scholarly journals Composition comparison of PM10and PM2.5fine particulate matter for Asian dust and haze events of 2010-2011 at Gosan site in Jeju Island

2014 ◽  
Vol 27 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Ki-Ju Kim ◽  
Seung-Hoon Lee ◽  
Dong-Rim Hyeon ◽  
Hee-Jung Ko ◽  
Won-Hyung Kim ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Asian Dust ◽  
Jeju Island

Contrasting synoptic weather patterns between non-dust high particulate matter events and Asian dust events in Seoul, South Korea

2019 ◽  
Vol 214 ◽  
pp. 116864 ◽  
Author(s):  
Myung-Il Jung ◽  
Seok-Woo Son ◽  
Hyun Cheol Kim ◽  
Sang-Woo Kim ◽  
Rokjin J. Park ◽  
...  
Keyword(s):  
Particulate Matter ◽  
South Korea ◽  
Asian Dust ◽  
Weather Patterns ◽  
Synoptic Weather ◽  
Dust Events

scholarly journals The value of satellite observations in the analysis and short-range prediction of Asian dust

2019 ◽  
Vol 19 (2) ◽  
pp. 987-998 ◽  
Author(s):  
Angela Benedetti ◽  
Francesca Di Giuseppe ◽  
Luke Jones ◽  
Vincent-Henri Peuch ◽  
Samuel Rémy ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Data Assimilation ◽  
Optical Depth ◽  
Short Range ◽  
Asian Dust ◽  
Satellite Observations ◽  
Global Model ◽  
Deep Blue ◽  
Dust Events

Abstract. Asian dust is a seasonal meteorological phenomenon which affects east Asia, and has severe consequences on the air quality of China, North and South Korea and Japan. Despite the continental extent, the prediction of severe episodes and the anticipation of their consequences is challenging. Three 1-year experiments were run to assess the skill of the model of the European Centre for Medium-Range Weather Forecasts (ECMWF) in monitoring Asian dust and understand its relative contribution to the aerosol load over China. Data used were the Moderate Resolution Imaging Spectroradiometer (MODIS) Dark Target and the Deep Blue aerosol optical depth (AOD). In particular the experiments aimed at understanding the added value of data assimilation runs over a model run without any aerosol data. The year 2013 was chosen as representative of the availability of independent AOD data from two established ground-based networks (AERONET, Aerosol Robotic Network, and CARSNET, China Aerosol Remote Sensing Network), which could be used to evaluate experiments. Particulate matter (PM) data from the China Environmental Protection Agency were also used in the evaluation. Results show that the assimilation of satellite AOD data is beneficial to predict the extent and magnitude of desert dust events and to improve the short-range forecast of such events. The availability of observations from the MODIS Deep Blue algorithm over bright surfaces is an asset, allowing for a better localization of the sources and definition of the dust events. In general both experiments constrained by data assimilation perform better than the unconstrained experiment, generally showing smaller normalized mean bias and fractional gross error with respect to the independent verification datasets. The impact of the assimilated satellite observations is larger at analysis time, but lasts into the forecast up to 48 h. The performance of the global model in terms of particulate matter does not show the same degree of skill as the performance in terms of optical depth. Despite this, the global model is able to capture some regional pollution patterns. This indicates that the global model analyses may be used as boundary conditions for regional air quality models at higher resolution, enhancing their performance in situations in which part of the pollution may have originated from large-scale mechanisms. While assimilation is not a substitute for model development and characterization of the emission sources, results indicate that it can play a role in delivering improved monitoring of Asian dust optical depth.

Size distribution and sources of humic-like substances in particulate matter at an urban site during winter

2016 ◽  
Vol 18 (1) ◽  
pp. 32-41 ◽  
Author(s):  
Seungshik Park ◽  
Se-Chang Son
Keyword(s):  
Particle Size ◽  
Particulate Matter ◽  
Size Distribution ◽  
Bimodal Distribution ◽  
Asian Dust ◽  
Urban Site

The highest contribution of HULIS-C to WSOC was observed to be in the particle size bins of 0.55–1.0 μm and 1.8–3.1 μm during non-Asian dust (NAD, 45 ± 6%) and Asian dust (AD, 44 ± 7%) periods, respectively. HULIS exhibited a uni-modal (@0.55 μm) distribution during the NAD and a bimodal distribution (@0.32 and 1.8 μm) during AD, respectively.

scholarly journals Extreme Aerosol Events at Mesa Verde, Colorado: Implications for Air Quality Management

Atmosphere ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1140
Author(s):  
Marisa E. Gonzalez ◽  
Jeri G. Garfield ◽  
Andrea F. Corral ◽  
Eva-Lou Edwards ◽  
Kira Zeider ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Extreme Events ◽  
Airborne Particulate Matter ◽  
Asian Dust ◽  
Weekly Cycle ◽  
Aerosol Model ◽  
Anthropogenic Pollutants ◽  
Mesa Verde ◽  
Aerosol Analysis

A significant concern for public health and visibility is airborne particulate matter, especially during extreme events. Of most relevance for health, air quality, and climate is the role of fine aerosol particles, specifically particulate matter with aerodynamic diameters less than or equal to 2.5 micrometers (PM2.5). The purpose of this study was to examine PM2.5 extreme events between 1989 and 2018 at Mesa Verde, Colorado using Interagency Monitoring of Protected Visual Environments (IMPROVE) monitoring data. Extreme events were identified as those with PM2.5 on a given day exceeding the 90th percentile value for that given month. We examine the weekly, monthly, and interannual trends in the number of extreme events at Mesa Verde, in addition to identifying the sources of the extreme events with the aid of the Navy Aerosol Analysis and Prediction (NAAPS) aerosol model. Four sources were used in the classification scheme: Asian dust, non-Asian dust, smoke, and “other”. Our results show that extreme PM2.5 events in the spring are driven mostly by the dust categories, whereas summertime events are influenced largely by smoke. The colder winter months have more influence from “other” sources that are thought to be largely anthropogenic in nature. No weekly cycle was observed for the number of events due to each source; however, interannual analysis shows that the relative amount of dust and smoke events compared to “other” events have increased in the last decade, especially smoke since 2008. The results of this work indicate that, to minimize and mitigate the effects of extreme PM2.5 events in the southwestern Colorado area, it is important to focus mainly on smoke and dust forecasting in the spring and summer months. Wintertime extreme events may be easier to regulate as they derive more from anthropogenic pollutants accumulating in shallow boundary layers in stagnant conditions.

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