Selection of Emission Factors for LDAR Monitoring with Handheld Tunable Diode Laser Methane Detectors

Growing concern about the threats of global warming attracts attention to greenhouse gas emission control. Natural gas consists of mainly methane, a gas with strong global warming potential. The oil & gas industry implements Leak Detection and Repair (LDAR) programs to curb uncontrolled methane emissions. There is a range of tools used for LDAR monitoring.

By Eugene Kolonsky, Ph.D.a, Semen Neverovb, Alexei Gribovc and Johan Wictord

Test Design and Results

The Goal of the Experiment

The goal of the experiment is to answer the following questions:

  1. How sensitive to leaks is TDL detector at the range of its working distances? In other words, what is the leak defi­nition threshold in grams per hour (g/h), for which operator with TDL detector can reliably distinguish a leak (emission over the leak definition threshold) from a no-leak (emission lower the leak definition threshold or zero emission).
  2. What is the TDL detector readings threshold in ppm×m, corresponding to this leak definition threshold in g/h?

Equipment and Materials Used

The test stand photo is shown in Fig­ure 1. The test stand scheme is shown in Figure 2.

Stand elements:

  1. A Gas cylinder with 98% methane equipped with a valve and reducer.
  2. Gas mass flow rate meter MV-302.
  3. Handheld TDL detector LaserMeth­ane mini by Tokyo Gas Engineering Solutions. Measurements interval: 1 – 50 000 ppm×m; graduation inter­val: 1 ppm×m; readings frequency: 2 readings per second.
  4. Laboratory equipment: a portable table for equipment, measuring tape, wiring, gas cylinder support, a smartphone for recording TDL detec­tor screening data.

Test Design

All measurements are taken at open air to eliminate background methane con­centration bias. Measurements were taken during 3 days with mild weath­er at day 1 and day 2 (temperature 25C, wind from 0 to 3 m/s), and windy weather on the day 3 (temperature 12C, wind up to 6 m/s).

  1. Measurements are taken with the fol­lowing parameter space:

a. Leak rates are set according to the leak definition at Table 1: 3, 6,  30, 60 g/h, extended with zero leak 0 g/h and a ‘big leak’ at 100 g/h.

b. Observation distances: ½, 2, 4, 6, 8, 10, 12, 15, 20, 25, 30 m.

c. Controlled leaks are observed at sources imitating a valve and a flange.

Figure 1. Test stand photo.
Figure 2. Test stand scheme.

2. Each observation is conducted in the following way:

a. Ensure that gas cylinder connected to the controlled leak source through reducer and mass flow meter;

b. Open gas cylinder valve and set gas flow rate; then wait 5-10 seconds to let the gas flow stabilize.

c. Record actual mass flow mereadings.

d. Start taking readings of a TDL detector. Readings are collected for 60 seconds until ~120 data points are collected. Collect data thoroughly as recommending by Method 21 [9].

e. Close gas cylinder valve;

f. Change experiment parameters (distance, leak rate, target source).

g. Repeat for a new observation with new parameters.

Figure 3. Excluding outliers from TDL detector readings data with sliding window smoothing method. On the figure is shown data from observation #27.
Figure 4. Dataset overview. In the rows - leak source types: either valve or flange. In columns – leak rates: 0, 3, 6, 30, 60 and 100 g/h. Each plot shows dependence between TDL smoothed maximal readings on log-scale y-axis and observations distance on x-axis at the fixed leak rate for a given leak source. Reference lines are drawn at 400 and 200 ppm×m.

Test Results Dataset Description and Data Clean-up

Raw data dataset contains 11,570 readings collected over 95 observa­tions.

As recommended by Method 21,9 the readings are taken thoroughly and then the maximal screening value should be taken. Observations might have outliers (see Figure 3). To exclude these outliers data is smoothed over sliding window be­fore taking the maximum. The width of the window is empirically set to four consequent readings, i.e. ap­proximately two seconds.

For each observation, a smoothed max­imum ppmm is calculated as a maxi­mum of sliding window mean values.

The cleaned-up dataset has one re­cord for each observation, with the following columns (Table 2).

Table 2. Cleaned-Up Dataset Columns Description.
Figure 5. All observations of the dataset on one scatter plot. Each point is one observation. As on Figure 4, TDL smoothed maximal readings on log-scale y-axis and observations distance on x-axis. Point size corresponds to the leak rate. Threshold lines are drawn at 400 and 200 ppm×m.

Dataset Exploration and TDL detector threshold suggestion

An overview look on the data col­lected on multiple plots is shown on Figure 4.

Note that TDL detector even for non-leaking sources returns non-ze­ro readings with magnitude from 50 ppm×m up to nearly 200 ppm×m. This could be explained by the ambient methane in the air detected by this high-sensitive tool.

At the leak rates 3 g/h and 6 g/h, TDL readings at distance 5m and more could be less than 200 ppm×m, overlapping with TDL readings for non-leaking sources. That means that small leaks cannot be reliably distin­guished from zero-leaks when the operator with TDL detector stands far enough from the source.

Table 3. Leak/No-leak Emission Factors for TDL detectors,

For leak rates 30 g/h and 60 g/h TDL detector returns readings over 400 ppm x m at all working distances. That means that these big enough leaks can be reliably detected by TDL operator, when TDL readings thresh­old is set to 400 ppm×m.

The TDL readings threshold line (red line at Figures 4 and 5) makes a bina­ry classifier for the leak\no-leak binary classification task. The quality of a bi­nary classifier is defined in terms Pre­cision and Recall16. The best quality with Precision = 0.77 and Recall = 1.0 is achieved for the leak rate thresh­old 30 g/h and over at TDL readings threshold 400 ppm×m for all operat­ing distances up to 30m. Note that it is possible to decrease leak threshold to 6 g/h by decreasing operation dis­tance to 5m, which is not suitable for all facilities.


Handheld TDL gas methane detectors could be suggested as a standalone tool for methane LDAR monitoring. It is possible to operate at distances up to 30 meters, but it is recommended to take the most of the observations at working distance up to 10-15 m, since the TDL detector ability to de­tect leaks degrades with the distance.

The TDL detector readings thresh­old, averaged over 2s window time, should be set at 400 ppm×m level. For this threshold leaks with mass rate 30 g/h and over are reliably de­tected. Some leaks with mass leak rate less than 30 g/h could be missed, especially at long distances.

For the leak emission mass quantifi­cation purposes it is recommended to take EFs for leak definition thresh­olds 30 g/h or 60 g/h from the Table 1. The selection is shown at Table 3. It is suggested that the result, validated experimentally for sources imitating valves and flanges, is valid for all component types.

a) Sibintek Ltd, Rosneft subsidiary; Haifa, Israel;; Dr. Eugene Kolonsky is an expert in the carbon management. Eugene has designed guidelines for methane Leak Detection and Repair (LDAR) programs implementation and methane leak emission quantification for upstream facilities and assisted in the launch of the world’s largest LDAR service in the Rosneft upstream segment. A former CIO and external expert in LUKOIL, he designed management systems for LUKOIL subs in Russia, Uzbekistan, Kazakhstan, UAE and Iraq (logistics, major capital projects, professional services automation). Eugene holds an MA degree in mathematics and a PhD in mechanics.
b) Pergam-Suisse AG, Zurich, Switzerland; \ ; Semen Neverov is a Head of Research and Development department in Pergam Group. He working in non-destroy area since 2011 and currently have a few articles and patent in remote gas leak detection with active laser. MS in Optical Science, PhD in multispectral cameras. His last interest is in LDAR service and reduction of fugitive emission.
c) Sibintek Ltd, Rosneft subsidiary; Moscow, Russia;; Alexey Gribov is an engineer in Rosneft- Sibintek carbon management team. As a technology expert Alexey is responsible for field engineers support, problem solving and staff training. Alexey designed test stand for this research and collected raw data. Alexey holds a Master degree in sociology.
d) Johan Wictor, Pergam Technical Service, Renton, USA; jwictor@ pergamusa.comJohan Wictor is a General Manager of Pergam Technical Service Inc. He has 20+ years experience in non-destroy testing and an expert in the carbon management. Johan is a very focused and energetic sales leader of laser remote detectors and acoustic cameras.


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  16. Google, “Google Developers Crash-course. Classification: Precision and Recall,” [Online]. Available:
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