Investigation of Solar Powered Drying System Potential in Niğde Province

Storage of the foods obtained by plant and animal production is as important as their cultivation. Crops cultivated around the world lose 28-36% of total yield during the process from agricultural land to consumption. With the most of this loss occurs after harvest and harvest, it can be reduced by suitable machines and appropriate methods to be used. Niğde is in third place in the list of cities with the highest apple production in Turkey. In addition, it is seen that the potential of the region to benefit from solar energy is quite high with 8.02 hours of daily sunshine duration and 1550-1800 kWh m-2 total solar radiation values. In line with the information given, Niğde province stands out as an important opportunity for apple drying processes using solar-powered drying methods. In this study, suitable drying methods that can be used for agricultural products in general and methods that can be used in Niğde province have been investigated and with the using the information obtained from previous studies related to the region its examined that the solar drying system and machines that can be developed for the province of Niğde are specified.

Prediction of solar radiation with air temperature data in a coastal location in Tamilnadu

The objective of this study is to evaluate the performance of the Hargreaves’ Radiation formula in estimating daily solar radiation for an Indian coastal location namely Annamalainagar in Tamilnadu State. Daily solar radiation by Hargreaves’ Radiation formula was computed using the observed data of maximum temperature, Tmax and minimum temperature, Tmin, sourced from the India Meteorological Observatory located at Annamalainagar and employing the adjustment coefficient KRS of 0.19. Daily solar radiation was also computed using Angstrom-Prescott formula with the measured daily sunshine hour data. The differences between the daily solar radiation values computed using the formulae were more pronounced in year around. Hence, the adjustment coefficient KRS is calibrated for the study location under consideration so that the calibrated KRS could be used to better predict daily solar radiation and hence better estimation of reference evapotranspiration.

Investigation of Climate Change Anomaly by Using Nonparametric Test for Navsari District of South Gujarat

Navsari district of rainfall was shows highest increasing rainfall trend obtained September and negative January, July, October, November and December. The regression slope of the yearly time series is about 12.35 mm/36 years. Maximum temperature shows the highest increasing trend in month October, followed by December and August. The month highest decreasing trend was noticed that January, followed by February and July. The regression slope of the yearly time series is about 0.025°C/36 years. Minimum temperature highest values of the slope (0.109°C/36 year) with high value of regression Slope of determination (0.111°C), the annual Kendall’s tau statistic (0.492°C/36 year), the Kendall Score (310). All the month January to December shows increasing trend. The highest increasing trend found that November, followed by March and July, respectively. This finding shows that all the month shows increasing trend with the range between 0.308°C to 0.390°C. In case of RH-I the highest increasing trend shows September, followed by April and June. Similarly decreasing trend was found that January, followed by February and October, respectively. Relative humidity-II increasing trend was found only at the September month 0.084%, the increasing trend was detected in January to August and October to December, respectively. The strongest trend in the Bright sunshine hour’s decline of all month’s average daily sunshine hours was for the Navsari district. No significant trends were detected in all months and seasons for all weather elements. A similar trend was found in Sen’s slope and regression slope all the months for all the weather elements.

Zoning forest fire risk at a county-level based on geographically weighted logistic regression: a case study of Wuyishan, China

Identification of the fire risk area at the county level is the key spatial unit for local forest resource protection and fire prevention. However, current methods and standards focus on the rating of risk level at a national scale which are not necessarily applicable at a local level. Wuyishan is a county-level city in southeastern China, which is rich in forest resources and is important for biodiversity conservation. We used a binary logistic regression (BLR) model and a geographically weighted logistic regression (GWLR) model to examine the indicators of forest fire occurrence and map the forest risk zones in the study area based on historical fire survey data from 1999 to 2013. The results showed that the BLR model simulation found that four indicators (daily average relative humidity, daily sunshine hours, elevation, and distance to the closest railway) had a significant impact on the risk of forest fires in Wuyishan City. Daily sunshine hours had a positive correlation with forest fire risk, and the other three factors were negatively correlated. The GWLR model incorporated the spatial heterogeneity of indicators into the simulation and further demonstrated that only daily average relative humidity was correlated over the entire study area. In contrast, daily sunshine hours, elevation, and distance to the closest railway were effective indicators of fire risk at a local level. The prediction accuracy of the GWLR model (85.3%) was slightly higher than that of the BLR model (84.4%). Around 19.9% of the study area was in a high fire risk zone, 34.0% was in a medium-risk zone, and 46.1% was in a low-risk zone. The high-risk zones were mainly concentrated in the central and southern areas. Our results indicate that, during the fire prevention period, the forest fire management department needs to increase the frequency of daily inspections of the forest edge areas in the high- and medium-risk areas based on the fire risk zoning map. Our approach may improve the identification of forest fire risk and fire prevention and suppression management at a county-level in mountainous and hilly areas.

Sun exposure, dressing habits, and vitamin D status in Morocco

Sunlight is the main source of vitamin D. Almost 80% of vitamin D3 is produced in the skin. The region of Draa Tafilalet benefits from long daily sunshine time. As such, vitamin D deficiency should be low in this region. However, dressing habits can highly influence vitamin D status. This study aimed to evaluate sun exposure and its relation to vitamin D status among the general population in the region of Draa-Tafilalet, Morocco. Clinical, biological, and sociodemographic data were obtained from 331 adults visiting local healthcare units during the summers of 2019 and 2020. Plasma 25(OH)D2/D3 was measured by immunofluorescence. The prevalence of vitamin D deficiency was 37.5%, while Vitamin D insufficiency represented 56.5%. Most of the studied population (76.4%) had restricting dressing habits and exposed only their faces. statistic tests showed a correlation of vitamin D levels with daily sun exposure (r= 0.308, p<0.001), dressing habits (p<0.001), age (r= -0.141, p=0.01), sex (p<0.001), physical activity level (p=0.003), and BMI (r= -0.298, p<0.001). The study showed a high prevalence of vitamin D deficiency in this region. Similarly, it exposed the effects of restricting clothes and low daily sun exposure on vitamin D status.

Empirical Equations to Estimate Evapotranspiration in Mosul City

Average daily data of solar radiation, relative humidity, wind speed and air temperature from 1980 to 2008 are used to estimate the daily reference evapotranspiration in the Mosul City, North of Iraq. ETo calculator software with the Penman Monteith method standardized by the Food and Agriculture Organization is used for calculations. Further, a nonlinear regression approach using SPSS Statistics is utilized to drive the daily reference evapotranspiration relationships in which ETo is function to one or more of the average daily air temperature, actual daily sunshine duration, measured wind speed at 2m height and relative humidity

The Effect of Latitude Differences, Sunshine Periods, Solar Radiation Quantities and Air Temperatures on Solar Electricity Generation.

Electricity supply has gained importance with the increase of electricity demand in the world. The energy that the sun can accept forever provides great convenience for electricity generation. In regions where the sun's rays are steep, it is easier to generate electricity from the solar energy, whereas in regions where the sun's rays are horizontal, the electricity production from the solar energy remains at a lower level. In this study, Istanbul and Adana are compared in the northern and southern regions of Turkey. These two cities were examined for daily sunshine periods, daily and monthly radiation amounts. The effects of air temperatures and sunshine durations on the average radiation amounts have been investigated. The province of Adana has an annual total of 1568.49 kWh, whereas the province of Istanbul has a total of 1327 kWh radiation. When the annual sunshine periods are examined, it is 97.13 hours in Adana and 78.99 hours in Istanbul. It is seen that less electricity production can be done year round in Istanbul province and the hourly production is more than that in Adana when compared to sunrise times. When the average annual temperatures are examined, Adana province is 19 °C and Istanbul province is 13.8 °C. Although the province of Istanbul has a lower average temperature, it has been found that it has a higher yield than the province of Adana.

Comparison of manual and automatic daily sunshine duration measurements at German climate reference stations

Precise quantification of climate change depends on long time series of meteorological variables. Such time series should be as homogeneous as possible but some changes of measurement conditions cannot be prevented. At German climate reference stations, parallel measurements are used to analyze the effects of changes in measurement systems for example for the transition from manual to automatic instruments. These parallel measurements aim to identify measurement uncertainties and to analyze the comparability of measurement systems to investigate the homogeneity. In this study, we investigate daily sunshine duration. Traditionally, manual measurements of daily sunshine duration are taken with Campbell-Stokes sunshine recorders. For automatic measurements the SONIe or SCAPP instrument is used. The different measurement principles (glass sphere and photodiode) cause systematic differences between the observations. During summer, values for manual observations are larger especially in case of frequent alternations between sunny and cloudy conditions. Furthermore, the standard deviation of the differences between the two measurement systems is larger during summer because of the greater day length. To adjust the automatic measurements a linear regression model is suggested based on parallel measurements from 13 climate reference stations in Germany. To validate the regression coefficients, a leave-one-out cross validation was performed (by leaving out data of individual stations). The regression coefficients (derived from different sets of stations) are similar, thereby indicating a robust data set for the estimation of the linear model. With this method we want to prevent breaks in long time series of daily sunshine duration caused by the transition from manual to automatic instruments.

Time-Scaling Properties of Sunshine Duration Based on Detrended Fluctuation Analysis over China

The spatial and temporal variabilities of the daily Sunshine Duration (SSD) time series from the Chinese Meteorological Administration during the 1954–2009 period are examined by the Detrended Fluctuation Analysis (DFA) method. As a whole, weak long-range correlations (LRCs) are found in the daily SSD anomaly records over China. LRCs are also verified by shuffling the SSD records. The proportion of the stations with LRCs accounts for about 97% of the total. Many factors affect the scaling properties of the daily SSD records such as sea-land difference and Tibetan Plateau landform and so on. We find land use and land cover as one of the important factors closely links to LRCs of the SSD. Strong LRCs of the SSD mainly happen in underlying surface of deserts and crops, while weak LRCs occur in forest and grassland. Further studies of scaling behaviors are still necessary to be performed due to the complex underlying surface and climate system.