메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색

논문 기본 정보

자료유형
학술저널
저자정보
Han, Young-Soo (Korea Institute of Geoscience and Mineral Resources) Demond, Avery H. (Department of Civil and Environmental Engineering, University of Michigan) Hayes, Kim F. (Department of Civil and Environmental Engineering, University of Michigan)
저널정보
한국지하수토양환경학회 지하수토양환경 지하수토양환경 제20권 제5호
발행연도
2015.1
수록면
1 - 10 (10page)

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색

초록· 키워드

오류제보하기
FeS, as a natural reduced iron mineral, has been recognized to be a viable reactive material for As(III) sequestration in natural and engineered systems. In this study, FeS-coated sand packed columns were tested to evaluate the As(III) removal capacities under anaerobic conditions at pH 5, 7 and 9. The column obtained As(III) removal capacity was then compared with the capacity result obtained from batch reactors. In the comparison, two different approaches were used. The first approach was used the total As(III) removal capacity which method was proved to be useful for interpreting pH 5 system. The second approach was used to consider sorption non-linearity and proved to be useful for interpreting the pH 9. The results demonstrated that a mechanistic understanding of the different removal processes at different pH conditions is important to interpret the column experimental results. At pH 5, where the precipitation of arsenic sulfide plays the major role in the removal of arsenic, the column shows a greater removal efficiency than the batch system due to the continuous dissolution of sulfide and precipitation of arsenic sulfide. At pH 9, where adsorption mainly governs the arsenic removal, the sorption nonlinearity should be considered in the estimation of the column capacity. This study highlighted the importance of understanding reaction mechanism to predict column performance using batch-obtained experimental results.

목차

등록된 정보가 없습니다.

참고문헌 (16)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0