Browsing by Author "Lodoysamba Sereeter"

Now showing 1 - 5 of 5
  • Thumbnail Image
    Item
    Assessment of ulaanbaatar air quality based on monitoring stations data
    (German Mongolian Institute for Resouce and Technology, 2018-08-10) Anu-Ujin Sarantuya; Lodoysamba Sereeter; Guyen Battuvshin
    This thesis assesses the air pollution data from twelve monitoring stations in Ulaanbaatar (UB). The measurements cover major six pollutants including Particulate Matters (PM10- all particles <10 µm and PM2.5- all particles <2.5 µm), Sulfur dioxide (SO2), Nitrogen dioxide (NO2), Carbon monoxide (CO) and Ozone (O3). The data obtained from open-source database named OpenAQ. Briefly, there are overall 15 monitoring stations in Ulaanbaatar, but 12 of them are connected to the OpenAQ source and each station’s data collected by 30-minutes range.
  • Thumbnail Image
    Item
    Chemical analysis and source apportionment of air pollutants in a remote area of ulaanbaatar, mongolia
    (German Mongolian Institute for Resouce and Technology, 2024-05-27) Sunderiya Ganzorig; Lodoysamba Sereeter; Gantuya Ganbat; Suriya
    Air pollution in Mongolia, particularly in Ulaanbaatar and remote areas, has been an urgent concern due to elevated levels of particulate matter (PM) and other pollutants. This thesis investigates the chemical composition and source apportionment of air pollutants in Nalaikh. Air sampling was conducted using high-volume air samplers and filters analyzed via inductively coupled plasma mass spectrometry (ICP-MS) and ion chromatography (IC). The Positive Matrix Factorization (PMF) model identified three major sources: crustal matter, coal combustion, and an industrial source (factor 1). Crustal matter, comprising elements like Ca and Al, accounted for 49.9% of the total pollution due to frequent dust storms and resuspension of soil dust. Coal combustion contributed 36.6%, marked by high levels of sulfur (S) and lead (Pb) due to extensive coal usage for heating. The industrial source, which made up 13.5% of the pollution, was identified based on elevated levels of Cr, Ni, and Cu, although no significant industrial activity exists in Nalaikh. There is a lack of comprehensive research on air pollution in Ulaanbaatar's remote areas like Nalaikh. This study will help address critical gaps in understanding pollution sources and composition in the region, emphasizing the necessity of emission control policies to protect both human and environmental health.
  • No Thumbnail Available
    Item
    Embedded Generative Air Pollution Model with Variational Autoencoder and Environmental Factor Effect in Ulaanbaatar City
    (2022) Bulgansaikhan Baldorj; Munkherdene Tsagaan; Lodoysamba Sereeter; Amanjol Bulkhbai
    Air pollution is one of the most pressing modern-day issues in cities around the world. However, most cities have adopted air quality measurement devices that only measure the past pollution levels without paying attention to the influencing factors. To obtain preliminary pollution information with regard to environmental factors, we developed a variational autoencoder and feedforward neural network-based embedded generative model to examine the relationship between air quality and the effects of environmental factors. In the model, actual SO2, NO2, PM2.5, PM10, and CO measurements from 2016 to 2020 were used, which were assembled from 15 differently located ground monitoring stations in Ulaanbaatar city. A wide range of weather and fuel measurements were used as the data for the influencing factors, and were collected over the same period as the air pollution data were recorded. The prediction results concerned all measurement stations, and the results were visualized as a spatial–temporal distribution of pollution and the performance of individual stations. A cross-validated R 2 was used to estimate the entire pollution distribution through the regions as SO2: 0.81, PM2.5: 0.76, PM10: 0.89, and CO: 0.83. Pearson’s chi-squared tests were used for assessing each measurement station, and the contingency tables represent a high correlation between the actual and model results. The model can be applied to perform specific analysis of the interdependencies between pollution and environmental factors, and the performance of the model improves with long-range data.
  • No Thumbnail Available
    Item
    Pollution reduction potential by implementing electrostatic dust precipitators on mongolian small-scale stoves (a pilot study in Ulanbaatar)
    (2020) Daniel Karthe; Tim Hafer; Byambasuren Battulga; Lodoysamba Sereeter; Gunther Stehr
    The Mongolian capital of Ulaanbaatarexperiences some of the world’s worst air pollution during the winter months, most of it being caused by small coal- and wood-fired stoves which are used for heating and cooking purposes in peri-urban parts of the city. A recent pilot study in Songinokhairkhan District of Ulaanbaatar City evaluated the feasibility of electrostatic dust precipitators (ESP) for reducing particulate matter (PM) emissions from small stoves. This paper focuses on the pollution reduction potentials that would result from a large-scale implementation of ESPs. Using a locally developed low- cost ESP system (which is currently in the process of further improvement), reduction rates ranging between 10 to 50% of the PM emissions (depending on the fuel and combustion conditions) could be achieved. Fitting all or at least a major fraction of the small stoves with such ESPs could reduce PM emissions by an order of several thousand tons per heating season for the whole city. The avoided particle emissions would simultaneously prevent atmospheric pollution by various trace metals and metalloids including As, Cd, Pb and Zn, which are known to be major soil and water pollutants locally, and several other toxic substances. However, this also means that safe disposal strategies must be developed for the fly ash precipitated during ESP operation.
  • Thumbnail Image
    Item
    Road dust suppression using lignosulfonate on unpaved road
    (German Mongolian Institute for Resouce and Technology, 2021-04-30) Nominjargal Otgonjargal; Baljinnyam Erdenetsoo; Lodoysamba Sereeter
    The term dust initially cited naturally to particles of earth or other matter small enough to be lifted and carried by wind. During the late Middle Ages of the post-classical era, dust claimed to be medical significant. The first English discourse on asthma, Sir John Floyer (1649-1734) described, dust as one of the environmental cause of asthma attacks. It was the beginning of Industrial Revolution that dust identified as a hazardous matter in the modern world. Since the Industrial Revolution took place, factories were built, agriculture, glass making, and textile manufacturing which had all undergone changes. The most popular invention during that time was steam-engine, which is more effective than men or animals that helped to power Industrial Revolution. The steam engine used hot steam from boiling water by burning coal. It created a huge demand of coal to power the inventions such as steam engine. As the coal demand increases, miners were forced to go deeper to find more coal. The tunnel was narrow and suffocating, which miners had to work on their knees and had not wearing proper, safe clothes. During the extraction, they contacted with dangerous gases that existed naturally underground such as methane. Many miners’ dead because of the explosions called: Fire damp, which causes thick clouds of coal dust and many more.