Search results for: crop modelling

Authors: Mapula Mothomogolo, Anria Clarke

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Ballistic grilles are adopted on military vehicles to mitigate the vulnerability of the radiator. The design of ballistic grilles needs to address conflicting requirements: shielding the surface area of the radiator from incoming projectile threats yet providing sufficient airflow through the radiator to yield adequate heat rejection. These conflicting requirements result in a unique and challenging design problem. In this paper, the airflow through a ballistic grille using a computational modelling approach is investigated. A comparative study was conducted between a standard grille and a ballistic grille of a military vehicle. The results were used as a benchmark study for optimizing the ballistic grille with pressure drop selected as the parameter for optimization. The grilles were modelled as a porous medium to account for the pressure drop in the porous region. The effects of the porous zone were accounted for in the source term of the momentum Navier Stokes equations. The source term defines the pressure drop in the porous region as a function of the velocity. A pressure drop curve approach was used to determine the Darcy coefficient and inertial resistance coefficients of the source terms. The empirically defined coefficients were used as simulation input for a more accurate pressure drop prediction in the porous region. Additionally, the ballistic grille was optimized using an adjoint solver (shape optimization module in Ansys Fluent) to reduce the pressure drop through the ballistic grille by 30%. Based on the simulation results, the optimized ballistic grille geometry needs to be experimentally tested to validate the numerical simulation data.

Keywords: ballistic grille, darcy coefficient, optimization, porous medium

Procedia PDF Downloads 27

Authors: Mohamed Trigui, Fatma Masmoudi, Imen Zouari

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Massive utilizations of chemical fertilizer and chemical pesticides in agriculture sector to improve the farming productivity have created increasing environmental damages. Then, agriculture must become sustainable, focusing on production systems that respect the environment and help to reduce climate change. Isolation and microbial identification of new bacterial strains from naturally saline habitats and compost extracts could be a prominent way in pest management and crop production under saline conditions. In this study, potential mechanisms involved in plant growth promotion and suppressive activity against fungal diseases of a compost extract produced from poultry manure/olive husk compost and halotolerant and halophilic bacterial strains under saline stress were investigated. On the basis of the antimicrobial tests, different strains isolated from Sfax solar saltern (Tunisia) and from compost extracts were selected and tested for their plant growth promoting traits, such as siderophores production, nitrogen fixation, phosphate solubilization and the production of extracellular hydrolytic enzymes (protease and lipase) under in-vitro conditions. Among 450 isolated bacterial strains, 16 isolates showed potent antifungal activity against the tested plant pathogenic fungi. Their identification based on 16S rRNA gene sequence revealed they belonged to different species. Some of these strains were also characterized for their plant growth promoting capacities. Obtained results showed the ability of four strains belonging to Bacillus genesis to ameliorate germination rate and root elongation compared to the untreated positive controls. Combinatorial capacity of halotolerant bacteria with antimicrobial activity and plant growth promoting traits could be promising sources of interesting bioactive substances under saline stress.

Keywords: abiotic stress, biofertilizer, biotic stress, compost extract, halobacteria, plant growth promoting (PGP), soil fertility

Procedia PDF Downloads 85

Authors: Saeed Vahedikamal, Ian Hepburn

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Microwave Kinetic Inductance Detectors (MKIDs) are considered as one of the most promising photon detectors of the future in many Astronomical applications such as exoplanet detections. The MKID advantages stem from their single photon sensitivity (ranging from UV to optical and near infrared), photon energy resolution and high temporal capability (~microseconds). There has been substantial progress in the development of these detectors and MKIDs with Megapixel arrays is now possible. The unique capability of recording an incident photon and its energy (or wavelength) while also registering its time of arrival to within a microsecond enables an array of MKIDs to produce a four-dimensional data block of x, y, z and t comprising x, y spatial, z axis per pixel spectral and t axis per pixel which is temporal. This offers the possibility that the spectrum and brightness variation for any detected piece of space debris as a function of time might offer a unique identifier or fingerprint. Such a fingerprint signal from any object identified in multiple detections by different observers has the potential to determine the orbital features of the object and be used for their tracking. Modelling performed so far shows that with a 20 cm telescope located at an Astronomical observatory (e.g. La Palma, Canary Islands) we could detect sub cm objects at GEO. By considering a Lambertian sphere with a 10 % reflectivity (albedo of the Moon) we anticipate the following for a GEO object: 10 cm object imaged in a 1 second image capture; 1.2 cm object for a 70 second image integration or 0.65 cm object for a 4 minute image integration. We present details of our modelling and the potential instrument for a dedicated GEO surveillance system.

Keywords: space debris, orbital debris, detection system, observation, microwave kinetic inductance detectors, MKID

Procedia PDF Downloads 90

Authors: Khuram Nawaz Sadozai, Rizwan Ahmad, Munawar Raza Kazmi, Awais Habib

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Climate change and crop production are intrinsically associated with each other. Therefore, this research study is designed to assess the impact of climate change on pulses production in Southern districts of Khyber Pakhtunkhwa (KP) Province of Pakistan. Two pulses (i.e. chickpea and mung bean) were selected for this research study with respect to climate change. Climatic variables such as temperature, humidity and precipitation along with pulses production and area under cultivation of pulses were encompassed as the major variables of this study. Secondary data of climatic variables and crop variables for the period of thirty four years (1986-2020) were obtained from Pakistan Metrological Department and Agriculture Statistics of KP respectively. Panel data set of chickpea and mung bean crops was estimated separately. The analysis validate that both data sets were a balanced panel data. The Hausman specification test was run separately for both the panel data sets whose findings had suggested the fixed effect model can be deemed as an appropriate model for chickpea panel data, however random effect model was appropriate for estimation of the panel data of mung bean. Major findings confirm that maximum temperature is statistically significant for the chickpea yield. This implies if maximum temperature increases by 1 0C, it can enhance the chickpea yield by 0.0463 units. However, the impact of precipitation was reported insignificant. Furthermore, the humidity was statistically significant and has a positive association with chickpea yield. In case of mung bean the minimum temperature was significantly contributing in the yield of mung bean. This study concludes that temperature and humidity can significantly contribute to enhance the pulses yield. It is recommended that capacity building of pulses growers may be made to adapt the climate change strategies. Moreover, government may ensure the availability of climate change resistant varieties of pulses to encourage the pulses cultivation.

Keywords: climate change, pulses productivity, agriculture, Pakistan

Procedia PDF Downloads 41

Authors: Bibiana Betancur-Corredor, Juan Carlos Loaiza, Manfred Denich, Christian Borgemeister

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Alluvial gold mining generates a vast amount of deposits that cover the natural soil and negatively impacts riverbeds and valleys, causing loss of livelihood opportunities for farmers of these regions. In Colombia, more than 79,000 ha are affected by alluvial gold mining, therefore developing strategies to return this land to productivity is of crucial importance for the country. A novel restoration strategy has been created by a mining company, where the land is restored through the establishment of agroforestry systems, in which agricultural crops and livestock are combined to complement reforestation in the area. The purpose of this study is to capture the knowledge of farmers who perform agroforestry in areas with deposits created by alluvial gold mining activities. Semi structured interviews were conducted with farmers with regard to the following: indicators of soil fertility, management practices, soil heterogeneity, pest outbreaks and weeds. In order to compare the perceptions of soil fertility of farmers with physicochemical properties of soils, the farmers were asked to identify spots within their farms that have exhibited good and poor yields. Soil samples were collected in order to correlate farmer’s perceptions with soil physicochemical properties. The findings suggest that the main challenge that farmers face is the identification of fertile soil for crop establishment. They identify the fertile soil through visually analyzing soil color and compaction as well as the use of spontaneous growth of specific plants as indicator of soil fertility. For less fertile areas, nitrogen fixing plants are used as green manure to restore soil fertility for crop establishment. The findings of this study imply that if gold mining is followed by reclamation practices that involve the successful establishment of productive farmlands, agricultural productivity of these lands might improve, increasing food security of the affected communities.

Keywords: agroforestry, knowledge, mining, restoration

Procedia PDF Downloads 228

Authors: Bahram Besharti, Hossein Navid, Hadi Karimi, Hossein Behfar, Iraj Eskandari

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Multiple or miss sowing by seed drills is a common problem on the farm. This problem causes overuse of seeds, wasting energy, rising crop treatment cost and reducing crop yield in harvesting. To be informed of mentioned faults and monitoring the performance of seed drills during sowing, developing a seed sensor for detecting seed mass flow rate and monitoring in a delivery tube is essential. In this research, an infrared seed sensor was developed to estimate seed mass flow rate in seed drills. The developed sensor comprised of a pair of spaced apart circuits one acting as an IR transmitter and the other acting as an IR receiver. Optical coverage in the sensing section was obtained by setting IR LEDs and photo-diodes directly on opposite sides. Passing seeds made interruption in radiation beams to the photo-diode which caused output voltages to change. The voltage difference of sensing units summed by a microcontroller and were converted to an analog value by DAC chip. The sensor was tested by using a roller seed metering device with three types of seeds consist of chickpea, wheat, and alfalfa (representing large, medium and fine seed, respectively). The results revealed a good fitting between voltage received from seed sensor and mass flow of seeds in the delivery tube. A linear trend line was set for three seeds collected data as a model of the mass flow of seeds. A final mass flow model was developed for various size seeds based on receiving voltages from the seed sensor, thousand seed weight and equivalent diameter of seeds. The developed infrared seed sensor, besides monitoring mass flow of seeds in field operations, can be used for the assessment of mechanical planter seed metering unit performance in the laboratory and provide an easy calibrating method for seed drills before planting in the field.

Keywords: seed flow, infrared, seed sensor, seed drills

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Authors: Mohamed Gaafar, Evan Davies

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Many municipalities within Canada and abroad use chloramination to disinfect drinking water so as to avert the production of the disinfection by-products (DBPs) that result from conventional chlorination processes and their consequential public health risks. However, the long-lasting monochloramine disinfectant (NH2Cl) can pose a significant risk to the environment. As, it can be introduced into stormwater sewers, from different water uses, and thus freshwater sources. Little research has been undertaken to monitor and characterize the decay of NH2Cl and to study the parameters affecting its decomposition in stormwater networks. Therefore, the current study was intended to investigate this decay starting by building a stormwater model and validating its hydraulic and hydrologic computations, and then modelling water quality in the storm sewers and examining the effects of different parameters on chloramine decay. The presented work here is only the first stage of this study. The 30th Avenue basin in Southern Edmonton was chosen as a case study, because the well-developed basin has various land-use types including commercial, industrial, residential, parks and recreational. The City of Edmonton has already built a MIKE-URBAN stormwater model for modelling floods. Nevertheless, this model was built to the trunk level which means that only the main drainage features were presented. Additionally, this model was not calibrated and known to consistently compute pipe flows higher than the observed values; not to the benefit of studying water quality. So the first goal was to complete modelling and updating all stormwater network components. Then, available GIS Data was used to calculate different catchment properties such as slope, length and imperviousness. In order to calibrate and validate this model, data of two temporary pipe flow monitoring stations, collected during last summer, was used along with records of two other permanent stations available for eight consecutive summer seasons. The effect of various hydrological parameters on model results was investigated. It was found that model results were affected by the ratio of impervious areas. The catchment length was tested, however calculated, because it is approximate representation of the catchment shape. Surface roughness coefficients were calibrated using. Consequently, computed flows at the two temporary locations had correlation coefficients of values 0.846 and 0.815, where the lower value pertained to the larger attached catchment area. Other statistical measures, such as peak error of 0.65%, volume error of 5.6%, maximum positive and negative differences of 2.17 and -1.63 respectively, were all found in acceptable ranges.

Keywords: stormwater, urban drainage, simulation, validation, MIKE URBAN

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Authors: Xavier Bertrand, Alexandre Cayrel

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The early phase of an aircraft development is instrumental as it really drives the potential of a new concept. Any weakness in the high-level design (wing planform, moveable surfaces layout etc.) will be extremely difficult and expensive to recover later in the aircraft development process. Aerodynamic evaluation in this very early development phase is driven by two main criteria: a short lead-time to allow quick iterations of the geometrical design, and a high quality of the calculations to get an accurate & reliable assessment of the current status. These two criteria are usually quite contradictory. Actually, short lead time of a couple of hours from end-to-end can be obtained with very simple tools (semi-empirical methods for instance) although their accuracy is limited, whereas higher quality calculations require heavier/more complex tools, which obviously need more complex inputs as well, and a significantly longer lead time. At this point, the choice has to be done between accuracy and lead-time. A brand new approach has been developed within Airbus, aiming at obtaining quickly high quality evaluations of the aerodynamic of an aircraft. This methodology is based on a joint use of Surrogate Modelling and a lifting line code. The Surrogate Modelling is used to get the wing sections characteristics (e.g. lift coefficient vs. angle of attack), whatever the airfoil geometry, the status of the moveable surfaces (aileron/spoilers) or the high-lift devices deployment. From these characteristics, the lifting line code is used to get the 3D effects on the wing whatever the flow conditions (low/high Mach numbers etc.). This methodology has been applied successfully to a concept of medium range aircraft.

Keywords: aerodynamics, lifting line, surrogate model, CFD

Procedia PDF Downloads 353

Authors: Maryam Hamlehdar, Guillermo A. Narsilio

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To enhance the feasibility of utilising geothermal hot sedimentary aquifers (HSAs) for clean hydrogen production, one approach is the implementation of solar-integrated geothermal energy systems. This detailed modelling study conducts a thermo-economic assessment of an advanced Organic Rankine Cycle (ORC)-based hydrogen production system that uses low-temperature geothermal reservoirs, with a specific focus on hot sedimentary aquifers (HSAs) over a 30-year period. In the proposed hybrid system, solar-thermal energy is used to raise the water temperature extracted from the geothermal production well. This temperature increase leads to a higher steam output, powering the turbine and subsequently enhancing the electricity output for running the electrolyser. Thermodynamic modeling of a parabolic trough solar (PTS) collector is developed and integrated with modeling for a geothermal-based configuration. This configuration includes a closed regenerator cycle (CRC), proton exchange membrane (PEM) electrolyser, and thermoelectric generator (TEG). Following this, the study investigates the impact of solar energy use on the temperature enhancement of the geothermal reservoir. It assesses the resulting consequences on the lifecycle performance of the hydrogen production system in comparison with a standalone geothermal system. The results indicate that, with the appropriate solar collector area, a combined solar-geothermal hydrogen production system outperforms a standalone geothermal system in both cost and rate of production. These findings underscore a solar-assisted geothermal hybrid system holds the potential to generate lower-cost hydrogen with enhanced efficiency, thereby boosting the appeal of numerous low to medium-temperature geothermal sources for hydrogen production.

Keywords: clean hydrogen production, integrated solar-geothermal, low-temperature geothermal energy, numerical modelling

Procedia PDF Downloads 61

Authors: I. Inuaeyen, L. Phil, O. Eni

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Fossil fuels have been the main source of global energy for many decades, accounting for about 80% of global energy need. This is beginning to change however with increasing concern about greenhouse gas emissions which comes mostly from fossil fuel combustion. Greenhouse gases such as carbon dioxide are responsible for stimulating climate change. As a result, there has been shift towards more clean and renewable energy sources of energy as a strategy for stemming greenhouse gas emission into the atmosphere. The production of bio-products such as bio-fuel, bio-electricity, bio-chemicals, and bio-heat etc. using biomass materials in accordance with the bio-refinery concept holds a great potential for reducing high dependence on fossil fuel and their resources. The bio-refinery concept promotes efficient utilisation of biomass material for the simultaneous production of a variety of products in order to minimize or eliminate waste materials. This will ultimately reduce greenhouse gas emissions into the environment. In Nigeria, cassava solid waste from cassava processing facilities has been identified as a vital feedstock for bio-refinery process. Cassava is generally a staple food in Nigeria and one of the most widely cultivated foodstuff by farmers across Nigeria. As a result, there is an abundant supply of cassava waste in Nigeria. In this study, the aim is to explore opportunities for converting cassava waste to a range of bio-products such as butanol, ethanol, electricity, heat, methanol, furfural etc. using a combination of biochemical, thermochemical and chemical conversion routes. . The best process scenario will be identified through the evaluation of economic analysis, energy efficiency, life cycle analysis and social impact. The study will be carried out by developing a model representing different process options for cassava waste conversion to useful products. The model will be developed using Aspen Plus process simulation software. Process economic analysis will be done using Aspen Icarus software. So far, comprehensive survey of literature has been conducted. This includes studies on conversion of cassava solid waste to a variety of bio-products using different conversion techniques, cassava waste production in Nigeria, modelling and simulation of waste conversion to useful products among others. Also, statistical distribution of cassava solid waste production in Nigeria has been established and key literatures with useful parameters for developing different cassava waste conversion process has been identified. In the future work, detailed modelling of the different process scenarios will be carried out and the models validated using data from literature and demonstration plants. A techno-economic comparison of the various process scenarios will be carried out to identify the best scenario using process economics, life cycle analysis, energy efficiency and social impact as the performance indexes.

Keywords: bio-refinery, cassava waste, energy, process modelling

Procedia PDF Downloads 364

Authors: Numair Ahmed Siddiqui, Abdul Hadi bin Abd Rahman, Chow Weng Sum, Wan Ismail Wan Yousif, Asif Zameer, Joel Ben-Awal

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Advances in data capturing from outcrop studies have made possible the acquisition of high-resolution digital data, offering improved and economical reservoir modelling methods. Terrestrial laser scanning utilizing LiDAR (Light detection and ranging) provides a new method to build outcrop based reservoir models, which provide a crucial piece of information to understand heterogeneities in sandstone facies with high-resolution images and data set. This study presents the detailed application of outcrop based sandstone facies connectivity model by acquiring information gathered from traditional fieldwork and processing detailed digital point-cloud data from LiDAR to develop an intermediate small-scale reservoir sandstone facies model of the Miocene Sandakan Formation, Sabah, East Malaysia. The software RiScan pro (v1.8.0) was used in digital data collection and post-processing with an accuracy of 0.01 m and point acquisition rate of up to 10,000 points per second. We provide an accurate and descriptive workflow to triangulate point-clouds of different sets of sandstone facies with well-marked top and bottom boundaries in conjunction with field sedimentology. This will provide highly accurate qualitative sandstone facies connectivity model which is a challenge to obtain from subsurface datasets (i.e., seismic and well data). Finally, by applying this workflow, we can build an outcrop based static connectivity model, which can be an analogue to subsurface reservoir studies.

Keywords: LiDAR, outcrop, high resolution, sandstone faceis, connectivity model

Procedia PDF Downloads 218

Authors: Natacha Fery, Guilherme L. Dalledonne, Xiangyang Zheng, Cheng Tang, Roberto Mayerle

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A Decision Support System (DSS) for supporting decision makers in the management of the Shandong Peninsula has been developed. Emphasis has been given to coastal protection, coastal cage aquaculture and harbors. The investigations were done in the framework of a joint research project funded by the German Ministry of Education and Research (BMBF) and the Chinese Academy of Sciences (CAS). In this paper, a description of the DSS, the development of its components, and results of its application are presented. The system integrates in-situ measurements, process-based models, and a database management system. Numerical models for the simulation of flow, waves, sediment transport and morphodynamics covering the entire Bohai Sea are set up based on the Delft3D modelling suite (Deltares). Calibration and validation of the models were realized based on the measurements of moored Acoustic Doppler Current Profilers (ADCP) and High Frequency (HF) radars. In order to enable cost-effective and scalable applications, a database management system was developed. It enhances information processing, data evaluation, and supports the generation of data products. Results of the application of the DSS to the management of coastal protection, coastal cage aquaculture and harbors are presented here. Model simulations covering the most severe storms observed during the last decades were carried out leading to an improved understanding of hydrodynamics and morphodynamics. Results helped in the identification of coastal stretches subjected to higher levels of energy and improved support for coastal protection measures.

Keywords: coastal protection, decision support system, in-situ measurements, numerical modelling

Procedia PDF Downloads 190

Authors: Nwogiji Cletus Olando, Oselebe Happiness Ogba, Enoch Achigan-Dako

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Digitaria iburua, commonly known as black fonio, is a cereal crop native to Africa and extensively cultivated by smallholder farmers in Northern Benin, Togo, and Nigeria. This crop holds immense nutritional and socio-cultural value. Unfortunately, limited knowledge about its genetic diversity exists due to a lack of scientific attention. As a result, its potential for improvement in food and agriculture remains largely untapped. To address this gap, a study was conducted using 41 accessions of D. iburua stored in the genebank of the Laboratory of Genetics, Biotechnology, and Seed Science at Abomey-Calavi University, Benin. The study employed both morphological and simple sequence repeat (SSR) markers to evaluate the genetic variability of the accessions. Agro-morphological assessments were carried out during the 2020 cropping season, utilizing an alpha lattice design with three replications. The collected data encompassed qualitative and quantitative traits. Additionally, molecular variability was assessed using eleven SSR markers. The results revealed significant phenotypic variability among the evaluated accessions, leading to their classification into three main clusters. Furthermore, the eleven SSR markers identified a total of 50 alleles, averaging 4.55 alleles per locus. The primers exhibited an average polymorphic information content value of 0.43, with the DE-ARC019 primer displaying the highest value (0.59). These findings suggest a substantial degree of genetic heterogeneity within the evaluated accessions, and the SSR markers employed in the study proved highly effective in detecting and characterizing this genetic variability. In conclusion, this study highlights the presence of significant genetic diversity in black fonio and provides valuable insights for future efforts aimed at its genetic improvement and conservation.

Keywords: genetic diversity, digitaria iburua, genetic improvement, simple sequence repeat markers, Nigeria, conservation

Procedia PDF Downloads 82

Authors: Juan A. Arzate, Funda C. Ertem, M. Nicolas Cruz-Bournazou, Peter Neubauer, Stefan Junne

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— One of the biggest challenges the world faces today is global warming that is caused by greenhouse gases (GHGs) coming from the combustion of fossil fuels for energy generation. In order to mitigate climate change, the European Union has committed to reducing GHG emissions to 80–95% below the level of the 1990s by the year 2050. Renewable technologies are vital to diminish energy-related GHG emissions. Since water and biomass are limited resources, the largest contributions to renewable energy (RE) systems will have to come from wind and solar power. Nevertheless, high proportions of fluctuating RE will present a number of challenges, especially regarding the need to balance the variable energy demand with the weather dependent fluctuation of energy supply. Therefore, biogas plants in this content would play an important role, since they are easily adaptable. Feedstock availability varies locally or seasonally; however there is a lack of knowledge in how biogas plants should be operated in a stable manner by local feedstock. This problem may be prevented through suitable control strategies. Such strategies require the development of convenient mathematical models, which fairly describe the main processes. Modelling allows us to predict the system behavior of biogas plants when different feedstocks are used with different loading rates. Life cycle assessment (LCA) is a technique for analyzing several sides from evolution of a product till its disposal in an environmental point of view. It is highly recommend to use as a decision making tool. In order to achieve suitable strategies, the combination of a flexible energy generation provided by biogas plants, a secure production process and the maximization of the environmental benefits can be obtained by the combination of process modelling and LCA approaches. For this reason, this study focuses on the biogas plant which flexibly generates required energy from the co-digestion of maize, grass and cattle manure, while emitting the lowest amount of GHG´s. To achieve this goal AMOCO model was combined with LCA. The program was structured in Matlab to simulate any biogas process based on the AMOCO model and combined with the equations necessary to obtain climate change, acidification and eutrophication potentials of the whole production system based on ReCiPe midpoint v.1.06 methodology. Developed simulation was optimized based on real data from operating biogas plants and existing literature research. The results prove that AMOCO model can successfully imitate the system behavior of biogas plants and the necessary time required for the process to adapt in order to generate demanded energy from available feedstock. Combination with LCA approach provided opportunity to keep the resulting emissions from operation at the lowest possible level. This would allow for a prediction of the process, when the feedstock utilization supports the establishment of closed material circles within a smart bio-production grid – under the constraint of minimal drawbacks for the environment and maximal sustainability.

Keywords: AMOCO model, GHG emissions, life cycle assessment, modelling

Procedia PDF Downloads 187

Authors: Gopika Rajagopal, Sudheesh Thiyyakkandi

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Back-to-back reinforced earth (RE) walls are extensively used in these days as bridge abutments and highway ramps, owing to their cost efficiency and ease of construction. High quality select fill is the most suitable backfill material due to its excellent engineering properties and constructability. However, industries are compelled to use low quality, locally available soil because of its ample availability on site. However, several failure cases of such walls are reported, especially subsequent to rainfall events. The stiffness of reinforcement is one of the major factors affecting the performance of RE walls. The present study focused on analyzing the effect of reinforcement stiffness on the performance of complete select fill, complete marginal fill, and hybrid-fill (i.e., combination of select and marginal fills) back-to-back RE walls, immediately after construction and upon rainwater infiltration through finite element modelling. A constant width to height (W/H) ratio of 3 and height (H) of 6 m was considered for the numerical analysis and the stiffness of reinforcement layers was varied from 500 kN/m to 10000 kN/m. Results showed that reinforcement stiffness had a noticeable influence on the response of RE wall, subsequent to construction as well as rainwater infiltration. Facing displacement was found to decrease and maximum reinforcement tension and factor of safety were observed to increase with increasing the stiffness of reinforcement. However, beyond a stiffness of 5000 kN/m, no significant reduction in facing displacement was observed. The behavior of fully marginal fill wall considered in this study was found to be reasonable even after rainwater infiltration when the high stiffness reinforcement layers are used.

Keywords: back-to-back reinforced earth wall, finite element modelling, rainwater infiltration, reinforcement stiffness

Procedia PDF Downloads 151

Authors: E. M. H. Maggie, M. N. A. Nazmey, M. A. Abdel-Sattar, S. A. Saied

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A successful trial of transplanting cotton is reported. Seeds grown in trays for 4-5 weeks in an easily prepared supporting medium such as peat moss or similar plant waste are tried. Careful transplanting of seedlings, with root system as intact as possible, is being made in the permanent field. The practice reduced damping-off incidence rate and allowed full winter crop revenues. Further work is needed to evaluate certain parameters such as growth curve, flowering curve, and yield at economic bases.

Keywords: cotton, transplanting cotton, damping-off diseases, environment sciences

Procedia PDF Downloads 362

Authors: Yuanchao Sang, Zhihao Gong, Longsheng Chen, Long Chen

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Clothing fashion represents a human’s aesthetic appreciation towards everyday outfits and appetite for fashion, and it reflects the development of status in society, humanity, and economics. However, modelling fashion by machine is extremely challenging because fashion is too abstract to be efficiently described by machines. Even human beings can hardly reach a consensus about fashion. In this paper, we are dedicated to answering a fundamental fashion-related problem: what image feature best describes clothing fashion? To address this issue, we have designed and evaluated various image features, ranging from traditional low-level hand-crafted features to mid-level style awareness features to various current popular deep neural network-based features, which have shown state-of-the-art performance in various vision tasks. In summary, we tested the following 9 feature representations: color, texture, shape, style, convolutional neural networks (CNNs), CNNs with distance metric learning (CNNs&DML), AutoEncoder, CNNs with multiple layer combination (CNNs&MLC) and CNNs with dynamic feature clustering (CNNs&DFC). Finally, we validated the performance of these features on two publicly available datasets. Quantitative and qualitative experimental results on both intra-domain and inter-domain fashion clothing image retrieval showed that deep learning based feature representations far outweigh traditional hand-crafted feature representation. Additionally, among all deep learning based methods, CNNs with explicit feature clustering performs best, which shows feature clustering is essential for discriminative fashion feature representation.

Keywords: convolutional neural network, feature representation, image processing, machine modelling

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Authors: M. Bischoff, F. Schmidt, J. Herrmann, J. Mattheß, G. Seide, T. Gries

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Crop yields have not increased as dramatically as the demand for food. One method to counteract this is to use pesticides to keep away predators, e.g. several forms of insecticide are available to fight insects. These insecticides and pesticides are both controversial as their application and their residue in the food product can also harm humans. In this study an alternative method to combat insects is studied. A physical insect-killing effect of SiO₂ particles is used. The particles are applied on fibres to avoid erosion in the fields, which would occur when applied separately. The development of such SiO₂ functionalized PP fibres is shown.

Keywords: agriculture, environment, insects, protection, silica, textile

Procedia PDF Downloads 295

Authors: Rachida Gherbi-Salmi, Abdelkarim Si Bachir, Salah Eddine Doumandji

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The Cattle Egret is a predatory bird with an insectivorous diet. It feeds in open environments (wetlands, meadows, farmland and cultivated land). Few studies have determined the status of its prey (useful or harmful species for agriculture). Hence, our study was carried out in the Bejaia region (Algeria). It consisted of examining adult rejection pellets collected in a heronry located in the lower Soummam Valley (El-Kseur), which has been a permanent habitat for over 30 years. Field sampling was carried out during the juvenile rearing period in 1998 (wet spring) and 2020 (almost dry spring). Examination of 50 pellets at a rate of 10 per month (May - September) in 1998 revealed the presence of 2,661 prey belonging to 170 species, i.e., an average of 53.36 prey per pellet. The results reveal that the diet of this Ardeidae consists mainly of Insecta (95.09%). Arachnida was a distant second (4.05%). Vertebrates (Reptilia and Rodentia) (0.82%) and myriapods (0.04%) are rare prey. We counted 2,154 plant pests (80.27%), of which 2,138 were insects (99.27%) and 0.73% rodents (Mus spretus). Of the plant-pest insects identified, 1385 were Orthoptera (64.78%). Fourmicidae came second (13.05%), and Coleoptera third (12.82%). Dermaptera, on the other hand, accounted for only 7.86%. Analysis of 30 rejection pellets, 10 per month (May - July) in 2020, identified 1,330 prey belonging to 80 species, an average of 44.33 prey per pellet. The results reveal that its diet is essentially made up of Insecta (94.81%). These are followed by Vertebrata (3.01%) and Arachnida (2.18%). We counted 1156 plant pests (86.82%), of which 86.02% are Insecta. Orthoptera are the most frequent (45.72%). They are followed by Dermaptera (33.74%) and Coleoptera (18.44%). The present study highlighted the importance of plant pests consumed by the Cattle Egret (80.27% in 1998 and 86.82% in 2020), which are far more numerous and diverse than auxiliary prey and pollinators. This confirms the bird's status as a biological control agent in the lower Soummam valley. It is, therefore, worth pointing out that this species deserves to be protected.

Keywords: bubulcus ibis, diet, lower soummam valley, insect crop pests

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Authors: Javed Sidiqi, Stephen Baezinger, Stephen Wegulo

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Wheat (Triticum aestivum L.) production continues to be challenged by foliar fungal diseases although significant improvement has been made to manage the diseases through developing resistant varieties and the fungicide use to ensure sufficient wheat is produced to meet the growing population’s need. Significant crop losses have been recorded in the history of grain production and yield losses due to fungal diseases, and the trend continues to threat food security in the world and particularly in the less developed countries. The impact of individual fungal diseases on grain yield has been studied extensively to determine crop losses. However, there is limited research available to find out the combined effects of fungal diseases on grain yield and the ways to effectively manage the diseases. Therefore, the objectives of this research were to study the effect of fungal pathogens on grain yield of pre-released winter wheat genotypes in fungicide treated and untreated plots, and to determine whether S7b gene was present in ‘Gage’ wheat as previously hypothesized. Sixty winter wheat genotypes in fungicide treated and untreated plots were studied across four environments. There was a significant effect of fungicide on grain yield consistently across four environments in three years. Fungicide treated wheat lines demonstrated (4,496 kg/ ha-1) grain yield compared to (3,147 kg/ ha-1) grain yield in untreated wheat lines indicating 43% increased grain yield due to severity of foliar fungal diseases. Furthermore, fungicide application also caused an increase in protein concentration from 153 (g kg-1) to 164 (g kg-1) in treated plots in along with test weight from 73 to 77 (kg hL-1) respectively. Gage wheat variety and ISr7b-Ra were crossed to determine presence of Sr7b in Gage. The F2 and F2:3 segregating families were screened and evaluated for stem rust resistance. The segregation of families fell within 15:1 ratio for two separate resistance genes suggesting that Sr7b segregates independently from an unknown resistance gene in Gage that needs to be characterized for its use in the future wheat breeding program to develop resistant wheat varieties.

Keywords: funicide, genetics, foliar diseases, grain

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Authors: Ahmed Ali Samejo, Riffat Sultana

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Pakistan has the sandy Thar Desert in the eastern area, which share border line with India and has exotic fauna and flora, the livelihood of native people rely on livestock and rain fed cultivated fields. The climate of Thar Desert is very harsh and stressful due to frequent drought and very little rainfall, which may occur during monsoon season in the months of July to October and temperature is high, and wind speed also increases in April to June. Schistocerca gregaria is a destructive pest of vegetation from Mauritania to the border line of Pakistan and India. Sometimes they produce swarms which consume all plant where ever they land down and cause the loss in agro-economy of the world. During the recent study, we observed that vegetation was not unique throughout the Thar Desert in the year 2015, because the first spell of rainfall showered over all areas of the Thar Desert in July. However, the second and third spell of rain was confined to village Mahandre jo par and surroundings from August to October. Consequently, vegetation and cultivated crops grew up specially bajra crop (Pennistum glaucum). The climate of Mahandre jo par and surroundings became favorable for S.gregaria, and remaining areas of Thar Desert went hostile. Therefore desert locust attracted to the pleasant area (Mahandre jo par and surroundings) and gradually concentrated, increased reproductive activities, but did not gregarize due to the harvest of bajra crop and the onset of the winter season with an immediate decrease in temperature. An outbreak was near to come into existence, and thereupon conditions become stressful for hoppers to continue further development. Afore mentioned was one reason behind hurdle to the outbreak, another reason might be that migration and concentration of desert locust took place at the end of the season, so climate becomes unfavorable for hoppers, due to dryness of vegetation. Soils also become dry, because rainfall was not showered in end of the season, that’s why eggs that were deposited in late summer were desiccated. This data might be proved fruitful to forecast any outbreak update in future.

Keywords: agro-economy, destructive pest, climate, outbreak, vegetation

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Authors: Alex Gonzalez Caceres, Jan Karlshøj, Tor Arvid Vik

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Life cycle of residential buildings are expected to be several decades, 40% of European residential buildings have inefficient energy conservation measure. The existing building represents 20-40% of the energy use and the CO₂ emission. Since net zero energy buildings are a short-term goal, (should be achieved by EU countries after 2020), is necessary to plan the next logical step, which is to prepare the existing outdated stack of building to retrofit them into an energy efficiency buildings. In order to accomplish this, two specialize and widespread tool can be used Building Information Modelling (BIM) and life-cycle assessment (LCA). BIM and LCA are tools used by a variety of disciplines; both are able to represent and analyze the constructions in different stages. The combination of these technologies could improve greatly the retrofitting techniques. The incorporation of the carbon footprint, introducing a single database source for different material analysis. To this is added the possibility of considering different analysis approaches such as costs and energy saving. Is expected with these measures, enrich the decision-making. The methodology is based on two main activities; the first task involved the collection of data this is accomplished by literature review and interview with experts in the retrofitting field and BIM technologies. The results of this task are presented as an evaluation checklist of BIM ability to manage data and improve decision-making in retrofitting projects. The last activity involves an evaluation using the results of the previous tasks, to check how far the IFC format can support the requirements by each specialist, and its uses by third party software. The result indicates that BIM/LCA have a great potential to improve the retrofitting process in existing buildings, but some modification must be done in order to meet the requirements of the specialists for both, retrofitting and LCA evaluators.

Keywords: retrofitting, BIM, LCA, energy efficiency

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Authors: Kanyaporn Sommeechai

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Air cadets who aspire to become military pilots upon graduation undergo rigorous training at military academies. As first-year cadets are akin to civilian freshmen, they encounter numerous challenges within the seniority-based military academy system. Imposed routines, such as mandatory morning runs and restrictions on mobile phone usage for two semesters, have the potential to impact their learning process and motivation to study, including second language (L2) acquisition. This study aims to investigate the motivational dynamics and L2 learning transitions experienced by air cadets. To achieve this, a Retrodictive Qualitative Modelling approach will be employed, coupled with the adaptation of the three-barrier structure encompassing institutional factors, situational factors, and dispositional factors. Semi-structured interviews will be conducted to gather rich qualitative data. By analyzing and interpreting the collected data, this research seeks to shed light on the motivational factors that influence air cadets' L2 learning journey. The three-barrier structure will provide a comprehensive framework to identify and understand the institutional, situational, and dispositional factors that may impede or facilitate their motivation and language learning progress. Moreover, the study will explore how these factors interact and shape cadets' motivation and learning experiences. The outcomes of this research will yield fundamental data that can inform strategies and interventions to enhance the motivation and language learning outcomes of air cadets. By better understanding their motivational dynamics and transitions, educators and institutions can create targeted initiatives, tailored pedagogical approaches, and supportive environments that effectively inspire and engage air cadets as L2 learners.

Keywords: second language, education, motivational dynamics, learning transitions

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Authors: Jacques M. Berner, Lehlogonolo Maloma

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Context: Glyphosate, a widely used herbicide, has raised concerns about its impact on various crops. Amaranthus cruentus, an important grain crop species, is particularly susceptible to glyphosate. Understanding the specific disruptions caused by glyphosate on the photosynthetic process in Amaranthus cruentus is crucial for assessing its effects on crop productivity and ecological sustainability. Research Aim: This study aimed to investigate the dose-dependent impact of glyphosate on the photochemical efficiency of Amaranthus cruentus using the OJIP transient analysis. The goal was to assess the specific disruptions caused by glyphosate on key parameters of photosystem II. Methodology: The experiment was conducted in a controlled greenhouse environment. Amaranthus cruentus plants were exposed to different concentrations of glyphosate, including half, recommended, and double the recommended application rates. The photochemical efficiency of the plants was evaluated using non-invasive chlorophyll a fluorescence measurements and subsequent analysis of OJIP transients. Measurements were taken on 1-hour dark-adapted leaves using a Hansatech Handy PEA+ chlorophyll fluorimeter. Findings: The study's results demonstrated a significant reduction in the photochemical efficiency of Amaranthus cruentus following glyphosate treatment. The OJIP transients showed distinct alterations in the glyphosate-treated plants compared to the control group. These changes included a decrease in maximal fluorescence (FP) and a delay in the rise of the fluorescence signal, indicating impairment in the energy conversion process within the photosystem II. Glyphosate exposure also led to a substantial decrease in the maximum quantum yield efficiency of photosystem II (FV/FM) and the total performance index (PItotal), which reflects the overall photochemical efficiency of photosystem II. These reductions in photochemical efficiency were observed even at half the recommended dose of glyphosate. Theoretical Importance: The study provides valuable insights into the specific disruptions caused by glyphosate on the photochemical efficiency of Amaranthus cruentus. Data Collection and Analysis Procedures: Data collection involved non-invasive chlorophyll a fluorescence measurements using a chlorophyll fluorimeter on dark-adapted leaves. The OJIP transients were then analyzed to assess specific disruptions in key parameters of photosystem II. Statistical analysis was conducted to determine the significance of the differences observed between glyphosate-treated plants and the control group. Question Addressed: The study aimed to address the question of how glyphosate exposure affects the photochemical efficiency of Amaranthus cruentus, specifically examining disruptions in the photosynthetic electron transport chain and overall photochemical efficiency. Conclusion: The study demonstrates that glyphosate severely impairs the photochemical efficiency of Amaranthus cruentus, as indicated by the alterations in OJIP transients. Even at half the recommended dose, glyphosate caused significant reductions in photochemical efficiency. These findings highlight the detrimental effects of glyphosate on crop productivity and emphasize the need for further research to evaluate its long-term consequences and ecological implications in agriculture. The authors gratefully acknowledge the support from North-West University for making this research possible.

Keywords: glyphosate, amaranthus cruentus, ojip transient analysis, pitotal, photochemical efficiency, chlorophyll fluorescence, weeds

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Authors: Shahzad M. A. Basra, Shahid Iqbal, Irfan Afzal, Hafeez-ur-Rehman

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Quinoa a facultative halophyte crop plant is a new introduction in Pakistan due to its superior nutritional profile and its abiotic stress tolerance, especially against salinity. Present study was conducted to explore halophytic behavior of quinoa. Four quinoa genotypes (A1, A2, A7 and A9) were evaluated against high salinity (control, 100, 200, 300 and 400 mM). Evaluation was made on the basis of ionic analysis (Na+, K+ and K+: Na+ ratio in shoot) and root- shoot fresh and dry weight at four leaf stage. Seedling growth i.e. fresh and dry weight of shoot and root increased by 100 mM salinity and then growth decreased gradually with increasing salinity level in all geno types. Mineral analysis indicated that A2 and A7 have more tolerant behavior having low Na+ and high K+ ¬concentration as compared to A1 and A9. Same geno types as above were also evaluated against high salinity (control, 10, 20, 30, and 40 dS m-1) in pot culture during 2012-13. It was found that increase in salinity up to 10 dS m-1 the plant height, stem diameter and yield related traits increased but decreased with further increase in salinity. Same trend was observed in ionic contents. Maximum grain yield was achieved by A7 (100 g plant-1) followed by A2 (82 g plant-1) at salinity level 10 dS m-1. Next phase was carried out through field settings by using salt tolerant geno types (A2 and A7) at Crop Physiology Research Area Farm (non saline soil as control)/ Proka Farm (salt affected with EC up to 15 dS m-1), University of Agriculture, Faisalabad and Soil Salinity Research Institute, Pindi Bhtiaan (SSRI) Farm (one normal as control and two salt affected fields with EC values up to 15 and 30 dS m-1) during 2013-14. Genotype A7 showed maximum growth and gave maximum yield (3200 kg ha-1) at Proka Farm which was statistically at par to the values of yield obtained on normal soils of Faisalabad. Geno type A7 also gave maximum yield 2800 kg ha-1 on normal field of Pindi bhtiaan followed by as obtained (2340) on salt problem field (15 dS m-1) of same location.

Keywords: quinoa, salinity, halophyte, genotype

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Authors: Kottaridi Klimentia, Demopoulos Vasilis, Sidiropoulos Anastasios, Ihara Diego, Nikolaidis Vasileios, Antonopoulos Dimitrios

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Aflatoxins are highly poisonous and carcinogenic compounds produced by species of the genus Aspergillus spp. that can infect a variety of agricultural foods, including dried figs. Biological and environmental factors, such as population, pathogenicity, and aflatoxinogenic capacity of the strains, topography, soil, and climate parameters of the fig orchards, are believed to have a strong effect on aflatoxin levels. Existing methods for aflatoxin detection and measurement, such as high performance liquid chromatography (HPLC), and enzyme-linked immunosorbent assay (ELISA), can provide accurate results, but the procedures are usually time-consuming, sample-destructive, and expensive. Predicting aflatoxin levels prior to crop harvest is useful for minimizing the health and financial impact of a contaminated crop. Consequently, there is interest in developing a tool that predicts aflatoxin levels based on topography and soil analysis data of fig orchards. This paper describes the development of a risk assessment tool for the contamination of aflatoxin on dried figs, based on the location and altitude of the fig orchards, the population of the fungus Aspergillus spp. in the soil, and soil parameters such as pH, saturation percentage (SP), electrical conductivity (EC), organic matter, particle size analysis (sand, silt, clay), the concentration of the exchangeable cations (Ca, Mg, K, Na), extractable P, and trace of elements (B, Fe, Mn, Zn and Cu), by employing machine learning methods. In particular, our proposed method integrates three machine learning techniques, i.e., dimensionality reduction on the original dataset (principal component analysis), metric learning (Mahalanobis metric for clustering), and k-nearest neighbors learning algorithm (KNN), into an enhanced model, with mean performance equal to 85% by terms of the Pearson correlation coefficient (PCC) between observed and predicted values.

Keywords: aflatoxins, Aspergillus spp., dried figs, k-nearest neighbors, machine learning, prediction

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Authors: Awais Ahmad, Mostafa Muhammad Selim, Ali Abdullah Alderfasi

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Water limitation is undoubtedly a critical environmental constraint limiting the crop production under arid and semiarid areas. Mung bean is susceptible to both drought and water logging stresses. Therefore, present study was conducted to assess the water deficit stress consequences of yield components and water use efficiency in Mung bean. A field experiment was conducted at Educational Farm, Crop Production Department, College of Food and Agricultural Sciences, Kind Saud University, Saudi Arabia. Trail comprised of four irrigation levels — total amount of irrigation divided into irrigation intervals — (3, 5, 7 and 9 days interval) and three Mung bean genotypes; Kawmay-1, VC-2010 and King from Egypt, Thailand and China respectively. Experiment was arranged under split plot design having irrigation as main while genotype as subplot treatment, and replicated thrice. Plant height, 100 seed weight, biological yield, seed yield, harvest index and water use efficiency were recorded at harvesting. Results revealed that decrease in irrigation have significantly hampered all the studied parameters. Mung bean genotypes have also shown significant differences for all parameters, whereas irrigation genotype interaction was highly significant for seed yield, harvest index and water use efficiency (WUE) while it was significant for biological yield. Plant height and 100 seed weight were recorded non-significant for irrigation genotype interaction. A statistically highly significant correlation among recorded parameters was observed. Minimum irrigation interval (3 days) significantly produced maximum values while VC-2010 comparatively performed better under low irrigation levels. It was concluded that Mung bean may be successfully adopted under Saudi Arabian climate but it needs high water or frequent irrigation, however, genotypic differences are a hope to develop some improved varieties with high water use efficiency.

Keywords: mung bean, irrigation intervals, water use efficiency, genotypes, yield

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Authors: A. Miškinytė, A. Dėdelė

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Road traffic is one of the main sources of air pollution in urban areas associated with adverse effects on human health and environment. Nitrogen dioxide (NO2) is considered as traffic-related air pollutant, which concentrations tend to be higher near highways, along busy roads and in city centres and exceedances are mainly observed in air quality monitoring stations located close to traffic. Atmospheric dispersion models can be used to examine emissions from many various sources and to predict the concentration of pollutants emitted from these sources into the atmosphere. The study aim was to compare modelled concentrations of nitrogen dioxide using ADMS-Urban dispersion model with air quality monitoring network in cold and warm seasons in Kaunas city. Modelled average seasonal concentrations of nitrogen dioxide for 2011 year have been verified with automatic air quality monitoring data from two stations in the city. Traffic station is located near high traffic street in industrial district and background station far away from the main sources of nitrogen dioxide pollution. The modelling results showed that the highest nitrogen dioxide concentration was modelled and measured in station located near intensive traffic street, both in cold and warm seasons. Modelled and measured nitrogen dioxide concentration was respectively 25.7 and 25.2 µg/m3 in cold season and 15.5 and 17.7 µg/m3 in warm season. While the lowest modelled and measured NO2 concentration was determined in background monitoring station, respectively 12.2 and 13.3 µg/m3 in cold season and 6.1 and 7.6 µg/m3 in warm season. The difference between monitoring station located near high traffic street and background monitoring station showed that better agreement between modelled and measured NO2 concentration was observed at traffic monitoring station.

Keywords: air pollution, nitrogen dioxide, modelling, ADMS-Urban model

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Authors: Karan Bhandari

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Almost quarter region of Indian terrain is covered by grasslands. Grass being a low maintenance perennial crop is in abundance. Farmers are well acquainted with its nature, yield and storage. The aim of this paper is to study and identify the applicability of grass as a source of bio fuel. Anaerobic break down is a well-recognized technology. This process is vital for harnessing bio fuel from grass. Grass is a lignocellulosic material which is fibrous and can readily cause problems with parts in motion. Further, it also has a tendency to float. This paper also deals with the ideal digester configuration for biogas generation from grass. Intensive analysis of the literature is studied on the optimum production of grass storage in accordance with bio digester specifications. Subsequent to this two different digester systems were designed, fabricated, analyzed. The first setup was a double stage wet continuous arrangement usually known as a Continuously Stirred Tank Reactor (CSTR). The next was a double stage, double phase system implementing Sequentially Fed Leach Beds using an Upflow Anaerobic Sludge Blanket (SLBR-UASB). The above methodologies were carried for the same feedstock acquired from the same field. Examination of grass silage was undertaken using Biomethane Potential values. The outcomes portrayed that the Continuously Stirred Tank Reactor system produced about 450 liters of methane per Kg of volatile solids, at a detention period of 48 days. The second method involving Leach Beds produced about 340 liters of methane per Kg of volatile solids with a detention period of 28 days. The results showcased that CSTR when designed exclusively for grass proved to be extremely efficient in methane production. The SLBR-UASB has significant potential to allow for lower detention times with significant levels of methane production. This technology has immense future for research and development in India in terms utilizing of grass crop as a non-conventional source of fuel.

Keywords: biomethane potential values, bio digester specifications, continuously stirred tank reactor, upflow anaerobic sludge blanket

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Authors: Shah Rucksana Akhter Urme

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Agriculture is the main source of food for human consumption and feeding the world huge population, the pressure of food supply is increasing day by day. Undoubtedly, quality strain, improved plantation, farming technology, synthetic fertilizer, readily available irrigation, insecticides and harvesting technology are the main factors those to meet up the huge demand of food consumption all over the world. However, depended on this limited resources and excess amount of consuming lands, water, fertilizers leads to the end of the resources and severe climate effects has been left for our future generation. Agriculture is the most responsible to global warming, emitting more greenhouse gases than all other vehicles largely from nitrous oxide released by from fertilized fields, and carbon dioxide from the cutting of rain forests to grow crops . Farming is the thirstiest user of our precious water supplies and a major polluter, as runoff from fertilizers disrupts fragile lakes, rivers, and coastal ecosystems across the globe which accelerates the loss of biodiversity, crucial habitat and a major driver of wildlife extinction. It is needless to say that we have to more concern on how we can save the nutrients of the soil, storage of the water and avoid excessive depends on synthetic fertilizer and insecticides. In this case, eco- friendly cultivation could be a potential alternative solution to minimize effects of agriculture in our environment. The objective of this review paper is about organic cultivation following in particular biotechnological process focused on bio-fertilizer and bio-pesticides. Intense practice of chemical pesticides, insecticides has severe effect on both in human life and biodiversity. This cultivation process introduces farmer an alternative way which is nonhazardous, cost effective and ecofriendly. Organic fertilizer such as tea residue, ashes might be the best alternative to synthetic fertilizer those play important role in increasing soil nutrient and fertility. Ashes contain different essential and non-essential mineral contents that are required for plant growth. Organic pesticide such as neem spray is beneficial for crop as it is toxic for pest and insects. Recycled and composted crop wastes and animal manures, crop rotation, green manures and legumes etc. are suitable for soil fertility which is free from hazardous chemicals practice. Finally water hyacinth and algae are potential source of nutrients even alternative to soil for cultivation along with storage of water for continuous supply. Inorganic practice of agriculture, consuming fruits and vegetables becomes a threat for both human life and eco-system and synthetic fertilizer and pesticides are responsible for it. Farmers that practice eco-friendly farming have to implement steps to protect the environment, particularly by severely limiting the use of pesticides and avoiding the use of synthetic chemical fertilizers, which are necessary for organic systems to experience reduced environmental harm and health risk.

Keywords: organic farming, biopesticides, organic nutrients, water storage, global warming

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