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Long-term temporal-spatial dynamics of marine coastal water quality in the Tolo Harbor,Hong Kong,China 被引量:4
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作者 XUFu-liu K.C.LAM +2 位作者 R.W.Dawson TAOShu y.d.chen 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 2004年第1期161-166,共6页
The long-term temporal and spatial dynamics of marine coastal water quality in Tolo Harbor, Hong Kong were explored. The Harbor is divided into three zones represented as Harbor, Buffer, and Channel Subzones. The time... The long-term temporal and spatial dynamics of marine coastal water quality in Tolo Harbor, Hong Kong were explored. The Harbor is divided into three zones represented as Harbor, Buffer, and Channel Subzones. The time range for the study covers the period from the 1970s to the 1990s. The selected indicators for the comprehensive assessment of water quality consist of physical, chemical and biological aspects, including suspended solids(SS), Secchi disk depth(SD), 5-day biochemical oxygen demand(BOD\-5), total nitrogen(TN), total phosphorus(TP), faecal coliform, chlorophyll-a(Chl-a), and the number of red tide occurrences. The results indicated the presence of obvious temporal and spatial trends with regard to changes in water quality. Spatially, water quality in the Channel Subzone is the best, while that in the Harbor Subzone is the worst. On a temporal basis, the average trend from bad to good was 1980s>1990s>1970s as indicated by most of the selected water quality indicators. Water quality during the late 1980s reached its worst level with the lowest SD, the highest BOD\-5, TN, TP, Chl-a concentrations, and the number of red tide occurrences. These long-term temporal-spatial water quality trends were also found in other studies of the Tolo Harbor. The large quantity of pollutants produced as a result of increasing population, industrial and commercial actives, and urbanization and industrialization trends in both Shatin and Tai Po seem to be primarily responsible for the changes in marine coastal water quality. 展开更多
关键词 temporal-spatial dynamics water quality INDICATORS pollution load Tolo Harbor
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Line-of-shower trigger method to lower energy threshold for GRB detection using LHAASO-WCDA
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作者 F.Aharonian Q.An +257 位作者 Axikegu L.X.Bai Y.X.Bai Y.W.Bao D.Bastieri X.J.Bi Y.J.Bi H.Cai J.T.Cai Z.Cao Z.Cao J.Chang J.F.Chang X.C.Chan B.M.Chen J.Chen L.Chen L.Chen L.Chen M.J.Chen M.L.Chen Q.H.Chen S.H.Chen S.Z.Chen T.L.Chen X.L.Chen Y.Chen N.Chen y.d.chen S.W.Cui X.H.Cui Y.D.Cui B.Z.Dai H.L.Dai Z.G.Dai Danzengluobu D.della Volpe B.D’Ettorre Piazzoli X.J.Don J.H.Fan Y.Z.Fan Z.X.Fan J.Fang K.Fan C.F.Feng L.Feng S.H.Fen Y.L.Feng B.Gao C.D.Gao Q.Gao W.Gao M.M.Ge L.S.Gen G.H.Gong Q.B.Gou M.H.Gu J.G.Guo X.L.Guo Y.Q.Guo Y.Y.Guo Y.A.Han H.H.He H.N.He J.C.He S.L.He X.B.He Y.He M.Heller Y.K.Hor C.Hou X.Hou H.B.Hu S.Hu S.C.Hu X.J.Hu D.H.Huang Q.L.Huan W.H.Huang X.T.Huang Z.C.Huang F.Ji X.L.Ji H.Y.Jia K.Jiang Z.J.Jiang C.Jin D.Kuleshov K.Levochkin B.B.Li C.Li C.Li F.Li H.B.Li H.C.Li H.Y.Li J.Li K.Li W.L.Li X.Li X.Li X.R.Li Y.Li Y.Z.Li Z.Li Z.Li E.W.Liang Y.F.Liang S.J.Lin B.Liu C.Liu D.Liu H.Liu H.D.Liu J.Liu J.L.Liu J.S.Liu J.Y.Liu M.Y.Liu R.Y.Liu S.M.Liu W.Liu Y.N.Liu Z.X.Liu W.J.Long R.Lu H.K.Lv B.Q.Ma L.L.Ma X.H.Ma J.R.Mao A.Masood W.Mitthumsiri T.Montaruli Y.C.Nan B.Y.Pang P.Pattarakijwanich Z.Y.Pei M.Y.Qi D.Ruffolo V.Rulev A.Sáiz L.Shao O.Shchegolev X.D.Shen J.R.Shi H.C.Song Yu.V.Stenkin V.Stepanov Q.N.Sun X.N.Sun Z.B.Sun P.H.T.Tam Z.B.Tang W.W.Tian B.D.Wan C.Wang H.Wang H.G.Wang J.C.Wang J.S.Wang L.P.Wang L.Y.Wan R.N.Wang W.Wang W.Wang X.G.Wang X.J.Wan X.Y.Wang Y.D.Wan Y.J.Wan Y.P.Wang Z.Wang Z.Wang Z.H.Wang Z.X.Wang D.M.Wei J.J.Wei Y.J.Wei T.Wen C.Y.Wu H.R.Wu S.Wu W.X.Wu X.F.Wu S.Q.Xi J.Xia J.J.Xia G.M.Xiang G.Xiao H.B.Xiao G.G.Xin Y.L.Xin Y.Xing D.L.Xu R.X.Xu L.Xue D.H.Yan C.W.Yang F.F.Yang J.Y.Yang L.L.Yang M.J.Yan R.Z.Yang S.B.Yang Y.H.Yao Z.G.Yao Y.M.Ye L.Q.Yin N.Yin X.H.You Z.Y.You Y.H.Yu Q.Yuan H.D.Zeng T.X.Zeng W.Zeng Z.K.Zeng M.Zha X.X.Zhai B.B.Zhang H.M.Zhang H.Y.Zhang J.L.Zhang J.W.Zhang L.Zhang L.Zhang L.X.Zhang P.F.Zhang P.P.Zhang R.Zhang S.R.Zhang S.S.Zhan X.Zhang X.P.Zhan Y.Zhan Y.Zhang Y.F.Zhang Y.L.Zhan B.Zhao J.Zhao L.Zhao L.Z.Zhao S.P.Zhao F.Zheng Y.Zheng B.Zhou H.Zhou J.N.Zhou P.Zhou R.Zhou X.X.Zhou C.G.Zhu F.R.Zhu H.Zhu K.J.Zhu X.Zuo The LHAASO Collaboration 《Radiation Detection Technology and Methods》 CSCD 2021年第4期531-541,共11页
Purpose Observation of high energy and very high emission from Gamma Ray Bursts(GRBs)is crucial to study the gigantic explosion and the underline processes.With a large field-of-view and almost full duty cycle,the Wat... Purpose Observation of high energy and very high emission from Gamma Ray Bursts(GRBs)is crucial to study the gigantic explosion and the underline processes.With a large field-of-view and almost full duty cycle,the Water Cherenkov Detector Array(WCDA),a sub-array of the Large High Altitude Air Shower Observatory(LHAASO),is appropriate to monitor the very high energy emission from unpredictable transients such as GRBs.Method Nevertheless,the main issue for an extensive air shower array is the high energy threshold which limits the horizon of the detector.To address this issue a new trigger method is developed in this article to lower the energy threshold of WCDA for GRB observation.Result The proposed method significantly improves the detection efficiency of WCDA for gamma-rays around the GRB direction at 10-300 GeV.The sensitivity of the WCDA for GRB detection with the new trigger method is estimated.The achieved sensitivity of the quarter WCDA array above 10 GeV is comparable with that of Fermi-LAT.The data analysis process and corresponding fluence upper limit for GRB 190719C is presented as an example. 展开更多
关键词 LHAASO WCDA GRB
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