Importance of regional PM2.5 transport and precipitation washout in heavy air pollution in the Twain-Hu Basin over Central China: Observational analysis and WRF-Chem simulation

Hu, Weiyang; Zhao, Tianliang; Bai, Yongqing; Kong, Shaofei; Xiong, Jie; Sun, Xiaoyun; Yang, Quan-Hui; Gu, Yu; Lu, Huicheng

doi:10.1016/j.scitotenv.2020.143710

Cited by 61 publications

(34 citation statements)

References 51 publications

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“…Yu et al [14] found unique "non-stagnant" meteorological conditions, including strong northerly winds, no temperature inversion, and additional unstable structures in the atmospheric boundary layer, during the noteworthy cases of heavy PM2.5 pollution in Wuhan of Hubei provinces. Figure 5d shows further that the hourly PM 2.5 concentrations exhibit inverse changes over the THB and the NCP regions during 30 THB-HPEs for the years of 2015-2019, and the PM 2.5 peak over the THB is delayed for almost 2 days compared with that of the NCP, which is consistent with the results of Hu et al [57]. Although the PM 2.5 peak concentrations in the THB are slightly smaller than those in the NCP, which are attributable to the dilution effect when being transported, local emission can also be important during these processes, considering the high levels of PM 2.5 concentrations in the THB.…”

Section: Attribution Of Heavy Pollution Events In the Twain-hu Basinsupporting

confidence: 90%

Changes in the Distribution Pattern of PM2.5 Pollution over Central China

Zhao

Bai

et al. 2021

Remote Sensing

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The extent of PM2.5 pollution has reduced in traditional polluted regions such as the North China Plain (NCP), Yangtze River Delta (YRD), Sichuan Basin (SB), and Pearl River Delta (PRD) over China in recent years. Despite this, the Twain-Hu Basin (THB), which covers the lower flatlands in Hubei and Hunan provinces in central China, was found to be a high PM2.5 pollution region, with annual mean PM2.5 concentrations of 41–63 μg·m−3, which is larger than the values in YRD, SB, and PRD during 2014–2019, and high aerosol optical depth values (>0.8) averaged over 2000–2019 from the MODIS products. Heavy pollution events (HPEs) are frequently observed in the THB, with HPE-averaged concentrations of PM2.5 reaching up to 183–191 μg·m−3, which exceeds their counterparts in YRD, SB, and PRD for 2014–2019, highlighting the THB as a center of heavy PM2.5 pollution in central China. During 2014–2019, approximately 65.2% of the total regional HPEs over the THB were triggered by the regional transport of PM2.5 over Central and Eastern China (CEC). This occurred in view of the co-existing HPEs in the NCP and the THB, with a lag of almost two days in the THB-PM2.5 peak, which is governed by the strong northerlies of the East Asian monsoon (EAM) over CEC. Such PM2.5 transport from upstream source regions in CEC contributes 60.3% of the surface PM2.5 pollution over the THB receptor region. Hence, a key PM2.5 receptor of the THB in regional pollutant transport alters the distribution patterns of PM2.5 pollution over China, which is attributable to the climate change of EAMs. This study indicates a complex relationship between sources and receptors of atmospheric aerosols for air quality applications.

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Section: Attribution Of Heavy Pollution Events In the Twain-hu Basinsupporting

confidence: 90%

Changes in the Distribution Pattern of PM2.5 Pollution over Central China

Zhao

Bai

et al. 2021

Remote Sensing

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“…Some studies reveal that raindrops can absorb the dust in the air. When raindrops and dust fall to the ground by gravity, the number of particles matter in the air decreases accordingly (Hu et al, 2020 ). The weakening effect of the increase of rainfall on the concentrations of PM 2.5 in a certain range was also found in our study.…”

Section: Discussionmentioning

confidence: 99%

Understanding the distribution and drivers of PM2.5 concentrations in the Yangtze River Delta from 2015 to 2020 using Random Forest Regression

Su¹,

Lin

Chen³

et al. 2022

Environ Monit Assess

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Understanding the drivers of PM 2.5 is critical for the establishment of PM 2.5 prediction models and the prevention and control of regional air pollution. In this study, the Yangtze River Delta is taken as the research object. Spatial cluster and outlier method was used to analyze the temporal and spatial distribution and variation of surface PM 2.5 in the Yangtze River Delta from 2015 to 2020, and Random Forest was utilized to analyze the drivers of PM 2.5 in this area. The results indicated that (1) based on the spatial cluster distribution of PM 2.5 , the northwest and north of Yangtze River Delta region were mostly highly concentrated and surrounded by high concentrations of PM 2.5 , while lowly concentrated and surrounded by low concentrations areas were distributed in the southern; (2) the relationship between PM 2.5 concentrations and drivers in the Yangtze River Delta was modeled well and the explanatory rate of drivers to PM 2.5 were more than 0.9; (3) temperature, precipitation, and wind speed were the main driving forces of PM 2.5 emission in the Yangtze River Delta. It should be noted that the repercussion of wildfire on PM 2.5 was gradually prominent. When formulating air pollution control measures, the local government normally considers the impact of weather and traffic conditions. In order to reduce PM 2.5 pollution caused by biomass combustion, the influence of wildfire should also be taken into account, especially in the fire season. Meanwhile, high leaf area was conducive to improving air quality, and the increasing green area will help reduce air pollutants. Supplementary information The online version contains supplementary material available at 10.1007/s10661-022-09934-5.

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“…Under the influence of emission source control during COVID-19, eastern Hubei saw a great decrease in locally sourced PM2.5 accumulation and long-distance inter-regional transport, while central-western Hubei experienced an increase in PM2.5 long-distance inter-regional transport. Hu et al(2020) [50] revealed that the regional PM2.5 transport of Central-East China made large contributions to Hubei's heavy air pollution, and such contribution was greater in the western region than in the eastern region. Thus, it can be seen that the PM2.5 high-value center in the urban circle of WH was dominated by high-level local emissions, while the high-value center in the transport channel cities in central-western Hubei was more affected by inter-regional transport.…”

Section: Discussionmentioning

confidence: 99%

Impact of Inter-Regional Transport in a Low-Emission Scenario on PM2.5 in Hubei Province, Central China

et al. 2021

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In 2020, when the novel coronavirus disease 2019 (COVID-19) broke out as a global pandemic, cities in Hubei Province first went into lockdown on 23 January and resumed work and production on 20 March. From February to March 2020, human activities in Hubei decreased significantly, with the average particulate matter smaller than 2.5 μm (PM2.5) concentration standing at 40 μg/m3, which is 21% lower than the expected based on a linear fitting trend in thePM2.5 concentration in Hubei. By using the empirical orthogonal function (EOF) method, this paper comparatively analyzes the spatial-temporal variations of Hubei’s PM2.5 concentration anomaly in February and March 2020 and the same periods of 2016–2019. The results show that the daytime peak of the PM2.5 daily variation in Hubei in a low-emission scenario during COVID-19 declined significantly, to which human activities contributed the most. However, during nighttime, the PM2.5 peak became more prominent, and the meteorological conditions had a more noticeable effect on the PM2.5 concentration. In addition, during COVID-19, there was a great drop in PM2.5 pollution accumulated from local sources within the urban circle of Wuhan City, while an increase was seen in central-western Hubei due to the inter-regional pollutant transport. Thus, the high PM2.5 concentration center in the urban circle of Wuhan disappeared, but the pollution transport channel cities in central-western Hubei remained as high-PM2.5-concentration centers.

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Importance of regional PM2.5 transport and precipitation washout in heavy air pollution in the Twain-Hu Basin over Central China: Observational analysis and WRF-Chem simulation

Cited by 61 publications

References 51 publications

Changes in the Distribution Pattern of PM2.5 Pollution over Central China

Changes in the Distribution Pattern of PM2.5 Pollution over Central China

Understanding the distribution and drivers of PM2.5 concentrations in the Yangtze River Delta from 2015 to 2020 using Random Forest Regression

Impact of Inter-Regional Transport in a Low-Emission Scenario on PM2.5 in Hubei Province, Central China

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