Air Monitoring 21
Carbon emissions calculation according to the MRR: CO2
• CO2 Emission can be expressed as tCO2 Emission = Flow × NCV × CEF × Oxidation Factor /TJ (Energy), tCO2 • Flow of natural gas is representative of the activity data
• Net Calorifi c Value (NCV) is the amount of heat released by the complete combustion with oxygen, under standard conditions, of a specifi ed quantity of natural gas excluding the condensation heat of water
• Carbon Emission Factor (CEF) is the quantity of equivalent CO2 used
• Oxidation Factor is the ratio of carbon oxidised to CO2 carbon contained in the natural gas
emitted per kWh of natural gas because of combustion to the total
While the fl ow is measured by a calibrated fl ow meter, there are three approaches for determining NCV and CEF through the analysis of natural gas composition. The fi rst option, for sites not using a process GC, is to collect weekly on-site natural gas samples, which are sent to an ISO 17025 accredited laboratory for analysis. This method is costly, demands logistical coordination, and provides only a snapshot sample, rendering the singular outcome non-representative. The second method is to validate the on-site process GC results through a sample sent to an ISO 17025 accredited laboratory for analysis. This validates the GC’s performance at a single point, and it does not ascertain its effectiveness across various compositions of natural gas (table 1).
Table 1 – Example of typical natural gas composition ranges – Components content in %mol/mol Component
Carbon Dioxide Ethane
Isobutane
Iso-Pentane Methane n-Butane
Neo-pentane n-Hexane Nitrogen
n-Pentane Propane
min
0.050 0.100 0.010 0.005
64.000 0.010 0.005 0.005 0.100 0.005 0.050
max 8.00
14.00 1.20 0.35
98.50 1.20 0.05 0.35
12.00 0.35 8.00
The third method is the performance evaluation of the process GC using ISO 10723. A process GC is often already in place on-site, incurring no additional capital costs.
Performance Evaluation Using ISO 10723
ISO 10723 provides a standardised approach to assess the process GC performance over a range of expected natural gas compositions. Conducted annually, these quantitative measurements involve injecting a suite of 7-10 ISO 17025 accredited secondary reference gas mixtures with different natural gas compositions to offer a comprehensive evaluation of the instrument’s performance, providing evidence of its usable range, linearity, accuracy, bias and uncertainty.
Performance Evaluation Process:
1. The data from each of the reference gases, injected individually, is used to establish the relationship between the instrument’s ‘actual response’ and the known reference compositions (fi gure 3).
Figure 4 – Comparison of results when operating in Type 2 and Type 1 modes – Red markers show the spread of results in Type 2 mode with linear response function. Blue markers show the spread of results in Type 1 mode, with signifi cant less spread of results and almost zero errors
Conclusions
In light of the ongoing climate crisis and the relevant evolving legislation, the European Emission Trading Scheme remains a crucial tool for driving carbon emissions reduction. Robust procedures – such as the ISO 10723 performance evaluation of process gas chromatographs – ensure accurate and reliable monitoring and reporting results. Implementing annual performance evaluations improves the accuracy of determining site-specifi c factors (i.e. NCV, CEF) for more precise carbon emissions calculation, providing operators within the EU-ETS with greater opportunities to save costs while trading carbon allowances.
/t (Mass) or tCO2 /Nm3 (Volumetric)
2. These results are then plotted, and a best fi t line established for the ‘true response’ required for each individual component. The best fi t line could be linear, quadratic or cubic. These co-effi cients are known as the ‘analysis functions’ and can be used to measure the individual component amounts in a gas sample most accurately. Operating in this way is known as Type 1 mode (ISO 6974-14
).
3. A Monte Carlo simulation – which simulates 30,000 gas compositions – is initially performed with the instrument in its normal process operating mode, which could be Type 1, using the analysis functions from a previous evaluation, or Type 2, using single-point calibration. The results determine whether the instrument meets requirements for bias and measurement uncertainty, in terms of Maximum Permissible Bias (MPB) and Maximum Permissible Error (MPE). MPB and MPE would typically be specifi ed by the gas network operator.
4. If the instrument is close to or outside the limits for MPB and MPE, an improved design of calibration gas can be modelled that reduces the errors by calibrating at a different point. Uncertainties can also be minimised by using calibration gas with smaller uncertainties. The Monte Carlo simulation would then be re-run and in many cases the MPB and MPE would be reduced to acceptable levels.
5. The fi nal, optional, stage – if the instrument can be operated in Type 1 mode – is to implement the analysis functions from step 2 (fi gure 4). Re-running the Monte Carlo simulation with these analysis functions can deliver a signifi cant improvement in the MPB and MPE.
1 2
Directive 2003/87/EC Commission Implementing Regulation (EU) 2018/2066
3 ISO/IEC 17025 – General requirements for the competence of testing and calibration laboratories 4
ISO 6974-1 – Natural Gas – Determination of composition and associated uncertainty by gas chromatography. Part 1 General guidelines and calculation of composition
Author Contact Details Roberto Parola, Senior Technology Expert • Linde GmbH • Dr-Carl-von-Linde-Strasse 6-14, 82049 Pullach, Germany • Tel: +49 89 7446-2167 • Email:
roberto.parola@
linde.com • Web:
https://www.effectech.co.uk/products-and-services/performance-evaluations-and-inspections/
Figure 3 – Non-linear response errors
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