Based on monitoring data of air quality and corresponding meteorological observation data in Zhumadian City during 2013-2015,temporalspatial distribution characteristics and influence factors of air pollution were ana...Based on monitoring data of air quality and corresponding meteorological observation data in Zhumadian City during 2013-2015,temporalspatial distribution characteristics and influence factors of air pollution were analyzed. The results showed that >Grade II of pollution occupied a certain proportion in Zhumadian City throughout the year,and annual pollution probabilities at three stations were 11%,11% and 6%; serious pollution occurred for six times at three stations,and they all occurred in autumn and winter; pollution probabilities at three stations in autumn and winter were 18%,17% and 12%,and pollution situation in autumn and winter was more serious than that in spring and summer,and seasonal sequence of pollution frequency from low to high was spring,summer,autumn and winter. Seen from three monitoring stations,there was little difference between new and old industrial zones. Since Branch II of China Meheco Topfond Pharma Co.,Ltd. which represented largescale pollution source took pollution prevention measures,pollution was relatively light,but serious pollution was easy to appear. Seen from temporal change of pollutant concentration,monthly distribution characteristics of three kinds of air pollutants( SO_2,NO_2 and PM_(10)) showed typical one-peak-one valley pattern,and peak occurred during December-January,while valley was during July-August. Due to straw burning,monthly change curve of PM_(10) concentration had two peaks in June and October. Dekad change characteristics of three kinds of air pollutants also showed one-peak-one-valley pattern,and peak occurred from middle dekad of December to middle dekad of January,while valley was from early dekad of July to last dekad of August. The concentration correlation among three kinds of pollutants was the most significant at station 3.Additionally,concentration correlation was significant in autumn and winter,but was relatively weaker in spring and summer. The correlation between pollutant concentration and meteorological factors in the same period was the most significant in autumn,followed by winter. Negative correlation between horizontal visibility and pollutant concentration was extremely significant in winter. There was positive correlation between air pressure and pollutant concentration in summer and autumn,while the correlation was unobvious in winter and spring. There was negative correlation between air temperature and pollutant concentration,which was the most significant in autumn. Negative correlation between relative humidity and pollutant concentration was significant in summer and autumn. Total cloud cover showed significantly positive correlation with pollutant concentration in winter,but the correlation was unobvious in other seasons. Average wind velocity and NO_2 concentration maintained significantly negative correlation in whole year,and there was significantly negative correlation between average wind velocity and concentrations of other two kinds pollutants in winter,but the correlation was worse in other seasons.展开更多
Based on the data of meteorological elements obtained at Jiujiang Meteorological Station and Lushan Meteorological Station from 1999 to 2008,the temporal variation characteristics of cloud landscape in Lushan Mountain...Based on the data of meteorological elements obtained at Jiujiang Meteorological Station and Lushan Meteorological Station from 1999 to 2008,the temporal variation characteristics of cloud landscape in Lushan Mountain and its relationship with temperature,precipitation,relative humidity and wind speed were analyzed.The results showed that the monthly variation of cloud landscape in Lushan Mountain had two peaks in one year,and the number of days with cloud landscape was the largest in spring and the smallest in autumn.There was no obvious correlation between the monthly average number of days with cloud landscape and monthly average temperature,but there was an obvious positive correlation between the monthly average number of days with cloud landscape and relative humidity.Rainfall usually occurred on the day or the day before the occurrence of cloud landscape.On the day when cloud landscape appears,relative humidity was generally more than 80%,and average wind speed was less than 4.5 m/s.Meanwhile,there was an inversion layer at low altitudes.展开更多
Landscape characteristics influence meteorological factors, thus affect the occurrence and nature of dust storm events. The present study investigates the spatiotemporal characteristics of six meteorological factors ...Landscape characteristics influence meteorological factors, thus affect the occurrence and nature of dust storm events. The present study investigates the spatiotemporal characteristics of six meteorological factors （wind velocity, wind direction, air temperature, relative humidity （RH）, photo synthetically active radiation （PAR）, and solar radiation） over different landscape types （shifting-sand frontier, semi-fixed sandy land, fixed sandy land, and the inner region of an oasis） before and after dust storms during four typical dust storm events in an oasis-desert ecotone in Cele, Xinjiang, China. The results show that the average wind velocity decreased significantly from the shifting-sand frontier to the inner oasis, which was mainly attributable to the vegetation coverage. Before the dust storm events, there were obvious differences in air temperature and RH either in the horizontal or vertical direction over the different landscape types. However, these factors were very similar during and following the dust storm events. PAR and solar radiation were significantly reduced during the dust storm events and the subsequent sand-blowing and floating-dust conditions. This effect was much stronger than during similar weather conditions without dust storm events such as sand-blowing and overcast and/or rainy days. Additionally, the variation in the meteorological factors among the different landscapes was also affected by the prevailing wind direction during the dust storm events. However, the landscape type slightly changed the prevailing wind direction, with the greatest dispersion distribution of wind direction in the inner oasis. The findings of this study are helpful for understanding the function of landscape types in the occurrence of dust storms, as well as for providing a theoretical basis for prevention of dust storms.展开更多
The characteristics of fine particulate pollution(PM10 and PM2.5) were measured at urban and suburban sites in Jinan during the 2008-2009 heating and non-heating seasons.The results showed that PM10 and PM2.5 pollutio...The characteristics of fine particulate pollution(PM10 and PM2.5) were measured at urban and suburban sites in Jinan during the 2008-2009 heating and non-heating seasons.The results showed that PM10 and PM2.5 pollution was quite serious,and PM mass concentration was higher during the heating season than the non-heating season.PM was the highest in the chemical factory and lowest in the development zone.The mass concentrations of PM10 and PM2.5 were linearly related,and the mass concentration ratio of PM2.5/PM10 was up to 0.59 in urban areas.PM pollution in Jinan was related to local meteorological factors:PM2.5 mass concentration and humidity were positively correlated,and PM2.5 mass concentration was negatively correlated with both click on the temperature and wind speed,although wind speed varied more.展开更多
为了揭示我国北方水稻田生态系统的碳通量动态特征及其对气象因子的响应,利用盘锦市水稻田生态系统观测站2018—2020年净碳交换量(NEE)观测数据,分析盘锦市水稻田NEE年变化、日变化特征,以及植被总初级生产力(GPP)日变化和季节变化;对比...为了揭示我国北方水稻田生态系统的碳通量动态特征及其对气象因子的响应,利用盘锦市水稻田生态系统观测站2018—2020年净碳交换量(NEE)观测数据,分析盘锦市水稻田NEE年变化、日变化特征,以及植被总初级生产力(GPP)日变化和季节变化;对比NEE与风向、净辐射关系,最后按季节对比地温对植被呼吸(Reco)的影响,计算生态系统呼吸温度敏感性(Q_(10))。结果表明,NEE的年总量都为负值,其中2018年NEE总量最大,为-574.09 g C/(m^(2)·y);NEE的年变化与风速呈正相关,与日照呈负相关;NEE的日变化为“U”型,GPP的日变化为倒“U”型,中午达到峰值,日变化值在夏季最大;NEE高值对应的风向是W、WSW、SW和NE、ENE;NEE低值对应的风向是SSE、S和NNW、NW;NEE绝对值随净辐射的增加而增大,有时出现NEE峰值滞后于净辐射的情况。GPP年值呈下降趋势,Reco年际变化较小。夏季Reco比其他季节高2.0~6.0倍。2019夏季呼吸强度随地温增值达到0.85 g C/(m^(2)·d)。计算2019年夏季Q_(10)值达到4.84。2018年夏季平均气温较高、温度日较差较小、风速较大共同促成了NEE2018年高值。而2020年6—7月降水量偏少造成2020年NEE值偏低。Reco与土壤温度存在明显的指数关系。Q_(10)值在夏季最高,是其他季节的1.9~2.6倍。展开更多
文摘Based on monitoring data of air quality and corresponding meteorological observation data in Zhumadian City during 2013-2015,temporalspatial distribution characteristics and influence factors of air pollution were analyzed. The results showed that >Grade II of pollution occupied a certain proportion in Zhumadian City throughout the year,and annual pollution probabilities at three stations were 11%,11% and 6%; serious pollution occurred for six times at three stations,and they all occurred in autumn and winter; pollution probabilities at three stations in autumn and winter were 18%,17% and 12%,and pollution situation in autumn and winter was more serious than that in spring and summer,and seasonal sequence of pollution frequency from low to high was spring,summer,autumn and winter. Seen from three monitoring stations,there was little difference between new and old industrial zones. Since Branch II of China Meheco Topfond Pharma Co.,Ltd. which represented largescale pollution source took pollution prevention measures,pollution was relatively light,but serious pollution was easy to appear. Seen from temporal change of pollutant concentration,monthly distribution characteristics of three kinds of air pollutants( SO_2,NO_2 and PM_(10)) showed typical one-peak-one valley pattern,and peak occurred during December-January,while valley was during July-August. Due to straw burning,monthly change curve of PM_(10) concentration had two peaks in June and October. Dekad change characteristics of three kinds of air pollutants also showed one-peak-one-valley pattern,and peak occurred from middle dekad of December to middle dekad of January,while valley was from early dekad of July to last dekad of August. The concentration correlation among three kinds of pollutants was the most significant at station 3.Additionally,concentration correlation was significant in autumn and winter,but was relatively weaker in spring and summer. The correlation between pollutant concentration and meteorological factors in the same period was the most significant in autumn,followed by winter. Negative correlation between horizontal visibility and pollutant concentration was extremely significant in winter. There was positive correlation between air pressure and pollutant concentration in summer and autumn,while the correlation was unobvious in winter and spring. There was negative correlation between air temperature and pollutant concentration,which was the most significant in autumn. Negative correlation between relative humidity and pollutant concentration was significant in summer and autumn. Total cloud cover showed significantly positive correlation with pollutant concentration in winter,but the correlation was unobvious in other seasons. Average wind velocity and NO_2 concentration maintained significantly negative correlation in whole year,and there was significantly negative correlation between average wind velocity and concentrations of other two kinds pollutants in winter,but the correlation was worse in other seasons.
文摘Based on the data of meteorological elements obtained at Jiujiang Meteorological Station and Lushan Meteorological Station from 1999 to 2008,the temporal variation characteristics of cloud landscape in Lushan Mountain and its relationship with temperature,precipitation,relative humidity and wind speed were analyzed.The results showed that the monthly variation of cloud landscape in Lushan Mountain had two peaks in one year,and the number of days with cloud landscape was the largest in spring and the smallest in autumn.There was no obvious correlation between the monthly average number of days with cloud landscape and monthly average temperature,but there was an obvious positive correlation between the monthly average number of days with cloud landscape and relative humidity.Rainfall usually occurred on the day or the day before the occurrence of cloud landscape.On the day when cloud landscape appears,relative humidity was generally more than 80%,and average wind speed was less than 4.5 m/s.Meanwhile,there was an inversion layer at low altitudes.
基金Supported by the Special Major Science and Technology Projects in Xinjiang Uygur Autonomous Region(201130106-1)China Meteorological Administration Special Public Welfare Research Fund(GYHY201106025)+1 种基金Xinjiang Normal University Doctor of Geography Supporting ProgramXinjiang Lake Environment and Resources Laboratory of Arid Zone(XJDX0909-2013-08)
文摘Landscape characteristics influence meteorological factors, thus affect the occurrence and nature of dust storm events. The present study investigates the spatiotemporal characteristics of six meteorological factors （wind velocity, wind direction, air temperature, relative humidity （RH）, photo synthetically active radiation （PAR）, and solar radiation） over different landscape types （shifting-sand frontier, semi-fixed sandy land, fixed sandy land, and the inner region of an oasis） before and after dust storms during four typical dust storm events in an oasis-desert ecotone in Cele, Xinjiang, China. The results show that the average wind velocity decreased significantly from the shifting-sand frontier to the inner oasis, which was mainly attributable to the vegetation coverage. Before the dust storm events, there were obvious differences in air temperature and RH either in the horizontal or vertical direction over the different landscape types. However, these factors were very similar during and following the dust storm events. PAR and solar radiation were significantly reduced during the dust storm events and the subsequent sand-blowing and floating-dust conditions. This effect was much stronger than during similar weather conditions without dust storm events such as sand-blowing and overcast and/or rainy days. Additionally, the variation in the meteorological factors among the different landscapes was also affected by the prevailing wind direction during the dust storm events. However, the landscape type slightly changed the prevailing wind direction, with the greatest dispersion distribution of wind direction in the inner oasis. The findings of this study are helpful for understanding the function of landscape types in the occurrence of dust storms, as well as for providing a theoretical basis for prevention of dust storms.
基金Supported by Natural Science Foundation of Shandong Province(Grant No.Z2008E04)"Austria-China"international government cooperation project"Control of Fine Particles"(Nr.CN10/2007)Dr.Foundation of Shandong Jianzhu University(XNBS0920)
文摘The characteristics of fine particulate pollution(PM10 and PM2.5) were measured at urban and suburban sites in Jinan during the 2008-2009 heating and non-heating seasons.The results showed that PM10 and PM2.5 pollution was quite serious,and PM mass concentration was higher during the heating season than the non-heating season.PM was the highest in the chemical factory and lowest in the development zone.The mass concentrations of PM10 and PM2.5 were linearly related,and the mass concentration ratio of PM2.5/PM10 was up to 0.59 in urban areas.PM pollution in Jinan was related to local meteorological factors:PM2.5 mass concentration and humidity were positively correlated,and PM2.5 mass concentration was negatively correlated with both click on the temperature and wind speed,although wind speed varied more.
文摘为了揭示我国北方水稻田生态系统的碳通量动态特征及其对气象因子的响应,利用盘锦市水稻田生态系统观测站2018—2020年净碳交换量(NEE)观测数据,分析盘锦市水稻田NEE年变化、日变化特征,以及植被总初级生产力(GPP)日变化和季节变化;对比NEE与风向、净辐射关系,最后按季节对比地温对植被呼吸(Reco)的影响,计算生态系统呼吸温度敏感性(Q_(10))。结果表明,NEE的年总量都为负值,其中2018年NEE总量最大,为-574.09 g C/(m^(2)·y);NEE的年变化与风速呈正相关,与日照呈负相关;NEE的日变化为“U”型,GPP的日变化为倒“U”型,中午达到峰值,日变化值在夏季最大;NEE高值对应的风向是W、WSW、SW和NE、ENE;NEE低值对应的风向是SSE、S和NNW、NW;NEE绝对值随净辐射的增加而增大,有时出现NEE峰值滞后于净辐射的情况。GPP年值呈下降趋势,Reco年际变化较小。夏季Reco比其他季节高2.0~6.0倍。2019夏季呼吸强度随地温增值达到0.85 g C/(m^(2)·d)。计算2019年夏季Q_(10)值达到4.84。2018年夏季平均气温较高、温度日较差较小、风速较大共同促成了NEE2018年高值。而2020年6—7月降水量偏少造成2020年NEE值偏低。Reco与土壤温度存在明显的指数关系。Q_(10)值在夏季最高,是其他季节的1.9~2.6倍。
