Effects of Meteorological Factors on PM10 Pollution in Yantai Urban Areas

2012 ◽  
Vol 178-181 ◽  
pp. 328-331
Author(s):  
Jian Guo Song ◽  
Ming Chang ◽  
Xin Zhi Wang ◽  
Wei Liu
Keyword(s):  
Relative Humidity ◽  
Frequency Distribution ◽  
Urban Areas ◽  
Meteorological Factors ◽  
Air Pressure ◽  
The Other ◽  
Average Temperature ◽  
The North

This paper makes analysis and statistics about the frequency distribution of average temperature, pressure, humidity and wind conditions between moderate pollution days of PM10(API>200) and conventional days from 2008 to 2010 in Yantai. The result shows that the frequency of PM10 pollution which occurred in winter is close to the sum of the other seasons. PM10 pollution days appears easily under such conditions: the average temperature below 10°C, average air pressure is higher than 101.0kPa, relative humidity is less than 70%, or average weed speed of 3-7m/s with the north-south wind.

‘The Colossus of the North’: One Man's Account of Queensland During the First World War

2004 ◽  
Vol 11 (1) ◽  
pp. 27-37
Author(s):  
Malcolm Saunders
Keyword(s):  
Twentieth Century ◽  
Urban Areas ◽  
First World War ◽  
The Other ◽  
Small Scale ◽  
World War ◽  
The North ◽  
The First World War ◽  
Principal Source ◽  
First World

Australians — not least of all historians and political scientists — have long wondered whether Queensland was any different from the other colonies/states. Some of the ways in which it differs from most of its southern sisters — such as its geographical size and decentralised population — have always been obvious. No less well known has been its pursuit of agrarian policies. For much of the second half of the nineteenth century and the first half of the twentieth century, governments of all political persuasions in Queensland preferred to develop primary rather than secondary industries, and consequently favoured rural rather than urban areas. An integral part of agrarianism was its emphasis on closer settlement — that is, breaking the pastoralists' (or squatters') hold over vast areas of land and making smaller and suitable plots of land available to men of limited means, people most often referred to almost romantically as ‘yeoman farmers’. Governments envisaged a colony or state whose economy was based less on huge industries concentrated in a few hands and situated in the cities than on a class of small-scale agriculturalists whose produce would not only feed the population but also be a principal source of wealth.

scholarly journals Epidemiological characteristics of bacillary dysentery from 2009 to 2016 and its incidence prediction model based on meteorological factors

2019 ◽  
Vol 24 (1) ◽  
Author(s):  
Qiuyu Meng ◽  
Xun Liu ◽  
Jiajia Xie ◽  
Dayong Xiao ◽  
Yi Wang ◽  
...  
Keyword(s):  
Urban Areas ◽  
Prediction Models ◽  
Mean Squared Error ◽  
Bacillary Dysentery ◽  
Meteorological Factors ◽  
Health Planning ◽  
Scientific Basis ◽  
Air Pressure ◽  
Support Vector ◽  
Epidemiological Characteristics

Abstract Background This study aimed to analyse the epidemiological characteristics of bacillary dysentery (BD) caused by Shigella in Chongqing, China, and to establish incidence prediction models based on the correlation between meteorological factors and BD, thus providing a scientific basis for the prevention and control of BD. Methods In this study, descriptive methods were employed to investigate the epidemiological distribution of BD. The Boruta algorithm was used to estimate the correlation between meteorological factors and BD incidence. The genetic algorithm (GA) combined with support vector regression (SVR) was used to establish the prediction models for BD incidence. Results In total, 68,855 cases of BD were included. The incidence declined from 36.312/100,000 to 23.613/100,000, with an obvious seasonal peak from May to October. Males were more predisposed to the infection than females (the ratio was 1.118:1). Children < 5 years old comprised the highest incidence (295.892/100,000) among all age categories, and pre-education children comprised the highest proportion (34,658 cases, 50.335%) among all occupational categories. Eight important meteorological factors, including the highest temperature, average temperature, average air pressure, precipitation and sunshine, were correlated with the monthly incidence of BD. The obtained mean absolute percent error (MAPE), mean squared error (MSE) and squared correlation coefficient (R2) of GA_SVR_MONTH values were 0.087, 0.101 and 0.922, respectively. Conclusion From 2009 to 2016, BD incidence in Chongqing was still high, especially in the main urban areas and among the male and pre-education children populations. Eight meteorological factors, including temperature, air pressure, precipitation and sunshine, were the most important correlative feature sets of BD incidence. Moreover, BD incidence prediction models based on meteorological factors had better prediction accuracies. The findings in this study could provide a panorama of BD in Chongqing and offer a useful approach for predicting the incidence of infectious disease. Furthermore, this information could be used to improve current interventions and public health planning.

scholarly journals Evaporation Of Snow and Ice In Scharffenbergbotnen, Dronning Maud Land, Antarctica

1990 ◽  
Vol 14 ◽  
pp. 342 ◽  
Author(s):  
Stig Jonsson ◽  
Per Holmlund
Keyword(s):  
Relative Humidity ◽  
Ablation Rate ◽  
The Other ◽  
Weather Data ◽  
The West ◽  
The North ◽  
Dronning Maud Land ◽  
Field Season ◽  
Weather Stations ◽  
North Western

Scharffenbergbotnen is a 3 × 6 km large basin of interior ice drainage on the north-western side of Heimefrontfjella in Dronning Maud Land, Antarctica. The elevation at the bottom of the depression is 1142 m a.s.l., while bedrock immediately to the south-east of this point rises to more than 2750 m. Ice enters the basin mainly from a low ice divide (1250 m a.s.l.) in the west but also through a 400 m high icefall in the east. Two separate blue-ice areas constitute approximately half the surface of the basin, while the other half is snow-covered. As part of SWEDARP (Swedish Antarctic Research Programme) 1988 a research project to study the origin and mass balance of this basin has been initiated. A net of 28 stakes has been established for studies of ablation and ice movement (Fig. 1). The ice thickness was measured by radio-echo sounding (Fig. 2) and particular care was devoted to get the correct ice depths at the entrance to the basin. The ice thickness along a central section of the basin varied from 1000 m in the west to 400 m at the bottom of the depression. In order to explain the ablation two automatic weather stations (Aanderaa 2700) were operated during the field season (mid-January to mid-February 1988). One was placed in the bottom of the depression, the other 13 km to the west in an area where a small net accumulation took place during the field season. The latter station should record “normal” weather. Sensors registering wind speed, wind gust, wind direction, incoming solar radiation, air temperature and relative humidity were installed at both weather stations, while reflected solar radiation, net radiation and air pressure were measured only at Scharffenbergbotnen. All sensors except the air pressure sensor were placed 270 cm above the ground, and all were read every 10 minutes. Ablation measurements were carried out between 16 January and 18 February on 24 of the stakes. 12 of these stakes were standing in snow. All but one recorded ablation and, as no signs of melting could be seen, all ablation must be due to evaporation and perhaps for the snowy areas some wind erosion. The average ablation rate for the whole field season was 0.7 mm w.eq. per day with a standard deviation of 0.3. Stakes in blue ice showed slightly higher values than those in snow. For January, when air temperatures always were above −10°C, the average ablation rate was 1.2 mm w.eq. per day. A regional difference in ablation rate across the depression was also measurable. Maximum ablation took place immediately below the arête forming the north-eastern boundary of the basin and diminished towards south-west. Below the arête the ablation rate was above 1 mm w.eq. per day for the whole field season and more than 2 mm w.eq. per day during January. A comparison of weather data between the two stations showed the following main differences. In the depression the temperature showed no daily variation and relative humidity varied between 40 and 60%. The weather at the other station was characterised by colder nights and weaker winds as well as by a relative humidity between 60 and 80%. The reason for the regional variation in ablation can be explained by almost constant easterly winds during January and the drop in altitude (between 300 and 500 m) along the north-western arête. On 11 February 1988 the weather station at Scharffenbergbotnen was converted into a system for satellite (Argos) transmission of weather data to Europe. The transmission seems to have been successful but the data are not yet processed. At present (January 1989) one of us is remeasuring the stakes (ablation and ice movement) during SWEDARP 1989. Preliminary results sent by radio point towards a yearly net ablation rate of 120 mm w.eq. for the blue-ice area in the bottom of the depression. 25% of the ablation took place during the field season 1988, but 75% has evaporated between 18 February 1988 and mid-January 1989. Probably most of the evaporation took place during December 1988 and January 1989, which means a very high daily evaporation rate (2.5 mm w.eq. per day).

scholarly journals Observations on the flight pattern of some Phlaeothripidae (Thysanoptera) species by using suction trap in Hungary

2016 ◽  
Vol 8 (1) ◽  
pp. 16-26 ◽  
Author(s):  
Szilvia Orosz ◽  
Ágnes Szénási ◽  
János Puskás ◽  
Rita Ábrahám ◽  
Andrea Fülöp ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Dominant Species ◽  
Meteorological Factors ◽  
Sunshine Duration ◽  
First Record ◽  
Flight Activity ◽  
Air Pressure ◽  
Flight Period ◽  
Flight Pattern ◽  
Suction Trap

Abstract In this study, the seasonal flight activity of the Phlaeothripidae (Thysanoptera) species was studied by using suction trap, in South-East Hungary, in the years 2000 and 2004 from April to October. The flight period of two dominant species, namely Haplothrips angusticornis Priesner and Haplothrips aculeatus Fabricius (Thysanoptera: Phlaeothripidae), was observed in high number in Europe. Also, it was the first record of mass flight observation of H. angusticornis. In addition, the effect of meteorological factors, such as temperature, sunshine duration, relative humidity, air pressure, and their influences, were evaluated.

scholarly journals Spatial-temporal mapping of hand, foot and mouth disease in relation to climate factors in Xinjiang, China from 2008 to 2016

2020 ◽  
Author(s):  
ling xie ◽  
Ruifang Huang ◽  
Hongwei Wang ◽  
Zhengqing Xiao
Keyword(s):  
Risk Factors ◽  
Relative Humidity ◽  
Spatial Autocorrelation ◽  
Meteorological Factors ◽  
Interactive Effect ◽  
Foot And Mouth Disease ◽  
Air Pressure ◽  
Temporal Heterogeneity ◽  
Northern Xinjiang ◽  
Monthly Average

Abstract [Objectives]: The study mainly aims to depict the epidemiological characteristics of hand, foot and mouth disease (HFMD) in Xinjiang, China and to evaluate the effects of meteorological factors on the incidence of HFMD and the spatial-temporal heterogeneity of HFMD in Xinjiang under the influence of meteorological factors.[Methods]: With the data from the national surveillance data of HFMD and meteorological parameters in the study area from 2008 to 2016. We first employed GeoDetector Model to examine the effects of meteorological factors on HFMD incidence in Xinjiang, China and to test the spatial-temporal heterogeneity of HFMD risk, and then the spatial autocorrelation was applied to examine the temporal-spatial pattern of HFMD.[Results]: From 2008 to 2016, the HFMD distribution showed a distinct seasonal pattern and HFMD cases typically occurred between May and July, peaking in June, in Xinjiang. The relative humidity, precipitation, air pressure and temperature had more influence than other risk factors on HFMD incidence with explanatory powers of 0.30, 0.29, 0.29 and 0.21(p<0.000), respectively. The interactive effect of any two risk factors would enhance the risk of HFMD and there was a nonlinear enhancement between any two risk factors interactive effect. The spatial relative risks in Northern Xinjiang were higher than in Southern Xinjiang. Global spatial autocorrelation analysis showed a fluctuating trend over the years, the spatial dependency on the incidence of HFMD in 2008, 2010, 2012, 2014 and 2015, the negative spatial autocorrelation in 2009 and a random distribution pattern in 2011, 2013 and 2016.[Conclusion]: Our findings show that the risk of HFMD in Xinjiang showed significant spatiotemporal heterogeneity. The monthly average relative humidity, monthly average precipitation, monthly average air pressure and monthly average temperature factors might have stronger relationships on the HFMD incidence in Xinjiang, China, compared with other factors. The differences in climate and latitude between Southern and Northern Xinjiang and their arid and semi-arid geographical environment are part of the reasons why the distribution of HFMD in Xinjiang is different from other temperate continental climatic zones. These associations draw attention to climate-related health issues and will help in establishing accurate spatiotemporal prevention of HFMD in Xinjiang, China.

Grey relation between main meteorological factors and mortality

2019 ◽  
Vol 9 (2) ◽  
pp. 185-196
Author(s):  
Xiaodong Chen ◽  
Desheng Pei ◽  
Liping Li
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Climate Changes ◽  
Meteorological Factors ◽  
Air Pressure ◽  
Content Type ◽  
Relational Analysis ◽  
Curve Approximation ◽  
Grey Relational ◽  
Grey Relation

PurposeThe purpose of this paper is to explore the effects of main meteorological factors on the mortality of urban residents and provide empirical evidence for the prevention of effects of climate changes.Design/methodology/approachGrey relational analysis (GRA) was used to analyse the interrelationships between meteorological factors and mortality among residents in Chaoyang District, Beijing, during the period between 1998 and 2008.FindingsThe changes of annual average mortality had a strong grey relation with temperature and relative humidity. The monthly average mortality (MAM) showed a strong grey relation with air pressure and the MAM in Summer season had a strong grey relation with air pressure, relative humidity and wind speed.Originality/valueMeteorological factors including temperature, relative humidity, air pressure and wind speed are all related with mortality changes. GRA can well reveal the trend of the curve approximation between meteorological factors and mortality and can quantify the different approximation.

scholarly journals Predicting the local COVID-19 outbreak around the world with meteorological conditions: a model-based qualitative study

BMJ Open ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. e041397
Author(s):  
Biqing Chen ◽  
Hao Liang ◽  
Xiaomin Yuan ◽  
Yingying Hu ◽  
Miao Xu ◽  
...  
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Qualitative Study ◽  
Meteorological Factors ◽  
Weather Data ◽  
Epidemic Control ◽  
Average Temperature ◽  
Term Model ◽  
The Future ◽  
Future Outbreak

ObjectivesThis study aims to investigate the relationship between daily weather and transmission rate of SARS-CoV-2, and to develop a generalised model for future prediction of the COVID-19 spreading rate for a certain area with meteorological factors.DesignA retrospective, qualitative study.Methods and analysisWe collected 382 596 records of weather data with four meteorological factors, namely, average temperature, relative humidity, wind speed, and air visibility, and 15 192 records of epidemic data with daily new confirmed case counts (1 587 209 confirmed cases in total) in nearly 500 areas worldwide from 20 January 2020 to 9 April 2020. Epidemic data were modelled against weather data to find a model that could best predict the future outbreak.ResultsSignificant correlation of the daily new confirmed case count with the weather 3 to 7 days ago were found. SARS-CoV-2 is easy to spread under weather conditions of average temperature at 5 to 15°C, relative humidity at 70% to 80%, wind speed at 1.5 to 4.5 m/s and air visibility less than 10 statute miles. A short-term model with these four meteorological variables was derived to predict the daily increase in COVID-19 cases; and a long-term model using temperature to predict the pandemic in the next week to month was derived. Taken China as a discovery dataset, it was well validated with worldwide data. According to this model, there are five viral transmission patterns, ‘restricted’, ‘controlled’, ‘natural’, ‘tropical’ and ‘southern’. This model’s prediction performance correlates with actual observations best (over 0.9 correlation coefficient) under natural spread mode of SARS-CoV-2 when there is not much human interference such as epidemic control.ConclusionsThis model can be used for prediction of the future outbreak, and illustrating the effect of epidemic control for a certain area.

scholarly journals On the conditions under which the "probable errors" of frequency distributions have a real significance

1915 ◽  
Vol 92 (634) ◽  
pp. 23-41 ◽  
Keyword(s):  
Standard Deviation ◽  
Frequency Distribution ◽  
North Sea ◽  
Probable Error ◽  
The Other ◽  
Adequate Description ◽  
Frequency Distributions ◽  
The North ◽  
The North Sea ◽  
The Mean

When we seek the value of a statistical constant, we may either consider the whole aggregate of individuals possessing characteristics of which the constant in question is a function, or we may limit ourselves, from choice or necessity, to the consideration of a ramdom sample of the whole population. The mean height of Englishmen of military age, at a given instant, is a constant which could be determined from a random sample. On the other hand, the mean weight of adult herrings frequenting the North Sea is necessarily to be determined only by a consideration of a sample of the whole population. Statistical constants calculated from a sample give us little information unless we know, at the same time, the manner in which the values may be expected to vary from ramdom sample to ramdom sample, i. e . the frequency distribution of the constant in many samples. The universal custom is to state the "probable error" of the constant, which is equivalent to giving the parameter of the values of the constant in the population as a whole. The parameter-the standard deviation of the frequency distribution-therefore ceases to provide an adequate description of the facts if the frequency distribution differs sensibly from the normal.

scholarly journals A retrospective study: meteorological factors and COVID-19

2020 ◽  
Author(s):  
Cai Chen ◽  
Xiyuan Li ◽  
Xiangwei Meng ◽  
Zhixiang Ma ◽  
Wei Li ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Correlation Coefficient ◽  
Meteorological Factors ◽  
Rank Correlation ◽  
Effect Of Temperature ◽  
Maximal Effect ◽  
Global Epidemic ◽  
Average Temperature ◽  
Daily Average ◽  
Daily Average Temperature

Abstract Background: With the outbreak of novel coronavirus, the global epidemic prevention form is severe. Purpose: This paper aimed to investigate the association between meteorological factors (temperature, precipitation and relative humidity) and the daily new cases in Wuhan. Methods: generalized linear model was built to evaluate the link between daily average temperature and the new cases COVID-19. Spearman rank correlation coefficient was used to investigate the association between temperature, relative humidity, precipitation and the daily new cases COVID-19. Result: The correlation coefficient for daily average temperature, relative humidity, precipitation and NCP were 0.11, -0.083 and 0.17, respectively. The maximal effect of temperature on the new cases NCP appeared on Lag0. Conclusion: The variation of temperature had an effect on the daily new cases.

scholarly journals Modeling analysis of the seasonal characteristics of haze formation in Beijing

2013 ◽  
Vol 13 (11) ◽  
pp. 30575-30610 ◽  
Author(s):  
X. Han ◽  
M. Zhang ◽  
J. Gao ◽  
S. Wang ◽  
F. Chai
Keyword(s):  
Relative Humidity ◽  
Urban Areas ◽  
Mass Concentration ◽  
Aerosol Size Distribution ◽  
Observation Data ◽  
Aerosol Optical Property ◽  
The North ◽  
Seasonal Characteristics ◽  
Simulation Results ◽  
Haze Formation

Abstract. The air quality modeling system RAMS-CMAQ coupled with an aerosol optical property scheme was applied to simulate the meteorological field, major aerosol components (sulfate, nitrate, ammonium, black carbon, organic carbon, dust, and sea salt), and surface visibility over the North China Plain (NCP) in 2011. The modeled results in February and July 2011 were selected and analyzed to obtain an in-depth understanding of the haze formation mechanism in Beijing in different seasons. The evaluations suggested that the modeling system provided reliable simulation results of meteorological factors (temperature, relative humidity, and wind field), visibility, mass concentrations of gaseous pollutants (NO2 and O3), and major aerosol components in PM2.5 by compared with various observation data at several measurement stations over NCP. The simulation results showed that the visibility below 10 km covered most regions of NCP and dropped below 5 km over the urban areas of Beijing, Tianjin, and Shijiazhuang during the pollution episodes in February and July. The heavy particulate pollutants were concentrated in the same areas as well. The heavy loading of PM2.5 which could reach 300 μg m−3 in Beijing should be the main reason of haze occurrence in February, and the visibility generally decreased to 3–5 km when the mass concentration of PM2.5 exceeded 200 μg m−3. However, similar values of visibility also appeared in July when the mass concentration of PM2.5 was merely in the range of 120 μg m−3 to 200 μg m−3. Analysis presented that nitrate, sulfate, and ammonium were the three major aerosol components in Beijing and their total mass burden was even higher in July than that in February. Thus, the significantly higher relative humidity and larger mass proportion of soluble aerosol components resulted in more haze days in July. Sensitivity test shows that the mass concentration threshold of PM2.5 to cause haze occurrence was about 80 μg m−3 when the relative humidity was 70% in Beijing. The change of aerosol size distribution can significantly influence the threshold of haze occurrence in Beijing, particularly for particles of smaller size.

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