Assessment of asbestos and asbestos waste quantity in the built environment of transition country

Abstract

Managing asbestos streams in developing and transition countries is particularly challenging. Deficiencies are often present for adequate procedures for the management of asbestos waste; solid quality data or databases on the quantities of asbestos production and usage are missing and asbestos inventories or the registry of asbestos-related diseases following European Union (EU) or other regulations are not in place. This paper aims to develop a model for determining and assessing the quantity of asbestos in the built environment of a transition country. Quantities of asbestos products and life expectancy of those products were assessed to develop a model that forecasts flows and stocks of asbestos products and wastes. The overall objective is to evaluate the model and show the manifestation of asbestos in the waste stream in a case study on a country with a transition economy, such as Serbia. Results show that total quantities of asbestos fibre consumption are approximately 0.5 million tonnes; the largest amount of waste generation is expected in the 2020s. Therefore, it is necessary to prepare for the forthcoming quantities of waste by improving legal procedures, implementation of existing regulations, and provision of economic resources. An important link for the adequate management of asbestos waste is to raise public awareness of the dangers and importance of proper and timely disposal of asbestos products.

Keywords

Asbestos asbestos waste quantity assessment transition country Serbia

Introduction

After a proven connection of asbestos and illnesses, countries are beginning to ban asbestos-extraction, production, import, use, and even requiring removal. Measures are generally encouraged to compose action plans for the safe removal of all asbestos and asbestos products (AP) used, as a priority of the European Union (EU) by 2028 (European Parliament and the Council, 2009; International Ban Asbestos Secretariat, 2020; La Dou et al., 2010). Since asbestos was widely used as a building material and in automobile products, large quantities of it are still in the built environment (Wilk et al., 2017). This leveraged asbestos to be high on the agenda in the research community, covering different topics associated with asbestos usage implications such as the challenges and difficulties in asbestos waste (AW) management in general (Paglietti et al., 2016).

Managing AW streams in developing and transition countries is essential, especially for countries that are determined to become members of the EU, as they are obliged to align with EU legislation and to meet the objectives of waste management. Besides limited economic resources, the general absence of a system for enforcing legislation poses a major obstacle for establishing an appropriate AW management system. Asbestos management legislation is incomplete and divided among many different government sectors, making it difficult to implement in practice. In addition to the non-application of regulations, capacities for material analysis, treatment and disposal are also insufficient. Causal fishbone diagram (Supplemental Appendix Figure A1) was created to identify possible factors that lead to overall mismanagement of asbestos and AW in transition countries. In addition to institutional, organisational, and financial difficulties, the human factor is also seen as a major obstacle in establishing an appropriate system. Facilities for collection, transportation, treatment, disposal, and monitoring of asbestos and AW are absent in most developing and transition countries, as shown for Asia-Pacific region in Li et al. (2014). It is especially important to determine attention to defining the quantities of abandoned and untreated AW in these countries. Most AW in this region has been dumped together with construction waste or household waste.

As for managing AW streams in developed economies, various technologies such as solidification and stabilisation, vitrification, thermal, mechanical, and chemical treatments have been in use (Spasiano and Pirozzi, 2017) and new methods for treating asbestos have been studied (Bloise et al., 2016; Colangelo et al., 2011; Iwaszko, 2019; Pawelczyk et al., 2017). Japan for instance promotes inertization and thermal processing for this kind of waste. Poland was the first country in EU to remove APs from public space and has strict legal regulations concerning procedures of dismantling asbestos-cement roof covers, but the problem is in the limited number of hazardous waste landfills and high charges for storage. This means illegal landfills for AW (Szymańska and Lewandowska, 2018). Italy is having at least 34,000 sites mapped to show the presence of APs. Similar to Poland, problems with AW management emerge with limited number of operating landfills whose capacity is insufficient to handle the large amount of AW produced every year, and it ends disposed of abroad or dumped illegally (Paglietti et al., 2016). Also, problems with asbestos exposure in the environment and ambient were investigated and shown in papers of Baumann et al. (2015) for United States, and Gualtieri et al. (2009) for Italy. Recently, Hellawell and Hughes (2021) published about UK measurements of asbestos in soil, findings are that improvements and standardisation of the detection method led to higher asbestos detection rates, for that asbestos testing is now almost routine on brownfield sites in United Kingdom.

To date, a few researchers have published about quantification of the asbestos stream in the built environment, among those Donovan and Pickin (2016) who published their research about the level of generation and estimation of future stocks and flows of AP and AW for Australia. Their paper elaborates expected lifetimes of APs according to different research and authors with defined sensitivity ranges. On the other hand, Li et al. (2014) have shown predicted volume of AW calculated for the Asian-Pacific region, according to their own defined factors, but under the assumption that all asbestos consumed were converted to construction materials. Common for both papers is adequate input data on consumed quantities of asbestos in their countries. Although this issue is present in developed countries, among recently published papers this issue has not been addressed in developing and transition countries, such as Serbia. Also, there are no papers on the topic of methods for estimating of the asbestos (fibres) consumptions (AC) amount where such data are not available. At present, there are no works with analysis of AW generation distinguishing between different types of asbestos per year, which is important for understanding capacities needed for specific recycling processes and managing in general.

The goal of this paper is to develop a model for AW generation assessment in the built environment in a transition country with limited available data. The overall aim is to generate a model applicable for transition economies where lack of data limits understanding and future planning of AW management. This research is focused on industrial product waste from the existing stock in the built environment that contains asbestos fibres, for it was taken for granted that asbestos production is now prohibited and ceased.

Materials and methods

Asbestos quantities assessment model

The model for AC and AW estimation introduced in this paper is based on multiple sources, including waste management regulations, governmental reports and published scientific literature (Donovan and Pickin, 2016; dos Muchangos et al., 2015; Fu et al., 2017; Li et al., 2014). The model for countries in transition is presented, while the verification was done on the example of Serbia as a representative of such a country.

The starting point for developing the model (Figure 1) was the existence of an organised database for AC or distribution. The analysis of previous research discussed in the previous section shows databases most often do not exist in countries in transition and development. While in developed countries, they are more organised (McGill University, 2021; UK National Asbestos Register, 2021). Furthermore, two possible situations were also recognised, the complete absence of a database and the partial absence of data for some years/decades. In case of lack of data on some years, they can be filled by following the algorithm for the situation when there is no data at all.

Annual asbestos consumption and assessment of historical consumption

Annual AC data can be obtained from official state data on quantities produced in mines (if any), factories that manufactured APs, and import data. In the absence of these data at the state level, a study conducted by Virta (2006, 2009) which provides data on the amounts of asbestos fibres consumed worldwide, may be useful.

In case the AC data are given for larger regions than the current situation (e.g. as a part of a state union), based on the equation (1), which consider area surface, GDP and population, the historical quantities can be developed specifically for country, region, and so on

Q = Q_{U n} * a

(1)

\begin{array}{l} Q i s t h e q u a n t i t i e s o f A C i n t r a n s i t i o n c o u n t r y, \frac{t}{y e a r}; \\ Q_{U n} i s t h e q u a n t i t i e s o f A C i n u n i o n, \frac{t}{y e a r}; a n d a i s t h e a v e r a g e \\ v a l u e f o r t h r e e c o e f f i c i e n t s k_{1}, k_{2} a n d k_{3}, % \end{array}

Coefficients k₁, k₂ and k₃ represents the percentage share of country as part of previous unions in terms of area surface, GDP and population, respectively. For calculations, it is important to consider coefficient a as country’s share in relation to the total figures for union state.

Types of asbestos products

Asbestos has been extensively used in many commercial products due to its unique properties. In total, 30 different types of APs are listed in 3 major categories distinguished by kind of the binding agent, within which 5 subgroups were selected for calculation based on the available data (Supplemental Appendix Table A1):

i. Solid bound AP – construction materials containing asbestos and mainly inorganic substances, bound in a cement matrix (e.g. asbestos cement products, friction products).

ii. Solid bound AP – construction materials containing asbestos and predominantly organic matter (e.g. vinyl asbestos flooring, paints and roof coating, gaskets and packings). Differences between solid bound AP type i. and ii are in the type of binder agents, in both cases the asbestos is tightly bound.

iii. Poorly bound AP – insulation materials containing asbestos (e.g. asbestos paper, asbestos felt, asbestos textile and filter media).

Share and life expectancy of AP

Different types of AP are considered in the total amount of used asbestos. The share of different APs in relation to the total consumption amount is shown in Table 1. This table also presents the expected lifetimes of the AP according to the experience of organisations in practice and published papers. Based on the correlation of the studies referencing this table, APs life expectancy are defined for this model.

Table 1.

Share of asbestos products types in the total amount of consumption of asbestos and life expectancy.

Subgroup	Bound type	Asbestos commercial applications	Share of asbestos products in the total amount of consumption, %	Life expectancy of the specific product (average), year
I	i.	Asbestos cement products (ACP)	70	50
II	ii.	Vinyl asbestos products (VAP)	10	30
III	i.	Friction products (FP)	7	5
IV	iii.	Asbestos paper and felt (APF)	5	20
V		Asbestos other (AO):	8	15
	ii.	Gaskets and packings	3
	ii.	Paints, roof coatings, caulks, etc.	2
	iii.	Filter media	2
	iii.	Asbestos textile products	1

Source: For share of asbestos products in total amount is used paper from Paglietti et al. (2016). Life expectancy is defined upon documents shown in Supplemental Appendix Table A3.

AW formation patterns

A causal fishbone diagram (Figure 2) indicates the basis that led to AW development patterns, helped the team visualise and sort the findings into five categories. The final fishbone categories point out the data required for approximation of AW quantities: historical consumption quantities, types of APs, life expectancy of APs, share of APs types in total AC, and data uncertainties in the model.

Based on the defined AP groups and the information about their life expectancy, the formula for AW formation patterns was developed for the calculation of the generation rate of AW. The AW generation amount is calculated by the given formula

W_{t o t} = \sum W_{n}^{i}

(2)

W_{n}^{i} = (μ * Q_{n - j}^{i}) + (η * Q_{n - (i + j)}^{i}) + (η * Q_{n - (i - j)}^{i})

(3)

$W_{t o t} i s t h e t o t a l s u m o f a s b e s t o s w a s t e, t$ ; quantities $o f a s b e s t o s w a s t e, \frac{t}{y e a r}$ ; $\frac{t}{y e a r}$ ; n is the calendar year of waste quantities expectancy (W) or calendar year of AP quantities used (Q); $o f a s b e s t o s p r o d u c t s, y e a r$ ; $j i s t h e s e n s i t i v i t y r a n g e, y e a r$ ; and µ, η $i s t h e s e n s i t i v i t y f a c t o r s, %$ .

Uncertainty

Since not all materials will become waste at the end of the predicted lifetime or will not immediately be replaced, while others will become waste before the predicted lifetime due to major construction and demolition activities, for the purpose of the model, APs are classified according to their lifetime and divided in five groups. The life expectancy of the specific AP was defined according to available data as shown in Table 1; therefore, APs are separated in groups: (1) ACP with 50 years, (2) VAP with 30 years, (3) FP with 5 years, (4) APF with 20 years, and (5) AO with 15 years that point to the end-of-life for products. equation (3) shows the calculation for all groups of APs.

Also, the complex mechanisms of the AW formation required for the purposes of the model development of a sensitivity range and sensitivity factors for different groups of APs, divided into groups as defined. So, in equations (2) and (3), j is the sensitivity range, depending on the type of product can be set on ±defined years. A variety of simulation methods can be used to determine how many years will be added or subtracted here. µ and ƞ are the addition sensitivity factors which supplement the factor j. Consistent with the approach for the j factor in equation (3) and applying simulation, for the AP lifetime group in the year of expiration, it was assumed that specific percent of the material entered the waste (therefore, a percentage factor can be set for µ). A years before (defined by factor j) the product end-of-life year, some percentage already went to waste; and a years after the end-of-life year, an additional percentage will enter the waste stream (a percentage factor can be set for ƞ).

Sensitivity range and sensitivity factors for life expectancy were developed reflecting uncertainty in the various evaluation. For this purpose, Monte Carlo (MC) simulation method was used in the verification of the model on the example of Serbia and analysis of the variance was obtained by means of the Minitab software with results reported below. To show AW quantities with complex mechanism of waste formation considered, a simulation of the decay of the APs over years was generated. An especially useful technique to achieve this objective is the MC simulation (Buslenko et al., 2014; Robert and Casella, 2013). In simulation-based approaches, MC simulation can be used to estimate the stochastic behaviour of the solutions and their reliability (Juan et al., 2011). In real-life problem settings like the AW generation pattern problems, there exist reliable experience values (like life expectancy of APs) to obtain good estimates of the key parameters. Therefore, MC simulation can be used to simulate such parameters and obtain realistic and reliable solutions (Sonnemann et al., 2003).

Study area

The Republic of Serbia

The Republic of Serbia, formerly the leading republic of Yugoslavia, is a country in south-eastern Europe. It is a landlocked country, covering an area of 88,000 square kilometres, with approximately 7 million inhabitants. Serbia is a transition economy country and has applied to become an administrative member of the EU (Ministry of Environment Protection, 2019; Stanisavljevic et al., 2017).

The use of asbestos in Serbia began in the early 20th century (Virta, 2006). Serbia had two large chrysotile mines that no longer operate, and no remediation of these sites was performed. The APs were manufactured in multiple companies (Ministry of Environment, Mining and Spatial Planning, 2011; Ministry of Health, 2017).

There has been a lack of any proposed or adequate procedures for the management of asbestos, as well as any quality data on asbestos generation. Only few companies have licences for AW collections. However, these companies do not collect significant quantities of AW, neither they do they cover all locations. Hence, it can be stated that currently there is no systematically organised AW collection system that covers entire territory of Serbia. The majority of the asbestos-containing waste originates with and is disposed together with construction and demolition waste, mainly at inappropriate locations, often with municipality solid waste (Ministry of Agriculture and Environmental Protection, 2015; Ministry of Environment Protection, 2017). The existing treatment capacities for AW do not treat significant quantities. AW that is not collected through the waste management system is typically inadequately and temporarily stored at the point of origin (individual households). Later, this waste is disposed of at local solid waste disposal sites (non-sanitary) without any record. Consequently, with these practices, data about AW generation in Serbia are scarce and difficult to access. There is no systematically organised database on the quantities of asbestos produced, asbestos used or asbestos inventories, which are required for establishing an adequate asbestos management system. Also, there is no register of asbestos-related diseases in accordance with EU regulations, which should be further monitored in the context of asbestos quantities and management methods.

Institutional framework

According to the legislation in Serbia, the complete ban on the production of asbestos fibres and the products containing them has been in force since 1 July 2011, while the complete ban on the use of AP has been in force since 2015 (Ministry of Health, 2017).

The establishment of a separate collection and recycling system for construction and demolition waste, storage, and disposal of waste, including AW, are regulated in Serbia by following list of documents. These contain defined procedures for processing as well as packaging, marking, collecting, transporting, storage and disposal, and is noted that AW can be disposed of under special conditions in municipal landfills (Official Gazette of Republic of Serbia, 2005, 2010a, 2010b, 2010c, 2010d, 2018). Although AW generators are obliged to inform the national environmental protection agency on quantities of AW generated, those data are incomplete and inconsistent with data from other governmental sources (Ministry of Health, 2017; Republic Bureau of Statistics, 2011).

For better visibility, sources for used data are given in the Table 2.

Table 2.

Source of data used for calculations and verification of the defined model.

Data		References
Assessment of historical consumption	For the calculations of the quantity of asbestos consumption in Serbia	● Virta (2006, 2009)
	Approximations when Serbia was part of Yugoslavia, 1930–1990 (Supplemental Appendix Table A2)	Population number	● Republic Bureau of Statistics (2011) ● Yarashevich and Karneyeva (2013)
		Surface area and GDP data	● Republican Bureau of Statistics (1989) ● Kelly (1989)
	Approximations when Serbia was part of Serbia and Montenegro, 1999–2000 (Supplemental Appendix Table A2)	Population number	● Republic Bureau of Statistics (2011)
		Surface area	● Republican Bureau of Statistics (2000)
		GDP data	● The World Bank (2020) ● Country economy (2020)
Types of Asbestos Products	30 different types of AP are identified and listed in Supplemental Supplemental Appendix Table A1	● Official Gazette of Republic of Serbia (2010c) ● Ministry of Environment, Mining and Spatial Planning (2012) ● Graham (2014)
Share of AP	Percentage share AP in total amount	● Paglietti et al. (2016)
Life expectancy of AP	The life expectancy of the specific product	● Supplemental Appendix Table A3
AW formation patterns	Importance of developing the sensitivity of the model through	● Donovan and Pickin (2016) ● Li et al. (2014)
	The input data in the formula, quantities of AP	● Table 2
	Official reports	● Ministry of Agriculture and Environmental Protection (2013, 2014, 2015, 2016a, 2016b)● Ministry of Environment, Mining and Spatial Planning (2010a, 2010b)● Ministry of Energy, Development and Environmental Protection (2011, 2012a, 2012b)● Ministry of Environment Protection (2019)

GDP: gross domestic product; AP: asbestos product.

Results and discussion

There was no systematic data for AC during some periods, considering that Serbia was part of the state union Yugoslavia (1930–1990) and Serbia and Montenegro (1999–2000). Based on the equation (1), which consider area surface, GDP and population, the historical quantities were developed specifically for Serbia. Coefficient a for Serbia in Yugoslavia was estimated as 0.31, and in Serbia and Montenegro as 0.9 (Supplemental Appendix Table A2).

The calculated data on total quantities (Q) of AC in Serbia are represented in Table 3, and Figures 3 and 4. In total, the calculated quantities of AC are 483,193 tonnes. The estimated share of different APs in the total amount of consumption for Serbia is listed in Table 4.

Table 3.

Calculated quantities (Q) of AC for Serbia per decade.

Year	1930–1939	1940–1949	1950–1959	1960–1969	1970–1979
Tonnes/decade	1895	6944	20,770	65,426	172,213
Year	1980–1989	1990–1999	2000–2009	2010–2019	Total sum in tonnes
Tonnes/decade	176,738	35,653	1443	2111	483,193

Table 4.

Calculated share of different asbestos products in the total amount of consumption for Serbia.

Asbestos commercial applications	% of total consumption	Serbia (total tonnes)
Asbestos cement products	70	336,758.04
Vinyl asbestos ﬂooring	10	48,108.29
Friction products	7	33,675.80
Asbestos paper and felt	5	24,054.15
Gaskets and packings	3	14,432.49
Paints, roof coatings, caulks, etc	2	9621.66
Filter media	2	9621.66
Asbestos textile products	1	4810.83

Figure 3 shows a comparison of AC for the world, Europe, and calculated values for Serbia, during period 1930–2000 (Ministry of Environment, Mining and Spatial Planning, 2012; Virta, 2006, 2009). For 1950–2013, the average consumption in the World varied from approximately 0.3 kg per capita to almost 1.2 kg per capita per year (Allen et al., 2017). Annual asbestos production and consumption worldwide have declined since their peak in 1980. AC in 1994 ranged, per capita, between 0.004 kg in northern Europe and 2.4 kg in the former Soviet Union, where Russia and Kazakhstan are still currently producing AP (Albin et al., 1999; Asbestos.com, 2021; Statista, 2021).

The highest consumption of asbestos for Serbia was recorded between 1975 and 1985 (Figures 3 and 4). Significant decreases in AC were recorded during the 1940s due to World War 2 in Serbia (25 tonnes for the 1940s). Before 1950, the main source of asbestos was through import, averaging 490 tonnes per year. Serbia relied on imports to meet all its asbestos needs. This practice continued until 1990, but with part of the source from domestic mining, with an average of 11,111 tonnes/year consumption (Virta, (2006). The increased use of asbestos, following trends in the world, during the 1970s (17,221 tonnes per year) and 1980s (17,674 tonnes per year) was by an economic boom (Woodward, 1995) and development (construction) of the country. During the 1990s Serbia was under sanctions and war, which is reflected in the declining use of asbestos (Figures 3 and 4). Asbestos use in Serbia for the 1990s was 3565 tonnes per year. After the 1990s high importation had stopped, but importation was continued in lower quantities and not continuously. Production from the mines continued until 2006 when the mines went bankrupt. The elaborated data indicates that for Serbia during 1930–2017, the usage was in the range of 0.003–2.45 kg per capita per year, averaging 0.65 kg per capita per year (Figure 4(a)).

The MC simulation procedure requires the random selection of a value from each of the probability distributions assigned for the input parameters to calculate a mathematical solution, defined by the AW formation patterns model used (equation (3)). Simulation is obtained on results for quantities of used APs in Serbia, five groups of APs and their life expectancies with defined sensitivity range and sensitivity factors.

The following steps are conducted based on the given formula and were applied on each group of products:

1. MC simulation using share of different APs in relation to the total consumption and triangular distribution for the life expectancy of the APs, where maximum and minimum years, as well as the mode, are taken as parameters. The count function counts the number of 10,500 to 11,000 data points, simulated years that are located between the upper and lower limits of confidence interval. Triangular distribution is used in the case when there is no reliable data on standard deviation and shape of the targeted distribution.

2. The next point is to find out appropriate distribution that fits the best with the following assumption for sensitivity range and sensitivity factors defined:

(a) For ACP and VAP in the year of the material life expiration 80% of the AW is generated, while 10% of waste is generated within 10 years before life expiration, and 10% within the 10 years after the material life expiration. Based on above assumption, Cauchy distribution with location = 0 and scale = 0.4 could approximate such a requirement.

(b) For FP in the year of the material life expiration 100% of waste to be generated.

(c) For APF and AO in the year of the material life expiration 80% of waste to be generated at the peak year of the life expiration, and 10% to be generated 5 years before, and 10% in 5 years after the life expectation. However, according to Cauchy distribution shape (with location = 0 and scale = 0.35), it is more likely to expect 90% of the waste to be generated at the peak year of the life expiration and 5% to be generated 5 years before, and 5% in 5 years after the life expiration. So, this assumption is used in the further analysis.

These distributions represent a correction to the triangular distribution created earlier.

3. Follows, total of the previous two MC phases by summing up triangular distribution for the life expectancy and corrective Cauchy distribution for the life expiration variability.

4. Next step is to find out if this new distribution fits to any other known distribution using Minitab function: Start > Quality tools > Individual Distribution Identification. With big sample cases (10,500–11,000 data points) Minitab is very restrictive even from small departure from any distribution. For that reason, graphical presentation is used for identification of the best goodness of fit where needed.

5. Calculating the amount of AW per each year from 1930 to 2067 based on the distribution parameters obtained in the previous step. In the case when no appropriate distribution could be defined by Minitab (i.e. the case of AC), it is proceeded with non-parametric method. That means all data were sorted, and individual and cumulative percentage for the ‘round calendar years’ is obtained in half-manual way. In both cases, parametric (when appropriate distribution could be defined) and non-parametric (when no distribution could be defined), the percentage of the life expectancy for the ‘round calendar years’ is used for multiplication with corresponding AP used in each calendar year to obtain waste generated in each calendar year from 1930 to 2067.

6. To predict the total annual removal of asbestos products from the environment over time summing up AW quantities from each of the five groups of products are obtained.

The inputs used for MC simulation and the results obtained by phases are shown in Supplemental Appendix Table A3.

Results are partly consistent with the Donovan and Pickin (2016) and their assumption that a Weibull function would provide an appropriate approximation of APs removal rate. The MC simulation, however, points that it cannot be generalised that Weibull distribution is adequate for all types of AP and that other adaptations are needed in cases of ACPs and VAPs.

Figure 4(b) shows the calculated amount of waste, starting from the 1930s and ending in the 2060s. The sharp rise and fall in proportion to the amount of waste follows the World’s AC trend. Large amounts of waste are expected in the upcoming years because asbestos from construction during the 1970s and 1980s will be ready for replacement due to deterioration. For 2021, it is estimated that 15,652 tonnes of waste will be generated. After 2040, the amount of AW drastically decreases because of sanctions during the 1990s, followed by a ban on the use of asbestos. It is important to note that only the quantities of asbestos fibres that are transferred to waste are shown here. When it comes to the quantities of waste that will be manipulated in practice, a larger amount should be considered. ACPs were mostly used in construction, so it can be assumed that all construction waste that contains asbestos can be considered hazardous (it will contain more than 0.1% asbestos). These quantities of ACPs, in relation to the proportions of asbestos fibres in the products, can increase to a total of 2–3 million tonnes of AW to be managed in Serbia. For comparison, Poland estimated the amount of AW for removal to be about 14.5 million tonnes for the period of 2009–2032 (not only fibres) and assumes that the problem of AW will have been solved with subsequent process of diminishing by 2032. But analyses show that until now the process of removing and neutralising asbestos has been performed significantly slower than it was planned. (Szymańska and Lewandowska, 2018)

Up to 2009, no systematic assessment of AW quantities in Serbia had been performed. In 2010, according to official reported data, 517 tonnes of AW was generated, and 1035 tonnes was landfilled (Ministry of Environment, Mining and Spatial Planning, 2010a, 2010b). For official amounts, there is no information on whether it is only asbestos fibres or overall waste that contains asbestos.

Figure 5 shows the differences between APs and their amounts of fibres that will be generating AW over the years, since the 1970s. At the beginning, as expected, waste from products with a shorter lifespan (FAP, AO, etc.) appeared. From 2000s, VAPs and ACPs significantly pass to waste. While in the years to come, waste quantities of ACPs are dominant.

Total asbestos consumption by the environment over the years is approximately 0.5 million tonnes of fibres as shown by a dotted part in Figure 6. This amount of consumed asbestos eventually goes to waste (shown by the part with the squares in Figure 6). The difference between consumed asbestos and asbestos that becomes waste is displayed as stocks (thick line on Figure 6). The calculated stocks for the year 2021 are 251,179 tonnes, while the most significant amount of AP, will become waste by 2045. Considerable amounts of generated AW are a direct consequence of high-level AP consumption.

Although it seems impossible to predict the precise amount of AW, the findings of this research indicate that the generation of AW in Serbia is at its peak now and will be high for the next 10–20 years. The high AW generation with 183,290 tonnes between 2021 and 2040 is a result of extensive AC in the 1970s–1980s. The obtained results compared with the works of Donovan and Pickin (2016) for Australia and Li et al. (2014) in the Asian-Pacific region mentioned above, corresponds in terms of the trend of high AW generation expected in the next two decades. Poland, as well, expects a great amount of AW in the next decade as a result of the systematic removal of used asbestos-containing materials (Szymańska and Lewandowska, 2018). Also, common to the research by Donovan and Pickin (2016) and Li et al. (2014) is that the model provides an alternative method for designing future waste management needs by accessing the problem from the perspective of the annual quantities of asbestos containing waste expected to be generated per year in the future and remaining stocks, which enables understanding of the needs for necessary capacities to ensure the safe management, recycling, and disposal of AW. What is new is the method of estimating quantities for countries with lack of data (such as transition countries) and the possibility of waste differentiation by product type.

Conclusion

This paper elaborates that a lack of data for asbestos quantities and poor management practice of AW are fundamental problems in dealing with the asbestos burden in countries in economic transition. The model developed and described in this paper provides an opportunity to access data about AC and AW amounts where information is lacking. It is shown first-order estimate of consumed asbestos quantities per year, amounts of stock, and flows of AW over time in Serbia as an example of transition country. It is known for the first time how much asbestos was consumed within, how much remains in the built environment, and how much is going to waste each year.

According to the generated results, quantities of asbestos consumption in Serbia are around 0.5 million tonnes, stocks of asbestos peaked in 1993 and waste quantities will peak in 2020s due to the expected end-of-life for products; in 2020, the stocks are at 54% of consumed AP. It is shown that calculated consumption of asbestos in Serbia for period 1930–2017 is on average 0.65 kg per capita per year. This corresponds to world’s average consumption of 0.75 kg per capita per year for period 1950–2013. Differentiation by groups of APs in terms of their waste generation is also shown. AW, at an estimated generation of 183,290 tonnes between 2021 and 2040, will pose health, occupational safety, and environmental risk, and must be handled properly as hazardous waste. Currently, in Serbia, almost all asbestos containing waste is disposed of to landfills. Landfills generally document and report to government the quantities of asbestos containing material received, but the actual quantity of asbestos is not apparent because this type of waste is often received mixed with construction waste. According to official data, the quantities of AW that have been generated and landfilled in last years are much smaller from the amounts in the modelled estimations. This can be explained by the existence of stocks in the environment. These stocks can be in the form of non-sanitary landfills/wild dumps, home backyards or that asbestos is left in first place even after its lifetime expires. As already mentioned, developed countries with more regulated systems, such as Italy and Poland, also face alike problems, especially regarding wild landfills.

The proposed model can be applied to the territory of a city, municipality, or region. Delivered data can help decision or policy makers to designate a capacity for proper sanitary landfills to accept the expected amount of AW that will emerge in specific year, also which new technologies need to be implemented and new treatment facilities established according to type of APs in AW during years. Knowing the dangers of asbestos dust, adequate treatment is extremely important from the standpoint of the health of workers (who will remove asbestos), the population and the environment in general. Local and government institutions can take the responsibility for prevention of occurrence asbestos-related diseases, knowing when can be expected to be managed with significant amounts of AW, and when workers in waste sector will be exposed. Moreover, this model can be applied to the landfill development programmes, financial resources distribution, improving legal procedures and application of monitoring policies. Finally, governments should raise public awareness of the dangers associated with asbestos and the importance of its safe removal in coming years. Countries with a lack of adequate data can apply model in the real domain to estimate annual AW generation and it can be an important tool for formulating strategies and preparing management resources, as highlighted above.

Determining the precise existence and distribution of stocks will be the subject of future research, with more focus on the flows and end of life disposal of asbestos stream, and evaluation of the impact (on human health) of the AW treatment and management in Serbia. Future directions of research would be to improve the model by determining the more precise life-expectancy of various APs. Conducting an asbestos inventory and mapping of asbestos locations throughout the country (city, region) with estimates of the asbestos amount, may improve the model as more accurate input data on quantities would be obtained.

Supplemental Material

sj-docx-1-wmr-10.1177_0734242X211064031 – Supplemental material for Assessment of asbestos and asbestos waste quantity in the built environment of transition country

Supplemental material, sj-docx-1-wmr-10.1177_0734242X211064031 for Assessment of asbestos and asbestos waste quantity in the built environment of transition country by Bojana Zoraja, Dejan Ubavin, Nemanja Stanisavljevic, Svjetlana Vujovic, Vladimir Mucenski, Miodrag Hadzistevic and Milos Bjelica in Waste Management & Research

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Dejan Ubavin

Nemanja Stanisavljevic

Vladimir Mucenski

Supplemental material

Supplemental material for this article is available online.

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