OCS Study

BOEM 2020-047

U.S. Department of the Interior

Bureau of Ocean Energy Management

Sterling, VA

Evaluation of NASA’s Remote-Sensing 

Capabilities in Coastal Environments
OCS Study

BOEM 2020-047

U.S. Department of the Interior

Bureau of Ocean Energy Management

Sterling, VA

Evaluation of NASA’s Remote-Sensing 

Capabilities in Coastal Environments

September 2020

Author:

Dr. Anne M. Thompson

Prepared under Interagency Agreement M17PG00026

By:

National Aeronautics and Space Administration (NASA)

NASA Goddard Space Flight Center

8800 Greenbelt Road

Greenbelt, MD 20771
DISCLAIMER

This study was funded, in part, by the U.S. Department of the Interior, Bureau of Ocean Energy 

Management (BOEM), Environmental Studies Program, Washington, DC, through Interagency 

Agreement Number M17PG00026 with the U.S. National Aeronautics and Space 

Administration (NASA). This report has been technically reviewed by BOEM, and it has been 

approved for publication. The views and conclusions contained in this document are those of 

the authors and should not be interpreted as representing the opinions or policies of the U.S.

Government, nor does mention of trade names or commercial products constitute endorsement 

or recommendation for use.

REPORT AVAILABILITY

To download a PDF file of this report, go to the U.S. Department of the Interior, Bureau of 

Ocean Energy Management Data and Information Systems webpage

(http://www.boem.gov/Environmental-Studies-EnvData/), click on the link for the Environmental 

Studies Program Information System (ESPIS), and search on 2020-047. The report is also 

available at the National Technical Reports Library at https://ntrl.ntis.gov/NTRL/.

CITATION

Thompson AM. 2020. Evaluation of NASA’s remote-sensing capabilities in coastal 

environments. Sterling (VA): U.S. Department of the Interior, Bureau of Ocean Energy 

Management. OCS Study BOEM 2020-047. 33 p.

ABOUT THE COVER

The SCOAPE logo was designed by Russell Yerkes, Visual Information Specialist, BOEM.

ACKNOWLEDGMENTS

This work was funded by the U.S. Department of the Interior, Bureau of Ocean Energy 

Management (BOEM) with additional funds provided by the U.S. National Aeronautics and 

Space Administration (NASA) Applied Sciences Program. BOEM donated the time of two 

additional personnel to participate in the SCOAPE field campaign in May 2019. The Royal 

Dutch Meteorological Office (KNMI) also donated the time of one employee to participate in the 

field campaign. Field support and analysis in this report were provided by D. E. Kollonige 

(Science Systems and Applications, Inc., Lanham, MD) and R. M. Stauffer (Univ. of MarylandCollege Park/Earth System Science Interdisciplinary Center, College Park, MD), both working at 

NASA/Goddard Space Flight Center.
ABSTRACT

This work represents the second part of a two-part study set up by the National Aeronautics and 

Space Administration (NASA) and Bureau of Ocean Energy Management (BOEM) in 2017. The 

study summarizes a three-year investigation on the feasibility of using satellite remote sensing 

to monitor emissions of oil and gas operations over the outer continental shelf (OCS) to 

determine if they have negative impacts on coastal air quality (AQ). The target pollutant is 

nitrogen dioxide (NO2), for which BOEM conducts regular emissions surveys. The major data 

source for this report is a May 2019 oceanographic cruise (“SCOAPE” = Satellite Coastal and 

Oceanic Atmospheric Pollution Experiment) conducted in the Gulf of Mexico (GoM) off 

Louisiana with the Research Vessel Point Sur, loaded with a suite of trace-gas analyzers and a 

direct-sun remote sensor Pandora spectrometer that measures column NO2. The SCOAPE 

cruise, augmented by in situ NO2 and Pandora measurements at Cocodrie (Louisiana; 29.25° N, 

90.66° W) showed that (1) under cloud-free conditions, satellites can detect elevated column 

NO2 amounts near isolated large platforms and from clusters of smaller operations; (2) satellite 

(the European Space Agency’s TROPOspheric Monitoring Instrument [TROPOMI]) total column 

(TC) NO2 agrees well with TC NO2 from ground-based Pandora spectrometers (to 11–18%), 

with the satellite biased low when pollution levels are higher; (3) in general, NO2 measured in

situ and in column amounts by Pandora or TROPOMI is greater over coastal Louisiana than 

over the OCS; (4) the extent to which Pandora or satellite measurements correlate with surface 

NO2 is highly variable.

It is recommended that BOEM and NASA continue to work together on collecting ground-truth 

NO2 data and on interpreting remote sensing data for BOEM’s AQ requirements. Specific 

recommendations:

1. BOEM and NASA should work together to analyze the 2019 SCOAPE data more 

thoroughly, including conducting studies with tracers, ancillary satellite data, trajectories,

and appropriate chemical transport model output to more firmly establish the magnitude 

of oil and natural gas influences on GoM AQ. Because remote-sensing measurements 

(satellite- and ground-based) do not provide ambient NO2 concentrations, these studies 

must be conducted to determine the column-surface NO2 relationship. NASA POC: 

anne.m.thompson@nasa.gov

2. Coastal monitoring along the GoM with NASA and the Environmental Protection Agency 

(EPA) using Pandora Spectrometer Instrument and other instruments would establish 

better statistics and contribute to the ongoing improvements in OMI (Ozone Monitoring 

Instrument) (mature algorithm) and the still evolving TROPOMI. Co-location with 

BOEM’s coastal project, aiming to begin in late 2020 at a remote unpolluted location in 

Louisiana, would greatly benefit BOEM. Daily overpass comparisons of OMI and 

TROPOMI TC NO2 with a Pandora instrument would give BOEM more complete 

statistics than the 5-week exploratory dataset of April–May 2019. Comparisons of the in 

situ and column NO2 amounts, along with other pollutants being measured, would further 

our understanding of the relationship of chemical transformation and interactions with 

dynamical processes in the boundary layer. NASA POC: 

anne.m.thompson@nasa.gov; barry.lefer@nasa.gov
i

Contents

List of Figures.......................................................................................................................................... ii

List of Tables...........................................................................................................................................iii

List of Abbreviations and Acronyms ........................................................................................................ iv

1 Introduction......................................................................................................................................1

1.1 Background..............................................................................................................................1

1.2 Remote Sensing of NO2 for BOEM’s Requirements..................................................................1

2 Findings from Previous Field Campaigns .........................................................................................2

2.1 South Korean Coastal Pollution Study: KORUS-OC 2016.........................................................2

2.2 Mid-Atlantic and Chesapeake Bay Ozone Study: OWLETS 2017..............................................4

2.3 Baltimore Harbor and Chesapeake Bay Pollution Study: OWLETS 2018...................................8

3 SCOAPE Cruise ............................................................................................................................11

3.1 Background: Emissions and Meteorological Conditions in Gulf of Mexico................................ 11

3.2 Onshore and Offshore SCOAPE Instrumentation and Plan.....................................................13

3.2.1 Onshore Observations....................................................................................................16

3.2.2 Offshore Observations: AQ Indicators on the SCOAPE Cruise........................................ 18

3.2.3 Satellite, Pandora and Surface NO2 Comparisons on the SCOAPE Cruise...................... 20

4 Summary of SCOAPE Cruise Analysis and Recommendations ......................................................25

5 References ....................................................................................................................................26
ii

List of Figures

Figure 1. KORUS-OC case study map. ...................................................................................................3

Figure 2. KORUS-OC in situ and Pandora TC NO2 on the R/V Onnuri.....................................................3

Figure 3. OWLETS 2017 map of the primary ground sites.......................................................................5

Figure 4. Histogram of OWLETS 2017 OMI-PSI % differences for LaRC (Pan 37) and CBBT (Pan 19)....6

Figure 5. OWLETS 2017 OMI pixel size examples. .................................................................................7

Figure 6. Map of TROPOMI TropC NO2 over LaRC and CBBT on 9 July 2018. .......................................8

Figure 7. Map of OWLETS-2 (2018) “super-sites”....................................................................................9

Figure 8. OMI (left) and TROPOMI (right) TC NO2 images in OWLETS 2018, 9 July 2018. ......................9

Figure 9. OWLETS 2018 satellite vs. Pandora comparisons..................................................................10

Figure 10. OWLETS 2018 satellite-PSI differences, based on same data as Figure 9........................... 10

Figure 11. TROPOMI TropC NO2 and VIIRS observations pre-SCOAPE: 6 January 2019. .................... 12

Figure 12. Two AQ regimes during SCOAPE: NASA surface CO forecast. ............................................12

Figure 13. TROPOMI TropC NO2 daily observations of marine vs. continental air during SCOAPE........ 13

Figure 14. View of Pandora spectrometers deployed pre- and during cruise.......................................... 14

Figure 15. Pictures of R/V Point Sur sampling and ONG operations during SCOAPE............................ 14

Figure 16. SCOAPE cruise R/V Point Sur track with onshore sampling locations................................... 15

Figure 17. Timeseries of Pandora and TROPOMI NO2 observations at LUMCON. ................................ 17

Figure 18. Comparison of three co-located Pandora instruments at LUMCON....................................... 17

Figure 19. Imported pollution during the SCOAPE cruise on 14 May 2019.............................................18

Figure 20 R/V Point Sur trace gas time series (a, c) and along-track maps (b,d).................................... 19

Figure 21. Ozonesonde profiles during SCOAPE. .................................................................................19

Figure 22. Summary of carbon-containing gases and DMS from R/V Point Sur flask samples. .............. 20

Figure 23. Pandora TC NO2 along ship track during SCOAPE cruise.....................................................21

Figure 24. Time series of TROPOMI, Pandora, and in situ NO2 during SCOAPE cruise......................... 22

Figure 25. Time series of Pandora and in situ NO2 on 15 May and along-track Pandora maps............... 22

Figure 26. Satellites vs. Pandora 66 TC NO2 on the R/V Point Sur during the period 10-18 May 2019. .. 24
iii

List of Tables

Table 1. Offshore instrumentation on R/V Point Sur during SCOAPE cruise........................................... 16

Table 2. Onshore instrumentation during SCOAPE cruise. ....................................................................16

Table 3. Extreme AQ conditions on 16 May near shallow-water platform, 28.9795°, -91.4760°............... 20
iv

List of Abbreviations and Acronyms

Acronym/Name Phrase/Description

Chemical Species

CH4

CO 

CO2

HCHO 

NO2

NOx

O3

SO2

VOC

Methane

Carbon Monoxide

Carbon Dioxide

Formaldehyde, a VOC

Nitrogen Dioxide

Nitrogen Oxides (NOx = NO + NO2)

Ozone

Sulfur Dioxide

Volatile Organic Compound

Instruments

MODIS 

OMI 

PSI

TEMPO 

TROPOMI 

VIIRS 

MODerate resolution Imaging Spectrometer

Ozone Monitoring Instrument

Pandora Spectrometer Instrument

Tropospheric Emissions: Monitoring of Pollution

TROPOspheric Monitoring Instrument [ESA]

Visible Infrared Imaging Radiometer Suite

Agencies/Programs

BOEM 

EPA 

ESA 

HAQAST 

KNMI

NASA

NIST

NOAA

Bureau of Ocean Energy Management

Environmental Protection Agency 

European Space Agency

NASA Health and Air Quality Applied Sciences Team

Royal Dutch Meteorological Office

National Aeronautics and Space Administration

National Institute of Standards and Technology

National Oceanic and Atmospheric Administration

Other

AQ 

AQS

CBBT

CEMS 

CONUS 

CS

GoM 

HDA

HMI

KORUS-AQ/OC 

LaRC

LOOP

LUMCON

OCS

ONG 

OWLETS 

SCOAPE 

TC NO2

TropC NO2

VCD

Air Quality

U.S. Air Quality System

Chesapeake Bay Bridge Tunnel

Continuous Emission Monitoring System

CONtinental United States

Case study

Gulf of Mexico

heavy density area

Hart Miller Island

Korea-U.S. Air Quality/Ocean Color campaign

Langley Research Center

Louisiana Offshore Oil Port

Louisiana Universities Marine Consortium

Outer Continental Shelf

Oil and Natural Gas

Ozone Water–Land Environmental Transition Study

Satellite Coastal & Oceanic Atmospheric Pollution Experiment

Total Column NO2 = atmospheric column

Tropospheric Column NO2 = tropospheric column

Vertical Column Density = the total number of molecules between the 

satellite and Earth’s surface per unit area, such as molecules/cm2.
1

1 Introduction

1.1 Background

The Outer Continental Shelf Lands Act (OCSLA) requires the Bureau of Ocean Energy 

Management (BOEM) to ensure compliance with the National Ambient Air Quality Standards

(NAAQS) so that Outer Continental Shelf (OCS) oil and gas exploration, development, and 

production do not significantly impact the air quality (AQ) of any state. In July 2015, BOEM 

personnel first approached the National Aeronautics and Space Administration (NASA) to 

inquire if satellite data could be used to help monitor offshore AQ in BOEM’s jurisdiction, that 

portion of the OCS west of 87°30’ West longitude in the Gulf of Mexico (GoM) Region and the 

Chukchi and Beaufort Sea Planning Areas in the Alaska Region. An interagency agreement was

signed in 2017 to begin a feasibility study on the use of NASA and related satellite data for 

BOEM’s requirements. 

The feasibility study consists of two parts. First is a review of satellite observations that can be 

applied to BOEM’s needs, including capacity-building tools and case studies, as described in 

Duncan (2020). This document reports on the second part of the feasibility study: the design 

and execution of a field campaign for validation of satellite NO2 columns and evaluation of 

surface instrumentation that will be useful to BOEM as it moves forward with satellite 

measurements aimed at quantifying the impacts of oil and gas (ONG) activity on coastal AQ. 

The field effort, designated as the Satellite Coastal and Oceanic Atmospheric Pollution 

Experiment (SCOAPE), was carried out in May 2019. This report begins with a review of coastal 

field experiments in 2016–2018 that are related to SCOAPE (Section 2), followed by a 

summary of findings from the SCOAPE oceanographic cruise (Section 3).

1.2 Remote Sensing of NO2 for BOEM’s Requirements

The first part of this study, as reported in Duncan (2020), reviews the basic principles of satellite 

detection of pollution and lists several atmospheric constituents of relevance to BOEM’s AQ 

requirements that NASA and other organizations monitor from space. Chief among these is the 

important ozone precursor nitrogen dioxide (NO2) that has been observed by satellite since 

1995 (Burrows et al., 1999). Over polluted regions of the globe, nearly all the total column (TC) 

of NO2 resides in the troposphere so satellite observations represent an ideal method for 

measuring NO2 emissions. Considerable effort has been put into algorithm development, 

validation and applications (Lamsal et al., 2008; Duncan et al., 2014; Lamsal et al., 2015; deFoy 

et al., 2016; Krotkov et al., 2017) for tracking pollution NO2, especially related to the DutchFinnish OMI instrument on NASA’s Aura satellite that has been in orbit for 16 years (Levelt et 

al., 2018). Since late 2017, ESA has flown the TROPOMI instrument that is now being heavily 

used for AQ applications, for example, recording reduced NO2 during the COVID-19 pandemic 

(Bauwens et al., 2020). Because oil and gas activity, both direct emissions from platforms 

(Wilson et al., 2017; Wilson et al., 2019) and from associated transportation, emit NO2, NO2 is 

the atmospheric constituent of focus for this report. (The primary product of combustion, of 

course, is NO, which is in chemical equilibrium with NO2; together NO + NO2 = NOx; the latter 

parameter is what BOEM and most Agencies use for emission inventories). Remote-sensing

instruments measure and report NO2 in column amounts of number of molecules called Dobson 

Units (1 DU = 2.69 x1016 cm-2

).
2

Both Ozone Monitoring Instrument (OMI) and TROPOspheric Monitoring Instrument

(TROPOMI) data are included in this report. OMI has a more mature and time-tested algorithm 

and is used to compare current views of NO2 pollution with the past, e.g., Figure 3 in Duncan 

(2020); Duncan et al. (2016); McLinden et al. (2016). TROPOMI has higher resolution, which 

will be shown to give superior views (Section 2) but is less well-developed for some 

applications. 

Evaluation of satellite NO2 columns is typically done with ground-based instruments such as 

MAX-DOAS (Piters et al., 2012) or aircraft versions of the ground instruments or other sensors 

meant to simulate the satellite (Lamsal et al., 2017; Nowlan et al., 2018; Judd et al., 2019). A 

relatively recent addition to the constellation of ground-based instruments is the Pandora 

spectrometer (or PSI, Pandora Spectrometer Instrument) that was developed about 15 years 

ago by scientists working at NASA/Goddard Space Flight Center (Herman et al., 2009). The PSI 

has been deployed in several coastal AQ investigations (Reed et al., 2013; Tzortziou et al., 

2015; Martins et al., 2016; Kollonige et al., 2018). A major series of hardware and software 

upgrades was being made to the PSI as the joint NASA-BOEM research study was beginning in 

2017. Thus, at NASA we viewed a GoM study as an ideal opportunity to evaluate OMI and 

TROPOMI NO2 products for BOEM and to further optimize the Pandora instrument for coastal 

applications.

2 Findings from Previous Field Campaigns

The relationship of satellite TC NO2 and TropC (tropospheric column) NO2 to surface NO2 can 

be complex. Thus, there is a need for independent verification of the satellite column amount 

and parallel measurement of surface NO2. Among a number of ground-based spectrometric 

approaches to TC NO2 is the Pandora instrument (Knepp et al., 2015; Reed et al., 2015; Martins 

et al., 2016; Kollonige et al., 2018). In this section, we present new analysis of data collected 

during recent (2016–2018) coastal field campaigns. Both satellite and spectrometric NO2 are 

assessed in terms of capability for monitoring AQ over open water and coastal environments.

2.1 South Korean Coastal Pollution Study: KORUS-OC 2016

Overall, the atmospheric-related goals of the joint venture between NASA and the Korean

Institute of Ocean Science and Technology (KIOST), KORUS-OC (Korea-United States Ocean 

Color), were to (1) characterize dynamics in surface air pollution and the variability of TC

measurements of gases over the South Korean coastal environment, (2) determine onshoreoffshore gradients in the region, and (3) link in situ and remotely sensed land and water 

observations to understand both the spatial and temporal variability of trace gas distributions. 

Essentially, these goals are similar to those of SCOAPE, but for a different region. 

Here, we analyze a set of surface and TC NO2 observations aboard the R/V Onnuri that 

operated from May–June 2016 to investigate coastal and offshore AQ near South Korea 

(Tzortziou et al., 2018; Thompson et al., 2019). Figure 1 shows the R/V Onnuri ship track as it 

sailed on the East and Yellow Seas along the South Korean coast from 20 May 2016 to 5 June 

2016. Data gaps in territorial waters are depicted as missing segments of the track. A temporary 

malfunction of OMI operation precluded comparisons between OMI and Pandora after 29 May 

2016, so statistics on satellite-spectrometer comparisons in Tzortziou et al. (2018) are 

somewhat limited. Thompson et al. (2019) focused on Pandora TC NO2 comparisons with in situ 

NO2 measurements on the R/V Onnuri to investigate factors influencing the relationship (good 

or poor correlations) between the Pandora (“PSI” in Figure 2) columns and shipboard NO2
3

measurements. Figure 2a is the time series of in situ and Pandora TC NO2, taken along the R/V 

Onnuri track. Coincident surface NO2 and PSI TC NO2 measurements presented as a 

scatterplot with linear least squares best-fit lines for Case Studies 1 (red), 2 (black), and 3 

(cyan), appear in Figure 2b.

Figure 1. KORUS-OC case study map.

Color scale by date; case study regions marked by arrows. Source: Thompson et al. (2019).

Figure 2. KORUS-OC in situ and Pandora TC NO2 on the R/V Onnuri.

Case studies (CS) marked. Source: Thompson et al. (2019).

The relationship between surface AQ and shipboard TC NO2 observations over open water 

varied considerably throughout KORUS-OC as indicated in the three case studies (Figure 2). 

Observations from Case Study 1 (CS 1, 26 May 2016, in Figure 2) took place as the ship sailed 

toward the city of Pohang on the East Sea. In the presence of a well-mixed boundary layer in a 

coastal environment, Pandora (PSI) observes near-surface pollution with a good correlation 
4

between TC and near-surface NO2 (r=0.73, red stars in Figure 2b). (Note that all observations 

except those recorded during the three case studies appear in light gray in Figure 2b). Under 

certain lower atmospheric conditions (i.e., one or more stable layers), the vertical distribution of 

NO2 can vary sharply with height throughout the column and limit the satellite and/or PSI’s

capacity for detecting near-surface NO2. Stable-layer conditions prevailed in the other cases

(Figure 2b) and consequently there is poor correlation: CS 2, 30 May 2016; black symbols; CS 

3, 1 June 2016, in cyan.

⇒ Relevance to BOEM: Overall, conclusions from the KORUS-OC South Korea coastal study:

(1) Near-surface meteorology and transport can affect comparisons between TC NO2

observations and near-surface NO2 measurements over coastal and open waters,

(2) Agreement between column and in situ NO2 depends on atmospheric stability near 

surface (i.e., stable layers affecting the vertical distribution of trace gases), and 

(3) A well-mixed lower atmosphere with local pollution shows the best correlation between 

the surface Pandora column and in situ NO2 observations in coastal waters.

In the next section, results are presented from a campaign similar to KORUS-OC but conducted 

with a suite of measurements called the Ozone Water–Land Environmental Transition Study 

(OWLETS). OWLETS focused on land-water ozone and ozone precursor gradients along the 

U.S. Mid-Atlantic coast and the Chesapeake Bay region.

2.2 Mid-Atlantic and Chesapeake Bay Ozone Study: OWLETS 2017

Past investigations into understanding poor AQ and pollution events at land-water interfaces in 

the U.S., particularly near major urban centers, include the Lake Michigan Ozone Study (LMOS) 

in 1991 (Dye et al., 1995) and 2017 (https://www-air.larc.nasa.gov/missions/lmos/), Texas Air 

Quality Study (TexAQS) in 2000 (Daum et al., 2003), TexAQS/GOMACCS in 2006, and Great 

Salt Lake City Ozone Study in 2015 (Blaylock et al., 2017). Within each of these land-water

investigations, and especially within the Chesapeake Bay, differences in emissions, mesoscale 

meteorology, cloud coverage, and aqueous deposition rates compared to nearby continental 

land masses drive gradients in ozone and other pollutants (Goldberg et al., 2014). 

In addition to typical mobile sources (e.g., automobiles and other transport vehicles) and point 

sources (e.g., power plants), the air pollution of the Chesapeake Bay is complicated by

recreational marine and large ship-produced emissions (Ring et al., 2018). OWLETS was a twopart campaign focused on the complexity of the water–land transition in the Chesapeake Bay

during two summer periods:

(1) In 2017 in the Tidewater Virginia area with two "super-site" locations at NASA 

Langley Research Center (LaRC) and Chesapeake Bay Bridge Tunnel (CBBT) Third 

Island site (Figure 3)

(2) In 2018 in the Baltimore Harbor region with the University of Maryland Baltimore 

County (UMBC) campus and Hart Miller Island (HMI) as "super-sites"

During OWLETS 2017, LaRC and CBBT were the "over-land" and "over-water" locations, 

respectively, following a similar setup as the Chemistry And Physics of the Atmospheric 

Boundary Layer Experiment (CAPABLE; Martins et al., 2012; Knepp et al., 2015). These supersites integrated a combination of remote sensors, including ozone lidars and Pandoras, with
5

surface and balloon-borne instrumentation. To better characterize the fundamental processes at 

the water–land interface and pollutants gradients, ongoing investigations use observations at 

the super-sites along with mobile (airborne, ship-based, and vehicular) observations connecting 

the two sites (Sullivan et al., 2018). Note, for example, the elevated ozone (Figure 3a) and NO2

(Figure 3b) as measured from a coastal research vessel operated by SERC, the Smithsonian 

Environmental Research Center. The Bay sampling illustrates the complexity of emissions and 

their interaction with the complicated Chesapeake coastline (cf. Stauffer et al. 2012; Stauffer 

and Thompson, 2013).

Figure 3. OWLETS 2017 map of the primary ground sites.

Primary ground sites marked in green stars: NASA LaRC and CBBT. Ship data marked in colors; see key.

Our OWLETS 2017 analysis focuses on the differences in TC NO2 measured by Pandora and 

OMI (satellite-based) over the "land" and "water" locations. Over 20 days of OWLETS 

observations, there were 11 and 17 coincidences between OMI and Pandora for LaRC and 

CBBT, respectively. Of these comparisons, each site had 11 total instances where percent 

differences were greater than 10% between OMI and Pandora. A histogram of the percent 

differences between the two instruments over both sites (Figure 4) demonstrates that the "overwater" site, CBBT (in green), is shifted to the left with better OMI-Pandora agreement than at 

LaRC and with a mean difference of ∼15%. At LaRC (in blue), with readings during cloud cover 

> 30% excluded, the "over-land" percent satellite-PSI offsets range from 10% to > 50% with a 

mean of ∼30%. This result is not surprising. Other studies of OMI-Pandora comparisons in the 

Chesapeake Bay region have shown that in more polluted areas on land there are larger offsets 

between the satellite and ground-based instruments (Flynn et al., 2014; Reed et al., 2015; 

Tzortziou et al., 2015). The main reasons: (1) differences in OMI vs Pandora field of view (i.e., 

whether Pandora “represents” the same air as OMI samples); (2) due to its relatively coarse 

horizontal resolution, OMI column TC NO2 readings are usually lower than those of Pandora.
6

Figure 4. Histogram of OWLETS 2017 OMI-PSI % differences for LaRC (Pan 37) and CBBT (Pan 19).

Mean percent differences on the figure do not include days with greater than 30% cloud fraction when offsets ranged 

near 50–75%.

⇒ Relevance to BOEM: Analyses of OMI and Pandora data at LaRC and CBBT pointed to four 

factors influencing the column NO2 comparisons. These factors, listed in order of importance 

based on frequency during the OWLETS 2017 time period, are the following:

1) Cloud cover,

2) Satellite pixel size and/or location with respect to the ground site,

3) Mixing height versus boundary layer height differences, and

4) A combination of cloud cover and satellite pixel size/location.

The OMI Cloud Fraction product was used to determine cloud influence during each OMI-PSI 

coincidence. Cloud cover alone affected only ∼20% of the comparisons at both CBBT and 

LaRC. However, cloud cover appeared to have a larger impact on LaRC, causing OMI-PSI 

differences as large as 70% or more. However, in 55% of the CBBT comparisons (36% for 

LaRC), the size of the OMI pixel and/or the location of that pixel with respect to the ground site 

(and/or the Pandora Field of View [FOV]) is the dominant factor contributing to larger percent 

differences between the two instruments. When high cloud cover is also a factor that degrades 

agreement, 64% of the comparisons at both sites also had large OMI-PSI differences. Figure 5

shows an example of OMI "good" (on 18 July) and "bad" (on 24 July) pixel size location with 

respect to the CBBT ground site. On 24 July, the OMI pixel size was three times larger than its 

nominal horizontal resolution at nadir (13x24 km2

); this can happen at the edges of the satellite 

instrument swath. The difference between OMI and Pandora on July 24 was ∼40%, the largest 

single offset observed at CBBT.
7

Figure 5. OWLETS 2017 OMI pixel size examples.

OMI smaller pixel size (left) leads to closer OMI-Pandora TC NO2 agreement at LaRC and CBBT than for larger OMI 

pixel size (right, 24 July 2017).

From these results, we conclude that the magnitude of OMI-Pandora disagreements for the 

OWLETS 2017 Tidewater region is most sensitive to

(1) Geographical complexity of the Chesapeake Bay land-water interface

(2) OMI-PSI coincidences, with best agreement when the super-sites are closely aligned 

with nearly overhead satellite

⇒ Things to Know: Based on the findings above, we assume that with the higher spatial 

resolution satellite data provided by TROPOMI NO2 in 2018, there is better potential for good 

satellite-PSI agreement than was possible for OMI in 2017. Figure 6 presents an image of 

TropC NO2 over the OWLETS 2017 LaRC and CBBT sites taken by TROPOMI during summer 

2018 (9 July). As expected, the retrieval problems inherent in OMI, i.e., large pixel size (Figure 

5), are less serious for TROPOMI than for OMI. Furthermore, TROPOMI discriminates NO2

differences between land and water. In Figure 6, values of TropC NO2 near CBBT are lower 

(mostly blue pixels in the area) than over land, where, for example, TropC NO2 near LaRC is 

higher (mostly green in the area) than over the nearby Bay. The polluted Norfolk region (orangered colors for TropC NO2), southwest of CBBT, is also distinct from the super-sites.

⇒ Relevance to BOEM: Higher spatial resolution observations from TROPOMI demonstrate a 

distinct land-water gradient in TC NO2 in the Tidewater area that was not well-resolved by OMI 

during OWLETS 2017. For the GoM Region, it was expected that the complications in trying to 

validate satellite column NO2 that were encountered during OWLETS 2017 would be reduced by 

having access to TROPOMI NO2 data during the 2019 SCOAPE cruise. However, based on our 

OWLETS 2017 and KORUS-OC results, high amounts of cloud cover and various properties of 

the marine mixed layer over water could still complicate surface and TROPOMI TC NO2

comparisons.

The next section focuses on preliminary evaluations of Pandora, OMI, and TROPOMI during 

OWLETS 2018 in the northern Chesapeake Bay area and the Baltimore Harbor region.
8

Figure 6. Map of TROPOMI TropC NO2 over LaRC and CBBT on 9 July 2018. 

Compare this to 2017 OMI views in Figure 5.

2.3 Baltimore Harbor and Chesapeake Bay Pollution Study: OWLETS 

2018

OWLETS 2017 was designed to investigate ozone and other pollutant behavior in the lower 

Chesapeake Bay. OWLETS 2018 (Sullivan et al., 2020) was a follow-on study to better 

understand behavior of ozone and related trace gases across the water–land transition zone in 

the upper Chesapeake Bay near Baltimore, Maryland. Two “super-sites,” located at UMBC on 

the west side of Baltimore and at HMI to the east side in the Bay, served as collection points to 

obtain data simultaneously over land and water from June 6 to July 6, 2018. Instrumentation

included two ozone lidar systems, Pandora Spectrometer Instruments, multiple wind and 

aerosol lidars, ozonesondes, research aircraft, and a suite of standard AQ measurements at 

other locations (Figure 7), some of which are State of Maryland monitoring sites.

With the newly available TROPOMI data, OWLETS 2018 facilitated the first comparisons of 

TROPOMI/OMI/Pandora TC NO2 over an urban and coastal environment during summer. Our 

comparisons include the two super-site locations, UMBC and HMI, as well as measurements 

from NASA Goddard Space Flight Center (GSFC) illustrated in Figure 7 where sampling 

extended from June to August 2018. Clearly, TROPOMI is more effective than OMI at capturing 

localized pollution sources and gradients (example: a distinct NO2 gradient between Baltimore 

and Washington, D.C. on July 9, 2018 in Figure 8). This is because only 1–2 OMI pixels 

covered the three ground sites with OMI (left side of Figure 8) compared to the multitude of 

TROPOMI pixels over HMI, UMBC, and GSFC (right side of Figure 8).
9

Figure 7. Map of OWLETS-2 (2018) “super-sites”.

Super-sites circled in red; Pandora Spectrometer Instruments also operated at GSFC and Beltsville.

Figure 8. OMI (left) and TROPOMI (right) TC NO2 images in OWLETS 2018, 9 July 2018.

We find that OMI and Pandora have little to no correlation in their TC NO2 observations at the

three marked sites (left panel of Figure 9), with mean differences at GSFC ∼20% and at UMBC 

∼50% (left panel of Figure 10). However, the mean difference between TROPOMI and Pandora 

TC NO2 at GSFC is ∼9% (right panel, Figure 10) compared to a ∼20% OMI-Pandora 

discrepancy. For TROPOMI, the comparisons with Pandoras are much improved with 

correlations ∼0.7 and ∼0.8 at HMI and GSFC, respectively (Figure 9, right). These findings are 

consistent with early TROPOMI-Pandora correlations (Griffin et al., 2019) based on 

measurements taken at Fort McKay in the Canadian oil sands in Alberta, Canada.
10

Figure 9. OWLETS 2018 satellite vs. Pandora comparisons.

Satellite (y-axis) vs Pandora (PSI) TC NO2 comparisons for cloud fraction < 0.3. OMI (left), TROPOMI (right).

Figure 10. OWLETS 2018 satellite-PSI differences, based on same data as Figure 9.

A lower correlation and higher percent TROPOMI-Pandora TC NO2 differences observed at 

UMBC (relative to the other sites) was caused by Pandora capturing some highly polluted days 

where TROPOMI was biased low. More analysis is needed to further investigate this bias. 

Differences in the vertical distribution of NO2 (i.e., pollution closer to ground and to Pandora) 

among the ground sites may be significant. HMI is in the Bay and subject to complex flows (cf. 

bay-breeze influences characterized by Stauffer et al., 2012; Stauffer and Thompson, 2013); 

UMBC is generally the most frequently polluted of the three sites in terms of NO2. The pattern of 

satellite-Pandora offsets increasing in magnitude as the TC NO2 absolute values increase has 

been noted in other field campaigns, e.g., Herman et al. 2018; Herman et al., 2019.

⇒ Relevance to BOEM: Preliminary comparisons between TROPOMI and Pandora TC NO2

during OWLETS 2018, as in Griffin et al. (2019) over the Canadian oil sands, demonstrate the 
11

effectiveness of the higher-resolution TROPOMI in capturing localized pollution gradients

relative to OMI. This is what was expected for the SCOAPE cruise assuming GoM sampling 

would be relatively free of cloud contamination or a stratified lower atmosphere.

3 SCOAPE Cruise

3.1 Background: Emissions and Meteorological Conditions in Gulf of 

Mexico

Figure 11, with imagery from January 2019, illustrates the first promising satellite data obtained

over the GoM prior to the SCOAPE cruise. Figure 11a displays the TropC NO2 measured 

midday from TROPOMI. The black circles in the image are the locations of the 200 highestranked NOx emitting platforms based on BOEM’s 2014 inventory (Wilson et al., 2017). Regions 

of white are too cloudy for a retrieval. The GoM segment displayed here is clear as are the 

adjacent portions of Louisiana, Mississippi, and Alabama. The dominant high TropC NO2

features are seen over the industrial coastal regions, consisting of Baton Rouge, New Orleans, 

ports, and petrochemical operations. The red-outlined region over the GoM in Figure 11a is 

shown in expanded scale in Figure 11b. The NO2 pollution in this region is elevated above 

background, represented by very low TropC NO2 (~0.03 DU). The enhanced TropC NO2 is 

depicted by orange-red colors, 0.08–0.10 DU. Checking the locations of these features in 

Figure 11b—each pixel is ~7x3.5 km2

—reveals them to coincide with the large and closelypositioned platforms Allegheny, Brutus, and Genesis; elevated TropC NO2 is also observed 

farther east at the Mars and Olympus platforms. The presence of elevated NO2 in satellite 

imagery mostly signifies combustion, of which there are various sources on an operating 

platform: flaring and different types of engines. There are often ships stationed near large 

platforms that also emit NO2. There are natural and other anthropogenic NO2 sources, notably 

lightning (Pickering et al., 2016), agricultural fires, and soils; these are mostly, but not always,

observed over the continent, as shown in Section 3.2.

In Figure 11c, a different satellite, the Suomi-NPP VIIRS, with a white area at the location of 

Mars and Olympus, detects elevated temperature anomalies associated with flaring. The 

images displayed in Figure 11 were the first confirmation of the feasibility of using satellites to 

observe offshore pollution at the relatively fine-scale over the GoM regions of interest to BOEM.

The timing of the SCOAPE cruise was chosen to optimize viewing conditions favorable for 

observing scenes such as those in Figure 11. Winter was avoided due to weather, ship 

schedule limitations and reduced likelihood of pollution buildup offshore. Early to mid-spring was 

chosen for an expected prevalence of onshore flow, relatively low cloud cover, and avoidance of 

hurricanes that occur in the latter part of the pollution season. A plethora of weather-related 

satellite imagery and customized model output for AQ was available to the ship and onshore 

scientific complement (Section 3.2; see also Duncan, 2020). This meant, for example, that the

NASA AQ forecasts showed us ahead of time the contrasting regimes through which the R/V

Point Sur sampled (Figure 12). The CO forecast for 12 May 2019 depicts a sharp gradient 

between the eastern and western part of the nearshore GoM.
12

Figure 11. TROPOMI TropC NO2 and VIIRS observations pre-SCOAPE: 6 January 2019.

Example: (a) and (b): TropC NO2 (DU) on 6 January 2019. Black circles indicate the 200 most highly emitting 

platform operations according to BOEM’s 2014 inventory (Wilson et al., 2017). In (c) the image is from the SuomiNPP satellite on 6 January 2019. The VIIRS instrument operates in the thermal infrared; white regions are elevated 

thermal anomalies detected in its Day-Night Band. The red marker denotes a flaring signature near the 

Mars/Olympus complex. Copernicus Sentinel data processed by ESA (https://doi.org/10.5270/S5P-s4ljg54).

Figure 12. Two AQ regimes during SCOAPE: NASA surface CO forecast. 

CO forecast is for 12 May 2019 at 18Z (midday). 
13

At the location of the ship on 12 May, CO mixing ratios were 50–75 ppbv, which are very low,

almost tropical, marine values. To the west, in a region traversed by the ship a day or so later, 

CO mixing ratios were predicted to be 150–190 ppbv, more representative of onshore 

conditions in southern Louisiana. Indeed, all the atmospheric constituents sampled on the R/V

Point Sur reflected two distinct regimes over the nine days of the cruise (illustrated in Section

3.2). The contrast of the two regimes was captured very well by the TROPOMI TropC NO2

(Figure 13). Cloud cover precluded extensive retrievals over much of the GoM coast and GoM

itself on 13 May. However, what was observable displayed very low levels of TropC NO2

(Figure 13a); only a few pixels of elevated TropC NO2 (> 0.05) are seen over the New OrleansBaton Rouge areas. Two days later, extensive regions onshore and in the adjacent GoM 

register readings from 0.05 DU to greater than 0.09 DU in TropC NO2 (Figure 13b). Section 3.2

illustrates contrasts in a number of other pollutants under the influence of onshore and offshore 

air masses. The signature of changing AQ regimes is reflected in TC NO2 as measured by the 

shipboard Pandora instrument.

Figure 13. TROPOMI TropC NO2 daily observations of marine vs. continental air during SCOAPE.

TROPOMI TropC NO2 (DU) over SCOAPE cruise region on (a) 13 May 2019 and (b) 15 May 2019. White open 

circles are the locations of the top 500 NOx-emitting platforms from BOEM’s 2014 inventory (Wilson et al., 2017). The 

white solid line marks the R/V Point Sur cruise track. Source: Thompson et al. (2020).

3.2 Onshore and Offshore SCOAPE Instrumentation and Plan

There were two objectives in choosing instrumentation (Tables 1 and 2) for the SCOAPE

cruise. The first was to use newly designed Pandora spectrometer instruments (PSI) to groundtruth TC NO2. We planned to do this on the ship sampling around the GoM and at a reference 

near-coastal site in Cocodrie, LA, (29.26°, -90.66°) at the Louisiana Universities Marine 

Consortium (LUMCON) facility, the departure port for the R/V Point Sur. In addition, to test the 

precision of the new Pandora we deployed three instruments, Pandoras 66, 67 and 68, at 

LUMCON starting on 10 April and continuing for four weeks prior to the cruise (Figure 14). Two 

of the instruments remained at LUMCON during the cruise; the third one, Pandora 66, specially 

outfitted for operations on a rolling platform, was installed on the R/V Point Sur. At both 

LUMCON and on the R/V Point Sur, a standard NO2 analyzer was operated in order to examine 

the relationship between column and ambient (“nose-level”) NO2. At LUMCON, low-cost sensors 

(i.e., “NO2-sondes”; Sluis et al., 2010; Duncan, 2020) were operated and occasionally deployed 

at remote coastal sites when the R/V Point Sur was a few tens of km offshore (Table 2). During 
14

these coastal coincidences, whole-air samples were taken by flask sampling onshore and on 

the ship (Figure 15). The whole-air samples were collected in specially prepared flasks and 

analyzed by the D. R. Blake group (Blake et al., 1992) for a range of VOC (e.g., alkanes, 

alkenes, and aromatics), halogenated carbon species, CO, CH4, dimethylsulfide (a biogenic 

marine tracer), and others.

Figure 14. View of Pandora spectrometers deployed pre- and during cruise.

(Left) The three Pandora spectrometers (PSI) during the calibration and intercomparison period at LUMCON, 10 April 

through 7 May. On 8 May, the PSI #66 was moved to the bow of the R/V Point Sur (Right). Credits: R. M. Stauffer

Figure 15. Pictures of R/V Point Sur sampling and ONG operations during SCOAPE.

(Left) Canister sampling and Pandora on the R/V Point Sur. (Right) Heavy-Density Area platforms. Credits: A. M. 

Thompson.
15

Second, to characterize AQ over the GoM, a complement of standard analyzers for ozone, CO, 

CH4, and CO2 were chosen for continuous sampling on the R/V Point Sur (Table 1). The carbon 

species act as tracers for the air masses being sampled. Unfortunately, the shipboard CO 

instrument malfunctioned so CO readings were provided only through the whole-air samples; 

there were 27 of those total. Flask sampling on the R/V Point Sur was normally coordinated with 

a platform encounter. For large platforms, when a plume downwind was intercepted, as denoted 

by simultaneous NO2 and CO2 spikes, a flask was exposed. The platform was circled to get an 

upwind sample. For smaller operations closer to shore (marked Heavy Density Area, HDA) in 

Figure 16, right), plumes were more frequent and there was no contrast sampling. Several 

flasks were filled during a circling of the LOOP on 16/17 May. 

For meteorological information, the R/V Point Sur was instrumented with a standard set of 

temperature, wind speed/direction and humidity sensors. One-two radiosondes were launched 

each day on the R/V Point Sur from 11–18 May for vertical information on pressuretemperature-humidity, wind speed, and direction; these give detailed information on boundary

layer and tropopause characteristics. Ten ozonesondes were launched with the radiosondes; 

the ozone mixing ratios provide vertical information on pollution structure and stratospheric 

influences on tropospheric ozone. Continuous information on boundary layer characteristics 

came from one ceilometer at LUMCON and one on the R/V Point Sur (Tables 1 and 2). 

Figure 16. SCOAPE cruise R/V Point Sur track with onshore sampling locations. Gray 

indicates the track of the R/V Point Sur between 10 and 18 May 2019. Details given in text. 
16

Table 1. Offshore instrumentation on R/V Point Sur during SCOAPE cruise. 

Species Instrument Collaborator

NO2 (and calibrator) In situ NASA GSFC

Column NO2 Pandora (PSI) NASA GSFC (Swap*) 

O3 In situ

Ozonesondes NASA GSFC

Temperature, RH, etc. Met system R/V Point Sur

Aerosol (AOD) & O3 columns Microtops Columns NASA GSFC

VOCs (plus CO & CH4) In situ canisters UCI (Blake)

HCHO In situ (Aeris) NASA GSFC (Hanisco)

PBL height Ceilometer UMBC (Delgado)

Black carbon Aethalometer NIST (Conny)

CH4, CO2, H2O In situ (Picarro) GSFC (Kawa / Hanisco)

* Collaborators for loaned instruments in parentheses.

Table 2. Onshore instrumentation during SCOAPE cruise.

Species Instrument Collaborator

NO2 In situ analyzer NASA GSFC (Sullivan)

NO2 Mobile in situ (NO2 sonde) KNMI (Stein-Zweers/den Hoed)

Column NO2 Pandora NASA GSFC (Swap)

VOCs (plus CO & CH4) In situ canisters UCI (Blake)

PBL height Ceilometer U Houston (Flynn)

The cruise track for the R/V Point Sur, superimposed on a Google Earth Map, with major land 

and platform locations and color-coded NOx emissions (Wilson et al., 2019), is shown in Figure 

16. The R/V Point Sur departed LUMCON at midnight starting 10 May and headed east,

sampling in the region labeled HDA-East (Heavy Density Area East) before heading south and

southwest toward the deepwater platforms. The 10 May sampling was conducted by automated

instruments only; it was stormy, and seas were too rough for deck work. Clouds continued

through 12 and 13 May. The farthest south point was near the Atlantis platform; an excursion to

Brutus and back to Atlantis followed. Deepwater sampling concluded after a return to

Mars/Olympus, followed by the track east and north to Petronius. HDA-East was sampled again

along with the region near the entry to the Port of New Orleans (“Venice” on the map) followed

by LOOP and HDA-West before the return to LUMCON in the afternoon (local time) of 18 May.

3.2.1 Onshore Observations

Figure 17 and Figure 18 display comparisons of the three Pandora instruments inclusive of the 

pre-cruise period along with Pandoras 67 and 68 during the cruise period. Overpass 

comparisons for TROPOMI and OMI are also shown. Figure 17 presents the TC NO2 readings 

from all three Pandoras pre-cruise at LUMCON followed by the two LUMCON Pandoras during 

the cruise. TROPOMI overpass measurements (gold diamonds) with coincident TC NO2 are 

also illustrated. R-values for comparisons with TROPOMI appear in legends within Figures 17

and 18 and mean Pandora-TROPOMI TC NO2 offsets are displayed. The latter are 12–13%, 

with the Pandora measuring higher column amounts than the satellite. There is more scatter 

among the three PSI during a cloudy period before the cruise on 4 through 8 May 2019. The 

R-values for the TROPOMI TC NO2 relative to the Pandoras range from 0.69–0.85 (Figure 17).
17

Figure 17. Timeseries of Pandora and TROPOMI NO2 observations at LUMCON. 

TC NO2 as measured by Pandoras 66, 67, and 68 prior to the SCOAPE cruise, from 10 April through 8 May with

TROPOMI overpass readings in gold diamonds. After the Pandora 66 was installed on the R/V Point Sur; only

Pandoras 67 and 68 recorded TC NO2 at LUMCON. Source: D. E. Kollonige. 

Figure 18. Comparison of three co-located Pandora instruments at LUMCON. 

Time-matched data from Pandora 66 (blue squares) and 68 (red circles) referenced to Pandora 67 at LUMCON from

10 April–8 May 2019. Linear best-fit lines are blue and red respectively with 1:1 black line for reference. Source: D. E. 

Kollonige. 

The reproducibility of the three Pandora instruments during their 4-week test period at LUMCON 

(Figure 17) is illustrated by referencing Pandoras 66 and 68 to Pandora 67. Figure 18 shows

the comparability of the three co-located Pandoras during the LUMCON test period. Agreement

in terms of slope and offset of the best-fit lines, as shown in the box at lower right in Figure 18, 
18

is excellent for both Pandora 66 and 68 relative to Pandora 67. The R-factor is lower for 

Pandora 66 because, as the blue symbols show, the latter instrument is noisier than the other 

two. 

3.2.2 Offshore Observations: AQ Indicators on the SCOAPE Cruise

Examples of AQ forecasts and satellite products described in Section 2.5 illustrate the 

complexity of pollution detection and attribution in the GoM. For example, the 11 September 

2019 flare detected by VIIRS described by Duncan (2020) did not coincide with elevated NO2

from satellite as did the early January 2019 examples shown in Figure 11. The SCOAPE cruise 

encountered pollution from Mexican agricultural fires with some of the trace gases on 14 May 

influenced by fires upwind of the R/V Point Sur. The tagged fire sources (Figure 19) show that 

correctly interpreting satellite and in situ NO2 is not yet complete. Accurate NO2 source 

attribution will require examining tracers, e.g., VOC, isotopes of CH4 and meteorological 

parameters from the ship.

Figure 19. Imported pollution during the SCOAPE cruise on 14 May 2019. 

(a) and (b) Tracers of fire pollution from Mexican origin, denoted as CO-fires and CO-fossil fuel, respectively, from the

GEOS-CF model forecast for 14 May 2019; (c) MODIS images showing fire locations on 14 May 2019. Discriminating

pollution sources on 14 May will require further analysis of both data and model output.

Figure 20 displays confirming evidence for the complexity of AQ encountered by the R/V Point 

Sur. In addition to the fire pollution episode, there were two general meteorological regimes with 

distinct chemical compositions. Late on 13 May, there was an abrupt transition in wind direction

from mostly southerly and southwesterly directions to north/northeast (Figure 20a). Surface 

ozone increased from 20 ppbv or less to more than 40 ppbv, with a peak of 70 ppbv on 16–17 

May. Shipboard ozone concentrations over the course of cruise (Figure 20b) show that these 

high levels near the final days of the cruise occurred in the westernmost segment (red colors in 

Figure 20b). The lowest ozone values (in blue near the coast) were measured at the beginning 

of the cruise. The days of the cruise up to the wind shift (10–13 May) are referred to as having 

air of “marine” origins. After that the air is designated as “continental,” with the understanding 

that the air from Mexican fires is included in that label.

The contrast of the marine and continental air is evident in the CH4 and CO2 time series (Figure

20c). The tropical marine (unpolluted) air averages ~1.90 ppmv CH4 and is only occasionally 

punctuated by high-CH4 plumes. With the transition to continental air (dashed vertical line in

Figure 20c), the mean CH4 mixing ratio is ~2.00 ppmv, with several extended peaks close 

~2.05 ppmv. Many of the latter observations were made close to shore in the HDA regions near 

natural gas operations. The time series of CO2 (Figure 20c) is opposite of the other constituents 

shown in Figure 20. CO2 levels decreased under the influence of continental air in mid-spring 

due to greening up of vegetation with an uptake of CO2. In Figure 20d, the highest surface NO2
19

measurements are more prevalent near shore, but elevated NO2 measurements were also 

found between Brutus and Atlantis and southwest of Mars/Olympus.

Figure 20 R/V Point Sur trace gas time series (a, c) and along-track maps (b,d).

Concentrations of trace gases measured over the course of the SCOAPE cruise on the R/V Point Sur. (a) ozone and 

wind direction, the latter measured by the ship’s instrumentation; (b) ozone mixing ratio time series along the ship 

track, 9–18 May; (c) as (b) except for CH4 and CO2; (d) as (b) except for NO2. Source: R. M. Stauffer.

The ozone vertical structure (Figure 21) shows the complex nature of the ozone columns 

sampled during the cruise. During the “clean marine” phase the sharp ozone gradient seen at 

15 km on 12–14 May is typical of a tropopause in subtropical or tropical air. The low-ozone layer 

between 10 and 14 km may originate from convective redistribution of air from the surface to 

cloud-outflow level that occurs frequently in the tropics (Petropavlovskikh et al., 2010; 

Thompson et al., 2010; Thompson et al., 2012). The continental air in contrast, appears to have 

a tropopause closer to 10 km and ozone greater than 80 ppbv is pervasive above 3 km.

Figure 21. Ozonesonde profiles during SCOAPE.

Based on 0.25 km resolution data. Mixing ratios to 16 km are illustrated; layers with > 80 ppbv may signify 

stratospheric influence. Source: R. M. Stauffer. 
20

A snapshot of marine vs continental influences for CH4, CO, CO2, and dimethylsulfide (DMS)

concentrations, based on the 27 flask samples taken on the R/V Point Sur, appears in 

Figure 22. DMS is of marine biogenic origin; comparisons of species with continental biogenic 

origin (isoprene, α- and β-pinene) exhibit the opposite pattern, not shown. 

Figure 22. Summary of carbon-containing gases and DMS from R/V Point Sur flask samples.

Box and whisker panels for CH4, CO, CO2, and dimethylsulfide (DMS) before (left side of each panel) and after 14 

May (right side of each panel). Sample numbers indicated at the top of each panel. Red line denotes median values, 

blue box denotes 25th and 75th percentile, and whiskers (dashed bars) are 95th percentile. Source: R. M. Stauffer. 

As the examples in Figure 20–Figure 22 demonstrate, throughout the cruise, there is 

considerable variability in all the constituents measured. One of the more extreme examples 

was captured in a whole-air sample near a shallow-water platform at 1612 hr Central Daylight 

Time on 16 May. A CH4 spike to 16 ppmv was observed by the Picarro instrument. 

Concentrations of representative carbon-containing compounds in the flask exposed at that time 

appear in Table 3. The CH4 increase in the flask was a factor of ~3, signifying leaks from gas 

production. CO2 was nearly identical to the cruise flask mean. However, ethane, n-propane and 

benzene amounts were 75, 130, and 45 times higher, respectively, than their cruise averages.

Table 3. Extreme AQ conditions on 16 May near shallow-water platform, 28.9795°, -91.4760°.

VOC Can 

Species

Cruise 

Median

16 May 

Plume Can Notes

CH4 (ppmv) 1.96 5.71 Deepwater platforms flare this off

CO2 (ppmv) 415 418 No combustion, likely just leaky pipes

Ethane (ppbv) 2.1 145 C2H6; second largest component of fossil gas after CH4

Propane (ppbv) 0.7 90.1 C3H8; byproduct of fossil gas processing

n-Butane (ppbv) 0.3 29.9 C4H10; i-Butane had similar concentrations

Benzene (ppbv) 0.04 1.88 C6H6; known carcinogen

3.2.3 Satellite, Pandora and Surface NO2 Comparisons on the SCOAPE Cruise

Figure 23–Figure 25 illustrate NO2 variability during the SCOAPE cruise, with observations 

from Pandora 66, TROPOMI and the R/V Point Sur trace gas analyzer. In Figure 23 the entire 

ship track is shown with Pandora TC NO2 columns for segments before 15 May 2019 mostly 

below 0.18 DU. After 15 May Pandora 66 records several segments with higher TC NO2. These 

occurred near large platforms like Petronius as well as in extended regions within the natural 

gas platforms in HDA-East and West (orange to red in Figure 23). Overall, both TC NO2 and the 
21

in situ NO2 measurements along the cruise track follow the two-regime pattern of the other 

constituents described above (Figure 24). Both Pandora 66 TC NO2 and surface NO2 increase 

an average of 50% between the clean marine and continental regimes. The increase in 

TROPOMI TC NO2 is not as large. This is similar to the pattern observed in the OWLETS 

campaigns where, as pollution measured at the ground increased, the satellite appeared to be 

less sensitive to it (Figure 9). In other words, at higher TC NO2, the deviation of the satellite 

reading was further from the 1:1 line; that tendency also appears in Figure 26 for both OMI and 

TROPOMI comparisons.

Figure 23. Pandora TC NO2 along ship track during SCOAPE cruise. 

Blue squares mark the locations of platforms that fall into the category of the top 200 NOx emitters according to the

2014 BOEM inventory (Wilson et al., 2017). Black is the R/V Point Sur track from 10–18 May 2019. The cleaner air

portion of the cruise as described above, was sampled prior to 14 May, more polluted air masses after 14 May.

Source: D. E. Kollonige. 
22

Figure 24. Time series of TROPOMI, Pandora, and in situ NO2 during SCOAPE cruise. 

Pandora TC NO2 measurements and in situ data are 5-min averages. Source: Thompson et al. (2020).

Figure 25. Time series of Pandora and in situ NO2 on 15 May and along-track Pandora maps. 

Time series (a) of Pandora 66 (green dots), in situ (black) and TROPOMI (golden diamond) NO2 on 15 May 2019 at 

the R/V Point Sur. Maps of Pandora NO2 on (b) 15 May, (c) 13 May, and (d) 16 May provide reference for NO2

variability along the cruise track. Color bar scales vary to highlight the gradients and elevated NO2 observed while 

passing near platforms (marked as orange squares). White line is the R/V Point Sur ship track. Source: Thompson et 

al. (2020).
23

As described in pre-SCOAPE studies (Section 2) relating the satellite and/or Pandora column 

NO2 amounts to surface NO2 is not straightforward. Generally speaking, when the boundary 

layer is not well-mixed, i.e., NO2 may be trapped near the surface, or when much of the NO2 

column is an above-boundary layer residual or is advected from upwind, the column amount 

does not correspond to the surface (or shipboard) concentration. These discrepancies between 

in situ and column NO2 variability are evident in Figure 25a, which is a close-up of the 15 May 

2019 observations (in local time) during the SCOAPE cruise. Figure 24 shows 15 May to be the 

day with the greatest range in TC NO2 values. There is a slow increase in Pandora TC NO2

during the morning hours and a few spikes for 15 May (magenta highlights in Figure 25a), while 

surface NO2 remains well below 5 ppbv. A VOC canister sample, taken at the time of the 

second Pandora TC NO2 spike in the morning of 15 May (second magenta circle in Figure 25a), 

indicates n-butane and i-pentane are ~2–3 times higher than other cruise samples (second 

highest of the campaign; 16 May example is highest) while passing the Petronius platform. 

Note: Different processes emit different gases, and this is dependent on the platform’s current 

operation at the time of the ship’s measurements. Both species, n-butane and i-pentane, 

sometimes emitted during the flaring process, are indicators of platform activity.

Midday Pandora TC NO2 averages ~0.20 DU in the “continental air” (Figure 24), approximately 

30% higher than the TROPOMI overpass value. However, for 15 May (Figure 25a), the 

Pandora appears to not be sensitive to several pollution plumes (spikes up to > 40 ppbv surface 

NO2), one of which is in the vicinity of a large platform in the afternoon ~1,500 LT (first magenta 

arrow). N-butane and i-pentane are again ~2–3 times higher than other cruise samples, with the 

exception of the 16 May outlier. More analysis is needed to understand the surface-column NO2

relationships displayed in Figure 25a, but individual NO2 spikes are enhanced above the daily 

mean for both when passing platforms on 15 May. This example highlights the value and 

complexity of taking both surface and column NO2 measurements in AQ monitoring.

Figures 25b–d illustrate three other regions, summarizing the range of in situ NO2 readings with 

the coincident Pandora readings along the track. In these regions there is a wide range of 

surface NO2, up to 45–50 ppbv over the HDA regions near shore on 15–16 May and 5–20 ppbv 

during the leg between Atlantis and Brutus, 13 May (Figure 25b–d). There is considerable 

variation within each region with very low TC NO2 (dark blue) as well as levels > 0.20 DU. These 

episodes will be investigated in detail with tracers, ancillary satellite data, air parcel trajectories 

and, where possible, with model output.

A summary of overpass comparisons from OMI and TROPOMI TC NO2 relative to the shipboard 

Pandora 66 appears in Figure 26. Although the TROPOMI satellite instrument footprint is 

smaller than that of the OMI satellite, the offsets with Pandora 66 are nearly the same. Also, in 

both cases, as TC NO2 increases, the discrepancy between ground-based and satellite column 

amounts increases, with the Pandora usually greater. These comparisons are typical for the low 

to moderate amounts of pollution observed over and near the GoM (see, for example, Herman 

et al., 2018; 2019).
24

Figure 26. Satellites vs. Pandora 66 TC NO2 on the R/V Point Sur during the period 10-18 May 2019. 

OMI (blue circles) and TROPOMI (gold diamonds) are on y-axis versus Pandora 66 on x-axis. Black line is 1:1 line.
25

4 Summary of SCOAPE Cruise Analysis and Recommendations

SCOAPE set out to answer three important questions for BOEM, and summary answers are as 

follows: 

• Can satellite observations detect emissions from ONG operations, and are the

measurements accurate? Using NO2 as our “Air Quality Proxy,” we find, based on the

May 2019 SCOAPE cruise, that the operational OMI and TROPOMI satellites are able to

detect elevated NO2 associated with ONG operations. Referenced to both land- and

ship-based Pandoras, satellite TC NO2 was accurate to 11–18%, with the satellite biased

low at the higher pollution levels. More analysis of the R/V Point Sur PSI and in situ NO2

measurements using tracers (CH4, CO2, other VOC), trajectories, and models is required

to better establish uncertainties.

• How reliable are the Pandora instruments used for ground-based remote sensing?

During the cruise and four weeks of pre-cruise calibration in coastal Louisiana,

comparisons of TC NO2 readings from the new Pandora instruments showed ~5%

precision or better.

• How do pollutant levels measured by satellite over coastal Louisiana and the adjacent

GoM compare? From our 2019 sampling, pollution appears to be greater over the

continent than the GoM, although both in situ and Pandora measurements during the

cruise display prominent NO2 spikes near platform operations. A comprehensive answer

to this question requires continued monitoring of satellite NO2, as well as coastal

observations of NO2-related pollutants and tracers and models with accurate NO2

sources.

⇒ Recommendations to BOEM: Based on SCOAPE Results

1. BOEM and NASA should work together to analyze the 2019 SCOAPE data more

thoroughly, including conducting studies with tracers, ancillary satellite data, trajectories,

and appropriate chemical transport model output to more firmly establish the magnitude

of ONG influences on GoM AQ.

2. Coastal monitoring along the GoM with NASA and EPA using Pandora Spectrometer

Instruments and other instruments would establish better statistics and contribute to the

ongoing improvements in OMI (mature algorithm) and the still evolving TROPOMI. Colocation with BOEM’s coastal project, aiming to begin in late 2020 at a remote unpolluted

location in Louisiana would greatly benefit BOEM. Daily overpass comparisons of OMI

and TROPOMI TC NO2 with a Pandora instrument would give BOEM more complete

statistics than the 5-week exploratory dataset of April–May 2019. Comparisons of the in

situ and column NO2 amounts, along with other pollutants being measured, would further

our understanding of the relationship of chemical transformation and interactions with

dynamical processes in the boundary layer.

Neither satellite nor Pandora column amounts provide ambient concentrations of NO2. By using 

case studies, of which we have identified a number in the May 2019 SCOAPE dataset, we can 

establish statistics for the column-surface NO2 connection and establish environmental 

conditions under which the relationship is strongest. NASA will continue to conduct this type of 

analysis as it prepares for the 2022 launch of a geostationary ozone and NO2 satellite, TEMPO. 

TEMPO is designed for hour-to-hour pollution monitoring over North America and its coastal 

waters, including the GoM, Atlantic, and Pacific areas of emerging interest to BOEM. 
26

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