Analytically Speaking Podcast, Episode 8

Estimation of the Fluorescence Band Parameters

Smoothing of the Time-Resolved Spectral Matrix Obtained by a Streak Camera

Clay and Soil Organic Matter Drive Wood Multi-Elemental Composition of a Tropical Tree Species

Three-Dimensional Printing and the Art of Making Small Working Prototype Spectrometers

The Emerging Leader in Atomic Spectroscopy Award recognizes the achievements and aspirations of a talented young atomic spectroscopist who has made strides early in his or her career toward the advancement of atomic spectroscopy techniques and applications.

The award will be given to a researcher who has focused the majority of his or her work in the field of analytical atomic spectroscopy, with direct contributions to inorganic mass spectrometry (MS), optical emission spectroscopy (OES), laser-induced breakdown spectroscopy (LIBS), atomic absorption spectroscopy (AAS), atomic fluorescence spectroscopy (AFS), and/or X-ray techniques through original research on the development or advancement of theory, instrumentation, measurement techniques, or applications.

The winner must be within 10 years of receiving his or her PhD in the year the award is granted. The winner is chosen by an independent scientific committee.

To nominate a candidate, please e-mail the following documents to Laura Bush, the editorial director of 

Information about the person submitting the nomination:

Year PhD was earned and from where (list degree, year, institution, and location). 

Important: Candidates must be within 10 years of receiving their PhD in the year the award is granted.

Short summary, in 100–200 words, of the candidate’s achievements or contributions (more details can follow in the sections below).

Please list the candidate’s five most important pieces of work (such as papers in peer-reviewed journals, technical reports written for an industrial community, or other) and explain briefly the significance of each.

Other key contributions to the field of atomic spectroscopy not captured above

Number of oral and poster presentations at scientific conferences

Service provided to the scientific community, such as volunteer work in scientific societies, work as a journal reviewer, and so on

Please include one seconding letter (letter of support) from a member of the atomic spectroscopy community (this person must be different from the nominator). The nominator may also provide an additional letter of support if desired.

Please provide a current resume or CV of the candidate in a Word or PDF file.

Include a high-resolution headshot of the nominee in a .jpg format.

The nomination form can be downloaded from this

Questions about the submission process should be directed to Laura Bush, the editorial director of 

Articles

Nominate a colleague for the 2024 Emerging Leader in Atomic Spectroscopy Award!

Call for Nominations: The 2024 Emerging Leader in Atomic Spectroscopy Award

Philip J. Grandinetti of the Ohio State University is the winner of the 2022 Eastern Analytical Symposium (EAS) Award for Outstanding Achievements in Magnetic Resonance. He received the award on Monday, November 14, in a session in his honor at EAS in Plainsboro, New Jersey.

Grandinetti studied for his PhD in physical chemistry at the University of Illinois, Urbana-Champaign, under Prof. Jiri Jonas, where he developed and applied in situ high-pressure nuclear magnetic resonance (NMR) methodologies to study the dynamics of elastohydrodynamic lubricants and pressure-induced phase transitions in lipids. After completing his PhD, Grandinetti worked at the University of California, Berkeley, in the laboratory of Prof. Alex Pines, from 1989 to 1993. While there, he made contributions to a new class of solid-state NMR methods for obtaining high-resolution spectra of half-integer quadrupolar nuclei.

Grandinetti’s current research interests focus on magnetic resonance to probe dynamics and structure in disordered and heterogeneous materials. He received an NSF CAREER award in 1995 and an NSF Creativity Award in 2004. He was a visiting professor at the Ecole Normale Supérieure de Lyon in 1999, a visiting professor and Le Studium Researcher at the CNRS in Orléans, France, in 2005-2006, the Allan Cox visiting professor in the School of Earth Sciences at Stanford University in 2009, and a visiting professor at the École Polytechnique Fédérale de Lausanne, Switzerland. He served on the editorial board of the journal 

 and was a council member of the International Society of Magnetic Resonance.

Each year, the Eastern Analytical Symposium honors analytical chemists who have distinguished career achievements. The recipients of these awards advanced these fields by superior work in developing theory, techniques, or instrumentation.

Philip J. Grandinetti of the Ohio State University is the winner of the 2022 Eastern Analytical Symposium (EAS) Award for Outstanding Achievements in Magnetic Resonance. 

Philip J. Grandinetti Receives 2022 EAS Award for Outstanding Achievements in Magnetic Resonance

Richard Crocombe of Crocombe Spectroscopy Consulting has won the 2022 Eastern Analytical Symposium (EAS) Award for Outstanding Achievements in Vibrational Spectroscopy. He was presented with the award on Tuesday, November 15, in an award session at EAS in Plainsboro, New Jersey.

Crocombe graduated from Oxford University with a BA and MA in chemistry, and the University of Southampton with a PhD in chemistry and spectroscopy. His thesis work involved classical infrared and Raman spectroscopy studies of small inorganic molecules, including matrix-isolation and isotopic substitution. A postdoctoral fellowship in the United States had Crocombe working on early applications of Fourier transform IR (FT-IR), including time-resolved spectroscopy and gas chromatography–IR (GC-IR), and infrared laser photolysis.

Crocombe joined Digilab (Bio-Rad) to work on laboratory FT-IR instrumentation. He held numerous positions at Digilab over the years, but concentrated on product, software, and applications development, including step-scan FT-IR applications, and spectroscopic imaging using two-dimensional focal plane array detectors. Later, he held positions at Axsun Technologies, Thermo Fisher Scientific, and finally PerkinElmer, concentrating on miniature, portable and handheld spectroscopic instruments, their development and applications. These spanned the range from near-infrared spectroscopy, X-ray fluorescence spectroscopy, Raman spectroscopy, and FT-IR spectroscopy to gas chromatography–mass spectrometry. In 2017 he left the corporate world to set up his own consulting company, helping to commercialize new miniature spectroscopic technologies.

He has been a co-chair of SPIE’s Next-Generation Spectroscopic Technologies conference for more than 10 years and is an SPIE Senior Member.He was selected for the Williams-Wright Award for Industrial Spectroscopy in 2012, is a Fellow of the Society for Applied Spectroscopy (SAS), and was President of SAS in 2020.

Crocombe has published extensively on the technologies and applications for miniature and portable spectrometers. He, Pauline Leary, and Brooke Kammrath are the joint editors of the two-volume book, 

Richard Crocombe of Crocombe Spectroscopy Consulting has won the 2022 Eastern Analytical Symposium (EAS) Award for Outstanding Achievements in Vibrational Spectroscopy. 

Richard Crocombe Receives 2022 EAS Award for Outstanding Achievements in Vibrational Spectroscopy

In the treatment of tuberculosis (TB), a contagious disease that causes 1.5 million deaths per year globally, early diagnosis is critical in order to control its spread. Unfortunately, standard tuberculosis diagnostic tests, such as sputum culture, can take days to weeks to yield results. In a recent paper, Ubaid Ullah of the Syed Babar Ali School of Science and Engineering in Pakistan and his colleaguesdemonstrate a quick, portable, easy-to-use, and non-invasive optical sensor based on sputum samples for tuberculosis detection using Raman spectroscopy to detect TB in a patient’s sputum supernatant. Ullah spoke to 

Your paper (1) demonstrates a quick, portable, easy-to-use, and non-invasive optical sensor for analysis of sputum samples for tuberculosis (TB) detection. What inspired the development of this sensor?

The current gold standard and most common practice test for TB diagnosis is the sputum culture, specifically in third-world countries where TB has a high impact. However, these tests take days to weeks to produce results. Meanwhile, the potential TB patient is out in the general public, probably infecting more and more people. Therefore, we devised an alternate approach that still makes use of the standard TB lab equipment and testing procedures, and yields findings within a couple of minutes. The catch is that we replace the time-consuming incubation step (where bacteria in TB liquid samples are nourished to form visible colonies) by exploiting spectroscopic information from the freshly prepared TB sample.

The probe uses Raman spectroscopy to evaluate detection of TB in a patient’s sputum supernatant. What advantages did Raman spectroscopy offer that other techniques available may have lacked?

Multiple techniques, including immune-chromatography, polymerase-chain-reaction (PCR), piezoelectricity, electrochemical, and surface plasmon resonance, have been implemented for TB detection. These methods, however, either have poor sensitivity and specificity, high operational cost, lack portability, invasiveness, or produce harmful byproducts. Raman spectroscopy, on the other hand, does not suffer from these limitations, and has been successfully applied to the diagnosis of various diseases, as evident from the fact that it has been used in clinical trials involving hundreds of patients to detect various types of cancer. In fact, companies now exist that provide commercial Raman systems for various disease diagnoses. For example, Kaiser Optical Systems, Inc. develops Raman systems for multiple applications, including cancer, skin, bone, eyes, and dental diagnosis.

How did you select the calibration set of samples and the validation set of samples? Were different samples used to develop the discriminant model versus samples used to test the model?

We employed principal component analysis (PCA) for the classification. Since PCA relies on dimensional reductionality, it bypasses the usual classification procedures of training and validation. We ran PCA on 112 patients’ data, and chose the first two orthogonal principal components, PC1 and PC2, for segregation.

Your paper states that the red and black dots are underneath the blue line—did you mean to say green and black dots, indicating the TB + samples are separated out from the red TB – samples?

Yes, the blue line serves as the classifier. As mentioned in Figure 3, the black and green dots below the blue line represent TB + patients on medication and recently diagnosed TB + patients, while red dots above the blue line denote TB – patients.

Briefly describe your discovery and development process.

Modern, sophisticated machine learning algorithms make it possible to detect very minute variations that were previously impossible to comprehend with conventional methods. It is well-researched that the sputum of a person with TB has a range of biomarkers, including esters and proteins. We hypothesize that the presence of these compounds minutely changes the Raman signature of the sputum’s supernatant sample, even after filtering mycobacterium tuberculosis (Mtb) bacteria cells. The change in the Raman signature is too weak to identify TB biomarkers, but is sufficient to probe TB. However, its weak nature makes it hard to differentiate the probe signal visually. Therefore, we utilized a machine learning algorithm, principal component analysis (PCA) for the classification.

The following is a brief description of the development process. We collected sputum from a potential TB patient, and prepared the sample following the standard TB culture protocol. Samples were then filtered to remove Mtb bacteria into a clean cuvette. Following this, we record Raman data of the cell-free sample supernatant using a wavelength and intensity calibrated diffraction limited spectrometer by averaging five frames of the Raman spectrum and subtracting the reference background spectrum. Each Raman spectrum was integrated for 1.5 min. The obtained Raman data was then regularized, a covariance matrix was found, principal components analysis was performed, and the sample data was plotted in the plane of the highest variance orthogonal components (PC1, PC2).

How does this work differ from what has been previously done by yourself or others?

As stated earlier, Raman spectroscopy has been successfully applied to detect various diseases, including cancer and skin diseases, and companies now exist that provide commercial Raman systems for various disease diagnoses. However, Raman spectroscopy is not widely exploited for TB detection, since it is predominantly a problem of developing countries. Researchers have utilized Raman spectroscopy to detect TB in blood and TB meningitis in cerebrospinal fluid (2,3). Even though these approaches accelerate TB diagnosis, their invasive nature limits its applications. A subsequent study that employed Raman spectroscopy of individual mycobacterium cells for TB detection offered even species-level information (4). Moreover, they achieved an accuracy of 94%. However, the complex sample preparation process necessitates the need for a specialist. Furthermore, human sampling was missing in the study. Here, for the first time, we utilize Raman spectroscopy and a machine learning algorithm to detect TB in sputum supernatant. The probe produces quick results, does not require trained laboratory personnel, is non-invasive in nature, and will use the already established state-of-the-art TB test facilities.

We demonstrate for the first time the application of Raman spectroscopy toward rapid TB detection using sputum samples. The sensor offers 100% true-positive and 93.3% true-negative accuracy after testing 112 TB patients. Significantly, our probe can provide a quick (few minutes) TB test result of an already processed sputum sample for the culture test. The probe can be easily integrated into conventional TB diagnostic labs where smear microscopy and culture tests are routinely conducted.

Were there any particular limitations or challenges you encountered in your work?

One particular limitation of our setup is its high capital cost, mainly due to the Raman spectrometer. Yes, working and gathering TB samples during the Covid pandemic was a huge challenge for us.

Can you please summarize the feedback that you have received from others regarding this work?

In addition to applause and greetings, we were advised to apply this technique to other infectious diseases such as malaria and pneumonia. Furthermore, it was suggested that we make a stand-alone commercial device out of this work.

What are the next steps in this research?

We are looking for further funding to make this probe more robust, reduce its capital cost, and to make feasible the replacement of the standard TB culture test with a low-cost setup.

Do you think this work be taken into clinical trials for use in diagnostics?

Yes, this work has the capability to be taken into clinical trials for use in diagnostics.

U. Ullah, Z. Tahir, O. Qazi, S. Mirza, and M.I. Cheema, 

S. Khan, R. Ullah, S. Shahzad, N. Anbreen, M. Bilal, and A. Khan, 

R. Sathyavathi, N. C. Dingari, I. Barman, P. S. R. Prasad, S. Prabhakar, D. N. Rao, R. R. Dasari, and J. Undamatla, 

S. Stöckel, S. Meisel, B. Lorenz, S. Kloß, S. Henk, S. Dees, E. Richter,S. Andres, M. Merker, I. Labugger, and P. Rösch, 

 received his BS degrees in Electronics from the University of Peshawar in 2014, M.Phil. and PhD degrees in Electronics and Electrical Engineering from Quaid-i-Azam University (Islamabad, Pakistan) and Lahore University of Management Science (Lahore, Pakistan) in 2016 and 2021, respectively. He is currently working as a Postdoctoral Researcher in the Bio-Agri-Photonics Lab at Lahore University of Management Sciences. His research interests include the design and development of optical sensors for biomedical and chemical applications.

In the treatment of tuberculosis (TB), a contagious disease that causes 1.5 million deaths per year globally, early diagnosis is critical in order to control its spread. Unfortunately, standard tuberculosis diagnostic tests, such as sputum culture, can take days to weeks to yield results. In a recent paper, Ubaid Ullah of the Syed Babar Ali School of Science and Engineering in Pakistan and his colleagues demonstrate a quick, portable, easy-to-use, and non-invasive optical sensor based on sputum samples for tuberculosis detection using Raman spectroscopy to detect TB in a patient’s sputum supernatant. Ullah spoke to Spectroscopy about this sensor and its development.

Raman Spectroscopy and Machine Learning-Based Optical Probe for Tuberculosis Diagnosis via Sputum 

This article gives a brief overview of the major portable techniques: those based on optical spectroscopy techniques, including near-infrared (NIR), mid-infrared (mid-IR), and Raman spectroscopy; mass spectrometry (MS) systems, including high-pressure MS (HPMS), gas chromatography–MS (GC–MS), ion mobility spectrometry (IMS); elemental techniques, such as X-ray fluorescence (XRF) and laser-induced breakdown spectroscopy (LIBS); and emerging miniaturized techniques like nuclear magnetic resonance (NMR). The above are all “conventional” spectroscopic techniques and reduced to a rugged portable format, containing self-contained data systems. They provide specific and actionable information to their operators working with them outside the laboratory—in the field—and these instruments have well-defined value propositions. A recent development is the availability of low cost (<$100) multispectral sensors operating in the visible and NIR regions. This low cost enables the sensors to be embedded into consumer products, such as smart “white goods” appliances, personal care, fitness products, and even “wearables” products. In the future, miniature and portable spectrometers will be ubiquitous—outside the laboratory, and in your home and pocket.

In Chapter 1 of “Alice in Wonderland,” Alice chases the white rabbit down a hole and looks into a small passage, seeing “the loveliest garden you ever saw” (1). She can’t go through the passage until she imbibes from a bottle labeled “Drink Me” and shrinks in size. Although she shrinks in size, she does maintain all her faculties. Like Alice, spectrometers have gone through this miniaturization process while maintaining their functionalities. In the past 20 years, spectrometers have shrunk dramatically in size, giving us first laboratory-portable, toaster-sized instruments, then cordless drill-sized portable instruments for use in the field, and finally spectrometers the size of a computer mouse or a deck of cards (2). This shrinking has been achieved with only modest performance reductions in sampling versatility, spectral range, spectral resolution, and signal-to-noise (S/N). However, by utilizing the ever-increasing power of consumer electronics, these instruments are capable of generating reliable and actionable results in the field. The latest development is the availability of very low-cost multispectral sensors that are the size of a computer chip, leading to the possibility of embedding them into consumer goods.

It is convenient to classify portable spectrometers into four types (Table I). In this article, we are concerned with just the first two—completely integrated instruments, and miniature spectrometers or multispectral sensors, designed to be embedded in consumer goods.

We can see four portable spectrometer techniques: optical molecular analysis (UV-visible [UV-vis], near-infrared [NIR], mid-IR, and Raman); mass spectrometry (MS; high pressure mass spectrometry [HPMS], gas chromatography–mass spectrometry [GC–MS], and ion mobility spectroscopy [IMS]), and elemental analysis (X-ray fluorescence [XRF] and laser-induced breakdown spectroscopy [LIBS]). Relative newcomers are ruggedized and field-portable nuclear magnetic resonance (NMR), both chemical shift and time-domain (relaxometry) variants. Each technique or instrument has its own benefits and limitations, so we have to choose the right technique for the problem at hand, and Table II shows some of their established applications.

Optical molecular instruments are widely used for the rapid identification or confirmation of chemical substances, often “white powders.” These applications can range from confirming incoming material in pharmaceutical manufacturing (3), detecting counterfeit pharmaceuticals in the field, and identifying suspicious materials by the police, customs, border officials, and airport security personnel. NIR, mid-IR, and Raman spectrometers are all used in these areas, but each has its strengths and weaknesses (3). Briefly, Raman spectroscopy is often preferred because of its “point-and-shoot” ability, whereas mid-IR typically requires the material to be handled. This drawback of mid-IR tends to outweigh the issue of fluorescence in Raman spectra. NIR spectroscopy has been used for many years for the quantitative analysis of natural products (grain, fruits, and so on), and it is well-suited to these highly heterogeneous materials. Raman and NIR spectroscopy are direct competitors in many pharmaceutical applications (3).

These optical techniques are limited to major component (percent level) analyses in condensed phases. For trace analysis and complex-mixture analysis, mass spectrometric (MS) techniques are required. MS has typically required the use of a high vacuum, and this precluded miniaturization of the instrument to a handheld format. Briefcase-sized gas chromatography–mass spectrometry (GC–MS) instruments have been commercially available since approximately 1996. They are widely used by hazardous material technicians, the military, and environmental scientists to investigate and characterize suspicious locales. Because these instruments use a separations front end, they are excellent for analyzing complex mixtures and detecting trace components within those samples. HPMS operates at a modest vacuum (0.1 atmospheres) using an array of micro-ion traps and is therefore available in a handheld format. HPMS is fast (seconds), reliable for programmed target chemicals, and provides a presumptive method for identification. IMS has been used in airport security applications since the late 1980s, with operators “swabbing” luggage and analyzing that swap in a small desktop instrument. Portable versions are available in a “dustbuster” format, and wearable versions are employed by the military.

Portable XRF has been used for at least 20 years in the lifecycle of metal, from mineral prospecting, mining, refining, raw material confirmation, in-process inspection, and finally, to scrap metal sorting. Other applications include detection of heavy metals (such as lead) in old house paint and imported toys, recycling automotive catalytic converters, the “cash for gold” business, environmental surveys, and cultural heritage studies. For fundamental physical reasons, portable XRF has some limitations for elements lighter that silicon, and portable LIBS is especially useful there; for instance, portable LIBS has been used in aluminum alloy sorting and lithium applications, as well as for ferrous alloy identification.

NMR instruments fall into two broad classes: chemical shift and time domain, or relaxometry. Benchtop relaxometers were developed around the same time as analytical NIR instruments and serve some of the same applications, such as moisture measurement. Advances in permanent magnet technology and cell phone electronics enable relaxometry to be offered in a handheld format (4). Benchtop chemical-shift NMR instruments are available from a number of vendors, some with simple functionality and some capable of advanced pulse sequences. Although most of these instruments utilize the familiar 5-mm diameter NMR tubes, the technology can be adapted to wider bore, flowthrough plastic tubing, which is more rugged and suitable for quality assurance (QA) and quality control (QC) applications (5).

The value proposition for portable spectroscopy is summarized in Figure 1. In many cases, a spectrometer taken to the sample will generate instant actionable information that can determine your next step. That next step might be accepting or rejecting incoming raw material; identifying a spill and determining how to handle it; analyzing a suspicious white powder and generating probable cause for arrest, or how to treat an overdose subject; determining the value of scrap metal; or deciding where to drill or mine next. The time saved in achieving these answers is valuable in all these scenarios.

FIGURE 1: The value of a portable spectrometer—taking the spectrometer to the sample and to the point of need.

Although portable and handheld spectrometers are physically smaller than their laboratory counterparts, they typically include many features that permit their use in the field. Table III summarizes these ideal features, and we should note that many portable instruments incorporate most of them depending on the technology and application. The ability to “point-and-shoot” is particularly important because this eliminates the need for sample handling, cuvettes, and reagents, which could be problematic in the field. Any field instrument needs to be splash- and dust-proof, be shock- and drop-resistant, operate reliably over wide range of temperatures and humidity, and so on. The ability to communicate results and spectra, with timestamps and geographical information, is important, and these data often need to be uneditable or unalterable for compliance and legal reasons.

The ability to generate those actionable answers depends on turning a spectrum or spectra into information, which could be identities or concentrations. Therefore, applications development and incorporating the resulting databases or calibrations, as well employing appropriate algorithms, is key to the success of these portable instruments. It has been observed that applications (user requirements) drive the development of these instruments, and in turn, the availability of portable instrumentation drives the development of new applications. This virtuous cyclic process is illustrated in Figure 2. It should be noted that qualitative applications (identification) are significantly easier to develop than quantitative applications (concentrations of each component present), and less sensitive to small variations in spectral quality (S/N, wavelength scale shifts, fluorescence, and so on).

FIGURE 2: Applications development for portable spectrometers (Reproduced with permission from John Wiley from Chapter 1 in 

, R.A. Crocombe, P.E. Leary and B.W. Kammrath (editors), John Wiley, Chichester and Hoboken, 2021).

Commercially available portable spectrometers, operating in the visible-NIR region have been surveyed recently (6), and research on “photonic,” “plasmonic,” and “computational” devices was also reviewed (7). Further miniaturization may also be possible via metamaterials and photonic integrated circuits, with developments to extend operation into the mid-IR (8).

The lowest cost devices, available for a few dollars each, are multispectral sensors (as opposed to full spectrometers), with a small number (usually 6–16) of discrete detectors each having a different thin-film bandpass filter or implemented via organic semiconductors (9–13). A selection of these is shown in Figure 3. Some of these have been demonstrated for use in conventional applications, like illicit drug detection (14), but given their very small size and low cost, the large potential is for their use in embedded applications, with an eventual goal of being incorporated into “wearables” like smartwatches and smartphones.

FIGURE 3: Examples of miniature multispectral sensors. Their small size and low cost enables them to be incorporated into consumer products. Clockwise from top left: (a) a 14-channel visible region spectral sensor; (b) a 16-channel sensor based on an array of detectors having selective wavelengths in the 850-1700 nm range; (c) a new-generation lead salt array detector, covering a wavelength range of 1-3 μm; and (d) an OEM module with 16 near-infrared channels in the 1200–1700 nm range.

As noted above, turning spectra into information is key. In the case of embedded instruments, the application is presumably well-defined and limited in scope, and the probability of success is therefore high, even with a limited resolution multispectral sensor. Some existing products with photonic devices or spectral sensors include high-end sport watches (15), a ring-sized sleep monitor (16), smart toothbrushes (17), hair analysis with custom formulations (18), a smart cosmetic applicator (19), and a vacuum cleaner equipped with a laser and particle counter (20). The latter isn’t something out of an Austin Powers movie but is a product from Dyson that tangentially illuminates the surface, highlighting dust and dander while giving the user a quantitative particle count.

A possible future application is a “smart toilet.” A 2020 paper in the scientific literature (21) discusses “easily deployable hardware and software for the long-term analysis of a user’s excreta through data collection and models of human health.” The Japanese company Toto has discussed this possibility for several years, proposing sensors embedded in the toilet seat to measure heartbeat, body fat, and so on, combined with sensors in the toilet bowl itself to check urine and stool (22). Following analysis of these date in the cloud, it is proposed that the customer could be provided with suggestions for diet, guidance for improving health, and so on. After the 2022 Consumer Electronics Show, there was a column in the Wall Street Journal entitled “The Bathroom of the Future is Here: From High-Tech Toilets to Self-Filling Tubs” (23), which describes these possibilities:

“The suggestion pops up on your phone in the produce section of the grocery store: ‘Your diet seems unbalanced.’ The recommended recipe is: ‘salmon or chicken avocado salad.’ A message from your nutritionist? Nope. Personal trainer? If only. In this vision of the future, it’s your toilet doing the talking. The Wellness Toilet concept that Toto presented at this year’s Consumer Electronics Show is a commode that doubles as a health-monitoring device.”

The author of this article, along with Pauline Leary and Brooke Kammrath, recently edited a two-volume book on portable spectroscopy and spectrometry (24–25). The interested reader is referred to that, as well as to the following papers in this issue, for authoritative reviews of the technologies, instrumentation, and applications.

Spectrometers have been shrinking over the years, from room-filling behemoths, to two-foot-square beige boxes, and now to being transportable within the laboratory. The last 20 years have seen further transitions to portable and handheld spectrometers, for use outside the laboratory, with some now not much larger than a pack of cards. The development of very compact and low-cost multispectral sensors is the latest stage in this journey, and it now permits spectrometers, spectral sensors, and other photonic devices to be completely outside the laboratory: embedded in consumer goods, eventually reaching smartphones as well as smart watches and other wearables. You will have spectral sensors in your home, and in your pocket, and they may also turn up in the most unlikely of places, for and example in smart toilets. But that’s another story (26).

In Figure 3, thank you to (a) ams, (b) MantiSpectra, (c) trinamiX, and (d) Senorics for permissions to reproduce the pictures. 

(12), 1701–1751 (2018). DOI: 10.1177/0003702818809719

(6) K. Beć, J. Grabska, H.W. Siesler, and C.W. Huck 

Wearable Health & Well-being Sensors Rely on Silicon Photonics and Aim for Consumer

https://www.vttresearch.com/en/news-and-ideas/wearable-health-well-being-sensors-rely-silicon-photonics-and-aim-consumer-and

(12) Trinamix, Mobile NIR Spectroscopy Solutions. 

https://trinamixsensing.com/nir-spectroscopy/mobile-nir-spectroscopy- solutions/

Imagine You Could Simply Point Your Smartphone Towards Your Skin and Learn About Your Hydration Level Right Away

https://trinamixsensing.com/news-events/blog/imagine-you-could-simply-point-your-smartphone-towards-your-skin-and-learn-about-your-hydration-level-right-away/

https://www.garmin.com/en-US/c/wearables-smartwatches/

https://shop.colgate.com/products/smart-electric-toothbrush#/

https://www.dyson.com/vacuum-cleaners/cordless/v15/detect/yellow-iron

How’s your health? Toto’s smart toilet will keep tabs for you.

https://asia.nikkei.com/Business/Health-Care/How-s-your-health-Toto-s-smart-toilet-will-keep-tabs-for-you

The Bathroom of the Future Is Here: From High-Tech Toilets to Self-Filling Tubs

https://www.wsj.com/articles/high-tech-bathroom-11642720799

(24) R.A. Crocombe, P.E. Leary and B.W. Kammrath, Eds., 

Portable Spectroscopy and Spectrometry: Technologies and Instrumentation

 (John Wiley, Chichester, United Kingdom, and Hoboken, NJ, 2021), vol. 1. DOI: 10.1002/9781119636489

(25) R.A. Crocombe, P.E. Leary and B.W. Kammrath, Eds., 

Portable Spectroscopy and Spectrometry, vol. 2

 (John Wiley, Chichester, United Kingdom and Hoboken, NJ, 2021) DOI: 

 heads Crocombe Spectroscopic Consulting in Winchester, Massachusetts. Direct correspondence to: 

In the past 20 years, spectrometers have shrunk dramatically in size, and this shrinking has been achieved with only modest performance reductions in sampling versatility, spectral range, spectral resolution, and signal-to-noise.

Spectrometers in Wonderland: Shrinking, Shrinking, Shrinking

Over the course of the 19th century, the former Cataract House Hotel of Niagara Falls, New York, became one of the largest hotels in the region while also serving as an important “station” on the Underground Railroad. A park now occupies the area covering its demolished ruins. Since 2017, archaeological excavations of the site have taken place, led by the Anthropology Department at SUNY Buffalo. Although much is known about the overall design of the Cataract House Hotel, a clearer understanding of its construction phases, as well as its role in the Underground Railroad, could be determined from spectroscopic analysis in tandem with ongoing archaeological investigations. In 2022, in situ data collection was performed on plaster walls at the excavation site using a portable X-ray fluorescence (pXRF) instrument. These elemental data were used in conjunction with archaeological information to form conclusions regarding different construction phases of the hotel. Samples of plaster walls were also collected for further ex situ analyses with pXRF and portable laser-induced breakdown spectroscopy (pLIBS) in a laboratory setting. Future work will include data collection and analysis by additional spectroscopic methods of other artifacts collected at the site, such as pigment samples removed from an unearthed stone step.

Archaeometry, the combination of archaeological knowledge and quantitative measurements, offers empirical information regarding material origin, time of use or construction, and artifact conservation (1,2). Spectroscopic techniques have been shown to be valuable for characterizing archaeological materials and may provide chemical data that can be used to determine the relative ages of those features (2). In particular, elemental composition has been useful for gauging similarities among man-made materials because the makeup of building materials often can be associated with a specific time period, raw material sources, or both (2). Two elemental analysis techniques that are well suited for the analysis of precious archaeological samples are X-ray fluorescence (XRF) and laser-induced breakdown spectroscopy (LIBS). In XRF analysis, a sample is bombarded by X-rays, and the inner electrons of elements in the sample are removed, allowing outer electrons to fill their empty spaces and causing energy to be released in the form of a fluorescent X-ray photons. The energy of the photon released during this process is characteristic of the element being interrogated. In LIBS, a high-energy laser is fired at a sample, a portion of which becomes ablated. At the same time, the energy density yields a high-temperature plasma, which atomizes and excites ablated material. As the elements decay to a lower energy state, light is emitted at wavelengths characteristic of the elements in the sample.

These methods are appropriate for this task because they are minimally or non-destructive in the case of portable LIBS (pLIBS) and portable XRF (pXRF), respectively. Furthermore, both are available as handheld instruments and provide spectral information in a matter of seconds. Although each technique has its unique drawbacks, when they are used in conjunction, many of these limitations are minimized. For instance, XRF provides qualitative and quantitative information for larger elements, whereas low-Z elements, such as carbon and lithium, are not detected. Meanwhile, LIBS is capable of measuring a wider range of elements, including light elements. The nature of the LIBS method also allows for faster data collection in much more focused areas; for LIBS instruments with automated two-dimensional (2D) elemental mapping modes, the technique can easily be applied for evaluating the homogeneity of a sample (3). However, the LIBS spectra are much more data-rich and with higher background than XRF spectra and require more analysis before the elements present can be identified and quantified. The LIBS method is also quasi-destructive. Depending on the intensity of the laser, the number of pulses used to generate a spectrum, and the type of material being ablated, LIBS leaves small, sometimes visible craters on the surface of a sample. The X-rays emitted in XRF leave no marks on any sample during data collection.

The development and proliferation of handheld chemical analysis instruments, such as XRF, LIBS, Raman spectroscopy, and infrared (IR) spectroscopy, has greatly expanded archaeometric capabilities: samples can be rapidly analyzed in situ where access can be sharply limited (4). Obtaining this information in the field allows conclusions to be made during an excavation and inform the direction of a project, such as taking additional samples or deciding where next to dig. This work describes the use of two spectroscopic techniques, XRF and LIBS, to analyze architectural features uncovered during the recent archaeological excavation of the Cataract House, which was once a spacious, luxury hotel that served as an important node on the Underground Railroad (5).

The Cataract House, located in Niagara Falls, New York, was built in 1825 and named for the nearby cataracts, or waterfalls. It began as a simple, three-story building, but by the mid-1840s, the Cataract House had undergone multiple expansions to become one of the largest hotels in the area (Figure 1) (6). The hotel drew tourists from across the United States, including slave-holding families from the southern United States, who were often accompanied by several enslaved persons (5).

FIGURE 1: Photograph of the Cataract House viewed from Goat Island in the Niagara River circa 1800s.

In the early 1840s, the Cataract House became the first hotel in Niagara Falls to employ African-Americans. Many of those hired were from southern states and may have been former slaves themselves (5). The hotel waitstaff made use of their positions as employees of the Cataract House and their proximity to Canada, where slavery had been abolished in 1834, to aid enslaved visitors in escaping to freedom (5). Their efforts resulted in several successful escapes, including in the cases of Cecelia Reynolds, Nancy Berry, and Patrick Sneed (5,7). Other less successful rescue attempts resulted in some negative press around the hotel, but the Underground Railroad “station” continued to operate out of the hotel through the end of the American Civil War in 1865 (5,7).

Between the 1890s and 1920s, the practice of hiring African-American waiters in American hotels and restaurants declined significantly, and the composition of the waitstaff at the Cataract House reflected this trend. The Cataract House continued operating as a hotel until 1945, when a fire destroyed the building (8,9). The ruined hotel was razed in 1946, with rubble from above-ground structures being used to fill in basements. Plans to rebuild were never realized and the site was covered. Today, Heritage Park occupies much of the former hotel’s location (8,9).

Recently, there has been renewed interest in the site, particularly with regard to the Underground Railroad activity. In 2015, preliminary work began to establish an excavation of the hotel (8,9). Digging started in 2017, and subsequent excavations were carried out in 2018 (7) and resumed in 2022. In 2017 and 2018, excavations took place along the former eastern wall of the hotel. In 2017, test units (TUs), which are one square meter trenches dug at areas of cultural interest and carefully documented, were dug, making up two larger trenches. Trench 1 contained TUs 1 and 2, Trench 2 contained TUs 3 and 4, and TU 5 was dug in a separate location (Figure 2). Both excavated trenches contained foundation-wall segments from the Cataract House, referred to as features, which are indicated in Figure 2. Feature 1 (Figure 3a), along the eastern side of Trench 1, is a semi-intact wall of an unknown substrate covered in plaster. Feature 2 (Figure 3b), on the northern side of Trench 2, is a semi-intact brick wall partially covered by a layer of plaster approximately 25 mm thick. In 2018, two additional trenches, Trench 3 containing TUs 6 and 7, and Trench 4 containing TUs 8 and 9, were dug and TU 10 was dug in a separate location (see Figure 2). These trenches lay to the east of the Cataract House’s easternmost wall. The spaces between these trenches and TU 5 were excavated, connecting them and turning TUs 5–9 into one large trench (8,9).

FIGURE 2: Field map of Test Unit (TU) 1–10 locations relative to Heritage Park landmarks. Each numbered TU is one square meter.

FIGURE 3: Photographs of Cataract House excavation sites of (a) Feature 1; (b) Feature 2; and (c) Feature 6 in May 2022.

In 2022, the focus of the excavations shifted toward the Cataract House’s kitchen, which is believed to have been the hub of local Underground Railroad activity. A new trench with four TUs (TUs 11–14) was dug several yards to the west of the original TUs. Site archaeologists used floor plans of the hotel to guide placement of the trench, approximating the location of the kitchen. Uncovered in this trench was Feature 6 (Figure 3c), an entryway flanked by plaster-covered wall remnants and lined on one side with wooden trim. To investigate the relative ages of these features and verify the accuracy of the hotel’s floor plan, atomic spectroscopic methods of analysis were employed.

In Summer 2022, a handheld XRF spectrometer was brought to the ongoing Cataract House excavation with the intention of determining whether construction features in separate trenches were of similar elemental composition and, therefore, likely built as part of the same expansion or modification. Because of the simplicity of the spectra produced and the possibility that the features being analyzed may be present in small quantities or considered precious, XRF was used for in situ data collection. Spectra were obtained with a Bruker Tracer III-V+ and fitted with a rhodium X-ray tube and a yellow filter with 305-μm aluminum and 25-μm titanium. The X-ray tube was operated at 40 keV of excitation energy and 3 μA of current. Each interrogate spot was analyzed with the head of the XRF instrument flush with the plaster surface for 120 s. Duplicate spectra were collected for select locations that were easily accessible based on geometric placement of the feature to be analyzed and instrument dimensions. The spectra were taken at points on the flattest parts of the plaster and were at least 15 cm apart from other points. A total of 39 spectra were obtained onsite from Features 1 and 6.

Excavation time constraints limited the number of sample spots and spectra obtained in situ. However, plaster wall samples were removed from Features 1, 2, and 6, and they were further analyzed in the laboratory. There were six samples collected from Feature 1, 11 samples collected from Feature 2, and seven samples collected from Feature 6. Additional pXRF data was collected with the same handheld XRF instrument and settings used for in situ analysis. For the laboratory measurements, the XRF instrument was mounted to a stand pointing upward and samples were placed on top of the device so that they were flush with its head. Replicate XRF spectra were obtained at every analyzed location.

To verify and support XRF results, pLIBS spectra were collected in the lab using the same set of samples from Features 1, 2, and 6. The pLIBS instrument used (the Z-300 LIBS Analyzer from SciAps) contained three charge-coupled device (CCD) spectrometers that together cover a wavelength range of 190–950 nm. The instrument utilizes an Nd:YAG laser at a wavelength of 1064 nm and a beam diameter of 100 μm. Spectra were obtained with a laser repetition rate of 50 Hz. Two cleaning shots and four data-collection shots were used to generate each spectrum. Additionally, argon gas (high purity grade from SciAps) was used to purge the sample area to increase the spectral intensity of most elemental lines; argon purge is an integrated feature of the instrument used for this study that delivers a few milliliters of gas per analysis. The samples were placed flush with the head of the instrument during analysis. Replicate analyses with LIBS were performed in certain locations to verify consistency in intensity and elements detected. These two instruments were used to collect data sets from the same set of samples from Features 1, 2, and 6. A total of 116 XRF and 60 LIBS spectra were collected in the laboratory, including replicate spectra.

Spectra taken in situ with pXRF were visually distinguishable by the intensity of the peaks. For example, spectra taken from the left side of Feature 1 had much more intense lead peaks than those taken from the right side. To demonstrate, a plot of overlayed spectra from both sides of Feature 1 is shown in Figure 4. For a more definitive conclusion regarding the elemental compositions of the plasters from the site, principal component analysis (PCA) was performed with Unscrambler (version 10.1 from AspenTech) on three data sets extracted from the Cataract House plaster sampling frame to compare the data from the different features; each is discussed below. Prior to principal component analysis (PCA), a subset of data was evaluated using a Shapiro-Wilkes test and was found to be normal.

FIGURE 4: Overlay of two XRF spectra collected in situ from different parts of Feature 1 showing dramatic differences in lead and zinc content.

XRF Data Extracted In Situ from Features 1 and 6

The XRF spectra from the in-field analysis was used for PCA analysis. This fully cross-validated PCA was performed at the site during the 2022 excavation season so that results could be quickly relayed to archaeologists. This initial PCA was produced using the XRF spectral intensity data that was mean centered for each analysis. Feature 1 was found to contain two different elemental compositions that were distinct from the single composition across Feature 6. Both features contained calcium, iron, zinc, lead, and strontium, though in different abundances. Feature 1 was found to be composed of two distinct regions, marked by different levels of lead, according to XRF spectra collected from various points on the feature (Figure 4). The left side of Feature 1 displayed higher amounts of lead than the right side of Feature 1 or any part of Feature 6. A thin, grayish coating—possibly paint—on the left side of Feature 1 may explain the higher lead levels. Lead was commonly used in paint formulations, with its use in the United States peaking in the 19th century. Because Feature 1 was a continuous piece of plaster, the higher lead composition on the left side is not indicative of a second construction event. Feature 6 has more strontium than Feature 1 and it is believed that Feature 6 was built earlier, a hypothesis supported by the floor plans and records available. At the site, the XRF analysis data corroborated the theory that Features 1 and 6 were built during separate construction events.

XRF Data Extracted In Situ Combined with XRF Data Extracted Ex Situ

Fully cross-validated PCA with XRF results verified that the in situ and ex situ data could be combined while also comparing the elemental compositions of Features 1, 2, and 6. The score plot from this PCA can be seen in Figure 5a. Integrated peak areas from the XRF spectra were used to generate this PCA and data were normalized to one, mean centered, and divided by the standard deviation of the data set. Elements included in the analysis included calcium, iron, nickel, lead, strontium, and zinc. Spectra taken from the high-lead portion of Feature 1 were excluded from this PCA because the high lead levels were found to be from paint (see above) and not part of the plaster composition. Sodium peaks, which are often inflated by soil contamination, were similarly excluded from the PCA. The explained variance of PCs 1 through 3 was 90.1%. The majority variance in PC1 was because of contributions from nickel, iron, and calcium. Meanwhile, zinc and lead contributed the most to variance in PC2 and iron and calcium to variance in PC3. This combined in situ and ex situ data analysis supports the earlier finding that Features 1 and 6 are made of different plasters. The XRF data collected ex situ also included Feature 2, which was not analyzed at the site. According to PCA results, Feature 2 has a third distinct plaster composition, containing more zinc than the other two features.

FIGURE 5: Three-dimensional PCA score plots for (a) in situ and ex situ XRF; and (b) ex situ LIBS from analyses of wall samples from Features 1 (blue squares), 2 (red circles), and 6 (green triangles).

LIBS Data Extracted Ex Situ from Features 1, 2, and 6 

The fully cross-validated PCA from the laboratory-based LIBS analysis corroborated the XRF results and further distinguished the features with a larger subset of elements detected by LIBS, which included nickel, carbon, magnesium, silicon, aluminum, lead, iron, calcium, strontium, barium, lithium, and potassium. Prior to PCA analysis, the data were normalized to one, mean centered, and divided by the standard deviation of the data set. This PCA was performed using integrated peaks at selected wavelengths, which are listed in Table I, with the score plot shown in Figure 5b. The explained variance across PCs 1–3 was 87.0%, where aluminum, strontium, silicon, carbon, and magnesium contributed the most to the variance in PC1. Variances for PC2 and PC3 was because of mainly barium, calcium, and potassium, respectively. As anticipated, analysis of these data revealed additional elements that could not be detected by XRF, providing information that may link the plasters to specific time periods. For example, carbon is identified in all three plasters, but almost twice as much carbon is present in Features 1 and 2 as in Feature 6. Calcium carbonate (CaCO

), or lime, was commonly used in North American plasters before the 20th century (10). These LIBS results also showed that Feature 6, in addition to high amounts of strontium, contained more lithium than either Feature 1 or 2 and revealed a higher degree of heterogeneity in Feature 2’s plaster than in Features 1 and 6, with Feature 2 being speckled with small, high-barium areas. However, the separation between Features 1 and 2 can be seen more clearly in the score plot of the XRF data. Overall, the LIBS and XRF results both demonstrated that Features 1 and 2 share many elemental components and are more similar to each other than either is to Feature 6, suggesting that Features 1 and 2 were built at approximately the same time.

Combining archaeological knowledge with empirical evidence established using analytical techniques, we have been able to distinguish features at the Cataract House excavation from one another and relate them to specific time periods. Through the application of handheld instruments for collecting and analyzing data in situ, archaeological endeavors can be supported by rapidly supplying information during an ongoing investigation. Such information may inform the direction of an excavation, enhancing or modifying conclusions based solely on a feature’s appearance and surroundings. Future work will focus on analysis of other, non-plaster artifacts recovered from the site, allowing archaeologists to confidently develop a clearer picture of the Cataract House during its time as a “station” on the Underground Railroad.

(2) M.K. Donais, S. Wojtas, A. Desmond, B. Duncan, and D.B. George, 

(3) R.S. Harmon, D. Khashchevskaya, M. Morency, L.A. Owen, M. Jennings, J.R. Knott, et al, 

Portable Spectroscopy and Spectrometry 2: Applications

, R. Crocombe, P. O’Leary, and B. Kammrath, Eds. (Wiley & Sons Ltd., West Sussex, United Kingdom, 2021), pp. 523–544.

(5) J. Wellman, “Niagara Falls Underground Railroad Heritage Area Management Plan, Appendix C: Survey of Sites Relating to the Underground Railroad, Abolitionism, and African American Life in Niagara Falls and Surrounding Area, 1820–1880”, for Companies and Niagara Falls Underground Railroad Heritage Area Commission, April 2012.

Descendants of John Whitney, Who Came from London, England, to Watertown, Massachusetts

(7) K. Whalen, R. Austin, N. Montague, and D.J. Perrelli, 

Famed Cataract House Turned Into Mass of Charred Ruins

(10) R.F. Austin, “Analysis of Wall Plasters at the Cataract House Site, City of Niagara Falls, Niagara County, New York”, State University of New York at Buffalo, 2022.

 are with the Department of Chemistry and Chemical Biology at Rensselaer Polytechnic Institute, in Troy, New York. 

 is with the Department of Anthropology, at the State University of New York at Buffalo, in Buffalo, New York. 

 is with the Chemistry Department at St. Anselm College, in Manchester, New Hampshire. Direct correspondence to: 

Portable X-ray fluorescence was used to analyze the archaeological remains of an Underground Railroad station to gain a clearer understanding of the construction phases it underwent during the 19th century.

An Archaeometric Investigation into the Former Cataract House Hotel via Elemental Analysis

Open-path spectroscopy is known for its ability to provide real-time measurements of dozens of compounds over sampling paths of up to 1000 meters in length. Advances in open-path monitoring technology and data processing techniques, coupled with new regulatory requirements, have greatly increased the acceptance and widespread application of spectroscopy-based open-path measurements. Large industrial facilities adjacent to residential communities are a particular application of interest, because traditional fixed-point analyzers lack the spatial coverage of the open-path instruments. This work discusses technical and practical considerations for the installation and operation of more than 120 open-path analyzers that are currently providing continuous data at several oil refineries in California. Open-path analyzers include ultraviolet differential optical absorbance spectroscopy (UV-DOAS), Fourier transform infrared (FT-IR), and tunable diode laser (TDL) technologies. We will discuss lessons learned from these projects, including fundamental approaches to compound identification, target species detectability, interferences, and data management.

 refers to air quality measurements collected at or around the perimeter of a facility, and is typically performed at industrial facilities with processes that may generate airborne emissions. A fenceline monitoring network often contains a range of instrumentation depending on the facility and monitoring objectives. Figure 1 shows a generic example of a large monitoring network, including fenceline open-path, point, meteorological monitors, and community point monitors.

FIGURE 1: A large-scale monitoring system at a generic petroleum refinery with open-path, point, and meteorological monitors (collocated with fixed- point and community sites).

Motivations for fenceline monitoring often include compliance with regulations, addressing community concerns about fugitive emissions, or consent agreements. Most facilities conducting fenceline monitoring do so to comply with state or local regulations. For example, in 2017, California Assembly Bill 1647 (AB-1647) (1) mandated fenceline monitoring programs at petroleum refineries, to be regulated by local Air Districts. Examples of the local regulations include Regulation 12 Rule 15 (2) from the Bay Area Air Quality Air Management District (BAAQMD), Rule 1180 (3) from the South Coast Air Quality Management District (SCAQMD), and Rule 4460 (4) from the San Joaquin Valley Air Pollution Control District (SJVAPCD). Two smaller air districts—San Luis Obispo and Santa Barbara—also instituted regulations, but there are no active refineries in those areas that currently meet the required production levels. Each of these regulations require facilities to establish air monitoring systems to provide air quality data along refinery boundaries. Similar regulations, such as Colorado House Bill 21-1189 (5), have been passed within the past year, and more are expected in other states with large industrial manufacturing presences. These state and local rules enhance the breadth and depth of other recent federal fenceline regulatory requirements, such as the Refinery Technology Review via the Clean Air Act Section 112(d) that resulted in the widespread application of passive fenceline monitoring for benzene (6).

These industrial monitoring programs typically require real-time monitoring of a range of compounds over large distances, and at detection limits relevant for comparison to health thresholds. The measurements must meet strict uptime requirements, and be displayed on a publicly accessible website shortly after collection, in some cases requiring public alerts during an emission event. This unique combination of requirements requires a robust technical approach, for which open-path spectroscopy is particularly well-suited.

Open-path analyzers measure absorbance of airborne compounds between a light source and a detector. Different compounds have unique absorbance characteristics at discrete wavelengths which correspond to absorption spectra when scanning over a range of wavelengths. The agreement between measured spectra and reference spectra (the 

) is used to identify compounds present. Quantification is achieved by scaling of the reference spectra. The appropriate open-path analyzer is selected based on the absorbance wavelengths of the compounds of interest.

 uses a combined light source and detector at one end of the open sampling path and a reflector located several hundred meters away, thus effectively doubling the path length. Figure 2 shows an example of a monostatic configuration. A 

 has the light source and detector on opposite sides of the path, across a single path. Importantly, while an open-path system can measure compounds over a large distance (500+ meters), it cannot distinguish between a concentrated or dispersed plume within that path.

FIGURE 2: Operating principle of a monostatic open-path analyzer.

Differences between open-path spectroscopy techniques are primarily due to the light source used, which subsequently determines the available wavelengths for measuring compounds.

UV-DOAS analyzers contain an ultraviolet (UV) light source—commonly a xenon or deuterium lamp, operating in the range of 225 nm to 400 nm. Target compounds for UV-DOAS analyzers include air toxics such as benzene, toluene, ethylbenzene, xylenes, and sulfur dioxide. This instrument simultaneously measures multiple compounds in real time at a time resolution as fast as every 30 sec. Detection limits are down to low ppb and, in some cases, sub-ppb levels. Typically, one-way path lengths range from 300–700 meters for monostatic configurations, and up to 1000 meters for bistatic configurations.

FT-IR analyzers contain an infrared laser operating in the wavelength range of 670 cm

. Target compounds for FT-IR analyzers primarily include short-chain hydrocarbons, methane, aldehydes, ammonia, hydrogen cyanide, and other volatile organic compounds (VOCs). FT-IR analyzers can be used to measure multiple compounds simultaneously in real time at a time resolution of approximately once every two to three minutes. Similar to UV-DOAS, typical one-way path lengths range from 300–700 meters for monostatic configurations. Bistatic configurations are not typically used for FT-IR.

 uses a diode laser that emits a narrow wavelength of light tuned to a specified range of interest, which is typically in the mid-IR spectrum. This technique is typically used to measure a single compound of interest, with one or two additional compounds (such as water or methane) measured to verify operations under normal ambient conditions. Example compounds measured by this instrument include hydrogen sulfide, hydrogen cyanide, and hydrogen fluoride.

With current regulations (see above) requiring detection of compounds at or below health thresholds, there has been increased focus on how to achieve the lowest possible detection limits for each compound of interest. In addition, the standardization of methodologies to calculate the minimum detection limits (MDLs) has become a growing topic of discussion. Broadly speaking, laboratory-derived MDLs do not represent actual performance in real-world applications, and real-world MDLs are dependent on operating conditions and interference from other similarly absorbing compounds.

Currently, there is no broadly accepted standard for MDL determination with open-path spectroscopy. Two common approaches include the U.S. Environmental Protection Agency (EPA) 

Compendium of Methods for the Determination of Toxic Organic Compounds in Ambient Air

American Society for Testing and Materials (ASTM) International Standard Test Method for Determination of Gaseous

Compounds by Extractive Direct Interface Fourier Transform Infrared (FT-IR) Spectroscopy

, known as ASTM D6348-03 (8). Both techniques generally provide similar results, but differ in their technical approach, and therefore implementation.

Selection of the instrument type to deploy depends on the compounds of interest. Many fenceline monitoring networks require a combination of open-path technologies to provide comprehensive coverage of many target compounds. TDL open-path analyzers generally provide single-gas measurements, where UV-DOAS and FT-IR can simultaneously monitor dozens of compounds in real time.

The definition of “real-time monitoring” depends on the regulatory driver, or the program goals, but most open-path analyzers can provide real-time measurements every five minutes and MDLs below health thresholds. Typical instrumental time resolutions of UV-DOAS, FT-IR, and TDL open-path analyzers are on the order of 30 sec, 3 min, and 5 min, respectively. If possible, it is preferable to select open-path analyzers that retain raw instrument data independent of calibration, which may be used at any time to verify real-time measurements.

Detectability of target compounds in the presence of atmospheric interferents is an important consideration in designing open-path fenceline monitoring networks. Many compounds can be measured by multiple types of open-path analyzers, but the appropriate open-path technology should be selected to meet the needs of the monitoring program. For example, benzene—a common target compound—can be measured by UV-DOAS and FT-IR open-path spectroscopy, but the two techniques have significantly different detection capabilities. For benzene, the Agency for Toxic Substances and Disease Registry (ATSDR) cites an inhalation reference concentration (RfC), which is an estimate of the concentration that a population can be exposed to without an “appreciable risk” of noncancer health effects, of 9.4 ppb (9). The Refinery Risk and Technology Review regulation cites benzene concentrations down to 2.8 ppb (10), and the California Office of Environmental Health Hazard Assessment (OEHHA) acute benzene REL of 8.6 ppb (11), so applications that require comparison to the applicable health thresholds must be capable of measuring well below them. With an appropriate application of these technologies (in this case UV-DOAS, and not FT-IR), these health-based fenceline concentration limits can be achieved (12).

Figure 3 shows absorbance spectra for benzene in the FT-IR and UV-DOAS spectral analysis regions, which illustrate the differences in detectability for these techniques.

FIGURE 3: Representative benzene absorbance spectra in the (a) FT-IR and (b) UV-DOAS spectral analysis regions.

As an example, for FT-IR analysis of benzene, the maximum usable absorbance units (AU) amplitude is 0.006 AU at 1037 cm

 is extremely sensitive but is obscured by interfering CO

 absorbance in ambient long path open-path applications. While FT-IR can be used to monitor benzene, the practical minimum detection limit (MDL) is on the order of greater than 100 ppb for a 300 m path, which is significantly higher than the applicable health thresholds. For UV-DOAS analysis of benzene, the maximum usable absorbance amplitude is 0.26 AU at 253 nm, and the practical MDL is on the order of less than 1 ppb for a 300 m path. Therefore, for applications requiring fenceline monitoring of benzene with comparison to health thresholds, UV-DOAS open-path spectroscopy is the ideal technique.

Some target compounds with few unique spectral features or spectral overlap with atmospheric interferents can be challenging to measure with open-path spectroscopy. An example of this is hydrogen sulfide—associated with a variety of industrial processes—which has an OEHHA (13) Acute Reference Exposure Level (REL) of 30 ppb (also the California 1-hour air quality standard [14]). Hydrogen sulfide can be measured by UV-DOAS open-path spectroscopy, but absorbance spectrum overlap with benzene, and other aromatics may result in false positive detections. FT-IR open-path spectroscopy can be used, but the MDL is commonly too high. The preferred technique for open-path monitoring of hydrogen sulfide is TDL, with high selectivity and lower detection limits compared to other available open-path technologies. Moreover, recent advances in signal processing and wavelength modulation approaches have allowed for enhanced signal-to- noise (S/N) ratios, more robust data post-processing, and lower MDLs (on the order of 25 ppb for a 300 m path). These technological advances have precipitated regulations from local air districts in California to encourage use of TDL for open-path monitoring of hydrogen sulfide.

Table I shows considerations for selecting an open-path technology for hydrogen sulfide monitoring based on selectivity, detectability, time resolution, single-gas or multiple-gas capability, and cost.

Considerations for installation of open-path analyzers can vary depending on the facility. For example, topography or fenceline perimeter distance typically determines the number instruments needed. Another consideration is whether a facility needs total fenceline coverage, or if partial coverage may be sufficient because of the proximity to local communities and typical wind conditions. Short paths with temporary installation may be achieved with basic tripods for the analyzer components, whereas permanent installations with longer pathlengths require more substantial infrastructure, such as concrete foundations or support pillars. If a monostatic configuration is selected, power and shelter requirements can be reduced to one side of the path, as those requirements for a reflector on the other side are minimal, or in some cases unnecessary. A bistatic configuration requires power and shelters at both ends of the path. In either case, placement of sampling paths can be optimized to minimize the total number of power and shelter installations to reduce costs while meeting the program objectives. As open-path analyzer operations depend on the amount of light that returns to the detector, instrument alignment is a critical component of continuous operations. Monostatic configurations double the effective pathlength, which can be helpful for achieving lower detection limits, but necessitates more frequent alignment. Conversely, bistatic configurations may achieve shorter paths that the light travels and require less-frequent alignment. Regardless, robust and stable infrastructure is critical.

Fenceline monitoring programs that incorporate open-path spectroscopy typically require an up-front capital investment from the facility. Although the per-analyzer cost may be greater for open-path technologies as compared to traditional point monitors, the spatial coverage provided by open-path analyzers is usually comparable to that provided by several point monitors. Moreover, depending on the target compounds and the corresponding point monitor technology, ongoing operations and maintenance activities may provide cost savings over time for open-path installations as compared to point monitors. The cost-benefit analysis of open-path vs. point monitors is a consideration when designing the fenceline monitoring program and will ultimately depend on the goals of the program and the regulatory drivers.

All fenceline monitoring programs require a data management system for the ingest, storage, quality control, and dissemination of data. Programs that require data display to the public in real time necessitate additional infrastructure, such as reliable internet connection at each sampling site and an automated quality control approach that can filter unreliable data points in real-time.

Depending on the size of the fenceline monitoring system, data flow can be on the order of 250 data points every five minutes, or 6.5 million data points per calendar quarter. Therefore, a robust data management solution is needed for this scale. Data quality control is typically performed in several ways. On a real-time basis, the data management system performs quality control based on instrument diagnostics to ensure proper operations, and flag data according to their quality indicators. Qualified personnel subsequently review the data on a daily, weekly, monthly, and/or quarterly basis, and may generate reports depending on the requirements of the program. For projects that require real-time display on a publicly accessible website, data must be displayed shortly (10–20 min) after they are collected. This requires rigorous automated quality control to minimize false positive alerts and ensure alerts are issued during potential emission events. Additional analysis tools may be used in conjunction with the data management system, such as source-receptor analysis metrics to assess origination of detections at the fenceline, as well as where potential emissions may travel based on local meteorological conditions.

Over the past five years, over 120 open-path analyzers (along with dozens of meteorological and point monitors for other compounds) have been installed and operated at the fenceline of several large oil refineries in California. Similar programs exist in other states or are under consideration. The open-path monitor types employed include UV-DOAS, FT-IR, and TDL, depending on the target species and site characteristics. These analyzers measure many key pollutants defined by regulatory or other site requirements at detection limits appropriate for the specified health-based standards. The open-path instruments cover large fenceline distances and provide better coverage than traditional point instruments, though point monitors are used for target compounds not suited to be measured by open-path methods. Besides the instrument selection process, robust infrastructure and data processing systems are critical elements due to the high data throughput and demanding public reporting requirements. These operating installations continue to successfully provide continuous data for public and regulatory use.

Assembly Bill No. 1647, Chapter 589, AB-1647 Petroleum refineries: air monitoring systems

https://leginfo.legislature.ca.gov/faces/billTextClient.xhtml?bill_id=201720180AB1647

(2) Bay Area Air Quality Management District, Air District Regulation 12, Rule 15: Petroleum Refining Emissions Tracking. Available at 

https://www.baaqmd.gov/~/media/files/planning-and-research/rules-and-regs/workshops/2015/1215-1216-workshop/1215_amg_-01282015.pdf

(3) South Coast Air Quality Management District, Rule 1180: Refinery Fenceline and Community Air Monitoring. Available at 

http://www.aqmd.gov/docs/default-source/rule-book/reg-xi/r1180.pdf?sfvrsn=9

(4) San Joaquin Valley Air Pollution Control District, 

Rule 4460: Petroleum Refinery Fenceline Air Monitoring

https://www.valleyair.org/Workshops/postings/2022/08-15-22/Proposed-Rule-4460.pdf

The implementation of 120 open-path spectroscopy analyzers at oil refineries has taught us lessons about compound identification, target species detectability, interferences, and data management, which can help spectroscopists generate more accurate data when monitoring air quality.


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