Meteorological Factors Affected Dew Condensation in Marsh Ecosystem

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.

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The Effect of Climate Change on Variations in Dew Amount in a Paddy Ecosystem of the Sanjiang Plain, China

Advances in Meteorology ◽

10.1155/2015/793107 ◽

2015 ◽

Vol 2015 ◽

pp. 1-9 ◽

Cited By ~ 1

Author(s):

Yingying Xu ◽

Baixing Yan ◽

Jie Tang

Keyword(s):

Global Warming ◽

Relative Humidity ◽

Meteorological Data ◽

Warming Trend ◽

Sanjiang Plain ◽

Dew Point ◽

The Sanjiang Plain ◽

Growing Seasons ◽

Paddy Ecosystem ◽

Dew Amount

Due to global warming, a drying and warming trend has been observed over the last 50 years in the Sanjiang Plain of Heilongjiang Province, China, which could significantly affect the condensation of vapor in paddy ecosystems. Dew is a crucial factor in the water and nutrient cycling of farmland ecosystems, and it exerts an important influence on fertilization and other agricultural activities. In order to reveal the effects of global warming on dew variation in a paddy ecosystem, anin situexperiment was conducted in paddy fields in the Sanjiang Plain during the growing seasons of 2011 to 2013. Dew was collected and measured with a poplar stick. The results of correlation analysis between meteorological factors and dew intensity in the paddy ecosystem indicate that the dew point temperature and relative humidity significantly influenced the dew intensity. Based on synchronous meteorological data, a stepwise linear multivariation regression model was established to predict dew amount. The model successfully interpreted the relationship between simulated and measured dew intensity. The results suggest that a warmer and drier climate would lead to a reduction in dew amount because water cannot condense when relative humidity falls below 71%.

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Dew Amount in Marsh Monitoring in the Sanjiang Plain

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.522-524.34 ◽

2014 ◽

Vol 522-524 ◽

pp. 34-37

Author(s):

Ying Ying Xu ◽

Bai Xing Yan ◽

Hui Zhu

Keyword(s):

Wind Speed ◽

Sanjiang Plain ◽

Dew Point ◽

Atmospheric Moisture ◽

The Sanjiang Plain ◽

Point Temperature ◽

Dew Point Temperature ◽

Dew Amount

Dew is the condensation of atmospheric moisture on objects that have radiated sufficient heat to lower their temperature below the dew point temperature. Dew amount was collected by woodstick in Craex lasiocarpa which the main community at Sanjiang Plain. The average daily cumulated dew yield, which is the important parameter for dew harvesting, reach the peak in August or September. The result implies there are around one fifth days are unsuitable for dew condensation. Dew amount correlated negatively with wind speed.

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Temporal Analysis of the Relationship between Meteorological Factors and Pollen Abundance in Raleigh, North Carolina

10.35831/ccr.jg112019 ◽

2019 ◽

Author(s):

Julie Gareton

Keyword(s):

Climate Change ◽

North Carolina ◽

Meteorological Factors ◽

Dew Point ◽

Pollen Count ◽

Tree Pollen ◽

Pollen Counts ◽

Temperature And Precipitation ◽

The Relationship ◽

Seasonal Data

Introduction: Climate change affects both meteorological factors and plant processes. As earth’s average climate conditions warm, it is predicted that pollen will produce even more allergenic spores in areas where it already exists, like Raleigh, North Carolina, becoming a serious human health issue. Methods: In order to observe climate and pollen relationships, pollen counts are plotted against temperature, humidity (in the form of dew point temperature), and precipitation in Raleigh, North Carolina from February 2, 1999 to September 4, 2018. Linear regression tools in Microsoft Excel were used to analyze annual and seasonal data that had been aggregated by month. Results: The annual data revealed the strongest correlation between the increased temperature in the area and pollen count, particularly in tree pollen species. Conversely, the seasonal data for spring showed a stronger correlation between average precipitation and pollen count. Conclusions: The IPCC has predicted that temperature and precipitation will both continue to rise and, based on historical data, it is likely that the relationship between pollen and temperature, as supported by annual tree pollen data, as well as the relationship between pollen and precipitation, as supported by weed and grass seasonal pollen analysis, will increase the pollen counts in Raleigh. While a direct correlation cannot be concluded definitively, the results indicate that temperature is related to tree pollen count and precipitation is related to grass and weed pollen count. Keywords: pollen, climate change, temperature, precipitation, humidity

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Estimation of resistance force at steady-state sinkage for cylindrical wheel-typed lunar/planetary exploration rovers with function of push–pull locomotion

ROBOMECH Journal ◽

10.1186/s40648-020-00183-0 ◽

2020 ◽

Vol 7 (1) ◽

Author(s):

Daisuke Fujiwara ◽

Naoki Tsujikawa ◽

Tetsuya Oshima ◽

Kojiro Iizuka

Keyword(s):

Steady State ◽

Estimation Method ◽

Planetary Exploration ◽

Experimental Result ◽

Resistance Force ◽

Estimation Model ◽

Loose Soil ◽

Key Factor ◽

The Relationship ◽

Resistance Forces

Abstract Planetary exploration rovers have required a high traveling performance to overcome obstacles such as loose soil and rocks. Push-pull locomotion rovers is a unique scheme, like an inchworm, and it has high traveling performance on loose soil. Push-pull locomotion uses the resistance force by keeping a locked-wheel related to the ground, whereas the conventional rotational traveling uses the shear force from loose soil. The locked-wheel is a key factor for traveling in the push-pull scheme. Understanding the sinking behavior and its resistance force is useful information for estimating the rover’s performance. Previous studies have reported the soil motion under the locked-wheel, the traction, and the traveling behavior of the rover. These studies were, however, limited to the investigation of the resistance force and amount of sinkage for the particular condition depending on the rover. Additionally, the locked-wheel sinks into the soil until it obtains the required force for supporting the other wheels’ motion. How the amount of sinkage and resistance forces are generated at different wheel sizes and mass of an individual wheel has remained unclear, and its estimation method hasn’t existed. This study, therefore, addresses the relationship between the sinkage and its resistance force, and we analyze and consider this relationship via the towing experiment and theoretical consideration. The results revealed that the sinkage reached a steady-state value and depended on the contact area and mass of each wheel, and the maximum resistance force also depends on this sinkage. Additionally, the estimation model did not capture the same trend as the experimental results when the wheel width changed, whereas, the model captured a relatively the same trend as the experimental result when the wheel mass and diameter changed.

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Levels, Inventory, and Risk Assessment of Heavy Metals in Wetland Ecosystem, Northeast China: Implications for Snow Cover Monitoring

Water ◽

10.3390/w13162161 ◽

2021 ◽

Vol 13 (16) ◽

pp. 2161

Author(s):

Fuxiang Zhang ◽

Bo Meng ◽

Shang Gao ◽

Rupert Hough ◽

Peng Hu ◽

...

Keyword(s):

Heavy Metals ◽

Snow Cover ◽

Environmental Quality ◽

Regional Scale ◽

Class Ii ◽

Sanjiang Plain ◽

Preliminary Evaluation ◽

Monitoring Method ◽

The Sanjiang Plain ◽

Water Pollution Index

Snow cover is a unique environmental medium in cold regions that can cause potential risks to the ecological environment, due to the release of pollutants that are stored in it. In this study, the Qixing River wetland, located in the Sanjiang Plain of China, was taken as the target research area. Heavy metals in snow cover, including Cu, Ni, Cr, Cd, Pb, and Zn were measured at 19 sampling sites. The results showed that the average concentrations of heavy metals were: Zn (103.46 ± 39.16) > Pb (13.08 ± 4.99) > Cr (11.97 ± 2.82) > Ni (9.55 ± 4.96) > Cu (6.19 ± 1.79) > Cd (0.55 ± 0.25) μg·L−1. Cr and Zn were between Class I and Class II in the “Environmental Quality Standards for Surface Water” of China (GB3838-2002). Pb in snow exceeded the upper limit of Class II, and was significantly higher than concentrations measured in water samples from the Qixing River wetland (p < 0.05), indicating that atmospheric deposition during winter was the major source of Pb. The water pollution index (WPI) indicated that 61.0% of samples could be considered of “clean” status, while the contribution of Zn, Pb, and Cr to WPI were 33.3%, 21.0%, and 19.3%, respectively. A preliminary evaluation of heavy metal inventory in snow cover showed that the residue level of Zn was the highest (2313.57 ± 1194.67 μg·m−2), while Cd was the lowest (13.91 ± 10.45 μg·m−2). The areas with high residues of heavy metals were all located near the buffer zone of the wetland (except for Zn), where snow depth tended to be greatest. Exposure analysis indicated that the risks to winter resident birds from snow ingestion was minimal, but it should be noted that the exposure risk was higher in birds with lower bodyweights. This study provides important information and scientific knowledge on the pollution characteristics and residue inventory of heavy metals in wetland ecosystems, while the results can also provide a monitoring method, reflecting atmospheric environmental quality at a local or regional scale.

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Simulating Land-Use Changes and Predicting Maize Potential Yields in Northeast China for 2050

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18030938 ◽

2021 ◽

Vol 18 (3) ◽

pp. 938

Author(s):

Luoman Pu ◽

Jiuchun Yang ◽

Lingxue Yu ◽

Changsheng Xiong ◽

Fengqin Yan ◽

...

Keyword(s):

Land Use ◽

Food Security ◽

Northeast China ◽

Land Use Changes ◽

Sanjiang Plain ◽

Potential Production ◽

Potential Yield ◽

The Sanjiang Plain ◽

Ecological Zones ◽

The Future

Crop potential yields in cropland are the essential reflection of the utilization of cropland resources. The changes of the quantity, quality, and spatial distribution of cropland will directly affect the crop potential yields, so it is very crucial to simulate future cropland distribution and predict crop potential yields to ensure the future food security. In the present study, the Cellular Automata (CA)-Markov model was employed to simulate land-use changes in Northeast China during 2015–2050. Then, the Global Agro-ecological Zones (GAEZ) model was used to predict maize potential yields in Northeast China in 2050, and the spatio-temporal changes of maize potential yields during 2015–2050 were explored. The results were the following. (1) The woodland and grassland decreased by 5.13 million ha and 1.74 million ha respectively in Northeast China from 2015 to 2050, which were mainly converted into unused land. Most of the dryland was converted to paddy field and built-up land. (2) In 2050, the total maize potential production and average potential yield in Northeast China were 218.09 million tonnes and 6880.59 kg/ha. Thirteen prefecture-level cities had maize potential production of more than 7 million tonnes, and 11 cities had maize potential yields of more than 8000 kg/ha. (3) During 2015–2050, the total maize potential production and average yield decreased by around 23 million tonnes and 700 kg/ha in Northeast China, respectively. (4) The maize potential production increased in 15 cities located in the plain areas over the 35 years. The potential yields increased in only nine cities, which were mainly located in the Sanjiang Plain and the southeastern regions. The results highlight the importance of coping with the future land-use changes actively, maintaining the balance of farmland occupation and compensation, improving the cropland quality, and ensuring food security in Northeast China.

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

Human Vaccines & Immunotherapeutics ◽

10.4161/hv.29286 ◽

2014 ◽

Vol 10 (8) ◽

pp. 2421-2432 ◽

Cited By ~ 22

Author(s):

Qiongying Yang ◽

Zhicong Yang ◽

Haiyuan Ding ◽

Xiao Zhang ◽

Zhiqiang Dong ◽

...

Keyword(s):

Meteorological Factors ◽

The Relationship

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An Empirical Research on the Relationship between Real Estate Prices and Inflation

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.55-57.1992 ◽

2011 ◽

Vol 55-57 ◽

pp. 1992-1996

Author(s):

Tie Qun Li

Keyword(s):

Real Estate ◽

Stock Prices ◽

Test Analysis ◽

Social Demand ◽

The Real Estate ◽

Key Factor ◽

Negative Effect ◽

Labor Service ◽

Real Estate Prices ◽

The Relationship

The former researches referring to inflation and real estate prices concentrated mainly on the stock prices rather than the real estate prices. Owing to the enlarging ratio of real estate industry in national economy with each passing day, as well as the overheating real estate prices in recent years, the relationship between real estate prices and inflation is particularly vital to the monetary policy making for the monetary authorities. According to the test analysis of data from 2001 to 2009, it is found that real estate prices is Granger Cause of inflation while inflation is not the Granger Cause of real estate prices in this paper. Through the Effects of Wealth, Credit and Tobin, real estate prices drive the growth of social consumption and investments and expand the total social demand which possess an positive effect on inflation; nevertheless the rising of real estate prices causes the rising of currency for real estate purchasing, which, under the circumstance of that currency supply remains, will inevitably bring about the reduction of currency for other consumption and investments and restrain the total social demand which would mean a suppression of continuous rising of prices of other commodity and labor service. All these show that real estate also has a negative effect on inflation. The cancellations between the two effects make the long-term influence real estate bearing on inflation is not obvious. The experimental results indicate that when the price of real estate rises 1%, inflation only rises 0.058%. Consequently, a strict controlling of the amount of money issued is the key factor for keeping the over rapid rising of real estate prices from leading to inflation.

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Microbial CO2 production from surface and subsurface soil as affected by temperature, moisture, and nitrogen fertilisation

Soil Research ◽

10.1071/sr07144 ◽

2008 ◽

Vol 46 (3) ◽

pp. 273 ◽

Cited By ~ 12

Author(s):

Xiaobin Jin ◽

Shenmin Wang ◽

Yinkang Zhou

Keyword(s):

Soil Temperature ◽

Water Content ◽

Soil Water ◽

Soil Water Content ◽

Sanjiang Plain ◽

Co2 Production ◽

The Sanjiang Plain ◽

Subsurface Soil ◽

C Mineralisation ◽

Q10 Values

The Sanjiang Plain of north-east China is presently the second largest freshwater marsh in China. The drainage and use of marshes for agricultural fields occurred in the past 50 years, resulting in the increase in cultivated land from about 2.9 × 108 m2 in 1893 to 4.57 × 1010 m2 in 1994. Under human disturbance in the past half century, the environment in Sanjiang Plain has had significant change. We hypothesised that environmental factors such as soil moisture, soil temperature, and soil N levels affect the rates of soil organic C mineralisation and the nature of the controls on microbial CO2 production to change with depth through the soil profile in the freshwater marsh in the Sanjiang Plain. In a series of experiments, we measured the influence of soil temperature, soil water content, and nitrogen additions on soil microbial CO2 production rates. The results showed that Q10 values (the factor by which the CO2 production rate increases when the temperature is increased by 10°C) significantly increased with soil depth through the soil profile (P < 0.05). The average Q10 values for the surface soils were 2.7 (0–0.2 m), significantly lower than that (average Q10 values 3.3) for the subsurface samples (0.2–0.6 m) (P < 0.05), indicating that C mineralisation rates were more sensitive to temperature in subsurface soil horizons than in surface horizons. The maximum respiration rate was measured at 60% water hold capacity for each sample. The quadratic equation function adequately describes the relationship between soil respiration and soil water content, and the R2 values were > 0.80. The sensitivity of microbial CO2 production rate response to soil water content for surface soils (0–0.2 m) was slightly lower than for subsurface soils (0.2–0.6 m). The responses of actual soil respiration rates to nitrogen fertilisation were different for surface and subsurface soils. In the surface soils (0–0.2 m), the addition of N caused a slight decreased in respiration rates compared with the control, whereas, in the subsurface soils (0.2–0.6 m), the addition of N tended to increase microbial CO2 production rates, and the addition of 10 µg N/g soil treatment caused twice the increase in C mineralisation rates of the control. Our results suggested that the responses of microbial CO2 production to changes in soil moisture, soil temperature, and soil N levels varied with soil depth through the profile, and subsurface soil organic C was more sensitive to temperature increase and nitrogen inputs in the freshwater marsh of the Sanjiang Plain.

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