scholarly journals Examine the impact of weather and ambient air pollutant parameters on daily case of COVID-19 in India

2020 ◽  
Author(s):  
Kousik Das ◽  
Nilanjana Das Chatterjee
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Solar Radiation ◽  
Ambient Air ◽  
List Type ◽  
Positive Relation ◽  
Weather Variables ◽  
Sensitive Analysis ◽  
Negative Relation ◽  
The Impact

AbstractThe present study presents a view on exploring the relationship pattern between COVID 19 daily cases with weather parameters and air pollutants in mainland India. We consider mean temperature, relative humidity, solar radiation, rainfall, wind speed, PM2.5, PM10, SO2, NO2 and CO as independent variable and daily COVID 19 cases as dependent variable for 18 states during 18th march to 30th April, 2020.After dividing the dataset for 0 to 10 day, 10 to 25 days and 0 to 44 days, the current study applied Akaike s Information Criteria (AIC) and Generalized Additive Model (GAM) to examine the kind of relationship between independent variables with COVID 19 cases. Initially GAM model result shows variables like temperature and solar radiation has positive relation (p<0.05) in 0 to 10 days study with daily cases. In 25 days dataset it significantly shows that temperature has positive relation above 23 degree centigrade, SO2 has a negative relationship and relative humidity has negative (between 30% to 45% and > 60%) and a positive relationship (45% to 60%) with COVID 19 cases (p=0.05). 44 days dataset has six parameters includes temperature as positive, relative humidity as negative (between 0 to 45%) and then positive (after >45%), NO2 as Positive (0 to 35 microgram/m3) followed by negative trend (after > 40 microgram/m3), SO2 and rainfall as negative relation. After sensitive analysis, it is found that weather variables like relative humidity, solar radiation and rainfall are more sensitive than temperature and wind speed. Whereas pollutants like NO2, PM2.5, PM10 and CO are more sensitive variables than SO2 in this study. In summary this study finds temperature, relative humidity, solar radiation, wind speed, SO2, PM2.5, and CO may be important factors associated with COVID 19 pandemic.Graphical AbstractHighlights➢There was a significant relationship between daily positive COVID-19 case with weather and pollution factors➢We found PM2.5 and CO positively associated with transmission of positive cases where as NO2 and SO2 have a negative relation after sensitive analysis.➢We have found temperature and wind speed have positive relation whereas, relative humidity and solar radiation have negative relation after sensitive analysis.➢Weather variables like relative humidity and solar radiation and rainfall are more sensitive than temperature and wind speed. Pollutants like NO2, PM2.5, PM10 and CO are more sensitive variables than SO2 in this study.

Influences of weather and time of day on trap catches of bush fly,Musca vetustissima Walker (Diptera: Muscidae)

1986 ◽  
Vol 76 (3) ◽  
pp. 359-366 ◽  
Author(s):  
W. G. Vogt
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Solar Radiation ◽  
New South ◽  
Time Of Day ◽  
Weather Variables ◽  
South Wales ◽  
Males And Females ◽  
Catch Rates ◽  
Trap Catches

AbstractField populations of Musca vetustissima Walker were sampled in a region of New South Wales at 2-h intervals on 35 occasions between spring 1984 and autumn 1985 using wind-oriented fly traps. Ambient temperature, solar radiation, relative humidity and wind speed explained 84·3% of the within-day deviance of total catches (both sexes combined). Temperature and solar radiation jointly explained 82·6% of this deviance (71·1 and 11·5%, respectively), indicating that the other variables, although significant, did not greatly affect trap catches. As air temperature increased, log catch rates increased non-linearly up to a maximum at 27·5°C and declined thereafter. Log catch rates increased linearly as solar radiation increased and declined linearly as relative humidity and wind speed increased. Changes in log catch rates with time of day were explained almost entirely by the four weather variables, i.e. when weather effects were removed, time of day effects were no longer significant. These weather variables also accounted for 79·9% of the between-day variation in logarithms of trap catches. Relative responses of males and females to traps differed significantly with respect to relative humidity, wind speed and time of day. Male catches tended to increase relative to female catches between 1200 h and 1800 h and also declined more slowly with increases in relative humidity and wind speed. Separate models are presented for standardization of male and female catch rates; the estimates differ from those obtained from observed sex ratios and total catch rates, but the differences are small compared to the observed day-to-day variation in catch rates.

scholarly journals Influence of Meteorological Factors on the Potential Evapotranspiration in Yanhe River Basin, China

2021 ◽  
Author(s):  
yu luo ◽  
Peng Gao ◽  
Xingmin Mu
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Solar Radiation ◽  
River Basin ◽  
Air Temperature ◽  
Hydrological Cycle ◽  
Meteorological Factors ◽  
Potential Evapotranspiration ◽  
Sensitivity Coefficients ◽  
The Impact

Potential evapotranspiration (ET) is an essential component of the hydrological cycle, and quantitative estimation of the influence of meteorological factors on ET can provide a scientific basis for studying the impact mechanisms of climate change. In the present research, the Penman-Monteith method was used to calculate ET. The Mann-Kendall statistical test with the inverse distance weighting were used to analyze the spatiotemporal characteristics of the sensitivity coefficients and contribution rates of meteorological factors to ET to identify the mechanisms underlying changing ET rates. The results showed that the average ET for the Yanhe River Basin, China from 1978–2017 was 935.92 mm. Save for a single location (Ganquan), ET increased over the study period. Generally, the sensitivity coefficients of air temperature (0.08), wind speed at 2 m (0.19), and solar radiation (0.42) were positive, while that of relative humidity was negative (-0.41), although significant spatiotemporal differences were observed. Increasing air temperature and solar radiation contributed 1.09% and 0.55% of the observed rising ET rates, respectively; whereas decreasing wind speed contributed -0.63%, and relative humidity accounted for -0.85%. Therefore, it was concluded that the decrease of relative humidity did not cause the observed ET increase in the basin. The predominant factor driving increasing ET was rising air temperatures, but this too varied significantly by location and time (intra- and interannually). Decreasing wind speed at Ganquan Station decreased ET by -9.16%, and was the primary factor underlying the observed, local “evaporation paradox.” Generally, increases in ET were driven by air temperature, wind speed and solar radiation, whereas decreases were derived from relative humidity.

scholarly journals Influence of Meteorological Factors on the Potential Evapotranspiration in Yanhe River Basin, China

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1222
Author(s):  
Yu Luo ◽  
Peng Gao ◽  
Xingmin Mu
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Solar Radiation ◽  
River Basin ◽  
Air Temperature ◽  
Hydrological Cycle ◽  
Meteorological Factors ◽  
Potential Evapotranspiration ◽  
Sensitivity Coefficients ◽  
The Impact

Potential evapotranspiration (ET0) is an essential component of the hydrological cycle, and quantitative estimation of the influence of meteorological factors on ET0 can provide a scientific basis for studying the impact mechanisms of climate change. In the present research, the Penman–Monteith method was used to calculate ET0. The Mann–Kendall statistical test with the inverse distance weighting were used to analyze the spatiotemporal characteristics of the sensitivity coefficients and contribution rates of meteorological factors to ET0 to identify the mechanisms underlying changing ET0 rates. The results showed that the average ET0 for the Yanhe River Basin, China from 1978–2017 was 935.92 mm. Save for a single location (Ganquan), ET0 increased over the study period. Generally, the sensitivity coefficients of air temperature (0.08), wind speed at 2 m (0.19), and solar radiation (0.42) were positive, while that of relative humidity was negative (−0.41), although significant spatiotemporal differences were observed. Increasing air temperature and solar radiation contributed 1.09% and 0.55% of the observed rising ET0 rates, respectively; whereas decreasing wind speed contributed −0.63%, and relative humidity accounted for −0.85%. Therefore, it was concluded that the decrease of relative humidity did not cause the observed ET0 increase in the basin. The predominant factor driving increasing ET0 was rising air temperatures, but this too varied significantly by location and time (intra- and interannually). Decreasing wind speed at Ganquan Station decreased ET0 by −9.16%, and was the primary factor underlying the observed, local “evaporation paradox”. Generally, increase in ET0 was driven by air temperature, wind speed and solar radiation, whereas decrease was derived from relative humidity.

scholarly journals Correlation Between Climatic Factors And Leafminer (Insecta: Agromyzidae) Infestation On Three Vegetable Crops In Chittagong, Bangladesh

2015 ◽  
Vol 41 (1) ◽  
pp. 1-5
Author(s):  
Santosh Mazumdar ◽  
Badrul Amin Bhuiya
Keyword(s):  
Wind Speed ◽  
Climatic Factors ◽  
French Bean ◽  
Infestation Rate ◽  
Vegetable Crops ◽  
Positive Relation ◽  
Significant Relation ◽  
Negative Relation ◽  
Correlation Studies ◽  
The Impact

Present study deals with the impact of climatic factors (temperature, humidity and wind speed) on agromyzid leafminers infestation in three cultivated crops viz. Tomato, French bean and Cowpea. Correlation studies showed that there was significantly positive relation of temperature, whereas wind speed showed negative relation to agromyzid infestation on cultivated crops. But there was no significant relation with humidity. Temperature influenced infestation rate as 18.70 ± 4.12, 16.01 ± 15.85 and 9.38 ± 9.10 % for Tomato, French bean and Cowpea respectively. Asiat. Soc. Bangladesh, Sci. 41(1): 1-5, June 2015

scholarly journals To Study the Temporal Variation of Capacity Utilization Factor (CUF) of PV Based Solar Power Plant with Respect to Climatic Condition

2016 ◽  
Vol 11 (2) ◽  
pp. 654-661 ◽  
Author(s):  
Ramesh Chaudhari ◽  
Bharat Chaudhari ◽  
Pratiksinh Dilipsinh ◽  
Vijya Leela bhai
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Solar Radiation ◽  
Power Output ◽  
Climatic Factors ◽  
Capacity Utilization ◽  
Ambient Air ◽  
Daily Basis ◽  
Utilization Factor ◽  
Performance Quality

Performance, quality and reliability of technology are becoming more and more important for the emerging photovoltaic markets worldwide. In this experiment the monitoring of climatic factors like, solar radiation, Ambient Temperature, Module Temperature, Relative Humidity and Wind Speed was carried out on daily basis for six months, between 7:00 A.M to 6:00 P.M. Data was measured with SCADA system. This analysis was carried out by monitoring the fluctuation in power output of the system with climatic factors. From the results, there is direct proportionality between the power output of the system and the climatic factors. The correlation between ambient air temperature, PV module temperature and CUF is strongly positive. The other climatic factor like wind speed is does not have much significant effect on CUF. The Relative humidity is negatively correlated with CUF. The correlation between solar radiation and the CUF is strongly positive.

The Concentration Characteristics of PM10 and PM2.5 in Eight Cities of China in March, 2013

2013 ◽  
Vol 807-809 ◽  
pp. 20-23 ◽  
Author(s):  
Tao Sheng ◽  
Jian Wu Shi ◽  
Sen Lin Tian ◽  
Li Mei Bi ◽  
Hao Deng ◽  
...  
Keyword(s):  
Air Quality ◽  
Wind Speed ◽  
Relative Humidity ◽  
Negative Correlation ◽  
Ambient Air ◽  
Quality Standard ◽  
Meteorological Factor ◽  
Urban Air ◽  
Ambient Air Quality ◽  
Ambient Air Quality Standard

According to the information of air quality which published by the urban air quality real-time publishing platform, the concentration characteristics of PM10 and PM2.5 were studied in Kunming (KM), Changsha (CS), Hangzhou (HZ), Shanghai (SH), Harbin (HEB), Beijing (BJ), Wuhan (WH) and Guangzhou (GZ). The results show that the concentrations of PM10 and PM2.5 exceeded the Ambient Air Quality Standard (GB3095-2012) in varying degrees in March, 2013. The concentrations of PM10 in Wuhan is the highest, reached 164μg/m3, exceeded the standard by 9.3%; the concentrations of PM2.5 is much higher in Wuhan, Changsha and Beijing, the average concentrations were 96μg/m3, 103μg/m3 and 110μg/m3, exceeded the standard by 28.0%, 37.3% and 46.7% respectively. The correlation of PM10 with PM2.5 in most of these cities was good in March. The correlation analysis of pollutant with meteorological factor in Hangzhou, Shanghai, Beijing and Guangzhou was also studied, the results show that the concentrations of PM10 and PM2.5 are weakly positive correlation with temperature in the four cities, negative correlation with relative humidity without Beijing, and negative correlation with wind speed.

scholarly journals A Practical Approach to Developing Climate Change Scenarios for Water Quality Models

2019 ◽  
Vol 20 (6) ◽  
pp. 1197-1211 ◽  
Author(s):  
Rakesh K. Gelda ◽  
Rajith Mukundan ◽  
Emmet M. Owens ◽  
John T. Abatzoglou
Keyword(s):  
Climate Change ◽  
Water Quality ◽  
New York ◽  
Wind Speed ◽  
Solar Radiation ◽  
Climate Change Scenarios ◽  
Quality Models ◽  
Hourly Data ◽  
Water Quality Models ◽  
The Impact

Abstract Climate model output is often downscaled to grids of moderately high spatial resolution (~4–6-km grid cells). Such projections have been used in numerous hydrological impact assessment studies at watershed scales. However, relatively few studies have been conducted to assess the impact of climate change on the hydrodynamics and water quality in lakes and reservoirs. A potential barrier to such assessments is the need for meteorological variables at subdaily time scales that are downscaled to in situ observations to which lake and reservoir water quality models have been calibrated and validated. In this study, we describe a generalizable procedure that utilizes gridded downscaled data; applies a secondary bias-correction procedure using equidistance quantile mapping to map projections to station-based observations; and implements temporal disaggregation models to generate point-scale hourly air and dewpoint temperature, wind speed, and solar radiation for use in water quality models. The proposed approach is demonstrated for six locations within New York State: four within watersheds of the New York City water supply system and two at nearby National Weather Service stations. Disaggregation models developed using observations reproduced hourly data well at all locations, with Nash–Sutcliffe efficiency greater than 0.9 for air temperature and dewpoint, 0.4–0.6 for wind speed, and 0.7–0.9 for solar radiation.

A Comparative Study of ASOS and USCRN Temperature Measurements

2005 ◽  
Vol 22 (6) ◽  
pp. 679-686 ◽  
Author(s):  
Bomin Sun ◽  
C. Bruce Baker ◽  
Thomas R. Karl ◽  
Malcolm D. Gifford
Keyword(s):  
Wind Speed ◽  
Solar Radiation ◽  
Local Heating ◽  
Ambient Air ◽  
Local Effect ◽  
Temperature Measurements ◽  
Reference Network ◽  
Shield Effectiveness ◽  
Average Difference ◽  
Bias Analysis

Abstract Temperature measurements from the U.S. Climate Reference Network (USCRN) instrument system were compared to the Automated Surface Observing System (ASOS) ambient air temperature measurements and were examined under different regimes of wind speed and solar radiation. Influences due to observing practice differences and the effects of siting differences were discussed. This analysis indicated that the average difference between the ASOS and USCRN temperatures is on the order of 0.1°C. However, problems were noticed that were possibly related to the ASOS shield effectiveness, including a solar radiation warm effect under calm conditions and the dependence of ASOS minus USCRN temperature on wind speed. The ASOS and USCRN time of observation difference was on the order of ∼0.05°C, with a warmer ASOS daily Tmax and a cooler ASOS daily Tmin. The local effect complicates the bias analysis because it depends not only on local heating/cooling, but it can be strongly modified by cloudiness, wind, and solar radiation.

scholarly journals Seasonal and Temporal Variations of Criteria Air Pollutants and the Influence of Meteorological Parameters on the Concentration of Pollutants in Ambient Air in Lahore, Pakistan

2016 ◽  
Vol 59 (1) ◽  
pp. 34-42
Author(s):  
Amtul Bari Tabinda ◽  
Saleha Munir ◽  
Abdullah Yasar ◽  
Asad Ilyas
Keyword(s):  
Wind Speed ◽  
Solar Radiation ◽  
Negative Correlation ◽  
Air Pollutants ◽  
Meteorological Parameters ◽  
Ambient Air ◽  
Temporal Variations ◽  
Criteria Air Pollutants ◽  
Summer Minimum ◽  
One Year

Criteria air pollutants have their significance for causing health threats and damage to theenvironment. The study was conducted to assess the seasonal and temporal variations of criteria air pollutantsand evaluating the correlations of criteria air pollutants with meteorological parameters in the city ofLahore, Pakistan for a period of one year from April 2010 to March 2011. The concentrations of criteriaair pollutants were determined at fixed monitoring stations equipped with HORIBA analyzers. The annualaverage concentrations (µg/m3) of PM2.5, O3, SO2, CO and NOx (NO+NO2) for this study period were118.94±57.46, 46.0±24.2, 39.9±8.9, 1940±1300 and 130.9±81.0 (61.8±46.2+57.3±22.19), respectively.PM2.5, SO2, CO and NOx had maximum concentrations during winter whereas O3 had maximum concentrationduring summer. Minimum concentrations of PM2.5, SO2 and NOx were found during monsoon as comparedto other seasons due to rainfall which scavenged these pollutants. The O3 showed positive correlation withtemperature and solar radiation but negative correlation with wind speed. All other criteria air pollutantsshowed negative correlation with wind speed, temperature and solar radiation. A significant (P<0.01)correlation was found between NOx and CO (r = 0.779) which showed that NOx and CO arise from commonsource that could be the vehicular emission. PM2.5 was significantly correlated (P<0.01) with NOx (r = 0.524)and CO (r = 0.519), respectively. High traffic intensity and traffic jams were responsible for increased airpollutants level especially the PM2.5, NOx and CO.

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