scholarly journals Modeling of Atmospheric Pollution in Urban and Rural Sites Using a Probabilistic and Objective Approach

2019 ◽  
Vol 9 (19) ◽  
pp. 4009 ◽  
Author(s):  
Francisco J. Moral ◽  
Francisco J. Rebollo ◽  
Pablo Valiente ◽  
Fernando López
Keyword(s):  
Solar Radiation ◽  
Air Temperature ◽  
Atmospheric Pollution ◽  
Climatic Factors ◽  
Barometric Pressure ◽  
Rural Site ◽  
Pollution Level ◽  
Environmental Deterioration ◽  
Rural Sites ◽  
The Rasch Model

Atmospheric pollution is affected by different individual pollutants (IP) and climatic factors (CF). In this work, the formulation of the Rasch model is proposed to get representative measures of atmospheric pollution in two urban locations, Badajoz and Cáceres, and one rural site, the Monfragüe Park (Southwest Spain). After applying the Rasch methodology, the ranking of all days was obtained according to their atmospheric pollution level and the influence on the environmental deterioration of each IP and CF (NO2, NO, SO2, O3, CO, benzene, PM10, precipitation, relative humidity, solar radiation, air temperature, and barometric pressure). The most influential items on atmospheric pollution are the O3 and the CF, mainly the lack of precipitation and those related to ozone generation (air temperature and solar radiation). Other IP exert a lower influence at both urban locations, being irrelevant at the Monfragüe Park. Unexpected behaviors of the CF or IP can be also analyzed.

scholarly journals Árbol De Decisión, Aplicación Con Datos Meteorológicos/Decision Tree, Application With Meteorological Data

2020 ◽  
Author(s):  
Silvia Mariana Haro Rivera
Keyword(s):  
Data Mining ◽  
Solar Radiation ◽  
Decision Tree ◽  
Air Temperature ◽  
Meteorological Data ◽  
Barometric Pressure ◽  
Global Solar Radiation ◽  
Meteorological Variables ◽  
Diffuse Solar Radiation ◽  
Abstract Data

La minería de datos es una técnica que hoy en día se aplica en muchas áreas de las ciencias, es por ello que con el objetivo de identificar variables meteorológicas predominantes a ocho intervalos de tiempo se aplicó la técnica supervisada árbol de clasificación en data mining. La información se obtuvo de la estación Alao, misma que se encuentra ubicada a 3064 m.s.m en la provincia de Chimborazo, Ecuador. El estudio se realizó mediante código desarrollado en el software estadístico R; los datos corresponden a información por hora del año 2016, las variables analizadas fueron; temperatura del aire, humedad relativa, presión barométrica, radiación solar difusa, radiación solar global, temperatura del suelo a −20cm y velocidad de viento. El árbol mostró que la principal variable en esta zona es la radiación solar global, a horas comprendidas de 06h00 a 08h00, si ésta es mayor o igual a 120w/m2, entonces se puede determinar la presión barométrica de 09h00 a 11h00 de la mañana; y si ésta es mayor o igual que 709w/m2, entonces se predice la temperatura del aire. El árbol de decisión es una técnica que permitió identificar variables meteorológicas relevantes, en determinadas horas donde se encuentra ubicada la estación Alao. Abstract: Data mining is a technique that today is applied in many areas of science, which is why in order to identify predominant meteorological variables at eight time intervals the supervised tree classification technique was applied in data mining. The information was obtained from the Alao station, which is located at 3064 m.s.m in the province of Chimborazo, Ecuador. The study was carried out using a code developed in statistical software R, the data correspond to information by hour of the year 2016, the variables analyzes were air temperature, relative humidity, barometric pressure, diffuse solar radiation, global solar radiation, soil temperature at −20cm and wind speed. The showed that the main variable in this area is the global solar radiation, at hours between 06h00 and 08h00, if it is greater than or equal to 120w/m2, then the barometric pressure can be determined from 09h00 to 11h00 of the morning, if, and it is great than or equal to 709w/m2, then the air temperature is predicted. The decision tree is a technique that allowed us to identify relevant meteorological variables in certain hours where the Alao station is located. Palabras clave: árboles de decisión, datos meteorológicos. Keywords: decision tree, meteorological data.

scholarly journals EVALUATION OF THE AMMONIA AIR POLLUTION AND CLIMATIC FACTORS INTERACTIONS, CASE STUDY 2008 BACAU CITY ROMANIA

2016 ◽  
Vol 22 (1) ◽  
pp. 24-31
Author(s):  
DOINA CAPȘA ◽  
NARCIS BÂRSAN ◽  
VALENTIN NEDEFF ◽  
EMILIAN MOȘNEGUȚU ◽  
DANA CHIȚIMUȘ
Keyword(s):  
Air Pollution ◽  
Solar Radiation ◽  
Atmospheric Pollution ◽  
Research Methodology ◽  
Meteorological Factors ◽  
Climatic Factors ◽  
Sunshine Duration ◽  
Air Pollutant ◽  
Economic Activities

Atmospheric pollution present interest for monitoring and analysis when one or more substances or mixture of pollutants are present in the atmosphere in quantities or for a period that can be dangerous for humans, animals or plants and contribute to endangering the activity or welfare of persons. The present research was aimed to establish a link between meteorological factors (temperature, wind, atmospherically humidity, solar radiation, air pressure) and the ammonia air pollutant. Particularities of research methodology consisted in establishing a connection between meteorological factors in Bacau area and its air quality, taking into account both direct and inverse effects induced by geographical complexity and economic activities. The correlations between ammonia air pollution and analyzed climatic factors variation were realized by graphical interpretations and observing the appropriate links of dependency. In one of the case (2008.08.20) a better dispersion of pollutants occurs in the case of sunshine duration over a longer period, without or with low nebulosity.

scholarly journals Determination of the dependence between climatic factors and Covid-19 disease incidence

2021 ◽  
Vol 38 (2) ◽  
pp. 94-103
Author(s):  
Olena P. Mitryasova ◽  
Anna S. Pryhodko
Keyword(s):  
Wind Speed ◽  
Solar Radiation ◽  
Correlation Coefficient ◽  
Air Temperature ◽  
Climatic Factors ◽  
Disease Incidence ◽  
Inverse Correlation ◽  
Disease Spread ◽  
Scientific Methods

The purpose of research consists in definition and an estimation of climatic factors influence on disease incidence of Covid-19 on an example of Mykolaiv city. In research we used such scientific methods: theoretical methods: analysis, synthesis, monitoring, systematization, generalization. For research facility, were held by calculations based on software Microsoft Excel. The calculations were performed using the formula correlation. Results. The study examines the influence of climatic factors such as air temperature, humidity, solar radiation activity, wind speed, rainfall, and length of daylight. For the pair «Disease incidence – Temperature» the correlation coefficient is −0.74. For the pair «Disease incidence − Solar Radiation» correlation coefficient is −0.71. For the pair «Disease incidence – Daylight hours» correlation coefficient is −0.70. Humidity, as a derivative of air temperature, is evidenced by a comparison of decline periods and growth of these values. In the spring, along with the increase in temperature, the humidity dropped, and in the fall, when the air temperature dropped, the humidity increased. This factor also affected the spread of the virus in the second half of the year, when the humidity increased the virus began to spread faster. For the pair «Disease incidence – Humidity» correlation coefficient is +0.73 (average direct correlation). Other climatic factors, such as wind speed and rainfall, have not been shown to have a significant effect on the rate of disease spread. For the pair «Disease incidence − Wind speed» correlation coefficient is +0.32, which corresponds to a weak direct correlation. For the pair «Disease incidence − Rainfall» correlation coefficient is −0.30, which indicates a weak inverse correlation. Conclusion. The results of the study show that the reduction of disease incidence is observed at high temperatures, high activity of solar radiation, and prolonged daylight, which determines the conditions for the prevention of such diseases and will improve the quality of life to achieve sustainable development.

scholarly journals Contributions of Climatic Factors to Interannual Variability of the Vegetation Index in Northern China Grasslands

2020 ◽  
Vol 33 (1) ◽  
pp. 175-183 ◽  
Author(s):  
Wei Zhao ◽  
Zhongmin Hu ◽  
Qun Guo ◽  
Genan Wu ◽  
Ruru Chen ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Solar Radiation ◽  
Air Temperature ◽  
Vegetation Index ◽  
Climatic Factors ◽  
Explanatory Power ◽  
Regional Scale ◽  
Temperate Grasslands ◽  
Study Region ◽  
Vegetation Activities

AbstractUnderstanding the atmosphere–land surface interaction is crucial for clarifying the responses and feedbacks of terrestrial ecosystems to climate change. However, quantifying the effects of multiple climatic factors to vegetation activities is challenging. Using the geographical detector model (GDM), this study quantifies the relative contributions of climatic factors including precipitation, relative humidity, solar radiation, and air temperature to the interannual variation (IAV) of the normalized difference vegetation index (NDVI) in the northern grasslands of China during 2000 to 2016. The results show heterogeneous spatial patterns of determinant climatic factors on the IAV of NDVI. Precipitation and relative humidity jointly controlled the IAV of NDVI, illustrating more explanatory power than solar radiation and air temperature, and accounting for higher proportion of area as the determinant factor in the study region. It is noteworthy that relative humidity, a proxy of atmospheric aridity, is as important as precipitation for the IAV of NDVI. The contribution of climatic factors to the IAV of NDVI varied by vegetation type. Owing to the stronger explanatory power of climatic factors on NDVI variability in temperate grasslands, we conclude that climate variability may exert more influence on temperate grasslands than on alpine grasslands. Our study highlights the importance of the role of atmospheric aridity to vegetation activities in grasslands. We suggest focusing more on the differences between vegetation types when addressing the climate–vegetation relationships at a regional scale.

scholarly journals Prediction of Temperature Distribution for Previous Cement Concrete Pavement with Asphalt Overlay

2020 ◽  
Vol 10 (11) ◽  
pp. 3697
Author(s):  
Lijuan Zhang ◽  
Jianwu Huang ◽  
Peilong Li
Keyword(s):  
Temperature Distribution ◽  
Solar Radiation ◽  
Air Temperature ◽  
Climatic Factors ◽  
Concrete Pavement ◽  
Inverse Laplace Transform ◽  
Surface Boundary ◽  
Cement Concrete ◽  
Asphalt Overlay ◽  
Cement Concrete Pavement

In this study, the temperature distribution of a pavement was predicted by developing an analytic algorithm. The Laplace and inverse Laplace transform techniques and Gaussian quadratic formula were applied to a pavement system of an asphalt overlay placed over an existing concrete pavement. The temperature distribution of the previous cement concrete pavement with an asphalt overlay can be estimated with the proposed analytical method regardless of the depth and time. To conduct the method, the layer thicknesses, material thermal properties and climatic factors (including air temperature, wind velocity and solar radiation) were firstly input. Then, a discrete least-squares approximation of the interpolatory trigonometric polynomials was used to fit some specific measured climatic factors considered in the surface boundary condition, i.e., the measured solar radiation intensity and air temperature. The pavement surface convection coefficient can be approximately calculated by the wind speed. The temperature solutions are validated with the measured pavement temperature data of two different periods of a whole year (summer and winter). The obtained results demonstrate the feasibility of the developed analytical approach to predict the temperature distribution of the existing cement concrete pavement with an asphalt overlay in different weather conditions with acceptable accuracy.

scholarly journals Detrended Multiple Cross-Correlation Coefficient applied to solar radiation, air temperature and relative humidity

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Andrea de Almeida Brito ◽  
Heráclio Alves de Araújo ◽  
Gilney Figueira Zebende
Keyword(s):  
Relative Humidity ◽  
Solar Radiation ◽  
Solar Energy ◽  
Correlation Coefficient ◽  
Air Temperature ◽  
Cross Correlation ◽  
Global Solar Radiation ◽  
Meteorological Variables ◽  
Hourly Data ◽  
Cross Correlations

AbstractDue to the importance of generating energy sustainably, with the Sun being a large solar power plant for the Earth, we study the cross-correlations between the main meteorological variables (global solar radiation, air temperature, and relative air humidity) from a global cross-correlation perspective to efficiently capture solar energy. This is done initially between pairs of these variables, with the Detrended Cross-Correlation Coefficient, ρDCCA, and subsequently with the recently developed Multiple Detrended Cross-Correlation Coefficient, $${\boldsymbol{DM}}{{\boldsymbol{C}}}_{{\bf{x}}}^{{\bf{2}}}$$DMCx2. We use the hourly data from three meteorological stations of the Brazilian Institute of Meteorology located in the state of Bahia (Brazil). Initially, with the original data, we set up a color map for each variable to show the time dynamics. After, ρDCCA was calculated, thus obtaining a positive value between the global solar radiation and air temperature, and a negative value between the global solar radiation and air relative humidity, for all time scales. Finally, for the first time, was applied $${\boldsymbol{DM}}{{\boldsymbol{C}}}_{{\bf{x}}}^{{\bf{2}}}$$DMCx2 to analyze cross-correlations between three meteorological variables at the same time. On taking the global radiation as the dependent variable, and assuming that $${\boldsymbol{DM}}{{\boldsymbol{C}}}_{{\bf{x}}}^{{\bf{2}}}={\bf{1}}$$DMCx2=1 (which varies from 0 to 1) is the ideal value for the capture of solar energy, our analysis finds some patterns (differences) involving these meteorological stations with a high intensity of annual solar radiation.

scholarly journals Solar Radiation, Air Temperature, Relative Humidity, and Dew Point Study: Damak, Jhapa, Nepal

2019 ◽  
Vol 2019 ◽  
pp. 1-7 ◽  
Author(s):  
Arun Kumar Shrestha ◽  
Arati Thapa ◽  
Hima Gautam
Keyword(s):  
Relative Humidity ◽  
Solar Radiation ◽  
Air Temperature ◽  
Gaussian Function ◽  
Great Influence ◽  
Dew Point ◽  
Upward Trend ◽  
Summer Maximum ◽  
Online Calculator ◽  
Climatic Phenomenon

Monitoring and prediction of the climatic phenomenon are of keen interest in recent years because it has great influence in the lives of people and their environments. This paper is aimed at reporting the variation of daily and monthly solar radiation, air temperature, relative humidity (RH), and dew point over the year of 2013 based on the data obtained from the weather station situated in Damak, Nepal. The result shows that on a clear day, the variation of solar radiation and RH follows the Gaussian function in which the first one has an upward trend and the second one has a downward trend. However, the change in air temperature satisfies the sine function. The dew point temperature shows somewhat complex behavior. Monthly variation of solar radiation, air temperature, and dew point shows a similar pattern, lower at winter and higher in summer. Maximum solar radiation (331 Wm-2) was observed in May and minimum (170 Wm-2) in December. Air temperature and dew point had the highest value from June to September nearly at 29°C and 25°C, respectively. The lowest value of the relative humidity (55.4%) in April indicates the driest month of the year. Dew point was also calculated from the actual readings of air temperature and relative humidity using the online calculator, and the calculated value showed the exact linear relationship with the observed value. The diurnal and nocturnal temperature of each month showed that temperature difference was relatively lower (less than 10°C) at summer rather than in winter.

Interval of days required for determining efficient relations between climatic factors and cotton flower and boll production

2002 ◽  
Vol 82 (3) ◽  
pp. 499-506 ◽  
Author(s):  
Zakaria M Sawan ◽  
Louis I Hanna ◽  
Willis L McCuistion
Keyword(s):  
Soil Temperature ◽  
Air Temperature ◽  
Surface Soil ◽  
Cultural Practices ◽  
Agricultural Research ◽  
Climatic Factors ◽  
Sunshine Duration ◽  
Field Trials ◽  
Cotton Production ◽  
Surface Soil Temperature

The cotton plant (Gossypium spp.) is sensitive to numerous environmental factors. This study was aimed at predicting effects of climatic factors grouped into convenient intervals (in days) on cotton flower and boll production compared with daily observations. Two uniformity field trials using the cotton (G. barbadense L.) cv. Giza 75 were conducted in 1992 and 1993 at the Agricultural Research Center, Giza, Egypt. Randomly chosen plants were used to record daily numbers of flowers and bolls during the reproductive stage (60 days). During this period, daily air temperature, temperature magnitude, evaporation, surface soil temperature, sunshine duration, humidity, and wind speed were recorded. Data, grouped into intervals of 2, 3, 4, 5, 6, and 10 d, were correlated with cotton production variables using regression analysis. Evaporation was found to be the most important climatic variable affecting flower and boll production, followed by humidity and sunshine duration. The least important variables were surface soil temperature at 0600 and minimum air temperature. The 5-d interval was found to provide the best correlation with yield parameters. Applying appropriate cultural practices that minimize the deleterious effects of evaporation and humidity could lead to an important improvement in cotton yield in Egypt. Key words: Cotton, flower production, boll production, boll retention

scholarly journals Transmission of solar radiation through clouds on melting glaciers: a comparison of parameterizations and their impact on melt modelling

2011 ◽  
Vol 57 (202) ◽  
pp. 367-381 ◽  
Author(s):  
Francesca Pellicciotti ◽  
Thomas Raschle ◽  
Thomas Huerlimann ◽  
Marco Carenzo ◽  
Paolo Burlando
Keyword(s):  
Solar Radiation ◽  
Air Temperature ◽  
Radiative Forcing ◽  
Model Performance ◽  
Horizontal Resolution ◽  
Swiss Alps ◽  
Cloud Radiative Forcing ◽  
Correct Definition ◽  
Diurnal Range ◽  
The Impact

AbstractWe explore the robustness and transferability of parameterizations of cloud radiative forcing used in glacier melt models at two sites in the Swiss Alps. We also look at the rationale behind some of the most commonly used approaches, and explore the relationship between cloud transmittance and several standard meteorological variables. The 2 m air-temperature diurnal range is the best predictor of variations in cloud transmittance. However, linear and exponential parameterizations can only explain 30–50% of the observed variance in computed cloud transmittance factors. We examine the impact of modelled cloud transmittance factors on both solar radiation and ablation rates computed with an enhanced temperature-index model. The melt model performance decreases when modelled radiation is used, the reduction being due to an underestimation of incoming solar radiation on clear-sky days. The model works well under overcast conditions. We also seek alternatives to the use of in situ ground data. However, outputs from an atmospheric model (2.2 km horizontal resolution) do not seem to provide an alternative to the parameterizations of cloud radiative forcing based on observations of air temperature at glacier automatic weather stations. Conversely, the correct definition of overcast conditions is important.

Sign in / Sign up

Export Citation Format

Share Document