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Abbasi O, Mokhtari M, Askari R, Jambarsang S, Ebrahimi A A. Forecast Future Production and Estimation of Future Costs of Municipal Solid Waste Collection and Transportation System in Yazd Using WAGS Software. J Environ Health Sustain Dev. 2020; 5 (4) :1126-1134
URL: http://jehsd.ssu.ac.ir/article-1-288-en.html
Environmental Science and Technology Research Center, Department of Environmental Health Engineering, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
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Forecast Future Production and Estimation of Future Costs of Municipal Solid Waste Collection and Transportation System in Yazd Using WAGS Software
 
Omid Abbasi 1, Mehdi Mokhtari 1, Roohollah Askari 2, Sara Jambarsang 3, Ali Asghar Ebrahimi 1*
 
1 Environmental Science and Technology Research Center, Department of  Environmental Health Engineering, School of Public Health, Shahid Sadoughi University of  Medical Sciences, Yazd, Iran.
2Health Policy and Management Research, Department of Healthcare Management, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
3 Research Center of Prevention and Epidemiology of Non-Communicable Disease, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
 
A R T I C L E  I N F O   ABSTRACT
ORIGINAL ARTICLE   Introduction: About 50 to 70 percent of the waste management total cost is spent on collection operations, so any little progress in reducing collection costs could significantly reduce total costs. This study aimed to analyze the collection and transportation of municipal solid waste cost in Yazd in the next 15 years.
Materials and Methods: The study location (five areas) was different urban areas of Yazd city.  To analyze the collection and transportation of normal waste cost in Yazd, WAGS software was used. To obtain demographic information, the Statistical Center of Iran data, information about the location of the area, equipment, costs, and taxes related to waste were obtained in cooperation with Yazd Municipality, Recycling Organization, Labor, and Social Affairs Office and field surveys. Apart from WAGS, the ARIMA time series method (1, 1, 0) was also used with SPSS 24.
Results: The highest costs of waste collection belonged to the human resources sector, and personnel costs were 75.24%, machinery supply capital was 13.85%, repair costs were 6.15%, fuel costs were 4.59%, and the costs of the other parts of the total cost of the waste collection were 0.14%.
Conclusion: The total collection and transfer of waste costs were estimated at 10414000 USD to collect and transfer municipal solid waste in Yazd in the next 15 years. Waste generation projection by time series method with the ARIMA model (1, 1, 0) showed more accurate results than waste generation projection with WAGS.
 
Article History:
Received: 02 August 2020
Accepted: 20 October 2020
 
 
 
*Corresponding Author:
Ali Asghar Ebrahimi
Email:
Ebrahimi 20007@ gmail.com
Tel:
+98 3531492273
 
 
 
Keywords:
Municipal Waste Management,
Costs and Cost Analysis,
 Yazd City.
Citation: Abbasi O, Mokhtari M, Askari R, et al. Forecast Future Production and Estimation of Future Costs of Municipal Solid Waste Collection and Transportation System in Yazd Using WAGS Software. J Environ Health Sustain Dev. 2020; 5(4): 1126-34.
 
Introduction
In recent years, environmental issues related to economic development have received much attention from various countries. With increasing environmental awareness of the people and economic development, governments' pressure to pay more attention to these issues has increased 1. Many changes in waste generation in today's world depend on human society and the urban environment 2. Increasing waste, especially in large cities and spending a lot of money to collect and dispose of them, highlights the need to take effective and fundamental steps in controlling the costs of the collection and transportation system 3.
System managers measure the profit and loss of collection as a component of the cost of the integrated waste management system 4.
Waste management is the most challenging and complex issue in the urban environment. As waste generation methods increase and its generated quantity increases, the supplies required for collection become more complex.
Collection system managers need to be familiar with the bills people pay for services to reflect the staggering costs of fuel and the workforce. In general, about 50 to 70 percent of total waste management costs (including collection, transportation, processing, recycling, and disposal) are spent on collection operations, so little progress in reducing collection costs will significantly reduce overall costs 5.
The cost of collection vehicles based on the numbers of program 6500 of the newly registered cost index of the engineering system is summarized in table 1. Collection costs presented in table 1 will vary depending on the type of services provided, the type of collection device used, the number of local staff, travel times, and community characteristics.
Table 1: Common costs related to the collection of segregated and non-segregated waste on site (a).
The type of collected waste Collection cost (dollars per ton) (b)
Manual waste collection with a worker Mechanical waste collection with a worker
Non-segregated
Non-segregated
Waste that remains after the recyclable material is separated
Segregated waste at the site
                  50-70                                      60-80
 
                  70-90                                     80-100
                100-140                                  140-140
(a) Expenditures based on the numbers of program 6500 of the newly registered cost index of the engineering system in 2002.
(b) Costs will vary depending on the type of service, type of collection, staff, features, and characteristics of the collection area.
 
Yazd is the central city of Yazd province and is located in the center of Iran. This city is located between Shirkuh and Khoranagh and in a wide plain with an urban population of 656,474 people, of which more than half of the population of the province (57.66%) are concentrated in the city of Yazd. The five municipal districts include the historical district with a population of 68840 people, the fourth district with 131725 people, the second district with 115033, the third district with 85731 people, and the first district 114330 people. Currently, household waste is collected from house to house or loaded from fixed containers and landed independently 6,7.
In a study conducted by Majlesi et al. in 2012, they concluded that 35 billion Tomans are needed to manage waste collection and transfer in District 1 of Bandar Abbas Municipality in the next 15 years. On average, in the next 15 years, the most basic expenses are related to personnel and furl costs 8.
In a study conducted by Razmjoo Asgarabadi in 2008 using WAGS, it was concluded that the total cost of waste collection in Tehran's 19th district was about 9.3 billion Tomans, which requires about 8 billion Tomans of additional investment by 2021 9. In a study conducted by Karbasi et al. in 2007 in District 22 of Tehran Municipality, it was shown that the highest costs of waste collection belonged to the workforce sector. The total collection costs were 44140 million Rials, which requires an additional investment of 36470 million Rials by 2020 10. In 2007, Zaheri estimated the cost of waste collection in District 22 of Tehran was about 5 billion Tomans. Also, the most basic expenses in this study were related to workforce and fuel costs 11. In a study conducted by Fernandez in 2018, it was stated that Spain is a semi-industrial country with a high rate of urbanization and the per capita generation of waste was 1100 grams. While this amount was about 300 grams 25 years ago; besides, the country has to allocate 350 hectares of its landfill for waste every 25 years. Addressing the issue, the parliament of Spain approved the need to create an integrated waste system consisting of recycling, collection, and disposal of waste in cooperation with the public and private sectors and the public sector, and the National Environmental Protection Agency. In 2001, when the program became operational, it cost $ 110 per ton of waste disposal in the city. Following the implementation of this program and also obliging government or municipal tendering contractors to have 14001 licenses in 2018, it was announced that the average cost of waste disposal in Spain has decreased to less than $ 80 per ton 12. A study in 2014 by Mercus in Belgium estimated that the cost of collecting and transporting each ton of waste was € 60 13. In a study conducted in Portugal by Cruz, the cost of collecting and transporting each ton of waste was estimated at € 49. In this study, the per capita cost per person was estimated at 19.71 Euros per year 14.
In 2016, Ebrahimi et al. concluded that the time series method and the ARMA model show more accurate results in predicting the amount of waste generated 15. The purpose of this study was to determine the municipal waste generation and estimating the investment, labor, fuel, maintenance, and other costs of municipal waste management in Yazd in the next 5 and 15 years.
Materials and Methods
Waste collection and transportation is of great importance. It is necessary to have a high-efficiency collection and transportation system mechanism to minimize costs and reduce community health problems 16.
In this research, WAGS, a management software in the field of waste collection, was used as an optimal waste management tool for analysis. WAGS was developed in 1990 by the United Nations Center for Human Settlements for some of the essential waste management elements, namely collection and transportation. It includes 40 main variables and 16 default variables.
The variables are divided into five categories: demographic information, quantity and quality of waste, location and characteristics of the area, equipment, costs, and taxes10. The information by the Statistical Center of Iran was used to obtain demographic information. Information about the location and characteristics of the area, equipment and costs, and taxes related to waste management were obtained in cooperation with Yazd Municipality, Yazd City Waste Management, Labor and Social Affairs Department, and field surveys in Yazd city and through direct observations.
Apart from WAGS, in order to waste generation projection using the time series method and ARIMA model (1, 1, 0), SPSS 24.0 was used, and the projection results by these two methods were compared.
 
Ethical issue
The proposal of this research was ethically approved with the ethics code of ID IR.SSU.SPH.REC1397.148 and can also be seen on the website of the National Ethics Committee in Biomedical Research.
Results
WAGS has seven outputs, and the economic costs of collection management include capital needed to purchase equipment, spent on workforce costs, fuel, maintenance, and more 17. In the following, each item, along with the relevant table or chart, is explained.
General Information output
According to the software's general information output, the time of waste collection and return of the truck to the disposal site was 245 min, and the compact volume of waste in the truck was 15 cubic meters. The maximum weight of compressed waste in the truck obtained from the software output was 7960 kg. The truck's efficiency in collecting and transferring the waste to the landfill was 85%, and the useful life of the truck in Yazd was 8.3 years.
 
Waste generation projection
According to the projection by WAGS in 2019, per capita waste generation in Yazd was 599.9 grams per day. The daily generated waste of this city was about 373 tons, and the annual waste generation was 136216 tons in 2019. Table 2 shows the amount of generated waste and the waste's density and volume from 2019 to 2033.
Table 2: The amount of generated waste and density and volume of the waste in 2019 to 2033.
Year Population Per capita waste generation per day (g) Total waste generation per day (tons) Total waste generation per year (tons) Municipal Compressed
Density
(kg / m3)
Volume (m3) Density (kg/m3) Volume (m3)
2019 621993 5599.9 373.194 136216 310 439406 560 243243
2020 636983 603 384.101 140197 311 450794 561 249906
2021 652334 606.01 395.323 144293 313 461000 563 256293
2022 668055 609.04 406.876 148510 315 471460 565 262850
2023 684155 612.08 418.764 152849 316 483699 566 270051
2024 700643 149.615 431 157315 318 494701 568 276963
2025 717529 218.618 443.59 161912 319 507561 569 284555
2026 734821 621.307 456.55 166643 321 519137 571 291844
2027 752531 624.412 469.89 171513 323 531000 573 299325
2028 770667 627.547 483.630 176525 324 54830 574 307535
2029 789240 630.683 497.761 181683 326 557310 576 315422
2030 808260 633.838 512.306 186992 327 571841 577 324076
2031 827729 637.003 527.273 192455 329 584970 579 332392
2032 847688 640.188 542.68 198079 331 598426 581 340928
2033 868117 643.391 558.539 203867 332 614057 582 350287
 
In the following, using the time series of the ARIMA model (1, 1, 0), the amount of waste generated during the years 2019 to 2024 was projected, presented in table 3.
Table 3: Waste Forecast future production by time series method during the years 2019 to 2024.
Year Population Per capita waste generation per day (g) Total waste generation per day (tons) Total waste generation per year (tons)
2019 621993 613.69 318.126 139110
2020 636893 619.307 394.431 143965
2021 652334 624.959 407.669 148797
2022 668055 630.574 420.844 153605
2023 584155 636.220 433.959 158392
2024 70643 641.840 447.018 163158
 
By comparing the statistics obtained from WAGS and projection of the amount of waste generation by time series method with ARIMA model (1, 1, 0) and the statistics obtained by Yazd Waste Management Organization in 2019 regarding the amount of waste generated, we concluded that the time series method and the ARIMA model (1, 1, 0) had a better projection of the amount of waste generation than WAGS. In table 4, these two methods were compared with the Waste Management Organization statistics in 2019. As it is shown, the statistics obtained from the projection made by the time series method with the ARIMA model (1, 1, 0) were closer to the statistics reported by the Yazd Waste Management Organization and had higher accuracy.
 
Table 4: Comparison of waste generation projection by time series method with the ARIMA model (1, 1, 0) and WAGS.
Year Source of the Statistics Per capita waste generation per day (g) Total waste generation per day (tons) Total waste generation per year (tons)
2019 Yazd Waste Management Organization 609.15 378.887 138293
WAGS Projection by WAGS 599.9 373.194 136216
ARIMA Model (1, 1, 0) Projection by time series 613.69 381.126 139110
 
Equipment Projection and Capital Projection
WAGS software showed that in 2019, 64 trucks were necessary for waste collection, which is consistent with the current situation in the studied area. Table 5 presents the number of trucks required to be purchased from 2019 to 2033. To supply the required equipment in the years 2019 to 2033, the capital projection was done. In the base year (2019), a total of 963,000 USD was paid, which included 64 trucks from previous years to 2019. Table 6 shows the capital required to supply the trucks in the years 2019 to 2033.
Table 5: Number of Machinery required to be purchased and capital required to supply
the trucks years from 2019 to 2033
Year Number of required Machinery Number of Machinery required to be purchased Annual capital requirement (thousand dollars) Total capital  requirement (thousand dollars)
2019 64 64 963 64
2020 66 2 30 2
2021 68 2 30 2
2022 70 2 30 2
2023 72 2 30 2
2024 74 2 30 2
2025 76 2 30 2
2026 79 3 45 3
2027 81 2 30 2
2028 83 2 30 2
2029 86 3 45 3
2030 88 2 30 2
2031 91 2 45 2
2032 93 2 30 2
2033 96 3 45 3
 
Labor Projection
Table 6 shows the capital required to provide labor. This table shows the increase in driver, labor, and management costs from 2019 to 2033.
Fuel and Maintenance Projection
Table 7 shows the fuel and maintenance projection from 2019 to 2033.
Finance Cost Projection
Table 8 shows the capital for the equipment supply, labor, fuel, maintenance, and other items. Figure 1 shows the percentage of each of the above compared to the total costs.

 
Table 6: Labor costs (labor, driver, and management) from 2019 to 2033.
Year Number of drivers Driver fee per year (thousand dollars) Number of labor Labor cost per year (thousand dollars) Total driver, labor, and management costs per year (thousand dollars)
2019 64 166 128 218 422
2020 66 172 132 224 436
2021 68 177 136 231 449
2022 70 182 140 238 462
2023 72 187 144 245 475
2024 74 192 148 252 488
2025 76 198 152 258 502
2026 79 205 158 269 521
2027 81 211 162 275 535
2028 83 216 166 282 548
2029 86 224 172 292 568
2030 88 229 176 299 581
2031 91 237 182 309 601
2032 93 242 186 316 614
2033 96 250 192 326 634
Table 7: Fuel and maintenance projection from 2019 to 2033.
Year Fuel costs
(thousand dollars)
Maintenance costs
(thousand dollars)
Total fuel and Maintenance costs
(thousand dollars)
2019 26 115 141
2020 27 119 146
2021 27 122 149
2022 28 126 154
2023 29 130 159
2024 30 133 163
2025 31 137 168
2026 32 142 174
2027 33 146 179
2028 33 149 182
2029 35 155 190
2030 35 158 193
2031 37 164 201
2032 37 167 204
2033 39 173 212
Table 8: Total costs of collection and transfer of waste to the landfill during 2019 to 2033.
Year Truck purchase capital (thousand dollars) Labor costs (thousand dollars) Fuel costs (thousand dollars) Maintenance costs (thousand dollars) Other (thousand dollars) Annual total (thousand dollars)
2019 963 422 26 35 1 1447
2020 30 436 27 36 1 530
2021 30 449 27 37 1 544
2022 30 462 28 38 1 559
2023 30 475 29 39 1 574
2024 30 488 30 40 1 589
2025 30 502 31 41 1 605
2026 45 521 32 42 1 641
2027 30 535 33 43 1 642
2028 30 548 33 45 1 657
2029 45 568 35 46 1 695
2030 30 581 35 48 1 695
2031 45 601 37 49 1 733
2032 30 614 37 50 1 732
2033 45 634 39 52 1 771
Total 15-year period 1443 7836 479 641 15 10414
Percentage 13.85 75.24 4.59 6.15 0.14 100
 


Figure 1: Financial costs of Yazd waste collection system.
 
Discussion
The collection of municipal solid waste (MSW) is a strategic issue for countries around the world4. Previous research conducted by Andic in Ardabil and Dehdasht showed that labor costs had the largest share, and then the highest costs were spent on the equipment purchase, which is consistent with the results of this study.17 The results of this study were inconsistent with a study conducted by Koushki et al.18 in Kuwait and Chalkias et al. in Greece, as the results showed that the highest cost after labor costs was spent on fuel.19 The main reason for this difference is the high cost of fuel and the low price of equipment in Greece compared to Iran. According to the above, it can be argued that in order to reduce the cost of labor in the total cost basket, the collection system should be mechanized. By improving the condition of machines and timely maintenance, the cost of fuel can be reduced, and machines' useful life can be increased.
The results of this study are consistent with the results of a study conducted by Ebrahimi and colleagues. In Ebrahimi's study, the time series method and ARMA technique had a more accurate prediction in predicting the amount of waste production .15
In a study conducted in 2010 by Karbasi et al., the supply of equipment accounted for 16.31% of the total budget, which is almost consistent with the present study. In this study, as in the study of Karbasi et al., due to the population's growth rate and the increase in the amount of waste generation, there is a need to buy new machines.
In the study by Razmjoo Askari9, the study by Hekmatnia7, and the study by Karbasi 10, the percentages of fuel supply costs compared to other parts were 2.65%, 2.66%, and 2.71%, respectively. Due to the implementation of the subsidy targeting plan in Iran and the liberalization of fuel prices, this study's percentage of fuel costs was slightly higher than the mentioned studies. It seems that fuel costs can be reduced by improving the condition of machines and timely maintenance.
In the studies conducted by Razmjoo Askari 9, Karbasi 10, Marques 13, and Andik et al.,17 the percentages of maintenance costs were 4.94%, 6.36%, 4.77%, and 3%, respectively, which was almost consistent with the results of our study.
Studies conducted in District 19 of Tehran and Yazd by Asgarabadi9 and Hekmatnia showed that collecting each kilogram of waste per month was 17.4 and 26, respectively, while in this study, it was 149.7 Tomans. Be. This difference was due to the liberalization of fuel prices and the increase in labor costs.
In this study, the average annual cost of collecting each ton of waste was estimated to be 10.62 $. Studies in different countries showed that the cost of collecting each ton of waste was 3.5 $in the United States20, 4.9 $ in Thailand21, and 3.8 $ in Spain12. Comparison of these studies with this study showed that the waste collection system in Yazd is traditional and inefficient, which increases the cost of waste collection management.
Conclusion
The results showed that most of the solid waste management budget was spent on waste collection and transportation costs, of which labor costs and equipment capital have the largest share. Also, in order to waste generation projection, the time series method and ARIMA model (1, 1, 0) showed more accurate results than WAGS waste generation projection.
 To reform the system of waste collection and transportation, municipal policies should be established to optimize the waste management system. To improve the current situation, it is necessary to organize labor and reduce costs by mechanizing the collection system and reducing fuel costs by improving machines' condition and timely maintenance.
Acknowledgments
This paper is based on the results of the master's thesis in environmental health engineering at Shahid Sadoughi University of Medical Sciences, Faculty of Health. The authors would like to thank the Faculty of Health of Shahid Sadoughi University of Medical Sciences and the officials of Yazd Waste Management who cooperated in this research.
Funding
This study was funded by the school of Health of Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
Conflict of interest
We have no competing interests.
 
This is an Open-Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt, and build upon this work for commercial use.
 
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Type of Study: Original articles | Subject: General
Received: 2020/08/2 | Accepted: 2020/10/20 | Published: 2020/12/26

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