Role of emissions and meteorology in the recent PM2.5 changes in China and South Korea from 2015 to 2018

Bae, Minah; Kim, Byeong-Uk; Kim, Hyun Cheol; Kim, Jhoon; Kim, Soontae

doi:10.1016/j.envpol.2020.116233

Cited by 48 publications

(18 citation statements)

References 40 publications

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“…However, few studies have examined the post-2018 changes in PM 2.5 concentrations in China in detail (Zhai et al 2019 ; Chen et al 2020 ; Bae et al 2021 ) (see Table 3 for more detail), or questioned if PM 2.5 concentration levels had continued to decline after the successful experience by the Action Plan (Yin and Zhang 2020 ; Zhong et al 2021 ). One recent study on the PM 2.5 pollution in Beijing-Tianjin-Hebei and the surrounding areas (the so-called “2 + 26” cities) estimated that PM 2.5 concentration levels increased by 6.8 µg/m 3 (9.46%) in the winter of 2018 (Dec–Feb).…”

Section: Introductionmentioning

confidence: 99%

“…Second, we adjust the PM 2.5 concentration data following the official monitoring method change for comparison consistency (see “ Materials and methods ” for more detail). Third, we apply a stepwise multiple linear regression (MLR) analysis (Li et al 2019a , 2020a ; Zhai et al 2019 ; Chen et al 2020 ; Bae et al 2021 ) to decompose PM 2.5 changes into contributions from meteorological and anthropogenic factors. We further relate the human factor contributions to actual policy adjustment and the rising marginal cost of these policy measures.…”

Section: Introductionmentioning

confidence: 99%

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Decomposing PM2.5 air pollution rebounds in Northern China before COVID-19

Dong

2022

Environ Sci Pollut Res

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China’s efforts to curb air pollution have drastically reduced its concentrations of fine particulate matter (PM 2.5 ) from 2013 to 2018 nationwide. However, few studies examined the most recent changes in PM 2.5 concentrations and questioned if the previous PM 2.5 declining trend was sustained or not. This study took a deep dive into the PM 2.5 trend for 136 northern cities of China from 2015 to early 2020 before the coronavirus disease 2019 (the COVID-19 hereafter) crisis, using ground-based PM 2.5 data notably adjusted for a key measurement method change. We find that mean PM 2.5 concentrations in northern China increased by 5.16 µg/m 3 in 2019, offsetting 80% of the large reduction achieved in 2018. The rebound was more significant during the heating seasons (HS; Nov to next Mar) over the 2 years: 10.49 µg/m 3 from the 2017 HS to the 2019 HS. A multiple linear regression analysis further revealed that anthropogenic factors contributed to around 50% of the PM 2.5 rebound in northern cities of China. Such a significant role of anthropogenic factors in driving the rebound was tightly linked to deep cuts in PM 2.5 concentrations in the previous year, systemic adjustment of policy targets and mitigation measures by the government, and the rising marginal cost of these measures. These findings suggest the need to chart a more sustainable path for future PM 2.5 emission reductions, with an emphasis on key regions during key pollution periods. Supplementary Information The online version contains supplementary material available at 10.1007/s11356-021-17889-2.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Decomposing PM2.5 air pollution rebounds in Northern China before COVID-19

Dong

2022

Environ Sci Pollut Res

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“…Over 2013-2017, anthropogenic emissions of nitrate precursors of NO x and NH 3 were reduced by 20.7 and 3.4% in China, respectively, and the concentrations of nitrate were reduced in China. However, the changes in anthropogenic emissions over China led to an increasing trend of nitrate in South Korea and Japan, which can be explained by that the reductions in SO 2 emissions changed the balance of the ammonia-nitric acid-sulfuric acid-water system, creating free NH 3 that reacted with HNO 3 to form NH 4 NO 3 (Bae et al, 2021;Uno et al, 2020).…”

Section: Frontiers In Environmentalmentioning

confidence: 99%

“…Uno et al (2020) reported that the observed surfacelayer PM 2.5 in Japan decreased in recent years, and the proportion of stations that satisfied the PM 2.5 air quality standard increased from 37.8% in 2014 to 89.9% in 2017. Bae et al (2021) showed that, from 2015 to 2018, the observed PM 2.5 concentrations averaged over 344 monitoring stations across South Korea decreased by 4.3% per year and the MODIS AOD in South Korea decreased by 4.7% per year. They also used the Community Multiscale Air Quality (CMAQ) model to quantify the impacts of the emissions and meteorology on the PM 2.5 concentration over 2015-2018.…”

Section: Introductionmentioning

confidence: 99%

The Impacts of Changes in Anthropogenic Emissions Over China on PM2.5 Concentrations in South Korea and Japan During 2013–2017

Xie

Liao

2022

Front. Environ. Sci.

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We applied the global 3-D chemical transport model GEOS-Chem to examine the effects of changes in anthropogenic emissions over China on PM2.5 concentrations in South Korea and Japan over 2013–2017 during which the Chinese governmental “Action Plan on the Prevention and Control of Air Pollution” was implemented. The reductions in anthropogenic emissions in China alleviated PM2.5 concentrations in South Korea and Japan. The reductions in anthropogenic emissions in China alone led to reductions in annual mean PM2.5 concentrations by 13.7 (19.7%), 2.7 (7.7%), and 1.0 (7.9%) μg m−3 over 2013–2017 in eastern China, South Korea, and Japan, respectively. The reductions in anthropogenic emissions in China also changed the components of PM2.5 in South Korea and Japan. The concentrations of sulfate, ammonium, black carbon and organic carbon were simulated to decrease and those of nitrate were simulated to increase in both South Korea and Japan. With the changes in anthropogenic emissions and the changes in meteorology (BASE simulation), the proportions of sulfate, nitrate, and OC in PM2.5 in South Korea (Japan) were, respectively, 17.1, 44.4, and 15.8% (27.2, 30.5, and 20.0%) in 2013, and 14.3, 46.0, and 17.8% (23.7, 33.2, and 21.6%) in 2017. Model results shown here are helpful for understanding the temporal evolution in PM2.5 on different timescales in the downwind regions of China.

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“…Regional air quality model predictions of PM2.5 are typically evaluated with observations from surface network sites, but the spatially continuous RF PM2.5 fields offer more extensive coverage for model evaluation. We demonstrate this capability here with Community Multiscale Air Quality Modeling System (CMAQ version 4.7.1) simulations for the Korean peninsula including both South and North Korea at 9-km resolution Bae et al, 2021]. There are no surface PM2.5 data in North Korea to train the RF so we use the South Korea categorical variable to generate the RF PM2.5 fields there.…”

Section: Regional Air Quality Model Evaluationmentioning

confidence: 99%

Continuous mapping of fine particulate matter (PM_2.5) air quality in East Asia at daily 6×6 km² resolution by application of a random forest algorithm to 2011–2019 GOCI geostationary satellite data

Pendergrass

Jacob

Zhai

et al. 2021

Preprint

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Abstract. We use 2011–2019 aerosol optical depth (AOD) observations from the Geostationary Ocean Color Imager (GOCI) instrument over East Asia to infer 24-h daily surface fine particulate matter (PM2.5) concentrations at continuous 6x6 km2 resolution over eastern China, South Korea, and Japan. This is done with a random forest (RF) algorithm applied to the gap-filled GOCI AODs and other data and trained with PM2.5 observations from the three national networks. The predicted 24-h PM2.5 concentrations for sites entirely withheld from training in a ten-fold crossvalidation procedure correlate highly with network observations (R2 = 0.89) with single-value precision of 26–32 % depending on country. Prediction of annual mean values has R2 = 0.96 and single-value precision of 12 %. The RF algorithm is only moderately successful for diagnosing local exceedances of the National Ambient Air Quality Standard (NAAQS) because these exceedances are typically within the single-value precisions of the RF, and also because of RF smoothing of extreme PM2.5 concentrations. The area-weighted and population-weighted trends of RF PM2.5 concentrations for eastern China, South Korea, and Japan show steady 2015–2019 declines consistent with surface networks, but the surface networks in eastern China and South Korea underestimate population exposure. Further examination of RF PM2.5 fields for South Korea identifies hotspots where surface network sites were initially lacking and shows 2015–2019 PM2.5 decreases across the country except for flat concentrations in the Seoul metropolitan area. Inspection of monthly PM2.5 time series in Beijing, Seoul, and Tokyo shows that the RF algorithm successfully captures observed seasonal variations of PM2.5 even though AOD and PM2.5 often have opposite seasonalities. Application of the RF algorithm to urban pollution episodes in Seoul and Beijing demonstrates high skill in reproducing the observed day-to-day variations in air quality as well as spatial patterns on the 6 km scale. Comparison to a CMAQ simulation for the Korean peninsula demonstrates the value of the continuous RF PM2.5 fields for testing air quality models, including over North Korea where they offer a unique resource.

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Role of emissions and meteorology in the recent PM2.5 changes in China and South Korea from 2015 to 2018

Cited by 48 publications

References 40 publications

Decomposing PM2.5 air pollution rebounds in Northern China before COVID-19

Decomposing PM2.5 air pollution rebounds in Northern China before COVID-19

The Impacts of Changes in Anthropogenic Emissions Over China on PM2.5 Concentrations in South Korea and Japan During 2013–2017

Continuous mapping of fine particulate matter (PM_2.5) air quality in East Asia at daily 6×6 km² resolution by application of a random forest algorithm to 2011–2019 GOCI geostationary satellite data

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Role of emissions and meteorology in the recent PM2.5 changes in China and South Korea from 2015 to 2018

Cited by 48 publications

References 40 publications

Decomposing PM2.5 air pollution rebounds in Northern China before COVID-19

Decomposing PM2.5 air pollution rebounds in Northern China before COVID-19

The Impacts of Changes in Anthropogenic Emissions Over China on PM2.5 Concentrations in South Korea and Japan During 2013–2017

Continuous mapping of fine particulate matter (PM2.5) air quality in East Asia at daily 6×6 km2 resolution by application of a random forest algorithm to 2011–2019 GOCI geostationary satellite data

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Product

Resources

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Continuous mapping of fine particulate matter (PM_2.5) air quality in East Asia at daily 6×6 km² resolution by application of a random forest algorithm to 2011–2019 GOCI geostationary satellite data