Search results for: environmental measures

Authors: Yasser Sanad, Thu Trang Dao

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Introduction: Implementing the One Health (OH) approach requires an integrated, interdisciplinary, and cross-sectoral methodology. OH is a key tool for developing and implementing programs and projects and includes developing ambitious policies that consider the common needs and benefits of human, animal, plant, and ecosystem health. OH helps humanity readjust its path to environmentally friendly and impartial sustainability. As co-leader of the Global Health Security Agenda’s Zoonotic Disease Action Package, Vietnam pioneered a strong OH approach to effectively address early waves of the COVID-19 outbreak in-country. Context and Aim: The repeated surges in COVID-19 in Vietnam challenged the capabilities of the national system and disclosed the gaps in multi-sectoral coordination and resilience. To address this, FHI 360 advocated for the standardization of the OH platform by government actors to increase the resiliency of the system during and post COVID-19. Methods: FHI 360 coordinated technical resources to develop and implement evidence-based OH policies, promoting high-level policy dialogue between the Ministries of Health, Agriculture, and the Environment, and policy research to inform developed policies and frameworks. Through discussions, an OH-building Partnership (OHP) was formed, linking climate change, the environment, and human and animal health. Findings: The OHP Framework created a favorable policy environment within and between sectors, as well as between governments and international health security partners. It also promoted strategic dialogue, resource mobilization, policy advocacy, and integration of international systems with National Steering Committees to ensure accountability and emphasize national ownership. Innovative contribution to policy, practice and/or research: OHP was an effective evidence-based research-to-policy platform linking to the National One Health Strategic Plan (2021-2025). Collectively they serve as a national framework for the implementation and monitoring of OH activities. Through the adoption of policies and plans, the risk of zoonotic pathogens, environmental agent spillover, and antimicrobial resistance can be minimized through strengthening multi-sectoral OH collaboration for health security.

Keywords: one health, national policies, health security, COVID-19, Vietnam

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Authors: Jinhoa Lee

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The relationships between environmental quality, energy use and economic output have created growing attention over the past decades among researchers and policy makers. Focusing on the empirical aspects of the role of carbon dioxide (CO2) emissions and energy use in affecting the economic output, this paper is an effort to fulfill the gap in a comprehensive case study at a country level using modern econometric techniques. To achieve the goal, this country-specific study examines the short-run and long-run relationships among energy consumption (using disaggregated energy sources: Crude oil, coal, natural gas, and electricity), CO2 emissions and gross domestic product (GDP) for Iran using time series analysis from the year 1980-2010. To investigate the relationships between the variables, this paper employs the Augmented Dickey-Fuller (ADF) test for stationarity, Johansen’s maximum likelihood method for cointegration and a Vector Error Correction Model (VECM) for both short- and long-run causality among the research variables for the sample. All the variables in this study show very strong significant effects on GDP in the country for the long term. The long-run equilibrium in VECM suggests that all energy consumption variables in this study have significant impacts on GDP in the long term. The consumption of petroleum products and the direct combustion of crude oil and natural gas decrease GDP, while the coal and electricity use enhanced the GDP between 1980-2010 in Iran. In the short term, only electricity use enhances the GDP as well as its long-run effects. All variables of this study, except the CO2 emissions, show significant effects on the GDP in the country for the long term. The long-run equilibrium in VECM suggests that the consumption of petroleum products and the direct combustion of crude oil and natural gas use have positive impacts on the GDP while the consumptions of electricity and coal have adverse impacts on the GDP in the long term. In the short run, electricity use enhances the GDP over period of 1980-2010 in Iran. Overall, the results partly support arguments that there are relationships between energy use and economic output, but the associations can be differed by the sources of energy in the case of Iran over period of 1980-2010. However, there is no significant relationship between the CO2 emissions and the GDP and between the CO2 emissions and the energy use both in the short term and long term.

Keywords: CO2 emissions, energy consumption, GDP, Iran, time series analysis

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Authors: Mohamed Redha Menani

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The Northern Saharan aquifer system “SASS” shared by Algeria, Libya, and Tunisia, covers a surface of about 1 100 000 km². It is composed of superposed aquifers; the upper one is the “Continental terminal – CT” (Eocene calcareous formation) situated at 400 m depth in average, while the” Continental Intercalaire – CI”(clay sands from Albian to Lower Cretaceous) is generally at 1500 m depth. This aquifer system is situated in a dry zone with a very weak current recharge but with a non-renewable big volume stored, estimated between 20 000 and 31 000 km³. From 1970 to nowadays, the exploitation of the SASS has increased from 0.6 to more than 2.5 km³/year. This situation provoked risks of water salinisation, reduction of the artesianisme, an increase of drawdowns, etc. which seriously threaten the sustainable socioeconomic development engaged in the SASS zone. Face the water shortage induced by the alarming dryness noted these last years, particularly in the MENA region, the joint management of this system by the three concerned countries, engaged for many years, needs a long-term strategy of integrated water resources management to meet the expected socio-economic goals projected not only in the SASS zone but also in other places, by water transfers. The sustainable management of this extensive aquifer system, aiming to satisfy various needs not only in the areas covered by the SASS but also in other areas through hydraulic transfers, can only be considered if this management is genuinely coordinated, incorporating schemes that primarily address the major constraint of climate change, which has been observed worldwide over the past two decades and is intensifying. In this particular climate context, management schemes must necessarily target several aspects, including (i) Updating the state of water resource exploitation in the SASS. (ii) Guiding agricultural usage as the primary consumer to ensure significant water savings. (iii) Constant monitoring through a network of piezometers to control the physicochemical parameters of the exploited aquifers. (iv) Other aspects related to governance within the framework of integrated management must also be taken into consideration, particularly environmental aspects and conflict resolution. However, problems, especially political ones as currently seen in Libya, may limit or at least disrupt the prospects of coordinated and sustainable management of this aquifer system, which is vital for the three countries.

Keywords: transboundary water resources, SASS, governance, climatic changes

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Authors: Ethel E. Phiri, Lionel Hartzenberg, Percy Chimwamuromba, Emmanuel Nepolo, Jens Kossmann, James R. Lloyd

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Orphan crops are underresearched and underutilized food plant species that have not been categorized as major food crops, but have the potential to be economically and agronomically significant. They have been documented to have the ability to tolerate extreme environmental conditions. However, limited research has been conducted to uncover their potential as food crop species. The New Partnership for Africa’s Development (NEPAD) has classified Marama bean, Tylosema esculentum, as an orphan crop. The plant is one of the 101 African orphan crops that must have their genomes sequenced, assembled, and annotated in the foreseeable future. Marama bean is a perennial leguminous plant that primarily grows in poor, arid soils in southern Africa. The plants produce large tubers that can weigh as much as 200kg. While the foliage provides fodder, the tuber is carbohydrate rich and is a staple food source for rural communities in Namibia. Also, the edible seeds are protein- and oil-rich. Marama Bean plants respond rapidly to increased temperatures and severe water scarcity without extreme consequences. Advances in molecular biology and biotechnology have made it possible to effectively transfer technologies between model- and major crops to orphan crops. In this research, the aim was to assemble the first transcriptomic analysis of Marama Bean RNA-sequence data. Many model plant species have had their genomes sequenced and their transcriptomes assembled. Therefore the availability of transcriptome data for a non-model crop plant species will allow for gene identification and comparisons between various species. The data has been sequenced using the Ilumina Hiseq 2500 sequencing platform. Data analysis is underway. In essence, this research will eventually evaluate the potential use of Marama Bean as a crop species to improve its value in agronomy. data for a non-model crop plant species will allow for gene identification and comparisons between various species. The data has been sequenced using the Ilumina Hiseq 2500 sequencing platform. Data analysis is underway. In essence, this researc will eventually evaluate the potential use of Marama bean as a crop species to improve its value in agronomy.

Keywords: 101 African orphan crops, RNA-Seq, Tylosema esculentum, underutilised crop plants

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Authors: Maria E. Laconi, Kyla D. Scherr, Mary A. Jamieson

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Human populations in urban environments have rapidly grown in recent decades. Consequently, the intensity of land-use and development has also increased in many urban and peri-urban environments. Some cities, such as Detroit, Michigan, USA, have embraced urban agriculture and local food production. Little is known, however, about how the local and landscape scale environmental factors influence crop productivity on urban farms. Our study aims to evaluate factors influencing the productivity of strawberries on community farms and gardens in the Detroit metropolitan area. Strawberries are one of few fruits that can provide an abundant harvest just after the first season of being planted, which is ideal for urban gardeners in developed areas. In the spring of 2016, we planted six different strawberry cultivars (three everbearing and three June bearing varieties) at five farm sites in Wayne and Oakland County (six replicate plants per cultivar per site). We surveyed flower and fruit phenology and production for everbearing varieties weekly (flowers for June bearing varieties were removed to enhance productivity in the coming growing season). Additionally, we conducted one initial 36hr pollinator survey in mid-September during peak fruit production and characterized local and landscape scale land-cover data. Preliminary results and observations from this first year of our study revealed that strawberry production varied significantly by site. Specifically, productivity at our most northern site appeared to suffer from delayed phenology and early frost damage to ripening strawberries. Bee abundance and diversity also differed among farms, though further surveys are needed to adequately inventory the pollinator community. Finally, strawberry cultivars demonstrated significant differences in the number and size of fruits produced. We plan to continue this study in the coming years, increasing the number of sites surveyed and number of pollinator sampling events. Our study aims to inform strategies for enhancing crop productivity on urban and peri-urban farms.

Keywords: insect pollination, strawberry productivity, sustainable agriculture, urban gardening

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Authors: Balazs Kulcsar

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Professional energy organizations perform analyses mainly on the global and national levels about the expected development of the share of renewables in electric power generation, heating, and cooling, as well as the transport sectors. There are just a few publications, research institutions, non-profit organizations, and national initiatives with a focus on studies in the individual towns, settlements. Issues concerning the self-supply of energy on the settlement level have not become too wide-spread. The goal of our energy geographic studies is to determine the share of local renewable energy sources in the settlement-based electricity supply across Hungary. The Hungarian energy supply system defines four categories based on the installed capacities of electric power generating units. From these categories, the theoretical annual electricity production of small-sized household power plants (SSHPP) featuring installed capacities under 50 kW and small power plants with under 0.5 MW capacities have been taken into consideration. In the above-mentioned power plant categories, the Hungarian Electricity Act has allowed the establishment of power plants primarily for the utilization of renewable energy sources since 2008. Though with certain restrictions, these small power plants utilizing renewable energies have the closest links to individual settlements and can be regarded as the achievements of the host settlements in the shift of energy use. Based on the 2017 data, we have ranked settlements to reflect the level of self-sufficiency in electricity production from renewable energy sources. The results show that the supply of all the energy demanded by settlements from local renewables is within reach now in small settlements, e.g., in the form of the small power plant categories discussed in the study, and is not at all impossible even in small towns and cities. In Hungary, 30 settlements produce more renewable electricity than their own annual electricity consumption. If these overproductive settlements export their excess electricity towards neighboring settlements, then full electricity supply can be realized on further 29 settlements from renewable sources by local small power plants. These results provide an opportunity for governmental planning of the realization of energy shift (legislative background, support system, environmental education), as well as framing developmental forecasts and scenarios until 2030.

Keywords: energy geography, Hungary, local small power plants, renewable energy sources, self-sufficiency settlements

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Authors: Mokhtar Nikgoo

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Today's industrial world has undergone tremendous changes in certain periods. These changes are called environmental changes. And they have a direct impact on organizations and bodies. Therefore, the importance of knowing these changes is clear. This importance has caused the manufacturing organizations to move towards multiple products and constantly change and expand their system. This research tries to show how the organization moves in this category by defining the basic steps of implementing a project. One of the most important features of a hard-to-order production organization is the definition of different production projects from different customers. Therefore, the lack of sufficient understanding of the type of work causes the project to be defined for the organization in question, and the managers of the organization (in every organizational level) are constantly involved with different projects. In the implementation of the production project of the aforementioned organizations, directing the facilities and people of the organization towards the implementation of the project is of particular importance. Therefore, it is felt necessary to define the project manager and his basic duties. Considering the importance of this topic, the project chapter deals with project management and its importance and examines all the different issues in that category from the perspective of implementation. A project includes certain activities of the organization that require the use of different resources and all the activities of the organization in order to implement the project with defined facilities and at the designated times. Project management is planning, organizing and controlling the organization's resources for a short-term goal that has been created for short-term and medium-term goals and objectives. Project management has the important task of centering and integrating (coordinating) task and line managers. In other words, project management requires having a strong and appropriate relationship with the internal people of the system to carry out the assigned activities and must have a general and technical knowledge related to various activities in the project environment. It seems that everything with project management in It is communication. One of the characteristics of production organizations under the order is the relationship between the customer (customers) and the organization until the completion of the defined project. Due to the nature of the work, it is necessary for a person to establish this relationship between the client and the organization's people and to establish this relationship in such a way that it does not cause a lack of coordination in the organization's activities. Therefore, project management has a very important role at this stage, because the relationship between the client and his organization will be any problems and problems and points of view that the client has, he must inform the management so that he can implement the cases with its analysis and special processes. To be transferred to other departments and line managers.

Keywords: project management, crisis management, project delays bill, project duration

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Authors: Pradip Choudhury, Tapobrata Sanyal

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Effectiveness of Jute Geotextiles (JGT) in hill slope management now stands substantiated. The reasons of its efficacy are attributed to its bio-degradability, hygroscopic property and its thickness. Usually open weave JGT is used for slope management. Thickness of JGT helps in reducing the velocity of surface run-off, thus curbing the extent of migration of soil particles detached as a result of kinetic energy of rain-drops and also of wind effects. Initially JGT acts as cover of the surface of slope thus protect movement of loose soil particles. Hygroscopic property of jute effects overland storage of the flow. JGT acts as mulch and creates a congenial micro-climate that fosters quick growth of vegetation on bio-degradation. In fact JGT plays an important role in bio-remediation of slope-erosion problems. Considering the environmental aftermath, JGT is the preferred option in developed countries for surface soil conservation against erosion. In India JGT has not been tried in low temperature zones at high altitudes where temperature goes below the freezing point (even below - 25° Celsius). The behavior of JGT in such low-temperature zones is not precisely known. The 16th BRTF of Project Himank of Border Roads Organization (BRO) has recently taken the initiative to try two varieties of JGT , ie, 292 gsm and 500 gsm at two different places for hill slope management in Leh, a high altitude place of about 2,660 mtrs and 4900 mtrs above MSL respectively in Jammu & Kashmir where erosion is caused more as a result of rapid movement of sand particles due to high wind (wind erosion. Soil particles of the region formed naturally by weathering of fragile rocks are usually loosely bonded (non-cohesive), undergo dissociation with the rise in wind force and kinetic energy of rain drops and are blown away by wind. Open weave JGT interestingly was observed to contain the dissociated soil particles within its pores and lend stability the affected soil mass to a great extent thus preventing its movement by extraneous agents such as wind. The paper delineates about climatic factors, type of JGT used and the prevailing site conditions with an attempt to analyze the mechanism of functioning of JGT in low temperature zones.

Keywords: climate, erosion, jutegeotextile, stabilize

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Authors: Hung Hing Chan, Tai-Shan Hu

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Kaohsiung has been an industrial city of Taiwan for over a hundred year. Consequently, there are several abandoned industrial lands left when the process of deindustrialization has started, resulting in the decay of the adjacent urban communities. These industrial lands, which are brownfields that are potentially or already contaminated by hazardous substances, have created social injustice to the surrounding communities. The redevelopments of industrial lands bring a sustainable development to the communities, while the redevelopments can be in different forms, depending on the natural conditions. This research studies the possible approaches to facilitate social sustainability of urban regeneration resulted from the industrial land redevelopment projects, which has always been ignored. The aim of the research is to find out the best western practices of brownfield redevelopment to facilitate social aspect of sustainable urban regeneration and make a contribution to the industrial land redevelopment of Taiwan. The research is conducted via literature review and case study. Industrial land redevelopment has been a social focus in the blighted communities to promote urban regeneration after the post-industrial age. The tendency of this kind of redevelopment is towards constructing the built environment, as a result the environmental and economic aspect of sustainability of the redeveloped industrial land will be boosted, while the social aspect will not be necessarily better since the local communities affected are rarely engaged in the decision-making process and inadequate resource allocation to the projects is not guaranteed. To ensure the improvement of social sustainability is reached, the recommendations of this research, such as civic engagement, a formation of dedicated brownfield regeneration agency and resource allocation to employ brownfield process manager and to strategic communication, should be incorporated into the real practices of industrial land-led urban regeneration. Besides, the case study also shows that the social sustainability of industrial land-led urban regeneration can be promoted by (1) upholding the local feature and public participation in the regeneration process, (2) allocating resources and enforcing responsibility system, and (3) assuring financial resource for the urban regeneration projects and residents. Subsequent research will involve in-depth interviews with the chiefs of the village of related communities in Kaohsiung and questionnaire with the community members to comprehend their opinions regarding social sustainability, aiming at evaluating the social sustainability and finding out which kind of redevelopment project tends to support the social dimension of sustainable development more.

Keywords: brownfield, industrial land, redevelopment, social sustainability, urban regeneration

Procedia PDF Downloads 217

Authors: Hasan Ustun Basaran

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Diesel engines are widely used in transportation sector due to their high thermal efficiency. However, they also release high rates of NOₓ and PM (particulate matter) emissions into the environment which have hazardous effects on human health. Therefore, environmental protection agencies have issued strict emission regulations on automotive diesel engines. Recently, these regulations are even increasingly strengthened. Engine producers search novel on-engine methods such as advanced combustion techniques, utilization of renewable fuels, exhaust gas recirculation, advanced fuel injection methods or use exhaust after-treatment (EAT) systems in order to reduce emission rates on diesel engines. Although those aforementioned on-engine methods are effective to curb emission rates, they result in inefficiency or cannot decrease emission rates satisfactorily at all operating conditions. Therefore, engine manufacturers apply both on-engine techniques and EAT systems to meet the stringent emission norms. EAT systems are highly effective to diminish emission rates, however, they perform inefficiently at low loads due to low exhaust gas temperatures (below 250°C). Therefore, the objective of this study is to demonstrate that engine-out temperatures can be elevated above 250°C at low-loaded cases via cylinder disablement. The engine studied and modeled via Lotus Engine Simulation (LES) software is a six-cylinder turbocharged and intercooled diesel engine. Exhaust temperatures and mass flow rates are predicted at 1200 rpm engine speed and several low loaded conditions using LES program. It is seen that cylinder deactivation results in a considerable exhaust temperature rise (up to 100°C) at low loads which ensures effective EAT management. The method also improves fuel efficiency through reduced total pumping loss. Decreased total air induction due to inactive cylinders is thought to be responsible for improved engine pumping loss. The technique reduces exhaust gas flow rate as air flow is cut off on disabled cylinders. Still, heat transfer rates to the after-treatment catalyst bed do not decrease that much since exhaust temperatures are increased sufficiently. Simulation results are promising; however, further experimental studies are needed to identify the true potential of the method on fuel consumption and EAT improvement.

Keywords: cylinder disablement, diesel engines, exhaust after-treatment, exhaust temperature, fuel efficiency

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Authors: S. Maleczek, K. Drabczyk, L. Bogdan, A. Iwan

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It is known that for industrial applications using solar panel constructed from silicon solar cells require high-efficiency performance. One of the main problems in solar panels is different mechanical and structural defects, causing the decrease of generated power. To analyse defects in solar cells, various techniques are used. However, the thermal imaging is fast and simple method for locating defects. The main goal of this work was to analyze defects in constructed flexible silicon photovoltaic modules via thermal imaging and electroluminescence method. This work is realized for the GEKON project (No. GEKON2/O4/268473/23/2016) sponsored by The National Centre for Research and Development and The National Fund for Environmental Protection and Water Management. Thermal behavior was observed using thermographic camera (VIGOcam v50, VIGO System S.A, Poland) using a DC conventional source. Electroluminescence was observed by Steinbeis Center Photovoltaics (Stuttgart, Germany) equipped with a camera, in which there is a Si-CCD, 16 Mpix detector Kodak KAF-16803type. The camera has a typical spectral response in the range 350 - 1100 nm with a maximum QE of 60 % at 550 nm. In our work commercial silicon solar cells with the size 156 × 156 mm were cut for nine parts (called single solar cells) and used to create photovoltaic modules with the size of 160 × 70 cm (containing about 80 single solar cells). Flexible silicon photovoltaic modules on polyamides or polyester fabric were constructed and investigated taking into consideration anomalies on the surface of modules. Thermal imaging provided evidence of visible voltage-activated conduction. In electro-luminescence images, two regions are noticeable: darker, where solar cell is inactive and brighter corresponding with correctly working photovoltaic cells. The electroluminescence method is non-destructive and gives greater resolution of images thereby allowing a more precise evaluation of microcracks of solar cell after lamination process. Our study showed good correlations between defects observed by thermal imaging and electroluminescence. Finally, we can conclude that the thermographic examination of large scale photovoltaic modules allows us the fast, simple and inexpensive localization of defects at the single solar cells and modules. Moreover, thermographic camera was also useful to detection electrical interconnection between single solar cells.

Keywords: electro-luminescence, flexible devices, silicon solar cells, thermal imaging

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Authors: N. N. Pandey, Raghvendra Singh, Biju S. Kamlam, Bipin K. Vishwakarma, Preetam Kala

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The rainbow trout (Oncorhynchus mykiss) is an exotic salmonid fish, well known for its fast growth, tremendous ability to thrive in diverse conditions, delicious flesh and hard fighting nature in Europe and other countries. Rainbow trout farming has a great potential for its contribution to the mainstream economy of Himalayan states in India and other temperate countries. These characteristics establish them as one of the most widely introduced and cultured fish across the globe, and its farming is also prominent in the cold water regions of India. Nevertheless, genetic fatigue, slow growth, early maturity, and low productivity are limiting the expansion of trout production. Moreover, farms adjacent to natural streams or other water sources are subject to escape of domesticated rainbow trout into the wild, which is a serious environmental concern as the escaped fish is subject to contaminate and disrupt the receiving ecosystem. A decline in production traits due to early maturity prolongs the culture duration and affects the profit margin of rainbow trout farms in India. A viable strategy that could overcome these farming constraints in large scale operation is the production of triploid fish that are sterile and more heterozygous. For better triploidy induction rate (TR), heat shock at 28°C for 10 minutes and pressure shock 9500 psi pressure for 5 minutes is applied to green eggs with 90-100% of triploidy success and 72-80% survival upto swim-up fry stage. There is 20% better growth in aquaculture with triploids rainbow trout over diploids. As compared to wild diploid fish, larger sized and fitter triploid rainbow trout in natural waters attract to trout anglers, and support the development of recreational fisheries by state fisheries departments without the risk of contaminating existing gene pools and disrupting local fish diversity. Overall, enhancement of productivity in rainbow trout farms and trout production in coldwater regions, development of lucrative trout angling and better ecological management is feasible with triploid rainbow trout.

Keywords: rainbow trout, triploids fish, heat shock, pressure shock, trout angling

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Authors: Liana Claudia Salanță, Anca Corina Fărcaș

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Valorization of agro-industrial by-products offers significant economic and environmental advantages. This study investigates the transformation of tomato processing residues into value-added products, contributing to waste reduction and promoting a circular, sustainable economy. Specifically, the development of sorghum flour-based crackers enriched with tomato waste powder targets the dietary requirements of individuals with celiac disease and diabetes, evaluating their nutritional and sensory properties. Tomato residues were obtained from Roma-Spania tomatoes and processed into powder through drying and grinding. The bioactive compounds, including carotenoids, lycopene, and polyphenols, were quantified using established analytical methods. Formulation of the crackers involved optimizing the incorporation of tomato powder into sorghum flour. Subsequently, their nutritional and sensory attributes were assessed. The tomato waste powder demonstrated considerable bioactive potential, with total carotenoid content measured at 66 mg/100g, lycopene at 52.61 mg/100g, and total polyphenols at 463.60 mg GAE/100g. Additionally, the crackers with a 30% powder addition exhibited the highest concentration of polyphenols. Consequently, this sample also demonstrated a high antioxidant activity of 15.04% inhibition of DPPH radicals. Nutritionally, the crackers showed a 30% increase in fiber content and a 25% increase in protein content compared to standard gluten-free products. Sensory evaluation indicated positive consumer acceptance, with an average score of 8 out of 10 for taste and 7.5 out of 10 for color, attributed to the natural pigments from tomato waste. This innovative approach highlights the potential of tomato by-products in creating nutritionally enhanced gluten-free foods. Future research should explore the long-term stability of these bioactive compounds in finished products and evaluate the scalability of this process for industrial applications. Integrating such sustainable practices can significantly contribute to waste reduction and the development of functional foods.

Keywords: tomato waste, circular economy, bioactive compounds, sustainability, health benefits

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Authors: Mark Morgan, Christine Li, Shuangyu Xu, Jenny McCarty

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The National Wild and Scenic Rivers System was created by the U.S. Congress in 1968 (Public Law 90-542; 16 U.S.C. 1271 et seq.) to preserve outstanding natural, cultural, and recreational values of some U.S. rivers in a free-flowing condition for the enjoyment of present and future generations. This Act is notable for safeguarding the special character of these rivers while supporting management action that encourages public participation for co-creating river protection goals and strategies. This is not an easy task. To meet the challenges of modern ecosystem management, federal resource agencies must address many legal, environmental, economic, political, and social issues. The U.S. Forest Service manages a 44-mile section of the Eleven Point National Scenic River (EPR) in southern Missouri, mainly for outdoor recreation purposes. About half of the acreage is in private lands, while the remainder flows through the Mark Twain National Forest. Private land along the river is managed by scenic easements to ensure protection of scenic values and natural resources, without public access. A portion of the EPR lies adjacent to a 16,500-acre tract known as the Irish Wilderness. The spring-fed river has steep bluffs, deep pools, clear water, and a slow current, making it an ideal setting for outdoor enthusiasts. A 10-month visitor study was conducted at five access points along the EPR during 2019 so the US Forest Service could update their river management plan. A mail-back survey was administered to 560 on-site visitors, yielding a response rate of 53%. Although different types of visitors use the EPR, boating and fishing were the predominant forms of outdoor recreation. Some river use was from locals, but other visitors came from farther away. Formulating unbiased policies for outdoor recreation is difficult because managers must assign relative values to recreational activities and travel distance. Because policymaking is a subjective process, management decisions can affect user groups in different ways (i.e., boaters vs. fishers; proximate vs. distal visitors), as seen through a GIS analysis.

Keywords: activity selection, forest recreation, policy, travel distance

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Authors: Molakala Mourya Vardhan Reddy, Kandimala Revanth, Koduru Sumanth, Beena B. M.

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Emergency response and recovery operations are severely hampered by natural catastrophes, especially floods. Understanding post-flood scenarios is essential to disaster management because it facilitates quick evaluation and decision-making. To this end, we introduce FloodNet, a brand-new high-resolution aerial picture collection created especially for comprehending post-flood scenes. A varied collection of excellent aerial photos taken during and after flood occurrences make up FloodNet, which offers comprehensive representations of flooded landscapes, damaged infrastructure, and changed topographies. The dataset provides a thorough resource for training and assessing computer vision models designed to handle the complexity of post-flood scenarios, including a variety of environmental conditions and geographic regions. Pixel-level semantic segmentation masks are used to label the pictures in FloodNet, allowing for a more detailed examination of flood-related characteristics, including debris, water bodies, and damaged structures. Furthermore, temporal and positional metadata improve the dataset's usefulness for longitudinal research and spatiotemporal analysis. For activities like flood extent mapping, damage assessment, and infrastructure recovery projection, we provide baseline standards and evaluation metrics to promote research and development in the field of post-flood scene comprehension. By integrating FloodNet into machine learning pipelines, it will be easier to create reliable algorithms that will help politicians, urban planners, and first responders make choices both before and after floods. The goal of the FloodNet dataset is to support advances in computer vision, remote sensing, and disaster response technologies by providing a useful resource for researchers. FloodNet helps to create creative solutions for boosting communities' resilience in the face of natural catastrophes by tackling the particular problems presented by post-flood situations.

Keywords: image classification, segmentation, computer vision, nature disaster, unmanned arial vehicle(UAV), machine learning.

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Authors: Esmael Makarian, Ayub Elyasi, Fatemeh Saberi, Olusegun Stanley Tomomewo

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Geothermal reservoirs (GTRs) have garnered global recognition as a sustainable energy source. The Thermo-Hydro-Mechanical-Chemical (THMC) integration coupling proves to be a practical and effective method for optimizing production in GTRs. The study outcomes demonstrate that THMC coupling serves as a versatile and valuable tool, offering in-depth insights into GTRs and enhancing their operational efficiency. This is achieved through temperature analysis and pressure changes and their impacts on mechanical properties, structural integrity, fracture aperture, permeability, and heat extraction efficiency. Moreover, THMC coupling facilitates potential benefits assessment and risks associated with different geothermal technologies, considering the complex thermal, hydraulic, mechanical, and chemical interactions within the reservoirs. However, THMC-coupling utilization in GTRs presents a multitude of challenges. These challenges include accurately modeling and predicting behavior due to the interconnected nature of processes, limited data availability leading to uncertainties, induced seismic events risks to nearby communities, scaling and mineral deposition reducing operational efficiency, and reservoirs' long-term sustainability. In addition, material degradation, environmental impacts, technical challenges in monitoring and control, accurate assessment of resource potential, and regulatory and social acceptance further complicate geothermal projects. Addressing these multifaceted challenges is crucial for successful geothermal energy resources sustainable utilization. This paper aims to illuminate the challenges and opportunities associated with THMC coupling in enhanced geothermal systems. Practical solutions and strategies for mitigating these challenges are discussed, emphasizing the need for interdisciplinary approaches, improved data collection and modeling techniques, and advanced monitoring and control systems. Overcoming these challenges is imperative for unlocking the full potential of geothermal energy making a substantial contribution to the global energy transition and sustainable development.

Keywords: geothermal reservoirs, THMC coupling, interdisciplinary approaches, challenges and opportunities, sustainable utilization

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Authors: May Newisar, Richard Kingston, Philip Black

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Heritage-led regeneration developments have been considered as one of the cornerstones of the economic and social revival of historic towns and cities in the UK. However, this approach has proved its deficiency within the development of Liverpool World Heritage site. This is due to the conflict between sustaining the tangible and intangible values as well as achieving the aimed economic developments. Accordingly, the development of such areas is influenced by a top-down approach which considers heritage as consumable experience and urban regeneration as the economic development for it. This neglects the heritage sites characteristics and values as well as the design criteria for public open spaces that overlap with the heritage sites. Currently, knowledge regarding the relationship between the physical built environment of the heritage sites including the intangible values and the design development of the public open spaces is limited. Public open spaces have been studied from different perspectives such as increasing walkability, a source of social cohesion, provide a good quality of life as well as understanding users’ perception. While heritage sites have been discussed heavily on how to maintain the physical environment, understanding the courses of threats and how to be protected. In addition to users’ experiences and motivations of visiting such areas. Furthermore, new approaches tried to overcome the gap such as the historic urban landscape approach. This approach is focusing on the entire human environment with all its tangible and intangible qualities. However, this research aims to understand the relationship between the heritage sites and public open spaces and how the overlap of the design and development of both could be used as a quality to enhance the heritage sites and improve users’ experience. A meaning-making approach will be used in order to understand and articulate how the development of Liverpool World Heritage site and its value could influence and shape the design of public open space Pier Head in order to attract a different level of tourists to be used as a tool for economic development. Consequently, this will help in bridging the gap between the planning and conservation areas’ policies through an understanding of how flexible is the system in order to adopt alternative approaches for the design and development strategies for those areas.

Keywords: historic urban landscape, environmental psychology, urban governance, identity

Procedia PDF Downloads 131

Authors: Lana Migla

Abstract:

Phase change materials (PCMs) have an important role in improving the efficiency of thermal heat storage. As these materials are characterized by low thermal conductivity, it is necessary to develop heat transfer techniques to improve their thermophysical properties. This scientific article focuses on the geometrical configurations of encapsulated PCM containers and the impact of designs to improve the performance of the solar thermal cooling system. The literature review showed that in-depth research is being conducted on different methods of improving the efficiency of PCM heat transfer, which is the main design task for the containers. Techniques such as microencapsulated PCMs, adding fins and different combinations of fins and nanoparticles are used. The use of graphite, metal foam and doping of high photothermal materials is also being studied. To determine most efficient container configuration, the article looks at different designs of PCM containers with fins for the storage tank. This paper experimentally investigates the effect of the encapsulation design on the performance of a lab-scale thermal energy storage tank. The development of optimized energy storage with integrated phase change material containers reduces auxiliary heater energy consumption, increases the COP of the solar cooling system, and reduces the environmental impact of the cooling system. The review shows that in the cylindrical construction, the ratio between the radius of shell and tube is significant, which means this ratio is the main issue to enhance transfer efficiency and to increase the value of stored heat. Therefore, three cylindrical tube containers with different radiuses 20mm, 35mm, 50mm filled with commercial phase change material were tested. The results show that using a smaller radius achieved a higher power, leading to a reduction in the charging and discharging time. The three fins were added to the selected cylindrical tube to determine their effects on heat exchanging efficiency. The observed optimized performance given by the fin’s arrangement achieved a 40% reduction of PCM's melting time compared to the heat exchanging without fins. The exact dimensions of the PCM containers and fins placements will be presented on-site.

Keywords: energy performance, PCM containers, solar thermal cooling, storage tank

Procedia PDF Downloads 140

Authors: Chiao-Yi Chen, Dung-Ying Lin

Abstract:

With the growing awareness of environmental protection and the implementation of government carbon reduction policies, the number of electric vehicles (EVs) has rapidly increased, leading to a surge in charging demand and imposing significant challenges on the existing power grid’s capacity. Traditional urban power grid planning has not adequately accounted for the additional load generated by EV charging, which often strains the infrastructure. This study aims to optimize grid operation and load management by dynamically adjusting EV charging prices based on real-time electricity supply and demand, leveraging consumer demand elasticity to enhance system efficiency. This study uniquely addresses the intricate interplay between urban traffic patterns and power grid dynamics in the context of electric vehicle (EV) adoption. By integrating Hsinchu City's road network with the IEEE 33-bus system, the research creates a comprehensive model that captures both the spatial and temporal aspects of EV charging demand. This approach allows for a nuanced analysis of how traffic flow directly influences the load distribution across the power grid. The strategic placement of charging stations at key nodes within the IEEE 33-bus system, informed by actual road traffic data, enables a realistic simulation of the dynamic relationship between vehicle movement and energy consumption. This integration of transportation and energy systems provides a holistic view of the challenges and opportunities in urban EV infrastructure planning, highlighting the critical need for solutions that can adapt to the ever-changing interplay between traffic patterns and grid capacity. The proposed dynamic pricing strategy effectively reduces peak charging loads, enhances the operational efficiency of charging stations, and maximizes operator profits, all while ensuring grid stability. These findings provide practical insights and a valuable framework for optimizing EV charging infrastructure and policies in future smart cities, contributing to more resilient and sustainable urban energy systems.

Keywords: dynamic pricing, demand elasticity, EV charging, grid load balancing, optimization

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Authors: Olanrewaju Kafayat, O., Salman Kabir, K.

Abstract:

The role of organic agriculture in providing food and income is now gaining wider recognition (Van Elzakker et al 2007). The increasing public concerns about food safety issues on the use of fertilizers, pesticide residues, growth hormones, GM organisms, and increasing awareness of environmental quality issues have led to an expanding demand for environmentally friendly products (Thompson, 1998; Rimal et al., 2005). As a result national governments are concerned about diet and health, and there has been renewed recognition of the role of public policy in promoting healthy diets, thus to provide healthier, safer, more confident citizens (Poole et al., 2007), With these benefits, a study into organic vegetables is very vital to all the major stakeholders. This study analyzed the willingness of consumers to pay for organic vegetables in Oyo state, Nigeria. Primary data was collected with the aid of structured questionnaire administered to 168 respondents. These were selected using multistage random sampling. The first stage involved the selection two (2) ADP zones out of the three (3) ADP zones in Oyo state, The second stage involved the random selection of two (2) local government areas each out of the two (2) ADP zones which are; Ibadan South West and Ogbomoso North and random selection of 4 wards each from the local government areas. The third stage involved random selection of 42 household each from of the local government areas. Descriptive statistics, the principal component analysis, and the logistic regression were used to analyze the data. Results showed 55 percent of the respondents were female while 80 percent were  50 years. 74 percent of the respondents agreed that organic vegetables are of better quality. 31 percent of the respondents were aware of organic vegetables as against 69 percent who were not aware. From the logistic model, educational attainment, amount spent on organic vegetables monthly, better quality of organic vegetables and accessibility to organic vegetables were significant and had a positive relationship on willingness to pay for organic vegetable. The variables that were significant and had a negative relationship with WTP are less attractiveness of organic vegetables and household size of the respondents. This study concludes that consumers with higher level of education were more likely to be aware and willing to pay for organic vegetables than those with low levels of education, the study therefore recommends creation of awareness on the relevance of consuming organic vegetables through effective marketing and educational campaigns.

Keywords: consumers awareness, willingness to pay, organic vegetables, Oyo State

Procedia PDF Downloads 271

Authors: Mine Koyaz, M. Cem Altun

Abstract:

Selection of the materials satisfying the expected performances is significantly important for any design. Today, with the constantly evolving and developing technologies, the material options are so wide that the necessity of the use of some support tools in the selection process is arising. Therefore, as a sub process of building element design, a systematic material selection tool is developed, that defines four main steps of the material selection; definition, research, comparison and decision. The main purpose of the tool is being an educational instrument that would show a methodic way of material selection in architectural detailing for the use of architecture students. The tool predefines the possible uses of various material databases and other sources of information on material properties. Hence, it is to be used as a guidance for designers, especially with a limited material knowledge and experience. The material selection tool not only embraces technical properties of materials related with building elements’ functional requirements, but also its sensual properties related with the identity of design and its environmental impacts with respect to the sustainability of the design. The method followed in the development of the tool has two main sections; first the examination and application of the existing methods and second the development of trial versions and their applications. Within the scope of the existing methods; design support tools, methodic approaches for the building element design and material selection process, material properties, material databases, methodic approaches for the decision making process are examined. The existing methods are applied by architecture students and newly graduate architects through different design problems. With respect to the results of these applications, strong and weak sides of the existing material selection tools are presented. A main flow chart of the material selection tool has been developed with the objective to apply the strong aspects of the existing methods and develop their weak sides. Through different stages, a different aspect of the material selection process is investigated and the tool took its final form. Systematic material selection tool, within the building element design process, guides the users with a minimum background information, to practically and accurately determine the ideal material that is to be chosen, satisfying the needs of their design. The tool has a flexible structure that answers different needs of different designs and designers. The trial version issued in this paper shows one of the paths that could be followed and illustrates its application over a design problem.

Keywords: architectural education, building element design, material selection tool, systematic approach

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Authors: Ashraf M. Khalifa, Hwat Bing So, Greg Maddocks

Abstract:

Changes to the mining environmental approvals process in Queensland have been rolled out under the MERFP Act (2018). This includes requirements for a Progressive Rehabilitation and Closure Plan (PRC Plan). Key considerations of the landform design report within the PRC Plan must include: (i) identification of materials available for landform rehabilitation, including their ability to achieve the required landform design outcomes, (ii) erosion assessments to determine landform heights, gradients, profiles, and material placement, (iii) slope profile design considering the interactions between soil erodibility, rainfall erosivity, landform height, gradient, and vegetation cover to identify acceptable erosion rates over a long-term average, (iv) an analysis of future stability based on the factors described above e.g., erosion and /or landform evolution modelling. ACARP funded an extensive and thorough erosion assessment program using rainfall simulators from 1998 to 2010. The ACARP program included laboratory assessment of 35 soil and spoil samples from 16 coal mines and samples from a gold mine in Queensland using 3 x 0.8 m laboratory rainfall simulator. The reliability of the laboratory rainfall simulator was verified through field measurements using larger flumes 20 x 5 meters and catchment scale measurements at three sites (3 different catchments, average area of 2.5 ha each). Soil cover systems are a primary component of a constructed mine landform. The primary functions of a soil cover system are to sustain vegetation and limit the infiltration of water and oxygen into underlying reactive mine waste. If the external surface of the landform erodes, the functions of the cover system cannot be maintained, and the cover system will most likely fail. Assessing a constructed landform’s potential ‘long-term’ erosion stability requires defensible erosion rate thresholds below which rehabilitation landform designs are considered acceptably erosion-resistant or ‘stable’. The process used to quantify erosion rates using rainfall simulators (flumes) to measure rill and inter-rill erosion on bulk samples under laboratory conditions or on in-situ material under field conditions will be explained.

Keywords: open-cut, mining, erosion, rainfall simulator

Procedia PDF Downloads 101

Authors: Josué Alfredo Tomas Machaca Fajardo, Jhon Elvis Chahua Janampa, Pedro Rau Lavado

Abstract:

A flood vulnerability index was developed for the Piura River watershed in northern Peru using Principal Component Analysis (PCA) to assess flood risk. The official methodology to assess risk from natural hazards in Peru was introduced in 1980 and proved effective for aiding complex decision-making. This method relies in part on decision-makers defining subjective correlations between variables to identify high-risk areas. While risk identification and ensuing response activities benefit from a qualitative understanding of influences, this method does not take advantage of the advent of national and international data collection efforts, which can supplement our understanding of risk. Furthermore, this method does not take advantage of broadly applied statistical methods such as PCA, which highlight central indicators of vulnerability. Nowadays, information processing is much faster and allows for more objective decision-making tools, such as PCA. The approach presented here develops a tool to improve the current flood risk assessment in the Peruvian basin. Hence, the spatial analysis of the census and other datasets provides a better understanding of the current land occupation and a basin-wide distribution of services and human populations, a necessary step toward ultimately reducing flood risk in Peru. PCA allows the simplification of a large number of variables into a few factors regarding social, economic, physical and environmental dimensions of vulnerability. There is a correlation between the location of people and the water availability mainly found in rivers. For this reason, a comprehensive vision of the population location around the river basin is necessary to establish flood prevention policies. The grouping of 5x5 km gridded areas allows the spatial analysis of flood risk rather than assessing political divisions of the territory. The index was applied to the Peruvian region of Piura, where several flood events occurred in recent past years, being one of the most affected regions during the ENSO events in Peru. The analysis evidenced inequalities for the access to basic services, such as water, electricity, internet and sewage, between rural and urban areas.

Keywords: assess risk, flood risk, indicators of vulnerability, principal component analysis

Procedia PDF Downloads 186

Authors: Rajesh Karki, Safal Bhattarai, Saket Adhikari

Abstract:

Reliable and economic operation of power systems are becoming extremely challenging with large scale integration of renewable energy sources due to the intermittency and uncertainty associated with renewable power generation. It is, therefore, important to make a quantitative risk assessment and explore the potential resources to mitigate such risks. Probabilistic models for different energy storage systems (ESS), such as the flywheel energy storage system (FESS) and the compressed air energy storage (CAES) incorporating specific charge/discharge performance and failure characteristics suitable for probabilistic risk assessment in power system operation and planning are presented in this paper. The proposed methodology used in FESS modelling offers flexibility to accommodate different configurations of plant topology. It is perceived that CAES has a high potential for grid-scale application, and a hybrid approach is proposed, which embeds a Monte-Carlo simulation (MCS) method in an analytical technique to develop a suitable reliability model of the CAES. The proposed ESS models are applied to a test system to investigate the economic and reliability benefits of the energy storage technologies in system operation and planning, as well as to assess their contributions in facilitating wind integration during different operating scenarios. A comparative study considering various storage system topologies are also presented. The impacts of failure rates of the critical components of ESS on the expected state of charge (SOC) and the performance of the different types of ESS during operation are illustrated with selected studies on the test system. The paper also applies the proposed models on the test system to investigate the economic and reliability benefits of the different ESS technologies and to evaluate their contributions in facilitating wind integration during different operating scenarios and system configurations. The conclusions drawn from the study results provide valuable information to help policymakers, system planners, and operators in arriving at effective and efficient policies, investment decisions, and operating strategies for planning and operation of power systems with large penetrations of renewable energy sources.

Keywords: flywheel energy storage, compressed air energy storage, power system reliability, renewable energy, system planning, system operation

Procedia PDF Downloads 130

Authors: Shaokun Ge, Bart Merci, Fubao Zhou, Gao Liu, Ya Ni

Abstract:

This study investigates the thermal response of main cables and suspenders in suspension bridges subjected to vehicle fires, integrating large-scale gasoline pool fire experiments with numerical simulations. Focusing on a suspension bridge in China, the research examines the impact of wind speed, pool size, and lane position on flame dynamics and temperature distribution along the cables. The results indicate that higher wind speeds and larger pool sizes markedly increase the mass burning rate, causing flame deflection and non-uniform temperature distribution along the cables. Under a wind speed of 1.56 m/s, maximum temperatures reached approximately 960 ℃ near the base in emergency lane fires and 909 ℃ at 1.6 m height for slow lane fires, underscoring the heightened thermal risk from emergency lane fires. The study recommends a zoning strategy for cable fire protection, suggesting a 0-12.8 m protection zone with a target temperature of 1000 ℃ and a 12.8-20.8 m zone with a target temperature of 700 ℃, both with a 90-minute fire resistance. This approach, based on precise temperature distribution data from experimental and simulation results, provides a vital reference for the fire protection design of suspension bridge cables. Understanding cable temperature response during vehicle fires is crucial for developing fire protection systems, as it dictates necessary structural protection, fire resistance duration, and maximum temperatures for mitigation. Challenges of controlling environmental wind in large-scale fire tests are also addressed, along with a call for further research on fire behavior mechanisms and structural temperature response in cable-supported bridges under varying wind conditions. Conclusively, the proposed zoning strategy enhances the theoretical understanding of near-field temperature response in bridge fires, contributing significantly to the field by supporting the design of passive fire protection systems for bridge cables, safeguarding their integrity under extreme fire conditions.

Keywords: bridge fire, temperature response, large-scale experiment, numerical simulations, fire protection

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Authors: Charbel Aoun, Loic Lagadec

Abstract:

A Sensor Network (SN) is considered as an operation of two phases: (1) the observation/measuring, which means the accumulation of the gathered data at each sensor node; (2) transferring the collected data to some processing center (e.g., Fusion Servers) within the SN. Therefore, an underwater sensor network can be defined as a sensor network deployed underwater that monitors underwater activity. The deployed sensors, such as Hydrophones, are responsible for registering underwater activity and transferring it to more advanced components. The process of data exchange between the aforementioned components perfectly defines the Marine Observatory (MO) concept which provides information on ocean state, phenomena and processes. The first step towards the implementation of this concept is defining the environmental constraints and the required tools and components (Marine Cables, Smart Sensors, Data Fusion Server, etc). The logical and physical components that are used in these observatories perform some critical functions such as the localization of underwater moving objects. These functions can be orchestrated with other services (e.g. military or civilian reaction). In this paper, we present an extension to our MO meta-model that is used to generate a design tool (ArchiMO). We propose new constraints to be taken into consideration at design time. We illustrate our proposal with an example from the MO domain. Additionally, we generate the corresponding simulation code using our self-developed domain-specific model compiler. On the one hand, this illustrates our approach in relying on Enterprise Architecture (EA) framework that respects: multiple views, perspectives of stakeholders, and domain specificity. On the other hand, it helps reducing both complexity and time spent in design activity, while preventing from design modeling errors during porting this activity in the MO domain. As conclusion, this work aims to demonstrate that we can improve the design activity of complex system based on the use of MDE technologies and a domain-specific modeling language with the associated tooling. The major improvement is to provide an early validation step via models and simulation approach to consolidate the system design.

Keywords: smart sensors, data fusion, distributed fusion architecture, sensor networks, domain specific modeling language, enterprise architecture, underwater moving object, localization, marine observatory, NS-3, IMS

Procedia PDF Downloads 177

Authors: Ursula D. C. Resende, Yan G. Santos, Lucas M. de O. Andrade

Abstract:

The recent and fast development of the internet, wireless, telecommunication technologies and low-power electronic devices has led to an expressive amount of electromagnetic energy available in the environment and the smart applications technology expansion. These applications have been used in the Internet of Things devices, 4G and 5G solutions. The main feature of this technology is the use of the wireless sensor. Although these sensors are low-power loads, their use imposes huge challenges in terms of an efficient and reliable way for power supply in order to avoid the traditional battery. The radio frequency based energy harvesting technology is especially suitable to wireless power sensors by using a rectenna since it can be completely integrated into the distributed hosting sensors structure, reducing its cost, maintenance and environmental impact. The rectenna is an equipment composed of an antenna and a rectifier circuit. The antenna function is to collect as much radio frequency radiation as possible and transfer it to the rectifier, which is a nonlinear circuit, that converts the very low input radio frequency energy into direct current voltage. In this work, a set of rectennas, mounted on a paper substrate, which can be used for the inner coating of buildings and simultaneously harvest electromagnetic energy from the environment, is proposed. Each proposed individual rectenna is composed of a 2.45 GHz patch antenna and a voltage doubler rectifier circuit, built in the same paper substrate. The antenna contains a rectangular radiator element and a microstrip transmission line that was projected and optimized by using the Computer Simulation Software (CST) in order to obtain values of S11 parameter below -10 dB in 2.45 GHz. In order to increase the amount of harvested power, eight individual rectennas, incorporating metamaterial cells, were connected in parallel forming a system, denominated Electromagnetic Wall (EW). In order to evaluate the EW performance, it was positioned at a variable distance from the internet router, and a 27 kΩ resistive load was fed. The results obtained showed that if more than one rectenna is associated in parallel, enough power level can be achieved in order to feed very low consumption sensors. The 0.12 m2 EW proposed in this work was able to harvest 0.6 mW from the environment. It also observed that the use of metamaterial structures provide an expressive growth in the amount of electromagnetic energy harvested, which was increased from 0. 2mW to 0.6 mW.

Keywords: electromagnetic energy harvesting, metamaterial, rectenna, rectifier circuit

Procedia PDF Downloads 167

Authors: Richard Ren

Abstract:

Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

Procedia PDF Downloads 127

Authors: Anindita Patra, Prasad K. Bhaskaran

Abstract:

The atmosphere-ocean is a dynamically linked system that influences the exchange of energy, mass, and gas at the air-sea interface. The exchange of energy takes place in the form of sensible heat, latent heat, and momentum commonly referred to as fluxes along the atmosphere-ocean boundary. The large scale features such as El Nino and Southern Oscillation (ENSO) is a classic example on the interaction mechanism that occurs along the air-sea interface that deals with the inter-annual variability of the Earth’s Climate System. Most importantly the ocean and atmosphere as a coupled system acts in tandem thereby maintaining the energy balance of the climate system, a manifestation of the coupled air-sea interaction process. The present work is an attempt to understand the long-term variability in atmospheric parameters (from surface to upper levels) and investigate their role in influencing the surface ocean variables. More specifically the influence of atmospheric circulation and its variability influencing the mean Sea Level Pressure (SLP) has been explored. The study reports on a critical examination of both ocean-atmosphere parameters during a monsoon season over the head Bay of Bengal region. A trend analysis has been carried out for several atmospheric parameters such as the air temperature, geo-potential height, and omega (vertical velocity) for different vertical levels in the atmosphere (from surface to the troposphere) covering a period from 1992 to 2012. The Reanalysis 2 dataset from the National Centers for Environmental Prediction-Department of Energy (NCEP-DOE) was used in this study. The study signifies that the variability in air temperature and omega corroborates with the variation noticed in geo-potential height. Further, the study advocates that for the lower atmosphere the geo-potential heights depict a typical east-west contrast exhibiting a zonal dipole behavior over the study domain. In addition, the study clearly brings to light that the variations over different levels in the atmosphere plays a pivotal role in supporting the observed dipole pattern as clearly evidenced from the trends in SLP, associated surface wind speed and significant wave height over the study domain.

Keywords: air temperature, geopotential height, head Bay of Bengal, long-term variability, NCEP reanalysis 2, omega, wind-waves

Procedia PDF Downloads 225

Authors: Anjali G. Pillai, S. Chadrakaran

Abstract:

The extensive amount of sludge generated throughout the world, as a part of water treatment works, have caused various social and economic issues, such as a demand on landfill spaces, increase in environmental pollution and raising the waste management cost. With growing social awareness about toxic incinerator emissions and the increasing concern over the disposal of sludge on the agricultural land, the recovery of sewage sludge as a building and construction raw material can be considered as an innovative approach to tackle the sludge disposal problem. The proposed work aims at studying the recycling ability of the sludge, generated from the water treatment process, by incorporating it into the fired clay brick units. The work involves initial study of the geotechnical characteristics of the brick-clay and the sludge. Chemical compatibility of both the materials will be analyzed by X-ray fluorescence technique. The variation in the strength aspects with varying proportions of sludge i.e. 10%, 20%, 30% and 40% in the sludge-clay mix will also be determined by the proctor density test. Based on the optimum moisture content, the sludge-clay bricks will be manufactured in a brick manufacturing plant and the modified brick units will be tested to determine the variation in compressive strength, bulk density, firing shrinkage, shrinkage loss and initial water absorption rate with respect to the conventional clay bricks. The results will be compared with the specifications given in Indian Standards to arrive at the potential use of the new bricks. The durability aspect will be studied by conducting the leachate analysis test using atomic adsorption spectrometry. The lightweight characteristics of the sludge modified bricks will be ascertained with the scanning electron microscope technique which will be indicative of the variation in pore structure with the increase in sludge content within the bricks. The work will determine the suitable proportion of the sludge – clay mix in the brick which can then be effectively implemented. The feasibility aspect of the work will be determined for commercial production of the units. The work involves providing a strategy for conversion of waste to resource. Moreover, it provides an alternative solution to the problem of growing scarcity of brick-clay for the manufacturing of fired clay bricks.

Keywords: eco-bricks, green construction material, sludge amended bricks, sludge disposal, waste management

Procedia PDF Downloads 305