scholarly journals GIST-PM-Asia v1: development of a numerical system to improve particulate matter forecasts in South Korea using geostationary satellite-retrieved aerosol optical data over Northeast Asia

2016 ◽  
Vol 9 (1) ◽  
pp. 17-39 ◽  
Author(s):  
S. Lee ◽  
C. H. Song ◽  
R. S. Park ◽  
M. E. Park ◽  
K. M. Han ◽  
...  
Keyword(s):  
Particulate Matter ◽  
South Korea ◽  
Northeast Asia ◽  
Initial Distribution ◽  
Low Earth Orbit ◽  
Optical Data ◽  
Future Research ◽  
Observation Data ◽  
Forecast System ◽  
Short Term

Abstract. To improve short-term particulate matter (PM) forecasts in South Korea, the initial distribution of PM composition, particularly over the upwind regions, is primarily important. To prepare the initial PM composition, the aerosol optical depth (AOD) data retrieved from a geostationary equatorial orbit (GEO) satellite sensor, GOCI (Geostationary Ocean Color Imager) which covers a part of Northeast Asia (113–146° E; 25–47° N), were used. Although GOCI can provide a higher number of AOD data in a semicontinuous manner than low Earth orbit (LEO) satellite sensors, it still has a serious limitation in that the AOD data are not available at cloud pixels and over high-reflectance areas, such as desert and snow-covered regions. To overcome this limitation, a spatiotemporal-kriging (STK) method was used to better prepare the initial AOD distributions that were converted into the PM composition over Northeast Asia. One of the largest advantages in using the STK method in this study is that more observed AOD data can be used to prepare the best initial AOD fields compared with other methods that use single frame of observation data around the time of initialization. It is demonstrated in this study that the short-term PM forecast system developed with the application of the STK method can greatly improve PM10 predictions in the Seoul metropolitan area (SMA) when evaluated with ground-based observations. For example, errors and biases of PM10 predictions decreased by  ∼  60 and  ∼  70 %, respectively, during the first 6 h of short-term PM forecasting, compared with those without the initial PM composition. In addition, the influences of several factors on the performances of the short-term PM forecast were explored in this study. The influences of the choices of the control variables on the PM chemical composition were also investigated with the composition data measured via PILS-IC (particle-into-liquid sampler coupled with ion chromatography) and low air-volume sample instruments at a site near Seoul. To improve the overall performances of the short-term PM forecast system, several future research directions were also discussed and suggested.

scholarly journals Development of a numerical system to improve particulate matter forecasts in South Korea using geostationary satellite-retrieved aerosol optical data over Northeast Asia

2015 ◽  
Vol 8 (7) ◽  
pp. 5315-5366
Author(s):  
S. Lee ◽  
C. H. Song ◽  
R. S. Park ◽  
M. E. Park ◽  
K. M. Han ◽  
...  
Keyword(s):  
Particulate Matter ◽  
South Korea ◽  
Northeast Asia ◽  
Low Earth Orbit ◽  
Optical Data ◽  
Future Research ◽  
Kriging Method ◽  
Forecast System ◽  
Short Term ◽  
Control Variables

Abstract. To improve short-term particulate matter (PM) forecasts in South Korea, the initial distribution of PM composition, particularly over the upwind regions, is primarily important. To prepare the initial PM composition, the aerosol optical depth (AOD) data retrieved from a geostationary equatorial orbit (GEO) satellite sensor, GOCI (Geostationary Ocean Color Imager) which covers Northeast Asia (113–146° E; 25–47° N), were used. Although GOCI can provide a higher number of AOD data in a semi-continuous manner than low Earth orbit (LEO) satellite sensors, it still has a serious limitation in that the AOD data are not available at cloud pixels and over high-reflectance areas, such as desert and snow-covered regions. To overcome this limitation, a spatio-temporal (ST) kriging method was used to better prepare the initial AOD distributions that were converted into the PM composition over Northeast Asia. One of the largest advantages to using the ST-kriging method in this study is that more observed AOD data can be used to prepare the best initial AOD fields. It is demonstrated in this study that the short-term PM forecast system developed with the application of the ST-kriging method can greatly improve PM10 predictions in Seoul Metropolitan Area (SMA), when evaluated with ground-based observations. For example, errors and biases of PM10 predictions decreased by ~ 60 and ~ 70 %, respectively, during the first 6 h of short-term PM forecasting, compared with those without the initial PM composition. In addition, the influences of several factors (such as choices of observation operators and control variables) on the performances of the short-term PM forecast were explored in this study. The influences of the choices of the control variables on the PM chemical composition were also investigated with the composition data measured via PILS-IC and low air-volume sample instruments at a site near Seoul. To improve the overall performances of the short-term PM forecast system, several future research directions were also discussed and suggested.

scholarly journals An Observing System Simulation Experiment Framework for Air Quality Forecasts in Northeast Asia: A Case Study Utilizing Virtual Geostationary Environment Monitoring Spectrometer and Surface Monitored Aerosol Data

2022 ◽  
Vol 14 (2) ◽  
pp. 389
Author(s):  
Hyeon-Kook Kim ◽  
Seunghee Lee ◽  
Kang-Ho Bae ◽  
Kwonho Jeon ◽  
Myong-In Lee ◽  
...  
Keyword(s):  
Air Quality ◽  
South Korea ◽  
System Simulation ◽  
Northeast Asia ◽  
Gobi Desert ◽  
Observation Data ◽  
Environment Monitoring ◽  
Study Results ◽  
Current Monitoring

Prior knowledge of the effectiveness of new observation instruments or new data streams for air quality can contribute significantly to shaping the policy and budget planning related to those instruments and data. In view of this, one of the main purposes of the development and application of the Observing System Simulation Experiments (OSSE) is to assess the potential impact of new observations on the quality of the current monitoring or forecasting systems, thereby making this framework valuable. This study introduces the overall OSSE framework established to support air quality forecasting and the details of its individual components. Furthermore, it shows case study results from Northeast Asia and the potential benefits of the new observation data scenarios on the PM2.5 forecasting skills, including the PM data from 200 virtual monitoring sites in the Gobi Desert and North Korean non-forest areas (NEWPM) and the aerosol optical depths (AOD) data from South Korea’s Geostationary Environment Monitoring Spectrometer (GEMS AOD). Performance statistics suggest that the concurrent assimilation of the NEWPM and the PM data from current monitoring sites in China and South Korea can improve the PM2.5 concentration forecasts in South Korea by 66.4% on average for October 2017 and 95.1% on average for February 2018. Assimilating the GEMS AOD improved the performance of the PM2.5 forecasts in South Korea for October 2017 by approximately 68.4% (~78.9% for February 2018). This OSSE framework is expected to be continuously implemented to verify its utilization potential for various air quality observation systems and data scenarios. Hopefully, this kind of application result will aid environmental researchers and decision-makers in performing additional in-depth studies for the improvement of PM air quality forecasts.

Temple Food As a Sustainable Tourism Attraction: Ecogastronomic Buddhist Heritage and Regional Development in South Korea

2020 ◽  
Vol 4 (4) ◽  
pp. 209-222
Author(s):  
Anne H.J. Lee ◽  
Geoffrey Wall
Keyword(s):  
South Korea ◽  
Regional Development ◽  
Participant Observation ◽  
Sustainable Tourism ◽  
Well Being ◽  
Future Research ◽  
Rich Description ◽  
Food Programs ◽  
Ongoing Development ◽  
Narrative Interpretation

This research explores Buddhist heritage-based tourism in South Korea. It examines temple food experiences provided in tandem with templestay programs that emphasize the Buddhist cooking tradition and share aspects of traditional Buddhist culture with visitors. Based primarily on participant observation, this ecologically friendly form of tourism is described and the ongoing development of temple food programs is documented. A "person-centric" perception is adopted from two perspectives: an emphasis on the holistic well-being of individual visitors, and the importance of a specific person in the provision of tourism experiences. Rich description and narrative interpretation are used to explain the phenomenon and provide a foundation on which future research can be grounded.

scholarly journals Staying Home, Staying Alive: Campus Food Pantry Student Clients’ Experiences During the COVID-19 Pandemic

2021 ◽  
pp. 193672442110356
Author(s):  
Elmira Jangjou
Keyword(s):  
Coping Strategies ◽  
Thematic Analysis ◽  
Future Research ◽  
Postsecondary Students ◽  
Structured Interviews ◽  
Short Term ◽  
Income Loss ◽  
Food Pantry ◽  
Global Pandemic ◽  
Seeking Help

In response to students’ food insecurity, a number of colleges and universities have taken action and established campus food pantries as part of their intervention plans. However, many of these pantries ceased operation due to COVID-19 campus shutdowns. The purpose of this study is to illustrate the short-term impacts of the COVID-19 pandemic on postsecondary students, who use a university-provided food pantry. Drawing from semi-structured interviews with 12 participants, the thematic analysis explored the initial coping strategies these students used to endure the pandemic. Findings revealed that many students experienced the immediate effects of the pandemic in the form of income loss, self-isolation, anxiety, and appetite change. Although the pandemic interrupted these students’ journeys to continue their studies and become independent in various ways, the affected students implemented various coping strategies, including seeking help from family or friends, using available resources, cooking at home, and even trying to save money. However, considering that the targeted population in this study was already at risk because of their basic needs insecurity, these postsecondary students require extra attention from their higher education institutions in the case of emergencies, such as a global pandemic. In addition to its timely and relevant findings, this study provides important avenues for future research and intervention efforts.

scholarly journals A global association between Covid-19 cases and airborne particulate matter at regional level

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Angelo Solimini ◽  
F. Filipponi ◽  
D. Alunni Fegatelli ◽  
B. Caputo ◽  
C. M. De Marco ◽  
...  
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Negative Binomial ◽  
Numerical Models ◽  
Regional Level ◽  
Pollution Level ◽  
Observation Data ◽  
Cumulative Number ◽  
Mixed Effect

AbstractEvidences of an association between air pollution and Covid-19 infections are mixed and inconclusive. We conducted an ecological analysis at regional scale of long-term exposure to air-borne particle matter and spread of Covid-19 cases during the first wave of epidemics. Global air pollution and climate data were calculated from satellite earth observation data assimilated into numerical models at 10 km resolution. Main outcome was defined as the cumulative number of cases of Covid-19 in the 14 days following the date when > 10 cumulative cases were reported. Negative binomial mixed effect models were applied to estimate the associations between the outcome and long-term exposure to air pollution at the regional level (PM10, PM2.5), after adjusting for relevant regional and country level covariates and spatial correlation. In total we collected 237,749 Covid-19 cases from 730 regions, 63 countries and 5 continents at May 30, 2020. A 10 μg/m3 increase of pollution level was associated with 8.1% (95% CI 5.4%, 10.5%) and 11.5% (95% CI 7.8%, 14.9%) increases in the number of cases in a 14 days window, for PM2.5 and PM10 respectively. We found an association between Covid-19 cases and air pollution suggestive of a possible causal link among particulate matter levels and incidence of COVID-19.

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