Search results for: environmental pOllution

Authors: Wicleffe Musingarimi

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Currently, the rising energy demand as a result of an increase in the world’s population and the sustainable use of abundant natural resources are key issues facing many developed and developing countries including South Africa. Most of the energy to meet this growing demand comes from fossil fuel. Use of fossil fuels has led to environmental problems such air pollution, climate change, and acid rain. In addition, fossil fuels are facing continual depletion, which has led to the rise in oil prices, leading to the global economies melt down. Hence development of alternative clean and renewable energy source is a global priority. Renewable biomass from forest products, agricultural crops, and residues, as well as animal and municipal waste are promising alternatives. South Africa is one of the leading wine producers in the world; leading to a lot of winery waste (ww) being produced which can be used in anaerobic digestion (AD) to produce biogas. Biogas was produced from batch anaerobic digestion of zebra manure (zm) and batch anaerobic co-digestion of winery waste (ww) and zebra manure through water displacement. The batch digester with slurry of winery waste and zebra manure in the weight ratio of 1:2 was operated in a 1L container at 37°C for 30days. Co-digestion of winery waste and zebra manure produced higher amount of biogas as compared to zebra manure alone and winery waste alone. No biogas was produced by batch anaerobic digestion of winery waste alone. Chemical analysis of C/N ratio and total solids (TS) of zebra manure was 21.89 and 25.2 respectively. These values of C/N ratio and TS were quite high compared to values of other studied manures. Zebra manure also revealed unusually high concentration of Fe reaching 3600pm compared to other studies of manure. PCR with communal DNA of the digestate gave a positive hit for the presence of archaea species using standard archea primers; suggesting the presence of methanogens. Methanogens are key microbes in the production of biogas. Therefore, this study demonstrated the potential of zebra manure as an inoculum in the production of biogas.

Keywords: anaerobic digestion, biogas, co-digestion, methanogens

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Authors: Saúl Rivero, Estefanya Marín, Katherine Bolaño, Elena Urán, Juan Yepes, Andrés Cossio

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Medellín is the Colombian city with the best public transport systems in the country, which is made up of two metro lines, five metrocables, two BRT-type bus lines, and a tram. But despite the above, the Aburrá Valley, the area in which the city is located, has about 3000 km of roads, which for the existing population of 3.2 million inhabitants, gives an indicator of 900 meters of road per 1000 inhabitants, which is lower than the country's average, which is approximately 3900 meters. In addition, given that in Medellín, there is approximately one vehicle for every three inhabitants, the problems of congestion and environmental pollution have worsened over the years. In this sense, due to the limitations of physical space, the low public investment in road infrastructure, it is necessary to opt for mobility alternatives according to the above. Among the options for the city, there is what is known as micromobility. Micromobility is understood to be those small and light means of transport that are used for short distances, that use electrical energy, such as skateboards and bicycles. Taking into account the above, in this work, the current state and future of micromobility in the city of Medellín were analyzed, carrying out a prospective analysis, supported by a PEST analysis, but also of the crossed impact matrices; of influence and dependence; and the technique of the actor's game. The analysis was carried out for two future scenarios: one normal and one optimistic. Result of the analysis, it was determined that micromobility as an alternative social practice to mobility in the city of Medellín has favorable conditions since the local government has adopted strategies such as the Metropolitan Bicycle Master Plan of Valle de Aburrá and the plan " Bicycle paths in the city: more public spaces for life,” where a projection of 400 kilometers of bicycle paths was estimated by the year 2030, as for that same year it is expected that 10% of all trips in the region will be in bike mode. The total trip indicator is an achievable goal, while that of the number of kilometers of bike paths would be close to being met.

Keywords: electric vehicles, micromobilty, public transport, sustainable transport

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Authors: Houmame Benbouali

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The risks, in general, exist in any project; one can hardly carry out a project without taking risks. The hydraulic works are rather complex projects in their design, realization and exploitation, and are often subjected at the multiple risks being able to influence with their good performance, and can have an negative impact on their environment. The present study was carried out to quote the impacts caused by purification plant STEP Chlef on the environment, it aims has studies the environmental impacts during construction and when designing this STEP, it is divided into two parts: The first part results from a research task bibliographer which contain three chapters (-cleansing of water worn-general information on water worn-proceed of purification of waste water). The second part is an experimental part which is divided into four chapters (detailed state initial-description of the station of purification-evaluation of the impacts of the project analyzes measurements and recommendations).

Keywords: treatment plant, waste water, waste water treatment, environmental impact

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Authors: Adem Öğüt, M. Tahir Demirsel

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Rapid changes and developments today, besides the opportunities and facilities they offer to the organization, may also be a source of danger and difficulties due to the uncertainty. In order to take advantage of opportunities and to take the necessary measures against possible uncertainties, organizations must always follow the changes and developments that occur in the business environment and develop flexible structures and strategies for the alternative cases. Perceived environmental uncertainty is an outcome of managers’ perceptions of the combined complexity, instability and unpredictability in the organizational environment. An environment that is perceived to be complex, changing rapidly, and difficult to predict creates high levels of uncertainty about the appropriate organizational responses to external circumstances. In an uncertain and complex environment, organizations experiencing cutthroat competition may be successful by developing their corporate entrepreneurial ability. Corporate entrepreneurship is a process that includes many elements such as innovation, creating new business, renewal, risk-taking and being predictive. Successful corporate entrepreneurship is a critical factor which has a significant contribution to gain a sustainable competitive advantage, to renew the organization and to adapt the environment. In this context, the objective of this study is to investigate the effect of perceived environmental uncertainty of managers on corporate entrepreneurship performance. The research was conducted on 222 business executives in one of the major industrial zones of Turkey, Konya Organized Industrial Zone (KOS). According to the results, it has been observed that there is a positive statistically significant relationship between perceived environmental uncertainty and corporate entrepreneurial activities.

Keywords: corporate entrepreneurship, entrepreneurship, industrial zone, perceived environmental uncertainty, uncertainty

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Authors: Sungwoo Park

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The paper attempts to investigate the correlation between climate change and migration that has caused violent disputes in some regions of the world. Recently, NGOs and educational institutions have proposed claims that migratory patterns and violent uprisings are intertwined with climate change. Thus, the paper is primarily concerned with collecting evidences provided from scholars, validating this significant connection between climate change and migration, and evaluating and suggesting current and future research approaches respectively to enhance the acknowledgment and protection of environmental refugees. In order to examine the linkage of environmental migration, primary sources, such as political speeches, and secondary sources like theses from environmental policy analysts, books, and reports are used. More specifically, the investigation focuses on an civil war in Syria to draw a connection between environmental migration and violent dispute that threatens the global security. The examination undertaken specifically analyzes examples where forced migration occurred due to climate change. In Bangladesh, Pakistan, and Kiribati, residents have been at risk of fleeing their countries because of abnormal climate patterns, such as the rise of sea level or an excessive heat stress. As the brutal uprising in Syria has proven that climate change can pose a significant threat to global security, correlation between climate change and migration is surely worth delving into.

Keywords: climate change, climate migration, global security, refugee crisis

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Authors: Huong Nguyen Thi Thanh, Van Mai Thi Khanh

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For around the world, payments for environmental services have been implemented since the late 1970s in Europe and North America; then, it was spread to Latin America, Asia, Africa, and finally Oceania in 2008. In Vietnam, payments for environmental services are an interesting issue recently with the forest as the main focus and therefore known as the program on payment for forest environmental services (PFES). PFES was piloted in Lam Dong and Son La in 2008 and has been widely applied in many provinces after 2010. PFES is in the orientation for the socialization of national forest protection in Vietnam and has made great strides in the last decade. By using the primary data and secondary data simultaneously, the paper clarifies two cases of implementing PFES in the Vietnam North Central area with the different mechanisms of payment. In the first case at Phu Loc district (Thua Thien Hue province), PFES is an indirect method by a water supply company via the Forest Protection and Development Fund. In the second one at Phong Nha – Ke Bang National Park (Quang Binh Province), tourism companies are the direct payers to forest owners. The paper describes the PFES implementation process at each site, clarifies the payment mechanism, and models the relationship between stakeholders in PFES implementation. Based on the current status of PFES sites, the paper compares and analyzes the advantages and disadvantages of the two payment methods. Finally, the paper proposes recommendations to improve the existing shortcomings in each payment mechanism.

Keywords: advantages and disadvantages, forest environmental services, forest protection, payment mechanism

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Authors: Nesrine Frifita

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In recent years, serious interest in underground sources has led to more intensive studies of depth, thickness, geometry and properties of aquifers. Geophysical method is the common technique used in discovering the subsurface. However, determining the exact location of groundwater in subsurface layers is one of problems that needs to be resolved. While the biggest problem is the quality of the groundwater which suffers from pollution risk especially with water shortage in arid regions under a remarkable climate change. The present study was conducted using electrical resistivity tomography at Jeffara coastal area in Southeast Tunisia to image the potential shallow aquifer and studying their physical properties. The purpose of this study is to understand the characteristics and depth of the Smar aquifer. Therefore, it can be used as a reference in groundwater drilling in order to guide the farmers and to improve the living of the inhabitants of nearby cities. The use of the Winner-Schlumberger array for data acquisition is suitable to obtain a deeper profile in areas with homogeneous layers. For that, six electrical resistivity profiles were carried out in Smar watershed using 72 electrodes with 4 and 5 m spacing. The resistivity measurements were carefully interpreted by a least-square inversion technique using the RES2DINV program. Findings show that the Smar aquifer has about 31 m thickness and it extends to 36.5 m depth in the downstream area of Oued Smar. The defined depth and geometry of Smar aquifer indicate that the sedimentary cover thins toward the coast, and the Smar shallow aquifer becomes deeper toward the West. While the resistivity values show a significant contrast even reaching < 1 Ωm in ERT1, this resistivity value can be related to the saline water that foretells a risk of pollution and bad groundwater quality. The ERT1 geoelectrical model defines an unsaturated zone, while under ERT3 site, the geoelectrical model presents a saturated zone, which reflect a low resistivity values indicate the locally surface water coming from the nearby Office of the National Sanitation Utility (ONAS) that can be a source of recharge of the studied shallow aquifer and more deteriorate the groundwater quality in this region.

Keywords: electrical resistivity tomography, groundwater, recharge, smar aquifer, southeastern tunisia

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Authors: S. Movafagh, Y. Bakhshan

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In this study, effect of adding Al2O3 nanoparticle to base fluid (water) in car radiator is investigated numerically. Radiators are compact heat exchangers optimized and evaluated by considering different working conditions. The cooling system of a car plays an important role in vehicle's performance, consists of two main parts, known as radiator and fan. Improving thermal efficiency of engine leads to increase the engine's performance, decline the fuel consumption and decrease the pollution emissions. In this study, the effects of fluid inlet flow rate and nanoparticle volume fraction on heat transfer and pressure drop of acar radiator are studied.

Keywords: forced convection, nanofluid, radiator, CFD simulation

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Authors: Amalia Zuhra

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Indonesia is very rich with its natural resources. Natural resource management becomes a challenge for Indonesia. Improper management will make the natural resources run out and future generations will not be able to enjoy the natural wealth. A good rule of law and proper implementation determines the success of the management of a country's natural resources. This paper examines the need to redefine problems and challenges in the management of natural resources in Indonesia in the context of law. The purpose of this article is to overview the latest issues and challenges in natural resource management and to redefine legal provisions related to environmental management and human rights protection so that the management of natural resources in the present and future will be more sustainable. This paper finds that sustainable management of natural resources is absolutely essential. The aspect of environmental protection and human rights must be elaborated more deeply so that the management of natural resources can be done maximally without harming not only people but also the environment.

Keywords: international environmental law, human rights law, natural resource management, sustainable development

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Authors: Okugbe Ebiotubo Ohore, Jingli Zhang, Binessi Edouard Ifon, Mathieu Nsenga Kumwimba, Xiaoying Mu, Dai Kuang, Zhen Wang, Ji-Dong Gu, Guojing Yang

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Antibiotic pollution and the evolution of antibiotic resistance genes (ARGs) are increasingly viewed as major threats to both ecosystem security and human health, and has drawn attention. This study investigated the fate of antibiotics in aqueous and sedimentary substrates and the impact of ecosystem shifts between water and sedimentary phases on resistome profiles. The findings indicated notable variations in the concentration and distribution patterns of antibiotics across various environmental phases. Based on the partition coefficient (Kd), the total antibiotic concentration was significantly greater in the surface water (1405.45 ng/L; 49.5%) compared to the suspended particulate matter (Kd =0.64; 892.59 ng/g; 31.4%) and sediment (Kd=0.4; 542.64 ng/g; 19.1%). However, the relative abundance of ARGs in surface water and sediment was disproportionate to the abundance of antibiotics concentration, and sediments were the predominant ARGs reservoirs. Phylogenetic divergence of the microbial communities between the surface water and the sedimentary ecosystems potentially played important roles in driving the ARGs profiles between the two distinctive ecosystems. ARGs of Clinical importance; including blaGES, MCR-7.1, ermB, tet(34), tet36, tetG-01, and sul2 were significantly increased in the surface water, while blaCTX-M-01, blaTEM, blaOXA10-01, blaVIM, tet(W/N/W), tetM02, and ermX were amplified in the sediments. cfxA was an endemic ARG in surface-water ecosystems while the endemic ARGs of the sedimentary ecosystems included aacC4, aadA9-02, blaCTX-M-04, blaIMP-01, blaIMP-02, bla-L1, penA, erm(36), ermC, ermT-01, msrA-01, pikR2, vgb-01, mexA, oprD, ttgB, and aac. These findings offer a valuable information for the identification of ARGs-specific high-risk reservoirs.

Keywords: antibiotic resistance genes, microbial diversity, suspended particulate matter, sediment, surface water

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Authors: Hung-Jen Lin, Chien-Hao Wang, Chien-Peng Huang, Yu-Sheng Tseng, En-Cheng Yang, Joe-Air Jiang

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Bees’ incoming and outgoing behavior is a decisive index which can indicate the health condition of a colony. Traditional methods for monitoring the behavior of honey bees (Apis mellifera) take too much time and are highly labor-intensive, and the lack of automation and synchronization disables researchers and beekeepers from obtaining real-time information of beehives. To solve these problems, this study proposes to use an Internet of Things (IoT)-based system for counting honey bees’ incoming and outgoing activities using an infrared interruption technique, while environmental factors are recorded simultaneously. The accuracy of the established system is verified by comparing the counting results with the outcomes of manual counting. Moreover, this highly -accurate device is appropriate for providing quantitative information regarding honey bees’ incoming and outgoing behavior. Different statistical analysis methods, including one-way ANOVA and two-way ANOVA, are used to investigate the influence of environmental factors, such as temperature, humidity, illumination and ambient pressure, on bees’ incoming and outgoing behavior. With the real-time data, a standard model is established using the outcomes from analyzing the relationship between environmental factors and bees’ incoming and outgoing behavior. In the future, smart control systems, such as a temperature control system, can also be combined with the proposed system to create an appropriate colony environment. It is expected that the proposed system will make a considerable contribution to the apiculture and researchers.

Keywords: ANOVA, environmental factors, honey bee, incoming and outgoing behavior

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Authors: M. Pena, J. Shin, H. Park

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The main objective of any engineering activity is the development of a system that fulfills the specific economic, social or environmental needs. Green growth policies, as a system, targets to satisfy two main needs: economic and environmental growth. Cities are complex systems composed of varied characteristics such as differences in socio-environmental conditions and local affordability, among others. Thus, commissioned policies are required to address these differences and to ensure green development. A more maintainable and justifiable, resource-efficient green growth can be obtained in urban areas if multi-criteria framework of policies relevant to green buildings is designed. Reason is that, this approach fits to target the differences and unique conditions of urban areas. By following the principles of axiomatic design, this paper urges to derive a framework for the application of green buildings policies in urban areas with distinctive socio-economic and environmental characteristics. Functional requirements defined as principles to ensure green growth and design parameters are identified in each set of conditions. Design matrices are constructed for each group of urban areas. Thus, the understanding of the needs and differences for each group of urban areas and the methodology to ensure green buildings is achieved.

Keywords: axiomatic design, green growth, sustainable development, urban planning

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Authors: Jinyoung Choi, Hyun-A Kim, Sunmook Lee

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The effects of environmental stress factors such as storage conditions on the deterioration phenomenon and the characteristic of the display glass were studied. In order to investigate the effect of chemical stress on the glass during the period of storage, the respective components of commercial glass were first identified by XRF (X-ray fluorescence). The glass was exposed in the acid, alkali, neutral environment for about one month. Thin film formed on the glass surface was analyzed by XRD (X-ray diffraction) and FT-IR (Fourier transform infrared). The degree of corrosion and the rate of deterioration of each sample were confirmed by measuring the concentrations of silicon, calcium and chromium with ICP-OES (Inductively coupled plasma-optical emission spectrometry). The optical properties of the glass surface were confirmed by SEM (Scanning electron microscope) before and after the treatment. Acknowledgement—The authors gratefully acknowledge the financial support from the Ministry of Trade, Industry and Energy (Grant Number: 10076817)

Keywords: corrosion, degradation test, display glass, environmental stress factor

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Authors: Melike Sultan Karasu Asnaz, Ayse Ozdogan Dolcek

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Crop drying, which aims to reduce the moisture content to a certain level, is a method used to extend the shelf life and prevent it from spoiling. One of the oldest food preservation techniques is open sunor shade drying. Even though this technique is the most affordable of all drying methods, there are some drawbacks such as contamination by insects, environmental pollution, windborne dust, and direct expose to weather conditions such as wind, rain, hail. However, solar dryers that provide a hygienic and controllable environment to preserve food and extend its shelf life have been developed and used to dry agricultural products. Thus, foods can be dried quickly without being affected by weather variables, and quality products can be obtained. This research is mainly devoted to investigating the modelling of drying kinetics of cantaloupe in a forced convection solar dryer. Mathematical models for the drying process should be defined to simulate the drying behavior of the foodstuff, which will greatly contribute to the development of solar dryer designs. Thus, drying experiments were conducted and replicated five times, and various data such as temperature, relative humidity, solar irradiation, drying air speed, and weight were instantly monitored and recorded. Moisture content of sliced and pretreated cantaloupe were converted into moisture ratio and then fitted against drying time for constructing drying curves. Then, 10 quasi-theoretical and empirical drying models were applied to find the best drying curve equation according to the Levenberg-Marquardt nonlinear optimization method. The best fitted mathematical drying model was selected according to the highest coefficient of determination (R²), and the mean square of the deviations (χ^²) and root mean square error (RMSE) criterial. The best fitted model was utilized to simulate a thin layer solar drying of cantaloupe, and the simulation results were compared with the experimental data for validation purposes.

Keywords: solar dryer, mathematical modelling, drying kinetics, cantaloupe drying

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Authors: Loreta Kaklauskiene, Arturas Kaklauskas

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The Integrated Human Resources and Work Environment Management (HOWE) System optimises employee productivity, improves the work environment, and, at the same time, meets the employer’s strategic goals. The HOWE system has been designed to ensure an organisation can successfully compete in the global market, thanks to the high performance of its employees. The HOWE system focuses on raising workforce productivity and improving work conditions to boost employee performance and motivation. The methods used in our research are linear correlation, INVAR multiple criteria analysis, digital twin, and affective computing. The HOWE system is based on two patents issued in Lithuania (LT 6866, LT 6841) and one European Patent application (No: EP 4 020 134 A1). Our research analyses ways to make human resource management more efficient and boost labour productivity by improving and adapting a personalised work environment. The efficiency of human capital and labour productivity can be increased by applying personalised workplace improvement systems that can optimise lighting colours and intensity, scents, data, information, knowledge, activities, media, games, videos, music, air pollution, humidity, temperature, vibrations, and other workplace aspects. HOWE generates and maintains a personalised workspace for an employee, taking into account the person’s affective, physiological and emotional (APSE) states. The purpose of this project was to create a HOWE for the customisation of quality control in smart workspaces taking into account the user’s APSE states in an integrated manner as a single unit. This customised management of quality control covers the levels of lighting and colour intensities, scents, media, information, activities, learning materials, games, music, videos, temperature, energy efficiency, the carbon footprint of a workspace, humidity, air pollution, vibrations and other aspects of smart spaces. The system is based on Digital Twins technology, seen as a logical extension of BIM.

Keywords: human resource management, health economics, work environment, organizational behaviour and employee productivity, prosperity in work, smart system

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Authors: Chinnawat Satsananan

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The amount of heavy metals in our environment has been of great concern because of their toxicity when their concentration is more than the permissible level. These metals enter the environment by different ways such as industrial activities, soil pollution. We have used flame atomic absorption spectrometry technique for determination of the concentration of Co, Cd and Pb in different tissues of five samples of seafoods (mackerel, squid, mussels, scallops and shrimp). The concentrations of Co, Cd and Pb in all examined seafoods were less than the reported literature values (WHO). The results mentioned that the seafoods obtained from Thewet Market were safety to consumption and make the quality of life of people in the community look better.

Keywords: heavy metals, seafood, atomic absorption spectrometry, Bangkok

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Authors: Elizaveta Petelina, Anton Sizo

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Environmental remediation projects deal with a wide spectrum of data, including data collected during site assessment, execution of remediation activities, and environmental monitoring. Therefore, an appropriate data management is required as a key factor for well-grounded decision making. The Environmental Data Management System (EDMS) was developed to address all necessary data management aspects, including efficient data handling and data interoperability, access to historical and current data, spatial and temporal analysis, 2D and 3D data visualization, mapping, and data sharing. The system focuses on support of well-grounded decision making in relation to required mitigation measures and assessment of remediation success. The EDMS is a combination of enterprise and desktop level data management and Geographic Information System (GIS) tools assembled to assist to environmental remediation, project planning, and evaluation, and environmental monitoring of mine sites. EDMS consists of seven main components: a Geodatabase that contains spatial database to store and query spatially distributed data; a GIS and Web GIS component that combines desktop and server-based GIS solutions; a Field Data Collection component that contains tools for field work; a Quality Assurance (QA)/Quality Control (QC) component that combines operational procedures for QA and measures for QC; Data Import and Export component that includes tools and templates to support project data flow; a Lab Data component that provides connection between EDMS and laboratory information management systems; and a Reporting component that includes server-based services for real-time report generation. The EDMS has been successfully implemented for the Project CLEANS (Clean-up of Abandoned Northern Mines). Project CLEANS is a multi-year, multimillion-dollar project aimed at assessing and reclaiming 37 uranium mine sites in northern Saskatchewan, Canada. The EDMS has effectively facilitated integrated decision-making for CLEANS project managers and transparency amongst stakeholders.

Keywords: data management, environmental remediation, geographic information system, GIS, decision making

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Authors: Richard Ren

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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

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Authors: Juan Manuel Brito-Diaz

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The emergence of urban environmentalism in Spain is related to the processes of economic transformation and growing urbanization that occurred during the end of the Franco regime and the democratic transition. This paper analyzes the urban environmental mobilizations and their impacts as relevant democratizing agents in the processes of political change in cities. It’s an under-researched topic and studies on environmental movements in Spain have paid little attention to it. This research takes as its starting point the close link between democratization and environmentalism, since it considers that environmental conflicts are largely a consequence of democratic problems, and that the impacts of environmental movements are directly linked to the democratization. The study argues that the environmental movements that emerged in Spain at the end of the dictatorship and the democratic transition are an important part of the broad and complex associative fabric that promoted the democratization process. The research focuses on investigating the environmental protest in Las Palmas de Gran Canaria—the most important city in the Canary Islands—between 1970 and 1983, concurrently with the last local governments of the dictatorship and the first democratic city councils. As it is a case study, it opens up the possibility to ask multiple specific questions and assess each of the responses obtained. Although several research methodologies have been applied, such as the analysis of historical archives documentation or oral history interviews, mainly a very widespread methodology in the sociology of social movements, although very little used by social historians, has been used: the Protest Event Analysis (PEA). This methodology, which consists of generating a catalog of protest events by coding data around previously established variables, has allowed me to map, analyze and interpret the occurrence of protests over time and space, and associated factors, through content analysis. For data collection, news from local newspapers have provided a large enough sample to analyze the properties of social protest -frequency, size, demands, forms, organizers, etc.—and relate them to another type of information related to political structures and mobilization repertoires, encouraging the establishment of connections between the protest and the political impacts of urban movements. Finally, the study argues that the environmental movements of this period were essential to the construction of the new democratic city in Spain, not only because they established the issues of sustainability and urban environmental justice on the public agenda, but also because they proposed that conflicts derived from such matters should ultimately be resolved through public deliberation and citizen participation.

Keywords: democratization, environmental movements, political impacts, social movements

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Authors: Danielle Katrina Santos, Koji Shimada

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Environmentally-friendly agriculture has been promoted for over two decades as a response to the environmental challenges brought by climate change and biological loss. Located above the equator, it is possible that Japan may benefit from future climate change, yet Japan is also a rarely developed country located in the Asian Monsoon climate region, making it vulnerable to the impacts of climate change. In this regard, the Japanese government has initiated policies to adapt to the adverse effects of climate change through the promotion and popularization of environmentally-friendly farming practices. This study aims to determine profit efficiency among environmentally-friendly rice farmers in Shiga Prefecture using the Stochastic Frontier Approach. A cross-sectional survey was conducted among 66 farmers from top rice-producing cities through a structured questionnaire. Results showed that the gross farm income of environmentally-friendly rice farmers was higher by JPY 316,223.00/ha. Production costs were also found to be higher among environmentally-friendly rice farmers, especially on labor costs, which accounted for 32% of the total rice production cost. The resulting net farm income of environmentally-friendly rice farmers was only higher by JPY 18,044/ha. Results from the stochastic frontier analysis further showed that the profit efficiency of conventional farmers was only 69% as compared to environmentally-friendly rice farmers who had a profit efficiency of 76%. Furthermore, environmentally-friendly agriculture participation, other types of subsidy, educational level, and farm size were significant factors positively influencing profit efficiency. The study concluded that substitution of environmentally-friendly agriculture for conventional rice farming would result in an increased profit efficiency due to the direct payment subsidy and price premium received. The direct government policies that would strengthen the popularization of environmentally-friendly agriculture to increase the production of environmentally-friendly products and reduce pollution load to the Lake Biwa ecosystem.

Keywords: profit efficiency, environmentally-friendly agriculture, rice farmers, direct payment subsidies

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Authors: Diqin Qi, Jiaming Li, Siman Li

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Based on the use of the three-point smoothing method for selectively processing original data columns, this paper establishes a group of grey GM(1,1) models to predict the concentration ranges of four major air pollutants in Shanghai from 2023 to 2024. The results indicate that PM₁₀, SO₂, and NO₂ maintain the national Grade I standards, while the concentration of PM₂.₅ has decreased but still remains within the national Grade II standards. Combining the forecast results, recommendations are provided for the Shanghai municipal government's efforts in air pollution prevention and control.

Keywords: atmospheric pollutant prediction, Grey GM(1, 1), model group, three-point smoothing method

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Authors: Abdelmoniem A. Attaelmanan, Ahmed A. H. Siddig

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This study was conducted in light of continual global climate changes that projected increasing aridity, changes in soil fertility, and pollution. Plant growth and development largely depend on the combination of availing water and nutrients in the soil. Changes in the climate and atmospheric chemistry can cause serious effects on these growth factors. Plant carbon (C), nitrogen (N), and hydrogen (H) play a fundamental role in the maintenance of ecosystem structure and function. Hashab (Acacia senegal), which produces gum Arabic, supports dryland ecosystems in tropical zones by its potentiality to restore degraded soils; hence it is ecologically and economically important for the dry areas of sub-Saharan Africa. The study aims at investigating the effects of water stress (simulated drought) and poor soil type on Acacia senegal C, N, and H contents. Seven days old seedlings were assigned to the treatments in Split- plot design for four weeks. The main plot is irrigation interval (well-watered and water-stressed), and the subplot is soil types (silt and sand soils). Seedling's C%, N%, and H% were measured using CHNS-O Analyzer and applying Standard Test Method. Irrigation intervals and soil types had no effects on seedlings and leaves C%, N%, and H%, irrigation interval had affected stem C and H%, both irrigation intervals and soil types had affected root N% and interaction effect of water and soil was found on leaves and root's N%. Synthesis application of well-watered irrigation with soil that is rich in N and other nutrients would result in the greatest seedling C, N, and H content which will enhance growth and biomass accumulation and can play a crucial role in ecosystem productivity and services in the dryland regions.

Keywords: Acacia senegal, Africa, climate change, drylands, nutrients biomass, Sub-Saharan, Sudan

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Authors: Simmi Chopra

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In the last few years, there has been a surge of Autoimmune diseases that have become more like an epidemic all over the world. The reasons vary from stress, insufficient sleep, smoking, genetics, environmental pollution, adulterated foods, and a diet full of “the deadly white,” which is white sugar and white flour. Most of the people diagnosed with these diseases are given steroids, opioids, supplements, or elimination diets to manage their lives, but most of them continue suffering to varying degrees. On the other hand, Ayurveda can help manage autoimmune problems effectively. Ayurveda is a 5000 years old holistic medical system from India that has an individualistic approach where health problems are looked at from the lens of balancing body and mind and by targeting the root cause of the problem. A combination of diet and lifestyle according to Ayurvedic principles, Ayurvedic herbal formulations and Ayurvedic therapies can help in the management of autoimmune and other chronic diseases. Panchkarma, which is an intense six weeks detox method, helps balance our body and mind, and has been very effective in managing autoimmune problems. The paper will introduce the basic concepts of Ayurveda and describe the terminologies- doshas, agni and ama. The paper will discuss the importance of diet and lifestyle according to the individual’s imbalance in the three functional parameters - doshas, which govern every aspect of our body and mind, our cells and tissues. The significance of agni, which can be correlated to digestive strength and ama, which can be correlated to toxins that are formed in our body leading to health problems, will be outlined. The Ayurvedic pathophysiology of autoimmune diseases will be discussed with emphasis on Rheumatoid arthritis, Multiple sclerosis and Psoriasis. Ayurvedic management will be discussed for these autoimmune conditions. As Ayurveda is an individualistic system, one protocol will not work for everyone. Therefore, case studies with Ayurvedic protocols for the above autoimmune disease will be presented. Conclusion: Ayurveda can help in managing as well as arresting the progression of autoimmune problems. Ayurveda is an ancient medical system, is much more needed today than ever. It is a tried and tested holistic system which has been practiced for the past many generations in India.

Keywords: ayurveda, autoimmune, diseases, nutrition

Procedia PDF Downloads 52

Authors: Thirupathi Thippani, Kothandaraman Ramanujam

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Current research on energy storage has been paid to metal-air batteries, because of attractive alternate energy source for the future. Metal – air batteries have the probability to significantly increase the power density, decrease the cost of energy storage and also used for a long time due to its high energy density, low-level pollution, light weight. The performance of these batteries mostly restricted by the slow kinetics of the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) on cathode during battery discharge and charge. The ORR and OER are conventionally carried out with precious metals (such as Pt) and metal oxides (such as RuO₂ and IrO₂) as catalysts separately. However, these metal-based catalysts are regularly undergoing some difficulties, including high cost, low selectivity, poor stability and unfavorable to environmental effects. So, in order to develop the active, stable, corrosion resistance and inexpensive bi-functional catalyst material is mandatory for the commercialization of zinc-air rechargeable battery technology. We have attempted and synthesized non-precious metal (NPM) catalysts comprising cobalt and N-doped multiwalled carbon nanotubes (N-MWCNTs-Co) were synthesized by the solid-state pyrolysis (SSP) of melamine with Co₃O₄. N-MWCNTs-Co acts as an excellent electrocatalyst for both the oxygen reduction reaction (ORR) and the oxygen evolution reaction (OER), and hence can be used in secondary metal-air batteries and in unitized regenerative fuel cells. It is important to study the OER and ORR at high concentrations of KOH as most of the metal-air batteries employ KOH concentrations > 4M. In the first 16 cycles of the zinc-air battery while using N-MWCNTs-Co, 20 wt.% Pt/C or 20 wt.% IrO₂/C as air electrodes. In the ORR regime (the discharge profile of the zinc-air battery), the cell voltage exhibited by N-MWCNTs-Co was 44 and 83 mV higher (based on 5th cycle) in comparison to of 20 wt.% Pt/C and 20 wt.% IrO₂/C respectively. To demonstrate this promise, a zinc-air battery was assembled and tested at a current density of 0.5 Ag⁻¹ for charge-discharge 100 cycles.

Keywords: oxygen reduction reaction (ORR), oxygen evolution reaction(OER), non-platinum, zinc air battery

Procedia PDF Downloads 218

Authors: Samira Mahmoudkelayeh, Katayoun Taghizade, Mitra Pourvaziri, Elnaz Asadian

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Over the recent decades, depletion of resources and environmental concerns made researchers and practitioners present sustainable approaches. Since construction process consumes a great deal of both renewable and non-renewable resources, it is of great significance regarding environmental impacts. Choosing sustainable construction materials is a remarkable strategy presented in many researches and has a significant effect on building’s environmental footprint. This paper represents an assessment framework for selecting best sustainable materials for exterior enclosure in the city of Tehran based on sustainability principles (eco-friendly, cost effective and socio-cultural viable solutions). To perform a comprehensive analysis of environmental impacts, life cycle assessment, a cradle to grave approach is used. A questionnaire survey of construction experts has been conducted to determine the relative importance of criteria. Analytic Network Process (ANP) is applied as a multi-criteria decision-making method to choose sustainable material which consider interdependencies of criteria and sub-criteria. Finally, it prioritizes and aggregates relevant criteria into ultimate assessed score.

Keywords: sustainable materials, building, analytic network process, life cycle assessment

Procedia PDF Downloads 224

Authors: Y. Landkocz, P. Gosset, A. Héliot, C. Corbière, C. Vendeville, V. Keravec, S. Billet, A. Verdin, C. Monteil, D. Préterre, J-P. Morin, F. Sichel, T. Douki, P. J. Martin

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Air Pollution produced by automobile traffic is one of the main sources of pollutants in urban atmosphere and is largely due to exhausts of the diesel engine powered vehicles. The International Agency for Research on Cancer, which is part of the World Health Organization, classified in 2012 diesel engine exhaust as carcinogenic to humans (Group 1), based on sufficient evidence that exposure is associated with an increased risk for lung cancer. Amongst the strategies aimed at limiting exhausts in order to take into consideration the health impact of automobile pollution, filtration of the emissions and use of biofuels are developed, but their toxicological impact is largely unknown. Diesel exhausts are indeed complex mixtures of toxic substances difficult to study from a toxicological point of view, due to both the necessary characterization of the pollutants, sampling difficulties, potential synergy between the compounds and the wide variety of biological effects. Here, we studied the potential indirect genotoxicity of emission of Diesel engines through on-line exposure of rats in inhalation chambers to a subchronic high but realistic dose. Following exposure to standard gasoil +/- rapeseed methyl ester either upstream or downstream of a particle filter or control treatment, rats have been sacrificed and their lungs collected. The following indirect genotoxic parameters have been measured: (i) telomerase activity and telomeres length associated with rTERT and rTERC gene expression by RT-qPCR on frozen lungs, (ii) γH2AX quantification, representing double-strand DNA breaks, by immunohistochemistry on formalin fixed-paraffin embedded (FFPE) lung samples. These preliminary results will be then associated with global cellular response analyzed by pan-genomic microarrays, monitoring of oxidative stress and the quantification of primary DNA lesions in order to identify biological markers associated with a potential pro-carcinogenic response of diesel or biodiesel, with or without filters, in a relevant system of in vivo exposition.

Keywords: diesel exhaust exposed rats, γH2AX, indirect genotoxicity, lung carcinogenicity, telomerase activity, telomeres length

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Authors: Mara Balestrieri, Clara Pusceddu

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Issues relating to the destructive phenomena that can damage people and goods have returned to the centre of debate in Italy with the increase in catastrophic episodes in recent years in a country which is highly vulnerable to hydrological risk. Environmental factors and geological and geomorphological territorial characteristics play an important role in determining the level of vulnerability and the natural tendency to risk. However, a territory has also been subjected to the requirements of and transformations of society, and this brings other relevant factors. The reasons for the increase in destructive phenomena are often to be found in the territorial development models adopted. Stewardship of the landscape and management of risk are related issues. This study aims to summarize the most relevant elements about this connection and at the same time to clarify the role of environmental risk assessment as a tool to aid in the sustainable management of landscape. How planners relate to this problem and which aspects should be monitored in order to prepare responsible and useful interventions?

Keywords: assessment, landscape, risk, planning

Procedia PDF Downloads 443

Authors: Bing-Shun Huang, Hung-Ju Chiu, Wen-Kai Hsieh, Hsiu-Chuan Lin, Ming-Lung Hung

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Taiwan's solar photovoltaic target in 2025 is 20 GW, of which the fish-electricity symbiosis target is 4 GW. In the future, many solar photovoltaic installations may cause local environmental or social impacts. Therefore, the Taiwan government inspects the fish-electricity symbiosis to reduce the impact of solar photovoltaics on the local environment or society. This stuy takes the symbiosis of fishery and electricity in Kaohsiung City as an example to explore Taiwan's environmental and social inspection practices. It mainly analyzes the two aspects of environmental ecology and social economy. The results show that the environmental inspection is mainly through site surveys, ecological information mapping, on-site interviews, and public consultation meetings. Social inspection mainly includes document analysis, on-site interviews, site surveys, expert discussions, and public consultations to identify possible local problems. Although the government had recognized the local issues, the future status may also change. It is recommended that future photoelectric companies should reconfirm the current situation of development sites when applying for the installation and propose countermeasures to solve the problem.

Keywords: taiwan, fish-electricity symbiosis, environment, society, inspection

Procedia PDF Downloads 182

Authors: James Kralj

Abstract:

Commercial shellfish aquaculture makes significant contributions to the economy and culture of the Pacific Northwest United States. The industry faces intense pressure to minimize environmental impacts as a result of Federal policies like the Magnuson-Stevens Fisheries Conservation and Management Act and the Endangered Species Act. These policies demand the protection of essential fish habitat and declare several salmon species as endangered. Consequently, numerous projects related to the protection and rehabilitation of eelgrass beds, a crucial ecosystem for countless fish species, have been proposed at both state and federal levels. Both eelgrass beds and commercial shellfish farms occupy the same physical space, and therefore understanding the effects of shellfish aquaculture on eelgrass ecosystems has become a top ecological and economic priority of both government and industry. This study evaluates the organismal communities that eelgrass and oyster aquaculture habitats support. Water samples were collected from Willapa Bay, Washington; Tillamook Bay, Oregon; Humboldt Bay, California; and Sammish Bay, Washington to compare species diversity in eelgrass beds, oyster aquaculture plots, and boundary edges between these two habitats. Diversity was assessed using a novel technique: environmental DNA (eDNA). All organisms constantly shed small pieces of DNA into their surrounding environment through the loss of skin, hair, tissues, and waste. In the marine environment, this DNA becomes suspended in the water column allowing it to be easily collected. Once extracted and sequenced, this eDNA can be used to paint a picture of all the organisms that live in a particular habitat making it a powerful technology for environmental monitoring. Industry professionals and government officials should consider these findings to better inform future policies regulating eelgrass beds and oyster aquaculture. Furthermore, the information collected in this study may be used to improve the environmental sustainability of commercial shellfish aquaculture while simultaneously enhancing its growth and profitability in the face of ever-changing political and ecological landscapes.

Keywords: aquaculture, environmental DNA, shellfish, sustainability

Procedia PDF Downloads 232

Authors: M. Stelmachowski, M. Wojtczak

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The aim of the work was to assess the environmental impact of the selected small and medium-sized companies supplying heat and electricity to the cities with a population of about 50,000 inhabitants. Evaluation and comparison of the impact on the environment have been carried out for the three plants producing heat and two CHP plants with particular attention to emissions into the atmosphere and the impact of introducing a system of trading carbon emissions of these companies.

Keywords: CO2 emission, district heating, heat and power plant, impact on environment

Procedia PDF Downloads 460