# On the Potential of the RST-FLARE Algorithm for Gas Flaring Characterization from Space
## 5 Discussion  
In this paper, the RST-FLARE algorithm, aimed at detecting flaring sites and computing the volumes of gas annually flared by these sources at national scale, by processing multi-year time series of nighttime MODIS infrared imagery, is presented. In detail, its performances when applied to the Niger Delta region, an area where gas flaring associated with petroleum exploration is contributing immensely to air pollution, are shown and discussed. In general, the results achieved confirm the RST-FLARE potential in providing quite reliable information on gas flaring activity in Niger Delta. The proposed method has been validated, in terms of temporal trend and spatial distribution of flaring sites, as well as of annually emitted gas volumes at national scale, by using different independent sources. An agreement between 74% and 95% versus MODET and VNF products was \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Max Bias** & **Min Bias** & **Mean Bias** \\ \hline
**RST-FLARE OPEC-based** & 78.4\% & 0.3\% & 19.7\% \\
**RST-FLARE EIA-based** & 67.0\% & 0.8\% & 15.9\% \\
**MOVET** & 78.9\% & 3.2\% & 34.1\% \\
**VNF** & 42.5\% & 6.2\% & 24.9\% \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Biases between NNPC and RST-FLARE, MOVET and VNF estimates. found when flaring sites were detected. Using the annual BTE values in the linear regression models provided satisfactory estimates of gas flared volumes, with a mean bias in between 16% and 20%, in the annual computation, decreasing up to 2% in the long period one. With reference to the BTE metric, it is very interesting to note its good agreement with the information reported in Section 3.1, referred to the history of Nigerian oil and natural gas productions as well as with the variation of flaring sites (black line in Figure 5). Regarding this aspect, it is very interesting to note that on years 2014-2016, a reversal behavior of gas flare numbers and BTEs is observed. In these years, in fact, the emissive power (BTE) decreases of about 68% while the number of flaring sites increases of about 77%. This seems to confirm the headway into drastically reducing the flaring of associated gas in Niger Delta, achieved through aggressive gas commercialization as said the NNPC Group General Manager [42]. Also online information, referring to the evolution of Nigeria gas flaring [11; 43; 44] are in line with BTE estimates confirming the decreasing of such a phenomenon in the Niger Delta basin. As reported by GGFR, in Nigeria alone gas flaring amounts to about 23 BCM per annum in over 100 flare sites, constituting over 13% of global gas flaring [44]. In the recent years, Nigeria, traditionally one of the highest flaring countries, has made significant progress to enforce zero gas flaring policy, reducing it by 18% since 2013, to less than 8 BCM in 2015 [44]. Although these satisfactory achievements, residual errors and inaccuracies have been identified and are briefly discussed in the following. 1. The first cause of inaccuracy in effectively discriminating flaring sites in the Niger Delta region could come from the use of the MIR signals. Considering that gas flares typically operate at temperatures \(>\)1400 K, with a peak spectral radiant output occurring in the SWIR region [7], at MIR wavelengths their emissions are significantly minor (about one third of the signals emitted in the SWIR region). This could result in an under estimation of flare spectral response, especially for the hottest sources [7; 25; 26]. However, RST-FLARE, thanks to its differential and self-adaptive nature (i.e., exploiting locally derived, in space and time domains, rather than fixed thresholds to identify signals above background), enables the identification of flaring sites over the considered long-period with a good accuracy level when compared with both ancillary data and satellite methods.