## 2 Review of Related Works  
In most state-of-the-art gas sensing systems using WMS, there are two approaches. In one, the raw transmitted signal is digitised and then sent to the high-level processor, with nearly all processing (i.e., the harmonics extraction as well as the computations of 2f/1f) done on the high-level processor offline [15; 16]. While this approach generally achieves high accuracy of the detected gas parameters, it places a huge burden on the data transfer link between the sampling circuits and the high-level processor. This often leads to lowering the scan rates, hence reducing the temporal resolution. In addition, the offline processing of this approach could limit its real-time requirements. In [15], the use of tuneable diode laser wavelength modulation spectroscopy (TDLS-WM) to measure CO\({}_{2}\) concentration and temperature in the exhaust plume of an aero engine is outlined. The 2f/1f tuneable diode laser wavelength modulation spectroscopy technique was used to perform single-path measurements of measure CO\({}_{2}\) concentration and temperature. The measurement results demonstrated high accuracy and confirmed the capability of the 2f/1f technique to provide reliable, in situ measurements of CO\({}_{2}\) concentration and temperature in harsh environments. However, in the work, transmitted signals are digitised in real time, while the harmonic extraction is carried out offline. In the same vein, ref. [16] presents a method for detecting six different gases (methane (CH\({}_{4}\)), ethane (C\({}_{2}\)H\({}_{6}\)), acetylene (C\({}_{2}\)H\({}_{2}\)), ethylene (C\({}_{2}\)H\({}_{4}\)), carbon monoxide (CO), and carbon dioxide (CO\({}_{2}\))) simultaneously using a system based on wavelength modulation spectroscopy (WMS). Data processing is handled by a Raspberry Pi using Python, and detection signals are demodulated using digital quadrature lock-in amplifiers. Harmonic extractions are carried out offline. The key advantage of offline processing is that the harmonic extraction process can leverage the full bits resolution on a high-level processor, leading to very high accuracies. However, large amounts of raw data are required to be transferred in real-time with significant bandwidth requirements. In the second approach, the DAQ not only digitises the transmitted signal, but it also extracts the harmonic information. Specifically, partially processed samples, whereby the demodulated in-phase (I) and quadrature (Q) components for both the first and second harmonics, are transferred to the high-level processor [6; 12; 17]. In this standard I-Q approach, the on-chip processing significantly reduces the load on the data transfer network and improves the real-time potential of WMS systems. However, four-components (i.e., two in-phase and two quadrature components) are generated for a set of transmitted signal samples. Transmitting these components to the processor in a bandwidth-constrained environment is often challenging. As a result, bit truncation is used to cope with the bandwidth requirements of most practical DAQ systems. The work in [17] presented a quasi-parallel DAQ for WMS. The method used involves multiplexing multibeam signals over high-frequency modulation within a wavelength scan to minimise the hardware requirements of the data acquisition system. Demodulation of the WMS signal is realised on-chip in real time, extracting the first and second harmonic I-and-Q components before sending these to the high-level processor. Similarly, ref. [6; 12] accomplished on-chip demodulation, resulting in four components. In state-of-the-art I-Q demodulation techniques, four harmonic components are transferred in real-time to the high-level processor. Although this technique has the potential to minimise the amount of data transferred compared to the raw data transfer technique, the demodulation process leads to an increase in the number of bits of harmonic components resulting from raw samples.