To elucidate the molecular composition and sources of organic aerosols in Central Asia, carbonaceous compounds, major ions, and 15 organic molecular tracers of total suspended particulates (TSP) were analyzed from September 2018 to August 2019 in Dushanbe, Tajikistan. Extremely high TSP concentrations (annual mean ± std: 211 ± 131 μg m⁻³) were observed, particularly during summer (seasonal mean ± std: 333 ± 183 μg m⁻³). Organic carbon (OC: 11.9 ± 7.0 μg m⁻³) and elemental carbon (EC: 5.1 ± 2.2 μg m⁻³) exhibited distinct seasonal variations from TSP, with the highest values occurring in winter. A high concentration of Ca²⁺ was observed (11.9 ± 9.2 μg m⁻³), accounting for 50.8% of the total ions and reflecting the considerable influence of dust on aerosols. Among the measured organic molecular tracers, levoglucosan was the predominant compound (632 ± 770 ng m⁻³), and its concentration correlated significantly with OC and EC during the study period. These findings highlight biomass burning (BB) as an important contributor to the particulate air pollution in Dushanbe. High ratios of levoglucosan to mannosan, and syringic acid to vanillic acid suggest that mixed hardwood and herbaceous plants were the main burning materials in the area, with softwood being a minor one. According to the diagnostic tracer ratio, OC derived from BB constituted a large fraction of the primary OC (POC) in ambient aerosols, accounting for an annual mean of nearly 30% and reaching 63% in winter. The annual contribution of fungal spores to POC was 10%, with a maximum of 16% in spring. Measurements of plant debris, accounting for 3% of POC, divulged that these have the same variation as fungal spores.

This paper presents the results of the study on columnar aerosol optical and physical properties and radiative effects directly observed over Dushanbe, the capital city of Tajikistan, a NASA AERONET site (equipped with a CIMEL sunphotometer) in Central Asia. The average aerosol optical depth (AOD) and Ångström exponent (AE) during the observation period from July 2010 to April 2018 were found to be 0.28 ± 0.20 and 0.82 ± 0.40, respectively. The highest seasonal AOD (0.32 ± 0.24), accompanied by the lowest average AE (0.61 ± 0.25) and fine-mode fraction in AOD (0.39), was observed during summer due to the influence of coarse particles like dust from arid regions. Fine particles were found in significant amounts during winter. The ‘mixed aerosol’ was identified as the dominant aerosol type with presence of ‘dust aerosol’ during summer and autumn seasons. Aerosol properties like volume size distribution, single scattering albedo, asymmetry parameter and refractive index suggested the influence of coarse particles (during summer and autumn). Most of the air masses reaching this site transported local and regional emissions, including from beyond Central Asia, explaining the presence of various aerosol types in Dushanbe’s atmosphere. The seasonal aerosol radiative forcing efficiency (ARFE) in the atmosphere was found high (>100 Wm⁻²) and consistent throughout the year. Consequently, this resulted in similar seasonally coherent high atmospheric solar heating rate (HR) of 1.5 K day⁻¹ during summer-autumn-winter, and ca. 0.9 K day⁻¹ during spring season. High ARFE and HR values indicate that atmospheric aerosols could exert significant implications to regional air quality, climate and cryosphere over the central Asian region and downwind Tianshan and Himalaya-Tibetan Plateau mountain regions with sensitive ecosystems.

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.

Nitrogen dioxide (NO₂) is one of the main air pollutants, formed due to both natural and anthropogenic processes, which has a significant negative impact on human health. The COVID-19 pandemic has prompted countries to take various measures, including social distancing or stay-at-home orders. This study analyzes the impact of COVID-19 lockdown measures on nitrogen dioxide (NO₂) changes in Central Asian countries. Data from TROPOspheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor satellite, as well as meteorological data, make it possible to assess changes in NO₂ concentration in countries and major cities in the region. In particular, the obtained satellite data show a decreased tropospheric column of NO₂. Its decrease during the lockdown (March 19–April 14) ranged from − 5.1% (Tajikistan) to − 11.6% (Turkmenistan). Based on the obtained results, it can be concluded that limitations in anthropogenic activities have led to improvements in air quality. The possible influence of meteorology is not assessed in this study, and the implied uncertainties cannot be quantified. In this way, the level of air pollution is expected to decrease as long as partial or complete lockdown continues.

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.

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.

A combined chemical and biological analysis of samples from a major obsolete pesticide and persistent organic pollutant (POP) dumpsite in Northern Tajikistan was carried out. The chemical analytical screening focused on a range of prioritized compounds and compounds known to be present locally. Since chemical analytics does not allow measurements of hazards in complex mixtures, we tested the use of a novel effect-based approach using a panel of quantitative high-throughput CALUX reporter assays measuring distinct biological effects relevant in hazard assessment. Assays were included for assessing effects related to estrogen, androgen, and progestin signaling, aryl hydrocarbon receptor-mediated signaling, AP1 signaling, genotoxicity, oxidative stress, chemical hypoxia, and ER stress. With this panel of assays, we first quantified the biological activities of the individual chemicals measured in chemical analytics. Next, we calculated the expected sum activity by these chemicals in the samples of the pesticide dump site and compared the results with the measured CALUX bioactivity of the total extracts of these samples. The results showed that particularly endocrine disruption-related effects were common among the samples. This was consistent with the toxicological profiles of the individual chemicals that dominated these samples. However, large discrepancies between chemical and biological analysis were found in a sample from a burn place present in this site, with biological activities that could not be explained by chemical analysis. This is likely to be caused by toxic combustion products or by spills of compounds that were not targeted in the chemical analysis.

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.