인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
Abstract This study evaluated the lead (Pb) immobilization efficiency of biochar in contaminated agricultural soil. The biochar was produced from a range of major biomass residues and pyrolyzed under well-controlled conditions. Ten different types of standard biochar samples were derived from five different feedstocks (i.e., softwood, miscanthus straw, rice husk, oilseed rape straw, wheat straw) and pyrolyzed at 550 ℃ and 700 ℃. Pb-contaminated soil near an abandoned mine was incubated with 2.5% (w w − 1 ) of biochar. Incubation was conducted for various durations at room temperature under both short-term (21 days) and long-term (214 days) conditions. This variation explicitly accounted for the simulated microplastic contamination during the long-term incubation period. A novel framework has been developed to predict the long-term immobilization effect of various biochar types using a machine-learning approach, following the successful identification of optimal biochar implementations. This prediction method utilizes a small on-field dataset by employing a data augmentation approach, showcasing an innovative approach to forecasting the effects of different biochar types over time. After the incubation period, soil samples were analyzed for their chemical properties. As a result, oil seed rape biochar was the highest in pH, EC, exchangeable Ca 2+ , Mg 2+ , and K + , total nitrogen content, soil organic matter content, and available phosphate. In return, OSR 700 treated soils showed the highest content of exchangeable cations and the lowest content of available Pb after the incubation period. The most efficient biochar for immobilizing lead (Pb) in soil appears to be OSR 700, based on the available evidence.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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