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Mandakh N.,Mongolian Academy of science | Tsogtbaatar J.,Mongolian Academy of science | Dash D.,Mongolian Academy of science | Khudulmur S.,National Agency for Meteorology and Environmental Monitoring
Journal of Geographical Sciences | Year: 2016

Wind erosion is a major contributor to land degradation and desertification. According to the Global Assessment of Human Induced Soil Degradation, the dryland territories of Mongolia are significantly affected by wind erosion. We used the wind erosion equation model in an ArcGIS environment to evaluate wind erosion across Mongolia. The individual factors of the wind erosion equation were parameterized using the following datasets: (a) monthly climatic data from 45 meteorological stations; (b) 16-day composites of MODIS Normalized Difference Vegetation Index data; (c) a SRTM DEM with a 90 m spatial resolution; and (d) the soil map of Mongolia. The results revealed the significant influence of aridity on wind erosion. The desert and semi-desert ecosystems were more vulnerable to wind erosion, hence more affected. The map of wind erosion revealed three major wind erosion regions where the maximum soil loss of 15–27 t/(hm2∙a) was observed. In general, the wind erosion potentials for the entire country of Mongolia are 15–27 t/(hm2∙a) in the deserts and semi-deserts, 10–15 t/(hm2∙a) in the dry steppes and 5–10 t/(hm2∙a) in the steppe regions. © 2016, Institute of Geographic Science and Natural Resources Research (IGSNRR), Science China Press and Springer-Verlag Berlin Heidelberg. Source


Jin Y.,Japan National Institute of Environmental Studies | Kai K.,Nagoya University | Kawai K.,Nagoya University | Nagai T.,Japan Meteorological Agency | And 6 more authors.
Journal of Quantitative Spectroscopy and Radiative Transfer | Year: 2014

Ceilometers are durable compact backscatter lidars widely used to detect cloud base height. They are also useful for measuring aerosols. We introduced a ceilometer (CL51) for observing dust in a source region in Mongolia. For retrieving aerosol profiles with a backscatter lidar, the molecular backscatter signal in the aerosol free heights or system constant of the lidar is required. Although the system constant of the ceilometer is calibrated by the manufacturer, it is not necessarily accurate enough for the aerosol retrieval. We determined a correction factor, which is defined as the ratio of true attenuated backscattering coefficient to the measured attenuated backscattering coefficient, for the CL51 ceilometer using a dual-wavelength Mie-scattering lidar in Tsukuba, Japan before moving the ceilometer to Dalanzadgad, Mongolia. The correction factor determined by minimizing the difference between the ceilometer and lidar backscattering coefficients was approximately 1.2±0.1. Applying the correction to the CL51 signals, the aerosol optical depth (AOD) agreed well with the sky-radiometer AOD during the observation period (13-17 February 2013) in Tsukuba (9×10-3 of mean square error). After moving the ceilometer to Dalanzadgad, however, the AOD observed with the CL51 (calibrated by the correction factor determined in Tsukuba) was approximately 60% of the AErosol RObotic NETwork (AERONET) sun photometer AOD. The possible causes of the lower AOD results are as follows: (1) the limited height range of extinction integration (<3km); (2) change in the correction factor during the ceilometer transportation or with the window contamination in Mongolia. In both cases, on-site calibrations by dual-wavelength lidar are needed. As an alternative method, we showed that the backward inversion method was useful for retrieving extinction coefficients if the AOD was larger than 1.5. This retrieval method does not require the system constant and molecular backscatter signals, and can be applied to severe dust and air pollution aerosol cases in East Asia. © 2014 Elsevier Ltd. Source


Allen R.W.,Simon Fraser University | Gombojav E.,Ulaanbaatar University | Barkhasragchaa B.,National Agency for Meteorology and Environmental Monitoring | Byambaa T.,Simon Fraser University | And 4 more authors.
Air Quality, Atmosphere and Health | Year: 2013

Epidemiologic studies have consistently reported associations between outdoor fine particulate matter (PM2. 5) air pollution and adverse health effects. Although Asia bears the majority of the public health burden from air pollution, few epidemiologic studies have been conducted outside of North America and Europe due in part to challenges in population exposure assessment. We assessed the feasibility of two current exposure assessment techniques, land use regression (LUR) modeling and mobile monitoring, and estimated the mortality attributable to air pollution in Ulaanbaatar, Mongolia. We developed LUR models for predicting wintertime spatial patterns of NO2 and SO2 based on 2-week passive Ogawa measurements at 37 locations and freely available geographic predictors. The models explained 74% and 78% of the variance in NO2 and SO2, respectively. Land cover characteristics derived from satellite images were useful predictors of both pollutants. Mobile PM2. 5 monitoring with an integrating nephelometer also showed promise, capturing substantial spatial variation in PM2. 5 concentrations. The spatial patterns in SO2 and PM, seasonal and diurnal patterns in PM2. 5, and high wintertime PM2. 5/PM10 ratios were consistent with a major impact from coal and wood combustion in the city's low-income traditional housing (ger) areas. The annual average concentration of PM2. 5 measured at a centrally located government monitoring site was 75 μg/m3 or more than seven times the World Health Organization's PM2. 5 air quality guideline, driven by a wintertime average concentration of 148 μg/m3. PM2. 5 concentrations measured in a traditional housing area were higher, with a wintertime mean PM2. 5 concentration of 250 μg/m3. We conservatively estimated that 29% (95% CI, 12-43%) of cardiopulmonary deaths and 40% (95% CI, 17-56%) of lung cancer deaths in the city are attributable to outdoor air pollution. These deaths correspond to nearly 10% of the city's total mortality, with estimates ranging to more than 13% of mortality under less conservative model assumptions. LUR models and mobile monitoring can be successfully implemented in developing country cities, thus cost-effectively improving exposure assessment for epidemiology and risk assessment. Air pollution represents a major threat to public health in Ulaanbaatar, Mongolia, and reducing home heating emissions in traditional housing areas should be the primary focus of air pollution control efforts. © 2011 The Author(s). Source


Jin Y.,Japan National Institute of Environmental Studies | Kai K.,Nagoya University | Kawai K.,Nagoya University | Sugimoto N.,Japan National Institute of Environmental Studies | And 4 more authors.
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2014

Ceilometer instruments are simple backscatter lidar systems and are usually set in airports for detecting the base of clouds. The instrument can also measure aerosol vertical distribution. Since ceilometers barely detect the molecular backscatter signals, retrieval of aerosol optical properties is an issue. This study investigates applicability of ceilometers to retrieval of optical properties. We make an idealized signal profile with the lidar ratio of 50 sr and calculate the retrieval errors caused by 30% errors of lidar ratio. In the forward inversion, useable (small error) optical properties are backscattering coefficients and the retrieval errors are less than 15% if the aerosol optical depth (AOD) is less than 0.2. The initial backscattering coefficients must be determined from other instruments (e.g., multi-wavelength lidar). Whereas in the backward inversion, if the AOD of idealized signals is larger than 1.5, extinction coefficients converge to the true value (within 5% errors), regardless of lidar ratios and initial conditions. Since there is no need for the system constant or molecular backscatter in this method, ceilometers can be an effective tool for retrieving extinction coefficients of dense aerosols in East Asia. © 2014 SPIE. Source


Bilguunmaa M.,Mongolian University of Science and Technology | Batbayar J.,National Agency for Meteorology and Environmental Monitoring | Tuya S.,Mongolian University of Science and Technology
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2014

The air quality indicator approximated by satellite measurements is known as an atmospheric particulate loading, which is evaluated in terms of the columnar optical thickness of aerosol scattering. This paper is attempting and estimating PM10 concentration by using Landsat 5 satellite data and validating these with air pollution measurements in Ulaanbaatar, Mongolia. We have been used the empirical method which based on multispectral algorithm PM10 model. Results from this research on concentration of PM10 in Ulaanbaatar city have been included. © 2014 SPIE. Source

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