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

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.

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A Multiscale Tiered Approach to Quantify Contributions: A Case Study of PM2.5 in South Korea During 2010–2017

Atmosphere ◽

10.3390/atmos11020141 ◽

2020 ◽

Vol 11 (2) ◽

pp. 141 ◽

Cited By ~ 11

Author(s):

Minah Bae ◽

Byeong-Uk Kim ◽

Hyun Cheol Kim ◽

Soontae Kim

Keyword(s):

Air Quality ◽

South Korea ◽

Sparse Matrix ◽

Action Plan ◽

Weather Research And Forecasting ◽

Study Results ◽

Simulation Based ◽

Operator Kernel

We estimated long-term foreign contributions to the particulate matter of 2.5 μm or less in diameter (PM2.5) concentrations in South Korea with a set of air quality simulations. The Weather Research and Forecasting (WRF)-Sparse Matrix Operator Kernel Emissions (SMOKE)-Community Multiscale Air Quality (CMAQ) modeling system was used to simulate the base and sensitivity case after a 50% reduction of foreign emissions. The effects of horizontal modeling grid resolutions (27- and 9-km) was also investigated. For this study, we chose PM2.5 in South Korea during 2010–2017 for the case study and emissions from China as a representative foreign source. The 9-km simulation results show that the 8-year average contribution of the Chinese emissions in 17 provinces ranged from 40–65%, which is ~4% lower than that from the 27-km simulation for the high-tier government segments (particularly prominent in coastal areas). However, for the same comparison for low-tier government segments (i.e., 250 prefectures), the 9-km simulation presented lowered the foreign contribution by up to 10% compared to that from the 27-km simulation. Based on our study results, we recommend using high-resolution modeling results for regional contribution analyses to develop an air quality action plan as the receptor coverage decreases.

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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

Geoscientific Model Development ◽

10.5194/gmd-9-17-2016 ◽

2016 ◽

Vol 9 (1) ◽

pp. 17-39 ◽

Cited By ~ 13

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.

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Impacts of atmospheric vertical structures on transboundary aerosol transport from China to South Korea

Scientific Reports ◽

10.1038/s41598-019-49691-z ◽

2019 ◽

Vol 9 (1) ◽

Cited By ~ 9

Author(s):

Hyo-Jung Lee ◽

Hyun-Young Jo ◽

Sang-Woo Kim ◽

Moon-Soo Park ◽

Cheol-Hee Kim

Keyword(s):

Boundary Layer ◽

Air Quality ◽

South Korea ◽

Long Range ◽

Korean Peninsula ◽

Ground Level ◽

The Yellow Sea ◽

Observation Data ◽

Haze Pollution ◽

High Concentrations

Abstract To forecast haze pollution episodes caused by high concentrations of long-range transported pollutants emitted in the areas upstream of South Korea, it is crucial to study and identify their behaviour. We analysed the three-dimensional air quality structure in Seoul using ground observation data and aerosol lidar measurements to identify vertical aerosol intrusion into the Korean Peninsula during the spring of 2016. The intrusions were particularly affected by the development of the atmospheric boundary layer (ABL) in the leeward regions. The nocturnal pollutant intrusion into the Korean peninsula via the Yellow Sea was examined using measured data. The pollutants first reached the area above the nocturnal boundary layer (548 ± 180 m) and approached ground level on the following day due to convective mixing depending on the convective ABL growth (1182 ± 540 m) in daytime. These intrusion mechanisms were mostly attributed to extremely high concentrations (i.e. >100 μg m−3) of fine particulate matter in the leeward regions, accounting for four of the total of six cases for which the warnings and alerts were issued in Seoul Metropolitan Area over a year-long period (2016). The horizontal and vertical pathways of the long-range transported pollutants and the atmospheric vertical structure were identified as key factors affecting the surface air quality concentration in the leeward regions.

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Internet of Things Sensor Data Analysis for Enhanced Living Environments: A Literature Review and a Case Study Results on Air Quality Sensing

Enabling AI Applications in Data Science - Studies in Computational Intelligence ◽

10.1007/978-3-030-52067-0_18 ◽

2020 ◽

pp. 397-414

Author(s):

Gonçalo Marques

Keyword(s):

Data Analysis ◽

Air Quality ◽

Internet Of Things ◽

Literature Review ◽

Sensor Data ◽

Study Results ◽

Living Environments

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Monitoring Spatial and Temporal Variability of Air Quality Using Satellite Observation Data: a Case Study of MODIS-Observed Aerosols in Southern Ontario, Canada

Air Quality ◽

10.5772/9753 ◽

2010 ◽

Cited By ~ 1

Author(s):

DongMei Chen ◽

Jie Ti

Keyword(s):

Air Quality ◽

Temporal Variability ◽

Satellite Observation ◽

Spatial And Temporal Variability ◽

Observation Data ◽

Southern Ontario

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Regional Differences of Primary Meteorological Factors Impacting O3 Variability in South Korea

Atmosphere ◽

10.3390/atmos11010074 ◽

2020 ◽

Vol 11 (1) ◽

pp. 74 ◽

Cited By ~ 1

Author(s):

Yeomin Jeong ◽

Hwa Woon Lee ◽

Wonbae Jeon

Keyword(s):

Air Quality ◽

South Korea ◽

Regional Differences ◽

Meteorological Factors ◽

Surface Ozone ◽

Maximum Temperature ◽

Observation Data ◽

Period 2 ◽

The Difference ◽

The Impact

Surface ozone (O3) is a harmful pollutant and effective strategies must be developed for its reduction. In this study, the impact of meteorological factors on the annual O3 variability for South Korea were analyzed. In addition, the regional differences of meteorological factors in six air quality regions in South Korea (Seoul Metropolitan Area, SMA; Central region, CN; Honam, HN; Yeongnam, YN; Gangwon, GW; Jeju, JJ) were compared. The analysis of ground observation data from 2001 to 2017 revealed that the long-term variability of O3 concentration in South Korea continuously increased since 2001, and the upward trend in 2010 to 2017 (Period 2, PRD2) was 29.8% higher than that in 2001 to 2009 (Period 1, PRD1). This was because the meteorological conditions during PRD2 became relatively favorable for high O3 concentrations compared to conditions during PRD1. In particular, the increase in the solar radiation (SR) and maximum temperature (TMAX) and the decrease in the precipitation (PRCP) and wind speed (WS) of South Korea in PRD2 were identified as the main causes for the rise in O3 concentrations. When meteorological factors and O3 variability were compared among the six air quality regions in South Korea during PRD1 and PRD2, significant differences were observed. This indicated that different meteorological changes occurred in South Korea after 2010 due to the different topographical characteristics of each region; thus, O3 variability also changed differently in each region. Interestingly, for the regions with almost similar meteorological changes after 2010, the O3 concentration changed differently depending on the difference in the distribution of emissions. These results indicate that the O3–meteorology relationship shows spatiotemporal differences depending on the topographical and emission distribution characteristics of each area and implies that it is necessary to fully consider such differences for efficient O3 reduction.

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Cross-verification of simulated GEMS tropospheric ozone retrievals and ozonesonde measurements over Northeast Asia

10.5194/amt-2019-19 ◽

2019 ◽

Author(s):

Juseon Bak ◽

Kang-Hyeon Baek ◽

Jae-Hwan Kim ◽

Xiong Liu ◽

Jhoon Kim ◽

...

Keyword(s):

Air Quality ◽

Tropospheric Ozone ◽

Northeast Asia ◽

Optimal Estimation ◽

New Delhi ◽

Air Quality Monitoring ◽

Environment Monitoring ◽

Satellite Mission ◽

Ozone Profile ◽

Column Ozone

Abstract. The Geostationary Environment Monitoring Spectrometer (GEMS) is scheduled to be launched in 2019 on board the GEO-KOMPSAT (GEOstationary KOrea Multi-Purpose SATellite)-2B, contributing as the Asian partner of the global geostationary constellation of air quality monitoring. To support this air quality satellite mission, we perform the cross-verification of simulated GEMS ozone profile retrievals based on the Optimal Estimation and ozonesonde measurements within the GEMS domain, covering from 5° S (Indonesia) to 45° N (south of the Russian border) and from 75° E to 145° E. The comparison between ozonesonde and GEMS shows a significant dependence on ozonesonde types. Ozonesonde data measured by Modified Brewer-Master (MB-M) at Trivandrum and New Delhi show inconsistent seasonal-variabilities in the tropospheric ozone, compared to latitudinally adjacent stations with Carbon Iodine (CI) and Electrochemical Condensation Cell (ECC). CI ozonesonde measurements are biased relative to ECC measurements by 2–4 DU; a better agreement with GEMS simulations is achieved with ECC measurements. ECC ozone data at Hanoi, Kuala Lump, and Singapore show abnormally worse agreements with simulated GEMS retrievals among ECC measurements. Therefore, ECC ozonesonde measurements at Hong Kong, Pohang, Naha, Sapporo, and Tsukuba are finally identified as an optimal reference. The accuracy of simulated GEMS retrievals is estimated to be ~ 5.0 % for both tropospheric and stratospheric column ozone with the precision of 15 % and 5 %, which meet the GEMS ozone requirements.

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