Exploitation of landfill gas vs refuse-derived fuel with landfill gas for electrical power generation in Basrah City/South of Iraq

2.1 Work program

The work program of this study was prepared by adopting the procedure illustrated by the block diagram shown in Figure 1. In the first step, the collected data about Basrah city included MSW management scheme, records of annual MSW production and city populations, and climatic conditions.

Figure 1

Procedure of the study work program.

2.2 MSW management in Basrah city

Basrah city is the largest city of Basrah governorate/southern Iraq (Figure 2) with respect to population. Basrah governorate is located within longitudes of (46°60′–48°60′)E and latitudes of (29°13′–31°29′)N. It is bordered by three Iraqi governorates (Maysan, DhiQar, and Al-Muthanna), Iran, Kuwait, and the Arabian Gulf. The climate of Basrah city is arid and hot. Concerning the subject of this study, rainfall is the most important meteorological factor that affects the production of LFG. Generally, the rainy season in Basrah city extends over 8 months (Oct–May). Al-Muhyi and Aleedani [16] studied the temporal variation of rainfall quantity in Basrah city for 50 years (1970–2019). They showed that 1 of 50 annual averaged rainfall values has exceeded 250 mm, which was in the year 1986. According to the data recorded at the Hi Al-Hussian Meteorological Station in Basrah city and obtained from the Iraqi Meteorological Organization and Seismology (IMOS), the monthly average relative humidity varies from 59% (in Jul) to 76% (in Nov–Jan) and averages 69% yearly. The monthly averaged temperature in Basrah city varies between 8˚C (in Jan) and 46˚C (in Aug). The prevailing wind direction in Basrah city is northeast during which the average wind speed is 2.7 m/s.

Figure 2

Profile of Basrah governorate: (modified following https://humanitarianatlas.org/iraq/atlasmaps/basraha.pdf).

MSW generated in Basrah city is managed by the Basrah Municipality Directorate. The management plan is based on dividing the city into six zones. Each zone is divided into several divisions, and each division is subdivided into partitions for the intent of MSW collection [14]. The waste is collected from the trash containers by vehicles of mobile mechanical waste compactor type. The vehicles transport the collected waste to a transfer station at which a simple waste sorting process is performed by poor people who collect plastic, ferrous, and aluminum wastes and seal them in a local recycling factory. Then, the waste is transported to the final disposal site in a sanitary landfill using dump tracks.

The sanitary landfill for Basrah city is located at Chwabedian area in AL-Berjesia zone/Zubair city (Figure 3). Its center is located at the latitude and longitude of 30°23.5′N and 47°31.25′E, respectively [17]. The landfill surface area is (400 × 600) m², and its depth varied over the range 12–14 m [18]. The landfill operation was commenced in 2010, and it is expected to end in 2035, considering 80% of its area will be occupied by waste and the remaining 20% be left for services (roads, garages, etc.) [8].

Figure 3

Location of Basrah landfill.

A complete description of MSW management in Basrah was presented by the Japan International Cooperation Agency/Yachiyo Engineering Co., Ltd. in a field study funded by the Iraqi Ministry of Construction and Housing and Municipalities and Public Works in 2022 [18]. In this study, MSW management in Basrah governorate was described, intensively, including the details of Basrah landfill facilities. These facilities include the following: (1) storm water drainage system, (2) leachate collection system completed with a storage tank, (3) weighbridge, (4) waste disposal platform, (4) tire wash facility, and (5) control office, fence, and gate. The landfill site does not incorporate a gas collection system, and the waste cells are below the ground level. From the aforementioned description of the MSW management status in Basra city, it can be noticed that there is no beneficial use of this waste. Subsequently, the city lacks sustainable MSW management, and this issue highlights the necessity of this study for the decision-makers.

2.3 MSW sampling

For a specific city, the composition of MSW varies with place and time due to the variation of climatic conditions, income level, in-home management of food waste, and industrial production. Thus, the method of waste sample collection and the number of samples are very important in analyzing the composition of MSW. The composition of MSW generated in Basrah city was analyzed by taking waste samples from Hamdan transfer station (HTS) following the standard ASTM D5231-92 [19]. Adopting this standard, the recommended sample weight ranges from 90 to 120 kg. Therefore, a waste sample of 100 kg was collected. The composition of each sample was analyzed manually by adopting the following procedure:

1. A platform scale of 150 kg capacity and 0.02 kg accuracy has been put on a flat area in the HTS.

2. The scale was calibrated using a known weight of sand sample.

3. A trash vehicle was informed to unload its contents at a clean area in the HTS.

4. A pre-weighed plastic bag was put at the scale and filled randomly with MSW until the scale reading reached a value of 100 kg.

5. The weighted plastic bag contents were emptied on a clean plastic mat.

6. The waste sample was sorted, manually, considering the waste categories presented in Table 1.

7. Each waste category was put in a pre-weighed container and weighed.

To analyze the waste composition, the necessary number of waste samples was determined based on sorting 14 primary collected waste samples. These samples were sorted into 12 categories listed in Table 1. The number of final collected waste samples (n) was determined as follows [19]:

where t ⁎ is the Student’s t-statistic at the desired confidence level, s and x ¯ are the standard deviation and mean for each waste category weight fraction, respectively, and e is the desired precision level. In this study, t ⁎ was obtained from the t-distribution table for a two-tailed test [20] considering a confidence level of 90%, and e was specified to be 10%.

2.4 Determination of MSW composition and generation rates

After the manual sorting of waste samples, the wet weight of each waste category was taken, then a subsample was taken from each category waste and put into a plastic bag. The subsamples of all the waste categories were transported to the laboratory within a time duration not exceeding 4 h for analyzing both their wet and dry mass values. Each of these subsamples was weighed using an analytical balance and then dried in an oven at a temperature of 105°C for a duration of 24 h. Then, the subsample was cooled to room temperature, and the dried weight was measured for the intent of moisture content determination.

The annual rate of MSW generation in Basrah city (ton/capita/year) was estimated using recorded populations and annual quantities of MSW for the period 2014–2019. Population records were obtained from the Iraqi Ministry of Planning/Central Statistical Organization. The future population was predicted by best fitting the population records for the years 2010–2019 (Figure 4), and the developed equation is as follows:

where n _y is the years’ number measured from the base year 2010. Using Equation (2), the population data were extrapolated until the year 2035, which is the proposed year of closing the existing landfill.

Figure 4

Population records of Basrah city during the period 2010–2019.

2.5 Estimation of methane gas emission

In this study, LandGEM (Landfill Gas Emissions Model) software, version 3.02, was used to estimate methane gas emission from the landfill of Basrah city. LandGEM was developed by USEPA in 2005, assuming that the biodegradable waste is decomposed following a first-order equation. It can be applied to estimate the emission rates of different gases from landfills including methane and carbon dioxide [21]. In this study, LandGEM software was chosen because it is freely available and presents a simple methodology for predicting the LFG emissions. Besides, it includes default parameters based on field data collected from existing landfills in the USA and depends on International landfill regulations [22]. LandGEM was developed using Excel software. It includes nine Excel spreadsheets. The function of each spreadsheet is illustrated in Table 2.

Although the LandGEM model is based on waste specifications and climatic conditions for the areas of the USA, it can be applied to other areas around the world by implementing field data for determining the model parameters instead of the default ones [22,23]. In this model, both the production percentages of carbon dioxide and methane gases were assumed to be 50% of total gas emission [22]. The LandGEM model was used for estimating the gaseous emission in many previous studies [4,10,23,24,25,26,27]. By adopting this model, the annual generation rate of methane gas is estimated as follows [21]:

where Q _meth is the annual generation rate of methane (m³/year); i and j are time increments of 1 year and 0.1 year, respectively; m is the time duration (year) from the start of waste dumped at the landfill and the considered year; k is the methane generation rate constant (1/year); L _O is the capacity of methane generation potential (m³/Mg); M _i is the mass of waste dumped in the ith year (Mg); and t _ij is the age of the jth section of waste mass dumped in the ith year (decimal years).

2.6 Estimation of electrical energy production potential

3.1 MSW composition

After categorization of each MSW sample, the recorded weight of each waste category is entered in an Excel worksheet. Then, for specific waste category, the mean and standard deviation of the weight values recorded for a number of waste samples were obtained and divided by 100, since the sample weight was 100 kg, as stated in Section 2.3. The mean and standard deviation for the weight fraction (weight of a specific waste category divided by 100) of all the 12 MSW categories are shown in Table 6. If wood is selected as the governing component, then s = 0.008 and x ¯ = 0.029, and Equation (1) gives an n value of 21 after substituting the t ^* value of 1.645. Now, to check if this n value gives an error not exceeding 10%, the t ^* values for n equal 20 and 21, which were obtained from the t-distribution table, which are 1.725 and 1.721, respectively. A new n value was obtained by substituting a t ^* value of 1.725 and the number of samples was 23. The new n value was compared with the old one, and the percent of error was 9.52%, which is less than 10%. Thus, the composition of MSW in Basrah city can be decided based on a number of samples not less than 23. In this study, the composition of MSW in Basrah city was analyzed based on the sorting of waste samples during a period of 4 months (Nov and Dec in 2022 and Jan and Feb in 2023). The total number of samples was 96 (24 samples during each month).

After the manual sorting of each of the 96 waste samples, MSW composition in Basrah city for 4 months (Nov and Dec in 2022 and Jan and Feb in 2023) is presented in Table 7, along with the average composition of the 4 months. From this table, it can be shown that the biodegradable organic components (food and garden waste) comprised about 50.52% of MSW, while the RDF components comprised 36.09% of the MSW.

3.2 Temporal variation of MSW composition

The temporal variation of daily MSW composition in Basrah city is shown in Figure 5 considering 13 daily samples during the period 15th–27th Nov 2022. The figure reveals some daily variations in waste composition. However, food waste is the main component of MSW in Basrah city and has the maximum percentage. It is followed, in sequence, by plastic (mainly empty bottled water), mixed paper, corrugated, textile, nappies, ferrous, aluminum, and garden waste. This sequence of MSW categories matches the findings of Bhat et al. [35], who showed that vegetable and food wastes form the major part of the MSW followed by plastic and other waste categories.

Figure 5

Daily variation of MSW composition.

Figure 6 shows the temporal variation of monthly averaged MSW composition. It can be shown from this figure that the variation in monthly averaged MSW composition is insignificant. This can be attributed to the meteorological condition during the study period, which was relatively cold months.

Figure 6

Temporal variation of monthly averaged MSW composition.

3.3 MSW generation rate

The records of annual MSW quantities produced in Basrah city were obtained from the Municipality Directorate of Basrah city. These records along with their corresponding population records during the period 2014–2019 were used to estimate the rate of MSW generation in Basrah city. The results of MSW generation rates are presented in Table 8. Based on these results, the average MSW generation rate was estimated to be 0.982 kg/capita/day (or 0.358 ton/capita/year). This generation rate was located within the recent MSW generation rate range in other Iraqi cities, 0.673–1.27 kg/capita/day, as presented in Table 9. However, it is less than that obtained for Basrah city during the years 2011–2014, which was varied over the range 1.05–1.97 kg/capita/day [15]. By using the average rate of MSW generation, the yearly production of MSW generation is estimated as follows:

where MSW_t and P _t are the MSW quantity (ton) and population of Basrah city in the year t, respectively.

3.4 Low heat value of RDF

The results of average wet and dry weights of all MSW categories, including the RDF components, in a wet sample of 100 kg are presented in Table 10. The dry weight for each category was determined based on its moisture content and wet weight. By multiplying the wet percentage of each RDF component (as obtained from Table 10) by its LHV value (as obtained from Table 4), the unit energy content was calculated to be 2,296,952 kJ/100 kg of wet weight (Table 11). The moisture content of the RDF was 12.6%, then on a dry basis, the LHV of RDF was 26,281 kJ/kg.

3.5 Methane gas quantity

To estimate methane gas emissions from Basrah sanitary landfill using the LandGEM model, the annual MSW quantities must be specified as input data, along with the years of landfill open and close and the model parameters k and L _O. The annual MSW quantities were obtained using equation (8), and the results are shown in Figure 7. The years of landfill open and close were specified to be 2010 and 2035, respectively. While the model parameters L _O and k were specified as described below.

Figure 7

Recorded and estimated MSW generation rates in Basra city for the period 2010–2035.

According to the data of Table 3 and by using the MSW composition data presented in Table 7, the calculated k values for the first and second proposed scenarios (LFG and RDF with LFG) are shown in Tables 12 and 13, respectively. In the LFG scenario, all the MSW components are dumped at the landfill, and in the RDF with LFG scenario, the MSW is segregated at first into recycled wastes (metals, glass, and aluminum), RDF (plastics, papers, wood, corrugates, and textiles), and organic wastes (food and garden waste). Thus, the three values of k obtained for the LFG scenario were 0.02 year⁻¹ (typical value), 0.013 year⁻¹ (Equation (4)), and 0.024 year⁻¹ (Table 12). While for RDF with LFG, the obtained k values were 0.02 year⁻¹ (typical value), 0.013 year⁻¹ (Equation (4)), and 0.03 year⁻¹ (Table 13) year⁻¹. LandGEM was run to estimate the methane production rate by LFG and RDF with LFG scenarios applying the averages of the three k values for the first and second scenarios, which are 0.019 and 0.021 year⁻¹, respectively.

The average L _O values given in Table 4 were used for L _O calculation. In the LFG scenario, the percentages of slowly, moderate, and highly biodegradable wastes were 17.74, 12.86, and 50.52% (Table 7), thus the calculated L _O value was 194 m³/mg. However, for the RDF and LFG scenario, there is only highly degradable waste at a percentage of 50.52%, thus the calculated L _O value was 262.5m³/mg. In addition, the L _O value was specified to be 132.8, 14.8, 62.6, 72, and 300.7 m³/mg for paper, textile, wood, garden waste, and food waste, respectively [22,32]. Based on these values and by applying the MSW composition for Basrah city (Table 6), L _O was calculated to be 171.7 and 297.9 for LFG and RDF with LFG scenarios, respectively. By taking the average of the three L _O values, LandGEM was run applying L _O values of 178.6 and 243.5 m³/Mg for LFG and RDF with LFG, respectively.

The results of applying LandGEM software to Basrah landfill (quantities of CO₂, CH₄, and total LFG) considering the first and second scenarios (LFG and RDF with LFG) are shown in Figures 8 and 9, respectively. From these figures, it can be noticed that the peak amount of methane emissions during the first and second scenarios are 23056.5 and 17189.2 Mg/year, respectively. Both these peak values will be generated in the year 2036, and after that the LFG production will continue along with the decay of biodegradable waste at a decreasing rate for more than 110 years.

Figure 8

Annual LFG mass production for Basrah landfill: LFG scenario.

Figure 9

Annual LFG mass production for Basrah landfill: RDF with LFG scenario.

Calculation of the annual production of electrical energy using methane gas as a fuel requires the annual flowrate of methane gas. Figure 10 presents the obtained annual flowrates of methane gas applying both LFG and RDF with LFG scenarios. It depicts the peak annual methane flowrate during the first and second scenarios, which are 34,559,772 and 25,765,183 m³/year, respectively. Thus, the produced methane emission adopting the first scenario is greater than that of the second. This is because during the first scenario all the MSW components are dumped at the landfill, whereas during the second scenario only the organic wastes are dumped at the landfill.

Figure 10

Comparison of methane gas annual flowrates adopting LFG and RDF with LFG scenarios.

3.6 Sensitivity analysis of LandGEM results

The estimation of methane emissions from MSW landfills using LandGEM is based on two main parameters: methane generation rate constant (k) and methane generation potential capacity (L _O). The sensitivity of model results to the variation of k and L _O was investigated by fixing one of the parameters and varying the value of the other parameter to be within the value range obtained in Section 3.5. The sensitivity analysis results for k and L _O are depicted in Figures 11 and 12, respectively. Figure 11 shows that during the landfill lifetime (2010–2035) the rate of methane gas emission increases with the increase of k. However, after certain years of landfill closure, k increase will reduce the gas emission. Figure 12 shows a positive correlation between the gas emission and L _O, and this trend continues until complete anaerobic decomposition of the dumped biodegradable organics. Generally, the sensitivity of LandGEM results to k variation is more than its sensitivity to L _O variation. Thus, great attention must be given when specifying the k value through inclusion of landfill site-specific characteristics.

Figure 11

Sensitivity of LandGEM results to the variation of methane generation rate constant (k in year⁻¹) at an L _O of 178.6 m³/Mg.

Figure 12

Sensitivity of LandGEM results to the variation of methane generation potential capacity (L _O in Mg/m³) at a k of 0.02 year⁻¹.

3.7 Electrical energy recovery potential

After determining the annual flowrates of methane gas production, the values of electrical energy produced by adopting the first and second scenarios were calculated using equations (5) and (7), respectively. Figure 12 shows a comparison of electrical energy generation potential by adopting LFG and RDF with LFG scenarios till the year 2035 (landfill close year). Starting from the present year (2022) till the year 2035, Figure 13 shows that the annual electrical power generated varied in the ranges 4.3–9.1 MW and 26.4–36.1 MW by adopting the first and second scenarios, respectively. Therefore, the application of RDF with LFG is the better choice for making beneficial use of MSW collected in Basrah landfill. Although the generated rate of electricity is relatively low, it can solve to some degree the problem of electricity shortage in Basrah city along with the reduction of pollution consequences as a result of gas emissions.

Figure 13

Comparison of electrical energy recovery potential using LFG and RDF with LFG.

It is important to mention here that each part of the world has its own characteristics (meteorological, waste management scheme, economics, social habits, etc.). To find whether another part of the world can take advantage of the study findings is a hard task. However, the concept of selecting the best way of converting waste to energy is important to be considered before deciding to follow a specific approach which in this study through the use of RDF with LFG.

3.8 Applicability of RDF with LFG scenario

Considering the quantity of generated energy, it is indicated in Section 3.7 that RDF with LFG waste-to-energy scenario is the better choice for generating electrical energy from the collected MSW in Basrah landfill. If this scenario is implemented successfully, it can reduce LFG emissions, provide new job opportunities, and decrease the need for fossil fuels like crude oil and natural gas. The applicability of this scenario depends on the composition and generation rate of MSW and landfill site proximity to the destination point of waste-to-energy conversion, where RDF preparation and combustion equipment are located. In addition to the economic feasibility of applying the RDF with LFG scenario, it also depends on the capital and operating costs of RDF and LFG processing, as well as the income gain by reducing fossil fuel consumption [41].

The composition and generation rate of MSW are dependent on the habits of MSW producers and their living standards, and these two factors cannot be controlled with a lack of awareness in developing countries such as Iraq. Thus, this study focused on the landfill proximity to the destination point of waste-to-energy conversion. It was assumed that the end user of the produced fuel would be one of the existing power generation stations within the area of the landfill site.

The area where Basrah landfill is located includes four power generation stations: Zubair Field, Shatt Al-Basra, North Rumila, and North Rumila power stations (Figure 14). The capacity, applied technology of power generation, used fuel type, and the location coordinated of each of these stations are presented in Table 14. From this table, it can be noticed that the generation capacity of these stations is much greater than the energy that could be produced by implementing the RDF with LFG scenario (36.1 MW/year).

Figure 14

Existing power stations near the Basrah landfill location with indication of access roads.

The access distance from the landfill location to each of the existing power stations is presented in Table 15. This table shows that the nearest power generation station to the landfill location is at a distance of 9.6 km. The cost of RDF material and LFG transportation to this station cannot balance the benefits gained from implementing the RDF with scenario. Thus, it is not feasible from economical and practical points of view to use the generated renewable fuel as a complementary source of fuel for any of the existing power stations.

Based on the above results and to make best use of the produced energy and since the landfill site needs electrical energy for its management, it is recommended to install the needed equipment for sorting, shredding, combusting the MSW, and gas filtering at the site of Basrah landfill.