Effect of different cold air intensities and their lagged effects on outpatient visits for respiratory illnesses in Handan in different seasons

本文利用2016年到2019年邯郸市气象要素和呼吸系统疾病门诊数据,分析了不同季节不同强度的冷空气过程及其对呼吸系统疾病的影响,结果显示:尽管呼吸系统疾病在冬季高发,夏季最低,但冷空气对呼吸系统疾病的影响在夏,春季最大,就诊人数分别在冷空气日后两天和五天增加18.4%和13.3%,而冬季就诊人数在冷空气日后三天仅增加3.2%.冷空气对疾病影响的滞后时间在夏,秋和冬季随冷空气强度的增加而减少,而春季的滞后时间总是很长.这些发现可为科学应对气候异常导致的人群健康风险提供针对性依据.

Distribution Characteristics of Air Anions in Beidaihe in Different Ecological Environments

Qinhuangdao is a provincial municipality under the jurisdiction of Hebei Province and a coastal city in China. Beidaihe is a district under the jurisdiction of Qinhuangdao and is a famous seaside scenic area. Alliance Peak, located in Beidaihe seashore scenic West. Jinshan mouth is the peak of the Union Peak, located in the easternmost Beidaihe waterfront. In this paper, we use the observed data of air negative ions in the Beidaihe, Qinhuangdao, Jinshanzui and Lianfeng Mountains for seven years to study the distribution characteristics of negative air ions in different ecological environments through meteorological observation. Research shows that the annual mean of air anion concentration fluctuates less. The annual mean is 1730 ind·cm-3, and the difference between the highest and lowest concentrations is 535 ind·cm-3. The average air anion concentration was the highest in August at 7785 ind·cm-3 and the lowest in January at 365 ind·cm-3. Negative air ions have obvious spatial characteristics, and negative ion concentrations of the sea and forest air are significantly high. The average annual mean of the sea is 3902 ind·cm-3, and that of the forest is 5403 ind·cm-3. The concentration of air anion changes daily, and daytime concentration is significantly lower than nighttime concentration. The highest peak appears at night or in the morning, while the lowest value appears between noon and afternoon. Inter-annual features and concentration of negative air ions, as well as annual rain days, total rainfall, thunderstorm days, and average relative humidity, are negatively related to the annual average temperature and sunshine hours. However, in the average concentration of negative air ions, the average correlation test of meteorological elements was insignificant. The air anion concentration is negatively correlated with the PM2.5 concentration of fine particulate matter. The concentrations of nitrogen dioxide, sulfur dioxide, and carbon monoxide in the fine particulate matter are negatively correlated with the ozone concentration, which is positively correlated with ozone concentration and is tested by significance. Atmospheric discharge (thunderstorm) can produce a considerable amount of air anion. Air negative ions are an important indicator of air quality, which is of great significance to the living environment. The distribution of negative ions in the study space and its influencing factors in order to provide a basis for air quality assessment in the region and provide references for the long-term research on air anion in different urban areas.

Effects of Simulated Heat Wave and Ozone on High Fat Diet ApoE Deficient Mice

Objective To discuss the cardiac toxicities of a heat waves and ozone exposure on cardiovascular diseases(CVDs) and explore a possible mechanism. Methods The incidence of ozone exposure combined with heat wave was simulated in the Shanghai Meteorological and Environmental Animal Exposure System(Shanghai-METAS). A total of 64 Apo E-/-mice, matched by weight, were randomly divided into 8 groups and exposed to heat wave conditions or ozone. The levels of creatine kinase(CK), D-lactate dehydrogenase(D-LDH), intercellular adhesion molecule 1(sICAM-1), tumor necrosis factor alpha(TNF-α), nitric oxide(NO), endothelin-1(ET-1), D-dimer(D2 D), plasminogen activator inhibitor-1(PAI-1) and blood lipid in plasma and heat shock protein-60(HSP60), hypoxia inducible factor 1 alpha(HIF-1α), interleukin-6(IL-6), C-reactive protein(CRP), superoxide dismutase(SOD), and malondialdehyde(MDA) in hearts were measured after exposure. Results The levels of all indicators, except for SOD, increased with the ozone-only exposure. However, cardiac damage was most significant when the heat wave conditions were combined with severe ozone exposure. Moreover, the levels of CK, D-LDH, NO, PAI-1, sICAM-1, and TNF-α in plasma increased significantly(P < 0.05), and the contents of HSP60, HIF-1α, CRP, and MDA in hearts increased considerably(P < 0.05), but the activity of SOD decreased significantly. In addition, the levels of four blood lipid items remarkably increased(except the level of HDL-C which decreased significantly) with ozone exposure. Conclusion A short-term exposure to a heat wave and ozone causes severe toxic effects on the heart. Cardiac damage was most significant under combined heat wave and severe ozone exposure simulations.

Observational Subseasonal Variability of the PM_(2.5) Concentration in the Beijing-Tianjin-Hebei Area during the January 2021 Sudden Stratospheric Warming

It is still not well understood if subseasonal variability of the local PM_(2.5) in the Beijing-Tianjin-Hebei(BTH)region is affected by the stratospheric state.Using PM_(2.5) observations and the ERA5 reanalysis,the evolution of the air quality in BTH during the January 2021 sudden stratospheric warming(SSW)is explored.The subseasonal variability of the PM_(2.5) concentration after the SSW onset is evidently enhanced.Stratospheric circumpolar easterly anomalies lasted for 53 days during the January-February 2021 SSW with two evident stratospheric pulses arriving at the ground.During the tropospheric wave weakening period and the intermittent period of dormant stratospheric pulses,the East Asian winter monsoon weakened,anomalous temperature inversion developed in the lower troposphere,anomalous surface southerlies prevailed,atmospheric moisture increased,and the boundary layer top height lowered,all of which favor the accumulation of pollutant particulates,leading to two periods of pollution processes in the BTH region.In the phase of strengthened East Asian winter monsoon around the very beginning of the SSW and another two periods when stratospheric pulses had reached the near surface,opposite-signed circulation patterns and meteorological conditions were observed,which helped to dilute and diffuse air pollutants in the BTH region.As a result,the air quality was excellent during the two periods when the stratospheric pulse had reached the near surface.The increased subseasonal variation of the regional pollutant particulates after the SSW onset highlights the important role of the stratosphere in the regional environment and provides implications for the environmental prediction.

Seasonal and Diurnal Variations of Cloud Systems over the Eastern Tibetan Plateau and East China:A Cloud-resolving Model Study

The seasonal and diurnal variations of cloud systems are profoundly affected by the large-scale and local environments.In this study,a one-year-long simulation was conducted using a two-dimensional cloud-resolving model over the Eastern Tibetan Plateau(ETP)and two subregions of Eastern China:Southern East China and Central East China.Deep convective clouds(DCCs)rarely occur in the cold season over ETP,whereas DCCs appear in Eastern China throughout the year,and the ETP DCCs are approximately 20%−30%shallower than those over Eastern China.Most strong rainfall events(precipitation intensity,PI>2.5 mm h−1)in Eastern China are related to warm-season DCCs with ice cloud processes.Because of the high elevation of the ETP,the warm-season freezing level is lower than in Eastern China,providing favorable conditions for ice cloud processes.DCCs are responsible for the diurnal variations of warm-season rainfall in all three regions.Warm-season DCCs over the ETP have the greatest total cloud water content and frequency in the afternoon,resulting in an afternoon rainfall peak.In addition,rainfall events in the ETP also exhibit a nocturnal peak in spring,summer,and autumn due to DCCs.Strong surface heat fluxes around noon can trigger or promote DCCs in spring,summer,and autumn over the ETP but produce only cumulus clouds in winter due to the cold and dry environment.

Vertical Distribution Characteristics of Precipitation Cloud in Tianjin Based on L-band Sounding Data

Based on L-band sounding data,threshold method of relative humidity was used to analyze vertical distribution characteristics of precipitation cloud system in Tianjin region.The results showed that main precipitation cloud system affecting Tianjin is cold and warm mixed cloud,followed by cold cloud,and precipitation of warm cloud is less.During May-November,precipitation of cold and warm mixed cloud is dominant,and it is dominant by precipitation of cold cloud from January to April.In four seasons,the precipitation frequency of double-layer cloud is the most,and precipitation of single-layer cloud mainly appears during March-November,and peak is in June.Peak of cloud system with three or more layers all appears in July and August.The cold cloud and warm cloud catalysts should be selected respectively for artificial precipitation enhancement in Tianjin.In winter,cold cloud catalyst operation is selected;in spring,summer and autumn,the cold cloud catalyst is spread in the cold cloud area,and the warm cloud catalyst is distributed in the warm cloud area according to the conditions of cloud layer.

Quantitatively determine the dominant driving factors of the spatial–temporal changes of vegetation NPP in the Hengduan Mountain area during 2000-2015

The Hengduan mountain area,located in the upper reaches of the Yangtze River of China,is an important ecological barrier that significantly impacts the climate and ecological environment of the surrounding region and western China as a whole.This paper introduces the gravity center model used to analyze the spatial-temporal variation patterns of vegetation Net Primary Productivity(NPP)from 2000 to 2015,which were determined by the use of MOD17 A3 NPP products.Additionally,the dominant driving factors of the spatial–temporal changes of vegetation NPP of the Hengduan Mountain area were quantitatively determined with a geographical detector over 2000-2015.The results revealed that:(1)From 2000 to 2015,there was an increasing trend of vegetation NPP in the Hengduan mountain area.Throughout the whole study region,the vegetation NPP with a mean value of 611.37 gC·m^(-2)·a^(-1) indicated a decreasing trend from southeast to northwest in terms of spatial distribution.(2)The gravity centers of vegetation NPP in 2000-2015 were mainly concentrated in Zhongdian County.During the study period,the gravity center of vegetation NPP moved northward,which indicated that the increment and increasing rate of vegetation NPP in the northern parts were greater than that of the southern areas.(3)The vegetation NPP showed a moderately positive correlation with temperature,accumulated temperature(>10℃),and sunshine,while there was an overall negative relationship between NPP and precipitation.(4)The dominant factors and interactive dominant factors changed in different subregions over different segments of the study period.The dominant factors of most sub-regions in Hengduan mountain were natural factors,and the climate change factors played an increasingly greater role over the 16 years of the study period.

Multi-Fractal Analysis of Daily Air Temperature Time Series in Coastal Areas of China

In this article,the Multi-Fractal Detrended Fluctuation Analysis(MF-DFA)method is adopted to study the temperature,i.e.,the maximum temperature(Tmax),mean temperature(Tavg)and minimum(Tmin)air temperature,multifractal characteristics and their formation mechanism,in the typical temperature zones in the coastal regions in Guangdong,Jiangsu and Liaoning Provinces.Following are some terms and concepts used in the present study.Multifractality is defined as a term that characterizes the complexity and self-similarity of objects,and fractal characteristics depict the distribution of probability over the whole set caused by different local conditions or different levels in the process of evolution.Fractality strength denotes the fluctuation range of the data set,and long-range correlation(LRC)measures the stability of the climate system and the trend of climate change in the future.In this research,it is found that the internal stability and feedback mechanism of climate systems in different regions show regional differences.Furthermore,the research also proves that the Tavg,Tmaxand Tminof the above three provinces are highly multifractal.The temperature series multifractality of each province decreases in the order of temperature series multifractality of Liaoning>temperature series multifractality of Guangdong>temperature series multifractality of Jiangsu,and the corresponding long-range correlations follow the same order.It reveals that the most stable temperature series is that of Liaoning,followed by the temperature series of Guangdong,and the most unstable one is that of Jiangsu.Liaoning has the most stable climate system,and it will thus be less responsive to the future climate warming.The stability of the climate system in Jiangsu is the weakest,and its temperature fluctuation will continue to increase in the future,which will probably result in the meteorological disasters of high temperature and heat wave there.Guangdong possesses the strongest degree of multifractal strength,which indicates that its internal temperature series fluctuation is the largest among the three regions.The Tmaxmultifractal strength of Jiangsu is stronger than that of Liaoning,while the Tavgand Tminmultifractal strength of Jiangsu is weaker than that of Liaoning,showing that Jiangsu has a larger internal Tmaxfluctuation than Liaoning does,while it has a smaller fluctuation of Tavgand Tminthan Liaoning does.Guangdong and Liaoning both show the strongest Tminmultifractal strength,followed by Tavgmultifractal strength,and the weakest Tmax multifractal strength.However,Jiangsu has the strongest Tmax,followed by Tavg,and the weakest Tmin.The research findings show that these phenomena are closely related to solar radiation,monsoon strength,topography and some other factors.In addition,the multifractality of the temperature time series results from the negative power-law distribution and long-range correlation,in which the long-range correlation influence of temperature series itself plays the dominant role.With the backdrop of global climate change,this research can provide a theoretical basis for the prediction of the spatial-temporal air temperature variation in the eastern coastal areas of China and help us understand its characteristics and causes,and thus the present study will be significant for the environmental protection of coastal areas.

Features of the new climate normal 1991-2020 and possible influences on climate monitoring and prediction in China

An update on the climate norms each decade is recommended by the World Meteorological Organization(WMO)partly to keep pace with conditions as climate changes over time.In accordance with such update,this study documents the features of the new climate normal defined for 1991-2020 and its impacts on climate monitoring and prediction in China.With on-site observation and model prediction datasets,our analysis reveals that the new normal of national average precipitation of China during winter and summer is respectively 3.0 and 10.8 mm higher than that of the period 1981-2010.As a result,precipitation observations during 1961-2020 consistently fall below the new normal.The adjustment of thresholds for precipitation extremes with new climate normals results in a decrease of extreme precipitation occurrence by 0.2-0.8 d on average over the winter and summer seasons during 1961-2020.Meanwhile,the application of new climate normals induces more pronounced negative temperature anomalies across most areas of China.The adjustments of extreme temperature thresholds have led to an increased occurrence of extremely cold days by 1-2 d on average over 1961-2020,while the frequency of extremely hot days decreases by more than 1.4 d.Furthermore,it is implied that with the development of global warming,the baselines for temperature and precipitation are rising.The application of the new climate normal may result in the omission of relative threshold based extreme events,promoting increased focus on climate risk reduction studies.Additionally,the average anomaly sign consistency rates(Pcs)of precipitation and temperature anomaly predictions,relative to the new normal and produced by the Beijing Climate Center,are consistently lower than those relative to the old normal.This decrease in Pcs implies new challenges for climate prediction,especially for temperature prediction.