 regarding the "H-Classic Papers in Atomic Spectroscopy" article published in the November 2021 issue, along with a response from the authors.

I write in response to the paper by Muhammad Rahil Rafiq and Sadiq M. Sait, “H-Classic Papers in Atomic Spectroscopy: An Integrative Literature Review,” published in the November 2021 issue of 

 (1). Rafiq is an engineer and Sait is a professor, both in the Center for Communications and IT Research at King Fahd University of Petroleum and Minerals in Dhahran, Saudi Arabia.

The paper is intended to provide insights into the key papers and researchers that have influenced the field of analytical atomic spectroscopy. As someone who worked in the field of atomic spectroscopy as a graduate student, postdoctoral fellow, and university researcher for about 30 years (from 1976 to 2005), I was keen to read the review. Unfortunately, I was quite disappointed. The publication is badly flawed as a result of a lack of knowledge about the history, evolution, and current state of the field. The problem is that the authors are computer engineers with no real knowledge of atomic spectroscopy. This was purely an academic exercise.

For their study, the authors searched the Web of Science (WoS) in April 2020, using the search term 

 (referred to as a topic search, or “TS”). The search query resulted in 1214 articles. The small number of documents was the first indication that something was amiss. An author search for only two of the most well-known and cited researchers in analytical atomic spectroscopy, Gary Hieftje and Jim Winefordner, yields 615 and 746 articles, respectively, for a total of 1361 articles. The fact that the list that didn’t include Hieftje, only named Winefordner as 45th, and omitted hundreds of other “household names” who have contributed to the atomic spectroscopy literature, also raises concerns about the methodology. These omissions were obvious to me because I am quite familiar with the field of atomic spectroscopy.

The core problem with the methodology is that 

 is a blanket term that includes many subdisciplines, such as 

inductively coupled plasma–mass spectrometry (ICP-MS)

ICP-optical emission spectroscopy (ICP-OES)

laser-induced breakdown spectroscopy (LIBS)

. Other related techniques include laser-based atomic spectroscopy for inorganic analysis such as laser-enhanced ionization, coherent forward-scattering spectrometry (CFS), resonance-ionization spectroscopy and spectrometry, and X-ray fluorescence. In addition to these techniques, there are associated topics, such as sample introduction systems (such as nebulizers, spray chambers, and hydride generation), and data-analysis methods such as background correction and multivariate analysis. Scientists in the field also often use the term 

. Many authors identify the topic of their manuscript using the subdisciplines identified above rather than the blanket term 

, so a search using that phrase would miss many important and relevant publications.

To give some insight into the numbers of papers published in these subdisciplines, I have carried out a search in the WoS Core Collection for which “Science Citation Index–Expanded” is one of the indexed sources. I limited my search to the period 1968 to 2020, to match the search carried out in the paper under discussion. Table I below summarizes the results of this exercise. This search was no means exhaustive or comprehensive; it is presented simply to give some insight into the scope of papers published in atomic spectroscopy. The table shows that tens of thousands of atomic spectroscopy articles are missed in a search using only the search term 

The authors also presented a table with the caption “H-classic papers in atomic spectrometry with their available impact factors (JCR).” The highest cited article in the table received 503 citations and the lowest received 64. As a comparison, I searched for the number of citations for a sample set of 12 highly cited atomic spectroscopy papers published from 1968 to 2020. The purpose here is to give an indication of some of the papers and authors that could be considered “citation leaders,” but did not appear in the authors’ table. This information is presented in Table II below. The least cited of these papers received 398 citations. There are hundreds of papers that have received in excess of 200 citations.

As a small step toward setting the record straight, I would like to briefly name a few scientists who were innovators and leaders in analytical atomic spectroscopy over the past six decades—scientists who developed new instruments, methods, and applications, and defined and advanced the field: James D. Winefordner, Gary Hieftje, Chuni Chakrabarti, Ralph Sturgeon, Ramon Barnes, Paul Boumans, Leo de Galan, Klaus Dittrich, Michael Epstein, Jim Harnley, Heinz Falk, Wolfgang Frech, Keiichiro Fuwa, Jim Holcombe, Gordon Kirkbright, Alan Walsh, Boris L’vov, Gary Holick, Kay Nimax, Walter Slavin, Jose Broekaert, Igor Gornushkin. Detlef Gunther, Sam Houk, Velmer Fassel, Javier Laserna, Arne Bengtson, John Olesik, Vincenzo Palleschi, Rick Russo, Frank Vanhaecke, Benli Huang, Nicolo Omenetto, Margaretha de Loos-Vollebregt, Annemie Bogaerts, Norbert Jakubowski, R. Kenneth Marcus, Don Douglas, and Scott Tanner. These are just a few whose contributions to atomic spectroscopy have been seminal.

My concern is not only with the shortcomings of the specific search methodology used in the published study. Because even if the authors’ search had used all the relevant terms to capture the breadth of the field, there would still be important limitations to trying to understand the significance of papers and authors using metrics alone. Even “ideal” metrics generally fall short. For example, are the most-cited papers necessarily the seminal papers that open and develop new lines of research and instrument and techniques? I would argue no.

In this context, it would be useful to have a curated compilation of the key papers in analytical atomic spectroscopy. Fortunately, just such a compilation is being prepared, by George Chan, a research scientist in the Laser Technologies Group at Lawrence Berkeley National Laboratory; Gary Hieftje, a professor emeritus from the Department of Chemistry at Indiana University, and Nicoló Omeneto, a research professor in the Department of Chemistry at the University of Florida. Starting three years ago, they consulted a large group of established scientists in the field of atomic spectroscopy and asked for a list of important papers published over the past 50 years—on theory, historical developments, fundamental studies and characterization, instrumentation, spectrochemical techniques or tricks, common but often overlooked mistakes and experimental precautions, philosophy of spectrochemical analysis, and any other relevant topics. From those suggestions, the project leads (Chan, Hieftje, and Omenetto) will compile a curated list of all the papers suggested, the individuals who suggested them, the suggested key points, and any additional background information or anecdotes. The curated list will be published in the near future as a single review article. This paper is expected to be a definitive compilation of the most important, influential, and in some cases, most highly cited papers of the past half-century in the field of analytical atomic spectroscopy. As is required for such an endeavor, it will be assembled and curated by experts in analytical atomic spectroscopy.

To end, I applaud the authors of “H-Classic Papers in Atomic Spectroscopy: An Integrative Literature Review” for attempting to shine a spotlight on an important field of endeavor. However, I would ask that, if they are considering future efforts of this kind, they consult with established scientists and experts in the field to understand the full picture before publishing a similar review.

Michael W. Blades, Professor Emeritus 
Editor, Applied Spectroscopy 
Department of Chemistry 
The University of British Columbia 
Vancouver, BC, Canada

https://www.spectroscopyonline.com/view/h-classic-papers-in-atomic-spectroscopy-an-integrative-literature-review

Our paper, “H-Classic Papers in Atomic Spectroscopy: An Integrative Literature Review,” focuses only on a set of papers (data harvested in April 2020) for analysis or review that fit our criteria of “H-Classics.” The selection criteria are elaborated in Section 2.3 of the manuscript. Other details about the selection of document types, topics (ts) which include titles, abstract, keywords, and so forth, are also discussed in the manuscript.

The main concern raised by Dr. Blades and other readers regards papers missing from the data set produced by our search terms. The reason for this is that the keywords we used for our search string focused only on atomic spectroscopy. This approach led to excluding other keywords or terms such as atomic emission spectroscopy or atomic absorption spectroscopy and so forth. Therefore, we acknowledge that the scope of our data set is very limited (because of the search string).

We would like to follow up with some discussion of issues related to how to develop a search string that can yield much more comprehensive results.

As an example, if we would like to work on the literature of “cloud computing,” we might use a search query of “ts=cloud”. Such a search will also retrieve publications related to rain, storms, and precipitation, which are completely out of scope for the research domain we seek to cover. Therefore, content analysis and scrutiny is needed, related to the most significant (primary) keywords, in order to avoid bias. The expertise of subject-matter domain experts is required to screen results by manual exclusion/inclusion to exclude or include relevant and irrelevant data.

In Web of Sciences (WOS), truncation, also called 

, can be used, at the beginning, middle, or end of words or phrases, and also with their combinations. Three main symbols (*, $, and ?) are used, as follows:

The asterisk (*) is used for retrieving multiple characters. It also matches zeroes and non-spaced characters. It can be used to find relevant keywords for prefixes, suffixes, and spelling variations. For example, a search for 

The dollar symbol ($) is used for retrieving a single character with zero or one non-space character, variations, or plural forms. For example, a search for 

The question mark (?) is used to retrieve a single (or repeated) character. For example, a search for 

In addition to the above, the Boolean operators OR, AND, and NOT are also available.

With respect to the valuable comments from Dr. Blades, we completely agree with him that our query is by no means sufficient for an exhaustive or comprehensive search. We would like to gratefully acknowledge and thank him for his valuable insights, referring to more relevant keywords. However, including them in the search query still excludes many more papers related to atomic spectroscopy, examples of which are: photoacoustic spectroscopy, photoelectron spectroscopy, and photoemission spectroscopy. Therefore, the query given below could be used, followed by a manual scan which is essential, to have a more relevant set of papers on 

TS=”*Spectrosc*” or TS=”*Spectrome*”

This approach seems more likely to capture the major publications related to 

 to be adequately considered for a more comprehensive review. But, again, extracted data should be accessed by domain experts to ensure irrelevant documents are removed, and that all relevant documents have been captured—as Dr. Blades points out. That should lead to a more accurate coverage of the topic.

Lastly, considering the major limitation of any literature search, no precise query constitutes a comprehensive literature search in a broad discipline. Efforts can be made to draw a comprehensive picture with greater and essential representation of overall knowledge but still some documents might always be missing.

Perhaps, the above recommended query may not be the perfect one, but using more truncations and Boolean operators, to include and exclude more relevant keywords, will definitely help in better defining the scope of literature or data set.

Dr. Sadiq M. Sait and Muhammad Rahil Rafiq
Center for Communications and IT Research 
King Fahd University of Petroleum and Minerals 
Dhahran, Saudi Arabia

Articles

A letter to the editors of Spectroscopy regarding the "H-Classic Papers in Atomic Spectroscopy" article published in the November 2021 issue, along with a response from the authors.

Letters to the Editor: H-Classic Papers in Atomic Spectroscopy

A note from the editors of Spectroscopy regarding the "H-Classic Papers in Atomic Spectroscopy" article published in the November 2021 issue.

, we published a review paper titled “H-Classic Papers in Atomic Spectroscopy: An Integrative Literature Review” (1). This paper caused quite a bit of concern in the atomic spectroscopy community, and understandably so.

In the work, the authors, who are faculty in a computer science department at a university outside the United States, presented a list of 64 papers that fit, according to the research criteria, the definition of “H-Classic” papers—highly cited papers that made key contributions to the field. When expert members of the atomic spectroscopy community read the paper, however, they found that many seminal works by icons in the field were missing. Several wrote to us, and we have published one comprehensive letter in this issue, from Mike Blades (page 10), along with a response from the authors.

The problem, which everyone quickly realized, resulted from a combination of two factors. First, the results were based on the use of a very limited search term, atomic spectroscopy, and second, the authors are computer scientists who did not realize the gaps because of their lack of familiarity with field of atomic spectroscopy.

The authors searched the Web of Science (WoS) for the years from 1968 to 2015 using the search term atomic spectroscopy. Their query identified 1214 papers in English, which were then sorted in descending order based on their respective citation counts. The H-Index, for the available data set, was found to be 64, and correspondingly, the first 64 articles were classified as the highly cited papers based on the H-Classic definition.

As the experts who wrote to us pointed out, it is very uncommon, especially in the older literature, for papers in the field to use the phrase atomic spectroscopy in the title or abstract; they might refer instead to a term such as 

inductively coupled plasma–optical emission spectroscopy (ICP-OES)

Thus, the teachable moment. We can all easily imagine that any undergraduate student or skilled librarian could similarly misunderstand the essential keywords needed to identify a comprehensive set of critical papers in any given field. Something similar could happen in molecular spectroscopy if one used search terms like Raman spectroscopy, visible spectroscopy, or infrared spectroscopy. This situation serves as a reminder to all who conduct any sort of literature search and as valuable lesson to teach students. For this purpose, we have published a resource article on our website entitled, “Literature Searches: A Guide to Getting it Right”(2).

For our part, we also learned an important lesson. We recognize, as an editorial staff, that review articles like this one should be reviewed by experts in the specific field in question. To set the record straight, this paper was not reviewed by any members of our editorial advisory board (EAB). We pledge to seek this expertise in future general topic reviews. Given the volume of papers we are currently handling in peer review, and the range of subject areas addressed in them, which include specialized applications in areas like material science, physics, clinical applications, astrobiology, we will often need to reach beyond our EAB. But we will certainly seek the advice of truly expert reviewers, and will also invite our EAB to weigh in.

We thank those who wrote to us and spoke with us about this topic. We appreciate your passion for science and for getting things right, which we wholeheartedly embrace.

(2) J. Workman, “Literature Searches: A Guide to Getting it Right,” Spectroscopy; online only. 

https://www.spectroscopyonline.com/view/literature-searches-a-guide-to-getting-it-right

A Teachable Moment: “H-Classic Papers in Atomic Spectroscopy”

Confused from Quality Control (QC) writes, “Doctor, Doctor, give me the news! Originally, it was just ALCOA criteria for data integrity, then a plus was added, but now its ALCOA++. What should I do? Help me please!”

Well, Confused, the good news is that the doctor is in and can help you unravel the delights and joys of ALCOA and its two offspring. We will trace the terminology from its inception in the last century and follow its evolution through two iterations from the original five criteria to 10 with ALCOA++.

What do you mean you have never heard of ALCOA++? Tut, tut, you are not keeping up with your regular medication of regulatory guidance documents. You really must do better. As punishment write out 100 times, 

I must not use spreadsheets for GXP calculations

To manage the expectations of readers, the use of 

 in this column does not refer to the Aluminium Company of America. I realize the disappointment that this may cause to many but sometimes, as you probably know, life stinks.

How Can You Determine the Integrity of Data?

A problem in the current regulatory climate is how to determine the integrity of the data in a record. This issue is not only prominent in regulated laboratories, but in all laboratories because any decision made using analytical data needs the integrity to be assured (can you trust the data?) before a decision is made using the extracted information. What is needed is a set of criteria that can be applied to the records set to provide assurance that the integrity of the data is good. Enter the ALCOA criteria, which are the focus of this column.

The ALCOA story goes back to last century: Stan Wollen, who was an FDA Good Laboratory Practice (GLP) inspector, was involved in training fellow inspectors on new inspection techniques. He developed the acronym as a means of understanding and evaluating GLP study data for data quality and not data integrity. As aluminium kitchen foil made by the ALCOA company was widely available, he used ALCOA as the basis for the following five criteria that could be applied to any data set:

These criteria are outlined in a publication entitled, 

, and available for download online (3). Wollen makes the point that the individual elements of ALCOA were already present in existing Good Manufacturing Practice (GMP) and GLP regulations. What he did was organize them into an easily memorized acronym (4).

Plagiarism Is the Sincerest Form of Flattery

Fast forward to this century, and we find that Wollen’s ALCOA data quality criteria have been taken by various regulatory guidance documents and repurposed for use as a cornerstone of data integrity in regulatory guidance documents from the following agencies:

Medicines and Healthcare Products Regulatory Agency (MHRA) 2015 and 2018 (5,6)

World Health Organization (WHO), 2016 (7)

Food and Drug Administration (FDA), 2018 (8).

The data integrity definitions of the five ALCOA criteria are presented with some explanation in Table I and are shown in yellow in Figure 1. Please read both; they are free of charge. Note that the WHO guidance document includes both permanent and understandable under “legible” (7). This WHO guidance has the best discussion of ALCOA criteria in Appendix 1 (7), and it is essential reading for anyone involved with data integrity.

Unfortunately, the WHO 2016 guidance has been superseded by an inferior guideline in 2021 (9) of limited scope that has deleted the superb ALCOA appendix. This new guidance still uses ALCOA with the addition of “enduring,” which is shown later in Table IV. My advice is to ignore the new guidance and stay with the 2016 document (7).

The 2018 MHRA data integrity guidance mentions in section 3.10:

.... ALCOA was historically regarded as defining the attributes of data quality that are suitable for regulatory purposes. .... (6).

The origin of ALCOA was focused on data quality, but the same criteria can be applied to data integrity, given that the same data set is involved. Therefore, ALCOA attributes apply to both data quality and data integrity. The two terms were discussed in an earlier “Focus on Quality” column (11).

In 2010, the European Medicines Agency issued a guidance on electronic source data in clinical trials (12), where four additional criteria were added to make ALCOA+. These four criteria were:

The definitions are presented with some explanation in Table II and are shown in green in Figure 1. The 2021 Pharmaceutical Inspection Convention/Pharmaceutical Inspection Cooperation Scheme (PIC/S) data integrity guidance also uses the ALCOA+ criteria (13).

Official media must be used to record data to ensure that they are “enduring” (equivalent to “permanent” in the WHO guidance mentioned earlier). However, Table II and Figure 1 list some unacceptable and unofficial media including a laboratory coat sleeve or the occasional body part—just don’t even think about these alternatives. You don’t want to have a starring role in a regulatory citation like the individual who wrote GMP information on his hand in front of an inspector (14).

Adding Up Nicely the Tenth ALCOA++ Criterion

The tenth and latest ALCOA criterion is “traceable,” from a draft EMA guidance on computerized systems and electronic data in clinical trials (15). The definition and meaning are presented in Table III and shown in purple in Figure 1.

There is a debate about whether a new criterion is necessary. You will notice in Tables I and II that there are references to Table III, which means that traceability is implied in the existing ALCOA+ criteria.

However, from an inspector’s or auditor’s perspective, any process or system should be able to show what has happened from data acquisition to generation of the reportable result. I also want to be able to do the same in reverse, from the result to the acquisition. Ideally, any system or process should facilitate this easily and be self-evident, including documenting any problems that occurred and their resolution.

Many would argue that the criterion “traceable” is implicit in ALCOA and ALCOA+. However, the implication of the term is the problem; it is always better in data regulatory guidance to be explicit. For example, consider the definition of raw data in the United States and Organization for Economic Cooperation and Development (OECD) GLP (4,16). There is the need to be able to reconstruct the study report from the original observations and activities, which is an explicit requirement for traceability. My argument is that if something is implied, then it may not be recognized as a necessity and not acted upon.

The next question is whether we need to change the name of ALCOA+ to ALCOA++. From a personal perspective, ALCOA++ is unwieldy and 10 ALCOA+ terms would be acceptable for me. However, others are just as content to leave ALCOA+ as nine terms with traceability implied. From the cross references between the three tables in the column, you can see that traceability is implicit already in ALCOA+.

However, there is more to traceability and we need to explore the full impact of this criterion because it is essential for the interactions between the other ALCOA criteria as presented in Figure 3. Each ALCOA criterion does not exist on its own in a silo but interacts with other criteria.

The center of Figure 3 depicts an analytical process in green from sample preparation to the analysis report and represents the “what” of what must be done.

At the top, two analysts performed the work and are the “who”: there is one analyst for the sample preparation and a second analyst for the analysis. Note that no second person review is shown. A common audit technique is to select an individual who performed a task and trace back to his or her training records and job description to ensure that the person had the combination of education, training, and experience to do the work at the time it was done.

The process flow shows the individual tasks that represent the “how,” and display how the analytical procedure is performed and the end result that is achieved. Traceability runs throughout the entire process to ensure that you have used the right instrument, glassware, instrument method, operating parameters, and so forth.

Data entered into a computerized system (batch and sample number, weights, and so on) must be traceable to the external source records outside of it.

Any changes to the data or metadata must have corresponding audit trail entries that trace the changes and the reasons for them.

The use of calibrated mass sets,reference standards, and calibration standards all require further traceability to calibration certificates or certificates of analysis.

Glassware needs to be identified and recorded in case of investigations. Recently, quick response (QR)–coded volumetric glassware has been introduced so that each flask or pipette is uniquely identified; this information can be set up in an informatics application. When any glassware is used, the code is scanned so that any items used are recorded automatically. However, in any automated process, there must be the ability to allow an analyst to record any issues in free text if a problem is found, which is important in complying with the “Analyst Responsibilities in the FDA Out of Specification” guidance (17) in case an activity has to be repeated because of a mistake.

To ensure reliable time and date stamps, a computerized system should be linked to the network with a time server that is synchronized to an external trusted time source, such as a network time protocol (NTP) server or a national legal time source.

Traceability ensures trusted and reliable records and activities that in turn ensure integrity of data and the whole record set. Therefore, you can see why traceability, an implied requirement of ALCOA and ALCOA+, is an important addition.

Mapping all ALCOA Criteria Across Regulatory Guidance Documents

To complete our discussion, Table IV maps all 10 ALCOA criteria to the respective GMP regulatory guidance documents for data integrity available at the start of 2022. As can be seen, the PIC/S (13) and two EMA GCP guidance documents (12,15) are the guidances with ALCOA+ and ALCOA++ criteria. However, reiterating my advice earlier, Appendix 1 of the WHO guidance (7) is still the must-read section to have an in-depth understanding of ALCOA, supplemented with PIC/S PI-041 (13) and the latest EMA (15) guidances for ALCOA+ and ALCOA++ criteria, respectively.

The criteria for data integrity continue to evolve, and the proposed criterion of traceability appears to be the dark matter that holds the remaining ALCOA+ criteria together. However, it is traceability that shows that each ALCOA criterion does not exist in a silo, but that they all interact with and are dependent upon each other.

I would like to thank Ulrich Köllisch and Chris Burgess for their input into the review of Figure 1. Figure 2 and the encompassing role of traceability in ensuring data integrity were developed during discussions with Chris Burgess. I would also like to thank Yves Samson, Peter Baker, and Chris Burgess for providing excellent review comments during the preparation of this paper.

(3) S.W. Wollen, Data Quality and the Origin of ALCOA in 

The Compass Summer 2010, Newsletter of the Southern Regional Chapter, Society of Quality Assurance

 (2010). Available from: http://www.southernsqa.org/newsletters/Summer10.DataQuality.pdf

 58 Good Laboratory Practice for Non-Clinical Laboratory Studies (Food and Drug Administration: Washington, DC, 1978). 

GMP Data Integrity Definitions and Guidance for Industry 2nd Edition

 (Medicines and Healthcare Products Regulatory Agency: London, United Kingdom, 2015).

GXP Data Integrity Guidance and Definitions

 (Medicines and Healthcare Products Regulatory Agency, London, United Kingdom, 2018).

Technical Report Series No. 996 Annex 5 Guidance on Good Data and Records Management Practices

FDA Guidance for Industry Data Integrity and Compliance With Drug CGMP Questions and Answers

 (Food and Drug Administration: Silver Spring, MD, 2018).

Technical Report Series 1033, Annex 4 Guideline on Data Integrity 

(World Health Organization, Geneva, Switzerland, 2021).

Good Laboratory Practices (GLP) Quality Practices for Regulated Non Clinical Research and Development, Second Edition

 (World Health Organization, Geneva, Switzerland, 2009).

Reflection paper on expectations for electronic source data and data transcribed to electronic data collection tools in clinical trials

 (European Medicines Agency, London, United Kingdom, 2010).

Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments Draft 

(Pharmaceutical Inspection Convention/Pharmaceutical Inspection Cooperation Scheme, Geneva, Switzerland, 2021).

FDA 483 Observations Aurobindo Pharma Ltd.

EMA Draft Guideline on Computerized Systems and Electronic Data in Clinical Trials

 (European Medicines Agency, Amsterdam, The Netherlands, 2021).

OECD Series on Principles of Good Laboratory Practice and Compliance Monitoring Number 1, OECD Principles on Good Laboratory Practice

 (Organization for Economic Cooperation and Development, Paris, France, 1998).

FDA Guidance for Industry Out of Specification Results

Columns: Focus on Quality

It is traceability that shows that the ALCOA criteria does not exist in individual silos, but that they all interact with and are dependent upon each other.

Is Traceability the Glue for ALCOA, ALCOA+, or ALCOA++?

Evidence and sentiment are both aligned towards the necessity of reducing the impact of greenhouse gases on climate. Although global CO

 emissions are relatively easy to assess because of their linear relationship with carbon-based fuel combustion, methane (CH

) is relatively difficult to measure because of the diversity of methane sources. Because it has over 25 times the potency of CO

 as a greenhouse gas and a much shorter atmospheric lifetime, controlling CH

 is one of the highest-impact ways to reduce climate impacts. Here, we look at the evidence and some of the ways spectroscopy is essential in this fight.

The recent international climate meeting, “Conference of the Parties 26” (COP26) that occurred in Glasgow, Scotland, in the fall of 2021 both highlighted the dangers associated with climate change and solidified the will for immediate action to reduce greenhouse gases. In the 30 years since the initial United Nations Framework Convention on Climate Change, substantial new evidence has been collected that documents the deleterious effects of greenhouse gas emissions on climate and the Earth’s ecosystem, and investments in renewable energy technology have been implemented to accelerate the transition to low carbon intensity and carbon-free energy sources. These two factors have moved public sentiment toward action while facilitating the possibility of reducing greenhouse gas emissions without an enormous drop in global productivity and standard of living that would be inevitable if low-carbon energy sources were not inexpensively available.

The result of these two factors is that the time for action is now. Many industries recognize the need for prioritizing developing technologies to combat climate change and are broadly aligned on this goal.

) is a much more potent greenhouse gas than carbon dioxide (CO

 is significantly higher in atmospheric concentration at 418 parts per million (ppm) (1) than CH

 absorption bands in the atmosphere are saturated, meaning that rising CO

 concentration influences absorption only on the wings of the absorption bands, while the CH

 bands are not saturated. As a result, rising CH

 concentration is much more impactful on warming. It is estimated that global CH

 concentrations are 2.5 times higher than in preindustrial periods (3), compared with a roughly 150% increase in CO

 levels from peaks in preindustrial times of approximately 280 ppm to present-day values.

 has a relatively short lifetime in the atmosphere, accounting for approximately 30% of the atmospheric reactions with the hydroxyl radical (OH) (4), which itself drives most of the reactions in Earth’s troposphere. During its oxidative breakdown, CH

 contributes substantially to tropospheric ozone (O

 is photolyzed into NO + O, and the oxygen radical reacts with O

 pathway forms essentially the only source of tropospheric ozone (4), which itself is a potent greenhouse gas. The IPCC’s 5th Assessment report in 2013 assigned CH

 for radiative forcing in the atmosphere (5). Because of its short lifetime, Inger Anderson, who is the executive director of the United Nations Environment Program, said “Cutting methane is the strongest lever we have to slow climate change over the next 25 years and complements necessary efforts to reduce carbon dioxide” (6).

 emissions, which are easily localized and primarily from combustion-driven energy sources, CH

 emissions are dispersed geographically and from a variety of source types. For example, substantial amounts of gas-phase hydrocarbons are locked in underground reservoirs along with liquid and solid hydrocarbons. Although in many cases these reservoirs of gas are successfully captured, extraction of fossil fuels (both coal and oil) leads to emissions. Successful capture depends on successful measurement. Table I shows some of the most important global emissions sources of CH

 has fundamental vibrational modes in the infrared (IR), with the main H-CH

 stretching modes approximately 3.4 μm and the H-CH

 deformation modes between 6.8–7.5 μm. Combination bands and the harmonics of these modes make the CH

 spectrum quite rich in the mid- and near-IR (NIR) regions. Although solid state electrochemical sensors are used in some situations for point monitoring applications, many, if not most, applications use some sort of spectroscopic measurement.

The simplest measurement scheme is nondispersive IR (NDIR), in which a broadband light source is directed onto a filtered photodiode or other detector. Gas in the path between the light source and the detector gener- ates an absorption signal, which can be used to quantify the gas. For CH

, the filter is typically in an interference-free region around 3.4 μm. NDIR gas sensors have been used for decades in air quality monitoring. Here, we focus on more complex sensors and evolving applications for local and global CH

 monitoring used to assess and control emissions for climate change.

Many of the methane concentration data series (for example, the global monitoring laboratory series maintained by the National Oceanic and Atmospheric Administration [NOAA]) rely on gas samples transported to the laboratory and measured using traditional, sensitive methods, such as gas chromatography (GC). However, these measurements are being supplemented by newer devices that can be used on-site and made portable. The most prevalent is the cavity ring-down spectrometer (CRDS), which is available from providers such as Picarro, Los Gatos Research (an ABB company), and Tiger Optics, among others.

In CRDS, pulsed light tuned to an absorption transition is directed through a gas cell containing the gas of interest. Highly reflective end mirrors in the cavity can yield pathlengths of at least 10 km quite easily. A small amount of light emitted from one end of the cavity is measured continuously. Trace gas absorption during roundtrips of the light in the cavity causes the light to diminish with each pass, as shown in Figure 1 and equation 1 (12):

Here, the intensity as a function of time, 

, is proportional to the initial intensity multiplied by the exponential decay function, where 

 is the transmissivity of the cavity (determined by the mirrors), 

 is the speed of light. If the reflectivity of the end mirrors and 

 are precisely known, the absorption because of a particular gas mixture can be precisely measured. For example, the Piccaro G2203 methane/acetylene monitor has ppm-level sensitivity with 3 ppb precision and a drift of less than 4 ppb. It can be used for measuring fugitive emissions from landfills or other broad-area sources, with an acetylene tracer for quantification. CRDS monitors can also be used in mobile mode, coupled with a GPS for mapping.

Another type of innovative mobile methane monitor uses tunable diode laser absorption spectroscopy (TDLAS) technology (13) to measure CH

 in a path up to approximately 30 m. A visible aiming laser allows for the pointing of the instrument, which works for NIR. Backscatter allows the determination of total CH

 in the path, reported in ppm meters, which is quite useful for detecting leaks in oil and gas plants, where it may be difficult to gain access to all parts of the process. Examples of these solutions are the Sensit Gas·Trac LZ-30 or the Crowcon LaserMethane Mini, among others. For a similar use case, Teledyne FLIR Inc. has a popular CH

 leak imager (GF320) that operates on the 3.2–3.4 μm band, detecting absorption in backscatter using a cooled camera detector (CCD). Recent tests indicate that these are good for detecting relatively large leaks (greater than 10 standard liters per min) under good meteorological conditions when the operator is well-trained (14). For more trace detection, the TDLAS units may prove more sensitive.

Increasingly, industrial fenceline monitors are under consideration not only for toxic air contaminants such as H2S and reactive organic compounds such as acetaldehyde from refineries, but also for CH

There are a number of technologies that can be used in an open-path configuration as a fenceline monitor to measure CH

. The simplest is open-path NIR with a broadband source, configured as an NDIR sensor as described above without the gas cell. However, this configuration has a limited range because of dissipation of the source at a distance, combined with the relative weakness of the NIR transition compared with the mid-IR.

Moving detection into the mid-IR has advantages, and there are several Fourier transform (FT)-IR systems configured as fenceline monitors. With a wide spectral range, these can typically measure a suite of gases. They typically have a longer pathlength than NIR monitors, and FT-IR is written into U.S. EPA standard methods, so it is widely accepted.

Using a laser has distinct advantages because of the collimation of the source. Numerous companies have fenceline monitors based on TDLAS, including Unisearch (LasIR) and Sensit (Gas·Trac FPL). These work in NIR spectroscopy, where tunable diode laser technology is mature. Newer systems include the LaserWarn by Block Engineering. Based on quantum cascade laser technology, these have the highest combined detection sensitivity and pathlength.

 measurement systems involve remote sensing. There are a number of interesting approaches. Current satellite instruments are able to measure atmospheric CH4 in the shortwave IR using absorption of solar radiation measured in backscatter. According to Varon and Associates, these measurements typically have resolutions of 1–10 km and precision between 0.1–1% (15). Given these parameters, they provide regionally accurate data but cannot resolve point sources. Upcoming instruments hope to provide improved resolution, both with more optical resolution and by using updated plume algorithms to pinpoint sources. Most of the recent instruments use this approach. Older satellite instruments use earth’s thermal radiation as a background source. These instruments are less sensitive in the lower troposphere because of the low temperature contrast with the earth but are useful at mid-latitudes. They are useful for quantifying CH

 in particulate-laden environments because the longer wavelengths are not sensitive to particulates (16).

A highly awaited mission called Methane Remote Sensing Light Detection and Ranging (LIDAR) Mission (MERLIN) is scheduled to launch in 2024. A joint effort of the French National Center for Space Studies (CNES) and the German Aerospace Center (DLR) will use differential absorption LIDAR in the 1.6 μm CH

 in the column at 20 Hz. Measurements are taken approximately every 400 m along the ground track (17). The MERLIN mission should have top-level scientific output daily maps of the column-weighted dry-air mixing ratio of methane (18). This view of global emissions on a daily basis should greatly improve our understanding of global sources and geographic variation and provide great insight into opportunities for CH

Evidence shows that there is an immediate need to control global warming, and low-carbon energy technologies and public sentiment are aligned for action. One of the most effective and quickest ways to minimize greenhouse gases is to control CH

 emissions, given their outsized impact and their relatively short lifetime in the atmosphere.

This crisis becomes an enormous opportunity for spectroscopists because detection works hand-in-hand with control strategies. Employing new methods, or achieving higher time- and spatial-resolution with existing methods for CH

 detection, is an enormous near-term opportunity for the spectroscopy community and readers of this column. Let’s get to work!

(1) National Aeronautics and Space Administration, Vital Signs: Carbon Dioxide. https://climate.nasa.gov/vital-signs/carbon-dioxide/ (accessed February 19, 2022).

(2) Global Monitoring Laboratory, Global CH

 Monthly Means. https://gml.noaa.gov/ccgg/trends_ch4/ (accessed February 19, 2022).

(3) A. Borunda, Methane, explained (2019). https://www.nationalgeographic.com/environment/article/ methane (accessed February 19, 2022).

 (Oxford University Press, Oxford, United Kingdom, 1990).

(5) Intergovernmental Panel on Climate Change (IPCC), Summary of Policymakers, in 

Climate Change 2013: The Physical Science Basis

, eds. TF. Stocker, et al. http://www.climatechange2013.org/images/report/WG1AR5_SPM_FINAL.pdf (accessed February 19, 2022).

(6) World Meteorological Society, Global Methane Assessment Released. https://public.wmo.int/en/media/news/global-methane-assessment-released (accessed February 19, 2022).

(7) IEA, Methane Emissions From Oil and Gas. https://www.iea.org/reports/methane-emissions-from-oil-and-gas (accessed February 19, 2022).

(8) U.S. Environmental Protection Agency, US EPA Activities to Support Global Coal Mine Methane Reductions. https://unece.org/fileadmin/DAM/energy/se/pp/coal/ cmm/7cmm_oct2011/5_US_EPA_Pamela_Franklin.pdf (accessed February 19, 2022).

(9) China Dialogue, How will China Control its Methane Emissions? https://chinadialogue.net/en/climate/how-will-china-control-its-methane-emissions/ (accessed February 19, 2022).

(10) R. Zhong, “Gas Stoves Methane Emissions.” https://www.nytimes.com/2022/01/27/climate/gas-stoves-methane-emissions.html (accessed February 19, 2022).

(11) U.S. Environmental Protection Agency, Importance of Methane. https://www.epa.gov/gmi/importance-methane (accessed February 19, 2022).

, 5190 (1995). https://doi.org/10.1063/1.469244.

(17) CNES, Measurement Concept. https://merlin.cnes.fr/en/measurement-concept (accessed February 20, 2022).

(18) CNES, Products. https://merlin.cnes.fr/en/products (accessed February 20, 2022).

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