Search results for: seasonal changes

Authors: Dacheng Li, Bo Huang, Qinjin Han, Ming Li

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Remotely sensed imagery with the high spatial and temporal characteristics, which it is hard to acquire under the current land observation satellites, has been considered as a key factor for monitoring environmental changes over both global and local scales. On a basis of the limited high spatial-resolution observations, challenged studies called spatiotemporal fusion have been developed for generating high spatiotemporal images through employing other auxiliary low spatial-resolution data while with high-frequency observations. However, a majority of spatiotemporal fusion approaches yield to satisfactory assumption, empirical but unstable parameters, low accuracy or inefficient performance. Although the spatiotemporal fusion methodology via sparse representation theory has advantage in capturing reflectance changes, stability and execution efficiency (even more efficient when overcomplete dictionaries have been pre-trained), the retrieval of high-accuracy dictionary and its response to fusion results are still pending issues. In this paper, we employ additional image pairs (here each image-pair includes a Landsat Operational Land Imager and a Moderate Resolution Imaging Spectroradiometer acquisitions covering the partial area of Baotou, China) only into the coupled dictionary training process based on K-SVD (K-means Singular Value Decomposition) algorithm, and attempt to improve the fusion results of two existing sparse representation based fusion models (respectively utilizing one and two available image-pair). The results show that more eligible image pairs are probably related to a more accurate overcomplete dictionary, which generally indicates a better image representation, and is then contribute to an effective fusion performance in case that the added image-pair has similar seasonal aspects and image spatial structure features to the original image-pair. It is, therefore, reasonable to construct multi-dictionary training pattern for generating a series of high spatial resolution images based on limited acquisitions.

Keywords: spatiotemporal fusion, sparse representation, K-SVD algorithm, dictionary learning

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Authors: Amir Shouri, Fereshteh Tabe

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Thoughtful and sequential design strategies will shape the future of human being’s lifestyle. Design, as a product, either being for small furniture on sidewalk or a multi-story structure in urban scale, will be important in creating the sense of quality for citizens of a city. Technology besides economy has played a major role in improving design process and increasing awareness of clients about the character of their required design product. Architects along with other design professionals benefited from improvements in aesthetics and technology in building industry. Accordingly, the expectation platforms of people about the quality of habitable space have risen. However, the question is if the quality of architectural design product has increased with the same speed as technology and client’s expectations. Is it behind or a head of technological and economical improvements? This study will work on developing a model of planning for New York City, from the past to present to future. The role of thoughtful thinking at design stage regardless of where or when it is for; may result in a positive or negative aspect. However, considering design objectives based on the need of human being may help in developing a successful design plan. Technology, economy, culture and people’s support may be other parameters in designing a good product. ‘Design Forms Urban Space’ is going to be done in an analytical, qualitative and quantitative work frame, where it will study cases from all over the world and their achievements compared to New York City’s development. Technology, Organic Design, Materiality, Urban forms, city politics and sustainability will be discussed in different cases in international scale. From design professional’s interest in doing a high quality work for a particular answer to importance of being a follower, the ‘Zero-Carbon City’ in Persian Gulf to ‘Polluted City’ in China, from ‘Urban Scale Furniture’ in cities to ‘Seasonal installations’ of a Megacity, will all be studied with references and detailed look to analysis of each case in order to propose the most resourceful, practical and realistic solutions to questions on ‘A Good Design in a City’, ‘New City Planning and social activities’ and ‘New Strategic Architecture for better Cities’.

Keywords: design quality, urban scale, active city, city installations, architecture for better cities

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Authors: Xianglu Tang, Zhenxue Jiang, Zhuo Li

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Characterization of shale multi scale heterogeneity is an important part to evaluate size and space distribution of shale gas reservoirs in sedimentary basins. The origin of shale heterogeneity has always been a hot research topic for it determines shale micro characteristics description and macro quality reservoir prediction. Shale multi scale heterogeneity was discussed based on thin section observation, FIB-SEM, QEMSCAN, TOC, XRD, mercury intrusion porosimetry (MIP), and nitrogen adsorption analysis from 30 core samples in Silurian Longmaxi formation. Results show that shale heterogeneity can be characterized by pore structure and mineral composition. The heterogeneity of shale pore is showed by different size pores at nm-μm scale. Macropores (pore diameter > 50 nm) have a large percentage of pore volume than mesopores (pore diameter between 2~ 50 nm) and micropores (pore diameter < 2nm). However, they have a low specific surface area than mesopores and micropores. Fractal dimensions of the pores from nitrogen adsorption data are higher than 2.7, what are higher than 2.8 from MIP data, showing extremely complex pore structure. This complexity in pore structure is mainly due to the organic matter and clay minerals with complex pore network structures, and diagenesis makes it more complicated. The heterogeneity of shale minerals is showed by mineral grains, lamina, and different lithology at nm-km scale under the continuous changing horizon. Through analyzing the change of mineral composition at each scale, random arrangement of mineral equal proportion, seasonal climate changes, large changes of sedimentary environment, and provenance supply are considered to be the main reasons that cause shale minerals heterogeneity from microcosmic to macroscopic. Due to scale effect, the change of shale multi scale heterogeneity is a discontinuous process, and there is a transformation boundary between homogeneous and in homogeneous. Therefore, a shale multi scale heterogeneity changing model is established by defining four types of homogeneous unit at different scales, which can be used to guide the prediction of shale gas distribution from micro scale to macro scale.

Keywords: heterogeneity, homogeneous unit, multiscale, shale

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Authors: A. Burakowska, M. Piotrowski, M. Kubicki, H. Trzaskowska, R. Sosnowiec, B. Myslek-Laurikainen

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The most important source of atmospheric radioactivity are radionuclides generated as a result of the impact of primary and secondary cosmic radiation, with the nuclei of nitrogen oxygen and carbon in the upper troposphere and lower stratosphere. This creates about thirty radioisotopes of more than twenty elements. For organisms, the four of them are most important: ³H, ⁷Be, ²²Na, ¹⁴C. The natural radionuclides, which are present in Earth crust, also settle on dust and particles of water vapor. By this means, the derivatives of uranium and thorium, and long-life 40K get into the air. ¹³⁷Cs is the most widespread isotope, that is implemented by humans into the environment. To determine the concentration of radionuclides in the atmosphere, high volume air samplers were used, where the aerosol collection took place on a special filter fabric (Petrianov filter tissue FPP-15-1.5). In 2002 the high volume air sampler AZA-1000 was installed at the Polish Polar Observatory of the Polish Academy of Science in Hornsund, Spitsbergen (77°00’N, 15°33’E), designed to operate in all weather conditions of the cold polar region. Since 1991 (with short breaks) the ASS-500 air sampler has been working, which is located in Swider at the Kalinowski Geophysical Observatory of Geophysics Institute of the Polish Academy of Science (52°07’N, 21°15’E). The following results of radionuclides concentrations were obtained from both stations using gamma spectroscopy analysis: ⁷Be, ¹³⁷Cs, ¹³⁴Cs, ²¹⁰Pb, ⁴⁰K. For gamma spectroscopy analysis HPGe (High Purity Germanium) detector were used. These data were compared with each other. The preliminary results gave evidence that radioactivity measured in aerosols is not proportional to the amount of dust for both studied regions. Furthermore, the results indicate annual variability (seasonal fluctuations) as well as a decrease in the average activity of ⁷Be with increasing latitude. The content of ⁷Be in surface air also indicates the relationship with solar activity cycles.

Keywords: aerosols, air filters, atmospheric beryllium, environmental radionuclides, gamma spectroscopy, mid-latitude regions radionuclides, polar regions radionuclides, solar cycles

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Authors: Khalil Trigui, Rafik Ben Said, Fourat Akrout, Neji Aloui

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In this study, we examined in the first part the eco-biology of Artemia (A.salina) collected from Sahline Salt Lake (governorate of Monastir: Tunisia) during an annual cycle. The correlations between environmental factors and some biological parameters of Artemia were determined. The results obtained showed that the environmental factors affected the biology of Artemia. The highest abundance was recorded in May (550 ± 2,16 ind/l) and all life history stages existed with different seasonal proportions. The Artemia population is bisexual with ovoviviparous reproduction at the beginning and oviparous at the end of the life cycle. We also recorded the dominance of males at the start and the females at the end of the cycle. During all the study period, the size of mature females is bigger than that of males. The fertility obtained resulted in a significant production of cysts compared to the nauplii. A negative correlation with highly significant effect was deduced between environmental factors (temperature and salinity) and the production of nauplii (ovoviviparity) in contrast with dissolved oxygen. In the second part of our work is consecrated to the mastery of breeding Artemia. For this, we tested the effect of five external factors (temperature, salinity, dissolved oxygen, light intensity and food) on the survival of this crustacean. Thereby, the survival rates of Artemia were affected by the different values of studied factors. The recorded results showed that Artemia salina has an optimum temperature ranged from 25 to 27°C with a survival rate ranging from 84 to 88%. The optimal salinity to breed Artemia salina was 37 psu (62 ± 0,23%). Nevertheless, this crustacean was able to survive and withstand the salinity of 0 psu (freshwater). The optimum concentration of dissolved oxygen was 7mg/l with a survival rate of 87,11 ± 0,04%. An optimum light intensity of 10 lux revealed a survival rate equal to 85,33 ± 0,01%. The results also showed that the preferred micro-algae by Artemia is Dunaliella salina with a maximum survival rate of the order of 80 ± 0,15%. There is a significant effect for all experienced parameters on the survival of Artemia reared except the nature of food.

Keywords: Artemia salina, biology, breeding, ecology, Sahline salt lake

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Authors: Akinnubi Rufus Temidayo

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Coastal West Africa is highly sensitive to climate variability, driven by complex ocean-atmosphere interactions that shape temperature, precipitation, and extreme weather. Radiative feedback mechanisms—such as water vapor feedback, cloud-radiation interactions, and surface albedo—play a critical role in modulating these patterns. Yet, limited research addresses these feedbacks in climate models specific to West Africa’s coastal zones, creating challenges for accurate climate projections and adaptive planning. This study aims to evaluate the influence of radiative feedbacks on the coastal climate of West Africa by quantifying the effects of water vapor, cloud cover, and sea surface temperature (SST) on the region’s radiative balance. The study uses a regional climate model (RCM) to simulate feedbacks over a 20-year period (2005-2025) with high-resolution data from CORDEX and satellite observations. Key mechanisms investigated include (1) Water Vapor Feedback—the amplifying effect of humidity on warming, (2) Cloud-Radiation Interactions—the impact of cloud cover on radiation balance, especially during the West African Monsoon, and (3) Surface Albedo and Land-Use Changes—effects of urbanization and vegetation on the radiation budget. Preliminary results indicate that radiative feedbacks strongly influence seasonal climate variability in coastal West Africa. Water vapor feedback amplifies dry-season warming, cloud-radiation interactions moderate surface temperatures during monsoon seasons, and SST variations in the Atlantic affect the frequency and intensity of extreme rainfall events. The findings suggest that incorporating these feedbacks into climate planning can strengthen resilience to climate impacts in West African coastal communities. Further research should refine regional models to capture anthropogenic influences like greenhouse gas emissions, guiding sustainable urban and resource planning to mitigate climate risks.

Keywords: west africa, radiative, climate, resilence, anthropogenic

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Authors: Shivankar Agrawal, Sunil Kumar Deshmukh, Colin Barrow, Alok Adholeya

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A variety of genetic and environmental factors cause various cosmetics and dermatological problems. There are already claimed drugs available in market for treating these problems. However, the challenge remains in finding more potent, environmental friendly, causing minimal side effects and economical cosmeceuticals. This leads to an increased demand for natural cosmeceutical products in the last few decades. Plant derived ingredients are limited because plants either contain toxic metabolites, grow too slow or seasonal harvesting is a problem. To identify new bioactive cosmetics ingredients of marine microbial bioresource, we screened 35 marine fungi isolated from marine samples collected from Andaman Island and west coast of India. Fungal crude extracts were investigated for their antityrosinase, antioxidant and antibacterial activities for the purpose of identifying anti-aging, skin-whitening and anti-acne biomolecule with the potential in cosmetics. In the tyrosinase inhibition and 2, 2-Diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging assays, two fungal extracts, including “P2”, Talaromyces stipitatus and “D4”, Aspergillus terreus showed high inhibitory activity at 1mg/mL for tyrosinase inhibition and 0.5mg/mL for DPPH scavenging. The in vitro antimicrobial activity was investigated by the agar well diffusion method. In the tyrosinase inhibition assay, 8 extracts showed significant antibacterial activity against bacteria causing skin and wound infection in humans. In the course of systematic screening program for bioactive marine fungi, strain “D5” was found to be most potent strain with MIC value of 1mg/mL, which was morphologically identified as Simplicillium lamellicola. The effects of the most active crude extracts against their susceptible test microorganisms were also investigated by SEM analysis. Further investigations will focus on purification and characterization major active components responsible for these activities.

Keywords: antioxidant, antimicrobial activity, tyrosinase, cosmeceuticals, marine fungi

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Authors: Zeina Bourhane, Anders Lanzen, Christine Cagnon, Olfa Ben Said, Cristiana Cravo-Laureau, Robert Duran

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The anthropogenic pressure in coastal areas increases dramatically with the exploitation of environmental resources. Biomonitoring coastal areas are crucial to determine the impact of pollutants on bacterial communities in soils and sediments since they provide important ecosystem services. However, relevant biomonitoring tools allowing fast determination of the ecological status are yet to be defined. Microbial ecology approaches provide useful information for developing such microbial monitoring tools reporting on the effect of environmental stressors. Chemical and microbial molecular approaches were combined in order to determine microbial bioindicators for assessing the ecological status of soil and river ecosystems around the Ichkeul Lake (Tunisia), an area highly impacted by human activities. Samples were collected along soil/river/lake continuums in three stations around the Ichkeul Lake influenced by different human activities at two seasons (summer and winter). Contaminant pressure indexes (PI), including PAHs (Polycyclic aromatic hydrocarbons), alkanes, and OCPs (Organochlorine pesticides) contents, showed significant differences in the contamination level between the stations with seasonal variation. Bacterial communities were characterized by 16S ribosomal RNAs (rRNA) gene metabarcoding. Although microgAMBI indexes, determined from the sequencing data, were in accordance with contaminant contents, they were not sufficient to fully explain the PI. Therefore, further microbial indicators are still to be defined. The comparison of bacterial communities revealed the specific microbial assemblage for soil, river, and lake sediments, which were significantly correlated with contaminant contents and PI. Such observation offers the possibility to define a relevant set of bioindicators for reporting the effects of human activities on the microbial community structure. Such bioindicators might constitute useful monitoring tools for the management of microbial communities in coastal areas.

Keywords: bacterial communities, biomonitoring, contamination, human impacts, microbial bioindicators

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Authors: Seulki Lee, Seoung Bum Kim

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Statistical process control (SPC) is a practical and effective method for quality control. The most important and widely used technique in SPC is a control chart. The main goal of a control chart is to detect any assignable changes that affect the quality output. Most conventional control charts, such as Hotelling’s T2 charts, are commonly based on the assumption that the quality characteristics follow a multivariate normal distribution. However, in modern complicated manufacturing systems, appropriate control chart techniques that can efficiently handle the nonnormal processes are required. To overcome the shortcomings of conventional control charts for nonnormal processes, several methods have been proposed to combine statistical learning algorithms and multivariate control charts. Statistical learning-based control charts, such as support vector data description (SVDD)-based charts, k-nearest neighbors-based charts, have proven their improved performance in nonnormal situations compared to that of the T2 chart. Beside the nonnormal property, time-varying operations are also quite common in real manufacturing fields because of various factors such as product and set-point changes, seasonal variations, catalyst degradation, and sensor drifting. However, traditional control charts cannot accommodate future condition changes of the process because they are formulated based on the data information recorded in the early stage of the process. In the present paper, we propose a SVDD algorithm-based control chart, which is capable of adaptively monitoring time-varying and nonnormal processes. We reformulated the SVDD algorithm into a time-adaptive SVDD algorithm by adding a weighting factor that reflects time-varying situations. Moreover, we defined the updating region for the efficient model-updating structure of the control chart. The proposed control chart simultaneously allows efficient model updates and timely detection of out-of-control signals. The effectiveness and applicability of the proposed chart were demonstrated through experiments with the simulated data and the real data from the metal frame process in mobile device manufacturing.

Keywords: multivariate control chart, nonparametric method, support vector data description, time-varying process

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Authors: Omer Al-Kaabi, Ahmed Nasr, Abdullah Al-Ghafri, Mohammed Abdelfattah

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The Falaj system, derived from natural water sources, is a man-made canal system designed to supply communities of farmers with water for domestic and agricultural purposes. For thousands of years, Falaj has served communities by harnessing the force of gravity; it persists as a vital water management system in numerous regions across the Sultanate of Oman. Remarkably, predates the establishment of many fundamental hydraulic principles used today. Al-Khatmain Falaj, with its accessibility and historical significance spanning over 2000 years, was chosen as the focal point of this study. The research aimed to investigate the efficiency of Al-Khatmain Falaj in meeting specific water demands. The HEC-RAS model was utilized to visualize water flow dynamics within the Falaj channels, accompanied by graphical representations of pertinent variables. The application of HEC-RAS helped to measure different water flow scenarios within the channel, enabling a clear comparison with the demand area catchment. The cultivated land of Al-Khatmain is 723,124 m² and consists of 16,873 palm trees representing 91% of the total area and the remaining 9% is mixed types of trees counted 3,920 trees. The study revealed a total demand of 8,244 m³ is required to irrigate the cultivated land. Through rigorous analysis, the study has proven that the Falaj system in Al-Khatmain operates with high efficiency, as the average annual water supply is 9676.8 m3/day. Additionally, the channel designed at 0.6m width x 0.3m height efficiently holds the optimal water supply, with an average flow depth of 0.21m. Also, the system includes an overflow drainage channel to mitigate floods and prevent crop damage based on seasonal requirements. This research holds promise for examining diverse hydrological conditions and devising effective strategies to manage scenarios of both high and low flow rates.

Keywords: Al-Khatmain, sustainability, Falaj, HEC-RAS, water management system

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Authors: Hafiz M. Rizwan, Muhammad S. Sajid, Zafar Iqbal, Muhammad Saqib

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Gastro-intestinal (GI) helminths infection in sheep causes a substantial loss in terms of productivity and constitutes serious economic losses in the world. Different types of forages are rich in trace element contents and may act as a natural resource to improve the trace element deficiencies leading to immunity boost-up in general and against gastrointestinal parasitic infections in particular. In the present study, the level of trace elements (Cu, Co, Mn, Zn) determined in sera of different breeds of sheep, available feedstuffs, respective soil samples and their association with GI helminths in Sialkot district, Punjab, Pakistan. Almost similar prevalence of GI helminths was recorded (32.81%) during spring 2015 and (32.55%) during autumn 2014. The parasitic species identified from the microscopically scanned faecal samples of district Sialkot were Fasciola (F.) hepatica, F. gigantica, Haemonchus contortus, Eimeria crandallis, Gongylonema pulchrum, Oesophagostomum sp., Trichuris ovis, Strongyles sp., Cryptosporidium sp. and Trichostrongylus sp. Among variables like age, sex, and breed, only sex was found significant in district Sialkot. A significant (P < 0.05) variation in the concentration of Zn, Cu, Mn, and Co was recorded in collected forages species. Soils of grazing field showed insignificant (P > 0.05) variation among soils of different tehsils of Sialkot district. Statistically, sera of sheep showed no variation (P > 0.05) during autumn 2014, While, variation (P < 0.05) among different tehsils of Sialkot district during spring 2015 except Co. During autumn 2014 the mean concentration of Cu, Zn, and Co in sera was inversely proportional to the mean EPG of sheep while during spring 2015 only Zn was inversely proportional to the mean EPG of sheep. The trace element-rich forages preferably Zn were effective ones against helminths infection. The trace element-rich forages will be recommended for their utilization as an alternate to improve the trace element deficiencies in sheep which ultimately boost up the immunity against gastrointestinal parasitic infections.

Keywords: coprological examination, gastro-intestinal parasites, prevalence, sheep, trace elements

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Authors: Abduladim Maitieg

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The oil manufacture is one of the main productive activities in Libya and has a massive infrastructure, including offshore drilling and exploration and wide oil export platform sites that located in coastal area. There is a threat to marine and coastal area of oil spills is greatest in those sites with a high spills comes from urban and industry, parallel to that, monitoring oil spills and risk emergency strategy is weakness, An approach for estimating a coastal resources vulnerability to oil spills is presented based on abundance, environmental and Scio-economic importance, distance to oil spill resources and oil risk likelihood. As many as 10 coastal resources were selected for oil spill assessment at the coast. This study aims to evaluate, determine and establish vulnerable coastal resource maps and estimating the rate of oil spill comes for different oil spill resources in Misratah marine environment. In the study area there are two type of oil spill resources, major oil resources come from offshore oil industries which are 96 km from the Coast and Loading/Uploading oil platform. However, the miner oil resources come from urban sewage pipes and fish ports. In order to analyse the collected database, the Geographic information system software has been used to identify oil spill location, to map oil tracks in front of study area, and developing seasonal vulnerable costal resources maps. This work shows that there is a differential distribution of the degree of vulnerability to oil spills along the coastline, with values ranging from high vulnerability and low vulnerability, and highlights the link between oil spill movement and coastal resources vulnerability. The results of assessment found most of costal freshwater spring sites are highly vulnerable to oil spill due to their location on the intertidal zone and their close to proximity to oil spills recourses such as Zreag coast. Furthermore, the Saltmarsh coastline is highly vulnerable to oil spill risk due to characterisation as it contains a nesting area of sea turtles and feeding places for migratory birds and the . Oil will reach the coast in winter season according to oil spill movement. Coastal tourist beaches in the north coast are considered as highly vulnerable to oil spill due to location and closeness to oil spill resources.

Keywords: coastal recourses vulnerability, oil spill trajectory, gnome software, Misratah coast- Libya, GIS

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Authors: Raquel Vianna Duarte Cardoso, Eduarda Lobato Faria, José Jorge Boueri

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Rapid urbanization has transformed the global landscape, presenting significant challenges to public health. This article delves into the impact of urbanization on the spread of infectious diseases in cities and identifies crucial strategies to enhance urban community resilience. Massive urbanization over recent decades has created conducive environments for the rapid spread of diseases due to population density, mobility, and unequal living conditions. Urbanization has been observed to increase exposure to pathogens and foster conditions conducive to disease outbreaks, including seasonal flu, vector-borne diseases, and respiratory infections. In order to tackle these issues, a range of cross-disciplinary approaches are suggested. These encompass the enhancement of urban healthcare infrastructure, emphasizing the need for robust investments in hospitals, clinics, and healthcare systems to keep pace with the burgeoning healthcare requirements in urban environments. Moreover, the establishment of disease monitoring and surveillance mechanisms is indispensable, as it allows for the timely detection of outbreaks, enabling swift responses. Additionally, community engagement and education play a pivotal role in advocating for personal hygiene, vaccination, and preventive measures, thus playing a pivotal role in diminishing disease transmission. Lastly, the promotion of sustainable urban planning, which includes the creation of cities with green spaces, access to clean water, and proper sanitation, can significantly mitigate the risks associated with waterborne and vector-borne diseases. The article is based on a review of scientific literature, and it offers a comprehensive insight into the complexities of the relationship between urbanization and health. It places a strong emphasis on the urgent need for integrated approaches to improve urban resilience in the face of health challenges.

Keywords: infectious diseases dissemination, public health, urbanization impacts, urban resilience

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Authors: Joshua Adan Valdez, Shawn Gallaher

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Global climate change has impacted atmospheric temperatures contributing to rising sea levels, decreasing sea ice, and increased freshening of high latitude oceans. This freshening has contributed to increased stratification inhibiting local mixing and nutrient transport, modifying regional circulations in polar oceans. In recent years, the Western Arctic has seen an increase in freshwater volume at an average rate of 397+-116km3/year across the Beaufort Gyre. The majority of the freshwater volume resides in the Beaufort Gyre surface lens driven by anticyclonic wind forcing, sea ice melt, and Arctic river runoff, and is typically defined as water fresher than 34.8. The near-isothermal nature of Arctic seawater and non-linearities in the equation of state for near-freezing waters result in a salinity-driven pycnocline as opposed to the temperature-driven density structure seen in the lower latitudes. In this study, we investigate the relationship between freshwater content and dynamic ocean topography (DOT). In situ measurements of freshwater content are useful in providing information on the freshening rate of the Beaufort Gyre; however, their collection is costly and time-consuming. Utilizing NASA’s ICESat-2’s DOT remote sensing capabilities and Air Expendable CTD (AXCTD) data from the Seasonal Ice Zone Reconnaissance Surveys (SIZRS), a linear regression model between DOT and freshwater content is determined along the 150° west meridian. Freshwater content is calculated by integrating the volume of water between the surface and a depth with a reference salinity of ~34.8. Using this model, we compare interannual variability in freshwater content within the gyre, which could provide a future predictive capability of freshwater volume changes in the Beaufort-Chukchi Sea using non-in situ methods. Successful employment of the ICESat-2’s DOT approximation of freshwater content could potentially demonstrate the value of remote sensing tools to reduce reliance on field deployment platforms to characterize physical ocean properties.

Keywords: Cryosphere, remote sensing, Arctic oceanography, climate modeling, Ekman transport

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Authors: Enrique González Pendás, Vidal Pérez Hernández, Jorge Ferro Díaz, Nelson Careaga Pendás

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The investigation is carried out on the Protected Area of San Ubaldo, toward the interior of an open pinegrove with palm trees in a dry plainness of quar zitic sands, belonging to the Floristic Managed Reservation San Ubaldo-Sabanalamar, Guane, Pinar del Río, Cuba. This area is characterized by drastic seasonal variations, high temperatures and water evaporation, strong solar radiation, with sandy soils of almost pure quartz, which are very acid and poor in nutrients. The objective of the present work is to determine evidence of facilitation and its relationship with the structure and composition of plant communities in these peculiar ecosystems. For this study six lineal parallel transepts of 100 m are traced, in those, a general recording of the flora is carried out. To establish which plants act as nurses, is taken into account a height over 1 meter, canopy over 1.5 meter and the occurrence of several species under it. Covering was recorded using the line intercept method; the medium values of species richness for the taxa under nurses is compared with those that are located in open spaces among them. Then, it is determined which plants are better recruiter of other species (better nurses). An experiment is made to measure and compare some parameters in pine seedlings under the canopy of the Byrsonima crassifolia (L.) Kunth. and in open spaces, also the number of individuals is counted by species to calculate the frequency and total abundance in the study area. As a result, it is offered an up-to-date floristic list, a phylogenetic tree of the plant community showing a high phylodiversity, it is proven that the medium values of species richness and abundance of species under the nurses, is significantly superior to those occurring in open spaces. Furthermore, by means of phylogenetic trees it is shown that the species which cohabit under the nurses are not phylogenetically related. The former results are cited evidences of facilitation among plants, as well as it is one more time shown the importance of the nurse effect in preserving plant diversity on extreme environments.

Keywords: facilitation, nurse plants, positive interactions, quarzitic sands

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Authors: Rahman Davtalab

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Florida is one of the most vulnerable states to natural disasters among the 50 states of the USA. The state exposed by tropical storms, hurricanes, storm surge, landslide, etc. Besides, the mentioned natural phenomena, global warming, sea-level rise, and other anthropogenic environmental changes make a very complicated and unpredictable system for decision-makers. In this study, we tried to highlight the effects of climate change and sea-level rise on surface water and groundwater systems for three different geographical locations in Florida; Main Canal of Jacksonville Beach (in the northeast of Florida adjacent to the Atlantic Ocean), Grace Lake in central Florida, far away from surrounded coastal line, and Mc Dill in Florida and adjacent to Tampa Bay and Mexican Gulf. An integrated hydrologic and hydraulic model was developed and simulated for all three cases, including surface water, groundwater, or a combination of both. For the case study of Main Canal-Jacksonville Beach, the investigation showed that a 76 cm sea-level rise in time horizon 2060 could increase the flow velocity of the tide cycle for the main canal's outlet and headwater. This case also revealed how the sea level rise could change the tide duration, potentially affecting the coastal ecosystem. As expected, sea-level rise can raise the groundwater level. Therefore, for the Mc Dill case, the effect of groundwater rise on soil storage and the performance of stormwater retention ponds is investigated. The study showed that sea-level rise increased the pond’s seasonal high water up to 40 cm by time horizon 2060. The reliability of the retention pond is dropped from 99% for the current condition to 54% for the future. The results also proved that the retention pond could not retain and infiltrate the designed treatment volume within 72 hours, which is a significant indication of increasing pollutants in the future. Grace Lake case study investigates the effects of climate change on groundwater recharge. This study showed that using the dynamically downscaled data of the groundwater recharge can decline up to 24% by the mid-21st century.

Keywords: groundwater, surface water, Florida, retention pond, tide, sea level rise

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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Manufacturing companies are facing global competition and enormous cost pressure. The use of machine learning applications can help reduce production costs and create added value. Predictive quality enables the securing of product quality through data-supported predictions using machine learning models as a basis for decisions on test results. Furthermore, machine learning methods are able to process large amounts of data, deal with unfavourable row-column ratios and detect dependencies between the covariates and the given target as well as assess the multidimensional influence of all input variables on the target. Real production data are often subject to highly fluctuating boundary conditions and unbalanced data sets. Changes in production data manifest themselves in trends, systematic shifts, and seasonal effects. Thus, Machine learning applications require intensive pre-processing and feature selection. Data preprocessing includes rule-based data cleaning, the application of dimensionality reduction techniques, and the identification of comparable data subsets. Within the used real data set of Bosch hydraulic valves, the comparability of the same production conditions in the production of hydraulic valves within certain time periods can be identified by applying the concept drift method. Furthermore, a classification model is developed to evaluate the feature importance in different subsets within the identified time periods. By selecting comparable and stable features, the number of features used can be significantly reduced without a strong decrease in predictive power. The use of cross-process production data along the value chain of hydraulic valves is a promising approach to predict the quality characteristics of workpieces. In this research, the ada boosting classifier is used to predict the leakage of hydraulic valves based on geometric gauge blocks from machining, mating data from the assembly, and hydraulic measurement data from end-of-line testing. In addition, the most suitable methods are selected and accurate quality predictions are achieved.

Keywords: classification, achine learning, predictive quality, feature selection

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Authors: Wilfred A. Abiaa, Chibundu N. Ezekiel, Benedikt Warth, Michael Sulyok, Paul C. Turner, Rudolf Krska, Paul F. Moundipa

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Mycotoxins are a wide range of toxic secondary metabolites of fungi that contaminate various food commodities worldwide especially in sub-Saharan Africa (SSA). Such contamination seriously compromises food safety and quality posing a serious problem for human health as well as to trade and the economy. Their concentrations depend on various factors, such as the commodity itself, climatic conditions, storage conditions, seasonal variances, and processing methods. When humans consume foods contaminated by mycotoxins, they exert toxic effects to their health through various modes of actions. Rural populations in sub-Saharan Africa, are exposed to dietary mycotoxins, but it is supposed that exposure levels and health risks associated with mycotoxins between SSA countries may vary. Dietary exposures and health risk assessment studies have been limited by lack of equipment for the proper assessment of the associated health implications on consumer populations when they eat contaminated agricultural products. As such, mycotoxin research is premature in several SSA nations with product evaluation for mycotoxin loads below/above legislative limits being inadequate. Few nations have health risk assessment reports mainly based on direct quantification of the toxins in foods ('external exposure') and linking food levels with data from food frequency questionnaires. Nonetheless, the assessment of the exposure and health risk to mycotoxins requires more than the traditional approaches. Only a fraction of the mycotoxins in contaminated foods reaches the blood stream and exert toxicity ('internal exposure'). Also, internal exposure is usually smaller than external exposure thus dependence on external exposure alone may induce confounders in risk assessment. Some studies from SSA earlier focused on biomarker analysis mainly on aflatoxins while a few recent studies have concentrated on the multi-biomarker analysis of exposures in urine providing probable associations between observed disease occurrences and dietary mycotoxins levels. As a result, new techniques that could assess the levels of exposures directly in body tissue or fluid, and possibly link them to the disease state of individuals became urgent.

Keywords: mycotoxins, biomarkers, exposure assessment, health risk assessment, sub-Saharan Africa

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

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

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

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Authors: Abdelrahman Elsehsah

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Land Use and Land Cover (LULC) dynamics in Riyadh over a decade were comprehensively analyzed using the Google Earth Engine (GEE) platform. By harnessing the Landsat 8 Image collection and night-time light image collection from May to August for the years 2013 and 2023, we were able to generate insightful datasets capturing the changing landscape of the region. Our approach involved a Random Forest (RF) classification model that consistently displayed commendable precision scores above 92% for both years. A notable discovery from the study was the pronounced urban expansion, particularly around Riyadh city. Within a mere ten-year span, urbanization surged noticeably, affecting the broader ecological environment of the region. Interestingly, the northeastern part of Riyadh emerged as a focal point of this growth, signaling rapid urban growth of urban sprawl and development. A comparison between the two years indicates a 21.51% increase in built-up areas, revealing the transformative pace of urban sprawl. Contrastingly, vegetation cover patterns presented a more nuanced picture. While our initial hypothesis predicted a decline in vegetation, the actual findings depicted both vegetation reduction in certain pockets and new growth in others, resulting in an overall 25.89% increase. This intricate pattern might be attributed to shifting agricultural practices, afforestation efforts, or even satellite image timings not aligning with seasonal vegetation growth. The bare soil, predominant in the desert landscape of Riyadh, saw a marginal reduction of 0.37% over the decade, challenging our initial expectations. Urban and agricultural advancements in Saudi Arabia appear to have slightly reduced the expanse of barren terrains. This study, underpinned by a rigorous methodological framework, reveals the multifaceted land cover changes in Riyadh in response to urban development and environmental factors. The precise, data-driven insights provided by our analysis serve as invaluable tools for understanding urban growth trajectories, guiding urban planning, policy formulation, and sustainable development endeavors in the region.

Keywords: remote sensing, KSA, ArcGIS, spatio-temporal

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Authors: Xiaohong Xu, Tianchu Zhang, Yangfan Chen, Rongtai Tan

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In Canada, Air Quality Health Index (AQHI) is a scale designed to help residences understand the impact of air quality on human health. In Ontario, Canada, AQHI was implemented in June 2015. This study investigated temporal variability of daily AQHI and impact of regional transport on AQHI in Windsor, Ontario, Canada from 2016 to 2019. During 2016–2019, 1428 daily AQHIs were recorded in Windsor Downtown Station. Among those, the AQHIs were at the low health risk level (AQHI = 1, 2 or 3) in 82% of days, only a few days at high risk level (AQHI = 7), the rest were at moderate health risk level (AQHI = 4, 5, 6), indicating air quality in Windsor was fairly good with relatively low health risk. The annual mean AQHI value decreased from 2.95 in 2016 to 2.81 in 2019, demonstrating the improvement of air quality. Half of the days, AQHI were 3 regardless of season. AQHI was higher in the warm season (3.1) than in the cold season (2.6) due to more frequent moderate risk days (27%, AQHI = 4) in warm season and more frequent low risk days (42%, AQHI = 2) in the cold season. Among the three pollutants considered in AQHI calculation, O3 was the most frequently reported dominant contributor to daily AQHI (88% of days), followed by NO2 (12%), especially in the cold season, with small contribution from PM2.5 (<1%). In the past two decades, NO2 concentrations had decreased significantly and O3 concentrations had increased, resulting in daily AQHI being less reliance on NO2 (from 51% of days being the primary contributor during 2003–2010 to 12% during 2016–2019) and more on O3 concentrations (49% to 88%). Trajectory analysis found that AQHI ≤ 3 days were closely associated with air masses from the north and northwest, whereas AQHI > 3 days were closely associated with air masses from the west and southwest. This is because northerly flows brought in clear air mass owing to less industrial facilities, while polluted air masses were transported from the south of Windsor, where several industrial states of the US were located. Overall, O3 concentrations dictate the daily AQHI values, the seasonal variability of AQHI, and the impact of regional transport on AQHI in Windsor. This makes further reductions of AQHI challenging because O3 concentrations are likely to continue increasing due to weakened consumption of O3 by NO owing to decreasing NO emissions and more hot days because of climate change. The predominant and increasing contribution of O3 to AQHI calls for more effective control measures to mitigate O3 pollution and its impact on human health and the environment.

Keywords: air quality, Air Quality Health Index (AQHI), hysplit, regional transport, windsor

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Authors: Zuoji Huang, Jinyan Sun, Chunlin Wang, Haiming Qian, Nan Xu

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The spatial extent and area of central river bars can always vary due to the impact of water level, sediment supply and human activities. In 2016, a catastrophic flood disaster caused by sustained and heavy rainfall happened in the middle and lower Yangtze River. The flood led to the most serious economic and social loss since 1954, and strongly affected the central river bar. It is essential to continuously monitor the dynamics change of central bars because it can avoid frequent field measurements in central bars before and after the flood disaster and is helpful for flood warning. This paper focused on the dynamic change of central bars of Phoenix bar and Changsha bar in the Yangtze River in 2016. In this study, GF-1 (GaoFen-1) WFV(wide field view) data was employed owing to its high temporal frequency and high spatial resolution. A simple NDWI (Normalized Difference Water Index) method was utilized for river central bar mapping. Human-checking was then performed to ensure the mapping quality. The relationship between the area of central bars and the measured water level was estimated using four mathematical models. Furthermore, a risk assessment index was proposed to map the spatial pattern of inundation risk of central bars. The results indicate a good ability of the GF-1 WFV imagery with a 16-m spatial resolution to characterize the seasonal variation of central river bars and to capture the impact of a flood disaster on the area of central bars. This paper observed a significant negative but nonlinear relationship between the water level and the area of central bars, and found that the cubic function fits best among four models (R² = 0.9839, P < 0.000001, RMSE = 0.4395). The maximum of the inundated area of central bars appeared during the rainy season on July 8, 2016, and the minimum occurred during the dry season on December 28, 2016, which are consistent with the water level measured by the hydrological station. The results derived from GF-1 data could provide a useful reference for decision-making of real-time disaster early warning and post-disaster reconstruction.

Keywords: central bars, dynamic change, water level, the Yangtze river

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Authors: Liliana Rusu

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The goal of the proposed work is to provide a more comprehensive picture of the wind and wave climate in the Romanian nearshore, using the results provided by numerical models. The Romanian coastal environment is located in the western side of the Black Sea, the more energetic part of the sea, an area with heavy maritime traffic and various offshore operations. Information about the wind and wave climate in the Romanian waters is mainly based on observations at Gloria drilling platform (70 km from the coast). As regards the waves, the measurements of the wave characteristics are not so accurate due to the method used, being also available for a limited period. For this reason, the wave simulations that cover large temporal and spatial scales represent an option to describe better the wave climate. To assess the wind climate in the target area spanning 1992–2016, data provided by the NCEP-CFSR (U.S. National Centers for Environmental Prediction - Climate Forecast System Reanalysis) and consisting in wind fields at 10m above the sea level are used. The high spatial and temporal resolution of the wind fields is good enough to represent the wind variability over the area. For the same 25-year period, as considered for the wind climate, this study characterizes the wave climate from a wave hindcast data set that uses NCEP-CFSR winds as input for a model system SWAN (Simulating WAves Nearshore) based. The wave simulation results with a two-level modelling scale have been validated against both in situ measurements and remotely sensed data. The second level of the system, with a higher resolution in the geographical space (0.02°×0.02°), is focused on the Romanian coastal environment. The main wave parameters simulated at this level are used to analyse the wave climate. The spatial distributions of the wind speed, wind direction and the mean significant wave height have been computed as the average of the total data. As resulted from the amount of data, the target area presents a generally moderate wave climate that is affected by the storm events developed in the Black Sea basin. Both wind and wave climate presents high seasonal variability. All the results are computed as maps that help to find the more dangerous areas. A local analysis has been also employed in some key locations corresponding to highly sensitive areas, as for example the main Romanian harbors.

Keywords: numerical simulations, Romanian nearshore, waves, wind

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Authors: Swati Rajput

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Environmental psychology explains that the person is a social agent that seeks to extract meaning from their built and natural environment to behave in a particular manner. It also shows the attachment or detachment of people to their environment. Assessing environmental psychology of people is imperative for planners and policy makers for urban planning. The paper investigates the environmental psychology of people living in nine districts of Delhi by calculating and assessing their Environmental Emotional Quotient (EEQ). Emotional Quotient deals with the ability to sense, understand, attach and respond according to the power of emotions. An Environmental Emotional Quotient has been formulated based upon the inventory administered to them. The respondents were asked questions related to their view and emotions about the green spaces, water resource conservation, air and environmental quality. An effort has been made to assess the feeling of belongingness among the residents. Their views were assessed on green spaces, reuse, and recycling of resources and their participation level. They were also been assessed upon health awareness level by considering both preventive and curative segments of health care. It was found that only 12 percent of the people is emotionally attached to their surroundings in the city. The emotional attachment reduces as we move away from the house to housing complex to neighbouring areas and rest of the city. In fact, the emotional quotient goes lower to lowest from house to other ends of the city. It falls abruptly after the radius of 1 km from the residence. The result also shows that nearly 54% respondents accept that there is environment pollution in their area. Around 47.8% respondents in the survey consider that diseases occur because of green cover depiction in their area. Major diseases are to airborne diseases like asthma and bronchitis. Seasonal disease prevalent, which specially occurred from last 3-4 years are malaria, dengue and chikengunya. Survey also shows that only 31 % of respondents visit government hospitals while 69% respondents visit private hospitals or small clinics for healthcare services. The paper suggests the need for environmental sensitive policies and need for green insurance in mega cities like Delhi.

Keywords: environmental psychology, environmental emotional quotient, preventive health care and curative health care, sustainable living

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Authors: Shreya Srivastava, Sagnik Dey

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Aerosol direct radiative forcing (ADRF) refers to the alteration of the Earth's energy balance from the scattering and absorption of solar radiation by aerosol particles. India experiences substantial ADRF due to high aerosol loading from various sources. These aerosols' radiative impact depends on their physical characteristics (such as size, shape, and composition) and atmospheric distribution. Quantifying ADRF is crucial for understanding aerosols’ impact on the regional climate and the Earth's radiative budget. In this study, we have taken radiation data from Clouds and the Earth’s Radiant Energy System (CERES, spatial resolution=1ox1o) for 22 years (2000-2021) over the Indian subcontinent. Except for a few locations, the short-wave DARF exhibits aerosol cooling at the TOA (values ranging from +2.5 W/m2 to -22.5W/m2). Cooling due to aerosols is more pronounced in the absence of clouds. Being an aerosol hotspot, higher negative ADRF is observed over the Indo-Gangetic Plain (IGP). Aerosol Forcing Efficiency (AFE) shows a decreasing seasonal trend in winter (DJF) over the entire study region while an increasing trend over IGP and western south India during the post-monsoon season (SON) in clear-sky conditions. Analysing atmospheric heating and AOD trends, we found that only the aerosol loading is not governing the change in atmospheric heating but also the aerosol composition and/or their vertical profile. We used a Multi-angle Imaging Spectro-Radiometer (MISR) Level-2 Version 23 aerosol products to look into aerosol composition. MISR incorporates 74 aerosol mixtures in its retrieval algorithm based on size, shape, and absorbing properties. This aerosol mixture information was used for analysing long-term changes in aerosol composition and dominating aerosol species corresponding to the aerosol forcing value. Further, ADRF derived from this method is compared with around 35 studies across India, where a plane parallel Radiative transfer model was used, and the model inputs were taken from the OPAC (Optical Properties of Aerosols and Clouds) utilizing only limited aerosol parameter measurements. The result shows a large overestimation of TOA warming by the latter (i.e., Model-based method).

Keywords: aerosol radiative forcing (ARF), aerosol composition, MISR, CERES, SBDART

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Authors: M. Amparo Núñez-Andrés, Felipe Buill, Albert Prades

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More and more frequently, geomatics techniques such as terrestrial laser scanning or digital photogrammetry, either terrestrial or from drones, are being used to obtain digital terrain models (DTM) used for the monitoring of geological phenomena that cause natural disasters, such as landslides, rockfalls, debris-flow. One of the main multitemporal analyses developed from these models is the quantification of volume changes in the slopes and hillsides, either caused by erosion, fall, or land movement in the source area or sedimentation in the deposition zone. To carry out this task, it is necessary to filter the point clouds of all those elements that do not belong to the slopes. Among these elements, vegetation stands out as it is the one we find with the greatest presence and its constant change, both seasonal and daily, as it is affected by factors such as wind. One of the best-known indexes to detect vegetation on the image is the NVDI (Normalized Difference Vegetation Index), which is obtained from the combination of the infrared and red channels. Therefore it is necessary to have a multispectral camera. These cameras are generally of lower resolution than conventional RGB cameras, while their cost is much higher. Therefore we have to look for alternative indices based on RGB. In this communication, we present the results obtained in Georisk project (PID2019‐103974RB‐I00/MCIN/AEI/10.13039/501100011033) by using the GLI (Green Leaf Index) and ExG (Excessive Greenness), as well as the change to the Hue-Saturation-Value (HSV) color space being the H coordinate the one that gives us the most information for vegetation filtering. These filters are applied both to the images, creating binary masks to be used when applying the SfM algorithms, and to the point cloud obtained directly by the photogrammetric process without any previous filter or the one obtained by TLS (Terrestrial Laser Scanning). In this last case, we have also tried to work with a Riegl VZ400i sensor that allows the reception, as in the aerial LiDAR, of several returns of the signal. Information to be used for the classification on the point cloud. After applying all the techniques in different locations, the results show that the color-based filters allow correct filtering in those areas where the presence of shadows is not excessive and there is a contrast between the color of the slope lithology and the vegetation. As we have advanced in the case of using the HSV color space, it is the H coordinate that responds best for this filtering. Finally, the use of the various returns of the TLS signal allows filtering with some limitations.

Keywords: RGB index, TLS, photogrammetry, multispectral camera, point cloud

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Authors: Shreya Goyal

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The study aims to build user-friendly software to understand patient arrival patterns and compute the number of potential patients who will visit a particular health facility for a given period by using a machine learning algorithm. The underlying machine learning algorithm used in this study is the Support Vector Machine (SVM). Accurate prediction of patient arrival allows hospitals to operate more effectively, providing timely and efficient care while optimizing resources and improving patient experience. It allows for better allocation of staff, equipment, and other resources. If there's a projected surge in patients, additional staff or resources can be allocated to handle the influx, preventing bottlenecks or delays in care. Understanding patient arrival patterns can also help streamline processes to minimize waiting times for patients and ensure timely access to care for patients in need. Another big advantage of using this software is adhering to strict data protection regulations such as the Health Insurance Portability and Accountability Act (HIPAA) in the United States as the hospital will not have to share the data with any third party or upload it to the cloud because the software can read data locally from the machine. The data needs to be arranged in. a particular format and the software will be able to read the data and provide meaningful output. Using software that operates locally can facilitate compliance with these regulations by minimizing data exposure. Keeping patient data within the hospital's local systems reduces the risk of unauthorized access or breaches associated with transmitting data over networks or storing it in external servers. This can help maintain the confidentiality and integrity of sensitive patient information. Historical patient data is used in this study. The input variables used to train the model include patient age, time of day, day of the week, seasonal variations, and local events. The algorithm uses a Supervised learning method to optimize the objective function and find the global minima. The algorithm stores the values of the local minima after each iteration and at the end compares all the local minima to find the global minima. The strength of this study is the transfer function used to calculate the number of patients. The model has an output accuracy of >95%. The method proposed in this study could be used for better management planning of personnel and medical resources.

Keywords: machine learning, SVM, HIPAA, data

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Authors: Ayat-Allah Bouramdane

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Since 2010, there have been sustained decreases in the unit costs of onshore wind energy and large increases in its deployment, varying widely across regions. In fact, the onshore wind production is affected by air density— because cold air is more dense and therefore more effective at producing wind power— and by wind speed—as wind turbines cannot operate in very low or extreme stormy winds. The wind speed is essentially affected by the surface friction or the roughness and other topographic features of the land, which slow down winds significantly over the continent. Hence, the identification of the most appropriate locations of onshore wind systems is crucial to maximize their energy output and therefore minimize their Levelized Cost of Electricity (LCOE). This study focuses on the preliminary assessment of onshore wind energy potential, in several areas in Morocco with a particular focus on the Dakhla city, by analyzing the diurnal and seasonal variability of wind speed for different hub heights, the frequency distribution of wind speed, the wind rose and the wind performance indicators such as wind power density, capacity factor, and LCOE. In addition to climate criterion, other criteria (i.e., topography, location, environment) were selected fromGeographic Referenced Information (GRI), reflecting different considerations. The impact of each criterion on the suitability map of onshore wind farms was identified using the Analytic Hierarchy Process (AHP). We find that the majority of suitable zones are located along the Atlantic Ocean and the Mediterranean Sea. We discuss the sensitivity of the onshore wind site suitability to different aspects such as the methodology—by comparing the Multi-Criteria Decision-Making (MCDM)-AHP results to the Mean-Variance Portfolio optimization framework—and the potential impact of climate change on this suitability map, and provide the final recommendations to the Moroccan energy strategy by analyzing if the actual Morocco's onshore wind installations are located within areas deemed suitable. This analysis may serve as a decision-making framework for cost-effective investment in onshore wind power in Morocco and to shape the future sustainable development of the Dakhla city.

Keywords: analytic hierarchy process (ahp), dakhla, geographic referenced information, morocco, multi-criteria decision-making, onshore wind, site suitability.

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Authors: Dewan Ali Ahsan

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Hilsa (Tenualosa ilisha) is one of the most important anadromous fish species of the trans-boundary ecosystem of Bangladesh, India and Myanmar. Hilsa is not only an economically important species specially for Bangladesh and India, but also for the integral part of the culture of the Bangladesh and India. This flag-ship species in Bangladesh contributed alone of 10.82% of the total fish production of the country and about 75% of world’s total catch of hilsa comes from Bangladesh alone. As hilsa is an anadromous fish, it migrates from the Bay of Bengal to rivers for spawning, nursing and growing and for all of these purposes hilsa needs freshwaters. Ripe broods prefer turbid, fast flowing freshwater for spawning but young prefer clear and slow flowing freshwater. Climate change (salinity intrusion, sea level rise, temperature rise, impact of fresh water flow), unplanned developmental activities and other anthropogenic activities all together are severely damaging the hilsa stock and its habitats. So, climate change and human interferences are predicted to have a range of direct and indirect impacts on marine and freshwater hilsa fishery, with implications for fisheries-dependent economies, coastal communities and fisherfolk. The present study identified that salinity intrusion, siltation in river bed, decrease water flow from upstream, fragmentation of river in dry season, over exploitation, use of small mesh nets are the major reasons to affect the upstream migration of hilsa and its sustainable management. It has been also noticed that Bangladesh government has taken some actions for hilsa management. Government is trying to increase hilsa production not only by conserving jatka (juvenile hilsa) but also protecting the brood hilsa during the breeding seasons by imposing seasonal ban on fishing, restricted mesh size etc. Unfortunately, no such management plans are available for Indian and Myanmar territory. As hilsa is a highly migratory trans-boundary fish in the Bay of Bengal (and all of these countries share the same stock), it is essential to adopt a joint management policy (by Bangladesh-India-Myanmar) for the sustainable management for the hilsa stock.

Keywords: hilsa, climate change, south-east Asia, fishery management

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Authors: Disha Bhanot, Vinish Kathuria

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This study focusses on the issue of distress sale in horticulture sector in India, which faces unique challenges, given the perishable nature of horticulture crops, seasonal production and paucity of post-harvest produce management links. Distress sale, from a farmer’s perspective may be defined as urgent sale of normal or distressed goods, at deeply discounted prices (way below the cost of production) and it is usually characterized by unfavorable conditions for the seller (farmer). The small and marginal farmers, often involved in subsistence farming, stand to lose substantially if they receive lower prices than expected prices (typically framed in relation to cost of production). Distress sale maximizes price uncertainty of produce leading to substantial income loss; and with increase in input costs of farming, the high variability in harvest price severely affects profit margin of farmers, thereby affecting their survival. The objective of this study is to model the occurrence of distress sale by tomato cultivators in the Indian state of Maharashtra, against the background of differential access to set of factors such as - capital, irrigation facilities, warehousing, storage and processing facilities, and institutional arrangements for procurement etc. Data is being collected using primary survey of over 200 farmers in key tomato growing areas of Maharashtra, asking information on the above factors in addition to seeking information on cost of cultivation, selling price, time gap between harvesting and selling, role of middleman in selling, besides other socio-economic variables. Farmers selling their produce far below the cost of production would indicate an occurrence of distress sale. Occurrence of distress sale would then be modelled as a function of farm, household and institutional characteristics. Heckman-two-stage model would be applied to find the probability/likelihood of a famer falling into distress sale as well as to ascertain how the extent of distress sale varies in presence/absence of various factors. Findings of the study would recommend suitable interventions and promotion of strategies that would help farmers better manage price uncertainties, avoid distress sale and increase profit margins, having direct implications on poverty.

Keywords: distress sale, horticulture, income loss, India, price uncertainity

Procedia PDF Downloads 243