scholarly journals The relationship between meteorological factors and mumps incidence in Guangzhou, China, 2005–2012:

2014 ◽  
Vol 10 (8) ◽  
pp. 2421-2432 ◽  
Author(s):  
Qiongying Yang ◽  
Zhicong Yang ◽  
Haiyuan Ding ◽  
Xiao Zhang ◽  
Zhiqiang Dong ◽  
...  
Keyword(s):  
Meteorological Factors ◽  
The Relationship

scholarly journals The relationship between meteorological factors and the risk of bacillary dysentery in Hunan Province, China

Weather ◽  
2018 ◽  
Vol 74 (4) ◽  
pp. 148-153 ◽  
Author(s):  
Xuewen Li ◽  
Ning Wang ◽  
Guoyong Ding ◽  
Xiaomei Li ◽  
Xiaojia Xue
Keyword(s):  
Bacillary Dysentery ◽  
Meteorological Factors ◽  
Hunan Province ◽  
The Relationship

Meteorological Factors Affected Dew Condensation in Marsh Ecosystem

2014 ◽  
Vol 535 ◽  
pp. 360-363 ◽  
Author(s):  
Ying Ying Xu ◽  
Bai Xing Yan ◽  
Hui Zhu
Keyword(s):  
Meteorological Factors ◽  
Meteorological Condition ◽  
Sanjiang Plain ◽  
Dew Point ◽  
Nutrient Cycle ◽  
The Sanjiang Plain ◽  
Dew Formation ◽  
Key Factor ◽  
The Relationship ◽  
Dew Amount

Dew is one of crucial factors in the water and nutrient cycle in wetland ecosystem, especially playing an important role in the water and nutrients balance. Identifying the meteorological factors which affect the formation of dew is necessary. The meteorological condition is the key factor of dew condensing; therefore, it is necessary to identify the relationship between meteorological factors and dew formation. Dew amount was monitored and collected in the Sanjiang Plain. The highest mean dew amounts at Sanjiang Plain were observed in Craex lasiocarpa community (0.130mm night-1). Nearly 50% dew events correspond to the smallest yields (<0.04 mm="" night="" sup="">-1) and it is implies there are around half days are unsuitable for dew condensation in Craex lasiocarpa community. Our study impies that dew data, taken in growthing season of 2003 to 2005 and 2008, correlated positive with relative humidity, dew point temperature, and vapour pressure.

The Relationship and Regression Analysis of Urban Water Supply and Temperature

2012 ◽  
Vol 256-259 ◽  
pp. 2420-2423
Author(s):  
Heng Hua Shi ◽  
Wen Guo Weng ◽  
Zheng Gan Zhai ◽  
Yuan Yuan Li
Keyword(s):  
Regression Analysis ◽  
Water Supply ◽  
Meteorological Factors ◽  
Supply System ◽  
Scientific Management ◽  
Urban Water ◽  
Urban Water Supply ◽  
Analysis Method ◽  
Factors Affecting ◽  
The Relationship

Urban water supply system and the people’s daily life are closely related. In addition to the urban population, the structure and the scale of economic, the factors affecting the requirement of urban water supply included the meteorological factors such as temperature. Based on Pearson product-moment correlation coefficient, we analyze the relationship between urban water supply and temperature with the actual data of Beijing from 2008 year to 2009 year, and get regression fitting function with multiple regression analysis method. The analysis result can provide the basis for scientific management and accurately predict urban water supply.

scholarly journals The relationship between flowering phenology and pollen seasons of Alnus Miller

2012 ◽  
Vol 65 (2) ◽  
pp. 57-66 ◽  
Author(s):  
Agnieszka Dąbrowska ◽  
Bogusław Michał Kaszewski
Keyword(s):  
Wind Speed ◽  
Pollen Season ◽  
Meteorological Factors ◽  
Airborne Pollen ◽  
Gravimetric Method ◽  
Air Humidity ◽  
Inflorescence Development ◽  
Relative Air Humidity ◽  
Pollen Seasons ◽  
The Relationship

The dynamics of flowering and pollen release in anemophilous plants and the length of the particular phases depend largely on the geobotanical features of a region, its climate, meteorological factors, biological characteristics of vegetation, and abundance of pollen resources. The aim of the study was to determine the relationship between the flowering phases in eight <i>Alnus</i> taxa and the dynamics of occurrence and abundance of airborne pollen grains as well as the meteorological factors (maximum and minimum temperature, relative air humidity, maximum wind speed, and precipitation). The flowering phenophases and pollen seasons were studied in 2008–2011. Phenological observations of flowering were conducted in the Maria Curie-Skłodowska University Botanical Garden in Lublin and they involved the following taxa: <i>Alnus crispa</i> var. <i>mollis</i>, <i>A. glutinosa</i>, <i>A. incana</i>, <i>A. incana</i> ‘Aurea’, <i>A. incana</i> ‘Pendula’, <i>A. maximowiczii</i>, <i>A. rubra</i> and <i>A. subcordata</i>. Spearman’s r correlation coefficients were calculated in order to determine the relationship between the dynamics of inflorescence development and meteorological conditions. Aerobiological monitoring using the gravimetric method was employed in the determination of <i>Alnus</i> pollen content in the air. The annual phenological cycles in 2008-2011 varied distinctly in terms of the time of onset of successive flowering phases in the <i>Alnus</i> taxa studied, which depended largely on the taxonomic rank and meteorological factors. The following flowering sequence was revealed in the 2008-2011 growing seasons: <i>A. subcordata</i> (December or January), <i>A. incana</i> ‘Pendula’, <i>A. incana</i>, <i>A. maximowiczii</i>, <i>A. rubra</i>, <i>A. glutinosa</i>, <i>A. incana</i> ‘Aurea’ (February or March), and <i>A. crispa</i> var. <i>mollis</i> (April). The study demonstrated that the pollen of the taxa persisted in the air, on average, from mid-December to early May. The mean length of the flowering period, which coincided with various phases of the pollen season, was 17 days. The <i>Alnus</i> pollen season in 2008 started at the end of January and lasted until mid-March. In 2009, 2010, and 2011, the beginning of the pollen season was recorded in the first week of March and the end in the first week of April. The maximum concentration of airborne <i>Alnus</i> pollen was found at the full bloom stage of mainly <i>A. glutinosa</i> and <i>A. rubra</i>. Inflorescence development was most closely related to temperature and relative air humidity; there was a weaker relationship with wind speed and precipitation.

scholarly journals PCA-Based Identification of Built Environment Factors Reducing PM2.5 Pollution in Neighborhoods of Five Chinese Megacities

Atmosphere ◽  
2022 ◽  
Vol 13 (1) ◽  
pp. 115
Author(s):  
Ming Chen ◽  
Fei Dai
Keyword(s):  
Built Environment ◽  
Meteorological Factors ◽  
Principal Component ◽  
Rate Of Change ◽  
Key Factors ◽  
Environment Factors ◽  
Pollution Levels ◽  
Principal Factors ◽  
Predicted Values ◽  
The Relationship

Air pollution, especially PM2.5 pollution, still seriously endangers the health of urban residents in China. The built environment is an important factor affecting PM2.5; however, the key factors remain unclear. Based on 37 neighborhoods located in five Chinese megacities, three relative indicators (the range, duration, and rate of change in PM2.5 concentration) at four pollution levels were calculated as dependent variables to exclude the background levels of PM2.5 in different cities. Nineteen built environment factors extracted from green space and gray space and three meteorological factors were used as independent variables. Principal component analysis was adopted to reveal the relationship between built environment factors, meteorological factors, and PM2.5. Accordingly, 24 models were built using 32 training neighborhood samples. The results showed that the adj_R2 of most models was between 0.6 and 0.8, and the highest adj_R2 was 0.813. Four principal factors were the most important factors that significantly affected the growth and reduction of PM2.5, reflecting the differences in green and gray spaces, building height and its differences, relative humidity, openness, and other characteristics of the neighborhood. Furthermore, the relative error was used to test the error of the predicted values of five verification neighborhood samples, finding that these models had a high fitting degree and can better predict the growth and reduction of PM2.5 based on these built environment factors.

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