Waste Management 34 (2014) 952–960

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A baseline study characterizing the municipal solid waste in the State of Kuwait Rawa Al-Jarallah a,⇑, Esra Aleisa b,1 a

Civil Engineering Department, College of Engineering and Petroleum, Kuwait University, Khaldia Bldg. # 14KH, 2nd Floor, P.O. Box 5969, Safat 13060, Kuwait, Kuwait Industrial and Management Systems Engineering Department, College of Engineering and Petroleum, Kuwait University, Khaldia Bldg. # 8KH, 3rd Floor, P.O. Box 5969, Safat 13060, Kuwait, Kuwait b

a r t i c l e

i n f o

Article history: Received 10 October 2013 Accepted 20 February 2014 Available online 20 March 2014 Keywords: Municipal solid waste Waste composition Waste characterization Statistical analysis Regression Kuwait

a b s t r a c t This paper provides a new reference line for municipal solid waste characterization in Kuwait. The baseline data were collected in accordance with the Standard Test Method for the Determination of the Composition of Unprocessed Municipal Solid Waste (ASTM). The results indicated that the average daily municipal waste generation level is 1.01 kg/person. Detailed waste stream surveys were conducted for more than 600 samples of municipal solid waste (MSW). The waste categories included paper, corrugated fibers, PET bottles, film, organic matter, wood, metal, glass, and others. The results indicated that organic waste dominated the characterization (44.4%), followed by film (11.2%) and then corrugated fibers (8.6%). Analysis of variance (ANOVA) was used to investigate the influence of season and governorate on waste composition. A significant seasonal variation was observed in almost all waste categories. In addition, significant differences in proportions between the current level and 1995 baseline were observed in most waste categories at the 95% confidence level. Ó 2014 Elsevier Ltd. All rights reserved.

1. Introduction Municipal solid waste (MSW) characterization is the first step toward achieving an integrated solid waste management system (ISWMS) that efficiently reduces and treats the ever-increasing amount of MSW (Metin et al., 2003). A waste characterization study quantifies waste components with respect to weight and composition fractions. Reliable data on MSW composition are key in determining and customizing suitable technologies for an overall ISWMS (Magrinho et al., 2006). This study has three objectives: conduct an up-to-date characterization of the MSW generated in Kuwait, investigate whether any significant changes have occurred since the previously established national waste characterization baseline study, and conduct a statistical analysis to detect sources of variations resulting from seasons and governorates. The objectives were achieved while adhering to the Standard Test Method for the Determination of the Composition of Unprocessed Municipal Solid Waste (ASTM) (ASTM, 2008). In addition, factorial analysis, regression, and residual analysis at the 95% confidence level were performed. ⇑ Corresponding author. Tel.: +965 2498 5738/9; fax: +965 2481 7524. E-mail addresses: [email protected], [email protected] (R. Al-Jarallah), [email protected], [email protected] (E. Aleisa). 1 Tel.: +965 2498 7527; fax: +965 2481 6137. http://dx.doi.org/10.1016/j.wasman.2014.02.015 0956-053X/Ó 2014 Elsevier Ltd. All rights reserved.

The MSW generation rate and composition are typically believed to be influenced by several factors, such as geographical and climatic conditions, population, and socio-cultural properties (Akinci et al., 2012; Al-Jarallah and Aleisa, 2013; Chandrappa and Das, 2012; Magrinho et al., 2006; Tinmaz and Demir, 2006). The economic status of a country is particularly related to its waste generation rate and composition (Khatib, 2011). Chandrappa and Das (2012) state that low-income countries with an annual GDP below US $5000 per capita have the lowest MSW generation rates of 0.3–0.9 kg/capita/day. In contrast, the MSW generation rates of countries with a higher GDP reach 1.4–2.0 kg/capita/day. The complexity of waste is also associated with country development (Khatib, 2011). Studies have reported that MSW in developing countries is rich with degradable material (Chandrappa and Das, 2012) and has an annual growth rate of 2–3%, whereas the MSW in developed countries is rich in recyclable materials and has an annual growth rate of 3.2–4.5% (Liao et al., 2009; Shekdar, 2009). Recent research suggests that despite the challenges that it may bring to MSW management, urbanization may still facilitate opportunities for lowering or at least stabilizing the rate of MSW generation (Rode and Burdett, 2011). According to Mazzanti (2008), although waste generation is still increasing proportionally with income, this correlation is lessened when waste policies are effectively implemented. The work of Sjöström and Östblom (2010) supports the assertion that waste management policies

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directed toward increased recycling activities have decoupled the classical association of MSW generation with GDP for some European countries. For instance, the Waste Prevention Programme for England (Defra, 2011) has led to a reduction in MSW generation in general and a 12% reduction in household MSW in 2012 compared to 2006 (Defra, 2013). Another example is the positive results of the New Zealand Waste Minimisation Act of 2008, which reduced MSW when curbside recycling was made available to 95% of the population (ISWA, 2010). This argument may also be applicable to some Asian countries, such as Japan, South Korea, and Taiwan, where urbanization and development appear less destructive to waste generation compared to developing countries within the same region (Othman et al., 2013). Table 1 compares the waste compositions of developing countries, such as the United Arab Emirates (UAE), Jordan, Egypt, and the Gaza Strip, as well those of developed countries, such as the USA, UK, and Japan. Developing countries have a high percentage of organic waste in the solid waste stream (Abd-Alqader and Hamad, 2012; Salah Abu-Salah, 2013; SCAD, 2013; Tinmaz and Demir, 2006; Zayani, 2010), followed by recyclable materials (Khatib, 2011), particularly plastics and paper. Developed countries tend to produce waste with a higher fraction of nondegradable waste due to the increased spending on packaging material, absence of rag picking, and lower number of scrap dealers (Chandrappa and Das, 2012).

2. The MSW of the State of Kuwait Kuwait occupies a land area of 17,818 km2 located on the Arabian (Persian) Gulf Peninsula of the Middle East. The population of Kuwait was approximately 3.250 million in 2012, with an average annual income of $47,926 per capita per year and an average family size of 5.6 persons (WBI, 2012). Kuwait has a hyper-arid desert climate. In the summer months, the average daily high temperatures range from 42 °C to 46 °C. From mid-August through September, humidity can exceed 95%. Dust storms are particularly frequent in the summer and can reach speeds up to 50 km/h. Winter seasons are short and relatively warm, with temperatures ranging from 7 °C to 21 °C. Rain events occur occasionally, with average annual rainfall amounts varying from 75 to 150 mm. Annual rainfall amounts as low as 25 mm and as high as 325 mm have been recorded (UNFCCC, 2012). Along with Kuwait’s acute increase in resource consumption, which has almost doubled over the last 10 years, statistics indicate that waste generation has also increased (WHO, 2012). The average waste generation rate is reported to be 1.4 kg/capita (Al-Meshan and Mahrous, 2002), which is one of the highest waste generation rates in the world (Al-Fares et al., 2009; Al Yaqout and Hamoda, 2002, 2005).

MSW management, including control, collection, processing, utilization, and disposal, is the responsibility of Kuwait Municipality. Dumping sites, which are commonly labeled landfills, are not properly cited or designed (Al-Muzaini, 2006; Al-Yaqout et al., 2002; Al Yaqout and Hamoda, 2002). Although the municipality waste management service continues to be provided free of charge, it has rapidly improved through the use of modern equipment and vehicles to transport the waste to the landfills. The daily collection service is provided to all residential areas using curbside collection for mixed municipal waste. Due to the absence of legislation that would either enforce recycling or compensate users for it, most of the recyclable materials are instead landfilled. A small amount of recyclables are either collected by scavengers from residential garbage containers or sent by advocates to recycling containers at community centers (Koushki et al., 2004a). Recently, the municipality has engaged in an effort to increase public awareness about waste minimization and waste segregation and has provided convenient community drop-off centers for recyclable materials. In addition, it has facilitated private recycling companies’ efforts to reclaim any recyclable material before being discarded at the landfills. However, these efforts are carried-out on a small scale. Collected residential waste is sent directly to the landfills. Kuwait Municipality has contracts with 16 private companies for the collection and transportation of household waste to landfill sites. The overall cost of this service is 266.8 million KD ($940 million) for 5 years. The MSW is deposited into three active MSW dumpsites (the Jahra, Mina Abdulla, and Seventh Ring Road dumpsites), in which waste is ‘‘dumped’’ in sand quarries rather than buried within engineered landfills.

3. Methodology Three approaches are commonly applied to characterize waste: waste product analysis, market product analysis, and direct sampling (Moore et al., 1994). Waste product analysis and market product analysis are suitable for large geographical areas, whereas direct sampling is suitable when site-specific data are not available (Kreith and Tchobanoglous, 2002). This study adheres to the international ASTM D5231-92 (ASTM, 2008) standard method, which a well-established method for waste characterization that has been widely used in the literature (Burnley et al., 2007; Dahlén et al., 2007; Koushki, 1995; Nas and Bayram, 2008; Tinmaz and Demir, 2006). This study adheres to the ASTM standards. An official agreement was established between Kuwait University and Kuwait Municipality for the purpose of this project; this agreement allowed the research team access to the daily and monthly waste generation reports and landfill sites to conduct the survey needed for waste composition analysis. The three operating landfill sites were visited and studied, and the Seventh Ring

Table 1 Comparing MSW composition of Kuwait to those of some developed and developing countries within close proximity and with similar cultures. Region

Kuwait (Koushki, 1995) UAE (SCAD, 2013) Jordan (Salah Abu-Salah, 2013) Egypt (Zayani, 2010) Gaza Strip (Abd-Alqader and Hamad, 2012) Turkey (Tinmaz and Demir, 2006) Japan (Shekdar, 2009) Malaysia (Shekdar, 2009) UK (Wales) (Burnley et al., 2007) USA (EPA, 2010)

Type Paper & cardboard

Organic

Metal

Plastics

Glass

Others

14.2 25 14.7 10 11 12.3 46 15 33.2 28.2

50.7 39 49.7 60 52 54.2 26 40 20.2 27.8

2.8 3 1.4 2 3 3 8 3 7.3 8.6

17.7 19 15.7 12 13 13.2 9 15 10.2 12.3

5.6 4 2.6 3 3 6.3 7 4 9.3 4.8

6 10 15.9 13 18 11 12 23 19.8 18.3

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Table 2 Waste characterization categories and their components. Category

Description

Sanitary Paper Corrugated fibers

Diapers, sanitary napkins, and tissues Office paper, newspaper, magazines, and paper bags Milk, juice, fruit and vegetable containers, cardboard, and paper cups and plates Containers (e.g., soft drink, milk, water containers) Packing plastic (e.g., bags, sacks, wraps) Food waste, yard waste, and tree leaves Wooden furniture and fruit and vegetable boxes Durable goods, such as appliances and furniture, in addition to containers and packaging, such as soda cans, food cans, pots, and clothes hangers Containers (soft drink bottles, jars for food, cosmetics, and other products)

PET bottles Film Organic waste Wood Metals

Glass

the maximum particle size of the remaining waste particles was approximately 12.7 mm. Particles that pass the screens were placed in their corresponding container. The gross weight corresponds to the wet weight sampled directly from waste containers. The weight of each waste component was recorded, and the site was cleaned after each sorting. Statistical tools, including hypotheses tests, were employed to compare the results among seasons and to a 1995 baseline. Full factorial analyses were performed to inspect the governorates’ and seasons’ effect on various waste categories. Regression models were formulated to model relationships into closed-form equations. A residual analysis was conducted to assure that the model

Table 3 Total descriptive statistics classified by category and season. Waste

Season

Sanitary

Summer Winter Overall

6.02 6.64 6.23

4536.5 2539.5 7076

18.52 21.16 19.39

Paper

Summer Winter Overall

6.40 7.21 6.67

4826.8 2759 7586

19.70 22.99 20.78

Corrugated fibers

Summer

7.75

5844

23.85

Winter Overall

9.67 8.40

3700.4 9544.4

30.84 26.15

PET bottles

Summer Winter Overall

5.97 8.64 6.890

4501.8 3305 7806.7

18.37 27.54 21.39

Film

Summer Winter Overall

11.7 10.4 11.3

8807.5 3978.1 12,785.6

35.95 33.15 35.03

Organic

Summer Winter Overall

49.4 38.6 45.8

37,281.2 14,765 52,046.1

152.17 123.04 142.59

Metals

Summer Winter Overall

2.77 6.29 3.950

2085.8 2404.1 4489.8

8.51 20.03 12.30

Glass

Summer Winter Overall

5.61 7.03 6.09

4230.3 2688.7 6919

17.27 22.41 18.96

Wood

Summer Winter Overall

2.96 5.51 3.82

2234.3 2108.8 4343.1

9.12 17.57 11.90

Fig. 1. The population, MSW generated (million tons/year), and daily average MSW generation per capita over the last 18 years for the State of Kuwait.

Road waste dumping site was selected for the waste characterization survey because it serves the vast majority of residential districts. Sampling containers, tarps, shovels, rakes, brooms, plastic containers, safety equipment, a scale, and first aid kits were purchased prior to the beginning of the waste stream survey. In addition, the scale was calibrated for use in the waste weighing process. The characterization study was performed during both the summer and winter seasons at the dumpsite for the main four (residential) governorates of Kuwait (i.e., Al-Asima, Hawalli, Farwaniya, and Mubarak Al-Kabeer), which constitute 68% of the country. The Al-Ahmadi governorate was excluded from the study because of heavy oil and military activities, which could bias the waste composition. The Al-Jahra governorate was excluded from the analysis because of ongoing construction; thus, the current data on Al-Jahra governorate will not be representative. Representative samples of raw MSW were sorted into individual components and weighed. A statistical analysis was then performed to determine the mean, standard deviation, and confidence level following the method of McCauley-Bell et al. (1997). To achieve adequate confidence levels and satisfy statistical data analysis requirements, 74 randomly selected MSW truckloads were thoroughly characterized during summer and winter according to the ASTM methods (ASTM, 2008). The sorting was conducted on an average of five trucks per day by six workers and an inspector. From each truck, approximately 454 kg of solid waste was spread on plastic sheets, mixed, coned, and quartered. One quarter of the mass (91–136 kg) was then selected randomly to be sorted into containers according to category. The categories are shown in Table 2. Manual sorting continued with the help of screens until

Composition (%)

Mass (ton)

Mass (ton/ day)

Fig. 2. Box plots displaying the MSW composition percentile with respect to season: summer (1) and winter (2).

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R. Al-Jarallah, E. Aleisa / Waste Management 34 (2014) 952–960 Table 4 Analysis of the differences in MSW composition between summer (1) and winter (2). Category a = 5%, Fa = 1.75

Equality of variance H0: r21 ¼ r22 H1 :

Sanitary Paper Corrugated fibers PET bottles Film Organic Wood Metal Glass

Equality of means H0: l1 = l2 H1: l1 – l2

r21 –r22

F0

Equal?

P

df

C.I.

Summer vs. winter?

1.17 2.3 1.95 1.17 3.33 3.82 0.78 0.62 0.89

Yes No No Yes No No Yes Yes Yes

0.204 0.144 0.001 0.000 0.071 0.000 0.000 0.000 0.002

72 62 65 72 55 53 72 72 72

(1.59, 0.34) (1.91, 0.28) (2.99, 0.85) (3.55, 1.8) (0.11, 2.67) (7.89, 13.79) (3.41, 1.69) (4.26, 2.78) (2.29, 0.55)

Same Same Winter higher Winter higher Same Summer higher Winter Higher Winter higher Winter higher

is statistically adequate and that the dataset is independent, unbiased, and thus a valid representation of the broader municipal waste activity of the region. 4. Results and discussion 4.1. Waste generation rate Waste generation data for the past 18 years were collected from Kuwait Municipality monthly records (Fig. 1). Fig. 1 illustrates the fluctuating growth in the annual waste generated, which may be associated with the steady population growth. In 1994, the quantity of solid waste generated appeared to be at its maximum level (975,205 tons) even though the population was at its lowest (below 2 million) due to the dumping of debris and wreckage for the four years following the Gulf War (1992–1995) (Koushki et al., 2004b). The apparent decrease in waste masses between 2003 and 2006 is misleading, as this decrease was only present in data records, not in the actual tonnage of waste generated. In 2003, new MSW management abandoned the Al-Jahra site, which led to temporary dumping outside the municipality jurisdictions until 2007 (Al-Fares et al., 2009). These quantities were not documented, which led to the apparent decrease in the data. The average waste production rate over the past 5 years was 1.01 kg/day/capita. Collaborative governmental-social efforts mentioned above have allowed the daily waste generation rate to remain constant at approximately 1 kg/day/capita.

Fig. 3. Differences between the current waste composition and a 1995 baseline. W&S refers to wood and sanitary; P&C refers to paper and corrugated fibers; and PET&F refers to PET bottles and film.

Table 5 Statistical comparison of the 1995 and 2012 MSW compositions. Waste category

Hypotheses

Sanitary & Wood*

H0: l = 7.4, H1: l – 7.4 P = 0.0 C.I. (4.9, 5.67)

t 10.7

H0: l = 18.1, H1: l – 18.1 P = 0.0 C.I. (7.34, 8.17)

t 48.4

H0: l = 13, H1: l – 13 P = 0.0 C.I. (8.64, 9.71)

t 14.1

H0: l = 51.9, H1: l – 51.9 P = 0.0 C.I. (42.13, 45.91)

t 8.17

H0: l = 5, H1: l – 5 P = 0.089 C.I. (3.979, 5.072)

t 1.70

H0: l = 4.6, H1: l – 4.6 P = 0.0 C.I. (5.87, 6.75)

t 7.74

Paper & corrugated fibers*

PET Bottles & Film*

Organic*

4.2. Descriptive statistics Metals

Detailed waste characterization data were summarized and segregated by season, and the results are shown in Table 3. A total of 666 samples from 37 trucks in summer (333 data points) and 37 trucks in winter (333 data points) were collected. The results indicated that organic waste comprised the highest weight percentage (44%) of the MSW for both seasons. The second highest weight percentage was attributed to film waste (11%), followed by corrugated fibers (8.7%). These results fit well with results from countries with similar climates, cultures, and manufacturing and trading practices (see Table 1). The percent composition of metal waste and wood waste was the lowest in winter and summer, respectively. Further analyses and discussion on seasonal effects are presented in the following section. 4.3. Effect of seasonal variations on solid waste composition The local climate mainly consists of the summer and winter seasons, with summer being the dominant season. According to the official Kuwait Metrological Administration, winter starts on

Glass*

*

N 148

148

148

74

74

74

Waste categories significantly different from the 1995 baseline.

December 6th and lasts for 71 days, whereas summer starts on May 21st and lasts for 167 days. The period from April 16th to May 20th is considered warm spring or early summer, and the periods between the two major seasons are not clearly distinguished as spring or autumn. In Fig. 2 and Table 4, the subscripts 1 and 2 denote summer and winter, respectively. Fig. 2 displays box plots for each waste category with respect to season. Organic waste is dominant in both seasons, followed by film and corrugated fibers. These observations have not yet been verified statistically. Table 4 displays a null hypotheses investigating the equality in mean composition H0: l1j ¼ l2j with the alternative hypotheses asserting the contrary,

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Table 6 ANOVA of the waste composition with respect to governorates and seasons. Source

Sum of squares

Factor 10,260.57 Error 334.54 Total 10,595.11 S = 2.304 R-Sq = 96.84% R-Sq(adj) = 96.44%

Degrees of freedom

Mean square

F

P-Value

8 63 71

1282.57 5.31

241.53

0.00

Table 7 Regression models for the factorial analysis. X1 represents the season, and X2 represents the governorate. Waste type

Sanitary waste Paper Corrugated fibers PET Bottles Film Organic Waste Wood Metals Glass

Regression model

4.83 + 1.04 x1 + 0.051x2 6.52 + 0.175x1 + 0.020x2 4.66 + 2.51x1 + 0.137x2 4.56 + 1.77 x1 + 0.141x2 11.9  0.676x1  0.0476x2 61.2  10.2x1  0.879x2 0.709 + 2.41 x1  0.0060x2  0.179 + 2.97 x1 + 0.164x2 5.23 + 0.498 x1 + 0.277x2

Significant factor

Regression adequacy

x1

x2

R2 (%)

Adequate?

Yes  Yes Yes Yes Yes Yes Yes 

  Yes    Yes  

44 5.6 88 39 62 81.9 97.6 83.2 14

No No Yes No Possible Yes Yes Yes No

Fig. 4. Main-effects plots for (a) organic, (b) wood, (c) corrugated, (d) metal, (e) sanitary, (f) PET bottles, (g) glass, and (h) paper. Seasons: summer (1) and winter (2); Governorates: Hawalli (1), Mubarak Al-Kabeer (2), Farwaniya (3), and Al-Asima (4).

H1: l1j – l2j where j = 1, 2, . . .9 denotes the MSW categories of sanitary waste, paper, corrugated fibers, PET bottles, film, organic, wood, metal, and glass, respectively. To assess the difference in mean composition, the equality of variances (H0: r21 ¼ r22 ) was assessed first, and then, the appropriate mean equality assessment method was selected.

Table 4 compares the test statistic F0 with a critical value Fa to examine the differences in seasonal variances. MSW categories of equal variances among seasons required the calculation of spooled variances for mean hypothesis testing. The H0 was rejected when the test statistic exceeded a critical value t for a specific degree of freedom df or when P < a, where a = 0.05. Thus,

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Fig. 4 (continued)

Fig. 6. Interaction-effects plot of paper waste. Fig. 5. Matrix plot comparing the governorates with respect to family members per household and average income (governorates 1, 2, 3, and 4 are Hawalli, Mubarak Al-Kabeer, Farwaniya, and Al-Asima, respectively).

4.4. Comparison of the current MSW composition to the 1995 baseline

the results indicate that the corrugated fibers, PET bottles, wood, metal, and glass wastes had significantly higher proportions in winter. However, organic waste had a significantly higher proportion in summer, possibly because of the greater amount of dining out and social gatherings in this season. No statistical seasonal variation was observed for sanitary, paper, and film waste. Calculations based on the absolute masses of MSW generation support this result (see Table 3).

Fig. 3 compares the MSW composition obtained in this study to the composition obtained by a similar baseline study conducted in 1995 (Koushki, 1995). In the 1995 study, wood waste and sanitary waste were considered a single category, as were paper and corrugated fibers and PET bottles and film. Thus, the current data of the aforementioned categories were combined to facilitate the comparison. Hypothesis tests were conducted to investigate differences between the composition obtained in the current study and the

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Table 8 Area and population of the four governorates selected for the study. Governorate

Area (km2)

Population (2011 census)

Remarks

Al-Asima Hawalli Farwaniya Mubarak Al-Kabeer

175 85 204 104

326,513 672,910 818,571 258,813

The Has Has The

capital of the state the highest population density; famous for its commercial districts the largest number of expatriate residents (602,346) newest governorate (established in 1999)

Fig. 7. Residual analyses.

1995 average baseline values. For instance, for the sanitary and wood category, the null hypothesis was H0: l = 7.4, and the alternate hypothesis was H1: l – 7.4. Similar hypotheses were created for the remaining categories. Table 5 presents the hypothesis test results and confidence intervals. At a = 0.05, the results indicated that all categories resulted in P < a, with extreme critical values for the test statistic t. Thus, the null hypothesis was rejected, indicating that the results, except for the percentage of metal waste, do statistically differ from those obtained in the 1995 study. The results reveal that the organic waste percent of the total composition decreased by 7.2% compared the 1995 baseline. In contrast, plastics (film and PET bottles combined) increased by 4.6%, possibly due to the increasingly widespread consumption of delivered foods and drinks that are packed and bottled with plastic containers. In addition, the proportion of combined paper and corrugated fibers decreased by 1.8% since 1995. This slight decrease may be due to advances in paperless communication. 4.5. Factorial and regression analyses of the MSW composition with respect to governorates The two factors of governorates and season were crosscombined on the waste composition. The seasonal factor consists

of two levels, summer and winter, whereas the governorate factor consists of four levels, Hawalli, Mubarak Al-Kabeer, Farwaniya, and Al-Asima. Table 6 displays the two-way ANOVA with two levels per season factor and four levels per governorate factor using the 95% significance level. Seventy-two of the 74 truckloads could be associated with governorates. A P value of 0 indicates that the main factors do significantly affect the solid waste composition. The model was validated, as it produced a high overall R2 value of 96.84% and an adjusted R2 value of 96.44%. Table 7 presents the regression formulas to predict each waste percentile with respect to season and governorate. The variables x1 and x2 are the seasonal and governorate variables, respectively. The correct waste percentile was obtained by substituting the values in accordance with the level. Although the overall regression was adequate (96%), not all waste-specific regression models provided such positive results. Only those of corrugated fibers, organic, wood, and metal waste were adequate due to the lack of a significant steady correlation. Fig. 4 presents the main-effects plots for different waste categories with respect to season (right side) and governorate (left side), where the y-axis represents average waste proportion. Main-effects plots are useful in depicting the direction (increase or decrease in

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waste categories); Table 3 provides the significance of these magnitudes. The y-axis is varied in each sub-graph according to the magnitude of each waste category for clarity, and the centerline depicts the overall mean. Fig. 4 illustrates that the effect of the governorate was less significant than the effect of season. The Al-Asima (4) governorate produced the smallest amount of organic waste (Fig. 4(a)) and the largest amount of corrugated fibers (Fig. 4(c)). This governorate ranks second in paper waste generation (Fig. 4(h)). The Mubarak Al-Kabeer (2) governorate produced the largest amounts of sanitary and glass waste (Fig. 4(e) and (g)). The Hawalli governorate produced the largest amount of paper waste (Fig. 4(h)) and the smallest amount of glass waste (Fig. 4(g)), which can be attributed to the large number of schools and local businesses in Hawalli. A considerable number of businesses are also located in the Al-Asima governorate (the capital of the State of Kuwait), which explains why it has the second-highest paper waste generation rate. Organic waste (Fig. 4(a)) was higher in the summer (1) than in winter (2). All other types of waste (approximately 56%) were higher in winter (2). In addition to the effect of seasonal variations, the effect of geographic location (represented as governorate) was also examined. Kuwait Municipality adopted the same waste management practice in all of the governorates. Fig. 5 and Table 8 comparison the waste generation rates of the governorates. The paper waste exhibits a considerable seasonal variation, as depicted in the interaction plot in Fig. 6. Paper waste is greater in winter (2) than in summer (1) due to academic summer vacations. The Mubarak Al-Kabeer and Farwaniya governorates also produced significantly less paper waste in the summer because of the lack of school activity. The Hawalli (1) and Al-Asima (4) governorates remain the highest producers of paper waste in summer because of business activities. 4.6. Assessment of the model adequacy Residual analyses were conducted to ensure that the model’s underlying statistical assumptions of normality and independence were valid (Montgomery, 2008). Fig. 7(a) presents the normal distribution of the results. Fig. 7(b) presents the plot of the residuals versus the fitted values, which indicates that the model variables are not bias. Fig. 7(c) presents the run test of the residuals. No clear pattern is evident, and thus, the runs were independent. The histogram of residuals in Fig. 7(d) supports the model assumptions. The model adequacy analyses indicate that the overall assumptions of the tests applied are fit and valid, and thus, the conclusions and predictions are reliable. 5. Conclusions This study formally established an up-to-date weight and composition of various MSW fractions generated in Kuwait. The daily average municipal waste for the last 5 years was found to be 1.01 kg/person. A direct sampling of raw municipal waste streams was conducted using the ASTM D5231-92 standard method to determine the MSW composition. The results of the study indicated that organic waste is dominant (44.4%), followed by film (11.2%) and then corrugated fibers (8.6%). Hypothesis tests were conducted to compare the municipal waste composition among seasons and indicated that season had a significant effect on composition. The summer had a higher proportion of organic waste, whereas winter produced higher proportions of corrugated fiber, PET bottle, wood, metal, and glass waste. A statistical comparison with a previously published waste characterization baseline from 1995 indicated that the proportions of all waste categories except metal waste have changed significantly. These significant changes in waste composition indicate a new trend in population lifestyle,

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which must be considered when planning future waste treatment scenarios. Although the data collection samples in percentile and tonnage are statistically reliable, the idea of collecting data with a higher level of detail within subcategories of dominant waste classes is inevitable. Further analysis on waste trends with respect to household, commercial, and industrial sectors is also necessary. Because organic waste treatment options depend on waste origin, it is important to determine whether the organic waste is pre- or post-consumed and its moisture content. Such information will allow for comparisons between various options, such as composting, biogas production, or utilization as animal feed. In theory, the same argument applies to corrugated fibers and plastic waste (film and PET bottles). However, whether the quantities produced are sufficient for a large-scale waste management system requires further analyses in terms of economies of scale, operating capacities, and break-even analysis. Such analyses must include financial, environmental, social, technical, and legal aspects as well as other criteria for each treatment option. The data presented here will facilitate a thorough compilation and evaluation of the inputs and outputs of such analyses. Despite these considerations, source waste minimization and the at-source separation of recyclables are indispensable aspects of effective waste management that must be required at both the corporation and individual levels through national policy. Acknowledgements The authors would like to acknowledge the Kuwait University Research Administration for funding this research under grant number EV03/10. The authors would like to thank the Kuwait Municipality for their co-operation. The authors would particularly like to thank Dana Shehada, the research assistant for this project, as well as the journal reviewers and editors for their insightful remarks on the manuscript. References Abd-Alqader, A., Hamad, J., 2012. Municipal solid waste composition determination supporting the integrated solid waste management in Gaza Strip. IJESD: Int. J. Environ. Sci. Develop. 3 (2), 172–176. Akinci, G., Guven, E.D., Gok, G., 2012. Evaluation of waste management options and resource conservation potentials according to the waste characteristics and household income: a case study in Aegean Region, Turkey. Resour. Conserv. Recycl. 58, 114–124. Al-Fares, R.A., Al-Jarallah, R.S., Abdulsalam, Z., 2009. Preliminary investigation of AlJahra waste disposal site using electrical resistivity (ER) Surveys, 2nd Kuwait Waste Management Conference & Exhibition, Kuwait City, Kuwait. Al-Jarallah, R., Aleisa, E., 2013. Investigating causes contributing to increased municipal solid waste in Kuwait: a national survey. J. Eng. Res. 1 (3), 123–143. Al-Meshan, M., Mahrous, F., 2002. Management of municipal solid waste ladfills in the State of Kuwait. In: Proceedings of the 2nd Asian Pacific Landfill Symposium, Seoul, Korea. Al-Muzaini, S., 2006. Characteristics of leachate at the Qurain dumping site. Food, Agric. Environ. 4 (2), 251–254. Al-Yaqout, A.F., Koushki, P.A., Hamoda, M.F., 2002. Public opinion and siting solid waste landfills in Kuwait. Resour. Conserv. Recycl. 35 (4), 215–227. Al Yaqout, A.F., Hamoda, M.F., 2002. Report: Management problems of solid waste landfills in Kuwait, Water Management and Research. Kuwait University, United Kingdom, 328–331. Al Yaqout, A.F., Hamoda, M.F., 2005. Prediction of contaminants migration at unlined landfill sites in an arid climate – a case study. Water Air Soil Pollut. 162 (1–4), 247–264. ASTM, 2008. ASTM D5231 – 92(2008) Standard Test Method for Determination of the Composition of Unprocessed Municipal Solid Waste. ASTM D5231 (Waste Management Standards) ASTM International, West Conshohocken, PA. Burnley, S.J., Ellis, J.C., Flowerdewe, R., Poll, A.J., Prosser, H., 2007. Assessing the composition of municipal solid waste in Wales. Resour. Conserv. Recycl. 4, 4–5. Chandrappa, R., Das, D.B., 2012. Solid Waste Management: Principles and Practice. Springer. Dahlén, L., Vukicevic, S., Meijer, J.-E., Lagerkvist, A., 2007. Comparison of different collection systems for sorted household waste in Sweden. Waste Manage. (Oxford) 27 (10), 1298–1305. Defra, 2011. Waste Prevention Programme for England. In: Department for Environment, F.R.A. (Ed.). UK Government, London, UK.

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A baseline study characterizing the municipal solid waste in the State of Kuwait.

This paper provides a new reference line for municipal solid waste characterization in Kuwait. The baseline data were collected in accordance with the...
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