Improvement of Air Pollution in China Inferred from Changes between Satellite-Based and Measured Surface Solar Radiation

Seasonal characterization of aerosol composition and sources in a polluted city in Central China

We characterized the aerosol composition and sources of particulate matter (PM) in Sanmenxia, a polluted city located in the Fen-Wei Plain region of Central China. The PM_2.5 concentration decreased by 18% from 72 μg m^-3 in 2014 to 59 μg m^-3 in 2019. All chemical species presented pronounced seasonal variations, with their highest concentrations in winter due to enhanced emissions and the frequent stagnant meteorological conditions. Nitrate was the major fraction of PM_2.5 during all seasons (35-41%) except summer (25%), while sulfate was a dominant species in summer (29%) compared to other seasons (16-18%) from July 2018 to June 2019. The detailed analysis of a wintertime severe haze episode that lasted for approximately half a month demonstrated that secondary aerosols, including secondary organic aerosol, sulfate, nitrate, and ammonium, contributed 89% to non-refractory PM₁ (NR-PM₁), indicating the remarkable role of secondary aerosol formation in air pollution in Sanmenxia. Positive matrix factorization analysis further showed considerably enhanced low-volatility oxygenated organic aerosol (OA) and hydrocarbon-like OA during severe haze episodes, while significant contributions in semi-volatile oxygenated OA and coal combustion OA during clean periods. Severe pollution events in the city were generally associated with air masses from the southwest, and we also found that aerosol species, especially secondary aerosol species, showed distinct forenoon increases that were caused by the subsidence of air pollutants aloft. Our results highlight that future air quality improvement would benefit substantially from a more efficient control of gaseous precursors, particularly the NO_x emissions from industry and vehicle emissions.

A New Long-Term Downward Surface Solar Radiation Dataset over China from 1958 to 2015

Downward surface solar radiation (Rs) plays a dominant role in determining the climate and environment on the Earth. However, the densely distributed ground observations of Rs are usually insufficient to meet the increasing demand of the climate diagnosis and analysis well, so it is essential to build a long-term accurate Rs dataset. The extremely randomized trees (ERT) algorithm was used to generate Rs using routine meteorological observations (2000–2015) from the Climate Data Center of the Chinese Meteorological Administration (CDC/CMA). The estimated Rs values were validated against ground measurements at the national scale with an overall correlation coefficient value of 0.97, a mean bias of 0.04 Wm⁻², a root-mean-square-error value of 23.12 Wm⁻², and a mean relative error of 9.81%. It indicates that the estimated Rs from the ERT-based model is reasonably accurate. Moreover, the ERT-based model was used to generate a new daily Rs dataset at 756 CDC/CMA stations from 1958 to 2015. The long-term variation trends of Rs at 454 stations covering 46 consecutive years (1970–2015) were also analyzed. The Rs in China showed a significant decline trend (−1.1 Wm⁻² per decade) during 1970–2015. A decreasing trend (−2.8 Wm⁻² per decade) in Rs during 1970–1992 was observed, followed by a recovery trend (0.23 Wm⁻² per decade) during 1992–2015. The recovery trends at individual stations were found at 233 out of 454 stations during 1970–2015, which were mainly located in southern and northern China. The new Rs dataset would substantially provide basic data for the related studies in agriculture, ecology, and meteorology.

Air Pollution Scenario over China during COVID-19

The unprecedented slowdown in China during the COVID-19 period of November 2019 to April 2020 should have reduced pollution in smog-laden cities. However, moderate resolution imaging spectrometer (MODIS) satellite retrievals of aerosol optical depth (AOD) show a marked increase in aerosols over the Beijing–Tianjin–Hebei (BHT) region and most of Northeast and Central China, compared with the previous winter. Fine particulate (PM2.5) data from ground monitoring stations show an increase of 19.5% in Beijing during January and February 2020, and no reduction for Tianjin. In March and April 2020, a different spatial pattern emerges, with very high AOD levels observed over 50% of the Chinese mainland, and including peripheral regions in the northwest and southwest. At the same time, ozone monitoring instrument (OMI) satellite-derived NO2 concentrations fell drastically across China. The increase in PM2.5 while NO2 decreased in BTH and across China is likely due to enhanced production of secondary particulates. These are formed when reductions in NOx result in increased ozone formation, thus increasing the oxidizing capacity of the atmosphere. Support for this explanation is provided by ground level air quality data showing increased volume of fine mode aerosols throughout February and March 2020, and increased levels of PM2.5, relative humidity (RH), and ozone during haze episodes in the COVID-19 lockdown period. Backward trajectories show the origin of air masses affecting industrial centers of North and East China to be local. Other contributors to increased atmospheric particulates may include inflated industrial production in peripheral regions to compensate loss in the main population and industrial centers, and low wind speeds. Satellite monitoring of the extraordinary atmospheric conditions resulting from the COVID-19 shutdown could enhance understanding of smog formation and attempts to control it.