318 research outputs found

    Biotechnology and Bioengineering

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    Biotechnology and Bioengineering presents the most up-to-date research on biobased technologies. It is designed to help scientists and researchers deepen their knowledge in this critical knowledge field. This solid resource brings together multidisciplinary research, development, and innovation for a wide study of Biotechnology and Bioengineering

    FLOWPATH 2019 โ€“ NATIONAL MEETING ON HYDROGEOLOGY

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    FLOWPATH 2019, the 4th National Meeting on Hydrogeology, was held in Milan from 12th to 14th June 2019. According to the aim of the previous Editions of FLOWPATH, held in Bologna (2012), Viterbo (2014) and Cagliari (2017), the conference is an opportunity for Italian hydrogeologists to exchange ideas and knowledge on different groundwater issues. The objectives of the conference are: โ€“ To promote dialogue and exchange of scientific knowledge among young hydrogeologists; โ€“ To deepen the theoretical and practical aspects of our understanding on groundwater; โ€“ To update all the stakeholders, researchers and professionals on recent challenges in the hydrogeological sciences; โ€“ To encourage researchers, professionals and administrators to contribute to the improvement of water resources management

    Remediation of Soils and Groundwater Contaminated with Hydrocarbons in Area the Operation of Ecopetrol in Palagua oil field, Columbia.

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    Import 21/10/2013The soils of the Station 1 in Palagua oil field and bordering property indicated similar characteristics of both, classifying them like sandy, which coincides with the high permeability and rapid infiltration, together with low relative thickness and low retention of moisture. Also both present a capacity of cationic exchange and granular structure. The underground water contains phenols and metals as the Barium, Lead, Arsenic, hexavalent Chromium and Cadmium that they overcome the limit allowed by the Colombian current environment policy in several points of sampling. The bioaugmentation process represent better results for biodegradation of TPH in 83,7% in average, as well as for biodegradation of oil and grease (58,2%) and PAHs (31,7%). Combination of two treatments is more convenient for elimination of hydrocarbons than bioremediation solo. The flushing with surfactant and washing with hydrogen peroxide solution as the pre-treatments, presented similar efficiency for elimination of TPH, oil and grease but elimination of PAHs it is better to handle with peroxide pre-treatment, where can be achieved more than 80%.The results of the modeling of groundwater flow in the zone of interest, indicate a predominant direction northwest - south-west (NW to SW) and a maximum speed of flow 0.37 m/d of groundwater. The direction of displacement of the underground water together with the pen is towards the Marsh Palagua. The calibration of model lives average error -0,007m and absolute error 0,346m. After one month of biostimulation and two weeks flushing with surfactant as pre-treatment in Palagua oil field, was achieved elimination of TPH (56,3%) oil and grease(44,8%) and PAHs (49,2%).Prezenฤnรญ546 - Institut environmentรกlnรญho inลพenรฝrstvรญvyhovฤ›

    Nuclear facility decommissioning and site remedial actions: A selected bibliography, Vol. 18. Part 2. Indexes

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    Study of Biodegradation and Bioremediation

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    Despite many years of efforts to reduce the emission of toxic pollutants into the environment, the contamination of air, soils and water by heavy metals and organic xenobiotics is still a serious problem. This has urged many scientists around the world to undertake research that aims to find effective methods of removing pollutants from the environment. Special attention is paid to biological methods, which, thanks to their numerous advantages, meet the expectations of the whole society. As part of the Special Issue โ€œStudy of Biodegradation and Bioremediationโ€, in the MDPI journal Processes, several valuable articles have been published, which together form a picture of the current state of advanced research on the effective fight against environmental pollution. These include papers on the biodegradation of petroleum compounds or synthetic dyes by microorganisms or the enzymes they produce. In addition, the Special Issue includes papers on the bioremediation of dangerous heavy metals such as mercury and copper, and the results make a valuable contribution to our current state of knowledge on this topic. A separate and valuable part of this collection of publications are review articles devoted to the remediation of antineoplastic drugs, as well as the hopes and challenges connected with the application of nanotechnology in bioremediation. We are pleased that so many researchers from different parts of the world have submitted their articles on this topic. We are very grateful to them. We hope that readers of this collection will find many interesting ideas and relevant information that will lead to new solutions in the bioremediation and biodegradation of emerging environmental contaminants. Prof. Ewa Kaczorek Dr. Wojciech Smuล‚e

    State of Knowledge of Soil Biodiversity โ€“ Status, Challenges and Potentialities, Report 2020

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    Our well-being and the livelihoods of human societies are highly dependent on biodiversity and the ecosystem services it provides. It is essential that we understand these links and the consequences of biodiversity loss for the various global challenges we currently face, including food insecurity and malnutrition, climate change, poverty and diseases. The Agenda 2030 for Sustainable Development sets out a transformative approach to achieve socio-economic development while conserving the environment. There is increasing attention on the importance of biodiversity for food security and nutrition, especially above-ground biodiversity such as plants and animals. However, less attention is being paid to the biodiversity beneath our feet, soil biodiversity. Yet, the rich diversity of soil organisms drives many processes that produce food, regenerate soil or purify water. In 2002, the Conference of the Parties (COP) to the Convention on Biological Diversity (CBD) decided at its 6th meeting to establish an International Initiative for the Conservation and Sustainable Use of Soil Biodiversity and since then, the Food and Agriculture Organization of the United Nations (FAO) has been facilitating this initiative. In 2012, FAO members established the Global Soil Partnership to promote sustainable soil management and increase attention to this hidden resource. The Status of the Worldโ€™s Soil Resources (FAO, 2015) concluded that the loss of soil biodiversity is considered one of the main global threats to soils in many regions of the world. The 14th Conference of the Parties invited FAO, in collaboration with other organizations, to consider the preparation of a report on the state of knowledge on soil biodiversity covering its current status, challenges and potentialities. This report is the result of an inclusive process involving 300 scientists from around the world under the auspices of the FAOโ€™s Global Soil Partnership and its Intergovernmental Technical Panel on Soils, the Convention on Biological Diversity, the Global Soil Biodiversity Initiative and the European Commission. The report presents the state of knowledge on soil biodiversity, the threats to it, the solutions that soil biodiversity can provide to problems in different fields, including agriculture, environmental conservation, climate change adaptation and mitigation, nutrition, medicine and pharmaceuticals, remediation of polluted sites, and many others. The report will make a valuable contribution to raising awareness of the importance of soil biodiversity and highlighting its role in finding solutions to todayโ€™s global threats; it is a cross-cutting topic at the heart of the alignment of several international policy frameworks, including the Sustainable Development Goals (SDGs) and multilateral environmental agreements. Furthermore, soil biodiversity and the ecosystem services it provides will be critical to the success of the recently declared UN Decade on Ecosystem Restoration (2021-2030) and the upcoming Post- 2020 Global Biodiversity Framework. Soil biodiversity could constitute, if an enabling environment is built, a real nature-based solution to most of the problems humanity is facing today, from the field to the global scale. Therefore efforts to conserve and protect biodiversity should include the vast array of soil organisms that make up more than 25% of the total biodiversity of our planet

    State of Knowledge of Soil Biodiversity: Status, Challenges, and Potentialities

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    This report presents the threats to soil biodiversity and the solutions that soil biodiversity can provide to problems in different fields, including agriculture, environmental conservation, climate change adaptation and mitigation, nutrition, medicine and pharmaceuticals, remediation of polluted sites, and many others. There is increasing attention on the importance of biodiversity for food security and nutrition, especially above-ground biodiversity such as plants and animals. Less attention is being paid to the biodiversity beneath our feet: soil biodiversity. Yet the rich diversity of soil organisms drives many processes that produce food, regenerate soil or purify water. This report is the result of an inclusive process involving more than 300 scientists from around the world under the auspices of FAO's Global Soil Partnership and its Intergovernmental Technical Panel on Soils, the Convention on Biological Diversity, the Global Soil Biodiversity Initiative, and the European Commission

    ํ•ด์–‘์ƒํƒœ๊ณ„ ๋‚ด ์œ ๊ธฐ์˜ค์—ผ๋ฌผ์งˆ์˜ ์ƒ์ง€ํ™”ํ•™์  ๊ฑฐ๋™ ํ‰๊ฐ€ ๋ฐ ์ œ์ผ์›๋ฆฌ๊ธฐ๋ฒ•์— ๊ธฐ๋ฐ˜ํ•œ ์ƒํƒœ๋…์„ฑ ๋ฐ˜์‘ ๊ทœ๋ช…

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ์ž์—ฐ๊ณผํ•™๋Œ€ํ•™ ์ง€๊ตฌํ™˜๊ฒฝ๊ณผํ•™๋ถ€, 2022. 8. ๊น€์ข…์„ฑ.ํ•ด์–‘ ํ™˜๊ฒฝ์€ ์œก์ƒ ๋ฐ ํ•ด์–‘์—์„œ์˜ ์ธ๊ฐ„ ํ™œ๋™์œผ๋กœ ์ธํ•ด ๊ด‘๋ฒ”์œ„ํ•œ ์˜ํ–ฅ์„ ๋ฐ›๋Š”๋‹ค. ํ•ด์–‘ ํ™˜๊ฒฝ ์ค‘ ์กฐ๊ฐ„๋Œ€๋Š” ์˜์–‘์—ผ๋ฅ˜ (์ด์งˆ์†Œ ๋ฐ ์ด์ธ), ํƒ„ํ™”์ˆ˜์†Œ (์œ ๋ฅ˜ ๋ฐ ๋‹คํ™˜๋ฐฉํ–ฅ์กฑํƒ„ํ™”์ˆ˜์†Œ), ์•Œํ‚ฌํŽ˜๋†€๋ฅ˜, ์Šคํƒ€์ด๋ Œ ์˜ฌ๋ฆฌ๊ณ ๋จธ๋ฅผ ํฌํ•จํ•œ ์œ ๊ธฐ ์˜ค์—ผ๋ฌผ์งˆ์˜ ์œ ์ž…์œผ๋กœ๋ถ€ํ„ฐ ์œก์ง€์™€ ๋ฐ”๋‹ค ์‚ฌ์ด์˜ ๊ท ํ˜•์„ ์œ ์ง€ํ•œ๋‹ค. ์œ ๊ธฐ ์˜ค์—ผ๋ฌผ์งˆ์˜ ๊ฑฐ๋™์€ ๋ฌผ์งˆ์˜ ๋ฌผ๋ฆฌํ™”ํ•™์  ํŠน์„ฑ์— ํฌ๊ฒŒ ์ขŒ์šฐ๋œ๋‹ค. ๋” ํฐ ์†Œ์ˆ˜์„ฑ ๋ฐ ์ž…์ž์™€์˜ ๋ฐ˜์‘์„ฑ์€ ์œ ๊ธฐ ์˜ค์—ผ๋ฌผ์งˆ์ด ํ‡ด์ ๋ฌผ์— ์ถ•์ ๋˜๊ฒŒ ๋งŒ๋“ค๊ณ  ๊ทธ ๊ฒฐ๊ณผ, ํ‡ด์ ๋ฌผ์—์„œ๋Š” ํ•ด์ˆ˜๋ณด๋‹ค ๋ช‡ ๋ฐฐ๋‚˜ ๋” ํฐ ์œ ๊ธฐ ์˜ค์—ผ๋ฌผ์งˆ์˜ ๋†๋„๋ฅผ ์œ ์ง€ํ•œ๋‹ค. ํ•ด์–‘ ์ €์„œ ํ‡ด์ ๋ฌผ์€ ์œก์ƒ๊ธฐ์ธ์˜ค์—ผ ๋ฌผ์งˆ์˜ ์ตœ์ข… ์ข…์ฐฉ์ง€์ด๊ธฐ ๋•Œ๋ฌธ์— ์ง€์†์ ์ธ ํ•ด์–‘ ํ™˜๊ฒฝ ์ƒํƒœ์„œ๋น„์Šค๋ฅผ ์ œ๊ณต๋ฐ›๊ธฐ ์œ„ํ•ด์„œ๋Š” ํ•ด์–‘ ํ™˜๊ฒฝ์˜ ์œ ๊ธฐ ์˜ค์—ผ๋ฌผ ์ •ํ™” ๋Šฅ๋ ฅ๊ณผ ์ƒํƒœ๋…์„ฑ ์˜ํ–ฅ์„ ๋ช…ํ™•ํžˆ ํ‰๊ฐ€ํ•˜๋Š” ๊ฒƒ์ด ์ค‘์š”ํ•˜๋‹ค. ํ˜„์žฌ๊นŒ์ง€ ์กฐ๊ฐ„๋Œ€์—์„œ์˜ ์œ ๊ธฐ์˜ค์—ผ๋ฌผ์งˆ ์ •ํ™” ๋Šฅ๋ ฅ์€ ์ •๋Ÿ‰์ ์œผ๋กœ ์•Œ๋ ค์ง€์ง€ ์•Š์•˜๊ณ  ์ •ํ™” ๊ณผ์ •์—์„œ ๋ฐœ์ƒํ•˜๋Š” ํ™”ํ•™์ , ๋…์„ฑํ•™์ , ์ƒํƒœํ•™์  ๋ฐ˜์‘์€ ์˜ˆ์ธกํ•˜๊ธฐ ์–ด๋ ค์› ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์กฐ๊ฐ„๋Œ€ ๋‚ด ํ‡ด์ ๋ฌผ์ด ์ •ํ™”๋˜๋Š” ๊ณผ์ •์—์„œ ๋ฐœ์ƒํ•˜๋Š” ํ˜„์ƒ๋“ค์„ ์‹คํ—˜์  ๊ทœ๋ชจ ์—ฐ๊ตฌ, ์ฆ‰ ๋ฉ”์กฐ์ฝ”์ฆ˜ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด ํ‡ด์ ๋ฌผ์˜ ์ƒํƒœ์œ„ํ•ด์„ฑ ํ‰๊ฐ€๋ฒ•์„ ์‚ฌ์šฉํ•˜์—ฌ ์ •๋Ÿ‰์ ์œผ๋กœ ํ™•์ธํ•˜์˜€๋‹ค. ์ด๋ฅผ ์œ„ํ•ด ํ™”ํ•™ ๋ถ„์„, ์ƒ๋ฌผ ๊ฒ€์ • ๋ฐ ์ €์„œ ๊ตฐ์ง‘ ๊ตฌ์กฐ ๋ถ„์„๋„ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์ธ ์‹ค๋ฆฌ๊ณ  ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด ์œ ๊ธฐ ์˜ค์—ผ๋ฌผ์งˆ์˜ ๋ฌผ๋ฆฌํ™”ํ•™์  ํŠน์„ฑ์„ ๋ถ„์„ํ•˜์—ฌ ํ‡ด์ ๋ฌผ์˜ ์ •ํ™” ๊ณผ์ • ์†์—์„œ ๋ฐœ์ƒํ•˜๋Š” ํ™”ํ•™์ , ๋…์„ฑํ•™์ , ๊ทธ๋ฆฌ๊ณ  ์ƒํƒœํ•™์  ๋ฐ˜์‘ ์›์ธ์„ ์ œ์‹œํ•˜์˜€๋‹ค. ์ฒซ์งธ๋กœ, ๊ฐฏ๋ฒŒ ํ‡ด์ ๋ฌผ์˜ ์ž์ •๋Šฅ์„ ํ‰๊ฐ€ํ•˜๊ธฐ ์œ„ํ•ด 0.2m3 ๋ถ€ํ”ผ์˜ ์œ ๋ฆฌ ์ˆ˜์กฐ์— ํ‡ด์ ๋ฌผ์„ ์ด์‹ํ•˜์—ฌ ์ด์ธ์„ ๋น„๋กฏํ•œ ๊ณ ๋†๋„์˜ ์œ ๊ธฐ๋ฌผ์งˆ์ด ํฌํ•จ๋œ ํ•ด์ˆ˜๋ฅผ ๋„ฃ์–ด ์‹œ๊ฐ„์— ๋”ฐ๋ฅธ ๋ณ€ํ™” ํŠน์„ฑ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๊ฐฏ๋ฒŒ ํ‡ด์ ๋ฌผ์€ ์ด์ธ ๋ฐ ํ™”ํ•™์  ์‚ฐ์†Œ ์š”๊ตฌ๋Ÿ‰์˜ ๋†๋„๋ฅผ ๊ฐ๊ฐ 2์ผ ๋ฐ 7์ผ ๋งŒ์— ๋ฐฐ๊ฒฝ ๋†๋„ ์ˆ˜์ค€์œผ๋กœ ์ œ๊ฑฐํ•˜์˜€๋‹ค. ๊ทธ๋ฆฌ๊ณ  ๊ฐฏ๋ฒŒ ํ‡ด์ ๋ฌผ์— ๊ฐˆ๋Œ€๋ฅผ ์‹ฌ์€ ์‹คํ—˜ ๊ตฌ์—์„œ๋Š” ํŠนํžˆ ์šฉ์กด ๋ฌด๊ธฐ์ธ์„ ๋น ๋ฅด๊ณ  ํšจ์œจ์ ์œผ๋กœ ์ œ๊ฑฐํ•˜์˜€์œผ๋ฉฐ ์ด๋Š” ์‹์ƒ์˜ ์กด์žฌ๊ฐ€ ์šฉ์กด ์œ ๊ธฐ ์˜ค์—ผ๋ฌผ์งˆ์˜ ์ •ํ™”๋ฅผ ์ด‰์ง„ํ•˜๋Š” ๊ฒƒ์„ ์˜๋ฏธํ•œ๋‹ค. ๋˜ํ•œ ์œ ๊ธฐ ์˜ค์—ผ๋ฌผ์งˆ์˜ ์นจ์ „์€ ์ƒ๋ฌผํ•™์  ๊ต๋ž€ ํšจ๊ณผ๊ฐ€ ์ž‘์€ ํ™˜๊ฒฝ์—์„œ ์šฐ์„ธํ•œ ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋‘˜์งธ๋กœ, ์ž๊ฐˆ ์กฐ๊ฐ„๋Œ€ ๋‚ด ์œ ๊ธฐ ์˜ค์—ผ๋ฌผ์งˆ์ด ์œ ์ž…๋˜์—ˆ์„ ๋•Œ๋ฅผ ๊ฐ€์ •ํ•˜๊ณ  ์ด๋ฅผ ํšŒ๋ณตํ•˜๊ธฐ ์œ„ํ•œ ๋ฌผ๋ฆฌ์ , ์ƒ๋ฌผํ•™์  ๊ธฐ์ˆ ๋“ค์˜ ํ˜„ํ™ฉ์„ ํŒŒ์•…ํ•˜๊ณ  ํšจ๊ณผ๋ฅผ ๋ถ„์„ํ•˜์˜€๋‹ค. ์ด๋ฅผ ์œ„ํ•ด 60์ผ ๋™์•ˆ์˜ ๋ฉ”์กฐ์ฝ”์ฆ˜ ์—ฐ๊ตฌ๋กœ ์ž”๋ฅ˜ ์œ ๋ฅ˜ ์ œ๊ฑฐ๋ฅผ ์œ„ํ•œ ๋ฌผ๋ฆฌ์ , ์ƒ๋ฌผํ•™์  ๊ธฐ์ˆ , ๊ทธ๋ฆฌ๊ณ  ์ž์—ฐ์ •ํ™”๋Šฅ์˜ ํšจ๊ณผ ๋ฐ ์˜ํ–ฅ์„ ๋น„๊ตํ•˜์˜€๋‹ค. ์šฐ์„  ๊ณ ์˜จ๊ณ ์•• ์„ธ์ฒ™ ์ฒ˜๋ฆฌ๋Š” ์ž”๋ฅ˜ ์œ ๋ฅ˜๋ฅผ ์ตœ๋Œ€ 93% ์ œ๊ฑฐํ•˜์˜€๋‹ค. ํ•˜์ง€๋งŒ ์ด์™€ ๊ฐ™์€ ๋ฌผ๋ฆฌ์  ์ •ํ™”๋Š” ์ดˆ๊ธฐ ์ •ํ™” ์ฒ˜๋ฆฌ ๊ธฐ๊ฐ„ ์ €์„œ๋™๋ฌผ ๊ตฐ์ง‘์— ์•…์˜ํ–ฅ์„ ๋ผ์ณค๋‹ค. ์˜์–‘์—ผ, ์œ ํ™”์ œ, ํšจ์†Œ ํ™œ์„ฑ์ œ, ๊ทธ๋ฆฌ๊ณ  ๋ฏธ์ƒ๋ฌผ ์ œ์ œ์™€ ๊ฐ™์€ ์ƒ๋ฌผํ•™์  ์ฒ˜๋ฆฌ๋Š” ์ตœ๋Œ€ 66%์˜ ์ž”๋ฅ˜ ์œ ๋ฅ˜๋ฅผ ์ œ๊ฑฐํ•˜์˜€๋‹ค. โ€˜์ž์—ฐ์ •ํ™”โ€™๋Š” ๋‹ค๋ฅธ ๋ฌผ๋ฆฌ์  ๋ฐ ์ƒ๋ฌผํ•™์  ๊ธฐ์ˆ ๋“ค์˜ ์ž”๋ฅ˜ ์œ ๋ฅ˜ ์ œ๊ฑฐ ํšจ๊ณผ์™€ ์œ ์‚ฌํ•œ ํšจ์œจ์„ ๋ณด์—ฌ์ฃผ์—ˆ๋‹ค. ํŠนํžˆ ์‹คํ—˜ ๊ธฐ๊ฐ„์€ ๋ฏธ์ƒ๋ฌผ๋“ค์˜ ์ฒœ์ด๋ฅผ ํ™•์ธํ•˜์˜€์œผ๋ฉฐ ์ด๋Š” ์‹œ๊ฐ„์— ๋”ฐ๋ฅธ ์ž”๋ฅ˜ ์œ ๋ฅ˜ ์„ฑ๋ถ„์˜ ๋ณ€ํ™” ๊ฒฐ๊ณผ๋กœ ํ™•์ธํ•˜์˜€๋‹ค. ์ž์—ฐ์ •ํ™”๋Š” ๋‹ค๋ฅธ ๊ธฐ์ˆ ๋“ค๋งŒํผ ์œ ๊ธฐ ์˜ค์—ผ๋ฌผ์งˆ ์ œ๊ฑฐ์— ํšจ์œจ์ ์ด์—ˆ์œผ๋ฉฐ ํŠนํžˆ ์ €์„œ ๊ตฐ์ง‘์— ๋Œ€ํ•œ ์•…์˜ํ–ฅ์„ ์ตœ์†Œํ™”ํ•˜๋Š” ํŠน์ง•์ด ์žˆ์Œ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์…‹์งธ๋กœ, ๊ฐฏ๋ฒŒ ํ‡ด์ ๋ฌผ์—์„œ ์ž”๋ฅ˜์„ฑ ๋…์„ฑ๋ฌผ์งˆ ํŠน์ด์  ์ •ํ™”์™€ ์ƒํƒœ๋…์„ฑ ์˜ํ–ฅ์„ ํ™•์ธํ•˜๊ธฐ ์œ„ํ•ด ์˜ค์—ผ ํ‡ด์ ๋ฌผ์„ ํ˜„์žฅ ๊ฐฏ๋ฒŒ์— ์ด์‹ํ•˜์—ฌ 60์ผ๊ฐ„ ํ™”ํ•™์ , ๋…์„ฑํ•™์ , ๊ทธ๋ฆฌ๊ณ  ์ƒํƒœํ•™์  ๋ฐ˜์‘์˜ ๋ณ€ํ™”๋ฅผ ํ™•์ธํ•˜์˜€๋‹ค. ๊ทธ๋ฆฌ๊ณ  ๋จธ์‹  ๋Ÿฌ๋‹์„ ํ†ตํ•ด ์ •ํ™” ๊ณผ์ • ๋™์•ˆ ์˜ค์—ผ ํ‡ด์ ๋ฌผ์˜ ํŠน์ง•์„ 4๊ฐ€์ง€๋กœ ์ถ”์ถœํ•˜์˜€๋‹ค. ๋Œ€ํ˜•์ €์„œ๋™๋ฌผ๊ณผ ์‹์ƒ์ด ํ•จ๊ป˜ ์ด์‹๋œ ์˜ค์—ผ ํ‡ด์ ๋ฌผ์€ ์ƒ๋ฌผ ๊ด€๊ฐœ ๋ฐ ์‹๋ฌผ ์ •ํ™” ํšจ๊ณผ๋กœ ๋น ๋ฅด๊ฒŒ ํšŒ๋ณต๋˜์—ˆ๋‹ค. ์‹คํ—˜ ๊ธฐ๊ฐ„์€ ์ž”๋ฅ˜์„ฑ ๋…์„ฑ๋ฌผ์งˆ ๋‚ด ๋‹คํ™˜๋ฐฉํ–ฅ์กฑํƒ„ํ™”์ˆ˜์†Œ, ์•Œํ‚ฌํŽ˜๋†€๋ฅ˜, ๊ทธ๋ฆฌ๊ณ  ์Šคํƒ€์ด๋ Œ ์˜ฌ๋ฆฌ๊ณ ๋จธ์˜ ๋ชจ๋ฌผ์งˆ๋“ค์ด ๋น ๋ฅด๊ฒŒ ๊ฐ์†Œํ•˜์˜€๋Š”๋ฐ ์ƒ๋ฌผ ๊ด€๊ณ„ ๋ฐ ์‹๋ฌผ ์ •ํ™”๋กœ ์ธํ•œ ๋ฏธ์ƒ๋ฌผ์˜ ํ™œ๋™์œผ๋กœ ์ธํ•œ ๊ฒฐ๊ณผ์ž„์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋„ท์งธ๋กœ, ๋งค์งˆ (ํ•ด์ˆ˜, ํ‡ด์ ๋ฌผ ๋ฐ ํ•ด์–‘ ์ƒ๋ฌผ)์— ๋Œ€ํ•œ ์œ ๊ธฐ ์˜ค์—ผ๋ฌผ์งˆ์˜ ๋ฐ˜์‘์„ฑ์„ ์˜ˆ์ธกํ•˜๊ธฐ ์œ„ํ•ด ์œ ๊ธฐ ์˜ค์—ผ๋ฌผ์งˆ์˜ ๋ฌผ๋ฆฌํ™”ํ•™์  ์„ฑ์งˆ์„ ๋ถ„์„ํ•˜์˜€์Šต๋‹ˆ๋‹ค. ์ œ1 ์›๋ฆฌ๋ฅผ ํ™œ์šฉํ•œ ๋ฐ€๋„๋ฒ”ํ•จ์ˆ˜์ด๋ก ์„ ํ†ตํ•ด ์œ ๊ธฐ ์˜ค์—ผ๋ฌผ์งˆ๊ณผ ๋งค์งˆ ์‚ฌ์ด ๋ฐ˜์‘์„ ์ •๋Ÿ‰์ ์œผ๋กœ ํ™•์ธํ•  ์ˆ˜ ์žˆ๋Š” ๋ฐฉํ–ฅ์„ฑ ๋ฐ˜์‘ ์ธ์ž๋ฅผ ๊ณ ์•ˆํ•˜์˜€๋‹ค. ๋ฐฉํ–ฅ์„ฑ ๋ฐ˜์‘ ๋ชจ๋ธ์€ ์œ ๊ธฐ ์˜ค์—ผ๋ฌผ์งˆ์˜ ๊ตฌ์กฐ, ์˜ˆ๋กœ ๋ฒค์   ๊ณ ๋ฆฌ์˜ ์ˆ˜, ๋ฉ”ํ‹ธํ™” ๋ฐ ํ•˜์ด๋“œ๋ก์‹ค ํ™”์™€ ๊ฐ™์€ ๊ตฌ์กฐ์  ๋ณ€ํ˜•์ด ์žˆ๋Š” ํฌ๋ผ์ด์„ผ์˜ ๋™์กฑ์ฒด๋ฅผ ๋Œ€์ƒ์œผ๋กœ ๊ณ„์‚ฐํ•˜์˜€๊ณ  ํŠนํžˆ ์•„๋ฆด ํƒ„ํ™”์ˆ˜์†Œ์ˆ˜์šฉ์ฒด์™€์˜ ๋ฐ˜์‘ ๊ด€๊ณ„ ์ค‘์‹ฌ์œผ๋กœ ์ ์šฉํ•˜์˜€๋‹ค. ๋ณธ ๋ฐ˜์‘ ๋ชจ๋ธ์˜ ๊ฒฐ๊ณผ๋Š” ํฌ๋ผ์ด์„ผ ๋™์กฑ์ฒด์˜ ์ƒ๋ฌผ๊ฒ€์ • ๊ฒฐ๊ณผ์™€ ์ผ์น˜ํ•˜์˜€๋‹ค. ์ œ1 ์›๋ฆฌ์— ๊ธฐ๋ฐ˜ํ•œ ์ธ ์‹ค๋ฆฌ์ฝ” ์—ฐ๊ตฌ๋Š” ์œ ๊ธฐ ์˜ค์—ผ๋ฌผ์งˆ์˜ ๋ฌผ๋ฆฌํ™”ํ•™์  ์„ฑ์งˆ์„ ๊ณ„์‚ฐํ•˜์˜€๊ณ  ๊ธฐ์กด์˜ ๊ฒฝํ—˜์  ์ ‘๊ทผ ๋ฐฉ์‹์„ ๋ณด์™„ํ•˜์—ฌ ํ–ฅํ›„ ํ•ด์–‘ ํ™˜๊ฒฝ ๋‚ด ๋งค์งˆ ๊ฐ„์˜ ๋ฐ˜์‘์„ฑ ์˜ˆ์ธก์— ํ™œ์šฉํ•  ์ˆ˜ ์žˆ๋‹ค. ๋์œผ๋กœ, ๋…์„ฑ ์ž‘์šฉ์— ๋Œ€ํ•œ ๋ฐ˜์‘ ์ค‘์‹ฌ ์ ‘๊ทผ ๋ฐฉ๋ฒ•๊ณผ ํ•จ๊ป˜ 16๊ฐœ์˜ ๋‹คํ™˜๋ฐฉํ–ฅ์กฑ ํƒ„ํ™”์ˆ˜์†Œ๋“ค์˜ ์ƒํƒœ๋…์„ฑ ํšจ๊ณผ๋ฅผ ์˜ˆ์ธกํ•˜๊ธฐ ์œ„ํ•ด ๋ฐฉํ–ฅ์„ฑ ๋ฐ˜์‘ ๋ชจ๋ธ์„ ์‘์šฉํ•˜์˜€๋‹ค. ๋ถ„์ž ์—ญํ•™ ๋ชจ๋ธ๋ง ๋ถ„์„์„ ํ†ตํ•ด ์•„๋ฆด ํƒ„ํ™”์ˆ˜์†Œ์ˆ˜์šฉ์ฒด์™€ ๋‹คํ™˜๋ฐฉํ–ฅ์กฑํƒ„ํ™”์ˆ˜์†Œ์˜ ๊ฒฐํ•ฉ ๊ฐ€๋Šฅ์„ฑ์„ ํ™•๋ฅ ์ ์œผ๋กœ ๊ณ„์‚ฐํ•˜์˜€๊ณ  ์ด๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ๋ฐฉํ–ฅ์„ฑ ๋ฐ˜์‘ ๋ชจ๋ธ๊ณผ ์—ฐ๊ด€์‹œํ‚จ ๋ฐฉํ–ฅ์„ฑ ๋ฐ˜์‘-๊ฒฐํ•ฉ ์ธ์ž๋ฅผ ๊ณ ์•ˆํ•˜์˜€๋‹ค. ์ด ์ธ์ž๋ฅผ ํ†ตํ•ด ์œ ๊ธฐ ์˜ค์—ผ๋ฌผ์งˆ-์ˆ˜์šฉ์ฒด ๊ฒฐํ•ฉ์„ ์˜ˆ์ธกํ•  ์ˆ˜ ์žˆ์—ˆ๊ณ  ๋‚˜์•„๊ฐ€ ์ƒ๋ฌผ๊ฒ€์ • ๊ฒฐ๊ณผ์™€ ์ผ์น˜ํ•˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์ž ์žฌ ๋…์„ฑ ์˜ˆ์ธก์— ์žˆ์–ด ๋ฐฉํ–ฅ์„ฑ ๋ฐ˜์‘-๊ฒฐํ•ฉ ์ธ์ž๋Š” ์œ ๊ธฐ ์˜ค์—ผ๋ฌผ์งˆ์˜ ๋ฌผ๋ฆฌํ™”ํ•™์  ํŠน์„ฑ์ด ์ƒ๋ฌผ๊ณผ์˜ ๋…์„ฑ ๋ฐ˜์‘์— ์ฃผ์š” ์š”์ธ์ด ๋  ์ˆ˜ ์žˆ์Œ์„ ์š”์ธ์ด ๋  ์ˆ˜ ์žˆ์Œ ๋ณด์—ฌ์ฃผ์—ˆ๋‹ค. ํ–ฅํ›„ ์ธ ์‹ค๋ฆฌ์ฝ” ๋ฐฉ๋ฒ•์„ ํ†ตํ•œ ์œ ๊ธฐ ์˜ค์—ผ๋ฌผ์งˆ์˜ ํŠน์„ฑ ๋ถ„์„์€ ์ƒ๋ฌผ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ํ•ด์ˆ˜ ๋ฐ ํ‡ด์ ๋ฌผ๊ณผ ๊ฐ™์€ ํ•ด์–‘ ํ™˜๊ฒฝ๊ณผ์˜ ๋ฐ˜์‘ ์˜ˆ์ธก์— ์œ ์˜๋ฏธํ•˜๊ฒŒ ํ™œ์šฉ๋  ๊ฐ€๋Šฅ์„ฑ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์ด์ƒ์˜ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋ฅผ ์ข…ํ•ฉํ•ด๋ณด๋ฉด, ์ฒซ์งธ, ๋จผ์ € ์กฐ๊ฐ„๋Œ€์— ์œ ์ž…๋œ ์œ ๊ธฐ ์˜ค์—ผ๋ฌผ์งˆ์˜ ๋†๋„๋Š” ์ดˆ๊ธฐ ๋‹จ๊ณ„์—์„œ ์ „๋ฐ˜์ ์œผ๋กœ ๊ธ‰๊ฒฉํ•œ ๊ฐ์†Œ๋ฅผ ํ–ˆ๊ณ , ๋ชจ๋ฌผ์งˆ์˜ ๋ถ„ํ•ด๊ฐ€ ํ™œ๋ฐœํžˆ ์ง„ํ–‰๋˜์—ˆ๋‹ค. ๋‘˜์งธ, ์œ ๊ธฐ ์˜ค์—ผ๋ฌผ์งˆ ๋†๋„์˜ ๊ฐ์†Œ์™€ ํ•จ๊ป˜ ํ‡ด์ ๋ฌผ์˜ ์ž ์žฌ ๋…์„ฑ๋„ ๊ธ‰๊ฒฉํžˆ ๊ฐ์†Œํ•˜์˜€๊ณ , ์œ ๊ธฐ ์˜ค์—ผ๋ฌผ์งˆ ๋†๋„์˜ ๊ฐ์†Œ ์†๋„๋ณด๋‹ค ๋” ๋นจ๋ž๋‹ค. ์…‹์งธ, ์ €์„œ ๊ตฐ์ง‘์€ ๊ธฐํ•˜๊ธ‰์ˆ˜์ ์œผ๋กœ ํšŒ๋ณต๋˜์—ˆ์œผ๋ฉฐ, ์˜์–‘์ˆ˜์ค€์— ๋”ฐ๋ผ ๊ฐ๊ฐ์˜ ํšŒ๋ณต ์†๋„์— ์ฐจ์ด๊ฐ€ ์žˆ์—ˆ๋‹ค. ๋„ท์งธ, ํ™”ํ•™์ , ๋…์„ฑํ•™์ , ์ƒํƒœํ•™์  ํšŒ๋ณต์˜ ์ฐจ์ด์™€ ๊ฐ ์˜ํ–ฅ ๊ด€๊ณ„๋Š” ์œ ๊ธฐ ์˜ค์—ผ๋ฌผ์งˆ์˜ ๋ฌผ๋ฆฌํ™”ํ•™์  ํŠน์„ฑ ์˜ํ–ฅ์— ๊ธฐ์ธํ•œ ๊ฒƒ์œผ๋กœ ํ™•์ธ๋˜์—ˆ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ, ๋ณธ ์—ฐ๊ตฌ์˜ ๋ฐฉํ–ฅ์„ฑ ๋ฐ˜์‘ ์ธ์ž๋Š” ์ƒ๋ฌผ ๋‚ด ์ž ์žฌ์ ์ธ ๋…์„ฑ์„ ์˜ˆ์ธกํ•˜๋Š” ๋ฐ˜์‘-๊ฒฐํ•ฉ ์ธ์ž๋กœ ๊ฐœ๋ฐœ๋  ์ˆ˜ ์žˆ์œผ๋ฉฐ ์ƒ๋ฌผ๊ฒ€์ • ๊ฒฐ๊ณผ์™€ ์ƒ๋‹นํžˆ ์ผ์น˜ํ•œ ๊ฒƒ์„ ํ™•์ธํ–ˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ ํ™œ์šฉํ•œ ํ†ตํ•ฉ์  ์ ‘๊ทผ์€ ํ•ด์–‘ ํ™˜๊ฒฝ ๋‚ด ์œ ๊ธฐ ์˜ค์—ผ๋ฌผ์งˆ์˜ ์ •ํ™”์™€ ์ƒํƒœ ๋…์„ฑํ•™์  ํšจ๊ณผ๋ฅผ ์ดํ•ดํ•˜๋Š” ๋ฐ ์žˆ์–ด ์œ ์šฉํ•˜๊ฒŒ ์‚ฌ์šฉ๋  ์ˆ˜ ์žˆ๋‹ค. ์•ž์œผ๋กœ ์šฐ๋ฆฌ๋‚˜๋ผ ํ•ด์–‘ ์ƒํƒœ๊ณ„ ์„œ๋น„์Šค์˜ ๊ฐ€์น˜๋ฅผ ์žฌ๊ณ ํ•˜๊ณ  ํ•ด์•ˆ์„ ์ฒด๊ณ„์ ์œผ๋กœ ๊ด€๋ฆฌํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ์œ„์™€ ๊ฐ™์€ ๋‹คํ•™์ œ์  ์ ‘๊ทผ์ด ์ง€์†ํ•ด์„œ ํ•„์š”ํ•˜๋‹ค.The marine environment is subject to a broad range of adverse impacts from anthropogenic activities. Among the marine environment, an intertidal zone maintains a balance as a buffer between the land and the sea from the introduction of organic pollutants, including nutrients (total nitrogen, TN; total phosphorus, TP), hydrocarbons (oil and polycyclic aromatic hydrocarbons, PAHs), alkylphenols (APs+APEOs), and styrene oligomers (SOs). The fate of organic pollutants in the marine environment is highly dependent on their physicochemical properties. Due to their hydrophobicity and particle reactivity, many organic pollutants have concentrations in sediments that are several orders of magnitude greater than those in the surrounding water. As a result, sediments are frequently regarded as the final destination for pollutants in the environment. Thus, it is crucial to estimate the restoration capacity and ecotoxicological effect of organic pollutants in the marine environment to maintain environmental services. Until this study, the restoration ability of organic pollutants in the intertidal zone was not quantitatively known, and the chemical, toxicological and ecological reactions occurring during the restoration process were not predicted. In this study, the ecological processes occurring in sediments being purified were identified quantitatively using an enhanced integrated sediment quality triad (SQT) approach with an enclosed experimental scale study (mesocosm). Additionally, using an in silico study, by examining the physico-chemical properties of organic pollutants, the causes of the restoration and ecotoxicity were analyzed. For evaluating the specific recovery of the benthic community health from the organic pollutants, instrumental analysis, bioassays, and investigation of the benthic community structure were also implemented. The mudflat sediments significantly removed waterborne organic pollutants to background levels in ~2 and 6โ€“7 days for TP and COD (chemical oxygen demand), respectively. This rapid removal of organic matters by natural sediments could be attributed to the microbe community degrading the corresponding pollutants. The temporal trend and removal efficacy for COD and TP were found to be similar between the bare tidal flat and salt marsh. Meantime, it was noteworthy that the salt marsh removed waterborne DIP much more quickly and efficiently, implying a high affinity of the halophyte on dissolved forms of organic matters. Of note, sedimentary organic sink prevailed in a defaunated condition under the lesser bioturbation effect. Physical and biological remediation techniques were compared to natural attenuation for the removal of residual oil using a 60-day mesocosm experiment with SQT. First, physical treatment of hot water + high pressure flushing maximally removed residual oils (max=93%), showing the greatest recovery among the SQT variables (mean=72%). Physical cleanup generally involved adverse effects such as depression of the microphytobenthic community during the initial period. Next, biological treatments, such as fertilizer, emulsifier, enzyme, and augmentation of the microbes, all facilitated the removal of oil (max=66%) enhancing the ecological recovery. Natural attenuation with โ€œno treatmentโ€ showed a comparable recovery to the other remediations (max=54%). During the experimental periods, the dynamics of the benthic community were presented. Artificial remediation techniques showed a better efficacy as indicated by the SQT parameters (mean=47%). Natural restoration was also often as efficient as most active restoration alternatives and was cost-effective while minimizing the impacts on benthic communities. Contaminated sediments were transplanted into the site tidal flats to confirm the PTS specific restoration in the tidal flat and their ecotoxicological effects. A 60-day in situ mesocosm study was implemented to quantify the restoration capacity using the SQT. Contaminated sediments recovered rapidly through bio-irrigation and phytoremediation (max. recovery: 71.2%). Machine learning classified the sedimentary qualities of the natural restoration process into four groups. During the 60-day sediment recovery period the benthic community changed through four stages. The reduction of parent compounds of PTSs (high molecular weight PAHs, STs, and APEOs) progressed primarily through bio-irrigation and phytoremediation. The results show that the presence of macrofauna and macrophytes in the tidal flat can promote the degradation of parent compounds with a rapid reduction of toxicity. The influence of the dipole-driven orientation and the resulting directional configuration of the organic pollutants on the predicted reactivity to the media (seawater, sediment, and marine organisms) were investigated. Using physico-chemical properties calculated by ab initio density functional theory, directional reactivity factors (DRF) were devised as the main indicators of reactivity, linking the interaction between the organic pollutants and the media. The directional reactive model was applied to predict the variation of the aryl hydrocarbon receptor (AhR)-mediated toxic potencies among homologues of chrysene with structural modifications such as the number of constituent benzene rings, methylation, and hydroxylation. The results of this study explain why the toxic responses of the parent and metabolites of the organic pollutants were different. Moreover, the results of the predictive models were consistent with the empirical potencies determined by the use of the H4IIE-luc transactivation bioassay. An experiment-free approach based on first principles would provide an analytical framework for estimating the molecular reactivity in silico and complements conventional empirical approaches for studying molecular initiating events in adverse outcome pathways. Because the advanced DRF model was calculated for the interaction between organic pollutants and media, quantitatively calculations for the dynamical mechanism were used for applying the potential toxicity prediction model. Using molecular dynamics (MD) analysis, given the possibility of AhR-organic pollutants binding (conjugated state), it was confirmed that the directional reactive binding factor (DRBF) could be a mechanistic predictive index linking molecular ligand-receptor binding to in vitro toxicity. The DR model accurately estimated the toxic potency of a set of 16 similar PAHs, as confirmed by the H4IIE-luc bioassay. The first application of DRF to the prediction of potential toxicity implies that the physico-chemical properties of organic pollutants can be a major driving factor in the reaction with a medium, and the in silico method will provide important basic data for predicting the restoration and ecotoxicity of organic pollutants in the future. To summarize the above study results, first, the concentration of organic pollutants introduced into the intertidal zone showed a rapid decrease in the initial stage overall, and the decomposition of the parent material proceeded actively. Second, with the decrease of the concentration of the organic pollutants, the potential toxicity of the sediment also decreased rapidly, and the rate of decrease was faster than the decrease of the concentration of the organic pollutants. Third, the benthic cluster recovered exponentially, and there was a difference in each recovery rate according to the trophic level. Fourth, it was confirmed that the differences in chemical, toxicological, and ecological recovery were affected by the physicochemical properties of the organic pollutants. Finally, the DRF in this study could be developed into a DRBF predicting the potential toxicity and corresponded to the results of the in vitro bioassay. An integrated approach for understanding the restoration capacity and ecotoxicological effects of organic pollutants in this study can be useful for interpreting the chemical, toxicological, and ecological responses. In the future, to systematically manage coastal waters with severe contamination of benthic sediments, continuous development of ecological risk assessment techniques is required. In the future, to reconsider the value of ecosystem services in the intertidal zone of Korea and systematically manage coasts, the above interdisciplinary approach is continuously needed.CHAPTER. 1. Introduction 1 1.1. Backgrounds 2 1.2. Objectives 15 CHAPTER. 2. Natural Restoration Capacity of Tidal Flats for Organic Matters and Nutrients: A Mesocosm Study 18 2.1. Introduction 19 2.2. Materials and Methods 21 2.2.1. Study design and development of mesocosm system 21 2.2.2. Sampling and data analyses 22 2.3. Results and Discussion 28 2.3.1. Natural restoration under waterborne organic matters and nutrients in tidal flat 28 2.3.2. Comparison of restoration capacity between bare and vegetated sediment 31 2.3.3. Restoration capacity in Bongam tidal flat, Masan Bay 38 2.3.4. Comparison to other mesocosm studies for restoration capacity of tidal flats 40 2.4. Conclusions 44 CHAPTER. 3. Best Available Technique for the Recovery of Marine Benthic Communities in a Gravel Shore after the Oil Spill: a Mesocosm-based Sediment Triad Assessment 45 3.1. Introduction 46 3.2. Materials and Methods 48 3.2.1. Sample preparations 48 3.2.2. Mesocosm experimental setting 49 3.2.3. Instrumental analysis of residual TPH and UCM in gravel 57 3.2.4. Zebrafish (Danio rerio) embryo test 57 3.2.5. Vibrio fischeri (V. fischeri) biossay 58 3.2.6. H4llE-luciferase transactiviation bioassay 58 3.2.7. Identification of MPB individual 58 3.2.8. Bacterial metagenomic analysis 59 3.2.9. Measurements of benthic primary production 59 3.2.10. Multi-attribute utility theory (MAUT) analysis for selection of the best available technique for remediation of oil 60 3.2.11. Statistical analysis 60 3.3. Results and Discussion 62 3.3.1. Physical and biological remediations 62 3.3.2. Dynamics in bacterial communities 78 3.3.3. Effectiveness of remediation techniques 85 3.3.4. Best available remediation techniques 86 3.4. Conclusions 95 CHAPTER. 4. Determining characteristics of Sediment Quality with Machine Learning to Evaluate the Natural Restoration of Persistent Toxic Substances in Contaminated Tidal Flat Sediments 96 4.1. Introduction 97 4.2. Materials and Methods 100 4.2.1. Sample preparation and In situ mesocosm experimental setting 100 4.2.2. Persistent toxic substances analysis (PAHs, APs, and SOs) 104 4.2.3. H4llE-luciferase transactivation bioassay 105 4.2.4. Bacterial metagenomic analysis 105 4.2.5. Identification of diatom individual 106 4.2.6. Identification of meiofauna individual 106 4.2.7. Measurements of benthic primary production 106 4.2.8. Self-Organizing Map (SOM) 107 4.2.9. K-means clustering via principal component analysis (PCA) 109 4.2.10. Statistical analysis 109 4.3. Results and Discussion 110 4.3.1. Chemical, toxicological, and biological responses in natural restoration process of tidal flat 110 4.3.2. Time series clustering in evaluating the recovery of each treatment with the self-organizing map (SOM) using machine learning 118 4.3.3. Effect of macrofauna (C. sinensis and M. japonicus) and salt marsh (P. australis) on the change of benthic community using K-means clustering: PCA 121 4.3.4. Correlation between composition of PTSs and bacterial community in each treatment groups 125 4.3.5. Evaluation to natural restoration of contaminated sediments & effect of bio-irrigation and phytoremediation in tidal flat by sediment quality triad approach (SQT) 130 4.4. Conclusions 132 CHAPTER. 5. Influence of Ligandโ€™s Directional Configuration, Chrysenes as Model Compounds, on the Binding Activity with Ahr Receptor 133 5.1. Introduction 134 5.2. Materials and Methods 138 5.2.1. Selection of Model Chemicals 138 5.2.2. Density Functional Theory Calculations 140 5.2.3. C 1s NEXAFS Spectroscopy 140 5.2.4. H4llE-luc transactivation bioassay for evaluating AhR-mediated potencies and calculation of EC50 of homologues of chrysene 141 5.2.5. In silico analysis: quantitative structure-activity relationship (QSAR) and molecular docking model 144 5.3. Results and Discussion 145 5.3.1. Directional Reactive Modeling 145 5.3.2. DRF as an indicator of ligand-binding reactivity 147 5.3.3. AhR-mediated toxic potency of chrysene homologues 158 5.3.4. Comparison of predicted potencies: DR model vs. current in silico models 162 5.4. Conclusions 167 CHAPTER. 6. Comprehension of Bio-Physical Communication for Predicting Potential Toxicity of 16 Polycyclic Aromatic Hydrocarbons 169 6.1. Introduction 170 6.2. Materials and Methods 175 6.2.1. Selection of Model Chemicals 175 6.2.2. Density Functional Theory Calculations 175 6.2.3. Molecular dynamics for calculating the probability of binding in ligand:AhR 176 6.2.4. Aryl hydrocarbon receptor homology modeling 177 6.2.5. H4llE bioassay and calculation in median effective concentration 177 6.2.6. In silico toxicity prediction analysis 178 6.3. Results and Discussion 179 6.3.1. A comprehensive driving force of ligand to receptor calculated from DR model based on first principles 179 6.3.2. Probability of 16 PAHs binding to AhR and determination of potential toxicity for 16 PAHs 188 6.3.3. Experimental and predicted potential toxicity of 16 PAHs using in vitro and in silico testing 195 6.4. Conclusions 201 CHAPTER. 7. Conclusions 202 7.1. Summary 203 7.2. Environmental implications and Limitations 208 7.3. Future Research Directions 211 BIBLIOGRAPHY 213 ABSTRACT (IN KOREAN) 236๋ฐ•
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