Nexus between Life Expectancy, CO2 Emissions, Economic Development, Water, and Agriculture in Aral Sea Basin: Empirical Assessment

By inergency On Mar 23, 2024

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1. Introduction

Access to clean water, green energy, and food are essential to ensure life expectancy and well-being. Sustainable access to and management of these resources is a foundation for long-term economic growth and ecological sustainability. A growing number of scholars have focused more on the concepts of life expectancy, environmental well-being, and the water–energy–food nexus in response to the pressing need for the efficient and balanced use of these limited resources. Indeed, the scientific community has focused particularly on the Aral Sea basin as a glaring illustration of ecological disasters caused by human activity [1]. One of the most notorious ecological disasters in history, the destruction of the Aral Sea area directly affects life expectancy in eight countries that make up the Aral Sea basin: Iran, Uzbekistan, Kazakhstan, Kyrgyz Republic, Tajikistan, Afghanistan, Turkmenistan, and Uzbekistan [2].

The United Nations defines that excessive water use is a reason for environmental catastrophe in the Aral Sea Basin (ASB) [3], where water resources are shared by the five major riparian countries of Central Asia (Uzbekistan, Turkmenistan, Tajikistan, Kazakhstan, and Kyrgyzstan), mismanagement of water resources and ineffective irrigation systems are to blame for the Aral Sea disaster [4]. The two most important resources for producing food are land and water, and they are closely related. Climate change, population increase, and increased irrigation are endangering the basin’s ability to sustain development [5].

Over the last 10,000 years, there have been several water level drops and subsequent recoveries in the Aral Sea prior to the current recession [6,7]. Since 1960, the Amu Darya and Syr Darya, the Aral’s two tributaries, have dried up and suffered significant damage to their deltas due to the unsustainable expansion of irrigation. This has caused the Aral to rapidly desiccate and salinate [8]. The imbalance of shared water resources available to Central Asian countries makes the Aral Sea Basin water resource system one of the most complex networks in the world. Water governance in the basin is challenging due to geopolitical concerns among these nations. To support energy production, economic expansion, and food security, each has its own national water policy [9,10]. There has been a significant change in the Aral Sea region’s ecological state [11]. It has caused the climate in the area to change, irrigated soils to turn into deserts, deterioration of surface and subsurface water quality, reduction of water available for domestic and agricultural needs, loss of Aral Sea fishing and transportation importance, and a host of other issues that have ultimately put the health of current and future generations at risk [12,13]. Due to the collapse of the local fishing industries, a large number of people have moved to the irrigation sector, which, for decades, has been the only industry sector that has consistently grown [14,15]. In the former Vozrozhdeniye Peninsula in the Aral Sea, there was even a biowarfare weapons test site during the Soviet era [16]. The Aral Sea’s severe desiccation accelerated the region’s desertification processes and resulted in the formation of the Aralkum, a new desert on the dried-out sea floor [17].

With the aforementioned context in mind, this study aimed to establish the relationship between life expectancy at birth and the basic indicators of socioeconomic development. The novelty of the study is to investigate the potential integration of “life expectancy” factors into policies pertaining to carbon dioxide (CO₂) emissions and water productivity in Aral Sea basin countries. The objective of the research is to examine the dynamic relationship between life expectancy, environmental degradation, economic development, water, and agriculture. In this regard, we set out to answer the following two research questions: (1) In the Aral Sea region, are CO₂ emissions contributing to a diminished life expectancy? (2) Does water scarcity contribute to a reduction in the region’s population’s life expectancy? As far as our understanding extends, there has been no single research that has specifically examined this matter. By providing answers to these two significant questions, the current research aims to provide policy recommendations for long-term sustainable development.

3. Methodology

Current theories suggest that the increase in life expectancy positively impacts economic growth by enhancing investments in human capital via enhancements in health. A prolonged lifespan enhances the desire to gain information by extending the time period in which the benefits of education may be realized. Further, Ref. [62] observes that investments in skill capital should decrease with age as the remaining period over which benefits can be accrued decreases, while investments in health tend to increase with age. Therefore, the conceptual framework of this research is rooted in the human capital approach [62], which highlights the significance of both health and education as key drivers of human growth [63]. Along these lines, Ref. [64] established the healthcare concept, in which he saw health as a long-term asset that can be enhanced via investment despite its depreciation with age [65]. Therefore, investing in health status encompasses several factors, such as leveraging the benefits of globalization, using electricity, ICT, financial growth, and quality of education. In this study, prior studies primarily provide the empirical basis for variable selection. Proceeding on with the research [66,67,68,69], the average life expectancy at birth is now considered an accurate gauge of health conditions. The present study employs a framework proposed by [70,71,72] for empirical estimates.

${l e x}_{i t} = f ({c o}_{2 i t}, {h e a l t h}_{i t}, {g d p}_{i t}, {w a t e r}_{i t}, {a g r}_{i t}, {u r b}_{i t}, {e n g}_{i t}, {r e}_{i t}, {h c}_{i t})$

(1)

In Equation (1), the variable “lex” represents life expectancy at birth and serves as an indicator of health status. The variable “co₂” represents carbon dioxide emissions. “health” refers to the amount of money spent on the health sector as a proportion of the GDP. “gdp” represents the overall economic growth of a country. “water” refers to water productivity, while “agr” represents the value added in the agriculture sector. “urb” represents the urbanization rate, which is measured by the urban population. “eng” refers to the overall energy consumption, while “re” represents the proportion of renewable energy consumed in relation to the entire amount of energy utilized. “hc” represents the human capital, which is proxied by primary school enrollment percentage (gross).

For the purpose of this research, countries such as Uzbekistan, Tajikistan, Turkmenistan, Afghanistan, Iran, and Kazakhstan have been considered at various points in time between the years 2002 and 2020 (Table 1).

By changing Equation (1) to its natural logarithmic format, we may reduce heteroskedasticity among the variables and do direct elasticity-based comparisons. So, the variables under the study have been converted to logarithmic form to get precise results:

$\begin{array}{c} {l n l e x}_{i t} = α + β_{1} {l n c o}_{2 i t} + β_{2} {l n h e a l t h}_{i t} + β_{3} {l n g d p}_{i t} + β_{4} {l n w a t e r}_{i t} + β_{5} {l n a g r}_{i t} \\ + β_{6} {l n u r b}_{i t} + β_{7} {l n e n g}_{i t} + β_{8} {l n r e}_{i t} + β_{9} {l n h c}_{i t} + ε_{i t} \end{array}$

(2)

in which variables and their long-run elasticities are represented by $β_{1}$ , $β_{2}$ , $β_{4}$ , $β_{4}$ , $β_{5}$ , $β_{6}$ , $β_{7}$ , $β_{8}$ , and $β_{9}$ , respectively; $ε$ denotes the error term; $i$ is the county; $t$ denotes the period. In the present research, panel data spanning the years 2002 to 2020 has been applied for empirical estimation purposes. The World Development Indicators database maintained by the World Bank provides all of the acquired data.

Table 2 demonstrates the statistical characteristics of the variables that are included in the model. The chosen variables (life expectancy, CO₂ emissions, healthcare expenditure, Gross Domestic Product, annual freshwater withdrawal, arable land, urbanization, and energy consumption) are important parameters to show socioeconomic aspects of well-being and livelihood in the Aral Sea basin. The presented data table indicates that the arithmetic mean and median measurements of the complete variable being examined fall within the scope of the highest and lowest recorded values. The mean values of LIFE, CO₂, HEALTH, GDP, WATER, AGR, URB, ENERGY, and RNEW are 4.22, 0.86, 0.43, 24.21, 0.29, 2.68, 3.73, 9.46, and 1.18. Accordingly, a remarkable amount of standard deviation is shown for each of the variables investigated in this research, which are as follows: 0.06, 1.53, 0.63, 1.53, 0.95, 0.62, 0.37, 1.40, and 2.20 for LIFE, CO₂, HEALTH, GDP, WATER, AGR, URB, ENERGY, and RNEW, respectively. There is just a small amount of informational dispersion from each variable’s mean value, as measured by their standard deviations.

In order to assess the correlation between variables, the Pearson correlation coefficient has been applied for matrix correlation, which is displayed in Table 3. According to the findings, there exists a positive correlation between the dependent variable (lnlex) and the independent variables lnco₂ (0.7341), lnhealth (0.8072), lngdp (0.5274), lnwater (0.5734), lnurb (0.7513), lneng (0.8516), and lnhc(0.2319). Based on these results, it can be inferred that there is a significant and favorable association between the variables. Conversely, an inverse correlation was observed between the dependent variable (lnlex) and the independent variables lnagr (−0.5195) and lnre (−0.4843).

6. Conclusions

The majority of the existing studies recommend that all Aral Sea basin countries should minimize water pressure, mostly resulting from the agriculture sector. Considering climatic changes and negative environmental changes happening in the deserts of the dried Aral Sea, more green growth strategies should be supported, both financially and technically. The increasing population of the Aral Sea basin can be directed to less water-dependent industries such as tourism, IT, and other soft industries that can generate even more revenue compared with agriculture.

The present research has examined the impact of CO₂ emissions, health spending, GDP, water usage, agricultural output, urbanization, renewable and non-renewable energy consumption, and the role of schooling on life expectancy at birth in the Aral Sea region. These outcomes might be related to outdated public infrastructure inherited from the Soviet period and environmental degradation in the Aral Sea basin. This research utilized data from the years 2002 to 2020 and employed various econometric approaches, including FMOLS, DOLS, and Driscoll–Kraay. The outcomes of the study reveal that health spending, GDP, water, agriculture output, energy consumption, and education rate have a positive impact on life expectancy, but CO₂ emissions have a negative impact on life expectancy. The most important policy takeaway from this study is the need to develop and implement comprehensive policies that take into account health spending, GDP, water, agricultural output, energy consumption, and education level in order to ensure health status. Furthermore, we advocate several policies in accordance with the results of the research:

Optimize the water management strategy and facilities: Formulate an integrated water management plan to enhance the region’s environmental position while ensuring an appropriate usage of its water resources. Furthermore, the authorities of the region ought to undertake a comprehensive and progressive rebuilding of water management facilities, together with broad adoption of water-saving technology and decreasing sewage, to accelerate progress.

Enhance Healthcare Investment: Authorities have to give precedence to the allocation of supplementary government resources in order to enhance the health system and broaden the availability of medical treatment to all individuals. Authorities have the ability to allocate a greater portion of the national budget to the healthcare industry. Another way to improve healthcare funding is through the establishment or expansion of health insurance schemes, which pool resources like premiums and government payments.

Addressing and reducing CO₂ emissions: Elevated levels of CO₂ emissions have a detrimental impact on life expectancy. CO₂ emissions have the potential to cause air pollution and poison the ecosystem. Individuals may have a range of illnesses pertaining to the cardiovascular and respiratory systems, which might reduce their lifespan, necessitating efforts to mitigate carbon dioxide emissions. Governments endeavor to incorporate ecologically sustainable practices across all sectors to enhance the overall well-being of individuals.

Accelerated economic growth: Increased economic growth positively impacts life expectancy. The presence of economic growth enables the establishment of advanced medical facilities such as state-of-the-art hospitals, complex medical equipment, and the development of effective drugs inside a country. Hence, implementing an effective strategy for promoting economic growth is crucial in order to enhance the life expectancy of individuals.

Strategic urban development: Urban development increases life expectancy. Structured urbanization provides individuals with health-related advantages such as minimal pollution, a lush landscape, fresh water, suitable sanitation facilities, sufficient medical facilities, and efficient medical services. Hence, it is imperative to implement urbanization policies that are both dynamic and health-oriented to guarantee a longer lifespan for individuals.

Enhancing Education: Education has a positive impact on lifespan by promoting greater health consciousness and facilitating the maintenance of a healthy lifestyle. Acquiring knowledge and receiving a comprehensive education empower individuals to comprehend the norms and regulations pertaining to health. Therefore, it is imperative to guarantee high-quality education for everyone to protect long-term sustainability.

Similar to any other study, the present investigation is not exempt from shortcomings. Due to insufficient data, we were unable to incorporate additional factors that influence well-being, such as calorie consumption, healthcare accessibility, lifestyle choices, criminal activity, and bribery levels. It is advised that future study efforts include elements that include greater panel regions.

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