scholarly journals Effect of meteorological factors on influenza-like illness from 2012 to 2015 in Huludao, a northeastern city in China

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6919 ◽  
Author(s):  
Ying-Long Bai ◽  
De-Sheng Huang ◽  
Jing Liu ◽  
De-Qiang Li ◽  
Peng Guan
Keyword(s):  
Relative Humidity ◽  
Vapor Pressure ◽  
Air Temperature ◽  
Meteorological Factors ◽  
Meteorological Data ◽  
Lag Time ◽  
Temperature Minimum ◽  
The Relationship ◽  
Maximum Air Temperature ◽  
Minimum Air Temperature

Background This study aims to describe the epidemiological patterns of influenza-like illness (ILI) in Huludao, China and seek scientific evidence on the link of ILI activity with weather factors. Methods Surveillance data of ILI cases between January 2012 and December 2015 was collected in Huludao Central Hospital, meteorological data was obtained from the China Meteorological Data Service Center. Generalized additive model (GAM) was used to seek the relationship between the number of ILI cases and the meteorological factors. Multiple Smoothing parameter estimation was made on the basis of Poisson distribution, where the number of weekly ILI cases was treated as response, and the smoothness of weather was treated as covariates. Lag time was determined by the smallest Akaike information criterion (AIC). Smoothing coefficients were estimated for the prediction of the number of ILI cases. Results A total of 29, 622 ILI cases were observed during the study period, with children ILI cases constituted 86.77%. The association between ILI activity and meteorological factors varied across different lag periods. The lag time for average air temperature, maximum air temperature, minimum air temperature, vapor pressure and relative humidity were 2, 2, 1, 1 and 0 weeks, respectively. Average air temperature, maximum air temperature, minimum air temperature, vapor pressure and relative humidity could explain 16.5%, 9.5%, 18.0%, 15.9% and 7.7% of the deviance, respectively. Among the temperature indexes, the minimum temperature played the most important role. The number of ILI cases peaked when minimum temperature was around −13 °C in winter and 18 °C in summer. The number of cases peaked when the relative humidity was equal to 43% and then began to decrease with the increase of relative humidity. When the humidity exceeded 76%, the number of ILI cases began to rise. Conclusions The present study first analyzed the relationship between meteorological factors and ILI cases with special consideration of the length of lag period in Huludao, China. Low air temperature and low relative humidity (cold and dry weather condition) played a considerable role in the epidemic pattern of ILI cases. The trend of ILI activity could be possibly predicted by the variation of meteorological factors.

scholarly journals Effects of Preharvest Precipitation, Air Temperature, and Humidity on the Occurrence of Soft Scald in ‘Honeycrisp’ Apples

HortScience ◽  
2009 ◽  
Vol 44 (6) ◽  
pp. 1645-1647 ◽  
Author(s):  
Renae E. Moran ◽  
Jennifer R. DeEll ◽  
William Halteman
Keyword(s):  
Relative Humidity ◽  
Air Temperature ◽  
Soluble Solids ◽  
Precipitation Temperature ◽  
Fruit Maturity ◽  
Honeycrisp Apples ◽  
Soft Scald ◽  
Relationship Of ◽  
The Relationship ◽  
Maximum Air Temperature

The relationship of soft scald incidence (SSI) with precipitation, temperature, and fruit maturity indicators in ‘Honeycrisp’ apples was examined using 7 years of data in Maine and 6 years in Ontario, Canada. Relative humidity was also examined in Maine. Soft scald incidence was highly variable from year to year ranging from 1% to 85% in Maine and from 0% to 76% in Ontario. In Ontario, SSI was negatively related to soluble solids at harvest (partial r2 = 0.50; P = 0.0041) and negatively related to precipitation during 90 to 120 days from bloom (DFB; partial r2 = 0.28; P = 0.0344). In Maine, SSI was most strongly related to precipitation in the 90 to 120 DFB (partial r2 = 0.53; P = 0.0001), maximum air temperature 60 to 90 DFB (partial r2 = 0.21; P = 0.0001), and number of hours when relative humidity was greater than 85% (partial r2 = 0.11; P = 0.0001).

scholarly journals Increase in Air Temperature in The Region of South Sumatra Province as the Indicator of Global Warming and the Effect on Transpiration of Lansium domesticum Corr.

2019 ◽  
Author(s):  
Ari Sugiarto ◽  
Hanifa Marisa ◽  
Sarno
Keyword(s):  
Global Warming ◽  
Air Temperature ◽  
Transpiration Rate ◽  
Temperature Increase ◽  
Secondary Data ◽  
Temperature Data ◽  
Randomized Design ◽  
Maximum Air Temperature ◽  
Lansium Domesticum ◽  
Minimum Air Temperature

Abstract Global warming is one of biggest problems faced in the 21st century. One of the impacts of global warming is that it can affect the transpiration rate of plants that °Ccur. This study purpose to see how much increase in air temperature that occurred in the region of South Sumatra Province and to know the effect of increase in ari temperature in the region of South Sumatra Province on transpiration rate of Lansium domesticum Corr. This study used a complete randomized design with 9 treatments (22.9 °C, 23.6 °C, 24.6 °C, 26.3 °C, 27 °C, 27.8 °C, 31.7 °C, 32.5 °C, and 32.9 °C) and 3 replications. Air temperature data as secondary data obtained from the Meteorology, Climatology and Geophysics Agency (MCGA) Palembang Climatology Station in South Sumatra Province. The measurement of transpiration rate is done by modified potometer method with additional glass box. The data obtained are presented in the form of tables and graphs. Transpiration rate (mm3/g plant/hour) at temperture 22.9 °C = 4.37, 23.6 °C = 7.03, 24.6 °C = 8.03, 26.3 °C = 10.11, 27 °C = 13.13, 27.8 °C = 17.87, 31.7 °C = 23.21, 32.5 °C= 25.45 and 32.9 °C= 27.24. At the minimum air temperature in the region of South Sumatra Province there is increase in air temperature of 1.5 °C, average daily air temperature increase 1.3 °C and maximum air temperature increase 1.2 °C.

scholarly journals Assessment of the Relationship between Cerebrospinal Meningitis and Climate Variables in Kaduna State, Nigeria

2021 ◽  
pp. 33-41
Author(s):  
Joyce Imara Nchom ◽  
A. S. Abubakar ◽  
F. O. Arimoro ◽  
B. Y. Mohammed
Keyword(s):  
Relative Humidity ◽  
Air Temperature ◽  
Linear Trend ◽  
Pearson Correlation ◽  
Maximum Temperature ◽  
Data Set ◽  
International Research Institute ◽  
Wind Speed Maximum ◽  
Weather Parameters ◽  
The Relationship

This study examines the relationship between Meningitis and weather parameters (air temperature, maximum temperature, relative humidity, and rainfall) in Kaduna state, Nigeria on a weekly basis from 2007–2019. Meningitis data was acquired weekly from Nigeria Centre for Disease Control (NCDC), Bureau of Statistics and weather parameters were sourced from daily satellite data set National Oceanic and Atmospheric Administration (NOAA), International Research Institute for Climate and Society (IRI). The daily data were aggregated weekly to suit the study. The data were analysed using linear trend and Pearson correlation for relationship. The linear trend results revealed a weekly decline in Cerebro Spinal Meningitis (CSM), wind speed, maximum and air temperature and an increase in relative humidity and rainfall. Generally, results reveal that the most important explanatory weather variables influencing CSM amongst the five (5) are the weekly maximum temperature and air temperature with a positive correlation of 0.768 and 0.773. This study recommends that keen interest be placed on temperature as they play an essential role in the transmission of this disease and most times aggravate the patients' condition.

scholarly journals The effect of air temperature on forest fire risk in the municipality of Negotin

2015 ◽  
Vol 95 (4) ◽  
pp. 67-76
Author(s):  
Stanimir Zivanovic ◽  
Milena Gocic ◽  
Radomir Ivanovic ◽  
Natasa Martic-Bursac
Keyword(s):  
Air Temperature ◽  
Forest Fires ◽  
Meteorological Data ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Fire Risk ◽  
Annual Number ◽  
Absolute Maximum ◽  
Maximum Air Temperature ◽  
Forest Fire Risk

Fires in nature are caused by moisture content in the burning material, which is dependent on the values of the climatic elements. The occurrence of these fires in Serbia is becoming more common, depending on the intensity and duration have a major impact on the state of vegetation. The aim of this study was to determine the association between changes in air temperature and the dynamics of the appearance of forest fires. To study the association of these properties were used Pearson correlation coefficients. The analysis is based on meteorological data obtained from meteorological station in Negotin for the period 1991-2010. Research has found that the annual number of fires, correlating with an average annual air temperature (p = 0.317, ? = 0.21). Also, it was found that the annual number of fires positive, medium intensity, correlate with the absolute maximum air temperature (p = 0.578, ? = 0.26), but not statistically significant (p> 0.05).

scholarly journals Characteristics of Heavy Storms and the Scaling Relation with Air Temperature by Event Process-Based Analysis in South China

Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 185 ◽  
Author(s):  
Cuilin Pan ◽  
Xianwei Wang ◽  
Lin Liu ◽  
Dashan Wang ◽  
Huabing Huang
Keyword(s):  
Relative Humidity ◽  
Air Temperature ◽  
South China ◽  
Meteorological Factors ◽  
Rainfall Data ◽  
Precipitation Extremes ◽  
Scaling Relation ◽  
Convective Storms ◽  
Warm Front ◽  
Storm Characteristics

The negative scaling rate between precipitation extremes and the air temperature in tropic and subtropic regions is still a puzzling issue. This study investigates the scaling rate from two aspects, storm characteristics (types) and event process-based temperature variations. Heavy storms in South China are developed by different weather systems with unique meteorological characteristics each season, such as the warm-front storms (January), cold-front storms (April to mid-May), monsoon storms (late May to June), convective storms, and typhoon storms (July to September). This study analyzes the storm characteristics using the hourly rainfall data from 1990 to 2017; compares the storm hyetographs derived from the one-minute rainfall data during 2008–2017; and investigates the interactions between heavy storms and meteorological factors including air temperature, relative humidity, surface pressure, and wind speed at 42 weather stations in Guangzhou during 2015–2017. Most storms, except for typhoon and warm-front storms, had a short duration (3 h) and intense rates (~13 mm/h) in Guangzhou, South China. Convective storms were dominant (50%) in occurrence and had the strongest intensity (15.8 mm/h). Storms in urban areas had stronger interactions with meteorological factors and showed different hyetographs from suburban areas. Meteorological factors had larger variations with the storms that occurred in the day time than at night. The air temperature could rise 6 °C and drop 4 °C prior to and post-summer storms against the diurnal mean state. The 24-hour mean air temperature prior to the storms produced more reliable scaling rates than the naturally daily mean air temperature. The precipitation extremes showed a peak-like scaling relation with the 24-hour mean air temperature and had a break temperature of 28 °C. Below 28 °C, the relative humidity was 80%–100%, and it showed a positive scaling rate. Above 28 °C, the negative scaling relation was likely caused by a lack of moisture in the atmosphere, where the relative humidity decreased with the air temperature increase.

scholarly journals Perceived Influence of Weather Conditions on Rheumatic Pain in Romania

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Adina-Eliza Croitoru ◽  
Gabriela Dogaru ◽  
Titus Cristian Man ◽  
Simona Mălăescu ◽  
Marieta Motricală ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Pain Intensity ◽  
Air Temperature ◽  
Correlation Matrix ◽  
Great Majority ◽  
Weather Conditions ◽  
Weather Variables ◽  
Rheumatic Pain ◽  
Atmospheric Fronts ◽  
The Relationship

The main objective of this study was to analyze the perception of the influence of various weather conditions on patients with rheumatic pathology. A group of 394 patients, aged between 39 and 87 years and diagnosed with degenerative rheumatic diseases, were interviewed individually by using a questionnaire created specifically for this study. Further on, to assess the relationship between pain intensity and weather conditions, a frequency analysis based on Pearson’s correlation matrix was employed. The most important results are as follows: the great majority of the participants (more than 75%) believe that their rheumatic pain is definitely or to a great extent influenced by different weather conditions; most of the patients reported intensification of their pain with weather worsening, especially when cloudiness and humidity suddenly increase (83.8% and 82.0%, respectively), air temperature suddenly decreases (81.5%), and in fog or rain conditions (81.2%). In our research, alongside simple meteorological variables, we established that complex weather variables such as atmospheric fronts, in particular, the cold ones and winter anticyclonic conditions, greatly intensify the rheumatic pain, whereas summer anticyclonic conditions usually lead to a decrease in pain severity. In terms of relationships between pain intensity and weather conditions, we found the strongest correlations (ranging between 0.725 and 0.830) when temperature, relative humidity, and cloudiness are constantly high.

scholarly journals Sensitivity of Precipitation Phase over the Swiss Alps to Different Meteorological Variables

2014 ◽  
Vol 15 (2) ◽  
pp. 685-696 ◽  
Author(s):  
S. Froidurot ◽  
I. Zin ◽  
B. Hingray ◽  
A. Gautheron
Keyword(s):  
Relative Humidity ◽  
Air Temperature ◽  
Meteorological Data ◽  
Explanatory Power ◽  
Surface Air Temperature ◽  
Ground Level ◽  
Swiss Alps ◽  
Meteorological Variables ◽  
Study Region ◽  
Precipitation Phase

Abstract In most meteorological or hydrological models, the distinction between snow and rain is based only on a given air temperature. However, other factors such as air moisture can be used to better distinguish between the two phases. In this study, a number of models using different combinations of meteorological variables are tested to determine their pertinence for the discrimination of precipitation phases. Spatial robustness is also evaluated. Thirty years (1981–2010) of Swiss meteorological data are used, consisting of radio soundings from Payerne as well as present weather observations and surface measurements (mean hourly surface air temperature, mean hourly relative humidity, and hourly precipitation) from 14 stations, including Payerne. It appeared that, unlike surface variables, variables derived from the atmospheric profiles (e.g., the vertical temperature gradient) hardly improve the discrimination of precipitation phase at ground level. Among all tested variables, surface air temperature and relative humidity show the greatest explanatory power. The statistical model using these two variables and calibrated for the case study region provides good spatial robustness over the region. Its parameters appear to confirm those defined in the model presented by Koistinen and Saltikoff.

scholarly journals Modeling Infection of Strawberry Flowers by Botrytis cinerea Using Field Data

2000 ◽  
Vol 90 (12) ◽  
pp. 1367-1374 ◽  
Author(s):  
Xiangming Xu ◽  
David C. Harris ◽  
Angela M. Berrie
Keyword(s):  
Vapor Pressure ◽  
Botrytis Cinerea ◽  
Vapor Pressure Deficit ◽  
Meteorological Data ◽  
Weather Conditions ◽  
Gray Mold ◽  
Weather Variables ◽  
Infection Models ◽  
The Relationship ◽  
Field Plots

The incidence of strawberry flower infection by Botrytis cinerea was monitored in unsprayed field plots in three successive years together with meteorological data and numbers of conidia in the air. There were large differences in conidia numbers and weather conditions in the 3 years. Three sets of models were derived to relate inoculum and weather conditions to the incidence of flower infection; by inoculum only, by weather variables only, and by both inoculum and weather variables. All the models fitted the observed incidence satisfactorily. High inoculum led to more infection. Models using weather variables only gave more accurate predictions than models using inoculum only. Models using both weather variables and inoculum gave the best predictions, but the improvement over the models based on weather variables only was small. The relationship between incidence of flower infection and inoculum and weather variables was generally consistent between years. Of the weather variables examined, daytime vapor pressure deficit and nighttime temperature had the greatest effect in determining daily incidence of flower infection. Infection was favored by low day vapor pressure deficit and high night temperature. The accuracy and consistency of the weather-based models suggest they could be explored to assist in management of gray mold.

scholarly journals Effects and interaction of meteorological factors on hemorrhagic fever with renal syndrome incidence in Huludao City, northeastern China, 2007–2018

2021 ◽  
Vol 15 (3) ◽  
pp. e0009217
Author(s):  
Wanwan Sun ◽  
Xiaobo Liu ◽  
Wen Li ◽  
Zhiyuan Mao ◽  
Jimin Sun ◽  
...  
Keyword(s):  
Public Health ◽  
High Temperature ◽  
Relative Humidity ◽  
Meteorological Factors ◽  
Meteorological Data ◽  
Additive Model ◽  
Hemorrhagic Fever ◽  
Epidemiological Data ◽  
Effect Of Temperature ◽  
Delayed Effects

Background Hemorrhagic fever with renal syndrome (HFRS), a rodent-borne disease, is a severe public health threat. Previous studies have discovered the influence of meteorological factors on HFRS incidence, while few studies have concentrated on the stratified analysis of delayed effects and interaction effects of meteorological factors on HFRS. Objective Huludao City is a representative area in north China that suffers from HFRS with primary transmission by Rattus norvegicus. This study aimed to evaluate the climate factors of lag, interaction, and stratified effects of meteorological factors on HFRS incidence in Huludao City. Methods Our researchers collected meteorological data and epidemiological data of HFRS cases in Huludao City during 2007–2018. First, a distributed lag nonlinear model (DLNM) for a maximum lag of 16 weeks was developed to assess the respective lag effect of temperature, precipitation, and humidity on HFRS incidence. We then constructed a generalized additive model (GAM) to explore the interaction effect between temperature and the other two meteorological factors on HFRS incidence and the stratified effect of meteorological factors. Results During the study period, 2751 cases of HFRS were reported in Huludao City. The incidence of HFRS showed a seasonal trend and peak times from February to May. Using the median WAT, median WTP, and median WARH as the reference, the results of DLNM showed that extremely high temperature (97.5th percentile of WAT) had significant associations with HFRS at lag week 15 (RR = 1.68, 95% CI: 1.04–2.74) and lag week 16 (RR = 2.80, 95% CI: 1.31–5.95). Under the extremely low temperature (2.5th percentile of WAT), the RRs of HFRS infection were significant at lag week 5 (RR = 1.28, 95% CI: 1.01–1.67) and lag 6 weeks (RR = 1.24, 95% CI: 1.01–1.57). The RRs of relative humidity were statistically significant at lag week 10 (RR = 1.19, 95% CI: 1.00–1.43) and lag week 11 (RR = 1.24, 95% CI: 1.02–1.50) under extremely high relative humidity (97.5th percentile of WARH); however, no statistically significance was observed under extremely low relative humidity (2.5th percentile of WARH). The RRs were significantly high when WAT was -10 degrees Celsius (RR = 1.34, 95% CI: 1.02–1.76), -9 degrees Celsius (1.37, 95% CI: 1.04–1.79), and -8 degrees Celsius (RR = 1.34, 95% CI: 1.03–1.75) at lag week 5 and more than 23 degrees Celsius after 15 weeks. Interaction and stratified analyses showed that the risk of HFRS infection reached its highest when both temperature and precipitation were at a high level. Conclusions Our study indicates that meteorological factors, including temperature and humidity, have delayed effects on the occurrence of HFRS in the study area, and the effect of temperature can be modified by humidity and precipitation. Public health professionals should pay more attention to HFRS control when the weather conditions of high temperature with more substantial precipitation and 15 weeks after the temperature is higher than 23 degrees Celsius.

scholarly journals Evaluation of nature-based solutions implementation scenarios, using urban surface modelling

2021 ◽  
pp. 1-42
Author(s):  
Emmanuel Panagiotakis ◽  
Dionysia Kolokotsa ◽  
Nektarios Chrysoulakis
Keyword(s):  
Heat Flux ◽  
Relative Humidity ◽  
Urban Environment ◽  
Air Temperature ◽  
Green Infrastructure ◽  
Model Simulation ◽  
Meteorological Data ◽  
Sensible Heat Flux ◽  
The Impact ◽  
The City

The present paper aims to study the impact of Nature Based Solutions (NBS) on the urban environment. The Surface Urban Energy and Water balance Scheme (SUEWS) is used to quantify the impact of NBS in the city of Heraklion, Crete, Greece, a densely built urban area. Local meteorological data and data from an Eddy Covariance flux tower installed in the city center are used for the model simulation and evaluation. Five different scenarios are tested by replacing the city’s roofs and pavements with green infrastructure, i.e., trees and grass, and water bodies. The NBS impact evaluation is based on the changes of air temperature above 2m from the ground, relative humidity and energy fluxes. A decrease of the air temperature is revealed with the highest reduction (2.3%) occurring when the pavements are replaced with grass for all scenarios. The reduction of the air temperature is followed by a decrease in turbulent sensible heat flux. For almost all cases, an increase of the relative humidity is noticed, accompanied by a considerable increase of the turbulent latent heat flux. Therefore, NBS in cities change the energy balance significantly and modify the urban environment for the citizens' benefit.

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