Search results for: meteorological model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 16981

Search results for: meteorological model

16891 Application and Aspects of Biometeorology in Inland Open Water Fisheries Management in the Context of Changing Climate: Status and Research Needs

Authors: U.K. Sarkar, G. Karnatak, P. Mishal, Lianthuamluaia, S. Kumari, S.K. Das, B.K. Das

Abstract:

Inland open water fisheries provide food, income, livelihood and nutritional security to millions of fishers across the globe. However, the open water ecosystem and fisheries are threatened due to climate change and anthropogenic pressures, which are more visible in the recent six decades, making the resources vulnerable. Understanding the interaction between meteorological parameters and inland fisheries is imperative to develop mitigation and adaptation strategies. As per IPCC 5th assessment report, the earth is warming at a faster rate in recent decades. Global mean surface temperature (GMST) for the decade 2006–2015 (0.87°C) was 6 times higher than the average over the 1850–1900 period. The direct and indirect impacts of climatic parameters on the ecology of fisheries ecosystem have a great bearing on fisheries due to alterations in fish physiology. The impact of meteorological factors on ecosystem health and fish food organisms brings about changes in fish diversity, assemblage, reproduction and natural recruitment. India’s average temperature has risen by around 0.7°C during 1901–2018. The studies show that the mean air temperature in the Ganga basin has increased in the range of 0.20 - 0.47 °C and annual rainfall decreased in the range of 257-580 mm during the last three decades. The studies clearly indicate visible impacts of climatic and environmental factors on inland open water fisheries. Besides, a significant reduction in-depth and area (37.20–57.68% reduction), diversity of natural indigenous fish fauna (ranging from 22.85 to 54%) in wetlands and progression of trophic state from mesotrophic to eutrophic were recorded. In this communication, different applications of biometeorology in inland fisheries management with special reference to the assessment of ecosystem and species vulnerability to climatic variability and change have been discussed. Further, the paper discusses the impact of climate anomaly and extreme climatic events on inland fisheries and emphasizes novel modeling approaches for understanding the impact of climatic and environmental factors on reproductive phenology for identification of climate-sensitive/resilient fish species for the adoption of climate-smart fisheries in the future. Adaptation and mitigation strategies to enhance fish production and the role of culture-based fisheries and enclosure culture in converting sequestered carbon into blue carbon have also been discussed. In general, the type and direction of influence of meteorological parameters on fish biology in open water fisheries ecosystems are not adequately understood. The optimum range of meteorological parameters for sustaining inland open water fisheries is yet to be established. Therefore, the application of biometeorology in inland fisheries offers ample scope for understanding the dynamics in changing climate, which would help to develop a database on such least, addressed research frontier area. This would further help to project fisheries scenarios in changing climate regimes and develop adaptation and mitigation strategies to cope up with adverse meteorological factors to sustain fisheries and to conserve aquatic ecosystem and biodiversity.

Keywords: biometeorology, inland fisheries, aquatic ecosystem, modeling, India

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16890 Vehicular Emission Estimation of Islamabad by Using Copert-5 Model

Authors: Muhammad Jahanzaib, Muhammad Z. A. Khan, Junaid Khayyam

Abstract:

Islamabad is the capital of Pakistan with the population of 1.365 million people and with a vehicular fleet size of 0.75 million. The vehicular fleet size is growing annually by the rate of 11%. Vehicular emissions are major source of Black carbon (BC). In developing countries like Pakistan, most of the vehicles consume conventional fuels like Petrol, Diesel, and CNG. These fuels are the major emitters of pollutants like CO, CO2, NOx, CH4, VOCs, and particulate matter (PM10). Carbon dioxide and methane are the leading contributor to the global warming with a global share of 9-26% and 4-9% respectively. NOx is the precursor of nitrates which ultimately form aerosols that are noxious to human health. In this study, COPERT (Computer program to Calculate Emissions from Road Transport) was used for vehicular emission estimation in Islamabad. COPERT is a windows based program which is developed for the calculation of emissions from the road transport sector. The emissions were calculated for the year of 2016 include pollutants like CO, NOx, VOC, and PM and energy consumption. The different variable was input to the model for emission estimation including meteorological parameters, average vehicular trip length and respective time duration, fleet configuration, activity data, degradation factor, and fuel effect. The estimated emissions for CO, CH4, CO2, NOx, and PM10 were found to be 9814.2, 44.9, 279196.7, 3744.2 and 304.5 tons respectively.

Keywords: COPERT Model, emission estimation, PM10, vehicular emission

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16889 Investigating the Urban Heat Island Phenomenon in A Desert City Aiming at Sustainable Buildings

Authors: Afifa Mohammed, Gloria Pignatta, Mattheos Santamouris, Evangelia Topriska

Abstract:

Climate change is one of the global challenges that is exacerbated by the rapid growth of urbanizations. Urban Heat Island (UHI) phenomenon can be considered as an effect of the urbanization and it is responsible together with the Climate change of the overheating of urban cities and downtowns. The purpose of this paper is to quantify and perform analysis of UHI Intensity in Dubai, United Arab Emirates (UAE), through checking the relationship between the UHI and different meteorological parameters (e.g., temperature, winds speed, winds direction). Climate data were collected from three meteorological stations in Dubai (e.g., Dubai Airport - Station 1, Al-Maktoum Airport - Station 2 and Saih Al-Salem - Station 3) for a period of five years (e.g., 2014 – 2018) based upon hourly rates, and following clustering technique as one of the methodology tools of measurements. The collected data of each station were divided into six clusters upon the winds directions, either from the seaside or from the desert side, or from the coastal side which is in between both aforementioned winds sources, to investigate the relationship between temperature degrees and winds speed values through UHI measurements for Dubai Airport - Station 1 compared with the same of Al-Maktoum Airport - Station 2. In this case, the UHI value is determined by the temperature difference of both stations, where Station 1 is considered as located in an urban area and Station 2 is considered as located in a suburban area. The same UHI calculations has been applied for Al-Maktoum Airport - Station 2 and Saih Salem - Station 3 where Station 2 is considered as located in an urban area and Station 3 is considered as located in a suburban area. The performed analysis aims to investigate the relation between the two environmental parameters (e.g., Temperature and Winds Speed) and the Urban Heat Island (UHI) intensity when the wind comes from the seaside, from the desert, and the remaining directions. The analysis shows that the correlation between the temperatures with both UHI intensity (e.g., temperature difference between Dubai Airport - Station 1 and Saih Al-Salem - Station 3 and between Al-Maktoum Airport - Station 2 and Saih Al-Salem - Station 3 (through station 1 & 2) is strong and has a negative relationship when the wind is coming from the seaside comparing between the two stations 1 and 2, while the relationship is almost zero (no relation) when the wind is coming from the desert side. The relation is independent between the two parameters, e.g., temperature and UHI, on Station 2, during the same procedures, the correlation between the urban heat island UHI phenomenon and wind speed is weak for both stations when wind direction is coming from the seaside comparing the station 1 and 2, while it was found that there’s no relationship between urban heat island phenomenon and wind speed when wind direction is coming from desert side. The conclusion could be summarized saying that the wind coming from the seaside or from the desert side have a different effect on UHI, which is strongly affected by meteorological parameters. The output of this study will enable more determination of UHI phenomenon under desert climate, which will help to inform about the UHI phenomenon and intensity and extract recommendations in two main categories such as planning of new cities and designing of buildings.

Keywords: meteorological data, subtropical desert climate, urban climate, urban heat island (UHI)

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16888 Flood Simulation and Forecasting for Sustainable Planning of Response in Municipalities

Authors: Mariana Damova, Stanko Stankov, Emil Stoyanov, Hristo Hristov, Hermand Pessek, Plamen Chernev

Abstract:

We will present one of the first use cases on the DestinE platform, a joint initiative of the European Commission, European Space Agency and EUMETSAT, providing access to global earth observation, meteorological and statistical data, and emphasize the good practice of intergovernmental agencies acting in concert. Further, we will discuss the importance of space-bound disruptive solutions for improving the balance between the ever-increasing water-related disasters coming from climate change and minimizing their economic and societal impact. The use case focuses on forecasting floods and estimating the impact of flood events on the urban environment and the ecosystems in the affected areas with the purpose of helping municipal decision-makers to analyze and plan resource needs and to forge human-environment relationships by providing farmers with insightful information for improving their agricultural productivity. For the forecast, we will adopt an EO4AI method of our platform ISME-HYDRO, in which we employ a pipeline of neural networks applied to in-situ measurements and satellite data of meteorological factors influencing the hydrological and hydrodynamic status of rivers and dams, such as precipitations, soil moisture, vegetation index, snow cover to model flood events and their span. ISME-HYDRO platform is an e-infrastructure for water resources management based on linked data, extended with further intelligence that generates forecasts with the method described above, throws alerts, formulates queries, provides superior interactivity and drives communication with the users. It provides synchronized visualization of table views, graphviews and interactive maps. It will be federated with the DestinE platform.

Keywords: flood simulation, AI, Earth observation, e-Infrastructure, flood forecasting, flood areas localization, response planning, resource estimation

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16887 Towards a Sustainable Energy Future: Method Used in Existing Buildings to Implement Sustainable Energy Technologies

Authors: Georgi Vendramin, Aurea Lúcia, Yamamoto, Carlos Itsuo, Souza Melegari, N. Samuel

Abstract:

This article describes the development of a model that uses a method where openings are represented by single glass and double glass. The model is based on a healthy balance equations purely theoretical and empirical data. Simplified equations are derived through a synthesis of the measured data obtained from meteorological stations. The implementation of the model in a design tool integrated buildings is discussed in this article, to better punctuate the requirements of comfort and energy efficiency in architecture and engineering. Sustainability, energy efficiency, and the integration of alternative energy systems and concepts are beginning to be incorporated into designs for new buildings and renovations to existing buildings. Few means have existed to effectively validate the potential performance benefits of the design concepts. It was used a method of degree-days for an assessment of the energy performance of a building showed that the design of the architectural design should always be considered the materials used and the size of the openings. The energy performance was obtained through the model, considering the location of the building Central Park Shopping Mall, in the city of Cascavel - PR. Obtained climatic data of these locations and in a second step, it was obtained the coefficient of total heat loss in the building pre-established so evaluating the thermal comfort and energy performance. This means that the more openings in buildings in Cascavel – PR, installed to the east side, they may be higher because the glass added to the geometry of architectural spaces will cause the environment conserve energy.

Keywords: sustainable design, energy modeling, design validation, degree-days methods

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16886 Advanced Analysis on Dissemination of Pollutant Caused by Flaring System Effect Using Computational Fluid Dynamics (CFD) Fluent Model with WRF Model Input in Transition Season

Authors: Benedictus Asriparusa

Abstract:

In the area of the oil industry, there is accompanied by associated natural gas. The thing shows that a large amount of energy is being wasted mostly in the developing countries by contributing to the global warming process. This research represents an overview of methods in Minas area employed by these researchers in PT. Chevron Pacific Indonesia to determine ways of measuring and reducing gas flaring and its emission drastically. It provides an approximation includes analytical studies, numerical studies, modeling, computer simulations, etc. Flaring system is the controlled burning of natural gas in the course of routine oil and gas production operations. This burning occurs at the end of a flare stack or boom. The combustion process will release emissions of greenhouse gases such as NO2, CO2, SO2, etc. This condition will affect the air and environment around the industrial area. Therefore, we need a simulation to create the pattern of the dissemination of pollutant. This research paper has being made to see trends in gas flaring model and current developments to predict dominant variable which gives impact to dissemination of pollutant. Fluent models used to simulate the distribution of pollutant gas coming out of the stack. While WRF model output is used to overcome the limitations of the analysis of meteorological data and atmospheric conditions in the study area. This study condition focused on transition season in 2012 at Minas area. The goal of the simulation is looking for the exact time which is most influence towards dissemination of pollutants. The most influence factor divided into two main subjects. It is the quickest wind and the slowest wind. According to the simulation results, it can be seen that quickest wind moves to horizontal way and slowest wind moves to vertical way.

Keywords: flaring system, fluent model, dissemination of pollutant, transition season

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16885 Effects of Convective Momentum Transport on the Cyclones Intensity: A Case Study

Authors: José Davi Oliveira De Moura, Chou Sin Chan

Abstract:

In this study, the effect of convective momentum transport (CMT) on the life of cyclone systems and their organization is analyzed. A case of strong precipitation, in the southeast of Brazil, was simulated using Eta model with two kinds of convective parameterization: Kain-Fritsch without CMT and Kain-fritsch with CMT. Reanalysis data from CFSR were used to compare Eta model simulations. The Wind, mean sea level pressure, rain and temperature are included in analysis. The rain was evaluated by Equitable Threat Score (ETS) and Bias Index; the simulations were compared among themselves to detect the influence of CMT displacement on the systems. The result shows that CMT process decreases the intensity of meso cyclones (higher pressure values on nuclei) and change the positions and production of rain. The decrease of intensity in meso cyclones should be caused by the dissolution of momentum from lower levels from up levels. The rain production and rain distribution were altered because the displacement of the larger systems scales was changed. In addition, the inclusion of CMT process is very important to improve the simulation of life time of meteorological systems.

Keywords: convection, Kain-Fritsch, momentum, parameterization

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16884 Outdoor Visible Light Communication Channel Modeling under Fog and Smoke Conditions

Authors: Véronique Georlette, Sebastien Bette, Sylvain Brohez, Nicolas Point, Veronique Moeyaert

Abstract:

Visible light communication (VLC) is a communication technology that is part of the optical wireless communication (OWC) family. It uses the visible and infrared spectrums to send data. For now, this technology has widely been studied for indoor use-cases, but it is sufficiently mature nowadays to consider the outdoor environment potentials. The main outdoor challenges are the meteorological conditions and the presence of smoke due to fire or pollutants in urban areas. This paper proposes a methodology to assess the robustness of an outdoor VLC system given the outdoor conditions. This methodology is put into practice in two realistic scenarios, a VLC bus stop, and a VLC streetlight. The methodology consists of computing the power margin available in the system, given all the characteristics of the VLC system and its surroundings. This is done thanks to an outdoor VLC communication channel simulator developed in Python. This simulator is able to quantify the effects of fog and smoke thanks to models taken from environmental and fire engineering scientific literature as well as the optical power reaching the receiver. These two phenomena impact the communication by increasing the total attenuation of the medium. The main conclusion drawn in this paper is that the levels of attenuation due to fog and smoke are in the same order of magnitude. The attenuation of fog being the highest under the visibility of 1 km. This gives a promising prospect for the deployment of outdoor VLC uses-cases in the near future.

Keywords: channel modeling, fog modeling, meteorological conditions, optical wireless communication, smoke modeling, visible light communication

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16883 Regional Changes under Extreme Meteorological Events

Authors: Renalda El Samra, Elie Bou-Zeid, Hamza Kunhu Bangalath, Georgiy Stenchikov, Mutasem El Fadel

Abstract:

The regional-scale impact of climate change over complex terrain was examined through high-resolution dynamic downscaling conducted using the Weather Research and Forecasting (WRF) model, with initial and boundary conditions from a High-Resolution Atmospheric Model (HiRAM). The analysis was conducted over the eastern Mediterranean, with a focus on the country of Lebanon, which is characterized by a challenging complex topography that magnifies the effect of orographic precipitation. Four year-long WRF simulations, selected based on HiRAM time series, were performed to generate future climate projections of extreme temperature and precipitation over the study area under the conditions of the Representative Concentration Pathway (RCP) 4.5. One past WRF simulation year, 2008, was selected as a baseline to capture dry extremes of the system. The results indicate that the study area might be exposed to a temperature increase between 1.0 and 3ºC in summer mean values by 2050, in comparison to 2008. For extreme years, the decrease in average annual precipitation may exceed 50% at certain locations in comparison to 2008.

Keywords: HiRAM, regional climate modeling, WRF, Representative Concentration Pathway (RCP)

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16882 Numerical Simulation of Air Pollutant Using Coupled AERMOD-WRF Modeling System over Visakhapatnam: A Case Study

Authors: Amit Kumar

Abstract:

Accurate identification of deteriorated air quality regions is very helpful in devising better environmental practices and mitigation efforts. In the present study, an attempt has been made to identify the air pollutant dispersion patterns especially NOX due to vehicular and industrial sources over a rapidly developing urban city, Visakhapatnam (17°42’ N, 83°20’ E), India, during April 2009. Using the emission factors of different vehicles as well as the industry, a high resolution 1 km x 1 km gridded emission inventory has been developed for Visakhapatnam city. A dispersion model AERMOD with explicit representation of planetary boundary layer (PBL) dynamics and offline coupled through a developed coupler mechanism with a high resolution mesoscale model WRF-ARW resolution for simulating the dispersion patterns of NOX is used in the work. The meteorological as well as PBL parameters obtained by employing two PBL schemes viz., non-local Yonsei University (YSU) and local Mellor-Yamada-Janjic (MYJ) of WRF-ARW model, which are reasonably representing the boundary layer parameters are considered for integrating AERMOD. Significantly different dispersion patterns of NOX have been noticed between summer and winter months. The simulated NOX concentration is validated with available six monitoring stations of Central Pollution Control Board, India. Statistical analysis of model evaluated concentrations with the observations reveals that WRF-ARW of YSU scheme with AERMOD has shown better performance. The deteriorated air quality locations are identified over Visakhapatnam based on the validated model simulations of NOX concentrations. The present study advocates the utility of tNumerical Simulation of Air Pollutant Using Coupled AERMOD-WRF Modeling System over Visakhapatnam: A Case Studyhe developed gridded emission inventory of NOX with coupled WRF-AERMOD modeling system for air quality assessment over the study region.

Keywords: WRF-ARW, AERMOD, planetary boundary layer, air quality

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16881 A New Nonlinear State-Space Model and Its Application

Authors: Abdullah Eqal Al Mazrooei

Abstract:

In this work, a new nonlinear model will be introduced. The model is in the state-space form. The nonlinearity of this model is in the state equation where the state vector is multiplied by its self. This technique makes our model generalizes many famous models as Lotka-Volterra model and Lorenz model which have many applications in the real life. We will apply our new model to estimate the wind speed by using a new nonlinear estimator which suitable to work with our model.

Keywords: nonlinear systems, state-space model, Kronecker product, nonlinear estimator

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16880 Study of Climate Change Scenarios (IPCC) in the Littoral Zone of the Caspian Sea

Authors: L. Rashidian, M. Rajabali

Abstract:

Climate changes have unpredictable and costly effects on water resources of various basins. The impact of atmospheric phenomena on human life and the environment is so significant that only knowledge of management can reduce its consequences. In this study, using LARS.WG model and down scaling of general circulation climate model HADCM-3 and according to the IPCC scenarios, including series A1b, A2 and B1, we simulated data from 2010 to 2040 in order to using them for long term forecasting of climate parameters of the Caspian Sea and its impact on sea level. Our research involves collecting data on monthly precipitation amounts, minimum and maximum temperature and daily sunshine hours, from meteorological organization for Caspian Sea coastal station such as Gorgan, Ramsar, Rasht, Anzali, Astara and Ghaemshahr since their establishment until 2010. Considering the fact that the fluctuation range of water level in the Caspian Sea has various ups and downs in different times, there is an increase in minimum and maximum temperature for all the mentioned scenarios, which will last until 2040. Overall, the amount of rainfall in cities bordering the Caspian Sea was studied based on the three scenarios, which shows an increase in the amount. However, there will be a decrease in water level of the Caspian Sea till 2040.

Keywords: IPCC, climate change, atmospheric circulation, Caspian Sea, HADCM3, sea level

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16879 Development of pm2.5 Forecasting System in Seoul, South Korea Using Chemical Transport Modeling and ConvLSTM-DNN

Authors: Ji-Seok Koo, Hee‑Yong Kwon, Hui-Young Yun, Kyung-Hui Wang, Youn-Seo Koo

Abstract:

This paper presents a forecasting system for PM2.5 levels in Seoul, South Korea, leveraging a combination of chemical transport modeling and ConvLSTM-DNN machine learning technology. Exposure to PM2.5 has known detrimental impacts on public health, making its prediction crucial for establishing preventive measures. Existing forecasting models, like the Community Multiscale Air Quality (CMAQ) and Weather Research and Forecasting (WRF), are hindered by their reliance on uncertain input data, such as anthropogenic emissions and meteorological patterns, as well as certain intrinsic model limitations. The system we've developed specifically addresses these issues by integrating machine learning and using carefully selected input features that account for local and distant sources of PM2.5. In South Korea, the PM2.5 concentration is greatly influenced by both local emissions and long-range transport from China, and our model effectively captures these spatial and temporal dynamics. Our PM2.5 prediction system combines the strengths of advanced hybrid machine learning algorithms, convLSTM and DNN, to improve upon the limitations of the traditional CMAQ model. Data used in the system include forecasted information from CMAQ and WRF models, along with actual PM2.5 concentration and weather variable data from monitoring stations in China and South Korea. The system was implemented specifically for Seoul's PM2.5 forecasting.

Keywords: PM2.5 forecast, machine learning, convLSTM, DNN

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16878 The Challenge of Characterising Drought Risk in Data Scarce Regions: The Case of the South of Angola

Authors: Natalia Limones, Javier Marzo, Marcus Wijnen, Aleix Serrat-Capdevila

Abstract:

In this research we developed a structured approach for the detection of areas under the highest levels of drought risk that is suitable for data-scarce environments. The methodology is based on recent scientific outcomes and methods and can be easily adapted to different contexts in successive exercises. The research reviews the history of drought in the south of Angola and characterizes the experienced hazard in the episode from 2012, focusing on the meteorological and the hydrological drought types. Only global open data information coming from modeling or remote sensing was used for the description of the hydroclimatological variables since there is almost no ground data in this part of the country. Also, the study intends to portray the socioeconomic vulnerabilities and the exposure to the phenomenon in the region to fully understand the risk. As a result, a map of the areas under the highest risk in the south of the country is produced, which is one of the main outputs of this work. It was also possible to confirm that the set of indicators used revealed different drought vulnerability profiles in the South of Angola and, as a result, several varieties of priority areas prone to distinctive impacts were recognized. The results demonstrated that most of the region experienced a severe multi-year meteorological drought that triggered an unprecedent exhaustion of the surface water resources, and that the majority of their socioeconomic impacts started soon after the identified onset of these processes.

Keywords: drought risk, exposure, hazard, vulnerability

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16877 Statistical Modelling of Maximum Temperature in Rwanda Using Extreme Value Analysis

Authors: Emmanuel Iyamuremye, Edouard Singirankabo, Alexis Habineza, Yunvirusaba Nelson

Abstract:

Temperature is one of the most important climatic factors for crop production. However, severe temperatures cause drought, feverish and cold spells that have various consequences for human life, agriculture, and the environment in general. It is necessary to provide reliable information related to the incidents and the probability of such extreme events occurring. In the 21st century, the world faces a huge number of threats, especially from climate change, due to global warming and environmental degradation. The rise in temperature has a direct effect on the decrease in rainfall. This has an impact on crop growth and development, which in turn decreases crop yield and quality. Countries that are heavily dependent on agriculture use to suffer a lot and need to take preventive steps to overcome these challenges. The main objective of this study is to model the statistical behaviour of extreme maximum temperature values in Rwanda. To achieve such an objective, the daily temperature data spanned the period from January 2000 to December 2017 recorded at nine weather stations collected from the Rwanda Meteorological Agency were used. The two methods, namely the block maxima (BM) method and the Peaks Over Threshold (POT), were applied to model and analyse extreme temperature. Model parameters were estimated, while the extreme temperature return periods and confidence intervals were predicted. The model fit suggests Gumbel and Beta distributions to be the most appropriate models for the annual maximum of daily temperature. The results show that the temperature will continue to increase, as shown by estimated return levels.

Keywords: climate change, global warming, extreme value theory, rwanda, temperature, generalised extreme value distribution, generalised pareto distribution

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16876 Numerical Modelling of Wind Dispersal Seeds of Bromeliad Tillandsia recurvata L. (L.) Attached to Electric Power Lines

Authors: Bruna P. De Souza, Ricardo C. De Almeida

Abstract:

In some cities in the State of Parana – Brazil and in other countries atmospheric bromeliads (Tillandsia spp - Bromeliaceae) are considered weeds in trees, electric power lines, satellite dishes and other artificial supports. In this study, a numerical model was developed to simulate the seed dispersal of the Tillandsia recurvata species by wind with the objective of evaluating seeds displacement in the city of Ponta Grossa – PR, Brazil, since it is considered that the region is already infested. The model simulates the dispersal of each individual seed integrating parameters from the atmospheric boundary layer (ABL) and the local wind, simulated by the Weather Research Forecasting (WRF) mesoscale atmospheric model for the 2012 to 2015 period. The dispersal model also incorporates the approximate number of bromeliads and source height data collected from most infested electric power lines. The seeds terminal velocity, which is an important input data but was not available in the literature, was measured by an experiment with fifty-one seeds of Tillandsia recurvata. Wind is the main dispersal agent acting on plumed seeds whereas atmospheric turbulence is a determinant factor to transport the seeds to distances beyond 200 meters as well as to introduce random variability in the seed dispersal process. Such variability was added to the model through the application of an Inverse Fast Fourier Transform to wind velocity components energy spectra based on boundary-layer meteorology theory and estimated from micrometeorological parameters produced by the WRF model. Seasonal and annual wind means were obtained from the surface wind data simulated by WRF for Ponta Grossa. The mean wind direction is assumed to be the most probable direction of bromeliad seed trajectory. Moreover, the atmospheric turbulence effect and dispersal distances were analyzed in order to identify likely regions of infestation around Ponta Grossa urban area. It is important to mention that this model could be applied to any species and local as long as seed’s biological data and meteorological data for the region of interest are available.

Keywords: atmospheric turbulence, bromeliad, numerical model, seed dispersal, terminal velocity, wind

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16875 Impact of Air Pollution and Climate on the Incidence of Emergency Interventions in Slavonski Brod

Authors: Renata Josipovic, Ante Cvitkovic

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Particulate matter belongs to pollutants that can lead to respiratory problems or premature death due to exposure (long-term, short-term) to these substances, all depending on the severity of the effects. The importance of the study is to determine whether the existing climatic conditions in the period from January 1st to August 31st, 2018 increased the number of emergency interventions in Slavonski Brod with regard to pollutants hydrogen sulfide and particles less than 10 µm (PM10) and less than 2.5 µm (PM2.5). Analytical data of the concentration of pollutants are collected from the Croatian Meteorological and Hydrological Service, which monitors the operation of two meteorological stations in Slavonski Brod, as well as climatic conditions. Statistics data of emergency interventions were collected from the Emergency Medicine Department of Slavonski Brod. All data were compared (air pollution, emergency interventions) according to climatic conditions (air humidity and air temperature) and statistically processed. Statistical significance, although weak positive correlation PM2.5 (correlation coefficient 0.147; p = 0.036), determined PM10 (correlation coefficient 0.122; p = 0.048), hydrogen sulfide (correlation coefficient 0.141; p = 0.035) with max. temperature (correlation coefficient 0.202; p = 0.002) with number of interventions. The association between mean air humidity was significant but negative (correlation coefficient - 0.172; p = 0.007). The values of the influence of air pressure are not determined. As the problem of air pollution is very complex, coordinated action at many levels is needed to reduce air pollution in Slavonski Brod and consequences that can affect human health.

Keywords: emergency interventions, human health, hydrogen sulfide, particulate matter

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16874 A Descriptive Study of Turkish Straits System on Dynamics of Environmental Factors Causing Maritime Accidents

Authors: Gizem Kodak, Alper Unal, Birsen Koldemir, Tayfun Acarer

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Turkish Straits System which consists of Istanbul Strait (Bosphorus), Canakkale Strait (Dardanelles) and the Marmara Sea has a strategical location on international maritime as it is a unique waterway between the Mediterranean Sea, Black Sea and the Aegean Sea. Thus, this area has great importance since it is the only waterway between Black Sea countries and the rest of the World. Turkish Straits System has dangerous environmental factors hosts more vessel every day through developing World trade and this situation results in expanding accident risks day by day. Today, a lot of precautions have been taken to ensure safe navigation and to prevent maritime accidents, and international standards are followed to avoid maritime accidents. Despite this, the environmental factors that affect this area, trigger the maritime accidents and threaten the vessels with new accidents risks in different months with different hazards. This descriptive study consists of temporal and spatial analyses of environmental factors causing maritime accidents. This study also aims at contributing to safety navigation including monthly and regionally characteristics of variables. In this context, two different data sets are created consisting of environmental factors and accidents. This descriptive study on the accidents between 2001 and 2017 the mentioned region also studies the months and places of the accidents with environmental factor variables. Environmental factor variables are categorized as dynamic and static factors. Dynamic factors are appointed as meteorological and oceanographical while static factors are appointed as geological factors that threaten safety navigation with geometrical restricts. The variables that form dynamic factors are approached meteorological as wind direction, wind speed, wave altitude and visibility. The circulations and properties of the water mass on the system are studied as oceanographical properties. At the end of the study, the efficient meteorological and oceanographical parameters on the region are presented monthly and regionally. By this way, we acquired the monthly, seasonal and regional distributions of the accidents. Upon the analyses that are done; The Turkish Straits System that connects the Black Sea countries with the other countries and which is one of the most important parts of the world trade; is analyzed on temporal and spatial dimensions on the reasons of the accidents and have been presented as environmental factor dynamics causing maritime accidents.

Keywords: descriptive study, environmental factors, maritime accidents, statistics

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16873 Artificial Neural Network Approach for Modeling Very Short-Term Wind Speed Prediction

Authors: Joselito Medina-Marin, Maria G. Serna-Diaz, Juan C. Seck-Tuoh-Mora, Norberto Hernandez-Romero, Irving Barragán-Vite

Abstract:

Wind speed forecasting is an important issue for planning wind power generation facilities. The accuracy in the wind speed prediction allows a good performance of wind turbines for electricity generation. A model based on artificial neural networks is presented in this work. A dataset with atmospheric information about air temperature, atmospheric pressure, wind direction, and wind speed in Pachuca, Hidalgo, México, was used to train the artificial neural network. The data was downloaded from the web page of the National Meteorological Service of the Mexican government. The records were gathered for three months, with time intervals of ten minutes. This dataset was used to develop an iterative algorithm to create 1,110 ANNs, with different configurations, starting from one to three hidden layers and every hidden layer with a number of neurons from 1 to 10. Each ANN was trained with the Levenberg-Marquardt backpropagation algorithm, which is used to learn the relationship between input and output values. The model with the best performance contains three hidden layers and 9, 6, and 5 neurons, respectively; and the coefficient of determination obtained was r²=0.9414, and the Root Mean Squared Error is 1.0559. In summary, the ANN approach is suitable to predict the wind speed in Pachuca City because the r² value denotes a good fitting of gathered records, and the obtained ANN model can be used in the planning of wind power generation grids.

Keywords: wind power generation, artificial neural networks, wind speed, coefficient of determination

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16872 Atmospheric Dispersion Modeling for a Hypothetical Accidental Release from the 3 MW TRIGA Research Reactor of Bangladesh

Authors: G. R. Khan, Sadia Mahjabin, A. S. Mollah, M. R. Mawla

Abstract:

Atmospheric dispersion modeling is significant for any nuclear facilities in the country to predict the impact of radiological doses on environment as well as human health. That is why to ensure safety of workers and population at plant site; Atmospheric dispersion modeling and radiation dose calculations were carried out for a hypothetical accidental release of airborne radionuclide from the 3 MW TRIGA research reactor of Savar, Bangladesh. It is designed with reactor core which consists of 100 fuel elements(1.82245 cm in diameter and 38.1 cm in length), arranged in an annular corefor steady-state and square wave power level of 3 MW (thermal) and for pulsing with maximum power level of 860MWth.The fuel is in the form of a uniform mixture of 20% uranium and 80% zirconium hydride. Total effective doses (TEDs) to the public at various downwind distances were evaluated with a health physics computer code “HotSpot” developed by Lawrence Livermore National Laboratory, USA. The doses were estimated at different Pasquill stability classes (categories A-F) with site-specific averaged meteorological conditions. The meteorological data, such as, average wind speed, frequency distribution of wind direction, etc. have also been analyzed based on the data collected near the reactor site. The results of effective doses obtained remain within the recommended maximum effective dose.

Keywords: accidental release, dispersion modeling, total effective dose, TRIGA

Procedia PDF Downloads 136
16871 The Influence of Air Temperature Controls in Estimation of Air Temperature over Homogeneous Terrain

Authors: Fariza Yunus, Jasmee Jaafar, Zamalia Mahmud, Nurul Nisa’ Khairul Azmi, Nursalleh K. Chang, Nursalleh K. Chang

Abstract:

Variation of air temperature from one place to another is cause by air temperature controls. In general, the most important control of air temperature is elevation. Another significant independent variable in estimating air temperature is the location of meteorological stations. Distances to coastline and land use type are also contributed to significant variations in the air temperature. On the other hand, in homogeneous terrain direct interpolation of discrete points of air temperature work well to estimate air temperature values in un-sampled area. In this process the estimation is solely based on discrete points of air temperature. However, this study presents that air temperature controls also play significant roles in estimating air temperature over homogenous terrain of Peninsular Malaysia. An Inverse Distance Weighting (IDW) interpolation technique was adopted to generate continuous data of air temperature. This study compared two different datasets, observed mean monthly data of T, and estimation error of T–T’, where T’ estimated value from a multiple regression model. The multiple regression model considered eight independent variables of elevation, latitude, longitude, coastline, and four land use types of water bodies, forest, agriculture and build up areas, to represent the role of air temperature controls. Cross validation analysis was conducted to review accuracy of the estimation values. Final results show, estimation values of T–T’ produced lower errors for mean monthly mean air temperature over homogeneous terrain in Peninsular Malaysia.

Keywords: air temperature control, interpolation analysis, peninsular Malaysia, regression model, air temperature

Procedia PDF Downloads 372
16870 Impact Assessment of Climate Change on Water Resources in the Kabul River Basin

Authors: Tayib Bromand, Keisuke Sato

Abstract:

This paper presents the introduction to current water balance and climate change assessment in the Kabul river basin. The historical and future impacts of climate change on different components of water resources and hydrology in the Kabul river basin. The eastern part of Afghanistan, the Kabul river basin was chosen due to rapid population growth and land degradation to quantify the potential influence of Gobal Climate Change on its hydrodynamic characteristics. Luck of observed meteorological data was the main limitation of present research, few existed precipitation stations in the plain area of Kabul basin selected to compare with TRMM precipitation records, the result has been evaluated satisfactory based on regression and normal ratio methods. So the TRMM daily precipitation and NCEP temperature data set applied in the SWAT model to evaluate water balance for 2008 to 2012. Middle of the twenty – first century (2064) selected as the target period to assess impacts of climate change on hydrology aspects in the Kabul river basin. For this purpose three emission scenarios, A2, A1B and B1 and four GCMs, such as MIROC 3.2 (Med), CGCM 3.1 (T47), GFDL-CM2.0 and CNRM-CM3 have been selected, to estimate the future initial conditions of the proposed model. The outputs of the model compared and calibrated based on (R2) satisfactory. The assessed hydrodynamic characteristics and precipitation pattern. The results show that there will be significant impacts on precipitation patter such as decreasing of snowfall in the mountainous area of the basin in the Winter season due to increasing of 2.9°C mean annual temperature and land degradation due to deforestation.

Keywords: climate change, emission scenarios, hydrological components, Kabul river basin, SWAT model

Procedia PDF Downloads 464
16869 Assessing Future Offshore Wind Farms in the Gulf of Roses: Insights from Weather Research and Forecasting Model Version 4.2

Authors: Kurias George, Ildefonso Cuesta Romeo, Clara Salueña Pérez, Jordi Sole Olle

Abstract:

With the growing prevalence of wind energy there is a need, for modeling techniques to evaluate the impact of wind farms on meteorology and oceanography. This study presents an approach that utilizes the WRF (Weather Research and Forecasting )with that include a Wind Farm Parametrization model to simulate the dynamics around Parc Tramuntana project, a offshore wind farm to be located near the Gulf of Roses off the coast of Barcelona, Catalonia. The model incorporates parameterizations for wind turbines enabling a representation of the wind field and how it interacts with the infrastructure of the wind farm. Current results demonstrate that the model effectively captures variations in temeperature, pressure and in both wind speed and direction over time along with their resulting effects on power output from the wind farm. These findings are crucial for optimizing turbine placement and operation thus improving efficiency and sustainability of the wind farm. In addition to focusing on atmospheric interactions, this study delves into the wake effects within the turbines in the farm. A range of meteorological parameters were also considered to offer a comprehensive understanding of the farm's microclimate. The model was tested under different horizontal resolutions and farm layouts to scrutinize the wind farm's effects more closely. These experimental configurations allow for a nuanced understanding of how turbine wakes interact with each other and with the broader atmospheric and oceanic conditions. This modified approach serves as a potent tool for stakeholders in renewable energy, environmental protection, and marine spatial planning. environmental protection and marine spatial planning. It provides a range of information regarding the environmental and socio economic impacts of offshore wind energy projects.

Keywords: weather research and forecasting, wind turbine wake effects, environmental impact, wind farm parametrization, sustainability analysis

Procedia PDF Downloads 71
16868 Decision Support System for Optimal Placement of Wind Turbines in Electric Distribution Grid

Authors: Ahmed Ouammi

Abstract:

This paper presents an integrated decision framework to support decision makers in the selection and optimal allocation of wind power plants in the electric grid. The developed approach intends to maximize the benefice related to the project investment during the planning period. The proposed decision model considers the main cost components, meteorological data, environmental impacts, operation and regulation constraints, and territorial information. The decision framework is expressed as a stochastic constrained optimization problem with the aim to identify the suitable locations and related optimal wind turbine technology considering the operational constraints and maximizing the benefice. The developed decision support system is applied to a case study to demonstrate and validate its performance.

Keywords: decision support systems, electric power grid, optimization, wind energy

Procedia PDF Downloads 151
16867 Wind Energy Resources Assessment and Micrositting on Different Areas of Libya: The Case Study in Darnah

Authors: F. Ahwide, Y. Bouker, K. Hatem

Abstract:

This paper presents long term wind data analysis in terms of annual and diurnal variations at different areas of Libya. The data of the wind speed and direction are taken each ten minutes for a period, at least two years, are used in the analysis. ‘WindPRO’ software and Excel workbook were used for the wind statistics and energy calculations. As for Derna, average speeds are 10 m, 20 m, and 40 m, and respectively 6.57 m/s, 7.18 m/s, and 8.09 m/s. Highest wind speeds are observed at SSW, followed by S, WNW and NW sectors. Lowest wind speeds are observed between N and E sectors. Most frequent wind directions are NW and NNW. Hence, wind turbines can be installed against these directions. The most powerful sector is NW (29.4 % of total expected wind energy), followed by 19.9 % SSW, 11.9% NNW, 8.6% WNW and 8.2% S. Furthermore in Al-Maqrun: the most powerful sector is W (26.8 % of total expected wind energy), followed by 12.3 % WSW and 9.5% WNW. While in Goterria: the most powerful sector is S (14.8 % of total expected wind energy), followed by SSE, SE, and WSW. And Misalatha: the most powerful sector is S, by far represents 28.5% of the expected power, followed by SSE and SE. As for Tarhuna, it is by far SSE and SE, representing each one two times the expected energy of the third powerful sector (NW). In Al-Asaaba: it is SSE by far represents 50% of the expected power, followed by S. It can to be noted that the high frequency of the south direction winds, that come from the desert could cause a high frequency of dust episodes. This fact then, should be taken into account in order to take appropriate measures to prevent wind turbine deterioration. In Excel workbook, an estimation of annual energy yield at position of Derna, Al-Maqrun, Tarhuna, and Al-Asaaba meteorological mast has been done, considering a generic wind turbine of 1.65 MW. (mtORRES, TWT 82-1.65MW) in position of meteorological mast. Three other turbines have been tested. At 80 m, the estimation of energy yield for Derna, Al-Maqrun, Tarhuna, and Asaaba is 6.78 GWh or 3390 equivalent hours, 5.80 GWh or 2900 equivalent hours, 4.91 GWh or 2454 equivalent hours and 5.08 GWh or 2541 equivalent hours respectively. It seems a fair value in the context of a possible development of a wind energy project in the areas, considering a value of 2400 equivalent hours as an approximate limit to consider a wind warm economically profitable. Furthermore, an estimation of annual energy yield at positions of Misalatha, Azizyah and Goterria meteorological mast has been done, considering a generic wind turbine of 2 MW. We found that, at 80 m, the estimation of energy yield is 3.12 GWh or 1557 equivalent hours, 4.47 GWh or 2235 equivalent hours and 4.07GWh or 2033 respectively . It seems a very poor value in the context of possible development of a wind energy project in the areas, considering a value of 2400 equivalent hours as an approximate limit to consider a wind warm economically profitable. Anyway, more data and a detailed wind farm study would be necessary to draw conclusions.

Keywords: wind turbines, wind data, energy yield, micrositting

Procedia PDF Downloads 185
16866 The Study of Dengue Fever Outbreak in Thailand Using Geospatial Techniques, Satellite Remote Sensing Data and Big Data

Authors: Tanapat Chongkamunkong

Abstract:

The objective of this paper is to present a practical use of Geographic Information System (GIS) to the public health from spatial correlation between multiple factors and dengue fever outbreak. Meteorological factors, demographic factors and environmental factors are compiled using GIS techniques along with the Global Satellite Mapping Remote Sensing (RS) data. We use monthly dengue fever cases, population density, precipitation, Digital Elevation Model (DEM) data. The scope cover study area under climate change of the El Niño–Southern Oscillation (ENSO) indicated by sea surface temperature (SST) and study area in 12 provinces of Thailand as remote sensing (RS) data from January 2007 to December 2014.

Keywords: dengue fever, sea surface temperature, Geographic Information System (GIS), remote sensing

Procedia PDF Downloads 197
16865 Possibilities to Evaluate the Climatic and Meteorological Potential for Viticulture in Poland: The Case Study of the Jagiellonian University Vineyard

Authors: Oskar Sekowski

Abstract:

Current global warming causes changes in the traditional zones of viticulture worldwide. During 20th century, the average global air temperature increased by 0.89˚C. The models of climate change indicate that viticulture, currently concentrating in narrow geographic niches, may move towards the poles, to higher geographic latitudes. Global warming may cause changes in traditional viticulture regions. Therefore, there is a need to estimate the climatic conditions and climate change in areas that are not traditionally associated with viticulture, e.g., Poland. The primary objective of this paper is to prepare methodology to evaluate the climatic and meteorological potential for viticulture in Poland based on a case study. Moreover, the additional aim is to evaluate the climatic potential of a mesoregion where a university vineyard is located. The daily data of temperature, precipitation, insolation, and wind speed (1988-2018) from the meteorological station located in Łazy, southern Poland, was used to evaluate 15 climatological parameters and indices connected with viticulture. The next steps of the methodology are based on Geographic Information System methods. The topographical factors such as a slope gradient and slope exposure were created using Digital Elevation Models. The spatial distribution of climatological elements was interpolated by ordinary kriging. The values of each factor and indices were also ranked and classified. The viticultural potential was determined by integrating two suitability maps, i.e., the topographical and climatic ones, and by calculating the average for each pixel. Data analysis shows significant changes in heat accumulation indices that are driven by increases in maximum temperature, mostly increasing number of days with Tmax > 30˚C. The climatic conditions of this mesoregion are sufficient for vitis vinifera viticulture. The values of indicators and insolation are similar to those in the known wine regions located on similar geographical latitudes in Europe. The smallest threat to viticulture in study area is the occurrence of hail and the highest occurrence of frost in the winter. This research provides the basis for evaluating general suitability and climatologic potential for viticulture in Poland. To characterize the climatic potential for viticulture, it is necessary to assess the suitability of all climatological and topographical factors that can influence viticulture. The methodology used in this case study shows places where there is a possibility to create vineyards. It may also be helpful for wine-makers to select grape varieties.

Keywords: climatologic potential, climatic classification, Poland, viticulture

Procedia PDF Downloads 105
16864 Application of Bayesian Model Averaging and Geostatistical Output Perturbation to Generate Calibrated Ensemble Weather Forecast

Authors: Muhammad Luthfi, Sutikno Sutikno, Purhadi Purhadi

Abstract:

Weather forecast has necessarily been improved to provide the communities an accurate and objective prediction as well. To overcome such issue, the numerical-based weather forecast was extensively developed to reduce the subjectivity of forecast. Yet the Numerical Weather Predictions (NWPs) outputs are unfortunately issued without taking dynamical weather behavior and local terrain features into account. Thus, NWPs outputs are not able to accurately forecast the weather quantities, particularly for medium and long range forecast. The aim of this research is to aid and extend the development of ensemble forecast for Meteorology, Climatology, and Geophysics Agency of Indonesia. Ensemble method is an approach combining various deterministic forecast to produce more reliable one. However, such forecast is biased and uncalibrated due to its underdispersive or overdispersive nature. As one of the parametric methods, Bayesian Model Averaging (BMA) generates the calibrated ensemble forecast and constructs predictive PDF for specified period. Such method is able to utilize ensemble of any size but does not take spatial correlation into account. Whereas space dependencies involve the site of interest and nearby site, influenced by dynamic weather behavior. Meanwhile, Geostatistical Output Perturbation (GOP) reckons the spatial correlation to generate future weather quantities, though merely built by a single deterministic forecast, and is able to generate an ensemble of any size as well. This research conducts both BMA and GOP to generate the calibrated ensemble forecast for the daily temperature at few meteorological sites nearby Indonesia international airport.

Keywords: Bayesian Model Averaging, ensemble forecast, geostatistical output perturbation, numerical weather prediction, temperature

Procedia PDF Downloads 277
16863 Renewable Energy System Eolic-Photovoltaic for the Touristic Center La Tranca-Chordeleg in Ecuador

Authors: Christian Castro Samaniego, Daniel Icaza Alvarez, Juan Portoviejo Brito

Abstract:

For this research work, hybrid wind-photovoltaic (SHEF) systems were considered as renewable energy sources that take advantage of wind energy and solar radiation to transform into electrical energy. In the present research work, the feasibility of a wind-photovoltaic hybrid generation system was analyzed for the La Tranca tourist viewpoint of the Chordeleg canton in Ecuador. The research process consisted of the collection of data on solar radiation, temperature, wind speed among others by means of a meteorological station. Simulations were carried out in MATLAB/Simulink based on a mathematical model. In the end, we compared the theoretical radiation-power curves and the measurements made at the site.

Keywords: hybrid system, wind turbine, modeling, simulation, validation, experimental data, panel, Ecuador

Procedia PDF Downloads 243
16862 Insects and Meteorological Inventories in a Mango-Based Agroforestry System in Bangladesh

Authors: Md. Ruhul Amin, Shakura Namni, Md. Ramiz Uddin Miah, Md. Giashuddin Miah, Mohammad Zakaria, Sang Jae Suh, Yong Jung Kwon

Abstract:

Insect species abundance and diversity associated with meteorological factors during January to June 2013 at a mango-based agroforestry research field in Bangladesh, and the effects of pests and pollinator species on mango are presented in this study. Among the collected and identified insects, nine species belong to 3 orders were found as pollinator, 11 species in 5 orders as pest, and 13 species in 6 orders as predator. The mango hopper, fruit fly and stone weevil appeared as major pest because of their high levels of abundance and infestation. The hoppers caused 100% inflorescence damage followed by fruit fly (51.7% fruit) and stone weevil (31.0% mature fruit). The major pests exerted significantly higher abundance compared to pollinator, predator and minor pests. Hemipteroid insects were most abundant (60%) followed by Diptera (21%), Hymenoptera (10%), Lepidoptera (5%), and Coleoptera (4%). Insect population increased with increasing trend of temperature and humidity, and revealed peak abundance during April-May. The flower visiting insects differed in their landing duration and showed preference to forage with time of a day. Their foraging activity was found to be peaked between 11.00 am to 01.00 pm. The activity of the pollinators led to higher level of fruit set. This study provides baseline information about the phenological patterns of insect abundance in an agroforestry research field which could be an indication to incorporate some aspects of pest management.

Keywords: agroforestry, abundance, abiotic factors, insects, mango

Procedia PDF Downloads 441