1. Introduction
Solid waste management remains a persistent global issue, and the situation in the Philippines exemplifies the challenges and opportunities in addressing it. Between 2012 and 2016, the Philippines saw an increase in daily waste generation from 37,427 tons to 40,087.45 tons, or about 0.40 kg per person per day. This situation is most acute in the densely populated and economically active National Capital Region (NCR), which produces the largest volume of waste. Moreover, the issue of solid waste is linked with climate change, particularly through the emission of methane, a potent greenhouse gas (GHG). Methane emissions, 60% of which are anthropogenic, contribute significantly to global warming [
1]. Methane is a greenhouse gas (GHG) that is 25 times more potent than carbon dioxide [
2], making its capture and recovery from landfill gas (LFG) crucial in preventing unexpected combustions in landfills. Such combustions can produce more methane and exacerbate global warming when methane escapes into the atmosphere. The Philippines aims to reduce short-lived climate pollutants (SLCPs) from the municipal solid waste sector by 2025, 2030, and 2040 [
3], as seen in its two of the seven main strategies that focus on reducing methane emissions by preventing further methane generation and treating existing methane at disposal sites. The targets for these strategies were validated using the Emission Quantification Tool (EQT) based on a January 2018 cost–benefit analysis (CBA) study. In the Philippines, key sectors such as agriculture, coal mining, and municipal solid waste management account for 18% of the country’s methane emissions, approximately 7.1 MMTCO
2e [
4]. The adverse effects of methane on both the climate and human health, due to its transformation in the troposphere, motivate the need for concerted efforts to mitigate these emissions [
5]. In 2005, human activities such as agriculture, fossil fuel production, and waste management were the source of 93% of methane emissions globally and projections indicate a potential increase of 25% in anthropogenic methane emissions by 2030 if no mitigation strategies are implemented, highlighting the critical need for action [
6]. In the context of waste management, the evolution of landfills from mere waste disposal sites to facilities with significant pollution potential has led to stricter regulations. These include criteria for the strategic location, preparation, and maintenance of landfills to prevent adverse environmental impacts and safety hazards. A 2014 study by the National Solid Waste Management Council (NSWMC) on sanitary landfill facilities (SLFs) in the Philippines highlighted the rapidly changing landscape of landfill operations and the importance of implementing waste management mitigation options sooner rather than later, particularly in anticipation of 2020, which was projected to have the highest number of operational SLFs. The development and implementation of sound policies by Philippine government units, informed by comprehensive economic and financial analyses, is crucial for the effective management of solid waste and mitigation of methane emissions, addressing not only environmental and health concerns but also contributing to the sustainable development of the country [
1,
4,
5,
6].
Several studies have effectively harnessed the Long-Range Energy Alternatives Planning (LEAP) system for robust energy planning, employing scenario analysis and energy projection planning to chart pathways toward sustainable energy futures. One of them is the work by Ref. [
7], which leveraged LEAP for energy planning processes in the West Java region towards alternative and renewable energy sources. In a similar vein, Ref. [
8] quantified energy demands while evaluating the environmental and socio-economic impacts of renewable energy adoption in Zhangjiakou, offering a forward-looking projection of energy consumption and associated GHG emissions across various sectors for the 2016–2050 period. The insights revealed the tangible benefits of renewable energy, notably in GHG mitigation, job creation, and cost efficiencies compared with traditional energy systems. The integration of sustainable energy planning with economic insights, as introduced by Ref. [
9], emphasizes a strategic approach aimed at minimizing energy consumption while optimizing economic outcomes. This perspective aligns with the endeavors of Ref. [
10], who utilized LEAP for comprehensive scenario analyses targeting the electricity sector in Bangladesh from 2022 to 2041, with an eye on navigating and surmounting emerging power challenges. The research conducted in Korea by Ref. [
11] presents a case study in employing LEAP to evaluate the economic and environmental implications of adopting landfill gas (LFG) methods for electricity generation, revealing a potential reduction in the global warming potential by 75% through the expanded use of LFG compared to conventional methane release practices. The critical role of municipal solid waste (MSW) as a significant methane emission source, and its potential for mitigation through energy recovery, was studied by Ref. [
12], with subsequent studies like that of Ref. [
13] using LEAP to envision scenarios that capitalize on renewable energy sources, including MSW, thus showcasing an anticipated annual growth rate of 39% due to the increasing volume of solid wastes. In Ghana, the work by Ref. [
14] presents a forward-thinking application of LEAP in modeling energy production, consumption, and resource extraction processes, aiming at a strategic replacement of fossil fuels with biomass-based alternatives and energy generation from MSW through landfill gas capture technologies. This endeavor anticipates renewable sources contributing 10% to the total electricity generation capacity. The integration of the IPCC model for methane flow rate estimation with LEAP, as demonstrated by Ref. [
15] in Tehran, highlights the development of two pivotal scenarios: business-as-usual (BAU) and Sustainable-Waste-Management (SWM), highlighting the cost implications and environmental benefits of LFG plants and advocating for their strategic role in reducing environmental concerns under the SWM scenario. The cost-effectiveness of landfilling, especially in converting poorly managed dumpsites into effective LFG recovery projects, was emphasized by Ref. [
16], pointing to a pathway for reducing GHG emissions from landfills and aligning with the highest standards of waste management. Given methane’s pronounced global warming potential relative to biogenic carbon dioxide, this paper centers on leveraging the methane content in waste for energy generation. This emphasis is crucial, particularly in assessing and strategizing mitigation efforts within a methane recovery scenario in the Philippines, as articulated by Ref. [
17]. As a developing nation, it is imperative for the Philippines to judiciously allocate its budgets to maximize the benefits and minimize risks associated with methane recovery initiatives. This entails a thorough cost–benefit analysis to identify viable solutions and alternatives, factoring in essential assumptions and potential risk scenarios.
In this paper, a comprehensive framework is proposed to model effective government strategies for addressing climate change through the implementation of landfill gas technology and modernizing waste management practices. The framework emphasizes the recovery of valuable materials such as papers, plastics, and rubbers as opposed to traditional disposal methods. The main goal is to evaluate the environmental and economic impacts of targeted waste management and to estimate methane emissions from landfills using the Intergovernmental Panel on Climate Change (IPCC) methane estimation methodology in conjunction with LEAP-IBC Software version: 2020.0.12. Additionally, the paper assesses the methane recovery policy for key short-lived climate pollutants (SLCPs) and compares the costs of mitigation options with those of the business-as-usual scenario. Specifically, the study aims to achieve the following:
Gather historical data on the MSW disposed of in landfills.
Calculate the degradable organic carbon (DOC) content in the landfills.
Calculate methane emissions from the SLF data.
Build the methane recovery scenario in LEAP-IBC.
Calculate the methane emissions of Metro Manila cities using LEAP-IBC in the baseline scenario.
Calculate the methane recovered using SLCP’s rate of methane capture.
Calculate the projected methane emissions of Metro Manila using LEAP-IBC by inputting the historical values, rates, constants, and solving for the relevant equations/formulas.
Analyze Long-Range Energy Alternatives Planning–Integrated Benefits Calculator (LEAP-IBC) output and evaluate its implications on health, the economy, and the environment.
The study used LEAP-IBC software to project significant data on Metro Manila’s total waste generated and methane emissions and analyzed data from LEAP-IBC using Stata 15 by building a panel dataset for the 17 cities in Metro Manila from 2010 to 2050. Then, it examined the economic implications through a cost–benefit analysis, identifying estimated costs and benefits, calculating the net present value (NPV) and benefit–cost ratio, and performing a sensitivity analysis to see how the NPV is affected by changes in parameters such as discount rate, waste-to-energy transformation efficiency rate, and recycling rate. This paper provides a reference for understanding how methane emissions from landfills affect the environment and focuses solely on methane emissions from disposed municipal solid waste in Metro Manila, using 2010 as the base year. In generating data and results in LEAP-IBC, the researchers used variables and constants from the 2006 IPCC guidelines for methane estimation: the oxidation factor was set to 0, the fraction of methane in landfill gas was set to 50%, and the fraction of DOC dissimilated was also set to 50%. Additionally, the researchers assumed that the SLFs used by Metro Manila were categorized as semi-aerobic managed solid waste disposal sites, which involve controlled waste placement and include structures to introduce air to the waste layer: (i) a permeable cover material; (ii) a leachate drainage system; (iii) regulating pondage; and (iv) a gas ventilation system (IPCC 2006 Guidelines for National Greenhouse Gas Inventories). Thus, a methane correction factor of 0.5 was used, as stated in Volume 5 (Waste) of the 2006 IPCC guidelines. In estimating the overall methane emissions of Metro Manila, the researchers used an MSW generation rate of 0.69 kg/capita/day, the average rate in Metro Manila according to the NSWMC in 2016, and the total population of Metro Manila in 2020 provided by the Philippine Statistical Authority.
However, for the estimation of methane emissions of each city, their respective populations and MSW generation rate per capita were used. The researchers also set the fraction of MSW disposed in landfills to 54.81% as, according to the Metropolitan Manila Development Authority (MMDA), 45.19% of MSW in the metro is not disposed properly and does not end up in the SLFs. The DOC fraction, although it has a default value of 18% for developing countries in the IPCC guidelines, was manually calculated in this study and was found to be 15.83%, which is only applicable for Metro Manila. The researchers set the amount of methane recovered to zero in the baseline scenario and used DENR’s targets for methane capture for the years 2025 (36%), 2030 (52%), and 2040 (54%) in the methane recovery scenario. Developed countries can expect data on a large collection of available information, while some developing countries have to construct data from scratch [
18]. With this, in conducting the cost–benefit analysis of this paper, the capital costs and operating & maintenance costs are computed from scratch using the guidelines of CCC/USAID-B-LEADERS in 2018, and the 2003 reference from Department of Environment and Natural Resources–Environmental Management Bureau (DENR-EMB) was used to establish the collection, transportation, and segregation costs in the model. Benefits like recyclables revenue and electricity savings were computed by the researchers, using market prices from the year 2010. The environmental impact was computed by assuming a 2.87mtCO
2e/ton of waste recycled avoided emissions from landfilling [
19], while the health and employment impact were directly transferred from the CCC/USAID-B-LEADERS study in 2018 into the model. The panel dataset used for analysis in Stata 15 only contains the variables methane emissions, population, GDP per capita, and life expectancy, wherein the methane emissions, population, and GDP per capita were all taken from the LEAP-IBC results of the study and the variable life expectancy specific to the Philippines was taken from the World Bank.
The study is valuable as it provides a comprehensive dataset that can be utilized for future research on modeling, forecasting, analysis, and case studies related to reducing municipal solid waste emissions. The use of LEAP-IBC allows for the easy calculation and forecasting of methane emissions. Moreover, alternative scenarios, such as methane recovery, can be assessed through the Integrated Benefits Calculator. This approach presents a new way to address climate change mitigation in the area of methane emissions, providing a valuable reference for future research and studies. In-depth studies on the composition, generation, and emissions of MSW are crucial for creating sustainable waste management plans, not only for environmental and health protection but also for economic purposes. Local government units (LGUs) play a key role in selecting facilities such as the type of technology to employ and how to utilize public funds for solid waste management. The detailed cost–benefit analysis conducted in this study, which is available for editing and adjustments, would be highly beneficial for LGUs in their budget proposals regarding solid waste management, enabling them to determine the economic viability of proposed technologies. Additionally, there is a notable lack of studies addressing methane recovery scenarios and scenario modeling for landfill gas technology in the context of the Philippines. This study can serve as a foundational resource for the private sector interested in exploring waste-to-energy technology and developing projects that address the issue of municipal solid waste while also being economically advantageous. This is especially relevant, as some landfills in the country are managed by the private sector, presenting an opportunity for mutually beneficial solutions.
3. Results
The projected waste generation in Metro Manila is seen to continuously increase over the years, as seen in
Figure 2. The LEAP-IBC tool calculated the projection from the 2010 base year to the 2050 end year by considering two variables, which are the population whose waste is collected and the annual MSW generation rate. Due to the expected increase in population as projected under the demographics branch inside the key assumptions of LEAP-IBC, MSW generation is also going to increase over the years.
In 2010, it is observed that Metro Manila generated 3,811,230 metric tonnes of municipal solid waste, which is higher compared to the 2.99 million metric tonnes projected by DENR-EMB in 2014. However, in comparison to the same study, Metro Manila, by 2020, generates 4.489 million metric tonnes of MSW, which is much closer to the 4.441 million metric tonnes projected by DENR-EMB. The deviation in the 2010 calculation may be explained by the higher averaged MSW generation rate used in LEAP-IBC, which is 0.69 kg/capita/day, whereas the study done by DENR-EMB (2014) used 0.40 kg/capita/day.
With MSW increasing over the years, Metro Manila’s methane emissions coming from the MSW sector is also in an increasing trend. The IPCC model for methane emission estimation was manually incorporated inside the LEAP-IBC tool for each of the 17 cities with varying population and waste generation rates. From
Figure 3, it can be seen that in 2010, 97.30 million metric tonnes of methane emissions were produced. Under the baseline scenario, it is assumed that no methane emission was recovered, so the projection continued to increase until the end year and, by 2050, Metro Manila could produce 158.06 million metric tonnes of methane emissions from the waste sector alone. The increasing trend of methane emissions in the baseline scenario agrees with the study done in Tehran; however, these projected values are smaller compared to Tehran’s projections that range from 150 to 200 million cubic meters of methane emissions. This can be explained by factors in the equation that can affect the methane emission calculation such as Tehran’s higher MSW generation rate of 0.84 kg/capita/day and better garbage collection efficiency. Even though Metro Manila produces 9500 tons of MSW daily, Ref. [
28] revealed that only 54.81% of it ends up in the SLFs and 45.19% is not properly disposed.
From the 17 cities, there are three outliers in the plot of methane emissions versus population density shown in
Figure 4. Going back to
Figure 2, these cities have the biggest methane emissions as a result of their bigger population and waste generation rates compared to the rest of Metro Manila. From the distribution of the plot, two extreme behaviors can be seen. The first one is Quezon City, which exhibits the highest methane emissions with a low population density. This behavior is explained by Quezon City having the biggest land area of 171.71 km
2, which is three to twenty-nine times larger compared to the other cities. On the other hand, Manila City has a lower methane emission relative to Quezon City but has the highest population density, as suggested by Manila’s higher population relative to its land area.
Figure 5 shows that methane emissions will decrease compared to the baseline scenario where no methane is to be recovered. It is apparent that, with the three different targets of methane capture, the amount of methane emissions will decrease significantly from 127.036 million metric tonnes (baseline) to 81.303 million metric tonnes by 2025, from 135.358 million metric tonnes (baseline) to 64.972 million metric tonnes by 2030, and from 150.554 (baseline) million metric tonnes to 69.255. The trend of the methane recovery scenario starts to increase after the biggest capture in 2030 as the volume of the methane being emitted is expected to increase with more intensity, especially when considering that, after 2040, no other target is specified. Hence, the trend continues to increase relatively with the increase in waste generated and the population whose waste is being collected.
From the perspective of GHG emissions, as methane is also a greenhouse gas, it is evident that the methane recovery scenario is better than the baseline as shown from the one hundred years GHG emissions diagram in
Figure 6. According to the baseline and methane recovery scenarios, the global warming potential in 2010 is estimated to be 2112 million metric tonnes of carbon dioxide equivalent. This value is much higher, since methane is 21 times more capable of warming the atmosphere than carbon dioxide. However, after 2010, the baseline’s global warming potential is much higher than the methane recovery scenario in each year. By 2050, the global warming potential reaches to 3.430 and 1.578 million metric tonnes of CO
2 equivalent for baseline and methane recovery, respectively. In the span of 40 years, from 2010 to 2050, a total of 10.249 million metric tonnes of CO
2 equivalent is avoided in the methane recovery compared to the BAU.
With the calculation done in the IBC feature of the software, this study was able to distinguish the temperature increase in each scenario. It is observable in
Figure 7 that the deviation from the temperature increase in each scenario becomes more observable as the years go on. Generally, the temperature increase is much higher in the baseline scenario compared to the methane recovery scenario, since the methane emissions keep on growing without any action or mitigation in the baseline. A minimum of
°C (year 2015) and a maximum of
°C (year 2050) increases in temperature can be avoided under the methane recovery scenario. It is implied that, in both scenarios, the temperature will still continue to increase over the years, but the increase will be slower if a mitigation like the methane recovery scenario from the waste sector is implemented. The slower increase in temperature aligns with the result of having a lower global warming potential of methane emissions under the mitigation scenario. Thus, it implies that, with a slower temperature increase and a lower global warming potential seen under the proposed mitigation scenario, the adverse effects of climate change brought about by the SLCP, methane, can be lessened and future costs due to damages or drastic adaptation measures can be avoided. For the ambient temperature change, there is a slight difference in projection compared to the actual temperatures during the COVID-19 situation, wherein the temperature change is seen to decline during 2019 to early 2021.
The Harris–Tzavalis unit root test, which is a specified unit root test for panel data, was used to check whether the variables methane emissions (ME), population (Pop), gross domestic product per capita (GDPC), and life expectancy (LE) were stationary. All of the variables used are in logarithmic form. The results indicated that the p-values of lnME, lnPop, lnGDPC, and lnLE are 0.9965, 0.9965, 1.000, and 0.9995, respectively. It can be seen that the p-values are greater than 0.01. Thus, the researchers failed to reject the null hypothesis at a 1% level of significance. This means that the researchers were confident that each of the panels contain a unit root, which implies that lnME, lnPop, lnGDPC, and lnLE are all stationary at their levels. Because they are stationary, the researchers confirmed that we do not have a spurious regression. In the fixed effects model, when the Prob > F has a value that is less than 0.05, it indicates that the model used is appropriate. This is a test to see whether all the coefficients in the model are different than zero. From the results generated by Stata, it is seen that the Prob > F is 0.0000. Thus, the fixed effects model was clearly the right model to use since the probability based on the F-test is less than 0.05. The variables lnPop and lnGDPC are significant variables since the Prob> |t|, which are 0.000 and 0.044, respectively, are less than 0.05.
Looking at the coefficients in
Table 3, there is a one percent increase in lnPop that leads to a 1.000001 increase in lnME. This information confirms and agrees with the result of the previous studies regarding methane emissions and urbanization. As people move to the cities and the population grows, waste generation increases, leading to a linear increasing effect on methane emissions. Furthermore, the result states that a one percent increase in lnGDPC causes a 0.00000137 decrease in methane emissions. As the GDP per capita is an indicator of human well-being, this only proves that, as the economic state of an area improves, the solid waste management also improves, which leads to a decline in the emission of said pollutant. Finally, a one percent increase in lnLE causes a 0.0000347 increase in methane emissions. This result only relays the information that the longer a human person lives, the more waste the individual generates and the more emissions the person leaves behind. From these results, it is seen that the improvement of solid waste management through the representation of GDP per capita is a vital key in reducing methane emissions as the population growing or the length of time a person lives on this planet cannot be controlled.
In order to determine if the random effects model is the appropriate model to use, the Prob > chi2 should be less than 0.05. This is a test to see whether all the coefficients in the model are different than 0. From the generated result from Stata, it is clearly seen that the Prob > chi2 is equal to 0.0000. Hence, the random effects model, as seen in the results in
Table 4, can also be used for these panel data. The RE model has almost the same interpretation as the FE model (
Table 5), except that, unlike the fixed effects model, the variation across entities for RE models is assumed to be random and uncorrelated with the predictor or independent of the variables included in the model. Again, the random effects model suggest that, to reduce methane emissions, better solid waste management is needed through the improvement of the economic state.
After getting the NPV and BCR, a sensitivity analysis was performed in order to identify how the net present value will change if particular parameters deviate from their target and anticipated values. In this analysis, three analysis scenarios were considered. Analysis 1 varied the discount rate, Analysis 2 varied the efficiency of LFG technology electricity generation, and Analysis 3 varied the rate of recycling collected waste from the total MSW generated. For Analyses 1 and 2, the researchers started at a 10% discount rate, and 50% efficiency, respectively. On the other hand, for the recycling rate of Analysis 3, the researchers started at 50%, 55%, and 60%, the same rates used in the calculations of recyclables above. The results in
Figure 8 show the different behavior of NPVs when specific parameters are accordingly varied by percent. The analysis with the largest positive slope on the positive range ahead of the base scenario, i.e., after the (0,0) point, is considered to be the highest contributor to the project’s economics, in this case, Analysis 2. It can also be observed how large its negative slope is, which means that it also has a negative impact on the project if its parameters are varied, in this case, specifically, the efficiency of methane transformation for electricity generation. It should be noted that the behavior of the graph of Analysis 1, when there is too much increase in the discount rate, will eventually have a negative effect on the project economics.
The net present value for the years 2010–2050 is PHP 52 billion. Since the NPV is greater than 0, this indicates that the project is economically viable and gives a better return on investment. In
Figure 9, the NPV across each year is uniformly positive, since the benefits are continuously greater than the costs and the slight tweak in the present costs in the year 2030 of the same figure is due to the fact that the full potential of the methane recovery system is set to be achieved during this year, deploying 56% of the SLFs’ waste capacity for methane recovery. Overall, the decreasing trend of the costs and benefits is also caused by the government’s target to close and rehabilitate the SWDS towards the end of the project period. For the benefit–cost ratio, a value of 2.10 was obtained. Through the benefit–cost ratio, the confidence regarding the costs and benefits can be justified. The BCR of 2.10 implies that the project is worth the investment. If the BCR is close to 1, then there is a risk than any cost overrun or changes in the key parameters could bring it below 1, which, in turn, indicates that the project is not worth the investment. With the BCR that is obtained, there is a safety margin that the researchers can hold onto if specific assumptions and target are not met along the way. However, even with this kind of safety margin, the researchers also have to look at how each benefit is sensitive to each change in the parameter. With the sensitivity analysis, it is found that changing the efficiency of the LFG technology has a great effect on the net benefits of the project. Therefore, this kind of risk should also be considered along the process of policy evaluation.
4. Conclusions
This research provided a comprehensive analysis on the environmental, financial, and economic impacts of implementing methane recovery for electricity generation for SLFs from 2010 to 2050. The LEAP-IBC results signify that megacities like Metro Manila have huge potential to turn their problems with managing MSW into clean energy and aid in the energy demand sector. Since methane recovery for electricity production is considered a renewable energy, this would help policymakers to lessen their dependence on non-renewable energies. The study calculated that Metro Manila generated about 3.8 and 4.5 million metric tonnes of MSW in 2010 and 2020, respectively—which will continue to grow until 2050. As a result, the methane emissions from the waste sector will also follow the same behavior and, by 2050, Metro Manila will be able to produce 158.06 million metric tonnes of methane emissions. The three most populous areas, which are Quezon, Manila, and Caloocan, comprise the largest parts of this accumulated methane emissions. There are different alternative technologies to treat waste in a more sustainable process. In this study, the methane recovery scenario was explored and assessed in order to derive possible costs and benefits that may come along with the project. The computation produced a positive net benefit, indicating that methane is a viable option for electricity generation.
In assessing additional benefits of the methane recovery scenario, the study considered the incremental economic impacts, particularly in job creation and electricity cost savings. From 2015–2030, methane recovery is anticipated to generate 1413 job years, with a monetized employment impact of PHP 148.99 million, calculated using the minimum wage rate of PHP 404 in July 2010. Regarding electricity, the study projected the growing energy demand up to 2050 and the potential electricity generation from landfill gas (LFG) technology, assuming 50% methane capture efficiency and its conversion to electricity with the same efficiency rate. This implies a direct benefit from avoided electricity costs across different sectors, highlighting the study’s comprehensive approach to evaluating the advantages of methane recovery in the context of sustainable waste management and its economic implications.
Although a large amount of costs is needed, these costs were compensated with the project’s significant benefits to human health, the environment, and the economy. Project risks such as the crucial MSW management and varying discount rates were identified, which shows that they greatly affect the benefits that will be derived from the methane recovery scenario. The study detailed that only 4% of the LGUs in the Philippines use SLFs as their disposal facilities. With this, the project’s effectiveness relies on the success of the most basic unit of waste initiatives of not just the Philippine Government Departments, but also LGUs. Since waste management cannot be done alone by the government, LGUs are strongly encouraged to participate in future waste management plans. For example, their participation in terms of collaborative planning and implementation of waste disposal to SLFs is significant, since not all municipalities have SLFs that they can use for electricity generation projects. SLFs in the Philippines are located in different places, they vary in solid waste capacities, and their life time is also limited. In 2016, since only 15 percent of LGUs had access to SLFs, it was recommended to also cluster sanitary landfills in the country in order for the LGUs to share costs in establishing each landfill site. These recommendations are supported by Republic Act 7160 Section 33, of the Philippine Constitution, that LGUs may group themselves and coordinate their resources, efforts, and their services for their benefit and the environment, as long as they abide by the law. This collaboration is also important because if the capacity of some SLFs is not maximized, or at least the minimum amount of waste needed to generate a substantial amount of methane for electricity generation is not achieved, then the costs associated with the whole investment of the landfill project might fail to generate the expected benefits above. With this, the researchers strongly assert that, in order to run an effective and efficient MSW management, LGUs’ compliance with RA 9903 is required, through participation in the waste management plans of the government. For further research, it is recommended to tackle the input and output associated with the facilities of methane recovery systems, for example, by exploring if the amount of fuel needed to run the facility is efficient, and the amount of emissions that will be generated is still sustainable and non-destructive to the environment. This kind of analysis can help discover new findings if the proposed mitigation will affect the benefits calculated above and formulate new alternatives or proposal in maintaining the project’s economic viability. It is also preferable to consider, first, the amount of methane being emitted by an area, since it is crucial to the success of implementing the mitigation scenario proposed in this study. Areas like the Municipality of Pateros and the City of Taguig with lower populations and annual organic waste generation naturally have low methane emissions, which may infer the possibility of coming together in order to come up with a better cost and bigger benefits.