# Dynamic Analysis of Construction and Demolition Waste Management System (A Case Study of Tehran, Iran)

Authors: Milad Ghanbari
Journal: Advances in Civil Engineering
 (2022)

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## Abstract

Increasing construction and demolition (C&D) waste generation has faced serious challenges in the metropolitan areas of Iran. The objective of this research is to present a system dynamics model for C&D waste management of Tehran. In particular, variables such as energy consumption and carbon dioxide (CO2) emissions for the city of Tehran to the horizon of 2041 are studied and predicted. Increasing the rate of construction of housing and urban infrastructure will increase C&D waste and, on the other hand, increase the demand for raw materials, which is contrary to the principles of sustainable development. The increase in quarries exploitation and the increase in C&D waste generation can reduce the buildable area of the city. The impacts of such factors are in a cyclic and systemic approach that either reinforces a destructive factor or balances the existing solution. In general, the assessment of the implementation or nonimplementation of C&D waste recycling in each city requires a system insight that examines the aspects of the subject with a systemic perspective over time. To this end, the system dynamic approach, along with the environmental and economic approach of the life cycle, can clarify the hidden dimensions of the problem. One of the important limitations of the research is the large number of variables in the model and finding reliable historical information for these variables.


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## Body

## 1. Introduction

According to the statistics, on average, about 35% of annual waste from countries is related to civil engineering activities and the building construction industry (mainly concrete) [1, 2]. In Tehran, 42,000 tons of construction and demolition (C&D) waste is produced daily, which is not subject to any control and management [3]. Among the C&D waste, about 25% of them are concrete waste, 15% are asphaltic waste, and the rest, other construction waste [2]. Considering the fact that there are concrete residential complexes in the area of industrialization and mass housing, in a large volume, a worry, and dilemma, of the progression of society is “the provision of space for landfilling the C&D wastes” which is one of the future concerns [4, 5].Approximately aggregates (stone aggregates) make up 80% of concrete and 90% of asphalt, so it is easy to say that about 12–15% of Iran’s total waste is aggregates [2]. The operation of hundreds of sand and gravel mines and the excessive, long-term, and unsustainable extraction of these mines have caused much environmental pollution. In general, more than 3 billion tons of raw materials are consumed every year to produce building materials worldwide [3, 6, 7]. This is another concern: what will be the growth of aggregates consumption in the coming years?The global contribution of cement production to carbon dioxide (CO2) emissions and the energy consumption is 7 percent and 12–15 percent, respectively [8]. In the case of aggregates, it should also be noted that the destructive effects are similar to (but less) cement, which requires analysis and evaluation [9]. Another concern is the process of CO2 emissions and energy consumption due to the aggregate sector [10], which needs to be analyzed over time.Given the environmental and economic considerations, recycling, especially waste recycling, is one of the key issues of sustainable development [11–13]. As countries are divided into two developed and developing countries, the same applies in the field of recycling technology, with Japan having 98% recycling of C&D waste (especially concrete waste) and Hong Kong with maximum utilization plans for recycled materials under development [4]. Australia, with a relatively slow process, is currently implementing concrete recycling in its construction industry, and in this case, it is a developing country [4].It should be noted that Iran is severely weak in the recycling industry and is in fact at the very beginning of its development. Because in Iran, the municipalities and the government are still not fully justified in installation C&D waste recycling equipment and they do not support the recycled materials producers. Also, the necessary standards for recycled products have not been published; there are no necessary regulations for financial support for investing in these projects. In Japan, even in the field of recycling, it has even the necessary regulations and guidelines [14]. France has been developing and expanding the use of recycled materials in its developmental areas for sustainable development [15].The effect of recycling materials (especially aggregates) on reducing CO2 emissions and energy consumption needs to be investigated over time because it is highly dependent on population growth rate and construction and the economic condition of the state and other stimulus variables [16]. Tehran is one of the big cities that needs a dynamic study due to the growth of construction, the growth of C&D waste generation, the population growth, and environmental consequences. Therefore, the main issue of this research is to investigate the future impacts of the extraction and recycling of stone materials in Tehran by considering the interaction of stimulus variables in the time horizon. Therefore, the present research seeks to study the dynamics of aggregate production and recycling in Iran, especially in Tehran, to develop a paradigm of C&D waste management. This dynamic paradigm, which is the innovation of this research, examines the interaction of the variables of several systems dynamically. The results of this research will be useful for any other area that has similar conditions to Tehran; therefore, the results of this research can be applied to other metropolises of the world with a little adjustment.


## 2. Methodology and Materials

### 2.1. Construction and Demolition Waste

The use of life cycle assessment theory is at the center of many environmental and economic researches. The use of LCA in the evaluation of in C&D waste recycling indicates that CO2 emission should be studied as an important variable [17]. This variable is directly related to energy consumption [18] and transportation distances [17] and is in line with green development.Alhawat et al. investigated the environmental research related to geopolymers from C&D waste, and they showed that the production of geopolymer concretes from C&D waste has acceptable properties with ordinary concrete [19]. Also, another research has studied the use of such recycled materials (geopolymer mortars) in 3D printing and achieved an acceptable compressive strength [20].The economic evaluation of C&D waste recycling has also been investigated in a research in Brazil, and it showed the feasibility of installation a recycling plant with a capacity of 90 tons per hour in Rio Branco [17]. The study of the supply chain management of recycled products has shown that the government has a direct effect on the pricing of these recycled materials; also, the profit of manufacturers and retailers in this chain depends on the level of government support [21]. On the other hand, according to another research [22], the profit of this chain depends on the competition between channels, the market share of recycling channels, and the efficiency of environmental responsibility investments; this benefit is generally dependent on information sharing [22]. In general, increasing the effectiveness of resources in the C&D waste management system requires considering the circular economy [23]. The use of circular economy causes innovation in the recycling process, evaluation of C&D waste recycling management performance, and also the creation of new treatment methods [24].Approximately most related researches have evaluated two or one of the following policy options [1]:(I) Landfilling the C&D waste; the continuation of C&D waste landfilling and nonrecycling of the C&D waste (using 100% natural aggregate for concrete, asphaltic, and road construction). They dispose the C&D waste into landfills, in which case they will have to use new and original mineral resources. So, they are once again faced with the extraction of rock in mines and their crushing and processing in crushing plants to produce new raw materials. (II) Recycling the C&D wastes; establishment of a central recycling plant and use of recycled aggregates in construction applications (using 100% recycled aggregates in concrete, asphaltic, and road construction). They will recycle the C&D waste instead of landfilling it.In general, this research seeks to present a solution for reducing C&D waste landfilling, as its environmental and economic implications are described in detail. This research examines the current situation in Iran and, more precisely, the city of Tehran. Therefore, the proposed model should be applied, and in this regard, it is necessary to seek out the feasibility of the establishment of recycling plants at the site of C&D waste landfills, to eliminate the current crisis of metropolises. Therefore, two policies of natural and recycled aggregate production should be carefully evaluated from a dynamic viewpoint. For dynamical analysis, the system dynamics (SD) method is used.


### 2.2. System Dynamics

Problems of human societies and organizations are becoming more complex and their solution requires better thinking [25]. There are many cases where the efforts of managers and authorities to solve a problem only made it easier and, after a short time, the situation has been the same as before, or it has led to problems that have become larger and worse. The system approach claims to provide a method for a more consistent approach to complexity. The purpose of system thinking is to improve understanding of the relationship between the performance of each organization with its internal structure and its operational policies (as well as the operational policies of its customers, competitors, and suppliers) to use this understanding to design effective leverage policies [26].System dynamics in mathematics and solving industrial-social and managerial problems are referred to as systems that change with time [26], such as a function that describes the time dependence of the different points of a moving pendulum or running water in a pipe [26]. The dynamical system for any given time has a “state” that can be expressed by a set of real numbers represented by a point in a “state space.” For each small change in the system dynamic model, there is a small change in the corresponding numbers [26].System thinking is a framework, method, and law and a rational one for understanding an issue that involves aspects of analytics (components of a problem) and aspects of a combination (the whole of the problem) [26]. To understand the system, it must first be defined. After determining the limitations of the system, it can be classified and understood from different angles. The system definition must be comprehensive and specific. That is, all systemic thinking in different sciences can be used by observing its boundaries. No system is aimless [26]. A nontarget system is a mass of elements. The system can have several goals. The goal can be hierarchical. Each subsystem can be part of the goal (obvious, hidden, wanted, or unwanted purposes of the system). One of the mechanisms that are available in most systems is feedback [26].


## 2.1. Construction and Demolition Waste

The use of life cycle assessment theory is at the center of many environmental and economic researches. The use of LCA in the evaluation of in C&D waste recycling indicates that CO2 emission should be studied as an important variable [17]. This variable is directly related to energy consumption [18] and transportation distances [17] and is in line with green development.Alhawat et al. investigated the environmental research related to geopolymers from C&D waste, and they showed that the production of geopolymer concretes from C&D waste has acceptable properties with ordinary concrete [19]. Also, another research has studied the use of such recycled materials (geopolymer mortars) in 3D printing and achieved an acceptable compressive strength [20].The economic evaluation of C&D waste recycling has also been investigated in a research in Brazil, and it showed the feasibility of installation a recycling plant with a capacity of 90 tons per hour in Rio Branco [17]. The study of the supply chain management of recycled products has shown that the government has a direct effect on the pricing of these recycled materials; also, the profit of manufacturers and retailers in this chain depends on the level of government support [21]. On the other hand, according to another research [22], the profit of this chain depends on the competition between channels, the market share of recycling channels, and the efficiency of environmental responsibility investments; this benefit is generally dependent on information sharing [22]. In general, increasing the effectiveness of resources in the C&D waste management system requires considering the circular economy [23]. The use of circular economy causes innovation in the recycling process, evaluation of C&D waste recycling management performance, and also the creation of new treatment methods [24].Approximately most related researches have evaluated two or one of the following policy options [1]:(I) Landfilling the C&D waste; the continuation of C&D waste landfilling and nonrecycling of the C&D waste (using 100% natural aggregate for concrete, asphaltic, and road construction). They dispose the C&D waste into landfills, in which case they will have to use new and original mineral resources. So, they are once again faced with the extraction of rock in mines and their crushing and processing in crushing plants to produce new raw materials. (II) Recycling the C&D wastes; establishment of a central recycling plant and use of recycled aggregates in construction applications (using 100% recycled aggregates in concrete, asphaltic, and road construction). They will recycle the C&D waste instead of landfilling it.In general, this research seeks to present a solution for reducing C&D waste landfilling, as its environmental and economic implications are described in detail. This research examines the current situation in Iran and, more precisely, the city of Tehran. Therefore, the proposed model should be applied, and in this regard, it is necessary to seek out the feasibility of the establishment of recycling plants at the site of C&D waste landfills, to eliminate the current crisis of metropolises. Therefore, two policies of natural and recycled aggregate production should be carefully evaluated from a dynamic viewpoint. For dynamical analysis, the system dynamics (SD) method is used.


## 2.2. System Dynamics

Problems of human societies and organizations are becoming more complex and their solution requires better thinking [25]. There are many cases where the efforts of managers and authorities to solve a problem only made it easier and, after a short time, the situation has been the same as before, or it has led to problems that have become larger and worse. The system approach claims to provide a method for a more consistent approach to complexity. The purpose of system thinking is to improve understanding of the relationship between the performance of each organization with its internal structure and its operational policies (as well as the operational policies of its customers, competitors, and suppliers) to use this understanding to design effective leverage policies [26].System dynamics in mathematics and solving industrial-social and managerial problems are referred to as systems that change with time [26], such as a function that describes the time dependence of the different points of a moving pendulum or running water in a pipe [26]. The dynamical system for any given time has a “state” that can be expressed by a set of real numbers represented by a point in a “state space.” For each small change in the system dynamic model, there is a small change in the corresponding numbers [26].System thinking is a framework, method, and law and a rational one for understanding an issue that involves aspects of analytics (components of a problem) and aspects of a combination (the whole of the problem) [26]. To understand the system, it must first be defined. After determining the limitations of the system, it can be classified and understood from different angles. The system definition must be comprehensive and specific. That is, all systemic thinking in different sciences can be used by observing its boundaries. No system is aimless [26]. A nontarget system is a mass of elements. The system can have several goals. The goal can be hierarchical. Each subsystem can be part of the goal (obvious, hidden, wanted, or unwanted purposes of the system). One of the mechanisms that are available in most systems is feedback [26].


## 3. Dynamic Analysis

In the present system dynamics model, two main options including the production of natural aggregate (current approach of Iranian) and C&D waste recycling are systematically evaluated along with the consequences of their selection for the city of Tehran on the horizon of 2041 for the based period from 2006 to 2021. In this section, which is a dynamic approach, the consequences of each option are evaluated, using Vensim software for this purpose. Before starting the modeling process, it is necessary to display the desired system and its important elements. The show, the data, and the theories contained in the research subject depict the capacity of the human mind to determine what the behavior of the system depends on.


### 3.1. System Dynamics Methodology

First, the problem is evaluated and defined. In the following, according to the process mentioned, the method of implementing system dynamics for the subject of this research is described.


#### 3.1.1. Dynamic Statement or Hypothesis

According to previous studies, 70 to 80 percent of the materials used in the construction of buildings and road projects are aggregates used in concrete and asphalt products [2]. Iran, especially Tehran, is rich in stone resources and mines, so there is no limit to the sources of stone materials; however, this kind of attitude is contrary to the principles of sustainable development [27–29]. Utilizing sand and gravel quarries for aggregate processing, as one of the building materials, will increase energy consumption [2] and, consequently, increase the emission of CO2 [1, 30]. The rate of construction is dependent on population growth and is directly linked to the economic growth of the city and the country. Building construction in cities will increase the generation rate of C&D waste [31]. The municipality’s most important action for C&D waste is landfilling that will result in landfill capacity being completed. Cities, especially metropolises, are facing a shortage of urban space due to population growth and construction [31]. Landfills should be as close to or near the city as possible because of the transportation and collection costs of urban waste [32–34]. Today, the metropolitan margin is considered as a residential building area; therefore, the occupancy of the city’s marginal lands by landfills, despite the imposed costs, reduces the buildable infrastructure of housing [35].In addition, with the construction of each of these landfill centers on the periphery of the city, the area around it is unusable for reasons of safety, noise pollution, environmental pollution, and smells. Generally, the construction of these centers outside the city (especially away from the city) will increase costs (related to transportation, time, and human resources) [32–34]. It is also impossible to set up them at the center of the urban context, so the city’s margin is the main landfill option, which directly reduces the buildable infrastructure of the city. Reducing urban constructable infrastructure will increase the density; in this case, due to the growing demand of the population, the marginalization intensifies, thus creating a cycle. Mining operations and the level of land occupation by them, especially the marginal mines, have the same effects as landfills in the city [33].Therefore, in all cities of the country, despite the extensive use of stone mines, there is limited space for landfilling and municipal waste disposal. Solid waste, especially C&D waste, despite the need for landfills, causes environmental pollution, and recycling can be an effective way to reduce environmental impacts (energy consumption and CO2 emissions) [36, 37]. The landfill process has its own cost, as well as taxes. It seems that with the establishment of recycling centers, aggregates can be recycled, which reduces energy consumption and gas emissions from natural mines, and, on the other hand, can prevent the completion of landfills capacity and the amount of land needed for construction of the new landfill [33]. However, the amount of demand for recycled materials is too low, which could be more effective in its construction if government support and tax increases (landfill and mining costs). Therefore, recycling is a scenario that requires a system review.


#### 3.1.2. List of Dynamics

In the following, the dynamics of this research are described:(i)
Population effect on construction: population is one of the direct drivers of construction. The increase in population will lead to growth in construction. The construction growth in addition to develop the city can also be a migrating factor and accommodate more people in the city. That means increasing the population.(ii)
Interaction of construction and gross domestic product (GDP): GDP growth impacts indirectly on construction [35]. That is, increasing GDP will increase housing demand and, consequently, increase construction costs. However, rising construction rates will directly increase GDP. That is, they will reinforce each other.(iii)
Construction effect on building waste generation: the new construction, as well as the renovation of existing structures (buildings and roads), leads to the C&D waste generation, part of which is the demolition waste that is a function of the existing infrastructure, and the other part, the waste associated with the infrastructure are being built. The increase in C&D waste generation accelerates the completion of the existing landfill capacity. As landfills area increase, the level of land occupancy increases, and in continues when the landfill capacity is completed, with the need to build another landfill, thus occupying a larger surface area. Finally, it reduces the constructable area of the city and the city’s margins, and consequently, it is reasonable to harm the construction.(iv)
The effect of landfill centers (waste disposal) and aggregates production centers on costs: both landfills and the production of stone materials increase the finished cost of aggregates, which is the cost associated with the life cycle (production and landfilling) of aggregates. Increasing this cost will directly increase the cost of construction. Increasing this cost also reduces construction demand, which further decreases the demand for materials and reduces construction and, consequently, reduces waste generation.


#### 3.1.3. Subsystems

The diagram of the subsystems of the C&D waste management system in the framework of the objectives of this research is shown in Figure1. The subsystems of the economy and population, housing, quarries, and landfills are the main subsystems of this research. Variables are also identified in the form of endogenous, exogenous, and excluded variables. Endogenous variables are the ones that are found inside the model, and the exogenous variables are the ones that are externally logged in [25].Figure 1
Chart of the subsystems of the C&D waste management.


#### 3.1.4. The Causal Loops Diagram

According to the dynamic hypothesis, the list of dynamics and subsystem diagrams are described. Now, the causal loop diagram can be defined. According to studies [38–40], economic growth or, in other words, GDP growth will increase housing demand. On the other hand, population growth also increases the demand for housing [27, 41]. Increasing housing demand has led to increased construction growth, or in other words, has led to an increase in built housing [10, 42]. Construction growth also has a positive and direct effect on GDP growth. Thus, the created loop can be defined as shown in Figure 2, which is a reinforcement (R) type, which is represented by the sign R.Figure 2
(R) The causal loop of impacts of the population and GDP on construction. (B1) The causal loop of the impact of mining on reducing construction. (B2) The causal loop of the impact of the C&D waste generation on reducing construction. (B3) The causal loop of the impact of the C&D waste cost on reducing the demand for housing. (B4) The causal loop of the impact of the cost of natural stone materials production on the reduction of housing demand.Increasing construction will increase the demand for construction materials [30, 39, 40], in which only aggregates are investigated. Demand for stone materials also increases the construction and extraction of stone resources from quarries. The exploitation of stone quarries increases the level of occupation of the land, which reduces the area of the city to be built. The existence of a constructable area in the city creates demand for housing [35]. Thus, if the area to be constructed is reduced, it reduces the construction potential or reduces the constructional capability (constructability). This leads to a reduction of construction, and thus, the marginalization around the metropolitan increases. The resulting causal loop is shown in Figure 2, which is a kind of balancing (B) loop and is represented by the sign B1.Increasing the population indirectly (with the growth of construction) leads to an increase in a waste generation [4, 7, 8]. In other words, the growth of housing construction results in the generation of C&D waste due to the waste of resources during the construction and renovation of worn-out urban textures and the depreciated building and roads [35, 39]. The C&D waste generated is disposed in landfills. Therefore, increasing C&D waste generation will increase the capacity of the city’s landfills and increase the landfill occupancy, and will face the city with a lack of space for waste disposal. That is, it reduces the constructable area of housing, as in the previous loop, reduces construction. The corresponding balancing loop is visible in Figure 2 by the sign B2.The cost of waste disposal operations in landfills increases with increasing waste volume [39, 43]. The cost of aggregate production also increases with increasing extraction rates [39, 40]. The sum of these two costs is the cost of production and the landfilling of aggregates, which is the total price of stones. The increase in the cost of aggregate (and however any construction material) will lead to an increase in the cost of building housing [35], thus reducing housing demand by increasing housing prices. The two corresponding balancing loops are shown in Figure 2 by the signs B3 and B4.


### 3.2. Dynamic Modeling (Flow Diagram of C&D Waste Generation)

In this section, the main variables and time horizons are expressed in terms of the description of the problem. Vensim software was used to conduct dynamic analysis. This software was developed for the first time in 1991 by Ventana Systems to develop and analyze dynamic feedback models and is now considered one of the strongest software in the field [25, 26].The time horizon, when used in the system dynamics simulation, should also cover the historical background of the problem so that it can be ensured by the model’s accuracy in the creation cycle of the system and, on the other hand, so long in the future, that the cycle of the problem is completely cover [25]. The whole period of time considered in this research is from 2006 to 2041. In fact, the period from 2006 to 2021 is the base period, and the period from 2022 to 2041 is the prediction period. All of the data needed for modeling are provided from reputable databases such as the Statistics Center of Iran. In cases where there are no complete and historical data required or lacking continuity, experts have also been used to cover the weakness of the data inconsistency of the variable in question. Due to the lack of a complete database of variables in the years before 2006, 2006 was necessarily selected as the starting year. As noted previously, this model is Tehran’s current status on how to use natural stone as well as C&D waste generation.With regard to the problem described in the sections of the dynamic hypothesis and the list of dynamics, the subsystem diagrams, the causal loops, the stock, and the flow diagram of the waste management system in Tehran can be defined and drawn according to Figure3. The dynamic flow model diagram of “Tehran Waste Management” consists of 5 stock variables, 5 flow variables, and 44 auxiliary variables (including auxiliary, constant, and lookup). In total, 54 variables are defined. In this section, the basic values of the system dynamic model are explained. The list of variables used in the modeling and related equations are summarized in Table 1.Figure 3
Chart of stock-flow of C&D waste generation in Iran.Table 1
Variables in the stock and flow diagram.
#TypeNameUnitsEquation1StockPOPThousand personsNet population growth rate2StockArea of houses builtMillion m2Rate of housing construction3StockTotal C&D waste landfilledMillion m3Rate of landfilling4StockTotal CO2 emissionTon CO2 eqRate of CO2 emission5StockTotal energy consumptionTon oil equivalentRate of energy consumption6FlowNet population growth rateThousand persons (year)Factor of net population growth rate∗POP7FlowRate of housing constructionMillion m2 (year)SMOOTHI (demand of new housing, 2.6, 13.646)8FlowRate of landfillingMillion m3 (year)C&D waste generation rate9ConstantLCA-energy-naturalKgoe (ton)2.302410FlowRate of energy consumptionTon oil equivalent (year)(1.6∗demand of aggregate∗“LCA-energy-natural”)∗100011ConstantLCA-CO2-naturalkg CO2 eq (ton)4.460912FlowRate of CO2 emissionTon CO2 eq (year)(1.6∗demand of aggregate∗“LCA-CO2-natural”)∗100013LookupFNPGR lookupThousand personsHistorical data14AuxiliaryFactor of net population growth rate—FNPGR lookup (time)15LookupEFA lookupm3/m2Historical data16AuxiliaryEffect factor of aggregatesm3/m2EFA lookup (time)17AuxiliaryFixed unit price of aggregatesUSD (m3)Unit price of natural aggregate + unit cost of landfilling18AuxiliaryFixed unit price of housing constructionUSD (m2)Fixed unit price of aggregates∗effect factor of aggregates19AuxiliaryDemand for new housingMillion m2ABS ((0.005297∗fixed unit price of housing construction) + (0.156357∗POP) − (0.05343∗GDP) − 1083.34 − area of houses built)20LookupNGDP lookupThousand USDHistorical data21AuxiliaryNormal GDPThousand USDNGDP lookup (time)22AuxiliaryGDPThousand USDNormal GDP + ((fixed unit price of housing construction/1000)∗rate of housing construction) − fixed price of aggregates23LookupPA lookupm3/m2Historical data24AuxiliaryAmount of aggregatesm3/m2PA lookup (time)25AuxiliaryDemand of aggregateMillion m3Percentage of aggregates∗rate of housing construction26ConstantDensity factor—0.6227AuxiliaryExtraction amountMillion m3Demand of aggregate∗density factor28LookupURRQ lookupm3/m2Historical data29AuxiliaryUrban reduction ratio of quarriesm3/m2URRQ lookup (time)30AuxiliaryLand-use of quarriesMillion m2Extraction amount∗urban reduction ratio of quarries31ConstantTotal constructable areaMillion m224032LookupURRL lookupm3/m2Historical data33AuxiliaryUrban reduction ratio of landfillingm3/m2URRL lookup (time)34AuxiliaryLand-use of landfillMillion m2Total C&D waste landfilled∗urban reduction ratio of landfilling35LookupLUAR lookup—Historical data36AuxiliaryLand-use/area ratio—LUAR lookup (time)37AuxiliaryLand-use of houses builtMillion m2Area of houses built∗“land-use/area ratio”38AuxiliaryRemained constructable areaMillion m2MAX (total constructable area − “land-use of quarries” − “land-use of houses built” − “land-use of landfill,” 0)39LookupUPNA lookupUSD (m3)Historical data40AuxiliaryUnit price of natural aggregateUSD (m3)UPNA lookup (time)41AuxiliaryPrice of natural aggregateUSDUnit price of natural aggregate∗extraction amount42LookupUCL lookupUSD (m3)Historical data43AuxiliaryUnit cost of landfillingUSD (m3)UCL lookup (time)44AuxiliaryLandfilling costUSDUnit cost of landfilling∗rate of landfilling45AuxiliaryFixed price of aggregatesThousand USD(Landfilling cost + price of natural aggregate)/100046AuxiliaryFixed unit price of aggregatesUSD (m3)Unit price of natural aggregate + unit cost of landfilling47LookupRCW lookupm3/m2Historical data48AuxiliaryRatio of construction wastem3/m2RCW lookup (time)49LookupRD lookup—Historical data50AuxiliaryRatio of depreciation—RD lookup (time)51AuxiliaryRenovation area of existing housesMillion m2Area of houses built∗ratio of depreciation52LookupRDW lookupm3/m2Historical data--lookup53AuxiliaryRatio of demolition wastem3/m2RDW lookup (time)54AuxiliaryC&D waste generation rateMillion m3(Rate of housing construction∗ratio of construction waste) + (ratio of demolition waste∗renovation area of existing houses)


#### 3.2.1. Relationship between GDP, Population, Houses Built, and Fixed Unit Price of Housing Construction with Demand for New Housing

Based on the data collected for these variables, it is necessary to perform a multivariable regression that can be a relationship for the “demand of new housing” (dependent variableY) with independent variables of the “fixed unit price of housing construction” (independent variable X1), “Tehran population” (Independent variable X2), and “GDP” (independent variable X3) over time (equation (1). In order to estimate this relationship, multivariable regression was used by Excel software. The regression results for the model are shown in Table 2. The correlation is 0.97, which indicates a strong correlation.(1)Y=b1X1+b2X2+b3X3+b4.Table 2
Multivariable regression results.
FactorQuantityb10.005297b20.156357b3−0.05343b4−1083.34R square0.9727AdjustedR square0.9611The new housing demand equation in terms of million square meters is in accordance with equation (2). GDP is in thousand USD and population in thousand persons. The unit price of housing is also in the amount of thousand USD per square meter.(2)Demandofnewhousing=b1∗fixedunitpriceofhousingconstruction+b2∗POP−b3∗GDP+b4−areaofhousesbuilt.


### 3.3. Model Calibration and Validation

#### 3.3.1. Calibration

By implementing the model, the behavior of variables in the simulation horizons was investigated. Then, according to defined relationships and recorded data, the behavior of the model was verified. Variables such as construction rates, housing demand, GDP, waste generation, and demand for materials were reviewed at various stages, and the model behavior was calibrated with resetting variables, especially data, up to ±5%. Finally, by examining all the variables and the effect of each behavior on the overall behavior of the model, the total calibration of the model was performed.


#### 3.3.2. Validation

Once a formulated model is obtained, it is time to get the two following processes simultaneously in equilibrium:(i)
Built-in model is improved(ii)
With the help of the model, the understanding and inference of the problem and possible solutions will increaseAfter the development of the model and before the analysis of the results and scenario, there are always some validation tests on the system dynamics models to ensure the validity and validity of the model under different conditions. Validation tests consist of a variety of types, and each one alone is enough to validate the model, which is [25] as follows:(i)
Boundary ability(ii)
Exponential terms(iii)
Evaluation of the structure and parameters(iv)
Reproduction behavior(v)
Sensitivity analysisHere, only the method of reproduction behavior is examined.Reproduction behavior: in this method, the comparison of the key and important variables of the model with the data and the time series available for these variables shows the validity of the constructed model. However, the need for this method is the existence of historical data. Fortunately, for most of the variables, required historical data are available. Historical data needed were collected from the statistics center of Iran. In the following, these data will be examined and compared with the model results.Comparing the model’s result with historical data on the “demand of new housing” variable indicates the behavior of this variable. As shown in Figure4(a), and as it is known, the flexibility and response of the model are similar to the historical data that shows the validity of the model. A comparison of the behavior of the model with the historical data on the amount of waste generated by the variable is also presented in Figure 4(b). In this variable, the similarity of the behavior of the model with the historical data indicates the validity of the model.Figure 4
(a) Comparison of housing demand and historical data and (b) comparison of C&D waste generation rate with historical data.
(a)(b)


## 3.1. System Dynamics Methodology

First, the problem is evaluated and defined. In the following, according to the process mentioned, the method of implementing system dynamics for the subject of this research is described.


### 3.1.1. Dynamic Statement or Hypothesis

According to previous studies, 70 to 80 percent of the materials used in the construction of buildings and road projects are aggregates used in concrete and asphalt products [2]. Iran, especially Tehran, is rich in stone resources and mines, so there is no limit to the sources of stone materials; however, this kind of attitude is contrary to the principles of sustainable development [27–29]. Utilizing sand and gravel quarries for aggregate processing, as one of the building materials, will increase energy consumption [2] and, consequently, increase the emission of CO2 [1, 30]. The rate of construction is dependent on population growth and is directly linked to the economic growth of the city and the country. Building construction in cities will increase the generation rate of C&D waste [31]. The municipality’s most important action for C&D waste is landfilling that will result in landfill capacity being completed. Cities, especially metropolises, are facing a shortage of urban space due to population growth and construction [31]. Landfills should be as close to or near the city as possible because of the transportation and collection costs of urban waste [32–34]. Today, the metropolitan margin is considered as a residential building area; therefore, the occupancy of the city’s marginal lands by landfills, despite the imposed costs, reduces the buildable infrastructure of housing [35].In addition, with the construction of each of these landfill centers on the periphery of the city, the area around it is unusable for reasons of safety, noise pollution, environmental pollution, and smells. Generally, the construction of these centers outside the city (especially away from the city) will increase costs (related to transportation, time, and human resources) [32–34]. It is also impossible to set up them at the center of the urban context, so the city’s margin is the main landfill option, which directly reduces the buildable infrastructure of the city. Reducing urban constructable infrastructure will increase the density; in this case, due to the growing demand of the population, the marginalization intensifies, thus creating a cycle. Mining operations and the level of land occupation by them, especially the marginal mines, have the same effects as landfills in the city [33].Therefore, in all cities of the country, despite the extensive use of stone mines, there is limited space for landfilling and municipal waste disposal. Solid waste, especially C&D waste, despite the need for landfills, causes environmental pollution, and recycling can be an effective way to reduce environmental impacts (energy consumption and CO2 emissions) [36, 37]. The landfill process has its own cost, as well as taxes. It seems that with the establishment of recycling centers, aggregates can be recycled, which reduces energy consumption and gas emissions from natural mines, and, on the other hand, can prevent the completion of landfills capacity and the amount of land needed for construction of the new landfill [33]. However, the amount of demand for recycled materials is too low, which could be more effective in its construction if government support and tax increases (landfill and mining costs). Therefore, recycling is a scenario that requires a system review.


### 3.1.2. List of Dynamics

In the following, the dynamics of this research are described:(i)
Population effect on construction: population is one of the direct drivers of construction. The increase in population will lead to growth in construction. The construction growth in addition to develop the city can also be a migrating factor and accommodate more people in the city. That means increasing the population.(ii)
Interaction of construction and gross domestic product (GDP): GDP growth impacts indirectly on construction [35]. That is, increasing GDP will increase housing demand and, consequently, increase construction costs. However, rising construction rates will directly increase GDP. That is, they will reinforce each other.(iii)
Construction effect on building waste generation: the new construction, as well as the renovation of existing structures (buildings and roads), leads to the C&D waste generation, part of which is the demolition waste that is a function of the existing infrastructure, and the other part, the waste associated with the infrastructure are being built. The increase in C&D waste generation accelerates the completion of the existing landfill capacity. As landfills area increase, the level of land occupancy increases, and in continues when the landfill capacity is completed, with the need to build another landfill, thus occupying a larger surface area. Finally, it reduces the constructable area of the city and the city’s margins, and consequently, it is reasonable to harm the construction.(iv)
The effect of landfill centers (waste disposal) and aggregates production centers on costs: both landfills and the production of stone materials increase the finished cost of aggregates, which is the cost associated with the life cycle (production and landfilling) of aggregates. Increasing this cost will directly increase the cost of construction. Increasing this cost also reduces construction demand, which further decreases the demand for materials and reduces construction and, consequently, reduces waste generation.


### 3.1.3. Subsystems

The diagram of the subsystems of the C&D waste management system in the framework of the objectives of this research is shown in Figure1. The subsystems of the economy and population, housing, quarries, and landfills are the main subsystems of this research. Variables are also identified in the form of endogenous, exogenous, and excluded variables. Endogenous variables are the ones that are found inside the model, and the exogenous variables are the ones that are externally logged in [25].Figure 1
Chart of the subsystems of the C&D waste management.


### 3.1.4. The Causal Loops Diagram

According to the dynamic hypothesis, the list of dynamics and subsystem diagrams are described. Now, the causal loop diagram can be defined. According to studies [38–40], economic growth or, in other words, GDP growth will increase housing demand. On the other hand, population growth also increases the demand for housing [27, 41]. Increasing housing demand has led to increased construction growth, or in other words, has led to an increase in built housing [10, 42]. Construction growth also has a positive and direct effect on GDP growth. Thus, the created loop can be defined as shown in Figure 2, which is a reinforcement (R) type, which is represented by the sign R.Figure 2
(R) The causal loop of impacts of the population and GDP on construction. (B1) The causal loop of the impact of mining on reducing construction. (B2) The causal loop of the impact of the C&D waste generation on reducing construction. (B3) The causal loop of the impact of the C&D waste cost on reducing the demand for housing. (B4) The causal loop of the impact of the cost of natural stone materials production on the reduction of housing demand.Increasing construction will increase the demand for construction materials [30, 39, 40], in which only aggregates are investigated. Demand for stone materials also increases the construction and extraction of stone resources from quarries. The exploitation of stone quarries increases the level of occupation of the land, which reduces the area of the city to be built. The existence of a constructable area in the city creates demand for housing [35]. Thus, if the area to be constructed is reduced, it reduces the construction potential or reduces the constructional capability (constructability). This leads to a reduction of construction, and thus, the marginalization around the metropolitan increases. The resulting causal loop is shown in Figure 2, which is a kind of balancing (B) loop and is represented by the sign B1.Increasing the population indirectly (with the growth of construction) leads to an increase in a waste generation [4, 7, 8]. In other words, the growth of housing construction results in the generation of C&D waste due to the waste of resources during the construction and renovation of worn-out urban textures and the depreciated building and roads [35, 39]. The C&D waste generated is disposed in landfills. Therefore, increasing C&D waste generation will increase the capacity of the city’s landfills and increase the landfill occupancy, and will face the city with a lack of space for waste disposal. That is, it reduces the constructable area of housing, as in the previous loop, reduces construction. The corresponding balancing loop is visible in Figure 2 by the sign B2.The cost of waste disposal operations in landfills increases with increasing waste volume [39, 43]. The cost of aggregate production also increases with increasing extraction rates [39, 40]. The sum of these two costs is the cost of production and the landfilling of aggregates, which is the total price of stones. The increase in the cost of aggregate (and however any construction material) will lead to an increase in the cost of building housing [35], thus reducing housing demand by increasing housing prices. The two corresponding balancing loops are shown in Figure 2 by the signs B3 and B4.


## 3.1.1. Dynamic Statement or Hypothesis

According to previous studies, 70 to 80 percent of the materials used in the construction of buildings and road projects are aggregates used in concrete and asphalt products [2]. Iran, especially Tehran, is rich in stone resources and mines, so there is no limit to the sources of stone materials; however, this kind of attitude is contrary to the principles of sustainable development [27–29]. Utilizing sand and gravel quarries for aggregate processing, as one of the building materials, will increase energy consumption [2] and, consequently, increase the emission of CO2 [1, 30]. The rate of construction is dependent on population growth and is directly linked to the economic growth of the city and the country. Building construction in cities will increase the generation rate of C&D waste [31]. The municipality’s most important action for C&D waste is landfilling that will result in landfill capacity being completed. Cities, especially metropolises, are facing a shortage of urban space due to population growth and construction [31]. Landfills should be as close to or near the city as possible because of the transportation and collection costs of urban waste [32–34]. Today, the metropolitan margin is considered as a residential building area; therefore, the occupancy of the city’s marginal lands by landfills, despite the imposed costs, reduces the buildable infrastructure of housing [35].In addition, with the construction of each of these landfill centers on the periphery of the city, the area around it is unusable for reasons of safety, noise pollution, environmental pollution, and smells. Generally, the construction of these centers outside the city (especially away from the city) will increase costs (related to transportation, time, and human resources) [32–34]. It is also impossible to set up them at the center of the urban context, so the city’s margin is the main landfill option, which directly reduces the buildable infrastructure of the city. Reducing urban constructable infrastructure will increase the density; in this case, due to the growing demand of the population, the marginalization intensifies, thus creating a cycle. Mining operations and the level of land occupation by them, especially the marginal mines, have the same effects as landfills in the city [33].Therefore, in all cities of the country, despite the extensive use of stone mines, there is limited space for landfilling and municipal waste disposal. Solid waste, especially C&D waste, despite the need for landfills, causes environmental pollution, and recycling can be an effective way to reduce environmental impacts (energy consumption and CO2 emissions) [36, 37]. The landfill process has its own cost, as well as taxes. It seems that with the establishment of recycling centers, aggregates can be recycled, which reduces energy consumption and gas emissions from natural mines, and, on the other hand, can prevent the completion of landfills capacity and the amount of land needed for construction of the new landfill [33]. However, the amount of demand for recycled materials is too low, which could be more effective in its construction if government support and tax increases (landfill and mining costs). Therefore, recycling is a scenario that requires a system review.


## 3.1.2. List of Dynamics

In the following, the dynamics of this research are described:(i)
Population effect on construction: population is one of the direct drivers of construction. The increase in population will lead to growth in construction. The construction growth in addition to develop the city can also be a migrating factor and accommodate more people in the city. That means increasing the population.(ii)
Interaction of construction and gross domestic product (GDP): GDP growth impacts indirectly on construction [35]. That is, increasing GDP will increase housing demand and, consequently, increase construction costs. However, rising construction rates will directly increase GDP. That is, they will reinforce each other.(iii)
Construction effect on building waste generation: the new construction, as well as the renovation of existing structures (buildings and roads), leads to the C&D waste generation, part of which is the demolition waste that is a function of the existing infrastructure, and the other part, the waste associated with the infrastructure are being built. The increase in C&D waste generation accelerates the completion of the existing landfill capacity. As landfills area increase, the level of land occupancy increases, and in continues when the landfill capacity is completed, with the need to build another landfill, thus occupying a larger surface area. Finally, it reduces the constructable area of the city and the city’s margins, and consequently, it is reasonable to harm the construction.(iv)
The effect of landfill centers (waste disposal) and aggregates production centers on costs: both landfills and the production of stone materials increase the finished cost of aggregates, which is the cost associated with the life cycle (production and landfilling) of aggregates. Increasing this cost will directly increase the cost of construction. Increasing this cost also reduces construction demand, which further decreases the demand for materials and reduces construction and, consequently, reduces waste generation.


## 3.1.3. Subsystems

The diagram of the subsystems of the C&D waste management system in the framework of the objectives of this research is shown in Figure1. The subsystems of the economy and population, housing, quarries, and landfills are the main subsystems of this research. Variables are also identified in the form of endogenous, exogenous, and excluded variables. Endogenous variables are the ones that are found inside the model, and the exogenous variables are the ones that are externally logged in [25].Figure 1
Chart of the subsystems of the C&D waste management.


## 3.1.4. The Causal Loops Diagram

According to the dynamic hypothesis, the list of dynamics and subsystem diagrams are described. Now, the causal loop diagram can be defined. According to studies [38–40], economic growth or, in other words, GDP growth will increase housing demand. On the other hand, population growth also increases the demand for housing [27, 41]. Increasing housing demand has led to increased construction growth, or in other words, has led to an increase in built housing [10, 42]. Construction growth also has a positive and direct effect on GDP growth. Thus, the created loop can be defined as shown in Figure 2, which is a reinforcement (R) type, which is represented by the sign R.Figure 2
(R) The causal loop of impacts of the population and GDP on construction. (B1) The causal loop of the impact of mining on reducing construction. (B2) The causal loop of the impact of the C&D waste generation on reducing construction. (B3) The causal loop of the impact of the C&D waste cost on reducing the demand for housing. (B4) The causal loop of the impact of the cost of natural stone materials production on the reduction of housing demand.Increasing construction will increase the demand for construction materials [30, 39, 40], in which only aggregates are investigated. Demand for stone materials also increases the construction and extraction of stone resources from quarries. The exploitation of stone quarries increases the level of occupation of the land, which reduces the area of the city to be built. The existence of a constructable area in the city creates demand for housing [35]. Thus, if the area to be constructed is reduced, it reduces the construction potential or reduces the constructional capability (constructability). This leads to a reduction of construction, and thus, the marginalization around the metropolitan increases. The resulting causal loop is shown in Figure 2, which is a kind of balancing (B) loop and is represented by the sign B1.Increasing the population indirectly (with the growth of construction) leads to an increase in a waste generation [4, 7, 8]. In other words, the growth of housing construction results in the generation of C&D waste due to the waste of resources during the construction and renovation of worn-out urban textures and the depreciated building and roads [35, 39]. The C&D waste generated is disposed in landfills. Therefore, increasing C&D waste generation will increase the capacity of the city’s landfills and increase the landfill occupancy, and will face the city with a lack of space for waste disposal. That is, it reduces the constructable area of housing, as in the previous loop, reduces construction. The corresponding balancing loop is visible in Figure 2 by the sign B2.The cost of waste disposal operations in landfills increases with increasing waste volume [39, 43]. The cost of aggregate production also increases with increasing extraction rates [39, 40]. The sum of these two costs is the cost of production and the landfilling of aggregates, which is the total price of stones. The increase in the cost of aggregate (and however any construction material) will lead to an increase in the cost of building housing [35], thus reducing housing demand by increasing housing prices. The two corresponding balancing loops are shown in Figure 2 by the signs B3 and B4.


## 3.2. Dynamic Modeling (Flow Diagram of C&D Waste Generation)

In this section, the main variables and time horizons are expressed in terms of the description of the problem. Vensim software was used to conduct dynamic analysis. This software was developed for the first time in 1991 by Ventana Systems to develop and analyze dynamic feedback models and is now considered one of the strongest software in the field [25, 26].The time horizon, when used in the system dynamics simulation, should also cover the historical background of the problem so that it can be ensured by the model’s accuracy in the creation cycle of the system and, on the other hand, so long in the future, that the cycle of the problem is completely cover [25]. The whole period of time considered in this research is from 2006 to 2041. In fact, the period from 2006 to 2021 is the base period, and the period from 2022 to 2041 is the prediction period. All of the data needed for modeling are provided from reputable databases such as the Statistics Center of Iran. In cases where there are no complete and historical data required or lacking continuity, experts have also been used to cover the weakness of the data inconsistency of the variable in question. Due to the lack of a complete database of variables in the years before 2006, 2006 was necessarily selected as the starting year. As noted previously, this model is Tehran’s current status on how to use natural stone as well as C&D waste generation.With regard to the problem described in the sections of the dynamic hypothesis and the list of dynamics, the subsystem diagrams, the causal loops, the stock, and the flow diagram of the waste management system in Tehran can be defined and drawn according to Figure3. The dynamic flow model diagram of “Tehran Waste Management” consists of 5 stock variables, 5 flow variables, and 44 auxiliary variables (including auxiliary, constant, and lookup). In total, 54 variables are defined. In this section, the basic values of the system dynamic model are explained. The list of variables used in the modeling and related equations are summarized in Table 1.Figure 3
Chart of stock-flow of C&D waste generation in Iran.Table 1
Variables in the stock and flow diagram.
#TypeNameUnitsEquation1StockPOPThousand personsNet population growth rate2StockArea of houses builtMillion m2Rate of housing construction3StockTotal C&D waste landfilledMillion m3Rate of landfilling4StockTotal CO2 emissionTon CO2 eqRate of CO2 emission5StockTotal energy consumptionTon oil equivalentRate of energy consumption6FlowNet population growth rateThousand persons (year)Factor of net population growth rate∗POP7FlowRate of housing constructionMillion m2 (year)SMOOTHI (demand of new housing, 2.6, 13.646)8FlowRate of landfillingMillion m3 (year)C&D waste generation rate9ConstantLCA-energy-naturalKgoe (ton)2.302410FlowRate of energy consumptionTon oil equivalent (year)(1.6∗demand of aggregate∗“LCA-energy-natural”)∗100011ConstantLCA-CO2-naturalkg CO2 eq (ton)4.460912FlowRate of CO2 emissionTon CO2 eq (year)(1.6∗demand of aggregate∗“LCA-CO2-natural”)∗100013LookupFNPGR lookupThousand personsHistorical data14AuxiliaryFactor of net population growth rate—FNPGR lookup (time)15LookupEFA lookupm3/m2Historical data16AuxiliaryEffect factor of aggregatesm3/m2EFA lookup (time)17AuxiliaryFixed unit price of aggregatesUSD (m3)Unit price of natural aggregate + unit cost of landfilling18AuxiliaryFixed unit price of housing constructionUSD (m2)Fixed unit price of aggregates∗effect factor of aggregates19AuxiliaryDemand for new housingMillion m2ABS ((0.005297∗fixed unit price of housing construction) + (0.156357∗POP) − (0.05343∗GDP) − 1083.34 − area of houses built)20LookupNGDP lookupThousand USDHistorical data21AuxiliaryNormal GDPThousand USDNGDP lookup (time)22AuxiliaryGDPThousand USDNormal GDP + ((fixed unit price of housing construction/1000)∗rate of housing construction) − fixed price of aggregates23LookupPA lookupm3/m2Historical data24AuxiliaryAmount of aggregatesm3/m2PA lookup (time)25AuxiliaryDemand of aggregateMillion m3Percentage of aggregates∗rate of housing construction26ConstantDensity factor—0.6227AuxiliaryExtraction amountMillion m3Demand of aggregate∗density factor28LookupURRQ lookupm3/m2Historical data29AuxiliaryUrban reduction ratio of quarriesm3/m2URRQ lookup (time)30AuxiliaryLand-use of quarriesMillion m2Extraction amount∗urban reduction ratio of quarries31ConstantTotal constructable areaMillion m224032LookupURRL lookupm3/m2Historical data33AuxiliaryUrban reduction ratio of landfillingm3/m2URRL lookup (time)34AuxiliaryLand-use of landfillMillion m2Total C&D waste landfilled∗urban reduction ratio of landfilling35LookupLUAR lookup—Historical data36AuxiliaryLand-use/area ratio—LUAR lookup (time)37AuxiliaryLand-use of houses builtMillion m2Area of houses built∗“land-use/area ratio”38AuxiliaryRemained constructable areaMillion m2MAX (total constructable area − “land-use of quarries” − “land-use of houses built” − “land-use of landfill,” 0)39LookupUPNA lookupUSD (m3)Historical data40AuxiliaryUnit price of natural aggregateUSD (m3)UPNA lookup (time)41AuxiliaryPrice of natural aggregateUSDUnit price of natural aggregate∗extraction amount42LookupUCL lookupUSD (m3)Historical data43AuxiliaryUnit cost of landfillingUSD (m3)UCL lookup (time)44AuxiliaryLandfilling costUSDUnit cost of landfilling∗rate of landfilling45AuxiliaryFixed price of aggregatesThousand USD(Landfilling cost + price of natural aggregate)/100046AuxiliaryFixed unit price of aggregatesUSD (m3)Unit price of natural aggregate + unit cost of landfilling47LookupRCW lookupm3/m2Historical data48AuxiliaryRatio of construction wastem3/m2RCW lookup (time)49LookupRD lookup—Historical data50AuxiliaryRatio of depreciation—RD lookup (time)51AuxiliaryRenovation area of existing housesMillion m2Area of houses built∗ratio of depreciation52LookupRDW lookupm3/m2Historical data--lookup53AuxiliaryRatio of demolition wastem3/m2RDW lookup (time)54AuxiliaryC&D waste generation rateMillion m3(Rate of housing construction∗ratio of construction waste) + (ratio of demolition waste∗renovation area of existing houses)


### 3.2.1. Relationship between GDP, Population, Houses Built, and Fixed Unit Price of Housing Construction with Demand for New Housing

Based on the data collected for these variables, it is necessary to perform a multivariable regression that can be a relationship for the “demand of new housing” (dependent variableY) with independent variables of the “fixed unit price of housing construction” (independent variable X1), “Tehran population” (Independent variable X2), and “GDP” (independent variable X3) over time (equation (1). In order to estimate this relationship, multivariable regression was used by Excel software. The regression results for the model are shown in Table 2. The correlation is 0.97, which indicates a strong correlation.(1)Y=b1X1+b2X2+b3X3+b4.Table 2
Multivariable regression results.
FactorQuantityb10.005297b20.156357b3−0.05343b4−1083.34R square0.9727AdjustedR square0.9611The new housing demand equation in terms of million square meters is in accordance with equation (2). GDP is in thousand USD and population in thousand persons. The unit price of housing is also in the amount of thousand USD per square meter.(2)Demandofnewhousing=b1∗fixedunitpriceofhousingconstruction+b2∗POP−b3∗GDP+b4−areaofhousesbuilt.


## 3.2.1. Relationship between GDP, Population, Houses Built, and Fixed Unit Price of Housing Construction with Demand for New Housing

Based on the data collected for these variables, it is necessary to perform a multivariable regression that can be a relationship for the “demand of new housing” (dependent variableY) with independent variables of the “fixed unit price of housing construction” (independent variable X1), “Tehran population” (Independent variable X2), and “GDP” (independent variable X3) over time (equation (1). In order to estimate this relationship, multivariable regression was used by Excel software. The regression results for the model are shown in Table 2. The correlation is 0.97, which indicates a strong correlation.(1)Y=b1X1+b2X2+b3X3+b4.Table 2
Multivariable regression results.
FactorQuantityb10.005297b20.156357b3−0.05343b4−1083.34R square0.9727AdjustedR square0.9611The new housing demand equation in terms of million square meters is in accordance with equation (2). GDP is in thousand USD and population in thousand persons. The unit price of housing is also in the amount of thousand USD per square meter.(2)Demandofnewhousing=b1∗fixedunitpriceofhousingconstruction+b2∗POP−b3∗GDP+b4−areaofhousesbuilt.


## 3.3. Model Calibration and Validation

### 3.3.1. Calibration

By implementing the model, the behavior of variables in the simulation horizons was investigated. Then, according to defined relationships and recorded data, the behavior of the model was verified. Variables such as construction rates, housing demand, GDP, waste generation, and demand for materials were reviewed at various stages, and the model behavior was calibrated with resetting variables, especially data, up to ±5%. Finally, by examining all the variables and the effect of each behavior on the overall behavior of the model, the total calibration of the model was performed.


### 3.3.2. Validation

Once a formulated model is obtained, it is time to get the two following processes simultaneously in equilibrium:(i)
Built-in model is improved(ii)
With the help of the model, the understanding and inference of the problem and possible solutions will increaseAfter the development of the model and before the analysis of the results and scenario, there are always some validation tests on the system dynamics models to ensure the validity and validity of the model under different conditions. Validation tests consist of a variety of types, and each one alone is enough to validate the model, which is [25] as follows:(i)
Boundary ability(ii)
Exponential terms(iii)
Evaluation of the structure and parameters(iv)
Reproduction behavior(v)
Sensitivity analysisHere, only the method of reproduction behavior is examined.Reproduction behavior: in this method, the comparison of the key and important variables of the model with the data and the time series available for these variables shows the validity of the constructed model. However, the need for this method is the existence of historical data. Fortunately, for most of the variables, required historical data are available. Historical data needed were collected from the statistics center of Iran. In the following, these data will be examined and compared with the model results.Comparing the model’s result with historical data on the “demand of new housing” variable indicates the behavior of this variable. As shown in Figure4(a), and as it is known, the flexibility and response of the model are similar to the historical data that shows the validity of the model. A comparison of the behavior of the model with the historical data on the amount of waste generated by the variable is also presented in Figure 4(b). In this variable, the similarity of the behavior of the model with the historical data indicates the validity of the model.Figure 4
(a) Comparison of housing demand and historical data and (b) comparison of C&D waste generation rate with historical data.
(a)(b)


## 3.3.1. Calibration

By implementing the model, the behavior of variables in the simulation horizons was investigated. Then, according to defined relationships and recorded data, the behavior of the model was verified. Variables such as construction rates, housing demand, GDP, waste generation, and demand for materials were reviewed at various stages, and the model behavior was calibrated with resetting variables, especially data, up to ±5%. Finally, by examining all the variables and the effect of each behavior on the overall behavior of the model, the total calibration of the model was performed.


## 3.3.2. Validation

Once a formulated model is obtained, it is time to get the two following processes simultaneously in equilibrium:(i)
Built-in model is improved(ii)
With the help of the model, the understanding and inference of the problem and possible solutions will increaseAfter the development of the model and before the analysis of the results and scenario, there are always some validation tests on the system dynamics models to ensure the validity and validity of the model under different conditions. Validation tests consist of a variety of types, and each one alone is enough to validate the model, which is [25] as follows:(i)
Boundary ability(ii)
Exponential terms(iii)
Evaluation of the structure and parameters(iv)
Reproduction behavior(v)
Sensitivity analysisHere, only the method of reproduction behavior is examined.Reproduction behavior: in this method, the comparison of the key and important variables of the model with the data and the time series available for these variables shows the validity of the constructed model. However, the need for this method is the existence of historical data. Fortunately, for most of the variables, required historical data are available. Historical data needed were collected from the statistics center of Iran. In the following, these data will be examined and compared with the model results.Comparing the model’s result with historical data on the “demand of new housing” variable indicates the behavior of this variable. As shown in Figure4(a), and as it is known, the flexibility and response of the model are similar to the historical data that shows the validity of the model. A comparison of the behavior of the model with the historical data on the amount of waste generated by the variable is also presented in Figure 4(b). In this variable, the similarity of the behavior of the model with the historical data indicates the validity of the model.Figure 4
(a) Comparison of housing demand and historical data and (b) comparison of C&D waste generation rate with historical data.
(a)(b)


## 4. Scenario Planning

Scenario design: considering the subject matter of this thesis as well as the results of model simulation, there is a recycling option that needs dynamic analysis. According to the research data, the recycling of aggregates by the private sector is not beneficial because recycled aggregates are not welcomed by customers. Due to their lower quality and the tax on recycling centers, there is no private sector interest in setting up such centers. Therefore, it should be supported by the government. The recycling process is carried out by the government in landfills, and by establishing national regulations, it is imperative to use recycled aggregates in construction, especially in prefabricated concrete units and national projects. On the other hand, the sale of recycled aggregates at a much lower price, as well as an increase in landfill taxes, would reduce the production of unnecessary construction waste. This policy will lead to a culture of reduction of waste generation and increased acceptance of recycled products. Therefore, in conjunction with politics, we try to introduce the ideal options. In the case of operational strategies, environmental scenarios are also planned.Therefore, in the case of dynamic analysis of the waste management system, there are 2 options that are known as the policy option. The first policy is to continue the current state of waste management named landfilling. The second policy is the recycling of C&D waste containing aggregates (i.e., concrete and asphalt). According to the current economic situation in the country and the stagnation, the stability of inflation and the decline in production in the country’s industries, it can be seen from the news of employment and production that the government seeks to increase the rate of employment-related production in the industrial sector. That means trying to increase GDP. Therefore, the first scenario, called ES1, is a 20% increase in normal GDP from 2022 (i.e., nonresidential GDP, since construction is an indirect source of waste production). On the other hand, new national policies also see the country’s population increase dramatically increase. Therefore, the second scenario or ES2, is a 10% increase in population since 2022. Due to the widespread building regulations as well as the requirements of national building regulations, new urban construction policies focus on extending shelf life. Increasing the useful life of the building will reduce the rate of depreciation. So, the third scenario or ES3, has reduced the ten-year depreciation rate by 2022. Table 3 shows the policy and options available along with the relevant scenarios.Table 3
Policies and strategies for C&D waste management in Tehran.
Policy optionEnvironmental scenarioBase runES1ES2ES3PO1Landfilling the C&D wasteBase run of landfilling20% increase in normal GDP since 202210% increase in population rate since 202210% reduction in depreciation rates since 2022PO2Recycling the C&D wasteBase run of recycling20% increase in normal GDP since 202210% increase in population rate since 202210% reduction in depreciation rates since 2022Figure5 illustrates the stock and flow diagram of the recycling option (PO2). The flow diagram of the dynamical model “Tehran Waste Management” consists of 5 stock variables, 5 flow variables, and 58 auxiliary variables. In total, 68 variables are defined. As is evident, part of the aggregate-containing waste is concrete waste and asphaltic. Among these waste, extraction, and recycling of aggregates occurs, which ultimately results in the production of recycled aggregates and reduces the demand for aggregates. In fact, in this option, the combined use of natural and recycled aggregates is modeled with a mixing percentage of 50%. So, in this option, 50% of the aggregate needed for construction is supplied by natural aggregates and 50% by recycled aggregate. The amount of CO2 and energy consumed is also obtained from the sum of these aggregates.Figure 5
Chart of stock-flow of recycling policy.


## 5. Results and Discussion

By executing the options and scenarios defined for each option, the results will be presented in the form of different charts. The results of the current waste management option (PO1), along with the existing scenarios, are in accordance with Figure 6. According to Figure 6, the POP growth scenario increases the rate of construction and C&D waste generation. Therefore, the direct and influential factor in increasing construction and waste generation is the factor of the population that has been observed in other studies [39, 43, 44]. The results of the waste recycling option (PO2), along with available scenarios are shown in Figures 7 and 8. As a result, according to Figure 7, it is possible to extract more recycled aggregates, as well as to finish the Landfill’s capacity more quickly. On the other hand, according to Figure 8, the GDP growth scenario causes Tehran’s construction space to be completed later, which is due to the increase in nonconstruction-dependent GDP.Figure 6
The variable process of C&D waste generation rate in current state scenarios.Figure 7
The variable trend of recycled aggregates in the recycling option scenarios.Figure 8
The variable trend of remained constructable area in the recycling option scenarios.In the LCA model of aggregates [2], CO2 emissions and energy consumption are estimated linearly and predicted, but in the SD model, these values are calculated based on the annual demand in Tehran. As shown in Figures 9 and 10, the recycling scenario (and using recycled and natural aggregate together) reduces the cumulative amounts of CO2 emissions and energy consumption of aggregate compared to landfilling scenario.Figure 9
Comparison of the variable trend of the accumulated CO2 emission for both options.Figure 10
Comparison of the variable trend of the total energy consumption for both options.Comparison of the results of each of the scenarios of the current waste management option with the construction waste disposal option is shown in Figures11 to 14, which are further elaborated and interpreted. However, here are just the key variables, as well as variables that are very different from each other with different scenarios.Figure 11
The trend of landfilled C&D waste for both options.Figure 12
The trend of stone extraction amount for both options.Figure 13
The trend of landfilling rate in the depreciation reduction scenario for both options.Figure 14
The trend of land use of landfills in the depreciation reduction scenario for both options.Observing and analyzing the results of each option and its scenarios, as well as comparing the results of each option, shows that the recycling of aggregates reduces the value-added of aggregates, which is actually due to the reduction of mining costs. This value-added difference was fixed in the first part of this chapter, in the context of the economic-environmental assessment of the life cycle of options. Other impacts are the reduction of landfill rates due to recycling. Thus, the amount of waste deposited decreases. The significant difference between these variables is observed even in 2041, and over time, the amount of this difference is increased.Evaluating the variable of remaining land in Tehran over time shows that, due to the implementation of the GDP growth scenario, the amount of land remaining is much higher than other scenarios, which are later expiring. The reason is that in this scenario, the amount of GDP nonrelated to construction has been increased, that is, the value-added of construction continues as usual. That is, only normal GDP has increased. It is reasonable to extend the useful life of the building by reducing the demolition waste generation, which reduces the landfilled waste, which is evident in the diagrams. Landfills’ land use should be able to reliably slow down the remained land in the scenario of reducing depreciation relative to the population growth scenario. However, its impact is negligible due to its insignificance, as well as the reduction of just 10% (that is, about 3 years). However, it is natural that if the useful life of the building increases to 30 or 40 years, that is, the depreciation rate will be reduced by about 0.4, and the amount of land constructed in Tehran will be completed later. The same applies to aggregate demand and extraction rates. With the increase in recyclable aggregates, the demand for natural aggregates decreases until it drops from one year to the next, which is an ideal phenomenon, that is, fully in line with the principles of sustainable development and green building.


## 6. Conclusions

In the system dynamics, the effects of time dynamics up to 2041, as well as population dynamics, GDP, housing demand, material demand, and land use of the city, were modeled and evaluated. The superiority of the recycling option and the use of combined aggregate in both approaches (LCA and SD) were confirmed. In the system dynamics approach, the adverse effects of choosing or not choosing this strategy on economic growth variables, construction rate, waste generation rate, waste landfilling rate, aggregate value-added, land use, and area of built houses, are completely illustrated. This means that the consequences of the continuation of the current situation from a systemic perspective to the 2041 horizon were evaluated for Tehran.Based on this research, the pattern of waste management in Iran’s metropolises, especially in Tehran, is as follows:(i)
An increase in population growth, as well as gross domestic product (GDP), has led to an increase in housing demand, followed by growth in construction. Due to the increase in construction, the land use of the city increases, as well as the amount of C&D waste generation. As a result, the capacity of landfills is being completed, which leads to an increase in new landfill construction costs and the occupancy of urban or urban marginal. Housing demand increases due to population growth and economic prosperity, due to the lack of sufficient space for urban construction, increasing marginalization. On the other hand, the construction of mines and landfills is a counter-offensive to marginalization. As a result, under the influence of the previous, and in accordance with Tehran’s current urban management policy, in 2028, the construction space will end in Tehran. As a result, the margin is intensified. On the other hand, the rates of extraction of natural resources of rock and, consequently, of environmental pollution increase.(ii)
Based on a life cycle study [2], the option of recycling waste and building recycled aggregate towards natural aggregate has at least 30% economic and environmental justification. Due to the impossibility of using recycled aggregate solely in construction projects and not being accepted by customers, its combined use with natural aggregates would be a major and significant option. The ratio of the combination of these 2 types of aggregate depends on the intended use and the economic and environmental variables, which requires testing and optimization. The main product of C&D waste recycling is aggregate, which is used as sand and gravel in the construction of concrete and asphalt construction projects. In each of the metropolitan area’s landfills, it is necessary to set up a waste recycling center. The recycling plant should be located exactly in landfill because it will prevent the costs of handling and transferring materials. The capacity of the recycling plant is proportional to the input waste rate.(iii)
The establishment and operation of C&D waste recycling centers should be carried out by the public sector. This is carried out by the private sector, because of the lack of acceptance of construction projects for the recycled product, causing them bankruptcy and, consequently, the failure of the project. The government should intervene with the adoption of recycled products in order to improve the situation. In such a way as to require the use of recycled aggregate in its urban planning regulations and technical regulations, and even design the standards in question. In this way, huge taxes will be levied on the private sector, and, on the other hand, the sale of recycled aggregates will be guaranteed. For the city of Tehran, it is proposed that the municipality be tasked with the construction, commissioning, and operation of the plant, as well as the production and sale of recycled aggregates. In addition, it is necessary to design different rules for the use of recycled aggregate and even insert them in the national building.(iv)
The output of the C&D waste recycling is aggregate and cements powder. This powder can be used as cement, cementitious materials, or other additives in the production of concrete. Therefore, the concrete and aggregate powder should be deposited individually in the warehouse and silos. According to the grain curve presented in this study, aggregates should be based on the size of the output, the granulation, and the deposition.(v)
The purpose of setting up different regulations for the use of recycled aggregates is to determine the percentage of natural and recycled aggregates that are minimized due to the use of aggregates, production costs, CO2 emissions, and energy consumption. Determining this percentage depends on the type of aggregate used. The major uses of these aggregates are concrete used in the structural elements and nonstructural elements, prefabricated concrete, and other prefabricated concrete components used in building and road construction, pavement layers, and fillings in road construction.



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*Source: 9348027-2022-12-24.xml*