-3000 ncps/ppb and mass resolution maintained at ∼5000 m/∆m. The

269

PTR-QiTOF system was calibrated every 2 weeks using a TO-15 mixture standard at

270

six different mixing ratios ranging from 1 to 10 ppbv.

271

In this study, an Aerodyne high-resolution time-of-flight aerosol mass spectrometer

272

(HR-TOF-AMS, Aerodyne Research, Inc., USA) was deployed to measure the

273

chemical composition of submicron aerosols, including sulfate, nitrate, chloride, and

274

OM; the time resolution is 4 min. Detailed information about this system is described

275

in Zheng et al. (2016). Two sets of scanning mobility particle sizers (SMPSs, TSI Inc.,

276

St. Paul, MN, USA) and an aerodynamic particle sizer (APS, TSI model 3321, TSI

277

Inc., St. Paul, MN, USA) were used to measure the particle number size distribution.

278

The first set of SMPSs consisted of a short differential mobility analyzer (DMA, TSI

279

model 3085) and a condensing particle counter (CPC, TSI model 3788) that were used

280

to measure the 3–60 nm particles. Another SMPS with a long DMA (TSI model 3081)

281

and CPC (TSI model 3787) was used for measuring the 60–700 nm particles. The

282

hygroscopicity tandem differential mobility analyzer is composed of a Nafon gas

283

dryer (Perma Pure Inc., USA), two DMAs (which we created), and a CPC (TSI model

284

3772); the specific description is provided in Jing et al. (2016). With the particle

285

number size distribution and hygroscopic growth coefficient, the actual particle

286

surface area concentration can be calculated. The rebound fraction f of size-resolved

287

particles was measured by a three-arm impactor we built ourselves, which

288

characterizes the particle state (Liu et al., 2017).

289

Ambient NO and NOx (NOx = NO + NO2) were measured by chemi-luminescence 14

290

(model 42i, Thermo Fischer Inc, U.S.), and ozone was measured by UV absorption

291

(model 49i, Thermo Fischer Inc, U.S.). CO was quantified by a commercial

292

non-dispersive infrared sensor (model 48i, Thermo Fischer Inc, 224 U.S.), which is

293

based on a gas filter correlation method. SO2 was measured by pulsed fluorescence

294

(model 43C, Thermo Fischer Inc, 225 U.S.; Yang et al., 2017). The photolysis

295

frequencies, including eight photolysis parameters, were measured by a spectral

296

radiometer. Meteorological parameters, such as temperature, wind speed, wind

297

direction, and relative humidity were measured by an automatic meteorological

298

station at this site with a time resolution of 1 minute.

299

3 Results

300

3.1 Time series

301

Figure 3 shows the time series of HCHOg, HCHOp, acetonitrile, PM2.5, O3, and the

302

meteorological parameters. It is well known that significant enhancements of

303

acetonitrile indicate biomass burning emissions, and the background level is about 0.1

304

ppb (de Gouw et al., 2003). In this campaign, sharp peaks of acetonitrile were

305

observed frequently and mostly appeared at night. For convenience, these periods

306

were identified as biomass burning–influenced plumes (BB plumes), identified with

307

yellow shading in Fig. 3. In correlation with the BB plumes, HCHOg, HCHOp, and

308

PM2.5 also showed increases from their typical levels. Quick enhancements of HCHOg

309

were observed along with acetonitrile, reaching as high as 16 ppb. Wang et al. (2016)

310

measured the mixing ratio of HCHOg as high as 25 ppb during BB plumes. In the

311

daytime, HCHOg increased rapidly after sunrise because of the photochemical 15

312

reaction of VOCs. However, the peak values of HCHOp in the BB plumes were far

313

above the normal values, reaching 2.5 µg/m3 (2.1 ppb) and occupying 12% of the total

314

HCHO. Toda et al. (2014) reported that HCHOp contributed 5% of the total HCHO on

315

average based on 1296 data pairs. The reasons for the remarkable rise of HCHOp in

316

the BB plumes are further discussed later.

317 318

Fig. 3. Time series of meteorological parameters, acetonitrile, PM2.5, O3, HCHOg, and HCHOp

319

measured at Taizhou (the yellow-shaded areas indicate BB plumes, and the dashed lines

320

indicate midnight).

321

During the BB plumes, wheat and rapeseed were being harvested nearby, and straw

322

was being set on fire in the field. Fire maps (Fig. S1) also confirm that biomass

323

burning

324

(https://firms.modaps.eosdis.nasa.gov). Thus, acetonitrile enhancement during the

325

campaign was likely due to sporadic open burning of crop straw in the field. As open

326

burning is illegal in Jiangsu Province, straw burning usually happens at night, which

327

corresponds with the peak time of acetonitrile.

activities

were

frequent

16

in

surroundings

328

3.2 Enhancement ratios of HCHOg in biomass burning

329

The enhancement ratio (ER) is defined as the excess of a species (△x, the mixing

330

ratio of species “X” in the plume above the mixing ratio of the background of species

331

“X”) divided by the excess of another species (△y), generally CO or acetonitrile

332

(Akagi et al., 2011). The ER is a widely used parameter in biomass burning studies

333

(Li et al., 2014a; Wang et al., 2016; Yuan et al., 2010). Here, the ER (relative to

334

acetonitrile) of HCHOg is determined by correlating the mixing ratio of HCHOg with

335

acetonitrile from fresh BB plumes and calculating the slope of the regression line

336

between the two compounds. Figure 4 (a) shows the burning event that happened on 5

337

June 2018, during which HCHOg and acetonitrile increased rapidly at the same time.

338

The linear regression analysis between HCHOg and acetonitrile in this burning event

339

is plotted in Fig. 4 (b). To a large extent, the value of ERs were decided by type of

340

biomass burning. The comparison of the estimated ERs of crop residues or

341

approximate type with the literature values are listed in Table 1 (Akagi et al., 2011;

342

Arlander et al., 1995; Karl et al., 2007; Li et al., 2014a). Due to the difference of crop

343

or the distance of the source to observation site, the ERs ranged from 4.5 to 13.5. The

344

ER of HCHOg in this study was close to that of burning of foliage and woody

345

material.

17

346 347

Fig. 4. (a) Variations in HCHOg and acetonitrile during a biomass burning event that occurred

348

on the morning of 5 June 2018. (b) Correlations between HCHOg and acetonitrile.

349

Table 1. ERs with respect to acetonitrile (ppb/ppb), comparisons to existing literature values,

350

and types of biomass burning. Type

ER

Reference

agricultural residues

9.56

(Andreae and Merlet, 2001)

crop residues

13.5

(Akagi et al., 2011)

foliage burned in Missoula burning facility

4.6±3.0 (Karl et al., 2007)

a mixture of foliage and woody material

4.5±3.7

home cooking and heating, smoking bacon, and garbage burning

8.5

(Li et al., 2014a)

crop residue

5.8

This study

351 352

3.3 Biomass burning contribution to HCHOg

353

The site for the campaign is in the suburbs surrounded by farmland, but it is also

354

adjacent to two expressways. Therefore, the main sources of HCHO are biomass

355

burning, traffic, and secondary production. Acetonitrile, n-pentane, and PAN are 18

356

chosen as the tracers of the sources mentioned (Li et al., 2014b). A multi-linear

357

regression model is used to calculate the portions of the sources that contributed to the

358

HCHOg. The results of the estimated source contributions are shown in Fig. 5. The

359

calculated concentrations of HCHOg agreed well with the measured values during the

360

campaign, and the R value is 0.87, indicating that the linear relationship is statistically

361

reliable. During the whole period, the background HCHOg represented most of the

362

concentration on average (46.7%), and biomass burning contributed 14.8%. The

363

contributing proportion of secondary production is the largest of the three sources

364

(26.5%), especially after the intense burning activities. It is assumed that the VOCs

365

emitted by biomass burning promoted the secondary production of HCHOg. Another

366

part of the secondary production is biogenic source, which mainly comes from

367

oxidation of isoprene. We classified HCHO precursors into biogenic VOCs and

368

anthropogenic VOCs (alkanes, alkanes, aromatics, alkyne), and showed the precursors

369

reactivity in Fig. S2. The biogenic VOCs included isoprene, methacrolein (MACR)

370

and methylvinylketone (MVK), and the reactivity of them account for 21% of total

371

precursors reactivity. Though anthropogenic VOCs contributed most to the secondary

372

production, at certain times biogenic source played a great role in that. During the

373

period of 6.16 to 6.18, the reactivity of anthropogenic VOCs at night was higher than

374

that in the daytime, while the reactivity of biogenic VOCs was opposite. And the

375

diurnal of secondary HCHO was similar with that of the reactivity of biogenic VOCs,

376

which meant that biogenic source was dominant in secondary source in this period.

19

377 378

Fig. 5. Time series of the calculated (multi-linear regression model) and measured

379

concentrations of HCHOg at Taizhou.

380

4 Discussion

381

4.1 The production of HCHOg and HCHOp: case studies

382

The concentrations of HCHOg and HCHOp were enhanced rapidly during the BB

383

plumes. However, the source apportionment of HCHOg indicates that biomass

384

burning is not the main contributor to the high mixing ratio of HCHOg, and the source

385

of the high HCHOp during the fire activities is uncertain. Two distinct periods were

386

therefore chosen to be analyzed. The period from 3–8 June was impacted by extensive

387

BB plumes, while the period of 15–18 June was clear.

388

4.1.1 Case Study 1: 3–8 June

389

Figure 6 (a-d) examines the profiles of HCHOg, HCHOp, their ratio (HCHOp/(HCHOg

390

+ HCHOp)), acetonitrile, J(O1D), RH, particle rebound fraction f, PM1 particulate

391

matter chemical composition fraction, f60, VOC reactivity, and uptake coefficient of

392

period 1. The rebound fraction f is used to infer the particle phase state at the ambient

393

RH. When the rebound fraction f changes from 0 to 1, the particles changed from

394

adhering to rebounding (Liu et al., 2017). f60 is the ratio of the signal at m/z 60 from

395

the mass spectrum to the total signal of organic aerosols , which is the tracer of

396

biomass burning (Zheng et al., 2017). VOC reactivity is an index for evaluating the 20

397

amounts of reductive VOCs in terms of ambient OH loss and their roles in

398

atmospheric oxidation, which is defined as:

399

=∑

VOC , (2)

400

where ki is the reaction rate constant for the reaction, and the ki values were taken

401

from the work of Yang et al. (2017). The initial uptake coefficient (γ0) is defined as

402

the reactive uptake rate of the adsorbate divided by the total number of gas-surface

403

collisions per unit time (Xu et al., 2011). Here, the uptake coefficient (γ) was obtained

404

from the measured change in HCHOp via Equations 3 and 4:

405

#=

$%&'&() * $+,-∗/

, (3) 9:;

406

0 = 1 234546 7 = 1 234546 78<=>, (4)

407

where d(HCHOp)/dt represents the reactive uptake rate of HCHO by particle surfaces,

408

Z is the rate of collisions of the HCHOg molecules with the particle surfaces, ? is the

409

mean molecular velocity of HCHOg, M is the molecular weight of HCHO, and A is

410

the effective surface area of the particles. We adopt the particle surface area

411

concentration of PM2.5 to calculate the effective surface area of the particles. As the

412

interval of the particle surfaces is at a maximum (5 min), $+,- is determined to be 5

413

min, and other parameters are also in 5-min averages. We assumed that the collected

414

particles came from the same air mass in 5 minutes and that γ represented the uptake

415

capacity of particles at the observation site in 5 minutes.

21

416

417 418 419

Fig. 6. Temporal profiles of HCHOg, the ratio (HCHOp/(HCHOg + HCHOp)), and VOC

420

reactivity, (b, f) HCHOp, O3, acetonitrile and f60, (c, g) uptake coefficient, rebound fraction f,

421

J(O1D) and RH, (d, h) mass fractions of different chemical species. The gray background of

422

(a~d) denotes biomass burning events (identified in Sect. 4.1.1), (e~h) denotes periods with

423

high uptake coefficient (identified in Sect. 4.1.2).

424

The periods with rapid increases of acetonitrile and f60, which were influenced by

425

intensive open burning, are shown as gray shaded areas. For convenience, these heavy

426

pollution episodes were defined as intensive BB plumes (IBB plumes). Biomass

427

burning emits HCHOg, acetonitrile, and other VOC species simultaneously, so there 22

428

are some similarities in the variations of their mixing ratios. Figure 6 (a) illustrates

429

that the HCHOg and VOC reactivity were enhanced quickly in IBB plumes. Except

430

for the peak during the burning, HCHOg reached another peakafter 2 or 3 hours.

431

Considering that the fire activities often occurred before dawn, the sun rose later (Fig.

432

6 (c), J(O1D)), and then photochemical reactions began. With the abundant freshly

433

discharged precursors, the secondary production of HCHOg was dominant. The source

434

contributions of HCHOg (Fig. 5) also confirmed this. Thus, the contribution of

435

biomass burning to HCHOg is low in this study (14.8%), compared to that in Li et al.

436

(2014a) (31.9%).

437

Figure 6 (b) shows the rapid enhancement of HCHOp during the IBB plumes;

438

meanwhile, the variation in HCHOp coincides with that of acetonitrile and f60. In this

439

case, we put forward two possible causes. The first is that HCHOp has the same

440

source as acetonitrile—biomass burning. That is to say, biomass burning emits

441

HCHOg and HCHOp.

442

Previous studies have suggested that HCHOp came from the uptake of HCHOg by

443

aerosols. Another assumption is that HCHOg discharged by biomass burning was

444

taken in by aerosols during the transportation from fire locations to the observation

445

site, as biomass burning also emits lots of aerosols. This provides a good

446

interpretation for the slow growth of HCHOg in IBB plumes. Furthermore, HCHO

447

may not remain in aerosols under the high temperatures during burning because of its

448

effumability. Paraformaldehyde, one possible form of HCHOp, is expected to

449

decompose when heated to 70 ºC (Toda et al., 2014). 23

450

Figure 6 (c) shows that the RH is high and the particle rebound fraction f ranges from

451

low to zero during the IBB plumes, which suggests that the particles transitioned into

452

a liquid state and benefitted from uptake, according to Liu et al. (2017). Liu et al.

453

(2017) also emphasized the dominance of the inorganic component on the particle

454

phase state; the proportion of the inorganic component in aerosols was between 40–80%

455

during their study, and the aerosol phase was adhered to when the organic component

456

was dominant. In this study, the organic component proportion is high during IBB

457

plumes, roughly 60–80%, so the particles may not be in a liquid state. The calculated

458

uptake coefficient γ is averaged to an hour and plotted on Fig. 6 (c). The value of γ

459

was between ~10-8–10-3, and it remained less than 10-3 for most of the time. The

460

uptake coefficient is likely ~10-7–0.023, based on past studies (Iraci et al., 1995; Jayne

461

et al., 1992; Sassine et al., 2010; Tie et al., 2001; Xu et al., 2011). The γ calculated

462

online indicated that the measured HCHOg and HCHOp were in reasonable ranges.

463

The averaged γ was 1.4 × 10-4 during IBB plumes, a little less than the average γ (2.1

464

× 10-4). However, it is not inconsistent that HCHOp is high but γ is low. The

465

calculated γ is the aerosols’ uptake capacity in the 5 minutes before it was collected,

466

and the high HCHOp is a result of long-time accumulation. The γ, aerosol component,

467

and other parameters that we discussed were measured at the same time and at the

468

same location.

469

4.1.2 Case Study 2: 15–18 June

470

Figure 6 (e-h) illustrates parameters during the second case study. During this time

471

period, the max mixing ratio of ozone did not exceed 80 ppb, and the concentration of 24

472

PM2.5 was under 40 µg/m3 (Fig. 3), which satisfies the first class of ambient air

473

quality standards. HCHOg has the same variation with ozone, reaching its peak at

474

noon via secondary production alone. The concentration of HCHOp was much lower

475

than in the first case study, between ~0–0.2 µg/m3. Periods with biomass burning

476

resulted in high proportion of the organic component in particles (Zheng et al., 2017),

477

and also brought about high concentration of O3 and PM2.5 due to abundant

478

precursors. In clean days with low O3 and PM2.5, particles were mainly composed of

479

inorganic component, which had a great influence on phase state of particles. In this

480

case, the inorganic component was dominant in the aerosols and occupied ~60–90%

481

of the mass concentration. The two periods had high RH values and a low particle

482

rebound fraction f, during which the average portion of the inorganic component was

483

about 80%. Thus, the particle phase could be regarded as being in liquid state. The

484

calculated γ in these two periods was higher than in other times with an average of 5.3

485

× 10-4, more than twice the average during the whole campaign (2.1 × 10-4). This also

486

confirms that the liquid particles might readily uptake pollutants (Liu et al., 2017).

487

4.1.3 Implications of the case studies

488

The two case studies discussed above demonstrate the changes in HCHOg and

489

HCHOp during haze episodes and on clean days and identify the responses of the

490

uptake coefficient to the changes in the related parameters (RH, rebound fraction f,

491

particulate matter chemical composition fraction). For HCHOg, biomass burning

492

emits primary HCHOg and precursors that facilitate secondary production in haze

493

episodes, which improve the HCHOg levels greatly. As for HCHOp, a combustion 25

494

chamber experiment is needed to verify the primary emissions from biomass burning.

495

4.2 Uptake coefficient γ

496

The uptake coefficient γ is influenced by many factors; figure 7 shows the correlations

497

among the ratio, RH, particle rebound fraction f, temperature, and uptake coefficient.

498

In order to make the relationship between the dependent variable and the independent

499

variable more explicit, the method introduced by Stutz et al. (2004) was adopted. We

500

analyzed the top 20% of dependent variables in each independent variable interval,

501

and the interval range changed according to the quantity of the corresponding

502

dependent variable. As RH increases, the probability of high ratio values with respect

503

to γ is higher. The same phenomenon with respect to the ratio and RH was also

504

observed by Toda et al. (2014) in Japan. When the value of the particle rebound

505

fraction f is 0 to 0.1, the γ is much higher, and the variation of γ is not obvious when

506

the rebound fraction f is in the range of 0.1 to 1.2. The correlation of γ with the RH

507

and particle rebound fraction f are in agreement in the two case studies; when RH is

508

high and the particle rebound fraction f is close to zero, the particle phase state may

509

change to a liquid phase and result in a high γ, which is determined by the particle

510

component. It is well known that HCHO is soluble in the liquid water content of

511

particles and reacts with water to form hydrates, gem-diols, and even polymers (Eqs. 5,

512

6, 7); meanwhile, Shen et al. (2018) referred to very different correlations between the

513

RH and HCHO partitioning coefficient in Beijing and speculated that high water

514

concentrations at elevated RH levels may hinder oligomerization reactions. However,

515

the overall reaction (Eq. 8) shows that aerosol liquid water content would promote 26

516

more HCHOg in the particle phase through aqueous reactions. The increasing RH

517

elevates the aerosol liquid water content, leading to the increasing γ:

518

HCHO + H< O ⇔ CH< +OH-<,

(5)

519

CH< +OH-< + +n − 1-HCHO ⇔ HO+CH< O-E H,

(6)

520

nCH< +OH-< ⇔ HO+CH< O-E H + +n − 1-H< O,

(7)

521

nHCHO + H< O ⇔ HO+CH< O-E H.

(8)

522

From Fig. 7, it can be seen that high temperatures lower the probability of high values

523

of γ. In previous field studies, Iraci and Tolbert (1997) similarly suggested that

524

ultralow temperatures could enhance γ effectively. Temperature affects γ in two ways.

525

First, high temperatures promote the volatilization of HCHO so that less HCHO will

526

remain in particles. Additionally, higher molecular velocities due to high temperatures

527

lead to low γ values (Eqs. 3, 4). On the other hand, aerosols with inorganic matter as

528

their main component are more likely to become hygroscopic aerosols, and low

529

temperatures and high humidity are conducive to hygroscopic aerosol growth.

530

Mitsuishi et al. (2018) found dicarbonyls and formaldehyde easily dissolve into

531

hygroscopic aerosols during they growth, which is consistent with our result.

27

532 533

Fig. 7. Correlations among ratio, RH, particle rebound fraction f, temperature, and uptake

534

coefficient. Triangles are the averaged top 20% dependent variables in each independent

535

variable interval.

536

The average field-derived effective Henry’s law coefficient is 6.6 × 107 in this study

537

(calculated by Shen et al., 2018), far higher than the Henry’s law constant (KH = 3555

538

M/atm) at 23.5 °C (the average temperature during the campaign) (Allou et al., 2011).

539

Previous studies have found similar results and attribute the findings to polymers that

540

formed via HCHO and aerosol liquid water contents. Using the Hantzsch method,

541

oligomers like the cyclic HCHO trimer 1, 3, 5-trioxane and paraformaldehyde may

542

hydrolyze to HCHO monomers and be measured as HCHOp. However, Toda et al.

543

(2014) also pointed out that not all of the oligomer was measured. Beyond that, the

544

products by which HCHO reacted with air pollutants in particles are ignored in this

545

study. Therefore, this leaves open the possibility that the actual value of γ is higher.

546

5. Conclusions 28

547

The HCHOg and HCHOp were measured at Taizhou in YRD from May to June of

548

2018, aiming at evaluating the influence of different environmental elements on

549

HCHOg and HCHOp. During the campaign, using acetonitrile as a tracer, several

550

biomass burning events were identified. During the period influenced by biomass

551

burning, the mixing ratios of HCHOg and HCHOp were 122% and 231% higher than

552

those during other times.

553

The ER was evaluated by the slope of HCHOg/acetonitrile, and the result showed that

554

the ER of HCHOg was similar to that in other regions. A multi-linear regression model

555

was used to apportion sources of HCHOg. Secondary production contributed most to

556

the HCHOg after taking out the background values. These results, in combination with

557

the case studies, indicate that the abundant freshly discharged precursors emitted by

558

biomass burning events greatly promoted the secondary production of HCHOg.

559

The great correlation between HCHOp and biomass burning traces during the fire

560

activities suggested that biomass burning may be another source of HCHOp (except

561

with respect to the uptake of aerosols), while the HCHOp may volatilize from aerosols

562

given the high temperature of the fire. We suppose that HCHOg was taken up into the

563

aerosols during the transportation. The high γ in the second case study verified that

564

the liquid state particles are conducive to uptake of reactive gases.

565

High RH, a low particle rebound fraction f, as well as low temperatures may result in

566

higher γ values, which is consistent with results from some of the previous literature

567

(Jayne et al., 1992; Liu et al., 2017; Toda et al., 2014). However, as the HCHOg taken

568

into the particles may change into other forms, the HCHOp measured by the Hantzsch 29

569

method is relatively low. Clearly, more intensive laboratory-based experiments are

570

necessary to explore what reaction may occur after the HCHOg is taken up into the

571

particles. In addition, more detailed work on the particle liquid state is still needed,

572

which is helpful for the uptake process.

573

30

574

Data availability. The data in the figures in the main text are available upon request to

575

the corresponding author ([email protected]).

576

Competing interests. The authors declare that they have no conflict of interest.

577

Acknowledgements. This work was supported by the National Natural Science

578

Foundation of China (91644108, 91544225) and by the National Key R&D Program

579

of China (2016YFC0202003, 2016YFC0202206).

31

580

Reference

581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622

Akagi, S., Yokelson, R.J., Wiedinmyer, C., Alvarado, M., Reid, J., Karl, T., Crounse, J., Wennberg, P., 2011. Emission factors for open and domestic biomass burning for use in atmospheric models. Atmos. Chem. Phys. 11, 4039-4072. Alicke, B., Platt, U., Stutz, J., 2002. Impact of nitrous acid photolysis on the total hydroxyl radical budget during the Limitation of Oxidant Production/Pianura Padana Produzione di Ozono study in Milan. J. Geophys. Res.-Atmos. 107, doi: 10.1029/2000jd000075. Allou, L., El Maimouni, L., Le Calvé, S., 2011. Henry’s law constant measurements for formaldehyde and benzaldehyde as a function of temperature and water composition. Atmos. Environ. 45, 2991-2998. Andraca-Ayala, G., Ruiz-Suarez, L.G., 2005. Partitioning of formaldehyde between gas phase and particles (PM2.5) in Mexico City. Atmosfera 18, 189-203. Andreae, M.O., Merlet, P., 2001. Emission of trace gases and aerosols from biomass burning. Global Biogeochem. Cycles 15, 955-966. Arlander, D.W., Bruning, D., Schmidt, U., Ehhalt, D.H., 1995. THE TROPOSPHERIC DISTRIBUTION OF FORMALDEHYDE DURING TROPOZ-II. J. Atmos. Chem. 22, 251-269. Cerón, R., Cerón, J., Muriel, M., 2007. Diurnal and seasonal trends in carbonyl levels in a semi-urban coastal site in the Gulf of Campeche, Mexico. Atmos. Environ. 41, 63-71. Chatfield, R.B., Ren, X., Brune, W., Schwab, J., 2010. Controls on urban ozone production rate as indicated by formaldehyde oxidation rate and nitric oxide. Atmos. Environ. 44, 5395-5406. de Gouw, J.A., Brock, C.A., Atlas, E.L., Bates, T.S., Fehsenfeld, F.C., Goldan, P.D., Holloway, J.S., Kuster, W.C., Lerner, B.M., Matthew, B.M., Middlebrook, A.M., Onasch, T.B., Peltier, R.E., Quinn, P.K., Senff, C.J., Stohl, A., Sullivan, A.P., Trainer, M., Warneke, C., Weber, R.J., Williams, E.J., 2008. Sources of particulate matter in the northeastern United States in summer: 1. Direct emissions and secondary formation of organic matter in urban plumes. Journal of Geophysical Research: Atmospheres 113, doi: 10.1029/2007JD009243. de Gouw, J.A., Middlebrook, A.M., Warneke, C., Goldan, P.D., Kuster, W.C., Roberts, J.M., Fehsenfeld, F.C., Worsnop, D.R., Canagaratna, M.R., Pszenny, A.A.P., Keene, W.C., Marchewka, M., Bertman, S.B., Bates, T.S., 2005. Budget of organic carbon in a polluted atmosphere: Results from the New England Air Quality Study in 2002. J. Geophys. Res.-Atmos. 110, doi: 10.1029/2004jd005623. de Gouw, J.A., Warneke, C., Parrish, D.D., Holloway, J.S., Trainer, M., Fehsenfeld, F.C., 2003. Emission sources and ocean uptake of acetonitrile (CH3CN) in the atmosphere. J. Geophys. Res.-Atmos. 108, doi: 10.1029/2002jd002897. Deandrade, J.B., Pinheiro, H.L.C., Andrade, M.V., 1995. THE FORMALDEHYDE AND ACETALDEHYDE CONTENT OF ATMOSPHERIC AEROSOL. J. Braz. Chem. Soc. 6, 287-290. Dixon, R.W., Aasen, H., 1999. Measurement of hydroxymethanesulfonate in atmospheric aerosols. Atmos. Environ. 33, 2023-2029. Dong, H.B., Zeng, L.M., Hu, M., Wu, Y.S., Zhang, Y.H., Slanina, J., Zheng, M., Wang, Z.F., Jansen, R., 2012. Technical Note: The application of an improved gas and aerosol collector for ambient air pollutants in China. Atmos. Chem. Phys. 12, 10519-10533. Harrison, R., Yin, J., Tilling, R., Cai, X., Seakins, P., Hopkins, J., Lansley, D., Lewis, A., Hunter, M., Heard, D., 2006. Measurement and modelling of air pollution and atmospheric chemistry in the UK West Midlands conurbation: Overview of the PUMA Consortium project. Sci. Total Environ. 360, 5-25. 32

623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666

Hellén, H., Hakola, H., Reissell, A., Ruuskanen, T., 2004. Carbonyl compounds in boreal coniferous forest air in Hyytiälä, Southern Finland. Atmos. Chem. Phys. 4, 1771-1780. Huang, G.C., Liu, Y., Shao, M., Li, Y., Chen, Q., Zheng, Y., Wu, Z.J., Liu, Y.C., Wu, Y.S., Hu, M., Li, X., Lu, S.H., Wang, C.J., Liu, J.Y., Zheng, M., Zhu, T., 2019. Potentially Important Contribution of Gas-Phase Oxidation of Naphthalene and Methylnaphthalene to Secondary Organic Aerosol during Haze Events in Beijing. Environ. Sci. Technol. 53, 1235-1244. Iraci, L.T., Middlebrook, A.M., Tolbert, M.A., 1995. Laboratory studies of the formation of polar stratospheric clouds: Nitric acid condensation on thin sulfuric acid films. Journal of Geophysical Research: Atmospheres 100, 20969-20977. Iraci, L.T., Tolbert, M.A., 1997. Heterogeneous interaction of formaldehyde with cold sulfuric acid: Implications for the upper troposphere and lower stratosphere. J. Geophys. Res.-Atmos. 102, 16099-16107. Jacob, D.J., Wofsy, S.C., 1988. Photochemistry of biogenic emissions over the Amazon forest. Journal of Geophysical Research: Atmospheres 93, 1477-1486. Jayne, J.T., Duan, S.X., Davidovits, P., Worsnop, D.R., Zahniser, M.S., Kolb, C.E., 1992. UPTAKE OF GAS-PHASE ALDEHYDES BY WATER SURFACES. J. Phys. Chem. 96, 5452-5460. Jayne, J.T., Worsnop, D.R., Kolb, C.E., Swartz, E., Davidovits, P., 1996. Uptake of gas-phase formaldehyde by aqueous acid surfaces. J. Phys. Chem. 100, 8015-8022. Jing, B., Tong, S.R., Liu, Q.F., Li, K., Wang, W.G., Zhang, Y.H., Ge, M.F., 2016. Hygroscopic behavior of multicomponent organic aerosols and their internal mixtures with ammonium sulfate. Atmos. Chem. Phys. 16, 4101-4118. Kaiser, J., Li, X., Tillmann, R., Acir, I., Holland, F., Rohrer, F., Wegener, R., Keutsch, F.N., 2014. Intercomparison of Hantzsch and fiber-laser-induced-fluorescence formaldehyde measurements. Atmos. Meas. Tech. 7, 1571-1580. Karl, T., Christian, T.J., Yokelson, R.J., Artaxo, P., Hao, W.M., Guenther, A., 2007. The Tropical Forest and Fire Emissions Experiment: method evaluation of volatile organic compound emissions measured by PTR-MS, FTIR, and GC from tropical biomass burning. Atmos. Chem. Phys. 7, 5883-5897. Kesselmeier, J., Bode, K., Hofmann, U., Müller, H., Schäfer, L., Wolf, A., Ciccioli, P., Brancaleoni, E., Cecinato, A., Frattoni, M., 1997. Emission of short chained organic acids, aldehydes and monoterpenes from Quercus ilex L. and Pinus pinea L. in relation to physiological activities, carbon budget and emission algorithms. Atmos. Environ. 31, 119-133. Kiernan, J., 2000. Formaldehyde, Formalin, Paraformaldehyde And Glutaraldehyde: What They Are And What They Do. Microscopy Today 8, 8-12. Kudo, S., Tanimoto, H., Inomata, S., Saito, S., Pan, X., Kanaya, Y., Taketani, F., Wang, Z., Chen, H., Dong, H., 2014. Emissions of nonmethane volatile organic compounds from open crop residue burning in the Yangtze River Delta region, China. Journal of Geophysical Research: Atmospheres 119, 7684-7698. Li, L.Y., Chen, Y., Zeng, L.M., Shao, M., Xie, S.D., Chen, W.T., Lu, S.H., Wu, Y.S., Cao, W., 2014a. Biomass burning contribution to ambient volatile organic compounds (VOCs) in the Chengdu-Chongqing Region (CCR), China. Atmos. Environ. 99, 403-410. Li, M., Shao, M., Li, L.-Y., Lu, S.-H., Chen, W.-T., Wang, C., 2014b. Quantifying the ambient formaldehyde sources utilizing tracers. Chin. Chem. Lett. 25, 1489-1491. Li, X., Rohrer, F., Hofzumahaus, A., Brauers, T., Haseler, R., Bohn, B., Broch, S., Fuchs, H., Gomm, S., Holland, F., Jager, J., Kaiser, J., Keutsch, F.N., Lohse, I., Lu, K.D., Tillmann, R., Wegener, R., Wolfe, 33

667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710

G.M., Mentel, T.F., Kiendler-Scharr, A., Wahner, A., 2014. Missing Gas-Phase Source of HONO Inferred from Zeppelin Measurements in the Troposphere. Science 344, 292-296. Li, Y., Shao, M., Lu, S., Chang, C.-C., Dasgupta, P.K., 2010. Variations and sources of ambient formaldehyde for the 2008 Beijing Olympic games. Atmos. Environ. 44, 2632-2639. Liu, Y., Wu, Z., Wang, Y., Xiao, Y., Gu, F., Zheng, J., Tan, T., Shang, D., Wu, Y., Zeng, L., 2017. Submicrometer Particles Are in the Liquid State during Heavy Haze Episodes in the Urban Atmosphere of Beijing, China. Environmental Science & Technology Letters. Mitsuishi, K., Iwasaki, M., Takeuchi, M., Okochi, H., Kato, S., Ohira, S.I., Toda, K., 2018. Diurnal Variations in Partitioning of Atmospheric Glyoxal and Methylglyoxal between Gas and Particles at the Ground Level and in the Free Troposphere. ACS Earth Space Chem. 2, 915-924. Muller, J.F., Stavrakou, T., 2005. Inversion of CO and NOx emissions using the adjoint of the IMAGES model. Atmos. Chem. Phys. 5, 1157-1186. Odabasi, M., Seyfioglu, R., 2005. Phase partitioning of atmospheric formaldehyde in a suburban atmosphere. Atmos. Environ. 39, 5149-5156. Possanzini, M., Di Palo, V., Cecinato, A., 2002. Sources and photodecomposition of formaldehyde and acetaldehyde in Rome ambient air. Atmos. Environ. 36, 3195-3201. Sassine, M., Burel, L., D'Anna, B., George, C., 2010. Kinetics of the tropospheric formaldehyde loss onto mineral dust and urban surfaces. Atmos. Environ. 44, 5468-5475. Scheinhardt,

S.,

van

Pinxteren,

D.,

Muller,

K.,

Spindler,

G.,

Herrmann,

H.,

2014.

Hydroxymethanesulfonic acid in size-segregated aerosol particles at nine sites in Germany. Atmos. Chem. Phys. 14, 4531-4538. Shen, H.Q., Chen, Z.M., Li, H., Qian, X., Qin, X., Shi, W.X., 2018. Gas-Particle Partitioning of Carbonyl Compounds in the Ambient Atmosphere. Environ. Sci. Technol. 52, 10997-11006. Shepson, P., Hastie, D., Schiff, H., Polizzi, M., Bottenheim, J., Anlauf, K., Mackay, G., Karecki, D., 1991. Atmospheric concentrations and temporal variations of C1-C3 carbonyl compounds at two rural sites in central Ontario. Stutz, J., Alicke, B., Ackermann, R., Geyer, A., Wang, S.H., White, A.B., Williams, E.J., Spicer, C.W., Fast, J.D., 2004. Relative humidity dependence of HONO chemistry in urban areas. J. Geophys. Res.-Atmos. 109, doi: 10.1029/2003jd004135. Tie, X., Brasseur, G., Emmons, L., Horowitz, L., Kinnison, D., 2001. Effects of aerosols on tropospheric oxidants: A global model study. J. Geophys. Res. 106, doi: 10.1029/2001jd900206. Toda, K., Tokunaga, W., Gushiken, Y., Hirota, K., Nose, T., Suda, D., Nagai, J., Ohira, S.-I., 2012. Mobile monitoring along a street canyon and stationary forest air monitoring of formaldehyde by means of a micro-gas analysis system. J. Environ. Monit. 14, 1462-1472. Toda, K., Yunoki, S., Yanaga, A., Takeuchi, M., Ohira, S.-I., Dasgupta, P.K., 2014. Formaldehyde Content of Atmospheric Aerosol. Environ. Sci. Technol. 48, 6636-6643. Wang, B.L., Liu, Y., Shao, M., Lu, S.H., Wang, M., Yuan, B., Gong, Z.H., He, L.Y., Zeng, L.M., Hu, M., Zhang, Y.H., 2016. The contributions of biomass burning to primary and secondary organics: A case study in Pearl River Delta (PRD), China. Sci. Total Environ. 569, 548-556. Wang, M., Zeng, L., Lu, S., Shao, M., Liu, X., Yu, X., Chen, W., Yuan, B., Zhang, Q., Hu, M., 2014. Development and validation of a cryogen-free automatic gas chromatograph system (GC-MS/FID) for online measurements of volatile organic compounds. Anal. Methods 6, 9424-9434. Wisthaler, A., Apel, E.C., Bossmeyer, J., Hansel, A., Junkermann, W., Koppmann, R., Meier, R., Muller, K., Solomon, S.J., Steinbrecher, R., Tillmann, R., Brauers, T., 2008. Technical Note: Intercomparison of 34

711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738

formaldehyde measurements at the atmosphere simulation chamber SAPHIR. Atmos. Chem. Phys. 8, 2189-2200. Xiaoyan, W., Huixiang, W., Shaoli, W., 2010. Ambient formaldehyde and its contributing factor to ozone and OH radical in a rural area. Atmos. Environ. 44, 2074-2078. Xu, B., Shang, J., Zhu, T., Tang, X., 2011. Heterogeneous reaction of formaldehyde on the surface of γ-Al2O3 particles. Atmos. Environ. 45, 3569-3575. Xue, Y., Xu, H., Guang, J., Mei, L., Guo, J., Li, C., Mikusauskas, R., He, X., 2014. Observation of an agricultural biomass burning in central and east China using merged aerosol optical depth data from multiple satellite missions. Int. J. Remote Sens. 35, 5971-5983. Yang, Y.D., Shao, M., Kessel, S., Li, Y., Lu, K.D., Lu, S.H., Williams, J., Zhang, Y.H., Zeng, L.M., Noelscher, A.C., Wu, Y.S., Wang, X.M., Zheng, J.Y., 2017. How the OH reactivity affects the ozone production efficiency: case studies in Beijing and Heshan, China. Atmos. Chem. Phys. 17, 7127-7142. Yuan, B., Chen, W.T., Shao, M., Wang, M., Lu, S.H., Wang, B., Liu, Y., Chang, C.C., Wang, B.G., 2012a. Measurements of ambient hydrocarbons and carbonyls in the Pearl River Delta (PRD), China. Atmos. Res. 116, 93-104. Yuan, B., Liu, Y., Shao, M., Lu, S.H., Streets, D.G., 2010. Biomass Burning Contributions to Ambient VOCs Species at a Receptor Site in the Pearl River Delta (PRD), China. Environ. Sci. Technol. 44, 4577-4582. Yuan, B., Shao, M., de Gouw, J., Parrish, D.D., Lu, S.H., Wang, M., Zeng, L.M., Zhang, Q., Song, Y., Zhang, J.B., Hu, M., 2012b. Volatile organic compounds (VOCs) in urban air: How chemistry affects the interpretation of positive matrix factorization (PMF) analysis. J. Geophys. Res.-Atmos. 117, doi: 10.1029/2012jd018236. Zheng, J., Hu, M., Du, Z.F., Shang, D.J., Gong, Z.H., Qin, Y.H., Fang, J.Y., Gu, F.T., Li, M.R., Peng, J.F., Li, J., Zhang, Y.Q., Huang, X.F., He, L.Y., Wu, Y.S., Guo, S., 2017. Influence of biomass burning from South Asia at a high-altitude mountain receptor site in China. Atmos. Chem. Phys. 17, 6853-6864. Zheng, J., Hu, M., Peng, J., Wu, Z., Kumar, P., Li, M., Wang, Y., Guo, S., 2016. Spatial distributions and chemical properties of PM2.5 based on 21 field campaigns at 17 sites in China. Chemosphere 159, 480-487.

35

Highlight 1.

Simultaneous online measurements of gaseous HCHO and particulate HCHO were conducted.

2.

Precursors emitted by biomass burning promoted the secondary production of gaseous HCHO.

3.

Particles in liquid state are conducive to uptake HCHO.

4.

High RH and lower temperature may result in higher uptake coefficient.

Declaration of interests ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: