Search results for: weather based advisory

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

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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

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Authors: Fatima S. Mohammed, Derrick Crump

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Harmattan, a dusty weather condition characterized by thick smog-like suspended particles and dust storm are the peculiar events that happen during ¾ of the year in the Sahelian regions including Damaturu Town, Nigeria), resulting in heavy dust deposits especially indoors. The inhabitants of the Damaturu community are always inflicted with different ailments; respiratory tract infections, asthma, gastrointestinal infections and different ailments associated with the dusty nature of the immediate environment. This brought the need to investigate the nature of the settled indoor dust. Vacuum cleaner bag dust was collected from indoor of some Nigerian and UK homes, as well as outdoors including during seasonal dusty weather event (Harmattan and Storm dust). The dust was sieved, and the (150 µm size) particles were examined using scanning electron microscope (SEM). The physical characterization of the settled dust samples has revealed the various shapes and sizes, and elemental composition of the dust samples is indicating that some of the dust fractions were the respirable fractions and also the dust contained PM10 to PM 2.5 fractions with possible health effects. The elemental compositions were indicative of the diverse nature of the dust particle sources, which showed dust as a complex matrix.

Keywords: indoor dust, Harmattan dust, SEM, health effects

Procedia PDF Downloads 273

Authors: Eszter Hamza

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The competitiveness of economic operators is based on interoperability, which is relatively low in Hungary. The development of co-operation is high priority in Common Agricultural Policy 2014-2020. The aim of the paper to assess co-operations in Hungarian agriculture, estimate the economic outputs and benefits of co-operations, based on statistical data processing and literature. Further objective is to explore the potential of agricultural co-operation with the help of interviews and questionnaire survey. The research seeks to answer questions as to what fundamental factors play role in the development of co-operation, and what are the motivations of the actors and the key success factors and pitfalls. The results were analysed using econometric methods. In Hungarian agriculture we can find several forms of co-operation: cooperatives, producer groups (PG) and producer organizations (PO), machinery cooperatives, integrator companies, product boards and interbranch organisations. Despite the several appearance of the agricultural co-operation, their economic weight is significantly lower in Hungary than in western European countries. Considering the agricultural importance, the integrator companies represent the most weight among the co-operations forms. Hungarian farmers linked to co-operations or organizations mostly in relation to procurement and sales. Less than 30 percent of surveyed farmers are members of a producer organization or cooperative. The trust level is low among farmers. The main obstacle to the development of formalized co-operation, is producers' risk aversion and the black economy in agriculture. Producers often prefer informal co-operation instead of long-term contractual relationships. The Hungarian agricultural co-operations are characterized by non-dynamic development, but slow qualitative change. For the future, one breakout point could be the association of producer groups and organizations, which in addition to the benefits of market concentration, in the dissemination of knowledge, advisory network operation and innovation can act more effectively.

Keywords: agriculture, co-operation, producer organisation, trust level

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Authors: William Anderson, Kyle Kobold, Oleg Yakimenko

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Green microgrids using mostly renewable energy (RE) for generation, are complex systems with inherent nonlinear dynamics. Among a variety of different optimization tools there are only a few ones that adequately consider this complexity. This paper evaluates applicability of two somewhat similar optimization tools tailored for standalone RE microgrids and also assesses a machine learning tool for performance prediction that can enhance the reliability of any chosen optimization tool. It shows that one of these microgrid optimization tools has certain advantages over another and presents a detailed routine of preparing input data to simulate RE microgrid behavior. The paper also shows how neural-network-based predictive modeling can be used to validate and forecast solar power generation based on weather time series data, which improves the overall quality of standalone RE microgrid analysis.

Keywords: microgrid, renewable energy, complex systems, optimization, predictive modeling, neural networks

Procedia PDF Downloads 257

Authors: O. B. Imoukhuede, M. O. Ale

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The periodic scarcity of onion requires an urgent solution in Nigerian agro- economy. The high percentage of onion losses incurred after the harvesting period is due to non-availability of appropriate facility for its storage. Therefore, some storage structures were constructed with different roofing materials. The response of the materials to the weather parameters like temperature and relative humidity were evaluated to know their effects on the performance of the storage structures. The temperature and relative humidity were taken three times daily alongside with the weight of the onion in each of the structures; the losses as indicated by loss indices like shrinkage, rottenness, sprouting, and colour were identified and percentage loss per week determined. The highest mean percentage loss (22%) was observed in the structure with iron roofing materials while structure with thatched materials had the lowest (9.4%); The highest temperature was observed in the structure with Asbestos roofing materials and no significant difference in the temperature value in the structure with thatched and Iron materials; highest relatively humidity was found in Asbestos roofing material while the lowest in the structure with iron matetrials. It was conclusively found that the storage structure with thatched roof had the best performance in terms of losses.

Keywords: Nigeria, onion, storage structures, weather parameters, roof materials, losses

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Authors: Imoukhuede Oladunni Bimpe, Ale Monday Olatunbosun

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Periodic scarcity of onion requires urgent solution in Nigerian agro-economy. The high percentage of onion losses incurred after harvesting period is due to non-availability of appropriate facility for its storage. Therefore, some storage structures were constructed with different roofing materials. The response of the materials to the weather parameters like temperature and relative humidity were evaluated to know their effects on the performance of the storage structures. The temperature and relative humidity were taken three times daily alongside with the weight of the onion in each of the structures; the losses as indicated by loss indices like shrinkage, rottenness, sprouting and colour were identified and percentage loss per week determined. The highest mean percentage loss (22%) was observed in the structure with iron roofing materials while structure with thatched materials had the lowest (9.4%); The highest temperature was observed in the structure with Asbestos roofing materials and no significant difference in the temperature value in the structure with thatched and Iron materials; highest relatively humidity was found in Asbestos roofing material while the lowest in the structure with Iron materials. It was conclusively found that the storage structure with thatched roof had the best performance in terms of losses.

Keywords: onion, storage structures, weather parameters, roof materials, losses

Procedia PDF Downloads 580

Authors: U. Ali Rahoma, Nabil Esawy, Fawzia Ibrahim Moursy, A. H. Hassan, Samy A. Khalil, Ashraf S. Khamees

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The design of any solar energy conversion system requires the knowledge of solar radiation data obtained over a long period. Satellite data has been widely used to estimate solar energy where no ground observation of solar radiation is available, yet there are limitations on the temporal coverage of satellite data. Reanalysis is a “retrospective analysis” of the atmosphere parameters generated by assimilating observation data from various sources, including ground observation, satellites, ships, and aircraft observation with the output of NWP (Numerical Weather Prediction) models, to develop an exhaustive record of weather and climate parameters. The evaluation of the performance of reanalysis datasets (ERA-5) for North Africa against high-quality surface measured data was performed using statistical analysis. The estimation of global solar radiation (GSR) distribution over six different selected locations in North Africa during ten years from the period time 2011 to 2020. The root means square error (RMSE), mean bias error (MBE) and mean absolute error (MAE) of reanalysis data of solar radiation range from 0.079 to 0.222, 0.0145 to 0.198, and 0.055 to 0.178, respectively. The seasonal statistical analysis was performed to study seasonal variation of performance of datasets, which reveals the significant variation of errors in different seasons—the performance of the dataset changes by changing the temporal resolution of the data used for comparison. The monthly mean values of data show better performance, but the accuracy of data is compromised. The solar radiation data of ERA-5 is used for preliminary solar resource assessment and power estimation. The correlation coefficient (R2) varies from 0.93 to 99% for the different selected sites in North Africa in the present research. The goal of this research is to give a good representation for global solar radiation to help in solar energy application in all fields, and this can be done by using gridded data from European Centre for Medium-Range Weather Forecasts ECMWF and producing a new model to give a good result.

Keywords: solar energy, solar radiation, ERA-5, potential energy

Procedia PDF Downloads 181

Authors: Haider Karar, Saghir Ahmad, Amjad Ali, Ibrar Ul Haq

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The experiment was conducted at Cotton Research Station, Multan to study the impact of weather factors and red cotton bug (RCB) on cotton boll disease yielded yellowish lint during 2012. The population on RCB along with abiotic factors was recorded during three consecutive years i.e. 2012, 2013, and 2014. Along with population of RCB and abiotic factors, the number of unopened/opened cotton bolls (UOB), percent yellowish lint (YL) and whitish lint (WL) were also recorded. The data revealed that the population per plant of RCB remain 0.50 and 0.34 during years 2012, 2013 but increased during 2014 i.e. 3.21 per plant. The number of UOB were more i.e. 13.43% in 2012 with YL 76.30 and WL 23.70% when average maximum temperature 34.73◦C, minimum temperature 22.83◦C, RH 77.43% and 11.08 mm rainfall. Similarly in 2013 the number of UOB were less i.e. 0.34 per plant with YL 1.48 and WL 99.53 per plant when average maximum temperature 34.60◦C, minimum temperature 23.37◦C, RH 73.01% and 9.95 mm rainfall. During 2014 RCB population per plant was 3.22 with no UOB and YL was 0.00% and WL was 100% when average maximum temperature 23.70◦C, minimum temperature 23.18◦C, RH 71.67% and 4.55 mm rainfall. So it is concluded that the cotton bolls disease was more during 2012 due to more rainfall and more percent RH. The RCB may be the carrier of boll rot disease pathogen during more rainfall.

Keywords: red cotton bug, cotton, weather factors, years

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Authors: Ibrahim A. Adeniran, Rui F. Zhu, Man S. Wong

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Owing to the insufficiency in the spatial representativeness and continuity of in situ temperature measurements from weather stations (WS), the use of temperature measurement from WS for large-range diurnal analysis in heterogenous landscapes has been limited. This has made the accurate estimation of land surface temperature (LST) from remotely sensed data more crucial. Moreover, the study of dynamic interaction between the atmosphere and the physical surface of the Earth could be enhanced at both annual and diurnal scales by using optimal LST data derived from satellite sensors. The tradeoff between the spatial and temporal resolution of LSTs from satellite’s thermal infrared sensors (TIRS) has, however, been a major challenge, especially when high spatiotemporal LST data are recommended. It is well-known from existing literature that polar satellites have the advantage of high spatial resolution, while geostationary satellites have a high temporal resolution. Hence, this study is aimed at designing a framework for the cross-comparison of LST data from polar and geostationary satellites in a heterogeneous landscape. This could help to understand the relationship between the LST estimates from the two satellites and, consequently, their integration in diurnal LST analysis. Landsat-8 satellite data will be used as the representative of the polar satellite due to the availability of its long-term series, while the Himawari-8 satellite will be used as the data source for the geostationary satellite because of its improved TIRS. For the study area, Hong Kong Special Administrative Region (HK SAR) will be selected; this is due to the heterogeneity in the landscape of the region. LST data will be retrieved from both satellites using the Split window algorithm (SWA), and the resulting data will be validated by comparing satellite-derived LST data with temperature data from automatic WS in HK SAR. The LST data from the satellite data will then be separated based on the land use classification in HK SAR using the Global Land Cover by National Mapping Organization version3 (GLCNMO 2013) data. The relationship between LST data from Landsat-8 and Himawari-8 will then be investigated based on the land-use class and over different seasons of the year in order to account for seasonal variation in their relationship. The resulting relationship will be spatially and statistically analyzed and graphically visualized for detailed interpretation. Findings from this study will reveal the relationship between the two satellite data based on the land use classification within the study area and the seasons of the year. While the information provided by this study will help in the optimal combination of LST data from Polar (Landsat-8) and geostationary (Himawari-8) satellites, it will also serve as a roadmap in the annual and diurnal urban heat (UHI) analysis in Hong Kong SAR.

Keywords: automatic weather station, Himawari-8, Landsat-8, land surface temperature, land use classification, split window algorithm, urban heat island

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Authors: V. Ziegler, F. Schneider, M. Pesch

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With the EDM264, GRIMM offers a solution for mobile short- and long-term measurements in outdoor areas and at production sites. For research as well as permanent areal observations on a near reference quality base. The model EDM264 features a powerful and robust measuring cell based on optical particle counting (OPC) principle with all the advantages that users of GRIMM's portable aerosol spectrometers are used to. The system is embedded in a compact weather-protection housing with all-weather sampling, heated inlet system, data logger, and meteorological sensor. With TSP, PM10, PM4, PM2.5, PM1, and PMcoarse, the EDM264 provides all fine dust fractions real-time, valid for outdoor applications and calculated with the proven GRIMM enviro-algorithm, as well as six additional dust mass fractions pm10, pm2.5, pm1, inhalable, thoracic and respirable for IAQ and workplace measurements. This highly versatile instrument performs real-time monitoring of particle number, particle size and provides information on particle surface distribution as well as dust mass distribution. GRIMM's EDM264 has 31 equidistant size channels, which are PSL traceable. A high-end data logger enables data acquisition and wireless communication via LTE, WLAN, or wired via Ethernet. Backup copies of the measurement data are stored in the device directly. The rinsing air function, which protects the laser and detector in the optical cell, further increases the reliability and long term stability of the EDM264 under different environmental and climatic conditions. The entire sample volume flow of 1.2 L/min is analyzed by 100% in the optical cell, which assures excellent counting efficiency at low and high concentrations and complies with the ISO 21501-1standard for OPCs. With all these features, the EDM264 is a world-leading dust monitor for precise monitoring of particulate matter and particle number concentration. This highly reliable instrument is an indispensable tool for many users who need to measure aerosol levels and air quality outdoors, on construction sites, or at production facilities.

Keywords: aerosol research, aerial observation, fence line monitoring, wild fire detection

Procedia PDF Downloads 117

Authors: Thanh Van Hoang, Tien Yin Chou, Yao Min Fang, Yi Min Huang, Xuan Linh Nguyen

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Reliable information on the spatial distribution of annual rainfall and temperature is essential in research projects relating to urban and regional planning. This research presents results of a classification of temperature and rainfall in the Red River Delta of northern Vietnam based on measurements from seven meteorological stations (Ha Nam, Hung Yen, Lang, Nam Dinh, Ninh Binh, Phu Lien, Thai Binh) in the river basin over a thirty-years period from 1982-2011. The average accumulated rainfall trends in the delta are analysed and form the basis of research essential to weather and climate forecasting. This study employs interpolation based on the Kriging Method for daily rainfall (min and max) and daily temperature (min and max) in order to improve the understanding of sources of variation and uncertainly in these important meteorological parameters. To the Kriging method, the results will show the different models and the different parameters based on the various precipitation series. The results provide a useful reference to assist decision makers in developing smart agriculture strategies for the Red River Delta in Vietnam.

Keywords: spatial interpolation method, ArcGIS, temperature variability, rainfall variability, Red River Delta, Vietnam

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Authors: Kay Thinzar Phu, Lwin Lwin Oo

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In an intelligent transport system and advanced driver assistance system, the developing of real-time traffic sign detection and recognition (TSDR) system plays an important part in recent research field. There are many challenges for developing real-time TSDR system due to motion artifacts, variable lighting and weather conditions and situations of traffic signs. Researchers have already proposed various methods to minimize the challenges problem. The aim of the proposed research is to develop an efficient and effective TSDR in real time. This system proposes an adaptive thresholding method based on RGB color for traffic signs detection and new features for traffic signs recognition. In this system, the RGB color thresholding is used to detect the blue and yellow color traffic signs regions. The system performs the shape identify to decide whether the output candidate region is traffic sign or not. Lastly, new features such as termination points, bifurcation points, and 90’ angles are extracted from validated image. This system uses Myanmar Traffic Sign dataset.

Keywords: adaptive thresholding based on RGB color, blue color detection, feature extraction, yellow color detection

Procedia PDF Downloads 275

Authors: Nishi Malhotra

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Art has developed as a mode of investment and saving. Art and culture of any nation is the source of foreign direct investment (FDI) generation and growth development. Several intermediaries and skill-building organizations thrive on at and culture for their earnings. Indian art market has grown to Rs. 2000 Crores. Art establishment houses access to privileged information is the main reason for arbitrariness and volatility in the market. The commercialization of art and development of the markets with refinement in the taste of the customers have led to the development of art as an investment avenue. Investors keen on investing in these products can do so, and earnings from art are taxable too, like any other capital asset. This research paper is aimed at exploring the role of art and culture as an investment avenue in India and reasons for increasing volatilities in the art market. Based on an extensive literature review and secondary research, a benchmarking study has been conducted to capture the growth of the art as an investment avenue. These studies indicate that during the financial crisis of 2008-10, the art emerged as an alternative investment avenue. The paper aims at discussing the financial engineering of various art funds and instruments. Based on secondary data available from Sotheby’s, Christies, Bonham, there is a positive correlation between strategic diversification and increasing return in the Art market. Similarly, digitization has led to disintermediation in the art markets and also helped to increase the market base. The data clearly enumerates the growing interest of the Indian investor towards art as an investment option. Much like any other broad asset class, art market too thrives on excess returns provided by diversification. Many financial intermediaries and art funds have emerged, to offer valuable investment planning advisory to a genuine investor. This paper clearly highlights the increasing returns of strategic diversification and its impact on reducing volatility in the art markets. Moreover, with coming up of e-auctions and websites, investors are able to analyse art more objectively. Digitization and commercialization of art have definitely helped in reducing volatility in world art markets.

Keywords: art, investment avenue, diversification, digitization

Procedia PDF Downloads 100

Authors: Sujoy Anirudha Das, Albert Thomas

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Building sector is a major consumer of energy globally, and it has corresponding effects to the environment with respect to the carbon emissions. Given the fact that India is expected to add 40-billion square meter of new buildings till 2050, we need frameworks that help in reducing the overall energy consumption in the building sector. Even though several simulation-based frameworks that help in analyzing the building energy consumption are developed globally, in the Indian context, to the best of our knowledge, there is a lack of a comprehensive, yet user-friendly framework to simulate and optimize the effects of various energy influencing factors, specifically for Indian buildings. Therefore, this study is aimed at developing a simulation-based optimization framework to model the energy interactions in different types of Indian buildings by considering the dynamic nature of various energy influencing factors. This comprehensive framework can be used by various building stakeholders to test the energy effects of different factors such as, but not limited to, the various building materials, the orientation, the weather fluctuations, occupancy changes and the type of the building (e.g., office, residential). The results from the case study involving several building types would help us in gaining insights to build new energy-efficient buildings as well as retrofit the existing structures in a more convenient way to consume less energy, exclusively for an Indian scenario.

Keywords: building energy consumption, building energy simulations, energy efficient buildings, optimization framework

Procedia PDF Downloads 140

Authors: Giuseppina Anna Giorgio, Angela Lorusso, Maria Ragosta, Vito Telesca

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Climate change is a major public health threat due to the effects of extreme weather events on human health and on quality of life in general. In this context, mean temperatures are increasing, in particular, extreme temperatures, with heat waves becoming more frequent, more intense, and longer lasting. In many cities, extreme heat waves have drastically increased, giving rise to so-called Urban Heat Island (UHI) phenomenon. In an urban centre, maximum temperatures may be up to 10° C warmer, due to different local atmospheric conditions. UHI occurs in the metropolitan areas as function of the population size and density of a city. It consists of a significant difference in temperature compared to the rural/suburban areas. Increasing industrialization and urbanization have increased this phenomenon and it has recently also been detected in small cities. Weather conditions and land use are one of the key parameters in the formation of UHI. In particular surface urban heat island is directly related to temperatures, to land surface types and surface modifications. The present study concern a UHI analysis of Matera city (Italy) based on the analysis of temperature, change in land use and land cover, using Corine Land Cover maps and satellite Landsat images. Matera, located in Southern Italy, has a typical Mediterranean climate with mild winters and hot and humid summers. Moreover, Matera has been awarded the international title of the 2019 European Capital of Culture. Matera represents a significant example of vernacular architecture. The structure of the city is articulated by a vertical succession of dug layers sometimes excavated or partly excavated and partly built, according to the original shape and height of the calcarenitic slope. In this study, two meteorological stations were selected: MTA (MaTera Alsia, in industrial zone) and MTCP (MaTera Civil Protection, suburban area located in a green zone). In order to evaluate the increase in temperatures (in terms of UHI occurrences) over time, and evaluating the effect of land use on weather conditions, the climate variability of temperatures for both stations was explored. Results show that UHI phenomena is growing in Matera city, with an increase of maximum temperature values at a local scale. Subsequently, spatial analysis was conducted by Landsat satellite images. Four years was selected in the summer period (27/08/2000, 27/07/2006, 11/07/2012, 02/08/2017). In Particular, Landsat 7 ETM+ for 2000, 2006 and 2012 years; Landsat 8 OLI/TIRS for 2017. In order to estimate the LST, Mono Window Algorithm was applied. Therefore, the increase of LST values spatial scale trend has been verified, in according to results obtained at local scale. Finally, the analysis of land use maps over the years by the LST and/or the maximum temperatures measured, show that the development of industrialized area produces a corresponding increase in temperatures and consequently a growth in UHI.

Keywords: climate variability, land surface temperature, LANDSAT images, urban heat island

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Authors: Jaime Martín-de-Nicolás, David Mata-Moya, Nerea del-Rey-Maestre, Pedro Gómez-del-Hoyo, María-Pilar Jarabo-Amores

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Ship detection is nowadays quite an important issue in tasks related to sea traffic control, fishery management and ship search and rescue. Although it has traditionally been carried out by patrol ships or aircrafts, coverage and weather conditions and sea state can become a problem. Synthetic aperture radars can surpass these coverage limitations and work under any climatological condition. A fast CFAR ship detector based on a robust statistical modeling of sea clutter with respect to sea states in SAR images is used. In this paper, the minimum SNR required to obtain a given detection probability with a given false alarm rate for any sea state is determined. A Gaussian target model using real SAR data is considered. Results show that SNR does not depend heavily on the class considered. Provided there is some variation in the backscattering of targets in SAR imagery, the detection probability is limited and a post-processing stage based on morphology would be suitable.

Keywords: SAR, generalized gamma distribution, detection curves, radar detection

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Authors: Rastislav Stojsavljevic

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During most of the Middle Ages, warmer-than-average weather prevailed in the Balkan Peninsula in Southeast Europe. This period is also called Medieval Climate Optimum. It had its most noticeable phases during the 12th and 13th centuries. Due to climatic conditions, the appearance of unstable weather was observed. Strong storms and hail were a frequent occurrence. From the 9th to the 15th century, the Christian religion dominated the Balkan Peninsula. From East-West Schism (1054 A.D.), most of the people in Balkan states belonged to Eastern Orthodox churches: Byzantium, Bulgaria, Serbia and Bosnia. Medieval Croatia and the coastal part (the Adriatic Sea) of Zeta belonged to the Roman Catholic church. In addition to the dominant Christian religion, a lot of pagan Slavic cults remained in the Balkans during the Middle Ages. Various superstitions were a regular occurrence. They were dominant during severe storms, floods, great droughts, the appearance of comets, etc. In this paper, the appearance of warm and cold temperature spells will be investigated. In the second half of the 14th century, the Little Ice Age began and lasted for several centuries. The period of the first half of the 15th century is characterized by cold and snowy winters. Hunger was a regular occurrence. This has given rise to many beliefs which will be researched and mentioned in the paper.

Keywords: the Balkans, religion, medieval climate optimum, little ice age

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Authors: Shih-Fang Lo, Tzu-Wei Guo, Chih-Hsuan Lee

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Tropical fisheries are vulnerable to the physical and biogeochemical oceanic changes associated with climate change. Warmer temperatures and extreme weather have beendamaging the abundance and growth patterns of aquatic organisms. In recent year, the shrinking of fish stock and labor shortage have increased the threat to global aquacultural production. Thus, building a climate-resilient and sustainable mechanism becomes an urgent, important task for global citizens. To tackle the problem, Taiwanese fishermen applies the artificial intelligence (AI) technology. In brief, the AI system (1) measures real-time water quality and chemical parameters infish ponds; (2) monitors fish stock through segmentation, detection, and classification; and (3) implements fishermen’sprevious experiences, perceptions, and real-life practices. Applying this system can stabilize the aquacultural production and potentially increase the labor force. Furthermore, this AI technology can build up a more resilient and sustainable system for the fishermen so that they can mitigate the influence of extreme weather while maintaining or even increasing their aquacultural production. In the future, when the AI system collected and analyzed more and more data, it can be applied to different regions of the world or even adapt to the future technological or societal changes, continuously providing the most relevant and useful information for fishermen in the world.

Keywords: aquaculture, artificial intelligence (AI), real-time system, sustainable fishery

Procedia PDF Downloads 90

Authors: Felipe Henao, Yeny Rodriguez, Juan P. Viteri, Isaac Dyner

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Colombia is rich in natural resources and greatly focuses on the exploitation of water for hydroelectricity purposes. Alternative cleaner energy sources, such as solar and wind power, have been largely neglected despite: a) its abundance, b) the complementarities between hydro, solar and wind power, and c) the cost competitiveness of renewable technologies. The current limited mix of energy sources creates considerable weaknesses for the system, particularly when facing extreme dry weather conditions, such as El Niño event. In the past, El Niño have exposed the truly consequences of a system heavily dependent on hydropower, i.e. loss of power supply, high energy production costs, and loss of overall competitiveness for the country. Nonetheless, it is expected that the participation of hydroelectricity will increase in the near future. In this context, this paper proposes a stochastic lineal programming model to optimize the insertion of renewable energy systems (RES) into the Colombian electricity sector. The model considers cost-based generation competition between traditional energy technologies and alternative RES. This work evaluates the financial, environmental, and technical implications of different combinations of technologies. Various scenarios regarding the future evolution of costs of the technologies are considered to conduct sensitivity analysis of the solutions – to assess the extent of the participation of the RES in the Colombian power sector. Optimization results indicate that, even in the worst case scenario, where costs remain constant, the Colombian power sector should diversify its portfolio of technologies and invest strongly in solar and wind power technologies. The diversification through RES will contribute to make the system less vulnerable to extreme weather conditions, reduce the overall system costs, cut CO2 emissions, and decrease the chances of having national blackout events in the future. In contrast, the business as usual scenario indicates that the system will turn more costly and less reliable.

Keywords: energy policy and planning, stochastic programming, sustainable development, water management

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Authors: Nagham Ismail, Djamel Ouahrani

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Thermal resilience in the built environment reflects the building's capacity to adapt to extreme climate changes. In hot climates, power outages in office buildings pose risks to the health and productivity of workers. Therefore, it is of interest to quantify the thermal resilience of office buildings by developing a user-friendly simplified model. This simplified model begins with creating an assessment metric of thermal resilience that measures the duration between the power outage and the point at which the thermal habitability condition is compromised, considering different power interruption times (morning, noon, and afternoon). In this context, energy simulations of an office building are conducted for Qatar's summer weather by changing different parameters that are related to the (i) wall characteristics, (ii) glazing characteristics, (iii) load, (iv) orientation and (v) air leakage. The simulation results are processed using SPSS to derive linear regression equations, aiding stakeholders in evaluating the performance of commercial buildings during different power interruption times. The findings reveal the significant influence of glazing characteristics on thermal resilience, with the morning power outage scenario posing the most detrimental impact in terms of the shortest duration before compromising thermal resilience.

Keywords: thermal resilience, thermal envelope, energy modeling, building simulation, thermal comfort, power disruption, extreme weather

Procedia PDF Downloads 43

Authors: Y. Karbhari, A. Benamraoui, A. Fahmi Sheikh Hassan

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The study applies role theory to investigate the quality of the compliance review in Malaysia, which is perceived to have the most advanced Islamic banking governance framework in the Islamic world. Drawing from the questionnaire survey and semi-structured interviews, our study reveals the existence of a well-established structure for compliance reviews which is found to be regulatory driven and contingent upon the level of commercial activity of individual Islamic bank’s. However, the compliance review process was found to be ceremonial and inadequately undertaken by some SBs with greater prominence placed on its advisory role. In particular, the study provides evidence of a lack of understanding on accounting issues when undertaking the compliance review. Problems in communication between SBs, board of directors and management were also reported to exist. Our findings raise concern over the quality and thus the credibility of the religious compliance assurance communicated in Islamic Banks annual reports.

Keywords: Islamic banks, religious compliance, Sharia board assurance, role theory

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Authors: Lenka Matulova

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Geopolymers are alumosilicate materials that have long been studied. Despite this fact, little is known about the long-term stability of geopolymer mechanical and structural properties, so crucial for their successful industrial application. To improve understanding, we investigated the effect of four different types of environments on the mechanical and structural properties of a metakaolin-based geopolymer (MK GP). The MK GP samples were stored in laboratory conditions (control samples), in water at 20 °C, in water at 80 °C, and outside exposed to the weather. Compressive and tensile strengths were measured after 28, 56, 90, and 360 days. In parallel, structural properties were analyzed using XRD, SEM, and mercury intrusion porosimetry. Whereas the mechanical properties of the samples in laboratory conditions and in 20 °C water were stable, the mechanical properties of the outdoor samples and the samples 80 °C water decreased noticeably after 360 days. Structural analyses were focused on changes in sample microstructure (developing microcrack network, porosity) and identifying zeolites, the presence of which would indicate detrimental processes in the structure that can change it from amorphous to crystalline. No zeolites were found during the 360-day period in MK GP samples, but the reduction in mechanical properties coincided with a developing network of microcracks and changes in pore size distribution.

Keywords: geopolymer, long-term properties, mechanical properties, metakaolin, structural properties

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Authors: E. O. Aluta, C. A. Booth, D. G. Proverbs, T. Appleby

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Challenges in the effective management of potable water have attracted global attention in recent years and remain many world regions’ major priorities. Scarcity and unavailability of potable water may potentially escalate poverty, obviate democratic expression of views and militate against inter-sectoral development. These challenges contra-indicate the inherent potentials of the resource. Thus, while creation of poverty may be regarded as a broad-based problem, it is capable of reflecting life-span reduction diseases, the friction of interests manifesting in threats and warfare, the relegation of democratic principles for authoritarian definitions and Human Rights abuse. The challenges may be identified as manifestations of ineffective management of potable water resource and therefore, regarded as major problems in environmental protection. In reaction, some nations have re-examined their laws and policies, while others have developed innovative projects, which seek to ameliorate difficulties of providing sustainable potable water. The problems resonate in Nigeria, where the legal framework supporting the supply and management of potable water has been criticized as ineffective. This has impacted more on rural community members, often regarded as ‘voiceless’. At that level, the participation of non-state actors has been identified as an effective strategy, which can improve water supply. However, there are indications that there is no pragmatic application of this, resulting in over-centralization and top-down management. Thus, this study focuses on how the participatory process may enable the development of participatory water governance framework, for use in Nigeria rural communities. The Rural Advisory Board (RAB) is proposed as a governing body to promote proximal relationships, institute democratisation borne out of participation, while enabling effective accountability and information. The RAB establishes mechanisms for effectiveness, taking into consideration Transparency, Accountability and Participation (TAP), advocated as guiding principles of decision-makers. Other tools, which may be explored in achieving these are, Laws and Policies supporting the water sector, under the direction of the Ministries and Law Courts, which ensure non-violation of laws. Community norms and values, consisting of Nigerian traditional belief system, perceptions, attitude and reality (often undermined in favour of legislations), are relied on to pave the way for enforcement. While the Task Forces consist of community members with specific designation of duties, which ensure compliance and enforceability, a cross-section of community members are assigned duties. Thus, the principle of participation is pragmatically reflected. A review of the literature provided information on the potentials of the participatory process, in potable water governance. Qualitative methodology was explored by using the semi-structured interview as strategy for inquiry. The purposive sampling strategy, consisting of homogeneous, heterogeneous and criterion techniques was applied to enable sampling. The samples, sourced from diverse positions of life, were from the study area of Delta State of Nigeria, involving three local governments of Oshimili South, Uvwie and Warri South. From the findings, there are indications that the application of the participatory process is inhered with empowerment of the rural community members to make legitimate demands for TAP. This includes the obviation of mono-decision making for the supply and management of potable water. This is capable of restructuring the top-down management to a top-down/bottom-up system.

Keywords: participation, participatory process, participatory water governance, rural advisory board

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Authors: Luis Guilherme Resende Santos, Ido Nevat, Leslie Norford

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The Urban Heat Island (UHI) is characterized by increased air temperatures in urban areas compared to undeveloped rural surrounding environments. With urbanization and densification, the intensity of UHI increases, bringing negative impacts on livability, health and economy. In order to reduce those effects, it is required to take into consideration design factors when planning future developments. Given design constraints such as population size and availability of area for development, non-trivial decisions regarding the buildings’ dimensions and their spatial distribution are required. We develop a framework for optimization of urban design in order to jointly minimize UHI intensity and buildings’ energy consumption. First, the design constraints are defined according to spatial and population limits in order to establish realistic boundaries that would be applicable in real life decisions. Second, the tools Urban Weather Generator (UWG) and EnergyPlus are used to generate outputs of UHI intensity and total buildings’ energy consumption, respectively. Those outputs are changed based on a set of variable inputs related to urban morphology aspects, such as building height, urban canyon width and population density. Lastly, an optimization problem is cast where the utility function quantifies the performance of each design candidate (e.g. minimizing a linear combination of UHI and energy consumption), and a set of constraints to be met is set. Solving this optimization problem is difficult, since there is no simple analytic form which represents the UWG and EnergyPlus models. We therefore cannot use any direct optimization techniques, but instead, develop an indirect “black box” optimization algorithm. To this end we develop a solution that is based on stochastic optimization method, known as the Cross Entropy method (CEM). The CEM translates the deterministic optimization problem into an associated stochastic optimization problem which is simple to solve analytically. We illustrate our model on a typical residential area in Singapore. Due to fast growth in population and built area and land availability generated by land reclamation, urban planning decisions are of the most importance for the country. Furthermore, the hot and humid climate in the country raises the concern for the impact of UHI. The problem presented is highly relevant to early urban design stages and the objective of such framework is to guide decision makers and assist them to include and evaluate urban microclimate and energy aspects in the process of urban planning.

Keywords: building energy consumption, stochastic optimization, urban design, urban heat island, urban weather generator

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Authors: Hassan Nabipour Afrouzi, Naser Mahmoudnia

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Broiler production has increased rapidly in tropical and subtropical regions in the past and sustained growth is forecast for the future. One of the greatest challenges to efficient production in these regions is reduced performance from warm and hot weather conditions. There are many ways to decrease these detrimental effects of heat on broiler chickens. One way is to supplement broiler diet with betaine added to feed or drinking water. A review of the results of this study suggest that betaine supplement was effective to significantly improve body weight and feed conversion ratio at the initial stages of growth but not in the finisher stages (P<0/05). It was also demonstrated that the use of betaine significantly reduced the percentage of abdominal meat and the percentage of breast meat (P<0/05), but had no effect on other carcass compositions. Betaine may improve the digestibility of specific nutrients. Betaine, as a methyl donor provides labile methyl groups for the synthesis of several metabolically active substances such as creatine and carnitine. Oil in a broiler diet is known to promote a response to dietary betaine supplements, that is, chicks have a higher demand for betaine with a high fat diet. This study implies that betaine supplement may stimulate protection of intestinal epithelium against osmotic disturbance, improve digestion and absorption conditions of the gastrointestinal tract and promote amended use of nutrients.

Keywords: heat stress, betaine, performance, broiler‚ growth

Procedia PDF Downloads 564

Authors: Abraham Castro-Alvarez, Luisaldo Sandate-Flores, Roberto Parra-Saldivar

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The losing of crops during the whole production process is a problem that is affecting farmers in the whole world, as climate change affects the weather behavior. Stenocereus spp. is a tropical, exotic and endemic columnar cacti, it produces a colored and expensive fruit known how “pitaya”. The quality and value of the fruit, these species represent an attractive option for economical development in arid and semi-arid regions. This fruits are produced in Mexico, mainly in 4 regions, Mixteca Oaxaca-Puebla, Michoacan, Sinaloa-Sonora, Jalisco-Zacatecas. Pitaya can be an option to try mixed crop in this states due to the resistance to hard weather conditions. And also because of the marginalization problems that exist in these townships. As defined by the Population National Council it consists in the absence of development opportunities and the lack of capacity to get them. According to an analysis done in EsriPress ArcGis 10.1 the potential area in the country is almost the half of the territory being the total area of Mexico 1,965,249 km2 and the area with potential to produce pitaya 960,527 km2. This area covers part of the most affected townships that also have a few options of maize varieties making even harder the production of maize and exposing farmers to crop losing if conditions are good enough. Making pitaya a good option for these farmers to have an economic backup in their productions.

Keywords: maize, pitaya, rain fed, Stenocereus

Procedia PDF Downloads 298

Authors: Jaswinder Kaur, Nitika, Navneet Kaur, Rajesh Khanna

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A hand-fan shaped microstrip patch antenna (MPA) for L-band and S-band applications is designed, and its characteristics have been reconnoitered. The proposed microstrip patch antenna with double U-slot defected ground structure (DGS) is fabricated on an FR4 substrate which is a very readily available and inexpensive material. The suggested antenna is optimized using Orthogonal Design Method (ODM) of Design of Experiments (DOE) to cover the frequency range from 0.91-2.82 GHz for L-band and S-band applications. The L-band covers the frequency range of 1-2 GHz, which is allocated to telemetry, aeronautical, and military systems for passive satellite sensors, weather radars, radio astronomy, and mobile communication. The S-band covers the frequency range of 2-3 GHz, which is used by weather radars, surface ship radars and communication satellites and is also reserved for various wireless applications such as Worldwide Interoperability for Microwave Access (Wi-MAX), super high frequency radio frequency identification (SHF RFID), industrial, scientific and medical bands (ISM), Bluetooth, wireless broadband (Wi-Bro) and wireless local area network (WLAN). The proposed method of optimization is very time efficient and accurate as compared to the conventional evolutionary algorithms due to its statistical strategy. Moreover, the antenna is tested, followed by the comparison of simulated and measured results.

Keywords: design of experiments, hand fan shaped MPA, L-Band, orthogonal design method, S-Band

Procedia PDF Downloads 106

Authors: Ankit Nagar, Dinesh Kumar Nauriyal, Sukhpal Singh

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This paper examines the key determinants of farmers’ access to agricultural extension services, sources of agricultural extension services preferred and accessed by the farmers. An ordered logistic regression model was used to analyse the data of the 360 sample households based on a primary survey conducted in western Uttar Pradesh, India. The study finds that farmers' decision to engage in the agricultural extension programme is significantly influenced by factors such as education level, gender, farming experience, social group, group membership, farm size, credit access, awareness about the extension scheme, farmers' perception, and distance from extension sources. The most intriguing finding of this study is that the progressive farmers, which have long been regarded as a major source of knowledge diffusion, are the most distrusted sources of information as they are suspected of withholding vital information from potential beneficiaries. The positive relationship between farm size and ‘Access’ underlines that the extension services should revisit their strategies for targeting more marginal and small farmers constituting over 85 percent of the agricultural households by incorporating their priorities in their outreach programs. The study suggests that marginal and small farmers' productive potential could still be greatly augmented by the appropriate technology, advisory services, guidance, and improved market access. Also, the perception of poor quality of the public extension services can be corrected by initiatives aimed at building up extension workers' capacity.

Keywords: agriculture, access, extension services, ordered logistic regression

Procedia PDF Downloads 180

Authors: Isaac Mugume

Abstract:

Since the beginning of the 21st century, climate change has been an issue due to the reported rise in global temperature and changes in the frequency as well as severity of extreme weather and climatic events. The changing climate has been attributed to rising concentrations of greenhouse gases, including environmental changes such as ecosystems and land-uses. Climatic projections have been carried out under the auspices of the intergovernmental panel on climate change where a couple of models have been run to inform us about the likelihood of future climates. Since one of the major forcings informing the changing climate is emission of greenhouse gases, different scenarios have been proposed and future climates for different periods presented. The global climate models project different areas to experience different impacts. While regional modeling is being carried out for high impact studies, bias correction is less documented. Yet, the regional climate models suffer bias which introduces uncertainty. This is addressed in this study by bias correcting the regional models. This study uses the Weather Research and Forecasting model under different representative concentration pathways and correcting the products of these models using observed climatic data. This study notes that bias correction (e.g., the running-mean bias correction; the best easy systematic estimator method; the simple linear regression method, nearest neighborhood, weighted mean) improves the climatic projection skill and therefore reduce the uncertainty inherent in the climatic projections.

Keywords: bias correction, climatic projections, numerical models, representative concentration pathways

Procedia PDF Downloads 91

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

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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

Procedia PDF Downloads 31