Three facets of urban metabolism (case of Kazakhstan)

ABSTRACT

The urbanisation growth causes problems related to the provision and consumption of resources, ecology, and social living conditions in cities. The purpose of the article is to study the dependence of metabolic factors and the level of urban conveniences on the urbanisation level and to justify the need to monitor these processes and improve the management of urban systems with the purpose to achieve sustainable development objectives. Three aspects of the problem of urban metabolism and sustainable development of cities are considered in the article. They are energy consumption by megacities, social aspects of metabolism and growth of megacities, problems of urban improvement. The increasing risks of negative impact of urban growth on the environment and living conditions has been proven. It is shown that the resettlement flow of village residents to cities, especially large ones, remains high despite the deterioration of the environmental situation in large cities and the lag in the urban infrastructure development from the population growth rate. The expediency to expand the context of the urban metabolism problem was noted, including the exchange of resources between urban and rural to reduce spatial inequality, and to increase the sustainability of urban and rural settlements.

KEYWORDS:

• City metabolism
• urbanisation
• sustainable city development
• liveability of city
• ecology
• resources
• consumption
• waste
• Kazakhstan

1. Introduction

In modern conditions, when an increasing part of the world’s population is concentrated in cities, the economic prosperity of countries largely depends on economic growth, social well-being, environmental safety, and the rational use of urban resources (Maksoud 2005). Experts predict that two-thirds of the world’s population could be affected by lack of land, water, and food by 2050 (Rivas and Nonhebel 2016; Cristiano et al. 2020). As alleged by Kennedy et al. (2015), the 27 largest metropolitan areas in the world are home to 7% of the world’s population, accounting for 9% of global electricity consumption, 13% of solid waste, that is, it can be said that they consume an ever-increasing share of the resources of countries and the planet. The life of cities implies the presence of input and output flows of resources that form a complex system of relationships both within the city and with the external environment. These processes are described within the concept of urban metabolism by analogy with the metabolic processes of living organisms. From the position of biology and biochemistry, ‘metabolism’ is the material exchange within an organism, or between organisms and the environment, during which consumed nutrients are converted into energy. Obviously, urbanisation and population growth in the largest cities can also have different nature and consequences both for cities and for the external environment. The result is a multifaceted picture of urbanisation and spatial inequality.

In Kazakhstan, the problems of urban metabolism have become very relevant on the modern stage of urbanisation, with the emergence of new megacities. The lack of scientific research against the backdrop of a growing and contradictory urbanisation picture in Kazakhstan determined the choice of the topic for the article.

The purpose of the article is to explore the dependence of metabolic factors and the level of urban conveniences on the urbanisation level and to justify the need to monitor these processes and improve the management of urban systems to achieve sustainable development goals. It is very important to assess the dependence of factors of urban metabolism, urbanisation, and its consequences for the implementation of sustainable development policies. The hypothesis of the study was the assumption of an increase in the dependence of factors of urban metabolism, the level of urban conveniences and ecology on the growth of the population in megacities.

2. Literature review

From the moment of the first study of urban metabolism, methodological approaches to its study have evolved considerably. Dinares (2014), Wachsmuth (2012), Saito (2016) consider that they were the conceptual provisions on metabolism, the modern understanding of urban metabolism that were outlined by K. Marx in the 19th century. They refer to the concept of the ‘metabolic gap’ resulted from the use of resources during the development of capitalism, industrialisation, and urban growth. Derrible et al. (2021) attribute the emergence of the term ‘urban metabolism’ (UM) to the work of Wolman (1965). Wolman considered urban pollution problems because of resource flow. Wolman’s approach helped his followers to focus on the system-wide consequences of resource consumption and waste generation in urban environments. He said that urban metabolism is based on controlling the daily exchange of energy and resources consumed, stored, imported into, or exported from cities that in itself is an extremely complex task.

The first metabolism studies through the example of real-world cities Tokyo (Hanya and Ambe 1976), Brussels (Lachmund 2017), Hong Kong (Newcombe et al. 1978), Miami (Zucchetto 1975) were performed in the 1970s by scientists from various industries (chemistry, ecology, construction).

During the 1980s and 1990s, interest to study urban metabolism declined slightly but the concept of UM regained popularity in the early 2000s fuelled by the growth of sustainability research (Sviden and Jonsson 2001; Tarr 2002; Sahely et al. 2003). The results of metabolism studies of such megacities as Sydney (Newman 1999), Vienna (Hendriks et al. 2000) and Hong Kong (Warren-Rhodes and Koenig 2001) were generated and published at the turn of the millennium.

The evolution of the concept of metabolism demonstrates the interdisciplinarity of the problem. Initially, these were studies investigating material and resource consumption (Zucchetto 1975; Haberl 2001; Warren-Rhodes and Koenig 2001; Wegener and Fuerst 2004) and problems of availability (Browne et al. 2009; Kennedy et al. 2011), as well as the reduction and recycling of industrial waste (Rees and Wackernagel 1996; Tarr 2002; Gandy 2006; Bai 2007). Further, a natural connection with analysis of the human living conditions, the social aspect of metabolism, has been considered (Newman 1999; Buhaug and Urdal 2013). A completely logical realisation arises cities can provide economic growth and comfortable living conditions, and thus it is important to preserve the metabolic process. There is an emerging awareness of the need to plan, organise and manage urban ecosystems properly (Barles 2010; Kennedy et al. 2011; Conke and Ferreira 2015; Currie and Musango 2017; Cristiano et al. 2020). Thus, the need for dialogue between representatives of economic, social, biological, political, environmental, engineering and other fields becomes evident. Only the integration of all approaches can provide a full understanding of urban problems and guarantee their sustainable development.

Kennedy et al. (2011) define urban metabolism as ‘the sum of the technical, social and economic processes occurring in cities that result in increase in energy production and waste reduction’. This definition includes the major technical and industrial components of the urban system, focusing on its quantification. Currie and Musango (2017) consider urban metabolism as ‘a set of complex social and technical, social and environmental processes through material, energy, human and information flows’. In the opinion of (Saguin 2019) urban metabolism broadly refers to the process of social and ecological exchange and transformation in cities.

The study of urban metabolism from different angles and perspectives defines its interdisciplinary nature (Broto et al. 2012). The concept of urban metabolism has contributed to the development of quantitative approaches to assess urban resource flows and inspired ideas to design sustainable cities (Brockerhoff 2000). In particular, the quantification of material and energy flows in close relationship with industrial ecology has been widespread at the most (Ulgiati and Zucaro 2019; Maranghi et al. 2020). The need for quantification is explained by the need to rationalise resource consumption, increase the sustainability of the exchange process, and reduce negative environmental impacts (Gandy 2004; Murray et al. 2005; Brunner 2007; Barles 2010).

Of special note is the work (Newman 1999) who proposed an extended metabolic model that includes health, employment, income, education, housing, and social leisure parameters. He demonstrated the applicability of the sustainability concept to urban systems by identification of the need to consider all aspects of human life during assessment of urban development outcomes, by demonstration of the interdependence of human quality of life indicators and urban metabolism in his model of extended urban metabolism. The relationship between urban metabolism and quality of life has subsequently become a topic of work by other scholars who examined the interdependencies of urban metabolism flows with social and demographic factors (Wegener and Fuerst 2004; Lyons et al. 2018) and social and cultural factors (Dijst 2018). Liu et al. (2010), Wu et al. (2018), D’Amico et al. (2021), Gan et al. (2023) attempted to quantify metabolism and develop measures to improve the efficiency of urban infrastructure systems through economies of scale. Cities are characterised by a great complexity of life support systems. In the scientists’ opinion, cities are complex ecosystems with different spatial, temporal, and organisational scales, formed by human-nature relationships where social, economic, and biophysical factors interact regularly and sustainably (Iodice and De Toro 2020). In the process of its functioning, a city interacts closely with the environment, consumes resources and generates significant amounts of emissions and waste, and the rapid population growth in cities creates the possibility of resource shortage. Urbanisation is fraught with problems explained by the urban metabolism theory that enables to estimate the material and energy flows of the urban system (Ulgiati and Zucaro 2019; Facchini et al. 2021).

Facchini et al. (2021) is convinced of the usefulness of quantification to identify actual resource stocks and optimise their use to avoid critical impacts. Some authors have tried to analyse the spatial characteristics of urban metabolism and its relationship with urban macroeconomic patterns (Fung and Kennedy 2005; Barles 2010; Kennedy et al. 2011; Conke and Ferreira 2015). Goldstein et al. (2013) notes that attempts to study metabolism comprehensively or to study its individual components vary widely in terms of aspects to be considered and parameters to be assessed. Besides, the problem of availability of the required accurate data and the complexity of their collection should be considered. It contributes to a significant simplification of the study subject (Bancheva 2014). However, it should be recognised that there are no methods that take the influence of all factors (social and economic, institutional, environmental) into account simultaneously during quantification of metabolism. At the same time, quantification of metabolism processes may also give a rather distorted picture with rapid urban growth. For example, a decrease in per capita water consumption may show a decrease in water availability rather than a more efficient use of water. Ideas of efficient use of urban land may result in the misuse of densification projects.

Rapid urban growth has inevitably contributed to changes not only in the form and structure of urban systems but also in the functions they fulfil (Sekovski et al. 2012; Von Glasow et al. 2013). This aspect determines the importance to study the urban metabolism phenomenon and the impact of cities on various aspects to of society. Dijst (2018) notes that the high concentration of material, service and energy flows in cities enables to generate a significant share of gross domestic product (GDP), ensuring the well-being of billions of people. However, not enough attention is paid to the problem of the urban metabolism impact on the metabolism and spatial inequality of territories, including rural areas. Thus, the conducted review shows the high significance of the study of these processes, as they show the increasing impact of urbanisation on the environment and social conditions of urban dwellers. Thus, accelerated urbanisation results not only in the need to address the issues of resource lack, waste management, infrastructure development for the ever-growing number of urban residents but also to various aspects of life in regions and in the country.

3. Materials and methods

The authors conducted dependency analysis the consumption by cities of resources and the generation of waste with applied correlation analysis. The relationship between the consumption of electricity and heat, and emissions of pollutants from population growth in Almaty and Astana is considered. Analysis of the main metabolic factors carried out using Pearson’s product moment correlation coefficient (PPMCC), formula 1.

(1) $\mathrm{R}=\frac{{\sum }_{\mathrm{i}=1}^{\mathrm{N}}\left({\mathrm{x}}_{\mathrm{i}}-\bar{\mathrm{x}}\right)\left({\mathrm{y}}_{\mathrm{i}}-\bar{\mathrm{y}}\right)}{\sqrt{{\sum }_{\mathrm{i}=1}^{\mathrm{N}}\left({\mathrm{x}}_{\mathrm{i}}-\bar{\mathrm{x}}\right)}{\sum }_{\mathrm{i}=1}^{\mathrm{N}}{\left({\mathrm{y}}_{\mathrm{i}}-\bar{\mathrm{y}}\right)}^2},$(1)

where

N – number of values in the sample; X – values of the variable.

Y – values of variable.

$\bar{\mathrm{x}}=\frac{{\sum }_{\mathrm{i}=1}^{\mathrm{N}}{\mathrm{x}}_{\mathrm{i}}}{\mathrm{N}}$ – arithmetic mean from the sample for variable X.

$\bar{\mathrm{y}}=\frac{{\sum }_{\mathrm{i}=1}^{\mathrm{N}}{\mathrm{y}}_{\mathrm{i}}}{\mathrm{N}}$ – arithmetic mean from the sample for variable Y.

To determine whether the growth of the city’s life support infrastructure corresponds to population growth, the liveability coefficient proposed by Kuznetsov (2000) was calculated using formula 2:

(2) $\mathrm{K}=\frac{1}{\mathrm{n}}\times {\sum }_1^{\mathrm{i}}\frac{{\mathrm{B}}_{\mathit{\phi }\mathrm{i}}}{{\mathrm{B}}_{\mathit{n}\mathrm{i}}}$(2)

where K – coefficient of well-being (K ≤ 1).

Bᵩ_i, – actual level of provision with the i-th type of household services.

В_ni – normative (standard) level of provision with the i-th type of household services. Normative (standard) level = 1.

n – number of types of household services.

The assessment of the level of demographic capacity of cities was carried out according to two indicators: the demographic capacity of the territory (formula 3) and the demographic capacity of water resources (formula 4).

Demographic capacity by territory:

(3) ${\mathrm{D}}_{\mathrm{t}}=\frac{\mathrm{S}\ast 1000}{\mathrm{H}}$(3)

where, S – territory, ha; H – required area for the city (30–40 hectares per 1000 people). Dt – demographic capacity by territory.

Demographic capacity in terms of water resources:

(4) $\mathrm{Dw}=\frac{{\mathrm{Q}}_{\mathrm{w}}}{{\mathrm{N}}_{\mathrm{w}}}$(4)

where Dw – demographic capacity for water resources.

Qw – water supplied to consumers per capita, cubic metres per day.

Nw – rate of consumption of cold water per capita, cubic metres per day.

Research information base amounted to official statistical data of the Bureau of National Statistics of the Agency for Strategic Planning and Reforms, data from the statistical departments of regions and cities of Kazakhstan, legal acts of the, construction norms and rules, databases of the National Hydrometeorological Service of the Ministry of Ecology and Natural Resources of the Republic of Kazakhstan (Kazhydromet), IQAir platform.

4. Results and discussion

4.1. Problems of metabolism in megacities (the example of Astana and Almaty)

It is widely recognised that cities provide more opportunities for business development, trade, economic growth, employment, higher incomes, as well as higher living standards, access to education, health care and culture. Besides, the average cost for construction of communications, transport networks, as well as the provision of vital services (water, electricity) is significantly reduced due to the higher density of urban population. The normal functioning of urban systems requires provision of sufficient resources. Increase in rates of consumption noted in the largest cities of Kazakhstan – Almaty and Astana (Figure 1).

Figure 1. Dynamics of energy consumption and Emissions of pollutants in Astana and Almaty.

Note - compiled by the authors based on data Bureau of National statistics

Thus, over the past 20 years, the consumption of electricity and heat by the population of the country’s metropolises has increased by 2.45 and 1.82 times, respectively. At the same time, it should be noted that the growth rate of demand for electricity in Astana is 3 times higher than in Almaty, and more than 2 times for heat energy. The situation is different regarding emissions of pollutants into the atmosphere. During the analysed period, the total amount of emissions in the two metropolises increased by 70% but the growth rate of pollution in Almaty was 2.7 times higher than in Astana. The main pollution sources are motor transport, industry and the heating and energy system of towns (the work of cogeneration plants and heating of private homes by coal).

A major role in the growth of emissions in Almaty is primarily due to an increase in the number of motor vehicles. Moreover, the number of cars in the southern capital exceeds their number in Astana by 2.7 times. The consequence of the increase in vehicles in the megacities of Kazakhstan has become the highest level of air pollution in the Republic. Thus, the pollution index in Almaty reached 8.0, and in Astana − 7.0.

The high concentration of pollutants in the atmosphere of Almaty is also due to the geographical location of the city, which is in a basin at the foot of the mountains and has low air mobility. Studies prove the linear dependence of urban consumption of many resources and the production of identical amounts of waste, affecting both the urban system as a whole and its individual hinterland areas. Correlation analysis of the dependence of the main urban metabolism factors (consumption of electricity and heat, as well as emissions of pollutants into the atmosphere) on the population growth (population size) through the example of Almaty and Astana was conducted to verify this point of view (Table 1).

Table 1. Coefficients of correlation dependence of the main factors of metabolism on the population of the cities of Astana and Almaty.

Basic factors of metabolism	Coefficients of correlation dependence
	Astana	Almaty
Electricity consumption	0,950768767	0,481822139
Heat consumption	0,9901132	0,43095419
Emissions of pollutants into the atmosphere	0,666895176	0,866108818

Note – Calculated on data of the Bureau of National statistics.

Calculations have shown that a positive correlation between energy consumption, pollutant emissions and population size is observed for both cities in all three dependencies. However, Astana is characterised by a higher degree of electricity and heat consumption dependence on its urbanisation level. At the same time, the Almaty is characterised by a high correlation dependence of atmospheric emissions on the number of populations. It should be noted that Almaty and Astana are in different climatic zones. Astana is one of the coldest capitals in the world. Besides, the concept and design of urban lighting in Astana is significantly different from Almaty, and the street lighting level is higher. The analysis of the correlation between the country’s energy consumption, electricity consumption and GDP has shown a positive relationship between the variables, with mutual influence of the components (Table 2). The constructed models are significant because the correlation coefficients are positive and have values from 0.918 to 0.952. The determinism coefficients of the models show the percentage of variation of dependent variables and are in the range of 0.838–0.905, i.e. close enough to one. The constructed plots of the models also demonstrate the close relationship of the data (Figure 2).

Figure 2. Dynamics of resource consumption and GDP.

Table 2. Correlation dependence of resource consumption and GDP.

No	Dependent variables	Depend	model function/equation				Student’s t-test			Determination coefficient	Fisher’s criterion
1	GDP, billion tenge/ Energy	0.9179	y = 0,0021536+ 84,27898*x (0,0002136) (7.593661)				t		P > t	R^2 = 0.8426	F(1, 19)	=	101.69
							44783,00		0.000		Prob > F	=	0.0000
							44845,00		0.000
2	Energy consumption, million ton of reference fuel / GDP per capita, thousand tenge	0.9155	y = 0,0402702+ 79.79213*x (0,0040606) (8,073044)				t		P > t	R^2 = 0.8381	F(1, 19)	=	98.35
							9,92		0.000		Prob > F	=	0.0000
							9,88		0.000
3	Electricity consumption, billion kWh/ GDP, billion tenge	0.9516	y = 0.0006635+44.44246*x (0,0000491) (1.747505)				t		P > t	R^2 = 0,905	F(1, 19)	=	182.25
							13.50		0.000		Prob > F	=	0.0000
							25.43		0.000
4	Electricity consumption, billion kWh/ GDP per capita, thousand tenge	0.9507	y = 0. 0124268+44. 02749*x (0, 0009304) (1.849777)				t		P > t	R^2 = 0,8987	F(1, 19)	=	178.39
							13.36		0.000		Prob > F	=	0.0000
							23.26		0.000
Source	SS	df	MS	Number of obs	=	21	Source	SS	df	MS	Number of obs	=	21
reg Energyuse GDP							reg Electricityconsumption GDP
				F(1, 19)	=	101.69					F(1, 19)	=	182.25
Model	47603.5998	1	47603.5998	Prob > F	=	0.0000	Model	4518.20745	1	4518.20745	Prob > F	=	0.0000
Residual	8894.6326	19	468.138558	R-squared	=	0.8426	Residual	471.044929	19	24.7918384	R-squared	=	0.9056
				Adj R-squared	=	0.8343					Adj R-squared	=	0.9006
Total	56498.2324	20	2824.91162	Root MSE	=	21.637	Total	4989.25238	20	249.462619	Root MSE	=	4,9791
Energyuse	Coefficient	Std. err.	t	P > t	[95% conf.	interval]	Electricity	Coefficient	Std. err.	t	P > t	[95% conf.	interval]
GDP	.0021536	.0002136	44783,00	0.000	.0017066	.0026006	GDP	.0006635	.0000491	13.50	0.000	.0005606	.0007663
_cons	84.27898	7.593661	44845,00	0.000	68.38527	100.1727	_cons	44.44246	1.747505	25.43	0.000	40.78489	48.10003
reg Energyuse GDPpc							reg Electricityconsumption GDPpc
				F(1, 19)	=	98.35					F(1, 19)	=	178.39
Model	47350.7348	1	47350.7348	Prob > F	=	0.0000	Model	4509.00364	1	4509.00364	Prob > F	=	0.0000
Residual	9147.49753	19	481.447239	R-squared	=	0.8381	Residual	480.248742	19	25.2762496	R-squared	=	0.9037
				Adj R-squared	=	0.8296					Adj R-squared	=	0.8987
Total	56498.2324	20	2824.91162	Root MSE	=	21.942	Total	4989.25238	20	249.462619	Root MSE	=	5.0275
Energyuse	Coefficient	Std. err.	t	P > t	[95% conf.	interval]	Electricity	Coefficient	Std. err.	t	P > t	[95% conf.	interval]
GDP	.0402702	.0040606	9,92	0.000	.0317712	.0487692	GDPpc	.0124268	.0009304	13.36	0.000	.0104795	.0143742
_cons	79.79213	8.073044	9,88	0.000	62.89506	96.68921	_cons	43.02749	1.849777	23.26	0.000	39.15586	46.89911

Note - Compiled and calculated by the authors using STATA.

In general, the conducted correlation analysis enabled to prove the importance and necessity to take the main factors of urban metabolism in management of the urban systems functioning and related social and technical processes into account.

4.2. Social aspects of UM

Urban growth is associated with a social resources and social consequences. Over 2000–2022, the urban population of Kazakhstan increased by 43.9%, while the population of megacities increased by 131.8%. Obviously, the growth of the largest cities significantly outpaced the growth of the population in other towns. According to official data, the total number of the employed in Astana and Almaty for 2010–2022 increased by 77.5% and 47.4% respectively. At the same time, the share of employed in Astana decreased from 56.48% to 48.2%, and in Almaty from 48.68% to 47.4%. These dynamics are a result of peculiarities of demographic processes, about the change in the structure of the population, the growth of the demographic burden (Table 3).

Table 3. Demographic dynamics, employment, living standards and poverty in Kazakhstan’s megacities in 2010–2022.

	Astana		Almaty
	2010	2022	2010	2022
Population, thousand people	649.2	1295.71	1390.6	2101.48
Net migration, thousand people	33.8	33.8	8.8	36.5
Total fertility rate, number of children per woman	2.45	2.58	1.71	2.05
Dependency ratio, per 1,000 productive population	385	661	443	570
Old-age dependency ratio, per 1,000 productive population	85	131	162	192
Employed population, thousand people	366.7	625.5	676.9	998.0
Share of employed population in total population, %	56.48	48.2	48.68	47.4
Number of self-employed, thousand people	29.9	75.9	56.7	112.4
Share of self-employed in total employed population, %	8.2	12.1	8.4	11.3
Average nominal cash income per capita, tenge	67 172	223 542	67 190	214 112
Household cash expenditures on average per month per capita, tenge	45 835	92 672	40 827	105 838
Median income, tenge	33 709	75 907	40 693	82 716
Poverty rate, %	3.4	1.9	2.6	4.8
Depth of poverty, %	0.6	0.3	0.3	1.0

Source - Bureau of National Statistics.

The most common area of employment remains wholesale and retail trade. Thus, in Almaty employment in trade increased from 21% to 24%. The growth of the employed population in Almaty was formed due to increase in the share of self-employment. Thus, the share of the self-employed in Almaty increased by 44%, and in Astana by more than twice as much. The high level of self-employment indicates the unstable nature of employment of a significant number of able-bodied populations largely due to the low level of the industrial base development. The highly contradictory nature of the urbanisation quality in Kazakhstan often results in increased social tensions in large cities. When the indicators of living standards of urban residents are compared, there is an outpacing growth rate of the average per capita cash income of metropolitan residents. If income level in Astana and Almaty was almost at the same level and was slightly more than KZT 67 000 in 2010, then in 2022 the income in Astana was ahead of income in Almaty. At the same time the median income in Astana was lower than in Almaty. Expenses of households per capita per month in Almaty city grew faster (in 2022 - by 159% compared to 2010) while the growth of expenses was much lower – by 102% in Astana. However, the increase in poverty and inequality in Almaty indicates that the economic development results have been very distributed unevenly.

The demand for living space increases as cities grow, often resulting in an increase in the cost of land and housing, to the point where their affordability for low-income populations, including rural migrants, is significantly reduced. As a result, there is a choice to return to the village, or to find housing in areas far from the city centre, often with underdeveloped infrastructure, spending hours travelling to work, sometimes engaging in informal activities. Studies conducted by Kazakhstani scientists (Alibekova et al. 2018; Shmelev et al. 2018; Chulanova 2019) draw attention to the fact that overpopulated Almaty, does not have time to adapt to population growth that occurs mainly due to migration. The inequality problem in the megacity manifests itself in different aspects: unemployment, high housing prices, illegal construction, the emergence of slums and sustainable pockets of unemployment, the growth of conflict potential. The urban population growth faces the limitations of the natural potential in the territory. These processes are reflected through the demographic capacity parameters of the territory. These indicators can reflect different aspects of the capacity: by territory, by water resources, by agricultural land, by recreation areas, etc. (Table 4).

Table 4. Demographic capacity of Kazakhstan’s megacities, 2021.

	Notation	Astana city	Almaty city
Population, people	P	1212078	2001060
Territory, ha	S	80000	70000
Need for territory per 1000 inhabitants (30–40 ha)	H	40	40
Demographic capacity by territory, people	Dt	2 000 000	1 750 000
Water supplied to consumers per capita, cubic metres per day	Qw	247678	471132
Norm of cold-water supply per capita, cubic metres per day	Nw	0,28	0,28
Demographic water availability capacity, people	Dw	884 564	1 682 614

Source.

1. On the operation of water supply and sanitation systems in the Republic of Kazakhstan. Series 4 Environmental Statistics. Nur-Sultan, 2021

2. Construction norms and rules of the Republic of Kazakhstan ‘Water supply External networks and structures’ (SNiP RK 4.01-02-2009)

According to calculations, the demographic capacity of the territory is already exceeded in Almaty. At first glance, Astana city has the potential for expansion but here it is required to take other demographic capacity components of the territory into account. The limits have been reached in all megacities under such parameter as demographic capacity in terms of water availability. The problems of limited water resources are very relevant in Kazakhstan and are a serious challenge for the expansion of Kazakhstani megacities and cities (Karatayev et al. 2017; Nyussupova et al. 2020).

In other words, a part of urban residents does not receive the amount of water required to ensure an acceptable quality of life. There are urban areas in megacities, particularly in Almaty, that have a time-limited drinking water supply regime, where there are no paved roads, no drainage system for storm water. Compacting development without expansion of green areas, public spaces, underground car parks, violation of building codes and regulations, illegal allocation of land for construction are manifestations of the fact that the priority in urban policy is given to the corporate interests of construction companies rather than the goals of urban environment development. In general, it can be said that Kazakhstani megacities have reached their limits in terms of utilisation of territorial and water potential. Their further expansion may take place through absorption of nearby villages and small towns with lower quality of environment and infrastructure, which creates new challenges for megacities.

Megacities are not coping with the role of drivers and growth points. Undoubtedly, Almaty plays a major role in Kazakhstani economy, generating 18.5% of GDP. However, Almaty’s foreign trade balance remains passive, while Astana’s foreign trade position is weak (Figure 3). Almaty accounts for 43% of all imports, and its activity structure is dominated by wholesale and retail trade (33.5% of gross regional product) that attracts labour from rural migrants and low-skilled workers as it is supported by numerous markets.

Figure 3. Foreign trade balance, million USD.

As international experience of megacity development shows, rapid urban population growth, poor environmental and social conditions, and significant water shortages result in increased atmospheric pollution and can act as an additional catalyst for the spread of infectious diseases. Besides, large cities around the world face the emergence of areas of poor-quality infrastructure, segregation, and marginalisation, where it is very difficult to ensure the required level of sanitary and epidemiological safety (Motta 2020). This statement is confirmed by Kazakhstani excess mortality statistics. Excess mortality totalled 81,887 persons in Kazakhstan for 2020–2021, 72% of which falls on the urban population. Most excess deaths occur in Almaty city − 14.6% in 2020 and 18.6% in 2021, and Astana city − 9.6% and 7.7% respectively.

Residents of megacities often experience stress, alienation, anxiety resulted in deviant behaviour and an increase in crime. A negative trend is also observed in Kazakhstani metropolises. If the population in Astana and Almaty during the analysed period increased by 75% and 38% respectively, the population of convicts – by 75% and 18%. Over a 10-year period, the number of crimes in Astana city increased 5.6-fold and in Almaty city − 3.3-fold, the crime rate − 3.43 and 2.5-fold respectively (Table 5).

Table 5. Dynamics of indicators of offences in megacities of Kazakhstan in 2010–2020.

	Astana		Almaty
	2010	2020	2010	2020
Number of registered crimes, units	4491	13 648	19002	28 672
Crime rate per 10,000 population	70	118	137	147
Number of convicts, persons	1464	1926	2501	2961

Note - Compiled from the Bureau of National Statistics.

In turn, residential neighbourhoods populated by marginalised populations constitute a parallel city, with its own economic, social, and political life. One cannot ignore the fact that the place of residence and activity has a great influence on persons’ behaviour. Despite the provision of a higher quality of life, urbanisation significantly changes persons’ values, behaviour, and preferences, as it can be seen, unfortunately, not always for the better. While in most countries in the last century the family was traditionally preferred as the basic unit of society, today the traditional social structures are in decline and new types of communities are emerging. Specialists note the growth of destructive behaviour among young persons, characterised by the development of addictive disorder (Buhaug and Urdal 2013). As a result of difficult life circumstances, persons want to escape from the real solution of problems through addictions and addictions (alcohol, drugs, gambling, religious sects). Troshin (1995) and Filyushkina (2014) pointed out possible destructive consequences of urbanisation as a probable source of society lumpenisation in their works. One of the manifestations of this phenomenon is the process of social and psychic epidemic generated because of the crisis of adaptation, changes in man’s relationship with nature and society. It is most often manifested in the growth of mental illnesses, suicides. High population density, unemployment, poverty, differences in the level of culture, loneliness, housing problems can become factors of stress intensification.

Excessive urbanisation reinforces inequalities between rich and poor, leading to the fragmentation of society and the escalation of conflicts. In turn, fragmentation can undermine the credibility and legitimacy of the political system. Limited access to certain goods and services, caused by the unequal distribution of opportunities and privileges among the population, contributes to social division. Economic shocks in the form of a recession or stagnation of a national economy can reinforce differences and economic privileges between individuals and groups, thereby increasing the level of dissatisfaction and discontent to the point that it can provoke violent reactions. Declining living standards, youth unemployment, economic inequality, and lack of encouraging prospects certainly played a role in the events of January 2022 in Almaty

4.3. UM and well-being of cities in Kazakhstan

An important factor affecting the sustainability of cities is their level of conveniences. International practice shows that there is a consistency where human needs increase with economic growth (Proto and Rustichini 2015). Therefore, people’s satisfaction with their standard of living is achieved only when an increase in average income is accompanied by the satisfaction of their growing needs, including the level of conveniences in their place of residence (Easterlin 2001). Many researchers agree that the individual well-being of people depends largely on the physical, social and economic environment where they live (Roback 1982; Winters 2009; Oswald and Wu 2011; Glaeser et al. 2014; Winters and Li 2015; Chulanova 2024).

The level of provision of cities with basic infrastructure of conveniences by regions is presented in Table 6. The analysis of the level of conveniences in the housing stock in the Kazakhstan regions, as one of the important factors determining the quality of life, and the calculation of conveniences coefficients showed that the situation with the life support infrastructure of cities in the context of regions is not unambiguous. Outsiders are Turkestan, Akmola and Kyzylorda regions. The lowest indicators of hot water supply are in these regions, as well as in Shymkent city. The problem of central water supply in cities with potable water has not been completely solved yet. The level of provision of cities with central sewerage system is from 29% to 76% in 10 regions.

Table 6. Indicators of the level of provision of urban households with infrastructure by regions of the Republic of Kazakhstan in 2022 year, share.

Regions	Central water supply	Central hot water supply	Central heating	Network gas	Central sewerage	Garbage collection and disposal	Fixed Internet	Mobile Internet	К
Republic of Kazakhstan	0.983	0.65	0.802	0.59	0.812	0.935	0.556	0.889	0.78
Abay	0.928	0.439	0.757	0.015	0.764	0.966	0.527	1.0	0.67
Akmola	0.945	0.168	0.69	0.0	0.704	0.572	0.687	0.784	0.57
Aktobe	0.994	0.658	0.754	0.936	0.763	1.0	0.418	0.938	0.81
Almaty	1.0	0.366	0.464	0.735	0.491	0.74	0.33	1.0	0.64
Atyrau	1.0	0.573	0.611	0.997	0.618	0.938	0.563	0.652	0.74
West Kazakhstan	0.996	0.692	0.697	0.996	0.718	0.989	0.333	0.962	0.80
Zhambyl	0.918	0.76	0.776	0.902	0.833	0.84	0.392	0.905	0.79
Zhetysu	1.0	0.475	0.425	0.412	0.475	0.942	0.466	1.0	0.65
Karaganda	0.985	0.661	0.929	0.015	0.941	0.972	0.753	0.991	0.78
Kostanay	0.975	0.83	0.833	0.583	0.857	0.886	0.708	0.949	0.83
Kyzylorda	1.0	0.0	0.488	0.7	0.488	0.915	0.258	0.742	0.57
Mangistau	1.0	0.994	1.0	0.999	0.997	0.665	0.774	0.982	0.93
Pavlodar	0.96	0.972	0.972	0.0	0.972	0.96	1.0	0.972	0.85
North Kazakhstan	0.88	0.697	0.744	0.0	0.728	0.821	0.682	0.93	0.69
Turkestan	0.752	0.0	0.28	0.731	0.294	0.976	0.024	0.813	0.48
Ulytau	1.0	1.0	1.0	0.0	0.96	0.972	0.932	1.0	0.86
East Kazakhstan	0.98	0.852	0.866	0.015	0.866	0.956	0.66	0.939	0.77
Astana city	0.989	0.979	0.986	0.151	0.988	1.0	0.415	0.92	0.80
Almaty city	0.99	0.814	0.834	0.992	0.83	0.973	0.635	0.879	0.87
Shymkent city	0.985	0.038	0.789	0.942	0.819	0.841	0.347	0.632	0.67

Note - Compiled from data from the Bureau of National Statistics.

Major problems are observed with rubbish removal and utilisation in Akmola and Almaty regions. Meanwhile, to solve the issue of timely disposal of rubbish is of particular importance in densely populated urban areas, as it improves the environmental situation, prevents the spread of diseases and deterioration of health. This process is most organised in large cities of the country, such as Almaty, Astana, Shymkent, Karaganda. The highest current costs of environmental protection are in the industrial centres of the country (Atyrau, Aktobe, Pavlodar, Ust-Kamenogorsk), where there are large emissions of pollutants into the atmosphere. However, according to the Air Quality Index (AQI) under the data of national platform IQAir, Almaty and Atyrau are characterised by the most polluted atmospheric air (Table 7).

Table 7. The main indicators characterising the state of the environment in large cities of Kazakhstan in 2019.

City	Current costs for environmental protection, thousand tenge	Emissions of pollutants into the atmosphere, tons	Air quality index (AQI) and air pollution PM2.5	The volume of collected and transported municipal waste, tons	Number of enterprises and organisations for the collection and removal of municipal waste, units
Astana	1 678 200	65 100	77	No data	No data
Almaty	4 512 795	46 062	152	490 100	63
Shymkent		29 802	54	191 870	13
Aktau	2 576 800	12 400	5	No data	No data
Aktobe	24 811 608	30 272	33	122 804	No data
Atyrau	33 625 855	66 112	197	38 577	2
Karaganda	3 354 946	56 000	57	228 320	2
Kokshetau		10 100	59	24 645	5
Kostanay	663 443	16 999	73	104 554	2
Kyzylorda	1 975 626	16 499	18	29 766	16
Pavlodar	16 896 192	200 900	49	142 449	3
Petropavlovsk	3 382 746	44 852	36	56 748	16
Taldykorgan		5	38	26 769	6
Taraz		28 323	38	No data	No data
Turkestan	99 845	2 313	54	19 532	1
Uralsk	428 380	10 400	4	65 018	No data
Ust-Kamenogorsk	15 059 200	54 800	49	No data	No data

Air quality in cities is affected not only by pollutant emissions from industrial enterprises but also by the constant growth of vehicles and the use of stove heating in some residential neighbourhoods. There is no network gas in the 8 coldest regions. There is still a low level of central heating in such cities of Kazakhstan as Almaty, Zhetysu, Kyzylorda and Turkestan. Even if the use of alternative gas heat supply is assumed, the total supply of heat and gas networks in these regions does not cover the needs of the urban population in full. Thus, the problems of urban improvement remain urgent for Kazakhstan. Insufficient provision of housing, communal and engineering infrastructure in cities, its physical and moral deterioration reduce the quality of services provided. Besides, the timely reconstruction of utility networks is often hampered by the outstripping growth of tariffs in relation to the growth of actual incomes of the population, which gives rise to the indebtedness problem.

Despite the deterioration of the environmental situation in large cities and the fact that the development of urban infrastructure lags the population growth rate, the flow of resettlement of villagers to cities, especially large cities, remains high. The conditions and quality of life in large cities far exceed those in rural areas. The coefficients of comparative conveniences of urban and rural areas were calculated to assess the provision of the population’s needs in services (formula 2). Calculations show that the level of conveniences, availability of services of paramount importance (water supply, heat supply, sewerage, rubbish collection and disposal, etc.) is several times higher in Kazakhstani cities than in rural areas (Figure 4).

Figure 4. Comparative levels of provision households with life support services in urban and rural areas of the Republic of Kazakhstan in 2022.

Degradation of life support infrastructure in villages and small towns has become the most important factor of rural population migration into megacities. In Kazakhstan, rural migration is also driven by the need to improve living conditions. Therefore, it is important to assess the level of correspondence between the scale and growth rates of life support infrastructure in the country’s cities and the growth rates of the population with their increasing needs for services to determine the opportunities and risks to achieve sustainable development goals for megacities in Kazakhstan.

The exchange of resources between urban and rural areas deserves attention in the problem of metabolism. The average annual growth rate of urban population in Kazakhstan was 1.3%, and 5.6%, 2.7% respectively in the largest cities of Astana and Almaty. Rapid population growth in megacities has implications for urban metabolism. These problems are not only related to the lack of resources in megacities. There is a need to adapt the labour market, develop business, industry, and services, and create new jobs to accommodate population growth. The structure and scale of trade flows between urban and rural areas are changing. At least, the traditional exchange of goods created in the city for rural goods has been disrupted in Kazakhstan. There is a process of dispossession of land in rural areas. This situation is clearly showed in the declining share of the population with guaranteed land rights. This share almost halved from 7.11% to 4.36% from 2012 to 2021. This indicator fell in some regions to 1% decreasing by 8–12 times. For example, households produce about 50% of livestock production. It is difficult to create alternative supplies in a short time, as it involves search for external sources as well as nutrition traditions.

Since the destruction of factories and entire manufacturing industries in cities in the 1990s, many agricultural raw materials are not processed by urban enterprises. That is, cities have limited channels through which they can influence economic growth in rural areas. There is a predominantly urban-rural exchange of domestic food products and imported manufacturing products. The domestic urban economy does not provide more market opportunities for rural areas, their economic growth, and the sustainability of rural settlements because the economic exchange between them is distorted.

The calculated correlation and improvement coefficients confirm the hypothesis put forward by the authors about the increase in the dependence of urban metabolism factors, urban improvement level and ecology on the urbanisation level. The study also indicates the insufficient and uneven provision of Kazakhstani cities with housing, utilities and engineering infrastructure that requires regular monitoring of these processes and improvement of the management of urban systems to achieve sustainable development goals.

5. Conclusion and recommendations

The urban metabolism concept has contributed to the development of methods intended to assess urban resource flows and tools to manage and plan urban development with the purpose to achieve the objectives of sustainable development and urban resource efficiency. Three main aspects seem relevant to the urban metabolism problems in Kazakhstan with the growth of urbanisation and the largest cities. They are ecology, social problems, and infrastructure development.

Urban population growth, energy consumption and environmental pollution have direct relationships, although the strength of these relationships may be different. Despite the deterioration of the environment and air quality in the Kazakhstan megacities, their growth proceeds at a swifter rate than the urban population growth. However, growth in emissions, poor air quality is not a strong factor retaining migration to the largest cities.

The modern urbanisation period, the growth of megacities, and internal migration in Kazakhstan are currently associated with social factors, inequality in living standards, income, and employment opportunities to a greater extent. The rapid growth of the population in megacities in Kazakhstan leads to an increase in the demographic burden, especially in terms of land and water resources, an increase in problems with social infrastructure and, therefore, an increase in social tension. The rapid increase of population of megacities results in a decrease in the level of amenities. The country’s megacities have the highest official unemployment rate in the country, with an increase in the share of self-employed and precarious. The crime situation in large cities of the country has significantly worsened. It was concluded that a large concentration of production and population in large cities does not always mean an improvement in the quality of life of all segments of their population; more often in large cities the social and economic situation deteriorates, which requires increased attention to the regulation of urbanisation processes.

In rapid growth conditions, the Kazakhstan megacities are faced with the problem of a shortage of land, water, energy resources, housing, and transport infrastructure. The analysis reports a decline in the employment structure in megacities due to the growth of vulnerable employment and a population with unstable incomes and an unstable position in society. The economic structure in megapolises has a weak competitive position in foreign trade. Not enough jobs with decent and safe employment are established, persistent pockets of poverty are formed. They are associated with a high concentration of wholesale and street trade served by low-skilled workers from among rural migrants.

The rapid growth of megacities and growing inequality have contributed to the increased conflict potential in megacities. The calculated improvement coefficients confirm an insufficient and uneven provision of housing and engineering infrastructure to the Kazakhstan cities, and it requires to monitor these processes regularly and to ensure the sustainability of cities.

It is appropriate to expand the context of the urban metabolism problem. The exchange of resources between the city and the village is noteworthy in the metabolism problem. It is required to consider not only the internal input and output processes but how the metabolism of cities influences other territories, including rural ones, the nature of metabolic processes, economic growth, and the sustainability of rural settlements.

Growth in urbanisation should not be driven solely by the growth of large cities. Considering the spatial characteristics of Kazakhstan with its relatively low population density, the focus on the development of the largest cities will have strong consequences in the form of spatial-demographic and spatial-economic imbalances, deterioration in the quality of the economic space, its development, weakening of local centres and the strength of intraregional ties. Therefore, it is required in regional policy to create a new impetus for the development of small and medium-sized cities, changing their specialisation, economy, and functional purpose. Along with this, tools for the revitalisation of rural areas should become an important direction of regional policy.

To improve resource management in urban systems, it is recommended to monitor resource consumption and waste generation, as well as assess the level of provision of services to the population of each city in Kazakhstan. Based on the monitoring information, it is advisable to develop individual urban development plans with constant updating of target indicators, specified characteristics of the required resources for the stable functioning of urban systems and the vital activity of the population.

Policy of urbanisation due to a further increase of only large cities turned out to be unfounded, short-sighted, and very risky. The way out of the critical situation should be the development for each type of city or specific city of individual development strategies related to new technologies and digitalisation, service orientation of the economy, expansion of small and medium-sized businesses and considering all its strengths, weaknesses, and development opportunities. Strategic plans should provide for changes in the functions and sectoral structure of the city economy, and consider historical, resource, natural, climatic, political, mental, cultural, and other features. Urban policy should develop of medium and small cities with socially oriented urban planning and green areas.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research supported by the Committee of Science Ministry of Science and Higher Education of the Republic of Kazakhstan [Grant BR21882122], Sustainable development of natural-industry and socio-economic systems in the West Kazakhstan region in the context of green growth: comprehensive analysis, concept, forecast assessments, and scenarios.

Notes on contributors

Aizhan T. Tleuberdinova

Aizhan T. Tleuberdinova – Doctor of Economic Science, Associate Professor, Chief Researcher. Member of Academic Council of the Institute of Economics of the CS MSHE RK. More than 8 years of experience as a responsible executor and head of scientific projects. Awards “Best university teacher” (2008, 2014). Erasmus Mundus scholarship holder 2010, 2013, 2015.

Nailya K. Nurlanova

Nailya K. Nurlanova – Doctor of Economic Science, Professor. Scientific experience 49 years, and head of of scientific projects. Scientific supervisor of 23 doctors of science and PhD. Author of more than 420 scientific papers. Member of Academic Council of the Institute of Economics of the CS MSHE RK, Eurasian National University dissertations PhD Councils (Astana). Member of the editorial board of the journals: Economics and Finance’ (Uzbekistan), Journal of Distribution Science, East Asian Journal of Business Management (KODISA).

Farida G. Alzhanova

Farida G. Alzhanova - Doctor of Economic Science, Associate Professor, Chief Researcher, Advisor of research project. More than 20 years of experience as a responsible executive and head of scientific projects. Author more than 200 articles, Ch. Valikhanov Science Prize (2005), member of Academic Council of the Institute of Economics of the CS MSHE RK.

Bekmukhamed T. Kalmenov

Bekmukhamed T. Kalmenov - Master of Economics, PhD student of the Joint program of Al-Farabi KazNU and the Institute of Economics CS MSHE RK.