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Two persistent and heavy haze episodes during the COVID‐19 lockdown (from 20 Jan to 22 Feb 2020) still occur in northern China, when anthropogenic emissions, particularly from transportation sources, are greatly reduced. To investigate the underlying cause, this study comprehensively uses in‐situ measurements for ambient surface pollutants, reanalysis meteorological data and the WRF‐Chem model to calculate the contribution of NOx emission change and weather‐climate change to the "unexpectedly heavy" haze. Results show that a substantial NOx reduction has slightly decreased PM2.5 concentration. By contrast, the weakest East Asian winter monsoon (EAWM) in the 2019–2020 winter relative to the past decade is particularly important for haze occurrence. A warmer and moister climate is also favorable. Model results suggest that climate anomalies lead to a 25–50 μg m−3 increase of PM2.5 concentration, and atmospheric transport is also an important contributor to two haze episodes. The first haze is closely related to the atmospheric transport of pollutants from NEC to the south, and fireworks emissions in NEC are a possible amplifying factor that warrants future studies. The second one is caused by the convergence of a southerly wind and a mountain wind, resulting in an intra‐regional transport within BTH, with a maximal PM2.5 increment of 50–100 μg m−3. These results suggest that climate change and regional transport are of great importance to haze occurrence in China, even with significant emission reductions of pollutants. Plain Language Summary: During the COVID‐19 lockdown (from 20 Jan to 22 Feb 2020), anthropogenic emissions, particularly from transportation sources, are significantly reduced. However, there are still two heavy haze pollution events occurred in northern China. Our modeling study constrained by measurements show that the substantial NOx reduction only leads to a slight decrease in PM2.5 concentration. In contrast, the weakest East Asian winter monsoon in the 2019–2020 winter relative to the past decade is very important for the haze occurrence. Climate anomalies contribute 25–50 μg m−3 to the PM2.5 concentration. Atmospheric transport such as the transport of pollutants from Northeast China to the south and the intra‐regional transport within the Beijing‐Tianjin‐Hebei, also plays an important role in the haze formation. The results suggest that weather‐climate anomalies and regional transport can significantly worsen air quality during the COVID‐19 lockdown in northern China, in spite of significant reductions in air pollutants and precursors. Key Points: Emission reduction and two heavy haze episodes simultaneously occur in northern China during the COVID‐19 lockdownAnomalously warm and moist climate with a weak East Asian Winter Monsoon, and regional atmospheric transport contribute to COVID‐19 hazeA substantial reduction of NOx emission slightly mitigates haze during the lockdown period [ABSTRACT FROM AUTHOR]

A variety of climatological indices have been established to illustrate the impact of climate change on air pollution in China, but major facts for causing variations of air pollution attributed to climate change are still unclear. Here, using in‐situ PM2.5 (particles with the aerodynamic diameter less than 2.5 μm) measurement, atmospheric reanalysis data and a chemical transport model, we show that meridional distribution of PM2.5 loadings is strongly modulated by the intensity of East Asian winter monsoon (EAWM). The EAWM drives the heavily polluted zone in eastern China to migrate southward, i.e., under stronger EAWM, more southward migration of air pollution occurs. We expect that the migration will likely re‐distribute carbon sources‐ and sinks‐related ecosystem, posing a new challenge for the Chinese government, who needs to implement region‐different emission reduction plans in the future, to mitigate air pollution and to go carbon neutral. Plain Language Summary: The relationship between the severe air pollution in China and climate has drawn much attention from scientific community, which still remains unclear. In this study, we present that air pollution with high PM2.5 loadings in winter, China is significantly modulated by East Asian winter monsoon (EAWM) based on ambient PM2.5 measurements, atmospheric reanalysis data and the GEOS‐Chem model. We find that the change in EAWM intensity dominates the location of heavily polluted zone and its meridional distribution. Stronger EAWM generally drives the zone to migrate more southward in eastern China, highlighting the predominant role of EAWM in redistributing air pollution of China during wintertime. Under climate change, the inter‐annual variability and decadal oscillation of EAWM projected by CMIP5 and CMIP6 models indicate a southward migration of the heavily polluted zone in next decades, probably approaching the Yangtze River Delta. This result may pose new challenges in air pollution control for local governments in different regions regarding climatic influence. Key Points: East Asian winter monsoon strongly modulates PM2.5 levels meridionally in eastern ChinaUnder climate change, the heavily polluted zone will likely move southward to Yangtze River Delta in the next decadesChina needs to implement regional‐different emission reduction measures regarding to the influence of climate change [ABSTRACT FROM AUTHOR]

In this study, the Dynamical‐Statistical‐Analog Ensemble Forecast model for landfall typhoon precipitation (the DSAEF_LTP model), which has been developed by Ren et al., in 2020, is applied to precipitation simulations for super‐typhoon Lekima (2019), a tropical cyclone (TC) that produced heavy rainfall over eastern China. A new variable, TC intensity, is introduced into the generalized initial value (GIV) of the DSAEF_LTP model. Two different groups of simulation experiments, one group including the new TC intensity variable in the GIV and the other group excluding it, have been conducted. Results show that, with TC intensity, the ability of the DSAEF_LTP model to forecast heavy rainfall (i.e. accumulated precipitation exceeding thresholds of 250 and 100 mm) for Lekima is improved. Its threat score (TS) ranks the second compared with that of three numerical weather prediction models (i.e. ECMWF, GRAPES and GFS). Further study shows that three factors prevent the DSAEF_LTP model from achieving more satisfactory results for Lekima: the historically rare occurrence of extreme precipitation in northern China during Lekima, the increase of forecast track error when Lekima moved northwards, and the calculation of similarity between tracks of Lekima and historical TCs within an improper region (i.e. similarity region). To solve the third problem, new similarity region schemes are adopted that produce higher TS, in which case TS of precipitation greater than 100 mm (TS100) ranks first and TS of precipitation greater than 250 mm (TS250) gets closer to the first place. [ABSTRACT FROM AUTHOR]

Abstract: China has suffered severe air pollutions during wintertime as national industrialization and urbanization have been increasingly developed in the past decades. Recent studies suggest that climate change has important impacts on extreme haze events in northern China. This study uses reanalysis datasets to analyze the trend and variability of Siberian High (SiH) intensity, and its relationship with the Arctic temperature and sea ice cover (SIC) in past two decades. The results show that Arctic is warming accompanied by a rapid decline of SIC, while Eurasia is cooling and SiH intensity is gradually enhancing. The statistics illustrates that the SiH has a significantly positive correlation to the temperature (R = 0.70), and a significant anticorrelation to the SIC (R = −0.69), and this is because the warming Arctic and the reducing SIC enhanced the SiH. The enhanced SiH leads to strengthened northerly winds in the North China Plain (NCP). The WRF‐Chem model calculation reveals the strengthened northerly winds during the stronger SiH period in January 2016 produce a significant decrease in PM2.5 (particulate matter with aerodynamic diameter less than 2.5 µm) concentrations by 100–200 µg m−3 than that during the weaker one in January 2013. A sensitivity calculation figures out the reduction of PM2.5 concentrations due to a decrease of 50% in emissions is comparable to changes from the weak SiH condition to the strong SiH condition, suggesting that extreme climate variability in the past few years could have an equivalent impact as a consequence of a large emission reduction on wintertime air pollution in the NCP. [ABSTRACT FROM AUTHOR]

Background: The incidence of ketosis-prone type 2 diabetes is very low except for people of sub-Saharan African origin and African Americans. However, there also are some type 2 diabetes patients with diabetic ketosis without acidosis (DKWA). We question whether DKWA should be included as a subtype of ketosis-prone type 2 diabetes mellitus and compared the clinical characteristics of DKWA and diabetic ketoacidosis (DKA) patients., Methods: The study population consisted of 594 consecutive unrelated Chinese inpatients with newly diagnosed type 2 diabetes. Demographic and clinical characteristics (age, gender, family history of diabetes, body mass index, blood pressure and plasma lipid parameters) were recorded. The patients were divided into ketosis-resistant diabetes (KRD), DKWA and DKA groups on the basis of urinary ketones, blood pH and bicarbonate levels. The blood glucose and c-peptide levels of the patients were also evaluated., Results: The prevalence of KRD, DKWA and DKA were 78.33%, 19.72% and 1.95%, respectively, in the study population. The clinical characteristics of patients with DKWA group patients were similar to those with DKA, except that DKA patients had higher blood glucose and deteriorated β cell function., Conclusions: Diabetic ketosis without acidosis and DKA patients share similar clinical characteristics; DKWA should be considered ketosis-prone type 2 diabetes. Therefore, the prevalence of ketosis-prone type 2 diabetes might be underestimated., (Copyright © 2013 John Wiley & Sons, Ltd.)