## 3 Results and Discussion
### Mitigation Measures to Reduce Methane Emission  
Diversion of solid waste from disposing to landfill is the fundamental pathway to reduce methane emission [1]. However, rarely are there clear guidelines available in Saudi Arabia on methane reduction based on different waste disposal scenarios. Figure 7 predicts the reduction of methane emissions due to waste diversion from landfills in 16 combinations of municipal as well as industrial waste between the year 2020 and 2050. As can be seen from Figure 7, for a 100% disposal (zero diversion) of municipal solid waste, methane emission can be reduced by 21%, if industrial waste disposal can be diverted by 25%. It was possible to further reduce the methane emission by 42% and 63% for a reduction of industrial waste disposal by 50% and 75%, respectively. The prediction clearly identifies that more attention is needed in Saudi Arabia for diverting industrial waste from landfills. In fact, the Saudi government has realized such a need of diverting industrial waste and has adopted several measures to reduce the disposal of industrial waste to landfills. According to GAS [49], in Jubail industrial area, 34% of industrial waste was  
Figure 6: Historical and predicted CH4 emission from MSW in major cities in Saudi Arabia between 2015 and 2025 (methane emission was calculated based on population data from the United Nations [51]). recycled in 2010, which increased to 54% in 2018; 41% of the industrial waste was landfilled in 2010, which decreased to 34% in 2018. It is obvious from Figure 7b-d that more reduction of methane emission is possible when MSW is also diverted from the landfill. However, the reduction of methane emission is more sensitive to industrial waste diversion compared to municipal waste. The phenomenon is presented in Figure 8. A sensitivity analysis was carried out to identify which waste diversion is crucial to the reduction of methane emission by assuming 50% disposal of both types of waste as the standard practice. It was observed (from Figure 8) that for a reduction of 25% disposal, emission from industrial waste was reduced by 38%, which was 27% for municipal solid waste. The findings again iterated that recycling and other types of mitigation measures will be more effective in reducing the methane emission in Saudi Arabia if applied to industrial waste. Figure 8: Sensitivity analysis of methane emission to waste diversion. Figure 7: Impact of waste diversion from landfills on CH\({}_{\textbf{4}}\) emission between 2020 and 2050 (**a**) diversion combinations of MSW of 0% with industrial waste of 0%, 25%, 50%, and 75%, respectively (**b**) diversion combinations of MSW of 25% with industrial waste of 0%, 25%, 50%, and 75%, respectively (**c**) diversion combinations of MSW of 50% with industrial waste of 0%, 25%, 50%, and 75%, respectively (**d**) diversion combinations of MSW of 75% with industrial waste of 0%, 25%, 50%, and 75%, respectively. Achievement of the above-mentioned disposal reduction is possible by utilizing several mitigation initiatives. For example, adaptation of 4R (i.e., reduce, reuse recycle, and recovery) approach could generate less waste and consequently less methane gas [57]. Waste-to-energy (WTE) tools such as incineration, pyrolysis, refuse derived fuel (RDF), or anaerobic digestion with biogas recovery approach could be implemented to reduce methane emissions in Saudi Arabia. Energy content of waste could be directly converted to steam or electricity through WTE technology [58]. Electricity and heat generation efficiencies for WTE systems were reported to be in the range of 18-35% and 63-78%, respectively. However, simultaneous production of power and heat was reported to have 83% efficiency [59; 60; 61]. Combustion efficiency of 25% was assumed by some reports in calculating the WTE for Saudi Arabia [62]. Recent studies using multi-criteria analysis done for the GCC countries showed that among the WTE technologies, anaerobic digestion (AD) and landfill gas recovery had the best and gasification had the worst model result [54].