Spatiotemporal characteristics of air pollutants and their associated health risks in '2+26' cities in China during 2016-2020 heating seasons.

To understand characteristics of air pollutants and their associated health risks in recent heating seasons in China, ambient monitoring data of six air pollutants in '2 + 26' cities in Beijing-Tianjin-Hebei and its surrounding areas (known as the BTH2+26 cities) during 2016-2020 heating seasons was analyzed. Results show that daily average concentrations of PM2.5, PM10, SO2, NO2, and CO dropped significantly in BTH2+26 cities from the 2016-2017 heating season to 2019-2020 heating season, while 8h O3 increased markedly. During 2016-2020 heating seasons, annual average values of total excess risks (ERtotal) were 2.3% mainly contributed by PM2.5 (54.4%) and PM10 (36.1%). With PM2.5 pollution worsening, PM10 and NO2 were the important contribution factors of the enhanced ERtotal. Higher health-risk based air quality index (HAQI) values were mainly concentrated in the western Hebei and northern Henan. HAQI showed spatial agglomeration effect in four heating seasons. Impact factors of HAQI varied in different heating seasons. These findings can provide useful insights for China to further propose effective control strategies to alleviate air pollution in the future.

Enhanced secondary pollution offset reduction of primary emissions during COVID-19 lockdown in China.

To control the spread of the 2019 novel coronavirus (COVID-19), China imposed nationwide restrictions on the movement of its population (lockdown) after the Chinese New Year of 2020, leading to large reductions in economic activities and associated emissions. Despite such large decreases in primary pollution, there were nonetheless several periods of heavy haze pollution in eastern China, raising questions about the well-established relationship between human activities and air quality. Here, using comprehensive measurements and modeling, we show that the haze during the COVID lockdown was driven by enhancements of secondary pollution. In particular, large decreases in NOx emissions from transportation increased ozone and nighttime NO3 radical formation, and these increases in atmospheric oxidizing capacity in turn facilitated the formation of secondary particulate matter. Our results, afforded by the tragic natural experiment of the COVID-19 pandemic, indicate that haze mitigation depends upon a coordinated and balanced strategy for controlling multiple pollutants.

Impact of clean air action on the PM2.5 pollution in Beijing, China: Insights gained from two heating seasons measurements.

Comprehensive observations have been carried out in Beijing to investigate the impact of the Clean Air Action implemented in 2013 on changes in aerosol chemistry characteristics in heating seasons of 2016-2017 and 2017-2018. Results showed that PM2.5, SO2, NO2, NH3, O3 and CO concentrations decreased by 40.9%, 46.0%, 29.0%, 40.6%, 11.0% and 44.4%, respectively. Significant decreases were also observed for NO3- (32.5%), SO42- (52.9%), NH4+ (56.0%), Cl- (64.6%) and K+ (68.2%), on average. Enhanced PM2.5 pollution has changed from sulfate-driven to nitrate-driven. The decrease in SO2 was more significant than NO2 as a response to one reason of the larger decrease in SO42- concentration. The formation of sulfate was dominated by heterogeneous reactions in two heating seasons. Low pH could facilitate more efficient conversion of SO2 to sulfate. Photochemical reactions played a much more important role in the formation of nitrate in the second heating season, especially in the daytime. The major source regions for sulfate and nitrate were identified by back trajectories and the potential source function (PSCF). More nitrate was brought into Beijing when air masses coming from polluted regions in the southwest prevailed in 2017-2018 heating season. Thus, regional joint prevention and control are of great importance in the achievement of an effective reduction in PM2.5 pollution in the future.

Cause of PM2.5 pollution during the 2016-2017 heating season in Beijing, Tianjin, and Langfang, China.

To investigate the cause of fine particulate matter (particles with an aerodynamic diameter less than 2.5 µm, PM2.5) pollution in the heating season in the North China Plain (specifically Beijing, Tianjin, and Langfang), water-soluble ions and carbonaceous components in PM2.5 were simultaneously measured by online instruments with 1-hr resolution, from November 15, 2016 to March 15, 2017. The results showed extreme severity of PM2.5 pollution on a regional scale. Secondary inorganic ions (SNA, i.e., NO3-+SO42+ NH4+) dominated the water-soluble ions, accounting for 30%-40% of PM2.5, while the total carbon (TC, i.e., OC + EC) contributed to 26.5%-30.1% of PM2.5 in the three cities. SNA were mainly responsible for the increasing PM2.5 pollution compared with organic matter (OM). NO3- was the most abundant species among water-soluble ions, but SO42- played a much more important role in driving the elevated PM2.5 concentrations. The relative humidity (RH) and its precursor SO2 were the key factors affecting the formation of sulfate. Homogeneous reactions dominated the formation of nitrate which was mainly limited by HNO3 in ammonia-rich conditions. Secondary formation and regional transport from the heavily polluted region promoted the growth of PM2.5 concentrations in the formation stage of PM2.5 pollution in Beijing and Langfang. Regional transport or local emissions, along with secondary formation, made great contributions to the PM2.5 pollution in the evolution stage of PM2.5 pollution in Beijing and Langfang. The favourable meteorological conditions and regional transport from a relatively clean region both favored the diffusion of pollutants in all three cities.

[Chemical Composition Characteristics and Source Apportionment of PM2.5 During Winter in Taiyuan].

To study the characteristics and sources of PM2.5 pollution in Taiyuan urban area in winter, PM2.5 and its chemical components (water-soluble ions, carbon components, and trace elements) and gaseous pollutants (SO2, NO2) were monitored by online instruments in January 2017. Combined with meteorological data, the characteristics of PM2.5 and its chemical components were analyzed. Also, source apportionment of PM2.5 was conducted by using positive matrix factorization (PMF). The results showed that the mean mass concentration of PM2.5 on polluted days (239.92 µg·m-3) was 5.70 times as much as that on clean days. The concentrations of the main chemical components of PM2.5 on polluted days, SO42-, NO3-, NH4+, Cl-, OC, and EC, were 7.04, 5.76, 6.51, 5.62, 4.06, and 4.70 times their respective values on clean days. The sulfur oxidation ratios (SOR) and the nitrogen oxidation ratios (NOR) on polluted days were 0.12 and 0.19, respectively, which were higher than those in clean days, indicating that secondary transformation was more significant on polluted days. The results of the PMF source apportionment showed that the contributions of secondary sources (35.06%), coal combustion (30.19%), and vehicle emissions (24.25%) were higher on polluted days than on clean days, with increases of 18.03%, 7.39% and 2.10%, respectively. Thus, air pollution control strategies should pay more attention to controlling secondary source precursors on the basis of controlling the primary emission sources on polluted days.

[Concentration Characteristics and Sources of Trace Metals in PM2.5 During Wintertime in Beijing].

To study the characteristics and sources of trace metals in PM2.5 during wintertime in Beijing, PM2.5 samples were collected from December 2014 to January 2015 by a middle volume sampler in the urban area of Beijing for 30 consecutive days. The mass concentration of PM2.5 was measured by filter membrane weighting method, and 16 kinds of trace metals were determined by inductively couple plasma-mass spectrometry (ICP-MS). In addition, the pollution characteristics and sources of trace metals were analyzed by enrichment factor (EF) method and factor analysis, respectively. The results showed that the concentrations of five elements (i. e. K, Ca, Fe, Al and Mg) accounted for 90.7% of the total metal elements. The concentrations of the metal elements changed obviously between day and night. Compared with daytime, crustal elements like Mg and Al decreased by more than 30% while anthropogenic elements like Cu and Pb increased by more than 40% in nighttime. Although the concentrations of metal elements increased by nearly one time in heavy pollution days compared with clean days, the mass percent of which in PM2.5 decreased from 10.9% in clean days to 4.6% in heavy pollution days. This result suggested the accumulation of metal elements in heavy pollution days had a minor contribution to the increased mass concentration of PM2.5. As the pollution episode progressed, anthropogenic elements (Cu,Zn,As,Se,Ag and Cd) increased faster than crustal elements (Al,Mg,Ca,Mn and Fe), which showed ratios ranging from 2.9 to 5.3 for anthropogenic elements and ratios ranging from 1.2 to 1.8 for crustal elements, when compared between heavy pollution days and clean days. In addition, the EF value of anthropogenic elements was also increased in the pollution days, indicating the concentrations of these elements was further influenced by the anthropogenic sources. Factor analysis showed that metal elements of PM2.5 during wintertime of Beijing were mainly from coal combustion and biomass burning, motor vehicle and industry emissions, and re-suspension of road dust, with the contributions of 34.2%,25.5% and 17.1%, respectively.