scholarly journals Quantifying the impact of synoptic circulations on ozone variations in North China from April–October 2013–2017

2019 ◽  
Author(s):  
Jingda Liu ◽  
Lili Wang ◽  
Mingge Li ◽  
Zhiheng Liao ◽  
Yang Sun ◽  
...  
Keyword(s):  
Local Governments ◽  
North China ◽  
Meteorological Factors ◽  
Meteorological Data ◽  
Dominant Factor ◽  
Maximum Temperature ◽  
Synoptic Classification ◽  
The Impact ◽  
Synoptic Circulation ◽  
Ozone Variations

Abstract. The ozone variation characteristics and the impact of synoptic and local meteorological factors in North China were analysed quantitively during the warm season from 2013 to 2017 based on multi-city, in-situ ozone and meteorological data, as well as meteorological reanalysis. The domain-averaged maximum daily 8-h running average O3 (MDA8 O3) concentration was 122 ± 11 μg m−3 with an increase rate of 7.88 μg m−3 year−1, and the three most highly-polluted months were June (149 μg m−3), May (138 μg m−3) and July (132 μg m−3), which was closely related to synoptic circulation variations. Twenty-six synoptic circulation types (merged into 5 weather categories) were objectively identified using the Lamb-Jenkinson method. The highly-polluted weather categories included S-W-N directions, LP (low-pressure related circulation patterns) and C (cyclone type), and corresponding domain-averaged MDA8 O3 concentration were 122, 126 and 128 μg m−3, respectively. Based on the frequency and intensity changes of synoptic circulations, 39.2 % of the inter-annual domain-averaged O3 increase from 2013 to 2017 was attributed to synoptic changes, and intensity of synoptic circulations was the dominant factor. Using synoptic classification and local meteorological factors, the segmented synoptic-regression approach was established to evaluate and forecast daily ozone variations on an urban scale. The results showed that this method is practicable in most cities, and that the dominant factors are the maximum temperature, southerly winds, relative humidity in the previous and in the same day, and total cloud cover. Overall, 43–64 % of the day-to-day variability of MDA8 O3 concentrations was due to local meteorological variations in most cities over North China, except for QHD~32 % and ZZ~25 %. Our quantitative exploration on synoptic and local meteorological factors influencing both on inter-annual and day-to-day ozone variations will provide the scientific basis for evaluating emission reduction measures, since the national and local governments have implemented a series of measures to mitigate air pollution in North China in these five years.

scholarly journals Quantifying the impact of synoptic circulation patterns on ozone variability in northern China from April to October 2013–2017

2019 ◽  
Vol 19 (23) ◽  
pp. 14477-14492 ◽  
Author(s):  
Jingda Liu ◽  
Lili Wang ◽  
Mingge Li ◽  
Zhiheng Liao ◽  
Yang Sun ◽  
...  
Keyword(s):  
Meteorological Factors ◽  
Northern China ◽  
Low Pressure ◽  
Dominant Factor ◽  
Maximum Temperature ◽  
Weather Types ◽  
Synoptic Classification ◽  
Circulation Patterns ◽  
The Impact ◽  
Synoptic Circulation

Abstract. The characteristics of ozone variations and the impacts of synoptic and local meteorological factors in northern China were quantitatively analyzed during the warm season from 2013 to 2017 based on multi-city in situ ozone and meteorological data as well as meteorological reanalysis. The domain-averaged maximum daily 8 h running average O3 (MDA8 O3) concentration was 122±11 µg m−3, with an increase rate of 7.88 µg m−3 yr−1, and the three most polluted months were closely related to the variations in the synoptic circulation patterns, which occurred in June (149 µg m−3), May (138 µg m−3) and July (132 µg m−3). A total of 26 weather types (merged into five weather categories) were objectively identified using the Lamb–Jenkinson method. The highly polluted weather categories included the S–W–N directions (geostrophic wind direction diverts from south to north), low-pressure-related weather types (LP) and cyclone type, which the study area controlled by a low-pressure center (C), and the corresponding domain-averaged MDA8 O3 concentrations were 122, 126 and 128 µg m−3, respectively. Based on the frequency and intensity changes of the synoptic circulation patterns, 39.2 % of the interannual increase in the domain-averaged O3 from 2013 to 2017 was attributed to synoptic changes, and the intensity of the synoptic circulation patterns was the dominant factor. Using synoptic classification and local meteorological factors, the segmented synoptic-regression approach was established to evaluate and forecast daily ozone variability on an urban scale. The results showed that this method is practical in most cities, and the dominant factors are the maximum temperature, southerly winds, relative humidity on the previous day and on the same day, and total cloud cover. Overall, 41 %–63 % of the day-to-day variability in the MDA8 O3 concentrations was due to local meteorological variations in most cities over northern China, except for two cities: QHD (Qinhuangdao) at 34 % and ZZ (Zhengzhou) at 20 %. Our quantitative exploration of the influence of both synoptic and local meteorological factors on interannual and day-to-day ozone variability will provide a scientific basis for evaluating emission reduction measures that have been implemented by the national and local governments to mitigate air pollution in northern China.

scholarly journals METHODOLOGICAL PROBLEMS OF THE MATHEMATICAL ESTIMATION OF THE IMPACT OF METEOROLOGICAL FACTORS ON ADAPTIVE FUNCTIONS OF THE HUMAN

2019 ◽  
Vol 96 (3) ◽  
pp. 253-257
Author(s):  
Nurlan K. Smagulov ◽  
A. A. Adilbekova
Keyword(s):  
High School ◽  
Mathematical Analysis ◽  
Meteorological Factors ◽  
Meteorological Data ◽  
Correlation Coefficients ◽  
Dose Effect ◽  
Output Factors ◽  
The Central Nervous System ◽  
Methodological Problems ◽  
The Impact

The work is dedicated to methodological problems of the mathematical assessment of the impact of meteorological factors on the adaptive function of the teachers of the High School Institutions. Objects of research. Male teachers of the High School Institution, aged of from 24 to 49 years. Meteorological data were evaluated during the investigation of anthropometric indices of height and weight, individual-typological features and the physiological assessment of the central nervous system, cardiovascular system of the High School teachers. Statistical analysis was performed with the use of Statistica 6.0 package and special statistical software. Paired correlation coefficients obtained as a result of calculation were used to estimate the proportion of the influence of input factors (arguments) on the output factors (functions). A mathematical analysis has allowed to reveal leading meteorological factors that cause a certain level of functional exhaustion during the investigated period. The use of a non-linear correlation analysis allowed to enhance significantly the ability for analytical processing of the results, increase of the effectiveness and the possibility of interpreting the interaction of factors in achieving optimal adaptation of teachers in the working process and to identify the role of meteorological factors in this process. Knowledge of leading factors and the percentage of their contribution to the functional state allowed to give the more accurate assessment of stress to the organism in specific circumstances. The ultimate aim of the mathematical analysis should be not only to find the critical value defined the priority factor characterizing the degree of of information load, but the critical combination of all priority factors causing disruption and the beginning of “start-up” adaptation process in the system “dose-effect. “

Estimation and Comparative Analysis of Daily Reference Evapotranspiration Based on Different Input Combinations and Different Models

2021 ◽  
Author(s):  
Chaojie Niu ◽  
Xiang Li ◽  
Chengshuai Liu ◽  
Shan-e-hyder Soomro ◽  
Caihong Hu
Keyword(s):  
Reference Evapotranspiration ◽  
Meteorological Factors ◽  
Meteorological Data ◽  
Pearson Correlation ◽  
Back Propagation ◽  
Maximum Temperature ◽  
Least Squares Regression ◽  
Simulation Performance ◽  
Bp Model ◽  
Plsr Model

Abstract Daily reference evapotranspiration (ET0) is the most crucial link in estimating crop water demand. In this study, Levenberg-Marquardt (L-M), Genetic Algorithm-Back Propagation (GA-BP) and Partial Least Squares Regression (PLSR) models were introduced to calculate the ET0 values, Based on the Pearson Correlation analysis method, five meteorological factors were obtained, which were combined into six different input scenarios. Compared with the values that calculated by the the Penman Monteith (PM) formula. Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Nash-Sutcliffe Efficiency (NSE), and Scatter Index (SI) were used to evaluate the simulation performance of the models. The results showed that the simulation effect of the L-M model is better than that of the GA-BP model and PLSR model in all scenarios. PLSR model has the worst performance. The SI index of L-M6 was 46.69% lower than that of GA-BP6 and 65.78% lower than that of PLSR6. When the input factors are 3, the simulation effect of the input wind speed, the maximum temperature and the minimum temperature is the best. L-M model and GA-BP model can predict the ET0 in the region with a lack of meteorological data. This study provides an important reference for high-precision prediction of ET0 under different input combinations of meteorological factors.

scholarly journals Association Between Meteorological Factors and Coronary Heart Disease in Northeast China

2020 ◽  
Author(s):  
Jinling Huang ◽  
Liqiang Zheng ◽  
Jinghai Zhu
Keyword(s):  
Coronary Heart Disease ◽  
Heart Disease ◽  
Northeast China ◽  
Protective Factor ◽  
Meteorological Factors ◽  
Meteorological Data ◽  
Warm Season ◽  
Multiple Linear Regression Model ◽  
Population Data ◽  
The Impact

Abstract Background: To investigate the effect of daily meteorological factors in northeast China on coronary heart disease and explore in depth the impact of the environment on health. Methods: The population data primarily included daily coronary heart disease hospitalizations between January 1, 2015 and December 31, 2019, comprising a total of 25,461 patients. The meteorological data included daily temperature, barometric pressure, relative humidity, precipitation, and wind speed between January 1, 2015 and December 31, 2019. A multiple linear regression model was constructed for analyzing the relationship between meteorological factors and coronary heart disease.Results: After controlling for confounding factors, the mean monthly temperature negatively correlated with the monthly number of coronary heart disease hospitalizations, particularly in the warm season (Apr–Sep; β = –12.468, p < 0.05).Conclusions: In the warm season and during a mild weather, high temperature might be a protective factor against coronary heart disease.

scholarly journals Meteorological factors affecting the risk of transmission of HPAI in Miyazaki, Japan

2019 ◽  
Vol 6 (1) ◽  
pp. e000341 ◽  
Author(s):  
Genki Arikawa ◽  
Yoshinori Fujii ◽  
Maiku Abe ◽  
Ngan Thi Mai ◽  
Shuya Mitoma ◽  
...  
Keyword(s):  
Bird Migration ◽  
Meteorological Factors ◽  
Meteorological Data ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Migratory Waterfowl ◽  
Generalised Linear Mixed Model ◽  
Fulica Atra ◽  
The Relationship

Highly pathogenic avian influenza (HPAI) outbreaks engender a severe economic impact on the poultry industry and public health. Migratory waterfowl are considered the natural hosts of HPAI virus, and HPAI viruses are known to be transmitted over long distances during seasonal bird migration. Bird migration is greatly affected by the weather. Many studies have shown the relationship between either autumn or spring bird migration and climate. However, few studies have shown the relationship between annual bird migration and annual weather. This study aimed to establish a model for the number of migratory waterfowl involved in HPAI virus transmission based on meteorological data. From 136 species of waterfowl that were observed at Futatsudate in Miyazaki, Japan, from 2008 to 2016, we selected potential high-risk species that could introduce the HPAI virus into Miyazaki and defined them as ‘risky birds’. We also performed cluster analysis to select meteorological factors. We then analysed the meteorological data and the total number of risky birds using a generalised linear mixed model. We selected 10 species as risky birds: Mallard (Anas platyrhynchos), Northern pintail (Anas acuta), Eurasian wigeon (Anas penelope), Eurasian teal (Anas crecca), Common pochard (Aythya ferina), Eurasian coot (Fulica atra), Northern shoveler (Anas clypeata), Common shelduck (Tadorna tadorna), Tufted duck (Aythya fuligula) and Herring gull (Larus argentatus). We succeeded in clustering 35 meteorological factors into four clusters and identified three meteorological factors associated with their migration: (1) the average daily maximum temperature; (2) the mean value of global solar radiation and (3) the maximum daily precipitation. We thus demonstrated the relationship between the number of risky birds and meteorological data. The dynamics of migratory waterfowl was relevant to the risk of an HPAI outbreak, and our data could contribute to cost and time savings in strengthening preventive measures against epidemics.

Evaluation Of Seasonality In The Incidence Of Promyelocytic Leukemia In Brazil

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 5005-5005 ◽  
Author(s):  
Karine Sampaio Nunes Barroso ◽  
Irene Lorand-Metze ◽  
Katia B. Pagnano ◽  
Eduardo M. Rego ◽  
Raul A Melo ◽  
...  
Keyword(s):  
Acute Promyelocytic Leukemia ◽  
Clinical Laboratory ◽  
Meteorological Data ◽  
Promyelocytic Leukemia ◽  
Fourth Quarter ◽  
Maximum Temperature ◽  
The South ◽  
The Third ◽  
The Impact ◽  
Spearman Test

Abstract Besides the known factors such as the presence of oncogenes, the macro-environment (pollution, infections) or organic microenvironment (dysregulation of the immune system) can be the triggering factor of the process of leukemogenesis. It is known that the amount of rainfall can affect the distribution (dilution) of pollutants in the air and water reserves. There is no description of the climate influence in the incidence of Acute Promyelocytic Leukemia (APL), which has its own clinical laboratory characteristics, and is defined by the presence of the PML-RARA rearrangement. The aim of this study was to investigate the impact of seasonality in the incidence of Promyelocytic Leukemia in Brazil, and its characteristics. Patients and methods we analyzed the clinical laboratory data and origin of participant cases of the International Consortium on Acute Promyelocytic Leukemia (IC-APL), a group multicenter treatment of APL with standardized diagnosis and treatment. We included all patients diagnosed with APL of Brazilian centers between 2006 and 2011. We excluded patients without demographics. Patients were divided into macro-climate (Northeast, South and Southeast). Northeast: 49 cases of Pernambuco, Southeast: 16 cases of Minas Gerais, São Paulo 88 cases; South: 27 cases of Rio Grande do Sul and 19 cases of Paraná. Meteorological data were extracted from the database Meteorological Research and Education (BDMEP) of the National Institute of Meteorology (INMET), and grouped by quarter. We studied the mean maximum temperature, mean minimum temperature and rainfall. The relationship between the number of cases and meteorological data were analyzed by the Spearman test. Results We included 149 patients with APL. In the South, there were 46 patients, 50% female and 50% male, mean age: 37 years, 16 cases occurred on the first quarter (January-March), 12 on the second quarter (April-June), 8 cases on third quarter (July-September) and 10 on the fourth quarter (October to December). In the Northeast, there were 49 cases, 25 female and 24 male, mean age 34 years with 11 cases on the first and second quarters, 12 cases on the third quarter and 15 cases on the fourth quarter. Southeast: 54 cases with 29 female cases and 25 male cases, mean age 25 years, with 12 cases on the first and second quarter, 11 cases on the third quarter and 19 cases on the fourth quarter. In the South, there was no statistically significant correlation between the weather and the number of registered cases of APL. In the Northeast, there was a negative correlation between the number of cases of APL and rainfall (r = -0.57, p = 0.004) and a trend with the maximum temperature (r = 0.34, p = .07). In the southeast, there was positive correlation between rainfall (r = 0.42, p = 0.02) but not with temperature. In the northeast, the smallest amount of rainfall is associated with higher temperatures (r = -0.49, p <0.0002), whereas in the Southeast, the greater amount of rainfall is associated with warmer temperatures. Conclusion There is no known etiology of APL, but the correlations found between rainfall and number of cases could be related to the dispersion of pollutants into the environment. Disclosures: No relevant conflicts of interest to declare.

scholarly journals Identification of meteorological factors affecting migration of wild birds into miyazaki and its relation to circulation of highly pathogenic avian influenza virus

2018 ◽  
Author(s):  
Genki Arikawa ◽  
Maiku Abe ◽  
Mai Thi Ngan ◽  
Shuya Mitoma ◽  
Kosuke Notsu ◽  
...  
Keyword(s):  
Avian Influenza ◽  
Highly Pathogenic Avian Influenza ◽  
Meteorological Factors ◽  
Meteorological Data ◽  
Wild Birds ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Highly Pathogenic ◽  
Pathogenic Avian Influenza ◽  
Fulica Atra

AbstractAim of our study is to establish models for predicting the number of migratory wild birds based on the meteorological data. From 136 species of wild birds, which have been observed at Futatsudate in Miyazaki, Japan, from 2008 to 2016, we selected the potential high-risk species, which can introduce highly pathogenic avian influenza (HPAI) virus into Miyazaki; we defined them as “risky birds”. We then performed regression analysis to model the relationship between the number of risky birds and meteorological data. We selected 10 wild bird species as risky birds: Mallard (Anas platyrhynchos), Northern pintail (Anas acuta), Eurasian wigeon (Anas penelope), Eurasian teal (Anas crecca), Common pochard (Aythya ferina), Eurasian coot (Fulica atra), Northern shoveler (Anas clypeata), Common shelduck (Tadorna tadorna), Tufted duck (Aythya fuligula), and Herring gull (Larus argentatus). We succeeded in identifying five meteorological factors associated with their migration: station pressure, mean value of global solar radiation, minimum of daily maximum temperature, days with thundering, and days with daily hours of daylight under 0.1 h. We could establish some models for predicting the number of risky birds based only on the published meteorological data, without manual counting. Dynamics of migratory wild birds has relevance to the risk of HPAI outbreak, so our data could contribute to save the cost and time in strengthening preventive measures against the epidemics.

scholarly journals Relationship between several meteorological factors and phenological features of apple cultivars

2008 ◽  
Vol 14 (1-2.) ◽  
Author(s):  
L. Lakatos ◽  
T. Szabó ◽  
S. Zhongfu ◽  
Y. Wang ◽  
J. Racskó ◽  
...  
Keyword(s):  
Daily Precipitation ◽  
Meteorological Factors ◽  
Meteorological Data ◽  
Gene Bank ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Night Time ◽  
Apple Cultivars

The trees observed are grown at Ofeherto, Eastern Hungary in the plantation of an assortment (gene bank) with 586 apple cultivars. Each of the cultivars were observed as for their dates of subsequent phenophases, the beginning of bloom, main bloom and the end of bloom over a period between 1984 and 2001. during this period the meteorological data-base keeps the following variables: daily means of temperature (°C), daily maximum temperature (°C), daily minimum temperature (°C), daily precipitation sums (mm), daily sums of sunny hours, daily means of the differences between the day-time and night-time temperatures (°C), average differences between temperatures of successive daily means (°C). Between the 90th and 147th day of the year over the 18 years of observation. The early blooming cultivars start blooming at 10-21April. The cultivars of intermediate bloom start at the interval 20 April to 3 May, whereas the late blooming group start at 2-10 May. Among the meteorological variables of the former autumnal and hibernal periods, the hibernal maxima were the most active factor influencing the start of bloom in the subsequent spring.

scholarly journals Factors affecting the trends in evaporation during different crop growing seasons over India

MAUSAM ◽  
2021 ◽  
Vol 62 (3) ◽  
pp. 391-402
Author(s):  
R.P. SAMUI ◽  
G. JOHN ◽  
S.P. RANSURE ◽  
M.A. PACHANKAR
Keyword(s):  
Relative Humidity ◽  
Wind Velocity ◽  
Meteorological Factors ◽  
Sunshine Duration ◽  
Meteorological Data ◽  
Maximum Temperature ◽  
Peninsular India ◽  
High Positive Correlation ◽  
Growing Seasons ◽  
Increasing Trend

Evaporation, rainfall and meteorological data for the period 1971-2004 for 58 well distributed stations over India were selected for the study. Trends of evaporation and rainfall in five regions, viz., Northwest, North, Northeast, Central and Peninsular regions of India during different crop growing seasons, viz., kharif, rabi and summer and the meteorological factors contributing towards the trend were analyzed. Annual evaporation shows decreasing trend in all the regions of the country. Trends in seasonal evaporation during kharif, rabi and summer seasons also showed decreasing trends in Northwest, North, Central and Peninsular regions of the country while few locations in Northeast India, viz., Guwahati, Dibrugarh and Tocklai showed significant increasing trend in evaporation during kharif and rabi seasons. No significant trend in annual and seasonal rainfall was observed in Indian region except a few stations in peninsular India where increasing trend was observed. Normalized anomalies of maximum temperature, relative humidity and vapour pressure showed increasing trend in Northwest and Northern regions during all the three crop growing seasons while decreasing trend or no trend in wind velocity was observed in all the regions except in central region where increasing trend was observed during summer season. As evaporation relates to the meteorological elements, viz., temperature, sunshine duration, wind velocity and relative humidity, the likely causative meteorological factors for such changes are studied. Increasing trends in maximum temperature was observed in central and peninsular inland regions of the country during rabi and summer seasons while slight decreasing trends were observed in the Northeast region during kharif season. High positive correlation found between maximum temperature and wind velocity indicates that the trend in evaporation is mostly influenced by these two factors. Increase in humidity and decrease in bright sunshine hours were both important and found correlated with the decrease in evaporation.

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