1

A global gridded (0.1º x 0.1º) inventory of methane 1

emissions from fuel exploitation based on national 2

reports to the United Nations Framework 3

Convention on Climate Change 4

Tia R. Scarpelli*,1, Daniel J. Jacob1, Joannes D. Maasakkers1, Melissa P. Sulprizio1, Jian-Xiong 5

Sheng1, Kelly Rose2, Lucy Romeo2, John R. Worden3, and Greet Janssens-Maenhout4 6

1Harvard University, Cambridge, MA 02138, United States 7

2U.S. Department of Energy, National Energy Technology Laboratory, Albany, OR 97321, 8

United States 9

3Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, United 10

States 11

4European Commission Joint Research Centre, Ispra (Va), Italy 12

ABSTRACT 13

We present a global inventory of methane emissions from oil, gas, and coal exploitation at 0.1° x 14

0.1° resolution with detailed resolution of oil/gas subsectors. The inventory is constructed by 15

2

spatially disaggregating the national emissions reported by individual countries to the United 16

Nations Framework Convention on Climate Change (UNFCCC) and filling gaps as necessary. 17

Global emissions for 2012 are 40.3 Tg a-1 for oil, 27.1 Tg a-1 for gas, and 37.1 Tg a-1 for coal. An 18

array of databases is used to spatially allocate national emissions to infrastructure including wells, 19

pipelines, oil refineries, gas processing plants, gas compressor stations, gas storage facilities, and 20

coal mines. Gridded error estimates are provided in normal and lognormal forms based on emission 21

factor uncertainties from the IPCC. Our inventory shows large differences with the EDGAR v4.3.2 22

global gridded inventory for total fuel exploitation both at the national scale and in finer-scale 23

distributions. Use of our inventory as prior estimate in inverse analyses of atmospheric methane 24

observations allows investigation of individual subsector contributions and can serve policy needs 25

by evaluating the national emissions totals reported to the UNFCCC. 26

ABSTRACT ART 27

28

INTRODUCTION 29

Methane is the second most important anthropogenic greenhouse gas after CO2, with an emission-30

based radiative forcing of 1.0 W m-2 since pre-industrial times as compared to 1.7 W m-2 for CO21. 31

Major anthropogenic sources of methane include the oil/gas industry, coal mining, livestock, rice 32

cultivation, landfills, and wastewater treatment. Individual countries must report their 33

3

anthropogenic methane emissions by source to the United Nations in accordance with the United 34

Nations Framework Convention on Climate Change (UNFCCC)2. These reported emissions may 35

have large uncertainties, especially for fugitive emissions from fuel exploitation which that may 36

vary considerably depending on operating conditions3. 37

Top-down inverse analyses of atmospheric methane observations can provide a check on the 38

national emission inventories4, but they require prior information on the spatial distribution of 39

emissions within the country. Such spatial information is not available from the UNFCCC reports 40

which only give national totals. The EDGAR v4.2 global gridded emission inventory5 has been 41

used extensively as prior estimate in inverse analyses, but its oil/gas emissions often show large 42

differences compared to inventories which utilize more detailed data specific to the country or 43

region6-9. The EDGAR methane inventory prioritizes the use of a consistent methodology between 44

countries for emissions estimates and allocation to sources10, including the use of IPCC Tier 1 45

methods11. The latest public version, EDGAR v4.3.2, combines all emissions from fuel 46

exploitation (oil, gas, and coal) into a single source and currently provides annual grid maps for 47

the years 1990 to 201210, 12. 48

Emissions from the oil/gas industry include unintended releases as leaks, and intended releases 49

as venting and flaring. They occur during resource extraction (upstream), processing and transport 50

(midstream), and end product distribution (downstream). Emissions from coal mining include 51

emissions from underground mine vents, degasification systems, volatilization from surface 52

mines, and volatilization during transport and storage. Emission factors (amount released per unit 53

of activity) vary widely depending on operating conditions13-18. Gridded emission inventories with 54

some sectoral resolution have been produced for specific oil/gas fields7, California6, 19, 20, and 55

individual countries including Australia21, Switzerland22, the United Kingdom23, China24, the US8, 56

4

and Canada and Mexico9. Methane is sometimes included in multi-species regional and global 57

inventories, but these may be based on limited information and have coarse spatial and/or sectoral 58

resolution25-28. 59

Here we create a global 0.1° x 0.1° gridded inventory of methane emissions from the oil, gas, 60

and coal sectors, resolving individual processes (subsectors) and matching emissions to UNFCCC 61

national totals. This represents a spatially downscaled representation of the UNFCCC national 62

emission reports. Our premise is that the national totals reported by individual countries contain 63

country-specific information not available to the public or accessible in global databases that 64

improves on the generic estimates from IPCC Tier 1 methods. In addition, these UNFCCC national 65

totals provide the most policy-relevant estimates of emissions to be compared with results from 66

top-down inverse analyses. Our downscaling relies on global data sets for oil/gas infrastructure 67

available from DrillingInfo29, Rose (2017)30, and the National Energy and Technology 68

Laboratory’s Global Oil & Gas Infrastructure (GOGI) inventory and geodatabase31, 32. National 69

emissions from coal mining are distributed according to mine locations from EDGAR v4.3.2. We 70

present results for 2012, but our method is readily adaptable to later years. 71

72

METHODS 73

The UNFCCC receives inventory reports from 43 developed countries as ‘Annex I’ parties and 74

communications from 151 countries as ‘non-Annex I’ parties. The 43 Annex I countries report 75

annual totals for the oil, gas, and coal emission sectors and disaggregate them to subsectors. Non-76

Annex I countries report total emissions for the combined oil/gas sector and the coal emission 77

sector, but they are not required to report annually or disaggregate emissions to subsectors. We 78

use the UNFCCC GHG Data Interface (as of October 2017)33 to download sector and subsector 79

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emissions for 2012 reported by Annex I countries and sector totals for oil/gas and coal for the year 80

closest to 2012 reported by non-Annex I countries (reporting year ranges from 1990 to 2015). If a 81

non-Annex I country does not report coal emissions separate from oil/gas we consider them as a 82

non-reporting country as described below. 83

Figure 1 gives a flow chart of the main emission processes from the exploitation of oil, gas, and 84

coal. These processes define the subsectors of our inventory with each box representing a separate 85

gridded inventory database. For oil and gas, methane may be emitted unintentionally (fugitive 86

emissions) or intentionally (venting and flaring emissions). For coal, methane is emitted from 87

surface and underground mines during the mining process and during post-mining activities11. The 88

IPCC provides methods to account for methane utilization at mines and emissions from abandoned 89

mines, so countries may choose to account for these factors in their estimates. 90

91 Figure 1. Methane emitting subsectors from fuel exploitation as resolved in our inventory. Each 92

box in the figure corresponds to a separate 0.1o x 0.1o gridded product in the inventory. 93

94

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National emissions by subsector. Our first step is to compile national emissions for each 95

subsector of Figure 1 in the year 2012. Annex I countries report fugitive emissions for all oil and 96

gas emission subsectors directly to the UNFCCC and these emission can be used as reported. Gas 97

transmission and storage emissions are an exception which are only reported as a combined total. 98

Venting and flaring emissions are only reported as sector totals: oil venting, oil flaring, gas venting, 99

and gas flaring. The fugitive emissions from gas transmission and storage, and the venting and 100

flaring emissions from the from the overall oil and gas sectors, have to be disaggregated in order 101

to spatially allocate emissions to infrastructure. This disaggregation is performed using IPCC 102

methods as described below for non-Annex I countries. 103

For most non-Annex I countries, reported emissions are available from the GHG Data Interface 104

as national totals for oil/gas and coal with no further sectoral breakdown. Some non-Annex I 105

countries also choose to report emissions disaggregated by subsectors similar to Annex I countries. 106

These reported emissions are not available in the GHG Data Interface and require inspection of 107

reports submitted by each country, including National Communications (submitted every 4 years)34 108

and Biennial Update Reports (submitted every 2 years)35. We utilize these reports for high emitting 109

countries (oil+gas emissions greater than 1 Tg a-1) including Venezuela, Uzbekistan, Iran, 110

Malaysia, India, Algeria, and Nigeria. Data for Venezuela and Nigeria in the GHG Data Interface 111

are for older years (1999 and 1994, respectively) compared to the reported emissions included in 112

their national reports (2010 and 2015, respectively), so we use the more recent data. The extent of 113

emissions disaggregation for these non-Annex I countries varies. Uzbekistan, Malaysia, Algeria, 114

and Nigeria report the same subsectors as Annex I countries while Venezuela, Iran, and India only 115

report oil fugitive emissions, gas fugitive emissions, and total venting and flaring emissions which 116

all require further disaggregation. 117

7

Reported non-Annex I emissions are disaggregated as needed by following IPCC Tier 1 118

methods11. Subsector emission contributions are estimated for the reported year of emissions by 119

applying IPCC emission factors for each subsector to national activity data from the U.S. Energy 120

and Information Administration (EIA)36. Exploration emissions are estimated using oil production 121

volume as activity data as indicated by IPCC methods and are therefore labeled as oil exploration. 122

Annex I countries report emissions specifically for gas exploration which account for

8

This is the case notably for Libya. We also use this method for countries that do not separately 141

report coal emissions from oil/gas which includes Angola. When EIA activity data for a country 142

are missing (notably South Sudan), we use the infrastructure data described below together with 143

the average emissions per infrastructure element based on countries that do report emissions. 144

For coal, Annex I emissions for 2012 are used as reported. Non-Annex I emissions reported as 145

total coal emissions are adjusted to 2012 as needed using activity data provided by the EIA36. For 146

the few countries that do not report to the UNFCCC, we use the coal emissions data embedded in 147

EDGAR v4.3.2 fuel exploitation with additional information from EDGAR to separate coal; these 148

account for less than 1% of global coal emissions. 149

Spatial Allocation of Emissions. Our next step is to allocate the national emissions from each 150

subsector of Figure 1 spatially on a 0.1o x 0.1o grid. National emissions are allocated following the 151

procedure described below for all countries except the use of existing gridded inventories for 152

oil/gas and coal in the contiguous US8 and for oil/gas in Canada and Mexico9. The gridded 153

inventories are scaled to match the UNFCCC subsector totals for those countries. We estimate 154

emissions for Alaska using the EPA State Inventory Tool37 following the methods outlined in the 155

Alaska Greenhouse Gas Emission Inventory38 and apply the procedures described below to 156

distribute these emissions spatially. Other gridded national emission inventories are not used here 157

due to limited spatial resolution and/or limited disaggregation of emissions21-23, 25, 26. 158

Upstream emissions, including exploration and production, are allocated to wells as illustrated 159

in Figure 2. Our principal source information on wells is DrillingInfo29. It provides worldwide 160

point locations of onshore and offshore wells, well activity status, and well content. Well activity 161

status is used to separate active from inactive wells with inactive wells assumed not to emit. Well 162

content is used to separate oil, gas, and unknown content wells. Wells labelled as oil+gas are 163

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combined with unknown content wells. We allocate a percentage of total oil and gas emissions to 164

unknown content wells corresponding to the percentage of total wells that have unknown content. 165

The remaining oil and gas emissions are allocated to wells with oil and gas contents, respectively. 166

Well data are missing from DrillingInfo for a number of countries. An alternative global well 167

database is available from Rose (2017)30 based on a combination of open source data and 168

proprietary data from IHS Markit39 and mapped on a 0.1o x 0.1o grid (total number of wells per 169

grid cell). The Rose database does not include information on oil versus gas content. We use this 170

database for all countries that are either missing from the DrillingInfo database or for which the 171

Rose database has 50% greater active wells than DrillingInfo and 50% greater total (inactive + 172

active) wells than DrillingInfo. This includes 47 of the 134 countries with active well infrastructure 173

notably Russia, United Arab Emirates (UAE), China, Libya, Saudi Arabia, Turkmenistan, Ukraine, 174

and Azerbaijan. We distribute total upstream emissions from both oil and gas evenly over all active 175

wells within each country. The Rose database includes offshore wells, but they are not identified 176

by country so we rely solely on DrillingInfo offshore wells. We use pipelines to allocate upstream 177

emissions if wells are missing in both databases (

10

processing plant, compressor station, and storage facilities, respectively, in each country. Annex I 187

countries report “Other” emissions for oil and gas which are distributed equally to wells and 188

pipelines. 189

190

191 Figure 2. Global distribution of oil/gas wells29, 30 and pipelines31, 40-42 used in our inventory. The 192

data are at 0.1o x 0.1o grid resolution but are degraded here to 0.2o x 0.2o for visibility. 193

194

The GOGI database was created through a machine-learning web search of public databases for 195

mention of oil and gas infrastructure, so it is limited to open-source resources. The database misses 196

11

some infrastructure locations32, so the spatial allocation of emissions within a country may be 197

biased. To alleviate this bias, we check each country for exceedance of an oil or gas volume-per-198

facility threshold (e.g., volume of gas processed per day per processing plant). If the threshold is 199

exceeded we estimate the percentage of facilities missing, and the corresponding percentage of 200

subsector emissions is allocated to pipelines since non-well infrastructure tend to lie along pipeline 201

routes. Visual inspection suggests that countries with pipelines in the GOGI database are not 202

missing any significant pipeline locations which is consistent with a gap analysis for the GOGI 203

database32. 204

For oil refining in each country, we determine a refining rate per refinery by distributing the total 205

volume of oil refined36 for 2012 over the GOGI refineries in that country. If the refining rate 206

exceeds the threshold set by the Jamnagar Refinery in India of 1.24 million barrels of crude oil per 207

day43, then oil refining emissions corresponding to the missing refineries are allocated to pipelines. 208

The same is done for processing plants, storage facilities, and compressor stations. Processing 209

plants are missing if production of natural gas36 distributed over processing plants exceeds 57 210

million cubic meters of gas per day per facility based on the Ras Laffan processing plant in Qatar44. 211

Storage facilities are missing if production of marketable gas36 exceeds 68 billion cubic feet per 212

year per facility, corresponding to the total US capacity determined from marketable gas volume 213

and number of active storage facilities45. Compressor stations are missing if the implied gas 214

pipeline length46 between GOGI stations is more than 100 miles. 215

In order to allocate the appropriate oil and gas emissions to oil and gas pipelines, we separate 216

the GOGI pipelines into oil and gas when possible though a significant number have unknown 217

content. We allocate a percentage of national oil and gas pipeline emissions to unknown content 218

pipelines corresponding to the percentage of total pipelines with unknown content, and the 219

12

remaining oil and gas emissions are allocated to oil and gas pipelines, respectively. In order to 220

avoid allocating Russia’s significant gas transmission emissions to unknown content pipelines, we 221

instead use a gridded 0.1o x 0.1o map of gas pipelines based on the detailed Oil & Gas Map of 222

Russia/Eurasia & Pacific Markets42. 223

Downstream gas distribution emissions are associated with residential and industrial gas use. 224

We allocate these emissions within each country on the basis of population using the Gridded 225

Population of the World (GWP) v4.10 30 arc second map47 for 2010. Midstream emissions are 226

also allocated to population for countries missing in the GOGI database (

13

Lower (%)

Upper (%)

RSD (%)

GSD Lower (%)

Upper (%)

RSD (%)

GSD

Oil Exploration (All)b 100 100 50 2.11 12.5 800 100 1.79 Production (Fugitive) 100 100 50 2.11 12.5 800 100 1.79 Production (Venting) 75 75 37.5 1.63 75 75 37.5 1.63 Production (Flaring) 75 75 37.5 1.63 75 75 37.5 1.63 Refining (All) 100 100 50 2.11 100 100 50 2.11 Transport (Fugitive)c 100 100 50 2.11 50 200 62.5 1.57 Transport (Venting)c 50 50 25 1.32 50 200 62.5 1.57 Gas Production (Fugitive) 100 100 50 2.11 40 250 72.5 1.55 Production (Flaring) 25 25 12.5 1.14 75 75 37.5 1.63 Processing (Fugitive) 100 100 50 2.11 40 250 72.5 1.55 Processing (Flaring) 25 25 12.5 1.14 75 75 37.5 1.63 Transmission (Fugitive) 100 100 50 1.41 40 250 72.5 1.55 Transmission (Venting) 75 75 37.5 1.63 40 250 72.5 1.55 Storage (All) 20 500 100 1.65 20 500 100 1.65 Distribution (All) 20 500 100 1.65 20 500 100 1.65 Coal 33 300 83.3 1.56 n/a n/a n/a n/a

a The uncertainty ranges (lower, upper) are provided by the IPCC and apply to the estimation of 242 national emissions using emission factors specified in Tier 1 methods11. We interpret them here as 243 95% confidence intervals, and infer the corresponding relative standard deviation (RSD, %) for 244 the assumption of a normal error pdf and geometric standard deviation (GSD, dimensionless) for 245 the assumption of a lognormal pdf. The IPCC provides uncertainty ranges for ‘developed’ and 246 ‘developing’ countries and we apply them to Annex I and non-Annex I countries, respectively. 247

b Well drilling 248

c Pipeline transport 249

250 In the absence of better information, we conservatively interpret the IPCC uncertainty ranges as 251

representing the 95% confidence intervals. The ranges are generally asymmetric, but we 252

approximate them in Table 1 in terms of a relative error standard deviation (RSD) assuming a 253

normal error probability density function (pdf) and a geometric error standard deviation (GSD) 254

assuming a lognormal error pdf. These pdf forms are commonly used as error estimates in 255

inversions because they allow straightforward mathematical formulation of the Bayesian 256

optimization problem48. The 95% confidence interval then represents ± 2 standard deviations in 257

linear space for the normal pdf and in log space for the lognormal pdf. For the assumption of a 258

normal error pdf, we take the average of the IPCC upper and lower uncertainty limits for each 259

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subsector and halve this value to get the RSD with an allowable maximum RSD of 100%. For the 260

assumption of a lognormal error pdf, the IPCC limits are log-transformed, halved, averaged and 261

transformed back to linear space to yield the GSD for the lognormal error pdf. The lower limits of 262

the IPCC uncertainty ranges are capped at 90% when determining the GSD. 263

We assume that errors are scale-independent, so that errors on the 0.1o x 0.1o grid are defined by 264

the national error estimates. A previous error analysis for the gridded EPA inventory based on 265

comparison to a more detailed inventory for the Barnett Shale showed that the error in emissions 266

from oil systems was not significantly higher on the 0.1o x 0.1o grid than the national error estimate 267

of 87%, while the error for gas systems on the 0.1o x 0.1o grid was twice the national estimate of 268

25%8. The uncertainty ranges in Table 1 are sufficiently large that we can reasonably apply them 269

to the 0.1o x 0.1o grid, though the implicit assumption then is that they are spatially correlated on 270

the national scale. Properly defining an error correlation spatial scale for the emissions is beyond 271

the quality of information that we have available. 272

273

RESULTS AND DISCUSSION 274

Table 2 lists the global methane emissions from fuel exploitation, broken down by the sectors and 275

subsectors resolved in our inventory. Global fuel exploitation emissions in 2012 are 104 Tg a-1, 276

including 40.3 Tg a-1 from oil, 27.1 Tg a-1 from gas, and 37.0 Tg a-1 from coal. Oil emissions are 277

mainly from production, in part because oil fields often lack the capability to capture associated 278

gas. Gas emissions are distributed over the upstream, midstream, and downstream subsectors. 279

EDGAR v4.3.2 has similar global emissions from fuel exploitation (107 Tg a-1), but the distribution 280

is very different as discussed below. Bottom-up estimates compiled by the Global Carbon Project49 281

give a best estimate of 134 Tg a-1 from fuel exploitation in 2012 with a range of 123-141 Tg a-1 282

15

across studies while the compilation of top-down inverse analyses gives a best estimate of 112 Tg 283

a-1 with a range of 90-137 Tg a-1. 284

Table 2. Global methane emissions from fuel exploitation (2012)a. 285

Subsector Total (Tg a-1)

Oil 40.3 Exploration (All) 1.3 Production (Fugitive) 16.8

Production (Venting) 21.4 Production (Flaring) 0.5 Refining (All)

16

UNFCCC account for 46% and 49% of global fuel exploitation emissions, respectively, with the 297

remaining emission contributed by countries that do not report to the UNFCCC. 298

299

Figure 3. Methane emissions (2012) from the top 20 emitting countries for the oil, gas, and coal 300

sectors. Arrows next to the top bars (highest emitting countries) indicate that emissions are not to 301

scale. 302

303

Figure 4 shows the global distribution of methane emissions separately for oil, gas, and coal. Oil 304

emissions are mainly in production fields. Gas exploitation emissions are more spread through the 305

gas lifecycle. Contributions from gas production, transmission, and distribution can all be seen in 306

Figure 4 with the dominant subsector varying between countries. The highest emissions are from 307

oil/gas production fields, gas transmission routes, and coal mines. 308

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309 Figure 4. Global distribution of 2012 methane emissions from oil, gas, and coal. The inventory is 310

at 0.1o x 0.1o grid resolution. Coal is shown here at 1º x 1º resolution for visibility. 311

312 Figure 5 shows the global distribution of methane emissions from total fuel exploitation and 313

EDGAR v4.3.2 is shown for comparison. Emissions along pipelines are generally lower and 314

emissions from production fields are generally higher in our work compared to EDGAR v4.3.2. 315

18

Differences in spatial patterns within each country are due to differences in subsector contributions 316

and source locations (for oil/gas), but there are also some large differences in national emissions 317

estimates. 318

319

Figure 5. Total methane emissions from fuel exploitation (oil, gas, and coal) in 2012 for this work 320

and EDGAR v4.3.2. 321

322 Figure 6 compares national fuel exploitation emissions as reported to the UNFCCC versus 323

EDGAR v4.3.2 emissions in the same year. Russia, Venezuela, and Uzbekistan report emissions 324

19

that are at least a factor of 2 greater than EDGAR v4.3.2. Iraq, Qatar, and Kuwait report emissions 325

that are at least an order of magnitude less than EDGAR v4.3.2 though their reporting years are 326

outdated (1997, 2007, and 1994, respectively) which may lead to greater uncertainty. Upstream 327

emissions estimates made based on gas utilization, venting, and flaring rates also show significant 328

upstream emissions in Russia (14 Tg a-1 for 2012) though for Iraq, Qatar, and Kuwait they show 329

upstream emissions similar to EDGAR v4.3.250. The discrepancies between this work and EDGAR 330

v4.3.2 in Russia and the Middle East lead to a greater emissions contribution from high latitudes 331

and a lesser contribution from low latitudes in the Northern Hemisphere in our work. 332

333 334 Figure 6. Fuel exploitation emissions from UNFCCC reports as compared to EDGAR v4.3.2. The 335

figure shows the UNFCCC/EDGAR ratio for individual countries with warmer colors indicating 336

higher UNFCCC emissions. Emissions from non-Annex I countries are taken from the most recent 337

year reported in the GHG Data Interface or in country specific reports (as described in the text) 338

and compared to EDGAR for the same year. The reporting year for non-Annex I countries with 339

emissions greater than 1 Tg a-1 in either inventory is shown to the right. Nigeria reported in 2015 340

but is compared to EDGAR in 2012. Countries in gray do not report oil/gas and coal emissions to 341

the UNFCCC. 342

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343 The cause of differences between the national UNFCCC totals and EDGAR v4.3.2 is complex 344

and country-specific. Emission factors per unit of activity inferred from the UNFCCC reports can 345

vary by orders of magnitude between countries51. This may reflect differences in regulation of 346

venting and flaring (especially for oil production), maintenance and age of infrastructure, the size 347

and number of facilities within a country, and inventory error. Middle East countries report low 348

emissions relative to their production volumes, but they tend to have a small number of wells. In 349

contrast, Russia and Uzbekistan report high emissions relative to oil production and gas processing 350

volumes. In the case of Uzbekistan, high emissions are attributed to leaky infrastructure and 351

increases in processed/transported gas volumes starting in the early 1990s52, possibly leading to 352

the use of infrastructure beyond the age or capacity it was designed for. This work can be used in 353

inverse analyses to compare the magnitude and sectoral breakdown of these UNFCCC reported 354

emissions to observations. Corrections to emission estimates revealed by the inverse analyses can 355

be of direct benefit to policy by identifying errors in the national inventories. The annual gridded 356

emission fields for each subsector in Figure 1 are available at [website]. 357

358

AUTHOR INFORMATION 359

Corresponding Author 360

*E-mail: tscarpelli@g.harvard.edu 361

Notes 362

The authors declare no competing financial interest. 363

ACKNOWLEDGMENTS 364

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This work was supported by the NASA Earth Science Division and by the NDSEG (National 365

Defense Science and Engineering Graduate) Fellowship to TRS. 366

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