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Water Interaction with Mineral Dust Aerosol: Particle Size and Hygroscopic Properties of Dust Sara Ibrahim, Manolis N. Romanias, Laurent Alleman, Mohamad N. Zeineddine, Giasemi Angeli, Pantelis N. Trikalitis, and Frederic Thevenet ACS Earth Space Chem., Just Accepted Manuscript • DOI: 10.1021/ acsearthspacechem.7b00152 • Publication Date (Web): 02 Mar 2018 Downloaded from http://pubs.acs.org on March 6, 2018

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ACS Earth and Space Chemistry

Water Interaction with Mineral Dust Aerosol: Particle Size and Hygroscopic Properties of Dust

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

Sara Ibrahim,1 Manolis N. Romanias*,1 Laurent Y. Alleman,1 Mohamad N. Zeineddine,1 Giasemi K. Angeli,2 Pantelis N. Trikalitis,2 Frederic Thevenet.1

1

: IMT Lille Douai, Univ. Lille, SAGE - Département Sciences de l’Atmosphère et Génie de l’Environnement, 59000 Lille, France

2

: Department of Chemistry, University of Crete, Voutes, 71003 Heraklion, Greece

20

*

Corresponding author:

21

Manolis N. Romanias, Tel.: +33 (0)3 27 71 26 33; Fax: +33 (0)3 27 71 29 14; E-mail:

22

[email protected]

ACS Paragon Plus Environment

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Abstract

24

For many years, the interaction between dust particles and water molecules has been a subject of

25

interest for the atmospheric sciences community. However, the influence of particles size on the

26

hygroscopicity of mineral particles is poorly evaluated. In the current study, Diffused Reflectance

27

Infrared Fourier Transform Spectroscopy (DRIFTS) is used to evaluate the in-situ water adsorption

28

on natural Arizona Test Dust (ATD) particles. Five different ATD dust sizes fractions, 0-3, 5-10, 10-

29

20, 20-40 and 40-80 µm are used, corresponding to the entire range of uplifted mineral particles in

30

the atmosphere (99.999%, Linde) is used as bath gas for water uptake experiments as

109

well as for the determination of the specific surface area (SSA) of the ATDs. Millipore-deionized

110

water is used as water vapor source to perform water uptake measurements.

111

II.2. Physicochemical characterization of the dust samples

112

i.

Specific surface area

113

Nitrogen adsorption measurements are performed with a laboratory gas sorption analysis

114

system,27, 34 and the Autosorb-1MP Quantachrome sorption analyzer. The (SSA) of the collected

115

dust samples is determined employing the BET method within 0.05 to 0.3 relative pressure range

116

(P/P0). To determine the range of uncertainty, four adsorption measurements are conducted for

117

each sample. Details regarding the procedure followed to determine the SSA are given in

118

supporting information.

3 ACS Paragon Plus Environment


119

ii.

Chemical composition

120

The elemental composition of the samples has been determined employing a PE NeXion 300x ICP-

121

MS. Few mg of the dust are acid digested (HF/ HNO3/ HCl) in a microwave oven at 220 oC before

122

analysis.35 Three sets of measurements are performed with each sample to evaluate the ATD

123

chemical heterogeneity. It has been observed that the variation coefficients for the major elements

124

do not exceed 10 %.

125

II.3. Experimental setup

126

The in-situ monitoring of the dust surface has been performed in a DRIFT cell (Harrick, Praying

127

Mantis) equipped with zinc selenide (ZnSe) windows and coupled with a Nicolet 6700 FTIR

128

spectrometer.27, 36 A scheme of the experimental setup is given in Figure 1. The dust sample is

129

placed in a crucible inside the DRIFT cell. Two ellipsoidal mirrors focus the infrared beam on the

130

sample surface, and the collected diffused radiation is monitored with a high sensitivity Mercury

131

Cadmium Telluride (MCT) detector cooled by liquid nitrogen. The detector of the spectrometer is

132

purged with zero air to reduce the contribution of atmospheric CO2 and H2O. The temperature of

133

the sample is recorded using a K-type thermocouple placed on the top of the sample holder, which

134

is also equipped with a heating resistor and a liquid (water/ethanol) circulation system connected

135

to a thermostat (Huber ministat 230) to limit temperature fluctuations during the experiment.

136

DRIFT spectra are recorded using Omnic software (version 9.2) at 100 scans per spectrum and a

137

spectral resolution of 4 cm−1. Further details regarding the experimental technique used can be

138

found in recent publications from our group.27, 36

139

II.4. Experimental protocol

140

Prior to the adsorption experiments, the sample is heated overnight under dry N2 atmosphere at

141

100 - 110oC to remove any pre-adsorbed surface species. Solely the sample of ATD 0-3 μm is heated

142

up to 140 oC to ensure complete removal of H2O and other pre-adsorbed species. Thereafter, the

143

sample is cooled down to 295 K, and the background DRIFT spectrum is collected under dry N2 flow.


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It should be noted that the stability of the background spectrum has been verified in separate test

145

experiments where the background is collected each 30 minutes within a time range of 14 hours

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and it is found to be characterized by fluctuations lower than 4% compared with the initial

147

spectrum. Besides, the background spectrum has been also daily verified at the beginning and at

148

the end of the adsorption/desorption kinetics. The total flow rate inside the DRIFT cell is set to 120

149

standard cubic centimeters per minute (sccm) using calibrated mass flow controllers (MKS

150

instruments). Subsequently, the humid flow of N2 with the desired level of RH is driven through the

151

reactor, and sequential DRIFT spectra are recorded to monitor H2O adsorption as a function of

152

time. The N2 flow is humidified by passing through a H2O bubbler and is further diluted with dry N2

153

to obtain the targeted RH level. The exact relative humidity in the gas flow is determined and

154

monitored using a temperature and relative humidity probe (KIMO HQ 210) with an accuracy ± 1%

155

as provided by the manufacturer.

156

Typical DRIFT spectra (100 co-added scans) collected at various RH conditions are shown in Figure

157

2. The water absorption bands are observed at 1500 - 1800 cm-1, 2100 - 2300 cm-1 and 2600 - 3800

158

cm-1 which are respectively assigned as water molecule bending, association, and stretching

159

vibration modes.24, 25, 27 The main broad band of the DRIFT spectra, localized between 2600 and

160

3800 cm-1, is a combination of O-H symmetric stretch around 3420 cm-1 and asymmetric stretch

161

around 3240 cm-1. In the literature, either the H-O-H bending mode24 or the O-H stretching broad

162

band,25, 27, 29 have been used to monitor water adsorption onto particles and to evaluate the

163

amount of water adsorbed on the surface. In the current study both bands are used to determine

164

the adsorption isotherms. However, in the case of ATD 20-40 μm and ATD 40-80 μm, the intensity

165

of the bending mode is significantly low as well as the background gaseous water that contributes

166

to that IR region; as a consequence, only the O-H stretching band is used to construct the

167

adsorption isotherm profiles for these samples. Possible contribution of gas-phase water to the

168

2600 - 3800 cm-1 region is negligible.25, 27



169

Several hours are required before water adsorption on mineral dust reaches equilibrium (see also

170

Figure S5). The adsorption equilibrium is denoted by the stability of the characteristic infrared

171

absorption bands of water. Specifically, it is considered that adsorption equilibrium is reached as

172

the main band of the DRIFT spectra, between 2600 and 3800 cm-1 remains constant within 5 %

173

experimental uncertainty corresponding to the dispersion of the integrated band areas recorded

174

during one hour. Under these conditions, a DRIFT spectrum, corresponding to 100 scans, is

175

collected each 5 minutes. Then the values of the integrated areas of the OH stretching band are

176

averaged and used for further calculations. Thereafter, the RH level in the optical cell is

177

incremented and the protocol is repeated.

178

At this point it should be noted that in principle there is no linear relationship between measured

179

absorbance with DRIFTs and adsorbed phase concentration. The application of Kubelka-Munk

180

function to the recorded DRIFT spectra provide a linear relationship between adsorbate

181

concentration and reflected radiation. 25, 37 This has also been validated in a recent study from our

182

group where the adsorption of limonene and toluene was studied on natural Saharan samples.36

183

II.5. Data fitting methods

184

Several adsorption theories have been developed and used in the literature to simulate H2O

185

adsorption on solid surfaces (Brunauer, Emmet and Teller (BET)38, Langmuir39, Freundlich, Dubinin

186

and Radushkevich, etc.). They deliver information either on the adsorbate monolayer formation or

187

on the SSA.1 Among adsorption theories, the BET isotherm is widely used to describe multilayer

188

sorption phenomena. The classical BET equation linearizes the curved part of the isotherm that

189

occurs near the monolayer completion:

190

1 c −1  P  1   + = Vads [(P0 / P) − 1] Vmonoc  P0  Vmonoc

191

where Vads (cm3) is the volume of gas adsorbed at equilibrium partial pressure P (Pascal), Vmono (cm3)

192

is the volume of gas necessary to cover the surface of the adsorbent with a complete monolayer, P0

(1)


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is the saturation vapor pressure of the adsorbate gas (Pascal) at the corresponding temperature

194

and c (dimensionless) is a temperature-dependent constant given by equation 2:

195

 ∆H10 − ∆H 20   c = exp RT  

196

where ∆H1 and ∆H 2 are the standard enthalpies of adsorption of the first and subsequent layers

197

(kJ mol-1), respectively. R is the gas constant (8.314 J K-1 mol-1), and T is the temperature (K). The

198

classical BET equation is generally applied in the relative pressure range 0.05-0.3, but it has been

199

evidenced that the isotherm is able to simulate experimental results up to a relative pressure of

200

0.6.23 Nevertheless, above that threshold and due to capillary condensation, the model fails to

201

simulate sorption data with a reliable accuracy.21, 40, 41 Similarly, at lower relative pressures and due

202

to physical phenomena, such as the possible presence of pores of molecular width, crevices

203

between particles, lateral interactions or defects, BET assumptions are inadequate and may not

204

satisfyingly fit the experimental data.23, 41

205

To simulate water adsorption on individual mineral oxides, Goodman et al.,24 proposed a modified

206

3-parameter BET equation that limits the number of layers of the adsorbed gas at high RH values

207

and thus is able to fit the experimental results over the entire RH range:

0

(2)

0

n +1

  P   P P  Vmonoc   1 − (n + 1)  + n   P0     P0   P0  = n +1   P  P P    1 −   P    1 + (c − 1)  − c    0     P0   P0  n

    (3)  

208

Vads

209

where Vads, Vmono and c are defined in Equations 1 and 2, and n is an adjustable parameter

210

corresponding to the maximum number of adsorbed gas layers also related to the morphological

211

properties of the sample. Alternatively, the results can be processed in terms of integrated

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absorbance of the corresponding water vibration mode.24, 25, 27 Therefore, Vads is substituted by Iads



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(integrated area of the adsorbed H2O stretching/bending bands in Kubelka-Munk units at a given

214

RH), and Vmono is replaced by Imono (the integrated area for one monolayer formation). Based on this

215

modification and the study of Joyner et al.,42 who proposed a linearization of the 3-parameter BET

216

equation, is obtained:

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Φ (n, x ) θ(n, x ) 1 = + Iads Imono c Imono

218

where:

219

Φ(n, x ) =

220

θ(n , x ) =

[(

(4)

]

)

x 1 − x n − nx n (1 − x )

(

x 1− xn 1− x

(1 − x )

(5)

2

)

(6)

221

and x = P / P0 = RH

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Plotting the first term of equation 4, Φ(n,x)/Iads versus θ(n,x), and adjusting parameter n to obtain

223

the optimized determination coefficient (r2) of the linear least-square fit of the experimental data

224

points, provides the parameters Imono and c from respectively the slope and the intercept (see also

225

Figure S2).24, 42 Consequently, the number of water layers at a given RH is derived from the ratio

226

between the integrated areas of adsorbed H2O stretching/bending bands at that given RH (Iads), and

227

the one corresponding to the monolayer formation: Iads/Imono.24, 25, 42

228

It has to be noted that the experimental method and protocol applied as well as the theoretical

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approach used to analyze the experimental measurements (3-parameter BET equation) have been

230

validated in our previous study,27 where the robustness and the reproducibility of this technique is

231

evidenced.

(7)


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II.6. Error analysis

233

In this section, we consider possible systematic contributions to the uncertainty of the

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isotherm determinations and the desorption rate kinetics. The dispersion of background

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spectrum is determined to be always below 4 % within the time range experiments are performed.

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Furthermore, the precision of the integrated band intensity of the water stretching mode under

237

equilibrium conditions is estimated to be ca. 5 %. Other systematic uncertainties in our

238

measurements are attributed to (i) reactor temperature (< 1 %), (ii) gas flow (4 %) that

239

impacts the values of RH (iii), accuracy of the RH probe (1 %). The systematic uncertainty

240

can results from the quadrature sum of the individual errors and is estimated to be ca. 8 %.

241

The overall uncertainty of water monolayer determinations is calculated considering the

242

quadrature sum of the systematic uncertainties and the 2σ precision of the slope of the

243

lineal fit of equation 4 (Figure S2) to the experimental data points (Table 1). Similarly errors

244

associated to the values of the BET constant c include the quadrature sum of the

245

systematic errors and that of the intercept of the linear fit. The error propagation method

246

is applied for the values of constant c to determine the error on water ΔΗads.

247

Concerning desorption rate kinetics, beside the systematic errors mentioned above, the

248

errors to the ATD mass weighing (ca. 3 %) and that of the BET surface area (from 8 to 22 %,

249

Table S1) have been taken into account. Therefore the overall systematic errors for kdes are

250

estimated to be in the range of 11 to 22 % depending on the ATD sample. Then considering

251

the 2σ precision of the fit of desorption profiles with equation 11 (always better than 5%)

252

the overall uncertainty range between 12 and 23 % (Table 1).



253 254 255

III.

Results and discussion

III.1. Physicochemical properties of the dust samples i.

Specific surface area analyses of the dust samples

256

Four measurements with different initial conditions of mass and thermal pretreatment

257

temperature are conducted to determine the specific surface area of each ATD sample as well as

258

the corresponding standard deviation (Table S1). Results evidence that the SSA increases as the size

259

of the mineral particles decrease. For ATD 40-80 μm, the average SSA (2.8 ± 0.4 m2 g-1) is lower by a

260

factor of 12 than that of ATD 0-3 μm ( 38.9 +−24..85 m2 g-1). It is important to note that the two different

261

gas sorption analyzers give similar values (Table S1).

262

ii.

Chemical composition of the dust samples

263

The elemental composition of the ATD samples, determined by ICP-MS, is reported in Table S2. The

264

principal elements identified are silicon (Si), aluminum (Al), iron (Fe), calcium (Ca), potassium (K),

265

magnesium (Mg) and sodium (Na) corresponding to more than 99 % of the elements analyzed for

266

every selected ATD grades. The dominant element in all samples is Si with a relative abundance

267

exceeding 58 %. ICP-MS analyses revealed that as size of the ATD particles increases, the relative

268

abundance of Si slightly increases, while the relative abundance of other detected elements (i.e. Al,

269

Fe, Ca, K, Mg) tend to decrease. These trends are in accordance with the recent study of Journet et

270

al.,43 who report similar behaviors using a global database of natural mineral samples. However,

271

according to the specification given by the supplier, all natural ATD grades should be characterized

272

by identical compositions. Our observations question the chemical characterization provided by the

273

ATD supplier. Therefore, samples originating from the same source but characterized by different

274

grades are necessarily slightly contrasted in terms of chemical composition.

275

In addition, for comparison purposes the chemical composition of ATD 0-3 μm determined in the

276

study of Joshi et al.,27 is included in Table S2. Interestingly, 16 % - 24 % differences are observed


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277

regarding the relative abundance of Si and Al respectively between both ATD 0-3 µm samples.

278

Given that the measurement reproducibility for these two elements is lower than 6 % in our

279

experiments, the observed differences could be attributed to (i) contrasted weathering conditions

280

of the samples in Arizona desert before or close to collection dates, or to (ii) the sieving method

281

applied by the ATD supplier.

282

III.2. Adsorption isotherms

283

Typical DRIFT spectra of adsorbed water on 0-3, 5-10, 10-20, 20-40 and 40-80 μm ATDs as a

284

function of increasing RH are presented in Figure 2. The experiments are conducted at 295 K in the

285

range of 2 - 90% of RH. An enhancement of the area of the DRIFT bands is observed with the

286

relative humidity pointing to an increase of water surface coverage increases with RH. In addition

287

as depicted in Figure 2 the vibrational O-H stretch region shows a shoulder at ca. 3200 cm-1

288

characteristic of ice-like structures. The latter is attributed to the coordination of water molecules

289

to the cations of the mineral dust that results to an ice-like structure.44 The absolute values of the

290

integrated band areas (Iads) of the 2600 -3800 cm-1 and 1500-1800 region, determined as a function

291

of RH, are introduced in the linear form of the 3-parameter BET equation (equation 4). Then the

292

results are plotted and linearly fitted by adjusting the value of parameter n to optimize the

293

correlation coefficient of the least-square fit to obtain the values of Imono and the BET constant c

294

from the slope and the intercept respectively (Figure S2).24, 25, 27 The model simulates excellent our

295

results (r2 > 0.97) and both H2O absorption bands provide similar results (Table 1). However, it

296

should be noted that the water bending band is characterized by a significantly lower intensity and

297

area than the corresponding water stretching band in DRIFTs, resulting to higher uncertainties to

298

the intercept of the linear fitting of experimental data with equation 4 that is used for

299

determination of c (see also Table 1). Therefore, although both results are discussed in the

300

manuscript, only those determined using the water stretching mode are used for further

301

comparison and correlation trends (see also Figures S2 and S3).



302

The number of adsorbed water layers is derived from the ratio of Iads to Imono, and the water

303

adsorption isotherms for each ATD dust grade can be constructed (Figure 3). Table 1, summarizes

304

the results obtained upon simulation of water adsorption measurements with the 3-parameter BET

305

equation.

306

i.

Adsorption isotherms on ATD 0-3 μm samples.

307

Regarding ATD 0-3 μm, the water adsorption isotherms determined in the current study and those

308

reported by Gustafsson et al.,28 using thermogravimetric analysis (TGA), and Joshi et al.,27

309

employing DRIFT spectroscopy, are displayed in Figure 3. Our study indicates that water monolayer

310

is formed at 13 ± 1 % of RH using the water stretching mode and 14 ± 1 % of RH using the water

311

bending mode, which is in excellent agreement with the values formerly reported by Gustafsson et

312

al.28 (12% RH) and Joshi et al.,27 (15%). Remarkably, the adsorption isotherm constructed with the

313

O-H stretching mode is identical to the one reported by Gustafsson et al. on the whole explored RH

314

range.28 However, although under lowest RH conditions an excellent agreement is observed with

315

the results of Joshi et al., above 30 % a significant deviation is noticed.27 The maximum deviation is

316

observed at 80% of RH where Joshi et al., underestimated the formation of water layers by a factor

317

of two.27 This discrepancy could be attributed to possible heterogeneities in the physicochemical

318

properties between the 0-3 μm ATD samples used (i.e. differences in chemical composition and

319

SSA, (see Tables S1 and S2), or to the incomplete degassing of pre-adsorbed species in the study of

320

Joshi et al., where the thermal pretreatment was settled at only 1000C.

321

The values of the BET constant (c) are determined to be 50 ± 33 and 20 ± 18 considering the water

322

stretching and bending bands respectively, and thus, the corresponding standard enthalpy of

323

adsorptions of water (ΔHo1) for ATD 0-3 μm, are -53.6 ± 1.6 kJ mol-1 and -51.3 ± 2.2 kJ mol-1 (Table

324

1). These values are comparable with those reported by Joshi et al.27 (c = 55.5 and ΔHo1 = -53.8

325

kJ.mol-1). However, the fitting parameter n, which is found to be 10 in our study, is twice the one

326

determined previously by Joshi et al.27 (n = 5.8). Since the parameter n describes the maximum


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327

number of water layers that can be formed over the considered surface and is related to the

328

morphology (e.g. porosity, surface irregularities, etc.) of the sample,24 our results point out

329

significant variations of the physical properties between the two samples.

330

Unlike the results reported in the present study as well as Gustafson et al.,28 and Joshi et al.,27

331

significantly higher number of water layers were reported by Navea et al.45 and Yeşilbaş and Boily,30

332

who report hundreds of water layers formed at ambient RH conditions. These authors deposited a

333

water slurry of ATD particles to coat the surface of the quartz crystal surface of the microbalance

334

used to quantify water adsorption. The slurry is then dried under a stream of dry N2 without

335

preheating the ATD samples. However, as shown in our recent study, preheating is necessary to

336

remove water already adsorbed on the surface of mineral dusts.27 Although no experimental

337

indications exist, Navea et al.,45 attributed the unusual high water coverage either to swelling of

338

clay minerals contained in ATD when being mixed with water or possible chemical reactions of ATD

339

particles in the aqueous mixture leading to different chemical compositions.

340

ii.

Adsorption isotherms on different ATD dust grades.

341

Besides ATD 0-3 µm, Figure 3 also presents the adsorption isotherms of the other ATD grades and

342

the obtained results are displayed in Table 1 as well. It is observed that the RH level required for

343

water monolayer formation increases as the size of the particles increases. More precisely, the

344

water monolayer is formed at 13 ± 1 % (14 ± 1 considering the bending mode), 17 ± 1 % (18 ± 2

345

considering the bending mode), 22 ± 2% (20 ± 2 considering the bending mode), 25 ± 2% and 28 ±

346

2% of RH for ATD 0-3, 5-10, 10-20, 20-40, and 40-80 µm respectively. Given the experimental

347

uncertainties these results highlight the fact that water-dust interaction is affected by the size of

348

the particles. This is in accordance with a former study on pure metal oxide nanoparticles (20-80

349

nm) that revealed an increase in water uptake as a function of diameter decrease.29 Figure S3a

350

shows the dependence of water monolayer formation threshold (considering solely the data

351

derived from the integration of O-H stretching mode) as a function of the specific surface area of



352

the ATD grades. There is a linear correlation (solid line fitting experimental data) between the SSA

353

and the monolayer threshold that is given by the following empirical expression:

354

%RH monolayer threshold = 25.9 – 0.35×SSA

355

where the SSA is given in m2 g-1. In addition, considering that the experimental determined water

356

monolayer surface density in the monolayer is equal to 1.3 × 1015 molecule cm-2,30 and knowing the

357

SSA of the ATD dust grades (Table S1) and the mass of each ATD sample used in the measurements,

358

it is possible to determine the number of water molecules adsorbed in the monolayer (Table 1).

359

Hence, it is evidenced that lower size particles (i.e. 0-3 and 5-10 µm) adsorb five times more water

360

than coarser dust fractions. Regarding higher RH conditions, the number of water layers formed on

361

the finest dust grades is larger. For instance, at 80 % of RH, the ATD 0-3 µm particles are covered

362

with around 4 water layers while for the coarser dust grades (i.e. 10-20, 20-40, and 40-80 µm), less

363

than 3 water layers are estimated to be formed (Figure 3).

364

Furthermore, comparing the values of parameter n obtained for each dust grades (ranging from 6

365

to 10) interesting conclusions can be drawn. The lowest value is observed for the ATD 40-80 µm,

366

and the highest one corresponds to ATD 0-3 µm sample. The variation of parameter n implies that

367

(i) the morphology differs between the dust grades and (ii) a higher number of water layers is

368

expected to be formed (in accordance to our measurements). Furthermore, as shown in Figure S3b,

369

a linear correlation is observed between the RH for monolayer formation and the parameter n. The

370

higher is the monolayer threshold, the lower is the n values. At this point, it should be noted that

371

observed trends regarding parameter n are unlikely attributed to porosity, since the measurements

372

performed with the Autosorb-1MP Quantachrome sorption analyzer revealed a wide inter-

373

particular porosity distribution for all ATD samples, but no intra-particular porosity. Thus,

374

complementary approaches would be required to correlate n parameter with the relevant

375

morphological determinant.

(8)


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376

Regarding the BET constant c and considering solely the data derived from the integration of O-H

377

stretching mode that encompass the lower uncertainty, one can note an increasing trend of the

378

constant c as the particle size of the mineral samples decreases (Table 1). Considering that the BET

379

constant c reflects the interaction strength between the water molecule and the dust substrate,

380

our measurements indicate that water interacts more strongly at the surface of the smallest dust

381

fractions. The corresponding enthalpies of adsorption are also determined and are displayed in

382

Table 1. Moreover, as shown in Figure S3-c, there is a linear correlation of water adsorption

383

enthalpies with the SSA of ATD samples, evidencing that water adsorption is a more exothermic

384

process on the finest particles.

385

In addition, water monolayer formation threshold is not expected to be significantly influenced by

386

small differences on the chemical composition between the studied samples that were by a factor

387

three or less. In particular, in Figure S4 are plotted the water monolayer threshold as a function of

388

ratio of the most abundant elements, Al/Si, Ca/Si and Fe/Si, for the ATDs studied along with other

389

natural dust samples previously reported in the literature.27, 46 In case of ATDs studies, it appears

390

that as the Al/Si, Ca/Si and Fe/Si increase, the water monolayer threshold decrease, contrariwise to

391

the trend observed and reported for other mineral surfaces and are also displayed in Figure S4. If

392

the chemical composition was a determining factor for the ATD monolayer thresholds, then one

393

would expect close correlation between the studies and not contrasted results. Considering all data

394

points, no particular conclusions can be drawn. Since the chemical composition of ATD varies with

395

size (as it has also been observed in literature), and considering the complete opposite trends with

396

the other natural dusts, it appears that water monolayer threshold of the samples studied is rather

397

influenced by morphological parameters (e.g particle size and SSA that change by a factor of 45 and

398

13 respectively) than variations of the chemical composition.

399 400

iii. Role of OH surface density Recent literature studies proposed that OH surface density plays a key role in the adsorption of

401

water on mineral particles influencing the water monolayer threshold and the enthalpy of 15 ACS Paragon Plus Environment


402

adsorption.47, 48 In particular, Puibasset and Pellenq,47 suggested that low OH surface density results

403

in relatively higher RH thresholds for monolayer formation and enthalpies of adsorption close to -

404

44 kJ mol-1. Navea et al.,48 reported that as the fly ash particle diameter increases, the OH surface

405

density decreases. These observations are in excellent agreement with those of the current study

406

and can be used to further interpret our results. In particular, it seems that OH terminals drive the

407

uptake of water on ATD particles and thus the inverse trend between OH surface density and

408

mineral particles diameter reported previously is also confirmed in our study.

409

However, it is important to note that water uptake on minerals is not only dependent on the OH

410

surface density.47 Grand Canonical Monte Carlo simulations (GCMC) carried out on silica substrates

411

evidenced that water molecules preferentially adsorb on sites located on high local curvature, or

412

defects like steps or holes (i.e. morphological parameters) regarding the surface of silica substrates.

413

Considering such adsorption sites, water molecules may establish more than two close interactions

414

with the substrate like hydrogen bonds. Therefore, the hydrophilic character of the surface is due

415

to a locally favorable arrangement of hydroxyl groups which maximizes the number of hydrogen

416

interactions, rather than simply the average surface hydroxyl density.47 Consequently, the results

417

from the simulations are in excellent agreement with those of the current study and Yeşilbaş et

418

al.,30 where it is evidenced that morphological parameters have a significant impact on the

419

adsorption of water on mineral particles.

420 421

iv.

Consistence with thermodynamic models

422

The size-dependence of adsorption process onto particles is addressed from a theoretical point of

423

view in the model proposed by Gommes et al.49 In order to describe the impact of particle size on

424

adsorption, these authors developed corresponding thermodynamic equations to characterize

425

adsorption on isolated and contacted particles as a function of adsorbate layer thickness t

426

(equation 9).


Page 18 of 31

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427

P 2γ Vm = × π(t) + ln  r + t RT  P0 

428

The left-hand side of equation 9 is related to (i) the curvature of the particle, a decreasing function

429

of r, radius of the particle and to (ii) the surface-adsorbate interaction through the parameter γ

430

corresponding to the surface tension of the adsorbate. On the right-hand side, P and P0 are the

431

partial and saturation partial pressures of the adsorbate that depicts relative humidity. Vm, R and T

432

are respectively the molar volume of the adsorbate, the perfect gas constant and the absolute

433

temperature. Finally, Π(t) is the disjoining pressure function. As a derivative of Gibbs energy of

434

interaction, i.e. thermodynamic potential, Π(t) corresponds to the attractive interaction between

435

the adsorbate and the particle surface. Experimental results reported previously evidence that a

436

decrease in particle size, i.e. an increase in the sample specific surface area and surface curvature,

437

induces (i) a decrease in RH threshold corresponding to water monolayer formation (Table 1), and

438

(ii) an increase in water enthalpy of adsorption (Table 1). These trends are consistent with the

439

thermodynamic model proposed by Gommes et al.49 Indeed, the disjoining pressure is an increasing

440

function of the particle surface curvature; meaning that lower particle radii promote water

441

adsorption from a quantitative as well as an intensity point of view.

442

III.3. Determination of the desorption rates

443

In order to confirm the effect of particle size on water uptake, a series of desorption experiments

444

are performed at room temperature under dry N2 environment. Initially, the dust sample is exposed

445

to RH corresponding to monolayer formation (i.e. 13%, 17%, 22%, 25% and 28% of RH for ATD 0-3,

446

5-10, 10-20, 20-40, and 40-80 µm respectively). After reaching monolayer equilibrium conditions,

447

the humid N2 flow is stopped and replaced by dry N2 of equal flow (120 sccm). The temporal profile

448

of the integrated area of water absorption band (stretching vibration mode between 2600 - 3800

449

cm-1) during a typical adsorption-desorption experiment for ATD 5-10 µm is reported in Figure S5a.

450

The desorption profiles of water from the different dust grades are displayed in Figure S6a. For

451

clarity purpose, the integrated intensities are normalized; Ir is the integrated area recorded at a

(9)



452

given time t, and I0 is the integrated area at monolayer equilibrium (Figure S5b). t = 0, corresponds

453

to the time when the desorption process is started. Results, depicted in Figure S6a, evidence that

454

water desorption is significantly slower as the particle size decreases. For instance, after 30

455

minutes, around 99 % of adsorbed water has been removed from ATD 40-80 µm while for ATD 0-3,

456

5-10, 10-20 and 20-40 µm, the corresponding desorbed fractions are 70%, 84%, 93% and 92%

457

respectively. Moreover, at the end of the desorption process, the quantity of initially adsorbed

458

water is not recovered (except ATD 40-80 µm), pointing that a small but non negligible fraction of

459

water remains irreversibly adsorbed at room temperature (Table 1). Nevertheless, in all cases, the

460

irreversibly adsorbed fraction is recovered after thermal pretreatment at 140oC. Obtained results

461

are in excellent agreement with literature data determined on synthetic porous oxide nanoparticles

462

such as SiO2 or HfO2.29

463

The interpolation of desorption profiles evidenced that water desorption follows a second order

464

kinetics:

465

−

466

where nads (molecule cm-2) corresponds to the concentration of water adsorbed on the surface and

467

kdes (cm2 molecule-1 s-1) is the second order desorption rate coefficient. The integration of Equation

468

10 leads to Equation 11:

469

nads (t) =

470

where n ads (t) corresponds to water concentration on the ATD surface at time t along the desorption

471

process, and n ads (eq) is the water concentration at equilibrium. Considering the experimental

472

determined value of water concentration in the monolayer (1 monolayer = 1.3 × 1015 molecule cm-

473

2

dn ads 2 = k desn ads dt

(10)

nads (eq)

(11)

1 +k des t nads (eq)

), integrated intensities recorded using DRIFT can be transformed into water concentrations.


Page 20 of 31

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474

Thereafter, by plotting 1/n ads (t) versus time (t), it is possible to determine the second order

475

desorption rate coefficient of water. To improve the precision of the fitting and thus the accuracy of

476

desorption rate coefficients we considered solely the data points that corresponds to surface

477

coverage three times higher than the non-covered water surface concentration (plateau achieved

478

at the end of desorption process). In other words, we fitted the data points where the integrated

479

area of water stretching mode band is 3 times higher than the final value obtained at the end of the

480

desorption process (this value was considered as background value of the desorption kinetics). The

481

fitting of the experimental data is displayed in Figure S6b, and the values of the second order

482

desorption rate coefficients of water are provided in Table 1. There is a progressive decrease of kdes

483

with the decrease in the particle size. For instance, kdes for ATD 0-3 µm is by a factor 50 lower than

484

that for ATD 40-80 µm. Figure 4 depicts the dependence of kdes as a function of mean particle

485

diameter, that is found to follow a power dependence according to Equation 12:

486

kdes = 1.1 + 6.7 × 10-3 × (mean particle diameter)2.0

(12)

487 488

III.4. Atmospheric implications

489

According to the results of the current study and those published recently, it appears that particle

490

size is a key parameter influencing water uptake and hygroscopicity of mineral dusts. The latter

491

indicates that the impact of mineral dust to the climate through cloud formation or ice nucleation

492

for instance or its ability to interact or react with gaseous pollutants is size dependent. Under

493

typical dust storm conditions (ca. 20% RH or lower), fine mineral particles (

Water Interaction with Mineral Dust Aerosol ... - ACS Publications

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