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    ํ•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•

    Biodegradation of Petroleum Hydrocarbons

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    Biodegradation of hydrocarbons in the environment is the natural way of cleaning the nature. The potential biodegradation of hydrocarbon contaminants by microorganisms is dependent on the environmental factors and the nutrients available. In this study culture conditions like temperature, pH, and nitrogen source were optimized by conventional one-factor at a time experimentation and the combination of other nutrients (nitrogen, phosphorus, magnesium, and sulfur) was optimized by using design of experiments (DOE) combined with grey relational analysis (GRA). Total petroleum hydrocarbons of oil sludge, light crude oil and heavy crude oil, degradation was studied for a period of thirty days using microbial strains isolated from the hydrocarbon contaminated sites. They have shown predominant results in the degradation of TPHโ€™s under optimized culture conditions and prior addition of biosurfactants in the culture flask has enhanced the degradation process and microbial biomass yield

    Characterisation of European Marine Sites: Mersey Estuary Special Protection Area. Occasional Publication of the Marine Biological Association 18

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    This report provides an overview of water and sediment quality within the Mersey Estuary European Marine Site (EMS) and examines evidence for their influence on bioloigcal condition. It has not been possible to determine adequately whether prevailing conditions in the Mersey impact on the interest features of the site as studies which address this issue have not been carried out. It is only possible to review the current level of knowledge regarding the biological and chemical status for the estuary, and extrapolate risks to the bird population. Often information relates to sites outside the EMS; where this is the case the authors have tried to appraise the general status of the estuary, based on best available knowledge

    Science-based restoration monitoring of coastal habitats, Volume Two: Tools for monitoring coastal habitats

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    Healthy coastal habitats are not only important ecologically; they also support healthy coastal communities and improve the quality of peopleโ€™s lives. Despite their many benefits and values, coastal habitats have been systematically modified, degraded, and destroyed throughout the United States and its protectorates beginning with European colonization in the 1600โ€™s (Dahl 1990). As a result, many coastal habitats around the United States are in desperate need of restoration. The monitoring of restoration projects, the focus of this document, is necessary to ensure that restoration efforts are successful, to further the science, and to increase the efficiency of future restoration efforts

    Sedimentos subaquรกticos como fontes de bactรฉrias anaerรณbicas facultativas hidrocarbonoclรกsticas e produtoras de biossurfactantes

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    Doutoramento em Engenharia QuรญmicaActualmente sรฃo conhecidas poucas estirpes bacterianas capazes de produzir biossurfactantes (BSFs) em condiรงรตes de microaerobiose ou anaerobiose. Estas bactรฉrias tรชm um papel importante nรฃo sรณ em processos naturais (ex. formaรงรฃo de biofilmes ou de hidratos de gรกs), como podem ter diversas aplicaรงรตes biotecnolรณgicas (ex. estratรฉgias de biorremediaรงรฃo e aplicaรงรตes industriais). As bactรฉrias produtoras de BSFs em condiรงรตes de limitaรงรฃo de oxigรฉnio, com capacidade para degradar hidrocarbonetos sรฃo de particular interesse para estratรฉgias de biorremediaรงรฃo de locais contaminados com hidrocarbonetos de petrรณleo (PHs) e na recuperaรงรฃo microbiana de petrรณleo (MEOR). Neste contexto, o objectivo deste trabalho foi o isolamento, identificaรงรฃo e a caracterizaรงรฃo de bactรฉrias anaerรณbias ou anaerรณbias facultativas produtoras de BSF e degradadoras de hidrocarbonetos (hidrocarbonoclรกsticas) na perspetiva da sua aplicaรงรฃo biotecnolรณgica em condiรงรตes de limitaรงรฃo de oxigรฉnio. Foram escolhidos dois ambientes contaminados com PHs como potenciais fontes de bactรฉrias hidrocarbonoclรกsticas produtoras de BSFs: vulcรตes de lama (MV) de mar profundo do Golfo de Cรกdis (Oceano Atlรขntico) e o sistema estuarino da Ria de Aveiro (Portugal). Foram preparadas culturas de enriquecimento com sedimentos subaquรกticos recolhidos nestes dois habitats, como potenciais inรณculos de bactรฉrias anaerรณbias facultativas. Um design experimental fatorial foi usado para testar o efeito do crude como fonte de carbono, e de nitrato e/ou sulfato, como aceitadores terminais de eletrรตes. De forma a melhor compreender a estrutura das comunidades bacterianas envolvidas na biodegradaรงรฃo de PHs nos MV do mar profundo procedeu-se ร  sequenciaรงรฃo do gene 16S rRNA das comunidades bacterianas de culturas de enriquecimento com sedimento de dois MVs, um activo e outro inactivo, e com ou sem adiรงรฃo de crude e/ou nitrato. Detetou-se uma diferenciaรงรฃo entre as comunidades dos dois MVs, independentemente dos suplementos a que as culturas foram expostas, sendo que Alphaproteobacteria e Bacilli predominaram nas culturas com sedimentos de MV activo e inactivo, respectivamente. De uma forma menos acentuada, tanto o nitrato como o crude afetaram a composiรงรฃo das comunidades bacterianas. Gรฉneros de bactรฉrias que sรณ foram detectados nos ensaios com adiรงรฃo de crude (ex. Erythrobacteraceae no MV activo e Acidimicrobiale no MV inactivo) poderรฃo ser usados como indicadores da presenรงa de hidrocarbonetos de petrรณleo nestes habitats. A biodegradaรงรฃo de PHs nas culturas com crude foi avaliada por cromatografia gasosa acoplada a espectrometria de massa. De uma forma geral, as comunidades de culturas do MV activo foram capazes de degradar n-alcanos de tamanho inferior a C13 e compostos monoaromรกticos, enquanto as comunidades do MV inactivo apresentaram a capacidade de metabolizar vรกrios tipos de hidrocarbonetos aromรกticos policรญclicos. A presenรงa de nitrato apenas afectou positivamente a biodegradaรงรฃo de alcanos, e nรฃo teve efeito ou foi mesmo inibitรณria da biodegradaรงรฃo de outros hidrocarbonetos. A partir de todas as culturas, com todos os tipos de sedimentos, dos MVs do Golfo de Cรกdis e do estuรกrio da Ria de Aveiro, foi possรญvel isolar-se um total de 13 isolados capazes de sobreviver exclusivamente com crude como fonte de carbono e produzir BSF em condiรงรตes de aerobiose. Destas, apenas duas nรฃo foram capazes de produzir BSFs em anaerobiose. A sequenciaรงรฃo do gene 16S rRNA dos isolados permitiu identifica-los como pertencendo aos gรฉneros Pseudomonas, Bacillus, Ochrobactrum, Brevundimonas, Psychrobacter, Staphylococcus, Marinobacter e Curtobacterium, a maioria dos quais nรฃo tinha ainda membros conhecidos como produtores de BSF em anaerobiose. Os resultados obtidos com este trabalho permitiram caracterizar melhor as comunidades envolvidas na degradaรงรฃo de PHs em MVs de mar profundo. Conseguiu-se ainda isolar e identificar estirpes, tanto de mar profundo como de ambiente estuarino, capazes de degradar PHs e produzir BSFs em condiรงรตes de anaerobiose. Estas estirpes apresentam elevado potencial biotecnolรณgico para aplicaรงรตes como MEOR e biorremediaรงรฃo em ambientes com escassez de oxigรฉnio.So far, only few bacterial strains are known to produce biosurfactants (BSFs) under microaerobic or anaerobic conditions. However, these bacteria are not only involved in important natural processes (e.g. biofilm and gas hydrates formations) but can also be used in several biotechnological applications (e.g. bioremediation strategies and industrial applications). Bacteria able to produce BSFs under oxygen-limiting conditions that are also able to degrade hydrocarbons, are of particular interest to bioremediation strategies of sites contaminated with petroleum hydrocarbons (PHs) and microbial enhanced oil recovery (MEOR) strategies. In this context, this work aims at isolating, identifying, and characterizing BSF-producing and hydrocarbon-degrading (hydrocarbonoclastic) bacteria grown under anaerobic conditions, which can be used in biotechnological applications under oxygen limitation. Two environments contaminated with PHs were chosen as potential sources of hydrocarbonoclastic BSF-producing bacteria: deep-sea mud volcanos from the Gulf of Cadiz (Atlantic Ocean), and the estuarine system of Ria de Aveiro (Portugal). Enrichment cultures were prepared using subaquatic sediments from both sites, as potential sources of facultative anaerobic bacteria. A factorial experimental design was used to test the effect of crude oil as carbon source, and nitrate and/or sulfate, as terminal electron acceptors. Aiming at better understanding the structure of bacterial communities involved in PHs biodegradation at deep-sea MVs, sequencing of the 16S rRNA gene was performed for bacterial communities from cultures containing sediments from two MVs, active and inactive, and with or without crude oil and/or nitrate. A distinction between the communities of MVs with different activity, independent of the supplements was observed. Alphaproteobacteria and Bacilli were the predominant classes found in enrichment cultures inoculated with active and inactive MVs sediments, respectively. In a minor scale, nitrate and crude oil additions also affected the composition of bacterial communities. Therefore, genera that only appeared in cultures with crude oil. (e.g. Erythrobacteraceae in active MV cultures and Acidimicrobiale in inactive MV cultures) can be used as biosensors of the presence of PHs in these habitats. Biodegradation of PHs in cultures containing crude oil was assessed by gas chromatography coupled with mass spectrometry. Overall, communities from active MV cultures were able to degrade n-alkanes below C13 and monoaromatic hydrocarbons, while communities from inactive MV cultures presented the ability to metabolize several types of polycyclic aromatic hydrocarbons. The presence of nitrate only had a positive effect on the biodegradation of alkanes, and had no effect or even an inhibitory effect on the biodegradation of other hydrocarbons. A total of 13 isolates able to survive on crude as carbon source and produce BSF under aerobic conditions were obtained from all cultures either from sediments of the Gulf of Cadiz MVs or the estuarine system of Ria de Aveiro. Only two isolates failed to produce BSF under anaerobiosis. Sequencing of 16S rRNA gene was used to establish the identification of isolates as Pseudomonas, Bacillus, Ochrobactrum, Brevundimonas, Psychrobacter, Staphylococcus, Marinobacter and Curtobacterium. Most of these genera had never been described as able to produce BSFs under anaerobic conditions. The results obtained in this work allowed to better characterize the deep-sea communities involved in PHs degradation, as well as, to identify strains from deep-sea and estuarine sediments able to degrade PHs and produce BSFs under anaerobic conditions. These bacteria present high biotechnological potential for applications in oxygen-limiting environments, such as, MEOR and bioremediation of environments contaminated with PHs

    Ecological risk assessment of the Miri coast, Sarawak, Borneo: A biogeochemical approach

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    Ecological risk assessment was made along the Miri coast based on trace element concentrations (Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, Rb, Zn) in the seawater, sediments, and aquatic biota (fish, shrimp, crabs, and bivalves). Prevailing major geochemical processes were identified. Contamination and risk assessment indices were estimated. Sediments were contaminated by Cu and Zn, but in the marine life the remaining metals were within the permissible limits set by international and national guidelines
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