Simulation of Air Pollution in Almaty City under Adverse Weather Conditions

Zakarin, E.; Baklanov, Alexander; Balakay, L.; Dedova, Tatyana; Bostanbekov, Kairat

doi:10.3103/s1068373921020072

Cited by 9 publications

(6 citation statements)

References 12 publications

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“…This study is a continuation of previous work [23][24][25] on modeling complex atmospheric processes occurring in the air basin of the city of Almaty, Kazakhstan (43°15′ N 76°54′ E). Almaty is a major urban center with a population exceeding 2 million people.…”

Section: Introductionmentioning

confidence: 72%

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Investigating Stagnant Air Conditions in Almaty: A WRF Modeling Approach

Dedova,

Balakay,

Zakarin

et al. 2024

Atmosphere

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This study investigates stagnant atmospheric conditions in Almaty, Kazakhstan, a city nestled within a complex terrain. These conditions, characterized by weak local winds and inversion layers, trap pollutants within the city, particularly during winter. The Weather Research & Forecasting (WRF) model was employed to simulate atmospheric conditions using Local Climate Zone data. Verification of the model’s accuracy was achieved through comparisons with data from weather stations and the Landsat-9 satellite. The model successfully reproduced the observed daily temperature variations and weak winds during the testing period (13–23 January 2023). Comparisons with radiosonde data revealed good agreement for morning temperature profiles, while underestimating the complexity of the evening atmospheric structure. The analysis focused on key air quality factors, revealing cyclical patterns of ground-level and elevated inversions linked to mountain-valley circulation. The model effectively captured anabatic and katabatic flows. The study further examined the urban heat island (UHI) using a virtual rural method. The UHI exhibited daily variations in size and temperature, with heat transported by prevailing winds and katabatic flows. Statistical analysis of temperature and wind patterns under unfavorable synoptic situations revealed poor ventilation in Almaty. Data from three Januaries (2022/2023/2024) were used to create maps showing average daytime and nighttime air temperatures, wind speed, and frequency of calm winds.

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Section: Introductionmentioning

confidence: 72%

“…Based on previous work [23,25], in this study, the WRF model of version 4.3 was used, for which three nested domains, D1, D2 and D3, were established in the Lambert conformal conic projection. The domains have grid resolutions of 9 km, 3 km, and 1 km, respectively.…”

Section: Methodsmentioning

confidence: 99%

Investigating Stagnant Air Conditions in Almaty: A WRF Modeling Approach

Dedova,

Balakay,

Zakarin

et al. 2024

Atmosphere

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“…Energy production costs are also lower than the conventional system of generating electricity and heat separately. While there are other sources of air pollution in Almaty, combined heat and power plants still contribute significantly to the total PM 2.5 concentration [10]. In 2021, the CHPPs in Almaty accounted for about 30% of the total energy production in the city.…”

Section: Introductionmentioning

confidence: 99%

Assessing the Impact of Combined Heat and Power Plants (CHPPs) in Central Asia: A Case Study in Almaty for PM2.5 Simulations Using WRF-AERMOD and Ground Level Verification

Ogbuabia,

Guney,

Baimatova

et al. 2023

Atmosphere

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According to the World Health Organization, Kazakhstan is one of the most polluted countries in the world. PM2.5, a major air pollutant, is six times higher than the recommended value of 5 mg/m3. The government has implemented measures to reduce air pollution, such as introducing green energy-powered buses for public transportation, but the results have not been sufficient. Therefore, it is necessary to investigate the sources of PM2.5. This study involved simulating the Combined Heat and Power Plants (CHPPs) emissions in Almaty using AERMOD and WRF for two weeks in January 2021. Two scenarios were performed: controlled and uncontrolled. The results showed that if the control mechanism of the CHPP functions at maximum efficiency, the impact of the CHPP emissions on the total emission concentration will be negligible, which is about 6% on average. However, for uncontrolled CHPPs, the emissions will contribute from 30% to 39% on average to the total PM2.5 concentration when compared with data from US Embassy monitoring stations and public air quality monitoring network, which use Pms5003 PM2.5 sensors.

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“…Industrial processes in the East Kazakhstan region include a wide range of activities that lead to the emission of various harmful substances into the atmosphere [43]. The state of atmospheric air in the second city, Almaty, has been studied in many works [44][45][46][47][48][49]. It is believed that the main sources of air pollution in the city are vehicles, thermal power plants, industrial enterprises, as well as private houses with their own heating system.…”

Section: Introductionmentioning

confidence: 99%

A Combined Approach for Predicting the Distribution of Harmful Substances in the Atmosphere Based on Parameter Estimation and Machine Learning Algorithms

Madiyarov,

Temirbekov,

Alimbekova

et al. 2023

Computation

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This paper proposes a new approach to predicting the distribution of harmful substances in the atmosphere based on the combined use of the parameter estimation technique and machine learning algorithms. The essence of the proposed approach is based on the assumption that the concentration values predicted by machine learning algorithms at observation points can be used to refine the pollutant concentration field when solving a differential equation of the convection-diffusion-reaction type. This approach reduces to minimizing an objective functional on some admissible set by choosing the atmospheric turbulence coefficient. We consider two atmospheric turbulence models and restore its unknown parameters by using the limited-memory Broyden–Fletcher–Goldfarb–Shanno algorithm. Three ensemble machine learning algorithms are analyzed for the prediction of concentration values at observation points, and comparison of the predicted values with the measurement results is presented. The proposed approach has been tested on an example of two cities in the Republic of Kazakhstan. In addition, due to the lack of data on pollution sources and their intensities, an approach for identifying this information is presented.

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Simulation of Air Pollution in Almaty City under Adverse Weather Conditions

Cited by 9 publications

References 12 publications

Investigating Stagnant Air Conditions in Almaty: A WRF Modeling Approach

Investigating Stagnant Air Conditions in Almaty: A WRF Modeling Approach

Assessing the Impact of Combined Heat and Power Plants (CHPPs) in Central Asia: A Case Study in Almaty for PM2.5 Simulations Using WRF-AERMOD and Ground Level Verification

A Combined Approach for Predicting the Distribution of Harmful Substances in the Atmosphere Based on Parameter Estimation and Machine Learning Algorithms

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