scholarly journals SEASONAL VARIATION CHARACTERISTICS OF WATER STRUCTURE AND QUANTITATIVE ANALYSIS OF SEAWATER EXCHANGE IN OHFUNATO BAY

2004 ◽  
pp. 69-80 ◽  
Author(s):  
Tadashi HIBINO ◽  
Hiroichi TSURUYA ◽  
Naoki ITABASHI
Keyword(s):  
Seasonal Variation ◽  
Quantitative Analysis ◽  
Water Structure ◽  
Variation Characteristics ◽  
Seawater Exchange

scholarly journals Seasonal Variation Characteristics of Bacteria and Fungi in PM2.5 in Typical Basin Cities of Xi’an and Linfen, China

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 809
Author(s):  
Sen Wang ◽  
Wanyu Liu ◽  
Jun Li ◽  
Haotian Sun ◽  
Yali Qian ◽  
...  
Keyword(s):  
Seasonal Variation ◽  
Relative Abundance ◽  
Pathogenic Bacteria ◽  
High Throughput Sequencing ◽  
Fine Particulate Matter ◽  
Ecological Functions ◽  
Factors Affecting ◽  
Bacterial Phyla ◽  
Variation Characteristics ◽  
Bacteria And Fungi

Microorganisms existing in airborne fine particulate matter (PM2.5) have key implications in biogeochemical cycling and human health. In this study, PM2.5 samples, collected in the typical basin cities of Xi’an and Linfen, China, were analyzed through high-throughput sequencing to understand microbial seasonal variation characteristics and ecological functions. For bacteria, the highest richness and diversity were identified in autumn. The bacterial phyla were dominated by Proteobacteria, Actinobacteria, Firmicutes, and Bacteroidetes. Metabolism was the most abundant pathway, with the highest relative abundance found in autumn. Pathogenic bacteria (Pseudomonas, Acinetobacter, Serratia, and Delftia) were positively correlated with most disease-related pathways. Besides, C cycling dominated in spring and summer, while N cycling dominated in autumn and winter. The relative abundance of S cycling was highest during winter in Linfen. For fungi, the highest richness was found in summer. Basidiomycota and Ascomycota mainly constituted the fungal phyla. Moreover, temperature (T) and sulfur dioxide (SO2) in Xi’an, and T, SO2, and nitrogen dioxide (NO2) in Linfen were the key factors affecting microbial community structures, which were associated with different pollution characteristics in Xi’an and Linfen. Overall, these results provide an important reference for the research into airborne microbial seasonal variations, along with their ecological functions and health impacts.

Seasonal variation of raindrop size distribution over a coastal station Thumba: A quantitative analysis

2019 ◽  
Vol 229 ◽  
pp. 86-99 ◽  
Author(s):  
S. Lavanya ◽  
N.V.P. Kirankumar ◽  
S. Aneesh ◽  
K.V. Subrahmanyam ◽  
S. Sijikumar
Keyword(s):  
Seasonal Variation ◽  
Quantitative Analysis ◽  
Size Distribution ◽  
Coastal Station ◽  
Raindrop Size Distribution ◽  
Raindrop Size

scholarly journals Spatial distribution and seasonal variation characteristics of global atmospheric moisture recycling

2014 ◽  
Vol 63 (9) ◽  
pp. 099201
Author(s):  
Su Tao ◽  
Lu Zhen-Yu ◽  
Zhou Jie ◽  
Hou Wei ◽  
Li Yue ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Seasonal Variation ◽  
Atmospheric Moisture ◽  
Moisture Recycling ◽  
Variation Characteristics

scholarly journals Study on Seasonal Variation Characteristics of Forest Phytoncide in Ulsan Metropolitan Trails

2013 ◽  
Vol 22 (11) ◽  
pp. 1415-1419 ◽  
Author(s):  
Heung Jai Park ◽  
Bong Gwan Yu ◽  
Sun Ho Park ◽  
Jin Yeol Lee ◽  
Yoo Sik Hahm ◽  
...  
Keyword(s):  
Seasonal Variation ◽  
Variation Characteristics

NDVI Changes of the Nansi Lake in Shandong Province of China

2014 ◽  
Vol 919-921 ◽  
pp. 1659-1662
Author(s):  
Chun Ling Liang
Keyword(s):  
Remote Sensing ◽  
Seasonal Variation ◽  
Remote Sensing Data ◽  
Wetland Vegetation ◽  
Shandong Province ◽  
Nansi Lake ◽  
Sensing Data ◽  
Vegetation Indexes ◽  
Vegetation Activity ◽  
Variation Characteristics

The normalized difference vegetation indexes (NDVI) of the Nansi Lake wetland in Shandong province is are calculated on the basis of MSS, TM and ETM+ remote sensing data collected by the Landsat satellites. The characteristics of seasonal vegetation activity of the Nansi Lake during 1973-2011 were revealed. The seasonal variation characteristics of wetland vegetation in Nansi Lake are not identical in the last 40 years. The NDVI in spring (P=0.0216) first decreased and then increased; The NDVI in summer (P=0.0007) and winter (P=0.0189) present a significant decreasing trend. The variation of the NDVI in autumn is small.

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