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Environmental Modeling

Linked Response of Aerosol Acidity and Ammonia to SO2 and NOx Emissions Reductions in the US Abiola S Lawal, Xinbei Guan, Cong Liu, Lucas R. F. Henneman, Petros Vasilakos, Vasudha Bhogineni, Rodney J. Weber, Athanasios Nenes, and Armistead G. Russell Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.8b00711 • Publication Date (Web): 23 Jul 2018 Downloaded from http://pubs.acs.org on July 23, 2018

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Environmental Science & Technology

Linked Response of Aerosol Acidity and Ammonia to SO2 and NOx Emissions Reductions in the US Abiola S. Lawal1, Xinbei Guan1, Cong Liu1,3, Lucas R.F. Henneman1,5, Petros Vasilakos4, Vasudha Bhogineni1, Rodney J. Weber2, Athanasios Nenes2,4,6,7, and Armistead G. Russell1*. 1 School of Civil & Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, United States. 2 School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, Georgia 30332, United States. 3 School of Energy and Environment, Southeast University, Nanjing 210096, China. 4 School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States. 5 Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA 02115. 6 Institute for Chemical Engineering Sciences, Foundation for Research and Technology – Hellas, Patras, GR-26504, Greece 7 Institute for Environmental Research and Sustainable Development, National Observatory of Athens, P. Penteli, Athens, GR-15236, Greece

*

Corresponding author: Armistead G. Russell.

1

ACS Paragon Plus Environment


1

TOC/ABSTRACT GRAPHIC

2 3

Abstract

4

Large reductions of sulfur and nitrogen oxide emissions in the United States have led to

5

considerable improvements in air quality, though recent analyses in the Southeastern United

6

States have shown little response of aerosol pH to these reductions. This study examines the

7

effects of reduced emissions on the trend of aerosol acidity in fine particulate matter (PM2.5), at a

8

nationwide scale, using ambient concentration data from three monitoring networks – the

9

Ammonia Monitoring Network (AMoN), the Clean Air Status and Trends network (CASTNET)

10

and the Southeastern Aerosol Research and Characterization Network (SEARCH), in

11

conjunction with thermodynamic (ISORROPIA-II) and chemical transport (CMAQ) model

12

results. Sulfate and ammonium experienced similar and significant decreases with little change

13

in pH, neutralization ratio (f=[NH4+]/2[SO42-]+[NO3-]), or nitrate. Oak Grove, MS was the only

14

SEARCH site showing statistically significant pH changes in the Southeast region where small

15

increases in pH (0.003 to 0.09 pH units/year) were observed. Of the five regions characterized

16

using CASTNET/AMoN data, only California exhibited a statistically significant, albeit small

17

pH increase of +0.04 pH units/year. Furthermore, statistically insignificant (α = 0.05) changes in

18

ammonia were observed in response to emission and PM2.5 speciation changes. CMAQ

2


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simulation results had similar responses, showing steady ammonia levels and generally low pH,

20

with little change from 2001 to 2011.

21

22

3



23

1. Introduction

24

Atmospheric aerosols, including fine particulate matter (PM2.5), are associated with

25

adverse effects on human health and the environment1-7. A key property of aerosol particles is its

26

acidity, as it can critically affect heterogeneous chemistry (e.g., secondary aerosol formation,

27

metal dissolution and nitrate/nitric acid partitioning), climate forcing, biogeochemical cycles,

28

ecosystem productivity, ocean oxygen levels, and has been linked to adverse health effects8-17.

29

Aerosol acidity (pH), is a function of its composition, driven largely by humidity,

30

temperature, sulfate (SO42-),

and nitrate (NO3-), both of which are formed through the

31

oxidization of sulfur and nitrogen oxides in the atmosphere18-21. These constituents are

32

neutralized to some degree by reactions with ammonia gas (NH3(g)) and the presence of non-

33

volatile cations (e.g. Mg2+, Ca2+, K+, Na+) from soil dust. Chloride (Cl-) formed from sea spray

34

and biogenic emissions is also known to impact acidity, though these would be considered non-

35

anthropogenic contributions to PM2.5. In light of notable decreases in both sulfur (87% reduction

36

from 1990-2016 of SO2) and nitrogen oxide (56% reduction from 1990-2016 of NOx)

37

emissions22, the question arises as to how aerosol pH has responded to emission changes over

38

time and how it will evolve as emissions further change23.

39

Effects of SO2, NOx, and precursor emissions on aerosol acidity and PM2.5 concentrations

40

have been studied previously 21, 24-32. Saylor et al., (2015)26 reported a decrease in particulate

41

ammonium PM2.5 concentrations (NH4+) and an increase in NH3(g) in response to decreased SO2

42

and NOx emissions. Weber et al., (2016)28 conducted thermodynamic analyses of aerosol pH in

43

the Southeast and concluded that in spite of significant sulfate decreases, particles remain highly

44

acidic and will remain so until sulfate levels decrease to pre-industrial levels. Guo et al., (2017)29

45

analyzed pH sensitivity to NH3(g) levels in a variety of locations worldwide, and noted that 4


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about a 10-fold increase (decrease) in NH3(g) levels is required to force a 1 unit pH increase

47

(decrease).

48

In this study, trends in ammonia, speciated aerosol concentrations in PM2.5, and aerosol

49

acidity in the United States are examined. The presence of organic compounds have been found

50

to have a smaller impact on aerosol pH33-34 and biogenic VOC emissions are not subject to

51

emissions controls, so acidity changes are expected to arise primarily from changes in inorganic

52

aerosol precursor emissions. While aerosol pH is not readily measured, a number of

53

thermodynamic models such as SCAPE35, AIM36, and ISORROPIA-II37 (used in this study) can

54

be employed using concentrations of key constituents within the aerosol-gas system to estimate

55

aerosol pH. Here, data obtained from the Ammonia Monitoring Network (AMoN), the Clean Air

56

Status and Trends network (CASTNET), and the Southeast Aerosol Research and

57

Characterization network (SEARCH) are used as inputs to ISORROPIA-II. The AMoN and

58

CASTNET are nationwide networks that measure NH3(g) and speciated PM2.5 concentrations.

59

SEARCH provides similar data for eight sites in the Southeastern US. In addition, a Chemical

60

Transport Model, the Community Multiscale Air Quality (CMAQ), was used to provide

61

information over a geographically wide domain. Data analysis with thermodynamic modeling,

62

along with air quality modeling are used to 1) investigate spatial and temporal trends of ammonia

63

and PM2.5 in the United States 2) examine how aerosol acidity has responded to reductions of

64

sulfate and nitrate in the past 3) observe how ammonia gas levels responded, given the role

65

ammonia plays in aerosol neutralization and nitrogen deposition and 4) better understand how

66

pH will respond to future emissions changes.

67 68 5



69 70

2. Data and Methods

71

2.1 CASTNET and AMoN

72

Data from CASTNET and AMoN sites were organized into five regions of the US:

73

Southeast (SE), Northeast (NE), Midwest (MW), Rocky Mountains (RK), and California (CA)

74

(Figure S1). The CASTNET database contains long-term records of air pollutant concentrations,

75

deposition and the ecological effects of changing air pollutant emissions. At more than 90 sites

76

across the U.S. and Canada, weekly ambient measurements were taken for gaseous species (e.g.

77

SO2, HNO3(g)) and condensed phase species (e.g. SO42-, NO3-, NH4+, Mg2+, Ca2+, K+, Na+, Cl-).

78

CASTNET also records daily average temperature and relative humidity (RH). Launched in

79

2007 and expanded in 2011, AMoN provides long-term records of ammonia gas concentrations

80

across the U.S. The lack of gas phase ammonia data from AMoN prior to 2011 limits the detailed

81

study period from March 2011 to February 2016. To provide complete ambient measurement

82

input data for ISORROPIA-II which requires “total” concentrations (gas and condensed phase)

83

of ammonium (TNHx=NH3(g) + NH4+) and nitrate (TNO3- = HNO3(g) + NO3-) in the forward

84

mode, only co-located CASTNET and AMoN sites were selected for this study. Additional

85

details about the sites can be found in Table S1 in the Supporting Information (SI) supplement.

86 87

2.2 SEARCH

88

SEARCH was a comprehensive ambient air monitoring network designed to gather long

89

term detailed data to characterize the chemical composition, sources of particulate matter and the

90

spatial and temporal distributions of PM2.5 in the Southeastern United States. SEARCH consisted

91

of eight highly instrumented stations located in four Southeastern states AL, GA, FL and MS, 6


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consisting of three urban/rural and one urban/suburban paired sites in each state as follows: GA

93

(Atlanta-Jefferson Street/JST, Yorkville/YRK), AL (Birmingham/BHM, Centerville/CTR), MS

94

(Gulfport/GFP, Oak Grove/OAK), and FL (Pensacola/PNS, Outlying Landing Field/OLF).

95

Further site location details and descriptions can be found in (Figure S2 and Table S2).

96

Data from SEARCH includes meteorology (temperature and RH), trace gas

97

concentrations and particulate compositional data. SEARCH also measured HCl(g) in addition to

98

particulate Cl-. Here, we used data from 2008-2015, though not all sites were active for the

99

entirety of the period Details of the data availability, along with the sampling frequency and site

100

abbreviations can be found in Edgerton et al., (2012)38 and in the SI (Tables S2 and Table S3).

101 102

2.3 Thermodynamic Modeling

103

2.3.1 ISORROPIA-II

104

ISORROPIA-II is a thermodynamic model that calculates the physical state, composition,

105

phase partitioning and pH of inorganic atmospheric aerosol and is generally found to be in good

106

agreement with other models and observations39-41. ISORROPIA-II has two run modes, forward

107

and reverse. Inputs for the forward mode, which was used in this study, include known quantities

108

such as temperature (T), relative humidity (RH), and total (gas + aerosol) concentrations. In this

109

case, constituents that can exist either as gases or particles—namely ammonia, hydrochloric acid,

110

and nitric acid—are given as total ammonia (TNHx = NH3(g) + NH4+), total nitrate (TNO3- =

111

HNO3(g) + NO3-) and total chloride (TCl = HCl(g) + Cl-), although HCl(g) was not available

112

from CASTNET. The remaining constituents—sulfate, and base cations of magnesium,

113

potassium, sodium, calcium — are also entered as inputs, although a fraction of some species

114

may not be water soluble (e.g. CaSO4). The reverse mode requires similar inputs, except the gas 7



115

phase concentrations are determined by aerosol phase concentrations only. Measurement errors

116

inherent in the latter mode (especially for mildly acidic aerosols) may give unrealistically large

117

gas-phase concentrations than the forward mode which ensures more thermodynamic constraints

118

to generate a more robust solution41-42. In line with previous studies, the aerosol is assumed to be

119

internally mixed so bulk properties are used43-44. This assumption, coupled with the fact that

120

ISORROPIA-II uses species concentrations as an input, eliminated the need to consider

121

volumetric effects, although this study specifically explores one aerosol size: PM2.5.

122

Although aerosols consist of organic and inorganic components, ISORROPIA-II only

123

models the aerosol’s inorganic constituents effect on pH. Organic acids and organic matter do

124

have some effect on pH, due to their contribution to water soluble ionic constituents (albeit

125

mostly at higher pHs44), and associated liquid water content (LWC). Organics are also purported

126

to affect pH by inhibiting NH3(g) uptake34. However, a fair amount of studies have found their

127

contributions to LWC and pH to be ineffectual, when compared to contributions from inorganic

128

constituents and were therefore, not considered in this study33, 44-50. We expand upon impacts of

129

organic constituents, including organic acids, organonitrates and organosulfates on aerosol pH in

130

greater detail within the SI.

131

In ISORROPIA-II, the user can specify the aerosol to be either in a thermodynamically

132

stable state, where salts precipitate if saturation is exceeded, or in a metastable state, where salts

133

do not precipitate under supersaturated conditions. ISORROPIA-II results in the metastable

134

mode have been found to agree better with observations over a wide range of RH (20-95%)

135

according to Guo et al., (2016)51. Though Guo et al., (2016) noted relatively large discrepancies

136

at lower RH values (20-40%), Song et al., (2018)42 in comparing ISORROPIA-II to E-AIM

137

found relatively small differences in pH over a wide range of RH. A boxplot of RH for SEARCH 8


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and CASTNET (Figures S3 and S4) shows generally high values that lie within the acceptable

139

range found in Guo et al., (2016), and above the listed mutual deliquescence relative humidity

140

values (MDRH) in Table 6 of Nenes et al., (1998)39 and Table 5 in Fountoukis and Nenes

141

(2007)37, although summer RH values for California in the CASTNET network were in the low

142

30s, around the crystallization RH of pure ammonium sulfate52. In addition to better model

143

agreement with observations, past studies, such as those by Rood et al., (1989)53 show that

144

metastable aerosols, in the range of 2 µm are fairly ubiquitous at RH’s between 45 and 75%.

145

Further, recent experiments by Liu et al., (2017)54 found that the sub micrometer aerosols were

146

liquid down to relatively low RH, so the aerosol particles are likely to be liquid at the RH range

147

used in this study. Thus, in this work, the metastable mode was used with the seasonal averages

148

of total species concentrations along with temperature and RH from SEARCH and

149

CASTNET/AMoN databases to model the seasonal average aerosol pH at each site location for

150

each region.

151

2.3.2 ISORROPIA-II Model Evaluation

152

As pH is difficult to measure, model evaluation of predicted pH is assessed by comparing

153

predicted LWC and partitioning ratios among semi-volatile constituents (i.e. NH4+, NH3(g))

154

between the gas and particle phase against observations. In comparison with other models,

155

ISORROPIA-II performs well, and its performance has been well documented and evaluated in

156

several studies37, 44. Here, we use ISORROPIA II 2.3, which addresses the issue identified Song

157

et al. (2018), and includes other algorithmic improvements. The differences between the updated

158

version and version 2.1 are small: the average pH for the SEARCH sites changed less than 0.01

159

units, and about 0.1 for the CASTNET sites (Table S4 and S5). Additional discussion on model

160

evaluation can be found in the SI as well. 9



161 162 163

2.4 Neutralization ratio f

164

While thermodynamic models can estimate pH, other parameters have been employed to

165

serve as proxies for in-situ pH to indicate the degree of acid neutralization with ammonia in lieu

166

of pH, though the utility of such measures is in question41. One commonly used proxy is an ion

167

ratio, otherwise referred to as the “neutralization ratio” of the condensed species of particulate

168

ammonium (NH4+) to sulfate (SO42-) and particulate nitrate (NO3-), although in many cases, the

169

latter is omitted44, 55-56.

170

Such proxies are not necessarily a good indicator of pH, as discussed by Hennigan et al.,

171

(2015)41 and Guo et al., (2016)51. One weakness of this measure is that it does not include the

172

presence or role of non-volatile cations, (which are not always available), nor the effects of

173

aerosol water variations (from RH changes) on pH. However, despite these aforementioned

174

short-comings, these proxies are still used in studies43, 57 to understand aerosol dynamics and

175

acidity changes in response to emissions precursors, so we include it here for completion and

176

discuss it further in the SI. Of note, the neutralization ratio, f in this study is calculated using

177

observed seasonal molar averages of NO3-, SO42-, and NH4+ as follows:

178

=

(1)

179 180

2.5 Chemical Transport Modeling

181

The Community Multiscale Air Quality (CMAQ) Model simulates the formation and fate

182

of air pollutants by solving the general atmospheric dynamic equations which takes into account

183

atmospheric reactive chemistry in addition to other physical processes (i.e. coagulation, 10


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deposition)58. ISORROPIA-II was used to calculate pH and inorganic species partitioning in

185

CMAQ. Simulations were conducted using CMAQ version 5.0.258 for the Eastern continental US

186

for the years 2001 and 2011, with a 12km horizontal grid resolution (Figure S5). This region

187

experienced large reductions in SO2 emissions over this time, which is why the domain was

188

chosen for more in depth study32. Emissions were developed using SMOKE, version 6, along

189

with the National Emissions Inventory (NEI)59-60. The Weather Research Forecast (WRF)

190

version 3.6.161 was employed to generate meteorological fields. Using CMAQ results, seasonal

191

maps in 2001 and 2011 of pH and gas-phase ammonia were created for the Eastern US.

192

A detailed evaluation of the model and how well it captured trends in PM and gaseous

193

species is found elsewhere, along with further discussion in the SI62-63. In general, the model

194

achieved the performance goals set by Emery et al., (2017)64 and captured observed sulfate and

195

ammonium trends .

196 197

2.6 Ambient Data analysis

198

Species concentrations (TNHx, TNO3-, TCl, SO42-, Mg2+, Ca2+, K+, Na+), average

199

temperatures and relative humidity from all three networks were averaged by season to

200

compensate for limited years of available data and seasonal effects for the trend analyses

201

conducted here19. These seasonal averages for winter (December to February), spring (March to

202

May), summer (June-August), and fall (September to November) were used as inputs to

203

ISORROPIA-II to model seasonal average aerosol pH at each site and region. The modeled pHs

204

from ISORROPIA-II, along with the observation data were compared as seasonal time series

205

trends, (Figures 1-3, Tables 1,2), reflecting spatial and temporal effects. Linear regressions for

206

selected speciated PM2.5 components, pH, ammonia-gas partitioning ratio RN (RN = [NH3(g)]/ 11



207

[TNHX]) and f as functions of time were performed and the slopes were evaluated for statistical

208

significance. Yearly percent changes were estimated from the slopes and intercepts. Throughout

209

this paper, statistical significance for these trends is assessed at α = 0.05 (Tables S6 and S7). To

210

assess the impact of finer temporal scales, monthly averaged species concentrations of the

211

SEARCH sites were calculated and used to generate modeled pH with ISORROPIA-II. The

212

results were evaluated similarly as the seasonal averages above with trends assessed for

213

statistical significance (Table S8).

214

For sake of brevity, only a few data tables and plots are shown here while additional

215

figures and data tables can be found in the SI. The choice of variables to include in the main text

216

are based on the sulfate/nitrate/ammonium aerosol model as these components largely influence

217

PM2.5 pH and constitute the bulk of its inorganic mass44, 52, 65.

218 219

3. RESULTS AND DISCUSSION

220

3.1 CMAQ and ISORROPIA Modeling Results pH

221

ISORROPIA-II calculated aerosol pH was low at the beginning of the observational

222

periods (SEARCH: 0.8-2.0. CASTNET/AMoN: 2.3-2.7), with small increases in pH (i.e. < 1 pH

223

unit) over time (Table 1, Table 2, Figures 2a and 3a). While almost all SEARCH sites (except

224

CTR) and CASTNET/AMoN regions (except RK, which has only one collocated network site,

225

Figure S1) exhibited positive trends for pH, only CA and OAK saw statistically significant

226

changes and those increases were less than one pH unit over the period of study.

227

Similar pH values were found using CMAQ (Figure 1) in comparable regions. CMAQ-

228

derived pHs in the upper Midwest region were typically between 3.5 and 4 in most seasons

229

except spring for both years, which matched the MW pH of 3.7 from CASTNET/AMoN. pH for 12


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the Southeast region from CMAQ were about 1.5-2.0, which agreed well with the overall

231

SEARCH site average of 1.8 and is also consistent with observations from Guo et al., (2015)’s

232

study within the same region44. The CMAQ simulated pH over the years 2001 and 2011 with

233

CMAQ also showed a small, typically positive trend. We discuss reasons for these differences in

234

regional pH values in subsequent sections as we look at the impact of different species

235

concentrations on pH.

236 237 Parameter

Metric

Units

NE

SE

MW

RK

CA

pH

Slope

pH/year

2.2E-2

1.9E-2

2.5E-2

-2.3E-4

3.8E-2

Intercept

pH

2.3

2.5

3.6

2.7

2.9

% Change

%/year

3.9%

3.0%

2.8%

-0.03%

5.2%

Slope

-3

-5.3E-2

-6.0E-2

-4.2E-2

-1.2E-2

-1.7E-2

SO4

2-

NO3

+ NH4

NH3(g)

TNHX

RN

ug m /Year -3

Intercept

ug m

2.4

2.6

2.2

0.58

1.1

% Change

%/year

-8.7%

-9.1%

-7.5%

-8.3%

-6.3%

Slope

-3

ug m /Year

1.1E-2

-2.7E-3

5.5E-3

-2.0E-3

-4.7E-3

Intercept

-3

ug m

0.76

0.71

1.5

0.2

0.87

% Change

%/year

5.6%

-1.5%

1.5%

-4.0%

-2.2%

-3

Slope

ug m /Year

-1.7E-2

-1.7E-2

-1.1E-2

-4.2E-3

-7.6E-3

Intercept

ug m

0.95

0.81

1.0

0.23

0.49

% Change

%/year

-7.3%

-8.4%

-4.4%

-7.2%

-6.2%

Slope

-3

-2.1E-3

2.5E-2

-1.5E-2

-3.6E-3

2.6E-2

-3

ug m /Year -3

Intercept

ug m

0.79

0.94

2.1

0.51

2.0

% Change

%/year

-1.1%

11%

-2.9%

-2.8%

5.4%

Slope

-3

-1.9E-2

7.9E-3

-2.6E-2

-7.8E-3

1.9E-2

ug m /Year -3

Intercept

ug m

1.7

1.8

3.1

0.74

2.4

% Change

%/year

-4.5%

1.8%

-3.4%

-4.2%

3.1%

Slope

1/Year

3.8E-3

9.8E-3

6.9E-4

3.8E-3

4.0E-3

Intercept

NA

0.47

0.54

0.68

0.66

0.79

% Change

%/year

3.3%

7.2%

0.4%

2.3%

2.0%

13



238

Table 1: Results from the linear regression analysis for: pH, sulfate (SO42-), particulate nitrate

239

(NO3-), particulate ammonium (NH4+), gaseous ammonia (NH3(g)), total ammonia (TNHx), and

240

ammonia gas molar partitioning ratio, (RN=[NH3(g)]/[TNHx]) in all five regions in the

241

CASTNET/AMoN network. Bolded results were found to be statistically significant at α=0.05.

242

(Note: Yearly percent changes are estimated from the slope and intercept and tabulated)

243 244

3.2 Sulfate (SO42-)

245

Analysis of the sulfate concentration data showed statistically significant yearly

246

reductions in sulfate (SO42-) across most CASTNET regions (except CA, Figure 2b, Table 1 and

247

Table S7), highlighting the effects of reduced SO2 emissions32. SO42- across the CASTNET

248

network varied regionally with the lowest concentrations (based on trend intercept) seen in RK

249

(0.6 ug/m3) and the highest observed in the SE (2.6 ug/m3).

250

Comparable SO42- results (Figure 3b) were observed at all SEARCH sites (except PNS)

251

which all saw major reductions. PNS data did not extend past 2009 (Table S2) and limited data at

252

this site did not allow for capture of sulfate reductions that were observed elsewhere. Significant

253

downward trends were noted at CTR, JST, OLF, YRK and BHM with yearly reductions of -7%

254

to -12% (Table 2). SO42- concentrations (from trend intercepts) at SEARCH sites ranged from

255

1.6 ug/m3 at PNS to 4.5 ug/m3 at YRK, with an overall average of 3.2 ug/m3, much higher than

256

the SE region concentration from CASTNET trend of 2.6 ug/m3. While these differences may be

257

attributed to spatial variation and characteristics of the sites in both networks (i.e. climate, source

258

apportionment), the median SO42- values in both cases had fewer discrepancies (Figure S6).

259

Organosulfates may be present, and there is a possibility that they could lead to artifact

260

sulfate in the measurement process, though this is expected to be minimum, particularly in areas 14


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261

like CA, as the presence of these compounds are likely to be associated with isoprene

262

oxidation66. Further, OS reactions within the aerosol tend to yield other OS compounds which do

263

not contribute to inorganic SO42,67.

264 265 266 267

pH

SO42-

NO3-

NH4+

NH3(g)

TNHX

RN

Metric

Units

CTR

GFP

JST

OAK

OLF

YRK

BHM

PNS

Slope

pH/year

-2.6E-3

1.7E-2

9.9E-3

9.1E-2

2.7E-3

4.2E-3

2.2E-3

9.1E-3

Intercept

pH

1.5

1.7

1.8

0.76

1.6

2.0

1.9

1.8

% Change

%/year

-0.70%

3.9%

2.3%

48%

0.69%

0.86%

0.44%

2.0%

Slope

-3

-6.2E-2

-9.0E-2

-8.7E-2

-7.7E-2

-5.5E-2

-1.3E-1

-7.3E-2

8.9E-2

3.0

3.1

3.7

2.9

3.0

4.5

3.6

1.6

ug m /Year -3

Intercept

ug m

% Change

%/year

-8.4%

-12%

-9.3%

-11%

-7.2%

-11%

-8.1%

22%

Slope

ug m-3/Year

4.9E-4

4.4E-5

2.6E-3

1.1E-2

6.5E-4

1.0E-3

4.8E-3

6.9E-3

Intercept

ug m

-3

0.10

0.14

0.21

0.047

0.11

0.20

0.13

0.15

% Change

%/year

1.9%

0.13%

4.8%

92%

2.4%

2.0%

15%

18%

Slope

-3

-2.0E-2

-1.3E-2

-2.7E-2

-9.7E-3

-1.2E-2

-4.4E-2

-1.9E-2

5.7E-2

0.96

0.85

1.3

0.81

0.89

1.6

1.2

0.40

ug m /Year -3

Intercept

ug m

% Change

%/year

-8.2%

-6.0%

-8.3%

-4.8%

-5.3%

-11%

-6.4%

56%

Slope

ug m-3/Year

1.4E-3

3.1E-3

4.5E-3

1.5E-2

2.1E-3

-1.2E-2

-3.3E-2

-2.5E-2

Intercept

ug m

-3

0.19

0.55

1.1

0.12

0.28

1.5

1.9

0.65

% Change

%/year

2.9%

2.3%

1.7%

49%

3.0%

-3.1%

-7.0%

-15%

Slope

-3

-1.8E-2

-9.5E-3

-2.3E-2

5.0E-3

-9.7E-3

-5.6E-2

-5.2E-2

3.4E-2

1.1

1.4

2.4

0.93

1.2

3.2

3.1

1.1

ug m /Year -3

Intercept

ug m

% Change

%/year

-6.4%

-2.7%

-3.8%

2.1%

-3.3%

-7.1%

-6.8%

12%

Slope

1/Year

5.5E-3

5.5E-3

8.1E-3

1.4E-2

5.1E-3

6.1E-3

-7.4E-4

-4.1E-2

Intercept

NA

0.17

0.40

0.45

0.14

0.25

0.52

0.62

0.67

% Change

%/year

13%

5.4%

7.1%

40%

8.2%

4.7%

-0.48%

-25%

268

Table 2: Results from the linear regression analysis for: pH, sulfate(SO42-), particulate nitrate

269

(NO3-), particulate ammonium (NH4+), gaseous ammonia (NH3(g)), Total ammonia (TNHx), and

270

ammonia gas molar partitioning ratio (RN= [NH3(g)]/[TNHx]) at all SEARCH sites. Bolded 15



271

results were found to be statistically significant at α=0.05. (Note: Yearly percent changes are

272

estimated from the slope and intercept and tabulated)

273 274

3.3 Particulate Ammonium (NH4+)

275

Reductions in observed SO42- were matched by similar reductions in particulate

276

ammonium (NH4+) in both networks. SEARCH sites with significant decreases in SO42- had

277

significant decreases in NH4+ that ranged from -0.012 ug/m3 NH4+/year at OLF to -0.044 ug/m3

278

NH4+/year at YRK. This trend was consistent with findings in the study by Saylor et al., (2015)26

279

and Shi et al., (2017)68.

280

CASTNET SO42- and NH4+ results showed comparable trends to SEARCH, albeit some

281

minor differences. The highest decrease of NH4+ (Table 1) was in the NE and SE (-0.02 ug/m3

282

NH4+/year) and the lowest decrease was in CA with (-0.008 ug/m3 NH4+/year). While the RK and

283

MW regions saw reductions in SO42-, only in the NE, SE and CA regions were reductions in

284

NH4+ statistically significant.

285 286

3.4 Particulate nitrate (NO3-), Total nitrate (TNO3-), and nitric acid gas (HNO3(g))

287

Our analysis showed no statistically significant changes in PM2.5 NO3- concentrations as

288

SO42- levels fell at CASTNET and SEARCH sites (the observations did not include coarse

289

particle nitrate concentrations, which could be substantial in regions with sea salt or high dust

290

loadings). In agreement with past studies, the NO3- concentrations were considerably lower than

291

SO42- concentrations (Table 1, Table 2), and remained so throughout the course of the study20, 30,

292

69

293

reductions. A general decrease in fine particulate TNO3- and HNO3(g) was observed (except at

. These low levels of NO3-, led to minimal effects on NH4+ levels in response to observed NOx

16


Page 16 of 32

Page 17 of 32


294

PNS where monitoring ceased after 2009; See SI Figures S7, S8, S13 and S14), but only the

295

HNO3(g) trends in the NE and SE regions from CASTNET were significant.

296

These observations, when viewed with additional factors (i.e. temperatures) explain, in

297

part, why the MW and RK did not have significant reductions in NH4+ despite high reductions in

298

SO42-. For instance, besides having the lowest SO42- levels in the network, RK winter time

299

temperatures were consistently lower than other regions (Figure S12), providing favorable

300

NH4NO3 formation conditions18. In the MW, the combination of low winter time temperatures

301

and high NH3(g) concentrations promotes NH4NO3 formation70. Further, pHs in the MW were

302

generally higher than in other regions (consistently above three), another favorable condition for

303

NH4NO3 formation28.

304

To further investigate pH and NO3- results in the MW, we examined regional cation

305

trends (Figure S9 and Figure S10) at all CASTNET sites. The MW had higher nonvolatile cation

306

concentrations compared to other regions, an observation which can be attributed to

307

contributions from dust, as shown in Ivey et al., (2015)71. Elevated nonvolatile cation

308

concentrations led to higher pHs and increased portioning to aerosol nitrate. Similar observations

309

have been reported in a number of studies which also show that high pH and more nitrate

310

partitioning can be attributed to such aerosol components from dust when conducting a bulk

311

analyses, assuming an internal mixture47,

312

aerosol is to a degree externally mixed.

68, 72-74

. And this conclusion still holds, even if the

313

While the study by Allen et al., (2015)74 suggests that aerosol NO3- formation in

314

submicron particles could occur as NaNO3 and Ca(NO3)2 as opposed to ammonium nitrate, the

315

high NH4+ concentrations in the MW support NH4NO3 formation, as the available cation data

316

find too little of these components to explain much of the nitrate. We conclude this based on the 17



Page 18 of 32

317

low fall-spring temperatures in the MW, the seasons during which high nitrate is found, which

318

would likely promote NH4NO3 formation. Further, when compared to CA trends with similar

319

NH3(g) and cation levels, the lack of cold temperatures did not promote extra NO3- formation in

320

CA as it did in the MW (Figure S19). Also, the concentrations of NH4+ and NO3- in the MW

321

(where NO3- levels were comparable to SO42-) tended to be the highest in the entire network.

322 323

Spring

Summer

Fall

2011

2001

Winter

324 325 326

Figure 1: CMAQ-derived pH fields for 2001 and 2011 found using seasonal average

327

compositions.

328

The respective seasons: Winter, Spring, Summer, Fall account for temporal effects.

329 330

3.5 Total Ammonium (TNHx), Ammonia gas (NH3(g)), and RN

331

As with pH, annually-average NH3(g) concentrations changed very little across the study

332

period. CASTNET/AMoN, NH3(g) remained stable, showing statistically insignificant changes

333

at the 95% confidence interval in all regions from 2011 to 2015. Results for TNHx were varied, 18


Page 19 of 32


334

with RK, MW and the NE showing yearly decreases of about -4% for all 3 regions, while the SE

335

and CA regions exhibited yearly increases in TNHx (+0.008 ug/m3 and 0.02 ug/m3 respectively).

336

However, the slope from the linear trends in all regions (except the NE) were insignificant at α =

337

0.05. TNHx peaks for MW (Figure 2), showed slightly different patterns than other sites (i.e.

338

spring vs. summer peaks) which we attribute to contribution of NH4+ from NH4NO3 formation at

339

lower temperatures, fertilizer use and increasing volatilization from animal waste in warmer

340

months.

341

Only CTR, JST, OLF, YRK, BHM SEARCH sites showed statistically significant

342

decreases in TNHx ranging from -3%/year to -7%/year, but no statistically significant change in

343

NH3(g) concentration was observed except at BHM (-7%/year). This negative downward trend

344

result for TNHx was also observed by Saylor et al., (2015), which is in contrast to expected

345

increases in emissions75. However, this trend is explained by both the rapid deposition of

346

NH3(g), leading to a pseudo-state state balance between emissions and gas-phase deposition,

347

leading to small changes in NH3(g), accompanied by a reduction in aerosol ammonium tied to

348

sulfate and nitrate.

349

Simulated seasonal and annual CMAQ concentrations of NH3(g) showed relatively

350

steady concentrations over the ten-year period (Figure 4 and Figure S20), though wintertime

351

NH3(g) concentrations decreased in the upper northern states with smaller changes elsewhere.

352

A noticeable and consistent increase in the molar concentration ratio of NH3(g) to TNHx

353

(RN=[NH3(g)]/[TNHx]) was observed at all CASTNET/AMoN (Figure 2g) and SEARCH (except

354

PNS and BHM Figure 3g) sites, another trend also noted by Saylor et al., (2015). This seasonal

355

trend of increased RN was significant at over 60% of SEARCH sites, CTR, JST, OAK, OLF, and

19



356

YRK and in the SE region from the CASTNET/AMoN network. The slope for RN at OAK is

357

substantially higher than at other sites, though the observational period was short.

358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 20


Page 20 of 32

Page 21 of 32


379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422

Figure 2: Linear regression time series trends for CASTNET/AMoN co-located sites labeled as follows, (2a): pH (2b): Sulfate (SO42-), (2c): Particulate ammonium (NH4+), (2d): Particulate nitrate (NO3-), (2e): Gaseous ammonia (NH3(g)), (2f): Neutralization Ratio (f), (2g): Gaseous ammonia partitioning molar ratio to total ammonia (RN), (2h): Total ammonia (TNHx). (CA: California; NW: Midwest; NE: Northeast; RK; Rocky Mountains; SE: Southeast).

21



423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439

Page 22 of 32

Figure 3: Linear regression time series trends for SEARCH sites labeled as follows, (3a): pH (3b): Sulfate (SO42-), (3c): Particulate ammonium (NH4+), (3d): Particulate nitrate (NO3-), (3e): Gaseous ammonia (NH3(g)), (3f): Neutralization Ratio (f), (3g): Gaseous ammonia partitioning molar ratio to total ammonia (RN), (3h): Total ammonia (TNHx). (Note: Results of PNS trends for sulfate, ammonium, and ammonia molar fraction are affected by limited data). (Note: Abbreviation for sites mentioned in Data and Methods section).

Spring

Summer

Fall

2011

2001

Winter

440 441 442

Figure 4: Seasonal average ammonia concentrations simulated by CMAQ for 2001 and 2011.

443

The respective seasons, Winter, Spring, Summer, Fall consider temporal effects.

444 445

3.6 Neutralization Ratio f

446

The observed changes in species concentrations had a minor impact on the neutralization

447

ratio f (Table S9) at the CASTNET/AMoN or SEARCH network sites (apart from OLF; Table

448

S10). While values obtained for f were similar with other studies, as earlier stated, f is an

449

inadequate proxy for acid neutralization or acidity41,

68

. Results from the MW, where the

22


Page 23 of 32


450

presence of other cations besides NH4+, lead to an elevated pH, illustrate this point. Additional

451

limitations of f are discussed further in the SI.

452 453

3.7 Fine Temporal Analysis

454

A comparison of modeled pH using a finer temporal scale was conducted at SEARCH

455

sites. Instead of seasonal averages, monthly averages were used as inputs into ISORROPIA-II.

456

Results of monthly modeled pH were statistically the same at all sites except at OAK. However,

457

the p-values between both temporal scales results were similar, differing only by 0.005 points

458

(Tables S6 and S8). This difference, which could be attributed to measurement errors does not

459

obscure or contradict the overall results from the seasonal average analysis which points to

460

minimal pH changes, despite significant reductions of sulfate at all sites. In fact, the statistical

461

analysis results for other speciated PM2.5 at this finer resolution mostly matched previous results

462

at all the sites, with one or two sites changing (i.e. NO3-, SO42- had same site statistical results,

463

while TNHx results changed, with OLF no longer showing statistical significance).

464 465

3.8 Implications

466

Similar to prior empirical analysis in the Southeast, the results show that neither sulfur

467

nor nitrogen oxide emission reductions are substantially impacting aerosol acidity at a national

468

level for PM2.5 particles. The two locations with statistically significant—but small—pH trends

469

(< 1pH unit yr-1), a near-coast SEARCH site in Mississippi (OAK) and another in California, did

470

not have statistically significant SO42- reductions (though annual average sulfate levels did

471

decrease), or high SO42- levels at the beginning of our analysis period as compared to other sites.

472

Due to large contributions of PM2.5 from vehicle motors76, California had the second lowest 23



Page 24 of 32

473

SO42- levels overall (Figure 2b), and also saw higher levels of NH3(g) than most

474

CASTNET/AMoN regions (Figure 2e). Similarly, OAK had the lowest SO42- concentration

475

(except PNS), although not considerably lower than CTR, and a high increase rate of NH3(g) and

476

NH3(g) partitioning than other SEARCH sites. Thus, the common factor between OAK and

477

California appears to be a combination of much lower SO42- levels, higher NH3(g) molar fraction

478

increases and the presence of other cations. This means that if the contribution of nonvolatile

479

cations doesn’t change significantly over time (as found in this analysis, Figures S21 to S23 &

480

Tables S6 to S7), much lower levels of SO42-, in addition to higher NH3(g) concentrations are

481

needed before significant changes in pH, or larger degrees of neutralization will be observed.

482

This was also noted in Weber et al., (2016).

483

For example, the potential coupled effect of low SO42- concentrations and high NH3(g) on

484

pH is further illustrated by comparing observations from JST, YRK and BHM SEARCH sites, all

485

of which had high initial SO42- levels and higher NH3(g) concentrations than OAK and showed

486

no statistically significant changes in pH. This demonstrates that even if NH3(g) emissions were

487

to remain stable or increase slightly as projected by Behera et al., (2013)77 and Paulot et al.,

488

(2016)75, it would not have a significant influence on acidity as aerosol sulfate levels decrease in

489

response to reductions.

490

Observed reductions in SO42- did not necessarily lead to NO3- substitution,

as

491

hypothesized, or as seen in other studies30, 78. This is because neutralization of SO42- solely by

492

NH3(g) at current levels did not lead to substantially higher pHs or increases in gaseous ammonia

493

which would promote NO3- formation. This effect of NH3(g) levels on NO3- formation was also

494

discussed in Blanchard et al., (2003) and Weber et al., (2016).

24


Page 25 of 32


495

The NH3(g) partitioning ratio (RN) increased across all regions and most sites (except

496

PNS and BHM) due to reduced SO2 and NOx emissions, as evidenced by reductions in PM2.5

497

sulfate concentrations while NH3(g) remained steady for reasons discussed earlier. Similar

498

results observed by Saylor et al., (2015) and Shi et al., (2017)68 indicate that this is not

499

unexpected. Even in areas like the MW, where high levels of ammonium nitrate did not lead to

500

significant reductions in NH4+, there was still a slight positive increase in NH3(g) partitioning.

501

However, the increased partitioning contributions, along with projected emission increases of

502

NH3(g) did not appear to have any statistically significant impact on NH3(g), which is impacted

503

by the rapid cycle that exists between emissions and deposition rates52, 75, 79. This, along with

504

observations noted in Guo et al., (2017) show that existing or higher levels of NH3(g) are not

505

likely to impact aerosol pH much. Results also show that RN is also not likely to be impacted by

506

NH3(g) projected emissions as a result, but more by SO2 and NOx emissions.

507

TNO3- trends were also small, despite NOx reductions30, 52, 80-81. This is partly impacted

508

by the fast deposition of HNO3(g), along with a steady ammonia concentration. These findings in

509

this study, would apply specifically to fine particulate nitrate, not coarse mode nitrate.

510

The statistically insignificant changes in pH corroborate and extend the findings by

511

Weber et al., (2016) and further support that aerosol pH has been impacted little by reductions in

512

sulfur dioxide and nitrogen oxide emissions across the US. Despite differences in slope direction

513

of both trends due to differences in data (i.e. seasonal trend vs summer), both studies show

514

insignificant changes in pH. The study also shows that reduced NOx emissions had little impact

515

on acidity (high or low) and that NH3(g) levels remained stable. Lower sulfate levels with an

516

abundance of ammonia, coupled with the presence of nonvolatile cations will be needed to see

517

significant pH increases and acidity levels decrease. A thermodynamic analysis on the effects of 25



518

different levels of ammonia on aerosol pH substantiate these findings82. Further, it is clear that

519

earlier assumptions that NH4NO3 would increase due to sulfate reductions did not consider that

520

the continued low pH, which is unfavorable to NH4NO3 formation in most regions and would

521

prevent substantial increases in particulate NH4NO3. What remains unclear, however, is how

522

long it will take to see significant changes in aerosol acidity as SO2 and NOx emissions continue

523

to decline, but based on the results of the study and others, it is likely to be substantial. While

524

reductions in aerosol acidity may not change much in response to SO2 and NOx emission

525

decreases, this does not mean that air quality improvements, in general will not be realized as

526

particulate matter levels will continue to decrease in response30, 83-84.

527

Lastly, despite the limited amount of data (i.e. both CASTNET and SEARCH data only

528

ranged between four to seven years), the conclusions and observations found are in line with

529

other studies focusing on spatially limited data over larger time periods (Saylor et al., 2015;

530

Weber et al., 2016). Further, air quality modeling results found in Vasilakos et al., (2017), along

531

with the CMAQ results in this study, all of which have longer time and can link the results

532

directly to emissions changes, found similar spatial and temporal patterns as the observations.

533 534

AUTHOR INFORMATION

535

Corresponding Author

536

*

537

Present Address

538

School of Civil & Environmental Engineering, Georgia Institute of Technology, 790 Atlantic

539

Drive, Atlanta, GA 30332-0355, United States.

540

Author Contributions

Phone: +1-404-894-3079; fax +1-404-894-2279; email [email protected]

26


Page 26 of 32

Page 27 of 32


541

The manuscript was reviewed by all authors. All authors have given approval to the final version

542

of the manuscript.

543

Notes

544

The authors declare no competing financial interest.

545 546 547 548 549 550

ACKNOWLEGEMENTS

551

This publication was made possible by funding from the US EPA under grants R834799,

552

R835882, and 83588001, the US NSF under award 1444745 and the Health Effects Institute. Its

553

contents are solely the responsibility of the grantee and do not necessarily represent the official

554

views of the supporting agencies. Further, the US government does not endorse the purchase of

555

any commercial products or services mentioned in the publication

556 557

Supporting Information

558

The Supporting Information (SI) accompanying this manuscript contains additional data, figures,

559

and tables, some of which are referenced directly within the manuscript. Also included is further

560

discussion regarding neutralization ratio (f) inadequacies and pH trend results. Additional

561

discussion on impact of organics, organosulfates and organonitrates on aerosol pH, model

562

evaluation on ISORROPIA and CMAQ is discussed in further detail as well. This information is

563

available free of charge via the Internet at http://pubs.acs.org. 27



564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602

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