Effect Of Meteorological Parameters Research Articles

Investigation of BTX Concentrations and Effects of Meteorological Parameters in the Steelpoort Area of Limpopo Province, South Africa

Investigation of BTX Concentrations and Effects of Meteorological Parameters in the Steelpoort Area of Limpopo Province, South Africa

Sorbent-coupled radiative cooling and solar heating to improve atmospheric water harvesting

Atmospheric water harvesting (AWH) technology is a promising technology for addressing global water shortages and contributing to social development. Current AWH technologies, including fog collection, dew collection, and sorption-based AWH mostly focus on a single water harvesting mechanism, and this can limit their working conditions and overall performance. In this work, a composite hydrogel with a low phase change enthalpy of water (1695 kJ kg−1) was coupled with radiative cooling and solar heating to improve passive AWH performance and working conditions. High thermal emittance ε¯LWIR = 0.98 and solar absorptance α¯solar = 0.93 were achieved for radiative cooling in the nighttime and solar heating in the daytime. During the night, radiative cooling could improve the water capture rate from 0.242 kg m-2h−1 (i.e., only sorbent) to 0.310 kg m-2h−1 (i.e., sorbent-coupled radiative cooling) in the outdoor experiment. In the daytime, solar interfacial evaporation improved the water release rate to 1.154 kg m-2h−1. Effects of meteorological parameters, such as relative humidity, ambient temperature, and solar intensity were also discussed theoretically and experimentally. It is indicated that the designed passive AWH device can work over a wide range of meteorological parameters. The outdoor all-day experiment indicated that the maximum water harvesting can be 2.04 kg m−2 in a cycle work. This demonstrates that sorbent-coupled radiative cooling and solar heating provide a potential approach for future solar-driven AWH systems.

Metamitron Thinning Efficacy of Apple Fruitlets Is Affected by Different Rates, Timings and Weather Factors in New York State

Precision chemical thinning is the most common method of thinning apple fruitlets because it requires little time and is cost-effective. The aims of the current study were I.- to investigate the effect of the application of metamitron at different rates on ‘Gala’ apples; II.- to determine which fruit diameters were most sensitive to metamitron spray at several rates (between 180 and 500 ppm); and III- to identify the key environmental factors that explain Metamitron efficacy on a year-to-year basis. Eighteen trials were conducted over seven seasons, from 2015 to 2022 in ‘Gala’ apple orchards in Geneva (New York State). Metamitron was applied at different rates between 180 and 500 ppm, and the timing of the application was between petal fall (4.5 mm) and 18.5 mm fruit size. In each of the studies and years, the effect of meteorological parameters was evaluated. Our results suggest that a linear rate effect was observed in all trials, but that there were differences between the slopes of the regression every year because chemical thinning efficacy was variable year to year. The maximum metamitron efficacy was between 9.5 and 11 mm king fruit diameter; however, metamitron showed thinning efficacy at all phenological stages, from petal fall to 18.5 mm in ‘Gala’ apples. Our results suggest that the important meteorological factors affecting thinning efficacy were temperature and solar radiation on the day of application and for the next 6 days. The solar radiation after application of metamitron was the most important meteorological factor. Fruit drop caused by metamitron increased with low solar radiation. The minimum and maximum temperatures were also important factors in determining metamitron efficacy. A high minimum temperature (during the night) increased the fruit drop caused by metamitron and the maximum temperature during the day showed a negative correlation with the efficacy of metamitron.

Effect of Meteorological Parameters on the Cosmic Muon Flux Studied Using the Effective Generation Level Method with the DANSS Detector Data

Effect of Meteorological Parameters on the Cosmic Muon Flux Studied Using the Effective Generation Level Method with the DANSS Detector Data

Synthesis and performance evaluation of Beta vulgaris based dye-sensitized organic solar cell

Solar cell has a potential to provide electricity on low cost. Therefore, a Beta vulgaris based dye-sensitized organic solar cell is developed in the laboratory. This bacteria multiply by following the conjugation methods which help to grow rapidly. This fabricated solar cell has cell area as 5.29 × 10−4 m2. To examine the performance of the organic cell, five days experimental work has been performed in the open atmosphere. Some key parameters such as voltage current, power generation, and efficiency have been investigated. The effect of meteorological parameters on the surface of the organic solar cell has also been investigated. The maximum generated power and efficiency have been calculated as 26.22 μWatt and 0.0076% respectively. The payback period of the solar cell has been calculated as 1.46 years. This study has been found quite new and innovative for power generation from solar energy.

Effect of meteorological parameters on population dynamics of brinjal shoot and fruit borer under central Punjab, India

Effect of meteorological parameters on population dynamics of brinjal shoot and fruit borer under central Punjab, India

Comparison between Drift Test Bench and Other Techniques in Spray Drift Evaluation of an Eight-Rotor Unmanned Aerial Spraying System: The Influence of Meteorological Parameters and Nozzle Types

In the past decade, an unmanned aerial spraying system (UASS) was applied more and more widely for low-volume aerial pesticides spraying operations in China. However, UASS have a higher drift risk due to more fine droplets sprayed with a higher working height and a faster driving speed than ground sprayers. Study on UASS spray drift is a new hot spot within the field of pesticide application technology. The field test bench was originally designed and applied for the measurement of the spray drift potential of ground sprayers. No methodology using the test bench for UASS drift evaluation was reported. Based on our previous study, field drift measurements of an eight-rotor UASS were conducted using three techniques (test bench, ground petri dish, and airborne collection frame) in this study, and the effects of meteorological parameters and nozzle types were investigated, to explore the applicability and the feasibility of the test bench used in UASS field drift evaluation. The test bench is proven promising for direct drift determination of UASS and the described methodology enabled classification of different UASS configurations. Higher wind speeds and finer droplets produced higher drift values. The faster the wind speed and the lower the humidity, the more the spray drift. The test bench can reduce the site requirements and improve the efficiency of the field drift test.

Effect of Meteorological Parameters on Population Dynamics of Sucking Pest and its Natural Enemy in Brinjal

Effect of Meteorological Parameters on Population Dynamics of Sucking Pest and its Natural Enemy in Brinjal

Comparative investigation of energy-saving potential and technical economy of rooftop radiative cooling and photovoltaic systems

Building-integrated radiative cooling (RC) and photovoltaic (PV) systems are promising renewable technologies harvesting energy from outer space and the sun, respectively, and can contribute to carbon neutrality. However, due to the limited building envelope area, it is significant to compare the energy-saving potential and technical economy of these two technologies, which helps to determine the system form under different working conditions. This study establishes the thermal models for rooftop RC and PV systems to simulate their temperature, heat transfer flux, and energy-saving performance. Then the energy-saving and economic indicators for comparative investigation are proposed, in which the cooling load reduction is converted into electricity saving to be compared with PV’s electricity generation. The comparison results show that RC roof has a lower energy-saving potential than PV roof during the cooling season in Beijing, China (the energy saving ratio of RC to PV is 0.536). However, the economic cost of equivalent electricity saving during the life cycle is $0.011 and $0.034 per kilowatt-hour for RC and PV systems, respectively, indicating that RC roof is more economical. In addition, applicability analysis indicates that the total cooling capacity of RC roof throughout the cooling season is larger in western and southern China, while the energy-saving potential of PV roof is higher in western and northern China. Moreover, the effects of meteorological parameters, indoor conditions, building roof characteristics, and surface optical properties on RC and PV roofs’ performance are thoroughly analyzed. The parametric analysis shows that RC roof is suitable for buildings with high heat dissipation demand and lightweight envelope structures. It is calculated that the energy yield of the RC roof is comparable to that of the PV roof in a telecommunication base station. This study will pave the way for maximizing the energy-saving potential of limited building roofs and contribute to the efficient utilization of renewable energy.

Evaluation of short-lived atmospheric fine particles in Tehran, Iran

Fine particles (PM2.5) have adverse impacts and risks on air quality and human health. The present research focuses on the concentrations of PM2.5, air quality index (AQI), and assessment of hospital admissions due to COPD attributed to PM2.5 particle levels in Tehran during the last 10 years from 2011 to 2020. The effects of meteorological parameters (i.e., wind speed, humidity, and temperature) and AQI on PM2.5 concentrations were examined using data from 21 active monitoring stations of the Air Quality Control Company (AQCC) and Mehrabad Meteorological Station. The health impact assessment of PM2.5 in terms of hospital admissions due to chronic obstructive pulmonary disease (COPD) was obtained by the AirQ2.2.3 model. Based on the results, the annual average PM2.5 concentrations decreased from 2011 through 2020. The results also show a significant effect of meteorological data on the changes in PM2.5 particle concentration. We also noticed that reduction of annual PM2.5 concentration from 38.55 (AQI = 104.08) in 2011 to 28.59 μg m−3 (AQI = 83.87) in 2020 could prevent 779 (by about 70%) premature deaths, and the estimated number of excess cases human respiratory system attributed to PM2.5 at central relative risk (RR) during the last decade was 6158 persons. Also, air quality got from unhealthy for sensitive groups of people to moderate air quality. Finally, any reduction in concentrations of PM2.5 in Tehran can reduce the number of hospital admissions due to COPD significantly. The results of investigations on PM2.5 particles have shown the need for the national clean air program policies and the necessity of urgent actions to improve the air quality to human health in Tehran.

Evaluation of fine particulate matter (PM2.5) concentration trends over heavily-industrialized metropolis of Ahvaz: Relationships to emissions and meteorological parameters

Introduction: Today, with the industrialization of societies, the expansion of urbanization and the increasing trend of population growth, sustainable livelihoods are severely polluted and unfortunately around the world, especially in developing countries, urban air quality is declining. This study is designed to determine the concentration of PM2.5 particles and the effect of meteorological parameters in 14 selected points in the metropolis of Ahvaz.
 Materials and methods: The sampling of Particulate Matter less than 2.5 µm (PM2.5) was in four seasons (winter, spring, summer and autumn). Sampling was performed using the Environmental Protection Agency, method TO-13A (EPA/TO-13A) guideline. Particle samples were collected on a fiberglass filter with a pore size of 1 µm and diameter of 37 mm. Information about meteorological parameters was also recorded by PHB-318. Finally, the obtained data were analyzed by SPSS and R.
 Results: The results showed that the concentration of PM2.5 particles in the metropolis of Ahvaz during the study period is 14 times higher than the value of the guidelines of the World Health Organization (WHO). Also, temperature had a negative relationship and relative humidity and pressure had a direct and positive relationship with concentration of PM2.5 particle. It was found that Zargan, Padadshahr 1and 2, Saadi and 17 Shahrivar stations are the most polluted points compared to PM2.5 particles.
 Conclusion: Planning appropriate strategies of air pollution control to reduce is important and necessary.

Seasonal Variation of Ultrafine Particulate Matter (PM1) and Its Correlation with Meteorological Factors and Planetary Boundary Layer in A Semi-Arid Region

The present study critically investigated the effect of meteorological parameters on the mass concentration of Ultrafine Particulate Matter (PM1) between October 2018 and September 2019 (n=102) in a semiarid region of Rajasthan, India. The concentration of PM1 ranged between 72-110.85 μg.m-3 with distinct seasonal variation. Higher PM1 concentrations are closely linked to decreased wind speeds and colder temperatures, according to the findings. The winter season showed the highest concentration followed by post monsoon and pre monsoon season. The cumulative effect of environmental variables such as temperature, relative humidity, and wind speed, as well as the height of the planetary boundary layer, was investigated using multiple regression analysis (HPBL). A significant negative correlation (p < 0.001) with HPBL and wind speed was observed in all three seasons. The temperature was found to have a significant (p<0.001) negative correlation during winters whereas in other seasons there was a positive but no significant (p>0.001) relationship. Relative humidity showed a negative relationship during withers and pre-monsoon season. The multiple regression model indicated a significant negative (p<0.001) relationship with HPBL in winters (R2=0.70) explaining the 70% effect of HPBL on mass concentration of PM1.During the post-monsoon (R2 = 0.69) and pre-monsoon (R2= 0.91) explains 69% and 91% effect of HPBL on mass concentrations of PM1.The results indicate that the concentration of PM1 cannot be explained by a single meteorological parameter but all the parameters show a cumulative effect.

Effects of meteorological parameters and fuel composition on the air pollution production from motor vehicles.

The aim of this study was to investigate the effect of changes in meteorological parameters and fuel composition on the emission rate of air pollutants in the vehicle fleet of the Tehran Metropolis. The results of this study can be used in management decisions to reduce the emission of air pollutants. In this paper, based on the international vehicle emission model and using mathematical equations, the effects of changing meteorological parameters and fuel composition on the emission of pollutants were modeled. The emission rates of CO, VOCs, and NOx pollutants were the most sensitive to the changes in meteorological parameters, respectively. Among all parameters studied in this research, the changes in sulfur level had the greatest effect on the emission of pollutants from the vehicle fleet of Tehran Metropolis. If the fuel was replaced with Euro 5 standard instead of Euro 3, the emission rates of CO, VOCs, NOx, PM, and SOx pollutants from the vehicle fleet of Tehran Metropolis would be reduced by 9%, 6%, 5%, 14%, and 90%, respectively. Managing and reducing the sources of production and emission of air pollution is one of the best ways to reduce the air pollution. In general, since the emission of pollutants from the fleet of Tehran Metropolis in the cold seasons of the year is greater than during hot seasons and the problem of air pollution is exacerbated by air stability, using Euro 5 fuel in cold seasons is one of the efficient ways to reduce the air pollution.

The effect of meteorological parameters on PM2.5 concentration changes in 2018 (Case study: Tehran)


 
 
 
 Introduction: Studies in different parts of the world have shown that exposure to air pollutants has a negative effect on human health.
 Materials and methods: For statistical analysis between the dependent variable Particulate Matter less than 2.5 μm (PM2.5) concentration and independent variables (wind speed, precipitation, humidity, and temperature) R version 3.6.2 was used. Spearman correlation coefficient was used to determine the correlation between the parameters with the dependent variable. In addition, the multiple linear regression model was used to investigate the relationship and prediction between the independent variables and the dependent variable. In the present study, the effect of meteorological parameters on PM2.5 concentration in different seasons in Tehran in 2018 was studied using Pearson correlation and linear regression statistical analyzes.
 Results: Based on the results, it was found that PM2.5 had no significant relationship with meteorological parameters. Only in summer, there was a significant relationship between the dependent variable and the independent variable (wind speed) (p-value=0.01) and there was also an inverse relationship between these variables (r=-0.65). Multiple linear regression was also used to investigate the significant effect of independent variables on the dependent variable.
 Conclusion: According to the coefficients of determination in this model, 47, 16, 45, and 20% of the dependent variable change in autumn, winter, spring, and summer, respectively, can be explained by meteorological parameters (independent). Due to the fact that the concentration of PM2.5 in Tehran is higher than the national standard, more attention of officials is necessary to improve air quality in Tehran.
 
 
 

Effect of meteorological parameters on Karnal bunt incidence in wheat under different agroclimatic zones of Punjab

To quantify the effect of meteorological parameters on incidence of Karnal bunt in wheat crop, an investigation was done using 9 to 12 season’s data of Bathinda and Ludhiana stations of Punjab. Maximum temperature during March in range of 25-31oC, minimum temperature of February (8.5-11.0oC), morning and evening relative humidity of March in range of 85-95 and 40-60 per cent respectively, rainfall more than 25 mm with sunshine hours 5.5-9.0 hrs/day during mid February to mid March favour Karnal bunt in wheat crop. Maximum temperature of March showed significant negative correlation with incidence of Karnal bunt whereas minimum temperature of February showed significant positive correlation with disease incidence at both locations. Morning and evening relative humidity showed significant positive correlation with disease incidence. Rain amount and rainy days during mid February to mid March significantly influenced disease incidence. Sunshine hours had negative correlation with disease incidence. Backward multiple linear regression (BMLR) analysis indicated maximum temperature, rainfall and sunshine hours play significant role in Karnal bunt incidence at Ludhiana. However, at Bathinda, maximum temperature, evening time relative humidity, rain amount and rainy days played significant role.

The Transfer Phenomena of Air Pollutants Emitted from Power Station and Generators in Nasiriyah City and the Effect of Meteorological Parameters on its Dispersion by Using Fixed Box Model

The study aims to use the fixed box model to calculate the spread of pollutants (CO2, SO2, NOX, particulate) resulting from the burning of fuel used to produce electrical energy in the Nasiriyah city and to know the way they spread in the city through being affected by the wind speed and compare the results calculated from the model with the results measured by the lancom4 device. The results showed that the main pollutants for the air in Nasiriyah was emitted from burning the fuel used for the production of electric power, and the results showed that the concentration of pollutants (CO2, SO2, NOX) was much higher inside the city when compared with the upstream direction of the winds due to its increase with the movement of winds and its entry into the city. Through the application of the fixed box model and when comparing the calculated results through the model with the results measured by the lancom4 device, the error rate was (4 %, 2%, 2%, 5%) for pollutants (CO2, SO2, NOX, particulate) respectively, it was also observed that the highest emission rate of pollutants was result from using heavy fuel (fuel oil) and the lowest emission was from light oil (Dry gas). We noted the spread of pollutants and dilution in the atmosphere increases with the increase in wind speed, excluding for particles mater.

Does the COVID-19 pandemic help with identifying measures to reduce atmospheric pollution?

This article analyses the variability of gas and aerosol pollution levels in Riga (Latvia) over different periods associated with Covid-19 restrictions. The variability of atmospheric pollution levels is described from a relative point of view; the effects of meteorological parameters were assessed using Pearson's correlation factor and statistical significance. To assess whether changes were statistically relevant during the various assessment periods, the analysis was performed using the ANOVA dispersion test and the post-hoc Tukey test. Major changes have been identified in the case of gaseous atmospheric pollution.

Characterization and Investigation of Nonlinear Behaviour of Radio Refractivity during the Rainy and Dry Seasons in the Coastal Region of Nigeria


 
 
 
 
 
 
 
 
 
 
 
 The transmission and receiving of good quality of signals globally has been impaired due to the internal activities of the troposphere linked to the nonlinear behaviour of the meteorological parameters. This paper focusses on characterizing and investigating the nonlinear behaviour of radio refractivity during the rainy and dry seasons in the coastal region of Nigeria using temperature, pressure and relative humidity data collected over a period of two years by the Centre for Atmospheric Research, National Space Research and Development Agency (NASRDA) from Lagos state. Data obtained were analyzed by False Nearest Neighbour (FNN) and Recurrence Quantification Analysis (RQA). The results show that recurrence techniques are able to identify the periods where there are high predictability and low predictability. The investigation of nonlinear effects of meteorological parameters and the hydrometeors on the troposphere help to avoid fading of radio signals along with the radio communication links.
 
 
 
 
 
 
 
 
 
 
 

Formulation of weekly and monthly thumb rule models for prediction of potential productivity of sunflower in Punjab


 A study was conducted to evaluate the effect of meteorological parameters on Sunflower crop by analyzing meteorological and crop data (2003-2017) for three locations (Ludhiana, Ballowal Saunkhari and Amritsar) and to develop weather based “Weekly and Monthly Thumb Rule Models” for predicting the potential yield of sunflower crop in Punjab. These climatic normals were used for comparing the actual data to evaluate the effect of meteorological parameters on the yield of sunflower. In Punjab, ideally humid (maximum relative humidity between 77% - 94%) weather from mid-February to mid-March is favourable for optimum growth and development of vegetative stage in crop. The warm temperature (>35 ºC) during the seed development period after the flowering stage of sunflower is favourable for seed yield. However, heavy rainfall in the months of April and May with cloudy weather (sunshine hour < 9.2 hour) are not favourable for its productivity. The actual meteorological data of high yield crop years over the past 15 years were analyzed for different growth stages of sunflower to work out the critical ranges of meteorological parameters. Weather based “Thumb Rule Models” using the weekly and monthly meteorological data for different growth stages were formulated for use in developing the crop weather insurance term sheets and also predicting the potential yield of sunflower crop.

Analysing of atmospheric conditions and their effects on air quality in Istanbul using SODAR and CEILOMETER.

In this study, first, air pollution that is caused by the air pollutants' concentration exceeding the limit value in Istanbul between 2017 and 2020 were analysed. In addition to this analysis, the effects of meteorological parameters on pollution were also examined within the same period of time. Second, for a 14-day period during which the concentration values of the air pollutants were calculated higher than the standards, therefore, were selected as an episode. In that respect, measurements of both pollutant and meteorological parameters were obtained from air quality monitoring stations. The Weather Research and Forecasting (WRF) model was used to examine the changes of meteorological parameters in the surface and upper atmospheric levels. The cross-correlation function (CCF) was performed together with both air quality monitoring station and the WRF model output data to examine the effects of temporal changes in meteorological parameters on air pollutant concentrations on a temporal scale. In addition, some meteorological parameters were obtained from remote sensing systems (SODAR and Ceilometer). Finally, with the help of the trajectory analysis model, it was determined whether the pollutant parameters were transported or not. Consequently, within a 3-year period, the most critical parameters in terms of pollution throughout the city were assessed as NO2 and PM10. Moreover, low wind speeds and high pressure values during the episode prevented the dispersion of pollutants and caused air pollution in Istanbul.