Using a global database of contaminated sites, toxic hotspots in eight former Soviet countries were analyzed to identify the prevalence, types and sources of toxic pollution, as well as their associated potential public health impacts. For this analysis, polluted sites in Armenia, Azerbaijan, Kazakhstan, Kyrgyzstan, Russia, Tajikistan, Ukraine, and Uzbekistan were compiled and analyzed. The levels of contamination of seven key pollutants were assessed in each country. 424 contaminated sites were identified using data from Blacksmith Institute. Pesticides, lead (Pb), radioactive metals, arsenic (As), mercury (Hg), chromium (Cr), and cadmium (Cd) were the most commonly identified key pollutants. Collectively, these sites pose health risks to an estimated 6.2 million residents. The existing data on toxic hotspots in former Soviet countries likely captures only a small percentage of actual contaminated sites, but suggests potentially severe public health consequences. Additional assessments are needed to understand the risks posed by toxic pollution in the region.

Thorough knowledge of hydrochemical characteristics and trace element concentrations in surface waters is crucial for protection of this resource, especially in arid regions. Uzbekistan lies in central, arid Central Asia, and is experiencing severe water scarcity as a consequence of warming climate and accelerated human impacts. Fifty-five surface water samples were collected from the Amu Darya Basin of Uzbekistan (ADBU) and measured for relevant variables, to determine hydrochemical characteristics and evaluate water quality. River water samples from the middle reach and Amu Darya Delta (ADD) were dominantly HCO₃–Ca and SO₄–Ca·Mg types, respectively, whereas water samples collected near the former shoreline and sewage outlets in the ADD were predominantly Cl–Ca·Mg and Cl–Na types, consistent with the distribution of sites that display high concentrations of trace elements and are seriously affected by human activities. Principal component analysis indicated that Pb and Cd in surface waters of the ADBU had industrial origins. Local agricultural activities are thought to have contributed to the concentrations of NO₃, Zn, Ni, Hg, and Mn, through pesticide and fertilizer applications, and concentrations of Cu, Cr, As, and Co are controlled by mixed natural and anthropogenic sources. Water quality and health risk assessments indicated that unsuitable drinking waters are distributed mainly near the former shoreline and sewage outlets in the ADD, making human health risks in these areas high.

Climate change and health are inextricably linked, especially the role of ambient temperature. This study aimed to analyze the non-communicable disease (NCD) burden attributable to low temperature globally, regionally, and temporally using data from the Global Burden of Disease (GBD) study 2019. Globally, in 2019, low temperature was responsible for 5.42% DALY and 7.18% death of NCDs, representing the age-standardized disability-adjusted life years (DALY) and death rates (per 100,000 population) of 359.6 (95% uncertainty intervals (UI): 306.09, 416.88) and 21.36 (95% UI:18.26, 24.74). Ischemic heart disease was the first leading cause of DALY and death resulting from low temperature, followed by stroke. However, age-standardized DALY and death rates attributable to low temperature have exhibited wide variability across regions, with the highest in Central Asia and Eastern Europe and the lowest in Caribbean and Western sub-Saharan Africa. During the study period (1990–2019), there has been a significant decrease in the burden of NCDs attributable to low temperature, but progress has been uneven across countries, whereas nations exhibiting high sociodemographic index (SDI) declined more significantly compared with low SDI nations. Notably, three nations, including Uzbekistan, Tajikistan, and Lesotho, had the maximum NCDs burden attributed to low temperature and displayed an upward trend. In conclusion, ambient low temperature contributes to substantial NCD burden with notable geographical variations.

Saline areas are progressively increasing in irrigated lands of the Aral Sea Basin and this obstructs intensive agricultural development and food security in this region. Such circumstances, leading to the expansion of salt-affected areas, are assumed to become climate change, rising of groundwater levels and its mineralizations, poor functioning of the collector-drainage system, and insufficient compliance with agro-technical requirements. These drivers, in turn, lead to the withdrawal of arable land for agricultural purposes and a significant drop in crop yields. Regarding Uzbekistan, this research on soil salinity assessment was conducted in the irrigated areas of the Sirdarya province by analyzing raw data derived from traditional methods from 2000 to 2015, as well as from 2016 to 2019, using the integrated traditional and geographic information systems (GIS)–based methods. Soil salinity maps of the Sirdarya province were created to investigate spatial and temporal changes in soil salinity using the inverse distance weighting (IDW) interpolation method based on the results of field survey and laboratory studies. The results of this research revealed that the IDW interpolation method had a great potential and accuracy to map longitudinal changes in salt-affected irrigated areas. Moreover, it was determined that soil salinity highly depends on local terrain conditions and there is a weak dependence on climatic factors. The main findings of this research advocate agricultural specialists and local farmers to get distinctly encouraged to take the following measures to address the actual soil salinity state in the irrigated areas of the province: targeted and economic use of irrigation water; existing drainage networks are in perfect working condition and monitoring their full effective operation; and, lastly, accelerating the integration of innovative GIS technologies into traditional methods.

This article investigates the long-run and causal linkages between economic growth, CO₂ emissions, renewable and non-renewable (fossil fuels) energy consumption, the Composite Trade Intensity (CTI) as a proxy for trade openness, and the Chinn-Ito index as a proxy for financial openness for a panel of the Commonwealth of Independent States (CIS) region including Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, Kyrgyzstan, Moldova, Russia, Tajikistan, Turkmenistan, Ukraine, and Uzbekistan over the period of 1992–2015. It is the first time that CTI and the Chinn-Ito indexes are used in an economic-pollution model. Employing three panel unit root tests, panel cointegration estimation methods (DOLS and FMOLS), and two panel causality tests, the main empirical results provided evidence for the bidirectional long-run relationship between all the variables in all 12 sampled countries except for economic growth-renewable energy use linkage. The findings of causality tests indicated that there is a unidirectional short-run panel causality running from economic growth, financial openness, and trade openness to CO₂ emissions and from fossil fuel energy consumption to renewable energy use.

The Aydar-Arnasay Lake System (AALS) is located in the middle of the Syrdarya River, to the south of the Chardara Reservoir, and in Jizakh and Navoi provinces of the Republic of Uzbekistan, adjacent to the low plain of South Mirzachul. Currently, the AALS has a significant impact on the regional ecosystem and socio-economic conditions of the region. Studying and evaluating the AALS hydrology, the water volume, surface area, and variability of water levels altogether play an important role in the development of fisheries and ecotourism in the region. However, in the past studies, the dynamic changes in the volume, area, and water levels of the AALS have not been investigated through up-to-the-date geo-information systems (GIS), requiring additional research to formulate a proper methodology considering the potential aspects of GIS. Therefore, this paper aims at analyzing the dynamics of changes in the water level, surface area, and water volume of the AALS by using GIS technologies within 1993–2017 years. During the period from 1993 to 2006, the water level and the surface area of the AALS steeply increased and remained stable with negligible positive and negative fluctuations in the rest of the experimental years. These findings were successfully tested and validated by ANOVA, indicating an exceptionally low F-significance of 0.0008. According to the AALS’s water volume dynamics, we investigated here the role of two factors: anthropogenic—the outflow water discharge from the reservoir located in the neighboring country; and natural—the amount of perennial precipitation. Consequently, we ascertained that the role of precipitation as a natural driving factor in expansion is majorly less than the outflow water from the reservoir, despite having a gradual increase in the perennial precipitation trend. As we assume that the hydrological characteristics of the AALS are strongly dependent on air temperature and the amount of precipitation due to the extreme restriction of outflow water discharge from the reservoir, thus the establishment of proper GIS-tracking and monitoring methodology is recommended to early warn the potential minor changes which could become severe in the near future.

Based on the environmental Kuznets curve (EKC) hypothesis, the aim of this paper is to examine the relationships among per capita CO₂ emissions, per capita real GDP, per capita renewable energy consumption, and urbanization in a panel of five Central Asian countries (Kazakhstan, Kyrgyz Republic, Tajikistan, Turkmenistan, and Uzbekistan) from 1992 to 2013. For robustness checking, three estimator techniques reveal no evidence of inverted U-shape EKC consistently. Moreover, renewable energy consumption plays negative impact on emissions, while urbanization plays positive, significantly. The findings of heterogeneous panel causality suggest that there are bidirectional causalities; each other expect no causality from emissions to renewable energy. Finally, some implications, such as developing a small renewable energy project and sustainable urbanization and strengthening in-regional and out-regional cooperation, are given in this region.

After political sovereignty, Uzbekistan’s industry is growing fast. However, no investigation was performed so far, to evaluate whether an environmental risk, associated with the industry, is also increasing. Our aim was to investigate whether the distance from factories, as a surrogate measurement for environmental exposure to community, has any influence on some health outcomes in communities of Uzbekistan. For this first investigation, we analyzed prevalence of congenital diseases, infant mortality, and incidence rates of lung cancer, as examples for diseases associated with environmental factors. As crude measurement for the association, we used correlation and regression analysis with the distance to the next factory or plant as explanatory variable. A regression analysis demonstrated an association between the three outcome variables, with the strongest negative correlation (r = − 0.48) and the highest determination power (r² = 0.23) for congenital diseases’ prevalence. For infant mortality and lung cancer incidence, descriptions and analyses demonstrated lower negative correlation of them with the distance and a lower predictive power of linear models. So, closer distance of the community to specific industrial plants can be considered an indirect factor of higher prevalence of congenital diseases in those communities. Prospective research is needed to further investigate whether the association between birth defects in a neighborhood of industrial plants is causal or due to confounding factors. A policy should consider a degree of known factors distribution in an environment and perform effective prevention of congenital diseases, in close communities.