Früher|Nächster

Satellite observations of the return-to-work over China during the period of COVID-19

  • role： First author第一作者
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Aerospace Information Research Institute of Chinese Academy of Sciences and Beijing Normal University, Beijing100101, China

  • Email：taojh@radi.ac.cn
  • Introduction：陶金花，1979年生,女,副研究员, 研究方向大气环境遥感的理论和应用。E-mail: taojh@radi.ac.cn
TAO Jinhua1,  
  • role： Corresponding author通信作者
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Aerospace Information Research Institute of Chinese Academy of Sciences and Beijing Normal University, Beijing100101, China

  • Email：fanmeng@radi.ac.cn
  • Introduction：范萌，1986年生，女，助理研究员，研究方向大气环境遥感的理论和应用。E-mail: fanmeng@radi.ac.cn
FAN Meng1*,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Aerospace Information Research Institute of Chinese Academy of Sciences and Beijing Normal University, Beijing100101, China

GU Jianbin1,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Aerospace Information Research Institute of Chinese Academy of Sciences and Beijing Normal University, Beijing100101, China

    University of Chinese Academy of Sciences, Beijing 100049, China

CHEN Liangfu12

Resümee

As the coronavirus COVID-19 broke out in the Chinese city of Wuhan and spread across China in late January 2020, governments at all levels in China introduced many policies (e.g. closing factories and schools, staying indoors and clearing street) to limit the further transmission of the illness. Chinese industrial activity was impacted and the return-to-work was delayed by the combination of the Chinese New Year holiday and COVID-19 outbreak. And with the abatement of COVID-19 in China, many provinces have downgraded their emergency response levels. Industrial factories stared to re-open, and people gradually returned to their jobs. In this paper, based on the satellite data, we compared and analyzed the temporal and spatial variations of industrial hot spot and tropospheric NO2 VCDs before and after the COVID-19 outbreak to estimate the situation of return-to back rate in China.Generally, several heavy industrial sectors with high-energy consuming (e.g. smelting industries, petrochemical industries and cement industries) have a close relationship with heat-related activities, and the heat emissions can reflect the level of energy consumption to some extent. Therefore, such industrial thermal anomalies have the potential to be detected by satellites sensors with infrared channels. NO2 primarily comes from fossil fuels burning, such as industrial emissions, power plants and vehicles, and it is a key indicator of industrial activities. NO2 measured by satellite from high above Earth’s surface are a good indicator of the geographical location of air pollution because NO2 has a life span of about a day, and thus is concentrated near its sources.Here, the industrial hot spots and the tropospheric NO2 Vertical Column Density (VCD) data over China during the periods from January to February in 2020 and 2019, respectively, were used for evaluating the impact of COVID-19 outbreak on China’s return-to-work. The industrial hot spots were extracted from the fires/thermal anomalies results which were retrieved by the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the new generation of polar-orbiting satellite, Suomi National Polar-orbiting Partnership (NPP). The tropospheric NO2 VCD data were directly obtained from the NO2 standard product of Ozone Monitoring Instrument (OMI) on Aura satellite.Our results indicate that there is a significant reduction of levels of energy consumption and NO2 emissions in February 2020, compared to those of both January 2020 and February 2019. Since the end of the Chinese New Year holiday on February 3, 2020, the number, range of distribution and density of industrial hot spots over China has been steadily rising. Except for a small amount of industrial hot spots still being detected in Wuhan, Huangshi and Ezhou, no more industrial hot spot was monitored in other cities of Hubei province in February 2020, meaning that there is no sign of return-to-work in the whole Hubei province. As the coronavirus epidemic eases in China, although the number of industrial hot spots increased remarkably over Jing-Jin-Ji region, the FRPs and tropospheric NO2 VCDs of most grids with increasing spots were still at low levels, compared to the same period in 2019. It means that production capacities of most heavy industries are limited under the influence of COVID-19 outbreak. Until the early March, both the number and averaged FRP of industrial hot spots began to gradually rise, which reflects the increasing return-to-work rate of heavy industries over most regions of China.

Schlüsselwort

remote sensing;industrial hot spot;energy consumption;NO2;return-to-work;COVID-19 outbreak;OMI;VIIRS

References

  1. 1.
    Bucsela E J, Krotkov N A, Celarier E A, Lamsal L N, Swartz W H, Bhartia P K, Boersma K F, Veefkind J P, Gleason J F and Pickering K E. 2013. A new stratospheric and tropospheric NO2 retrieval algorithm for nadir-viewing satellite instruments: applications to OMI. Atmospheric Measurement Techniques, 6(10): 2607-2626
  2. 2.
    De Foy B, Lu Z F and Streets D G. 2016. Satellite NO2 retrievals suggest china has exceeded its NOx reduction goals from the twelfth five-year plan. Scientific Reports, 6(1): 35912
  3. 3.
    Krotkov N A, Mclinden C A, Li C, Lamsal L N, Celarier E A, Marchenko S V, Swartz W H, Bucsela E J, Joiner J, Duncan B N, Boersma K F, Veefkind J P, Levelt P F, Fioletov V E, Dickerson R R, He H, Lu Z and Streets D G. 2015. Aura OMI observations of regional SO2 and NO2 pollution changes from 2005 to 2014. Atmospheric Chemistry and Physics Discussions, 15(19): 26555-26607
  4. 4.
    Liu Y X, Hu CM, Zhan WF, Sun C, Murch B and Ma L. 2018. Identifying industrial heat sources using time-series of the viirs nightfire product with an object-oriented approach. Remote Sensing of Environment, 204: 347-365
  5. 5.
    Schroeder W, Oliva P, Giglio L and Csiszar I A. 2014. The new VIIRS 375 m active fire detection data product: algorithm description and initial assessment. Remote Sensing of Environment, 143: 85-96
  6. 6.
    Zhou Y, Zhao F, Wang S X, Liu W L and Wang L T. 2018. A method for monitoring iron and steel factory economic activity based on satellites. Sustainability, 10(6): 1935

Lesen Sie die ganze Passage

The above content is generated by Large Model Translation. The translated content is for reference only. We do not assume any commercial or legal responsibilty for any consequences arising from the use of our website