[Analysis of O3 Pollution Affected by a Succession of Three Landfall Typhoons in 2020 in Eastern China].

Based on air quality monitoring, surface meteorological data, wind profile radar observation, and the HYSPLIT model, the characteristics and causes of O3 pollution in eastern China during the period of the typhoons BAVI, MAYSAK, and HAISHEN from August 26 to September 8, 2020 were analyzed. The results showed that during the succession of the three landfall typhoons, the O3 pollution sites in Beijing Tianjin Hebei and its surrounding areas (BTHS) and the Yangtze River Delta (YRD) exceeded 50%. During the HAISHEN period, O3 pollution days in the two regions reached 2.22 d and 2.97 d, respectively, with significant persistence characteristics. The location of the typhoon had an obvious influence on O3 concentration. When the typhoons were located within the 24h warning line, the O3 concentrations in BTHS and YRD were relatively low. When the typhoons were located between the 24 h and 48 h warning lines, the O3 concentration in BTHS was the highest. When the typhoons moved north of 34°N, the YRD was most prone to regional O3 pollution. O3 pollution in Shanghai mainly occurred under the control of the northward air flow to the west side of the typhoons, and the regional transport from the upstream area had a significant impact on the increase in O3 and its precursor concentrations. The downdraft below 1 000 m maintained O3 at a high concentration at night. In Jinan, O3 pollution mainly occurred under the control of the subtropical high and typhoon periphery. The downdraft prevailed in the middle and lower levels during the O3 pollution. From August 28 to 30, under the control of the subtropical high, the pollutants were mainly accumulated locally, and some of them were transmitted within the province, showing a "double high" phenomenon of O3 and PM2.5. From September 5 to 8, under the influence of HAISHEN peripheral circulation, the regional transport was obvious, and the O3 concentration increased earlier than that of PM2.5.

Contrast-enhanced magnetic resonance angiography for monitoring an embolized renal artery aneurysm: A case report and literature review.

This case report describes a 69-year-old male patient with a renal artery aneurysm that was followed up with contrast-enhanced magnetic resonance angiography at 8 months after coil embolization treatment. Due to the disappearance of residual lumen with few metal artifacts, the therapeutic effect was satisfactory. At present, the indications for the treatment of renal artery aneurysms are still controversial and there are very few reports of postembolization images of renal artery aneurysms, with no criteria for reintervention and few reports for monitoring the embolized aneurysms. Further reports and research are still needed for the treatment of this rare disease.

[Influencing Factors of Long-term Variations on Gridded PM2.5 of Typical Regions in China Based on GAM Model].

This study investigates annually-averaged surface PM2.5 concentrations with the spatial resolution of 0.01°×0.01° to explore spatio-temporal variations and influencing factors of annual PM2.5 over typical regions in China during the period of 1998-2016, applying the generalized additive model (GAM). Regionally-averaged PM2.5 concentrations of five typical regions are ranked from high to low as follows:East China (40.5 µg·m-3) > North China (37.4 µg·m-3) > South China (27.8 µg·m-3) > Northeast China (23.7 µg·m-3) > Sichuan Basin (22.4 µg·m-3). The PM2.5 over Northeast China showed a linear increasing trend, while in other regions, PM2.5 tended to increase from 1998 to 2007 and decrease after 2007. PM2.5 concentrations over typical regions were all stably distributed which clearly exhibited areas with high PM2.5 values. For the single influencing factor GAM model of PM2.5 concentration, all influencing factors passed the significance test. The most influential factors with regard to the variations in the PM2.5 concentration differed among typical regions. In the multiple-influencing-factors-GAM model of PM2.5 concentration, all factors exhibited a non-linear relationship with PM2.5, and they accounted for 87.5%-92% (average 89.0%) of variations in the PM2.5 concentration, suggesting a good model fit. The most significant influencing factors on PM2.5 concentrations were YEAR and LON-LAT in all typical regions. Meteorological factors have different impacts on PM2.5 concentrations among the typical regions. The three most influential meteorological factors in the five typical regions ranked from high to low are as follows:tp > v10 > ssr for Northeast China; temp > tp > msl for North China; temp > tp > ssr for East and Central China; temp > RH > blh for South China; tp > temp > u10 for the Sichuan Basin. Our results demonstrated that the GAM model could quantitatively analyze influencing factors in long-term variations of the regional PM2.5 concentration, which is important for the assessment of PM2.5 pollution.

[Relationship Between Atmospheric Visibility and PM2.5 Concentrations and Distributions].

Monitoring data were used to analyze the relationships among relative humidity (RH), visibility, and PM2.5 concentrations. A strong, linear relationship expression between the extinction coefficient and PM2.5 concentrations at different relative humidities is proposed. The mean correlation coefficient at RH 40%-90% was higher than 0.75 for most of Central and Eastern China, and reached 0.9 in Beijing. Comparatively, the extinction efficiency of PM2.5 was much larger in Beijing, the Yangzi River Delta Region, and Sichuan than in other regions. However, the influence of RH on visibility varied from region to region. In Beijing, RH dominated the decrease in visibility when RH>90%, while in Guangzhou, this was the case when RH>80%. From 1980 to 1996, the annual variation in PM2.5 concentrations was not significant in Beijing and the PM2.5 concentrations were significantly higher than in the 2000s because of the dominant mode of heating. From 1997 to 2009, PM2.5 concentrations in Beijing showed a slow downward trend, and from 2010 to 2012, showed an upward trend. Since 1980, PM2.5 concentrations in the entire country have been rising. PM2.5 concentrations have always been higher in North China than in other parts of the country.