feasibility study of concrete and brick waste recycling program using system dynamics modelling...

Australian Journal of Asian Country Studies

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Feasibility Study of Concrete and Brick Waste Recycling

Program using System Dynamics Modelling Approach

Dat Tien Doan1*

Thanwadee Chinda2

1. Master Student, Sirindhorn International Institute of Technology, Thammasat University, Thailand;

2. Assistant Professor, Sirindhorn International Institute of Technology, Thammasat University,

Thailand;

*Email address of corresponding author: [email protected]

Abstract

In Thailand, many infrastructures have been built, such as building, roads etc. to meet the needs of the

rapid development of economy. This, in turn, leads to the higher construction and demolition waste,

especially concrete and brick waste, with the lower landfill spaces. Recycling program is therefore

needed to properly manage the waste, and avoid the future environmental problems. This paper

investigates the feasibility of the concrete and brick waste recycling program in Bangkok, Thailand,

using a system dynamics modeling technique. The model consists of two main elements, namely the

total costs and the total benefits. Five factors, including the truck costs, the fuel costs to recycling

places, the labor costs, the training costs, and the machine costs, are under the total costs element.

While the total benefits element consists of four factors, namely the savings in leveling costs, the

savings in virgin materials, the savings in landfill charge, and the savings in fuel costs to landfills. The

simulation results show that it takes 21 years for the recycling program to worth the investment. The

government and construction companies could then use the study results as a guideline to plan for their

recycling programs.

Keywords: concrete and brick waste, recycling program, system dynamics modeling, Thailand

1. Introduction

In Thailand, the construction area has increased year by year, leading to the raising in the amount of

construction and demolition (C&D) waste in which concrete and brick waste made up the majority,

around 91.2 % (Sorpimai, 2008). However, almost such waste ends up at landfills whereas it can be

recycled or reused for different purposes, such as for levelling or for replacing sand and gravel in

aggregate. Plus, there are only two main landfills, Khampangsan and Phanomsarakham, to handle the

total waste originating in Bangkok, accounting for one fourth of the amount of waste in this country.

(Chinda et al., 2012a). This tendency may, in turn, lead to the shortage of landfills and negative impacts

on the environment in the near future.

Although C&D waste recycling has been researched for a long time, at least from 2001 according to

Yuan and Shen (2010), especially in developed countries. However, until now it has still received

inconsiderable attention from construction companies in Thailand in general and in Bangkok in

particular. And those published papers did not concentrate on economic factor, one of the essential

criteria that assists such companies consider whether they should investigate in recycling program or

not (Chinda et al., 2012b).

In this paper, the feasibility of the concrete and brick waste recycling program in Bangkok is

investigated by using a system dynamics modeling (SD) technique to help construction companies have

a better view in this activity. They could then use the study results as a guideline to plan for their

recycling programs. By doing this, landfills may receive less waste than they used to be and the

environmental pollution can be solved.

2. The development of concrete and brick waste recycling program model

SD, introduced by Forrester (1958), is an efficiency tool that can provide a deep insight of the behavior

of a complex system. It can be used to build the model in the real world that describe the

interrelationship between variables and create different scenarios that can be happened. Users‘

decision-making progress will be better because they can use this tool to predict the future situations.

Therefore, it has been used widely in many studies with various domains, especially in C&D waste in

recent years. Hao et al. (2007, 2008 and 2010) adopted SD method for C&D waste management,

evaluating the alternative of type in C&D waste recycling center was carried out by Zhao et al. (2011)

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and Karavezyris et al. (2002) used SD method to forecast municipal solid waste.

The model in this paper consists of two main elements, namely the total costs and the total benefits.

Five factors, including the truck costs, the fuel costs to recycling places, the labor costs, the training

costs, and the machine costs, are under the total costs element. While the total benefits element consists

of four factors, namely the savings in leveling costs, the savings in virgin materials, the savings in

landfill charge, and the savings in fuel costs to landfills.

2.1 Total costs element

Figure 1 shows the total costs element that is the sum of five different factors; training costs, labor

costs, fuel costs to recycling places, truck costs, and machine costs, see (1).

Total costs = Training_Costs_submodel.Training_Costs + Labor_Costs_submodel.Labor_Costs +

Fuel_Costs_to_construction_sites_submodel.Fuel_Costs + Truck_Costs_submodel.Truck_Costs +

Machine_Costs_submodel.Machine_Costs (1)

Figure 1. The total costs element

2.1.1 Training costs factor

To have a higher productivity in concrete and brick waste sorting activity, new labors who are recruited

for this sector will be trained for five days before working. One way to save a large amount of money

for this is that trained workers in the first year will train others in the following years. In other word,

the costs for training (as shown in Figure 2) are only paid in the first year, see (2).

Training costs = IF Year = 1 THEN New_Sorting_Labors*Cost_per_Labor*(1+Inflation_Rate) ELSE 0

(2)

Figure 2. Training costs factor

2.1.2 Labor costs factor

In this part, the costs are based on the number of labors working in recycling sector, see (3). And the

total amount of waste that is sorted (as shown in Figure 3) will help to define the number of workers,

see (4). In each year, the total sorted waste is computed by the working productivity of new recruited


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labors and current labors.

Labor costs = IF Year = 0 THEN 0 ELSE (Final_Total_New_Sorting_Labors +

Final_Total_Regular_Labors)*Number_of_Working_Days*Wage_per_Labors*(1 +

Inflation_Rate)^Year (3)

Final sorted waste = IF Year = 0 THEN 0 ELSE IF Year=1 THEN

Sorting_Productivity*(Final_Total_New_Sorting_Labors*(Number_of_Working_Days –

Number_of_Training_Days) + Final_Total_Regular_Labors* Number_of_Working_Days) ELSE

Sorting_Productivity*( (Final_Total_Regular_Labors + Final_Total_New_Sorting_Labors -

Final_Training_Group - Final_New_Sorting_Labors)* Number_of_Working_Days +

(Final_Training_Group+Final_New_Sorting_Labors)*(Number_of_Working_Days –

Number_of_Training_Days)) (4)

Figure 3. Labor costs factor

2.1.3 Truck costs factor

In order to transport the concrete and brick waste to landfills or recycling places, construction

companies need to buy or hire trucks. In this paper, trucks will use natural gas vehicle (NGV) instead

of diesel to save the cost for fuel, according to Jaroonrat Engineering company. The truck costs are sum

of buying costs and renting costs, see (5). The costs for buying new trucks are calculated based on nine

factors; including NGV installation cost, cost for new trucks, big maintenance cost, selling trucks

savings, regular maintenance cost, tire cost, insurance cost, driver cost, and route cost, see (6). While

six elements are used to define the costs for rent; regular maintenance cost, tire cost, insurance cost,

driver cost, rental trucks cost and route cost, see (7).

Truck costs = Buying_Costs + Renting_Costs (5)

Buying costs = NGV_Installation_Cost + Cost_for__New_Trucks + Big_Maintenance_Cost -

Selling_Trucks_Saving + (Regular_Maintenance_Cost + Tire_Cost + Insurance_Cost + Driver_Cost +

Route_Cost)*Bought_Trucks (6)

Renting costs = (Regular_Maintenance_Cost + Route_Cost + Tire_Cost + Insurance_Cost +

Driver_Cost + Rental_Trucks_Cost)*Number_of_Rented_Trucks (7)


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2.1.4 Fuel costs factor

Figure 5 shows the way to determine the fuel costs. They are the product of the fuel cost per kilometer

and the distance from construction sites to recycling places, see (8).

Fuel costs = Distance*Fuel_Costs_per_km (8)

Figure 4. Truck costs factor

Figure 5. Fuel costs factor

Figure 6. Machine costs factor

2.1.5 Machine costs factor


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Machines will be bought to crush brick and concrete. The number of machines depends on the total

waste that labor sorted (as shown in Figure 6). And its costs are shown on (9).

Machine costs = Number_of_Bought_Machines*Cost_per_Machine*(1+Inflation_rate)^Year (9)

2.2 Total benefits element

Figure 7 shows the total benefits element that is the sum of four factors; including savings in fuel costs

to landfill, savings in landfill charge, savings in levelling costs, and savings in virgin materials, see

(10).

Total benefits = Savings_in_Fuel_Costs_to_Landfill_submodel.Fuel_Costs

Savings_in_Landfill_Charge_submodel.Savings_in_Landfill_Charge

Savings_in_Leveling_Costs_submodel.Savings_in_leveling_cost

Savings_in_Virgin_Materials_submodel.Savings_in_virgin_materials (10)

Figure 7. The total benefits element

2.2.1 Savings in fuel costs to landfill factor

When the waste recycling program is applied by construction companies, fuel costs are saved (as

shown in Figure 8). That is because the average distance from construction sites to recycling places is

less than the distance from construction sites to landfills, see (11).

Savings in fuel costs to landfill = Distance*Fuel_Costs_per_km +

Number_of_Trucks*(Regular_Maintenance_Cost + Tire_Cost) (11)

Figure 8. Savings in fuel costs to landfill factor


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Figure 9. Savings in landfill charge factor

2.2.2 Savings in landfill charge factor

A large amount of money can be saved from landfill charge because almost concrete and brick waste is

reused or recycled rather than being transported to landfills (as shown in Figure 9). (12) shows the way

to determine the savings.

Savings in landfill charge =

Fuel_Costs_submodel.Reused_and_Recycled_Waste*Landfill_Charge_per_ton*(1 +

the_Increasing_Percentage_of_Landfill_Charge)^Year_stock (12)

2.2.3 Savings in levelling costs factor

Concrete and brick waste can be reused directly to replace the role of sand or gravel for some activities

such as levelling roads or building (as shown in Figure 10). These savings are affected by the price of

material that is replaced by concrete and brick waste, see (13).

Savings in levelling costs = Reused_Waste*Sand_Price*(1 +

the_Increasing_Percentage_of_Sand_Price)^Year (13)

Figure 10. Savings in levelling costs factor

2.2.4 Savings in virgin materials factor

New aggregate can be created by recycling concrete and brick waste. Such waste will be crushed by

machines to generate standard aggregate (as shown in Figure 11). And the price of aggregate will have

an impact on these savings see (14).

Savings in virgin materials = Machine_Costs_submodel.Recycled_Waste* Aggregate_Price*(1 +

the_Increasing_Percentage_of_Aggregate_Price)^Year (14)

Figure 11. Savings in virgin materials factor

2.3 Financial statement

After defining the total costs and benefits, the feasibility of the recycling program will be assessed by

using net present value (NPV) method (as shown in Figure 12). (15) and (16) help to determine the

financial statement and NPV result.


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Financial statement = Total_Benefits-Total_Costs (15)

NPV result = ∑ Financial_Statement/(1+Rate_of_Return)^Year (16)

3. Results

This dynamic model is stimulated with the iThink program and all the data input is taken from

construction companies in Bangkok. Figure 13, 14, 15 and Table 1, 2, 3 show the results of the study.

Figure 13 indicates that the labor costs make up the majority of the total costs, while the truck costs

fluctuate every ten years. That is because the huge amount of concrete and brick waste needs a large

number of labors, leading to the highest cost and every ten years, construction companies will buy new

trucks to replace the old ones.

In terms of the total benefits (as shown in Figure 14), savings in landfill charge stand at the highest

position and they will increase dramatically every five years owing to the raising in the landfill charge.

Figure 15 shows that although the total benefits are greater than the total cost in the tenth year,

construction companies will get the profit in the twenty first year.

Figure 12. Financial statement

Figure 13. The total costs graphical result

1: Training costs 2: Labor costs 3: Fuel costs to recycling places 4: Truck costs 5: Machine costs

Table 1. Total costs result (Bath)


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Year Training

costs

Labor costs Fuel costs to

Recycling places

Truck costs Machine

costs

Initial

1

0.00

374,418.00

0.00

1,455,763,270.50

0.00

17,388,725.82

0.00

365,532,764.22

0.00

5,427,636.98

2

3

4

5

6

7

8

9

10

11

…

20

21

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

…

0.00

0.00

1,521,090,656.66

1,589,282,516.13

1,660,450,535.27

1,734,875,056.44

1,812,434,438.20

1,893,505,623.02

1,978,140,782.57

2,066,569,415.04

2,158,757,459.51

2,255,131,212.83

…

3,029,271,038.16

3,120,627,639.85

18,917,949.42

20,382,411.69

21,953,175.08

23,843,090.89

25,660,921.03

27,839,489.73

29,941,026.09

32,450,230.13

34,877,301.31

37,765,032.87

…

68,473,987,33

72,952,090.33

66,905,469.68

71,824,065.71

76,933,524.17

97,292,191.56

89,860,897.09

97,171,374.54

103,193,054.91

111,377,245.79

91,334,544.37

567,016,512.46

…

103,915,665.29

782,347,275.30

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

8,760,151.15

…

0.00

12,218,711.97

Figure 14. The total benefits graphical result

1: Savings in fuel cots to landfill 2: Savings in landfill charge

3: Savings in levelling costs 4: Savings in virgin materials

Table 2. Total savings result (Bath)

Year Savings in fuel

costs to landfill

Savings in landfill

charge

Savings in levelling costs Savings in virgin

materials

Initial

1

0.00

80,573,200,43

0.00

583,425,285.00

0.00

8,968,671.54

0.00

385,423,721.76

2

3

86,361,019.75

91,694,189.47

595,882,110.00

608,598,465.00

13,244,040.66

18,267,724.31

402,767,789.24

420,892,339.75


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4

5

6

7

8

9

10

11

…

20

21

97,352,113,78

104,254,060.14

110,663,481.32

118,444,144.57

125,706,298.03

134,481,682.04

142,711,604.86

152,613,332.19

…

250,209,703.79

263,931,460.73

621,556,515.00

1,047,445,245.00

1,069,671,314.25

1,092,393,596.25

1,115,563,383.00

1,139,230,397.25

1,919,438,743.61

1,960,048,125.34

…

5,841,569,565.31

5,882,460,552.27

24,137,713.41

30,990,584.81

38,926,406.05

48,125,772.42

58,744,687.71

70,985,141.72

85,028,022.06

8,478,319.94

…

102,488,301.05

13,001,200.42

439,832,495.04

459,624,957.32

480,308,080.40

501,921,944.02

524,508,431.05

548,111,310.92

572,776,319.91

769,565,898.39

…

1,143,648,141.83

1,327,902,564.68

Figure

15.

Financial statement graphical result

1: Financial statement 2: NPV result

Table 3. Financial statement result (Bath)

Year Financial statement NPV result

Initial

1

0.00

-786,095,936.79

0.00

-701,871,372.14

2

3

4

5

6

7

8

9

10

-508,659,116.12

-542,036,305.00

-576,458,397.28

-213,695,491.63

-228,386,974.29

-257,631,030.03

-286,752,063.33

-317,588,359.04

434,985,385.26

-1,107,371,305.27

-1,493,182,040.76

-1,859,531,773.68

-1,980,788,334.58

-2,096,496,283.43

-2,213,035,477.71

-2,328,849,826.51

-2,443,375,372.78

-2,303,321,720.76


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11

…

20

21

22,032,766.54

…

4,136,255,021.20

3,499,150,060.65

-2,296,987,826.51

…

-222.242,142.58

101,437,828.24

4. Conclusion

This paper uses a system dynamics modeling technique to predict whether the concrete and brick waste

recycling program worth investing. And the results of the model reveal that landfill charge plays an

important role in such program. Therefore, once the government imposes a high landfill charge,

construction companies will surely apply recycling program instead of transporting waste to landfill.

However, as a financial statement shown above, in the beginning years, companies need a lot of capital

so as to pay for equipment and recruit labors, so it is hard for small and medium companies to put such

program into practice. Thus, both government and companies should work together to make this

program more effective. For example, the government can encourage companies participate in this

activity by reducing tax or supporting a part of capital.

There are some limitations in this study. Firstly, all the data is taken from companies in Bangkok, so the

results might be different when applying in other areas. Users ought to adjust this model to make it

more precise. Secondly, there might be more types of costs and benefits in the real situation to add in

the model. For instance, if recycling program was applied by companies, they could gain a benefit from

brand image which could help to attract more customers and get more profit.

References

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