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Spatiotemporal Variations Of Dissolved Organic Matter In Water Of Inflow Rivers Along Chaohu Watershed

Posted on:2022-06-08Degree:MasterType:Thesis
Country:ChinaCandidate:C W NingFull Text:PDF
GTID:2491306542966949Subject:Environmental Engineering
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Dissolved organic matter(DOM)including humic-like,fulvic-like and various water-soluble organic compounds,is the largest organic pool in aquatic ecosystems.The dissolved organic matter in water is composes of allochthonous sources(e.g.runoff and atmospheric deposition)and autochthonous sources(e.g.degradation of phytoplanktons and microorganisms).Dissolved organic matter(DOC)is a proxy for DOM in aquatic ecosystems.The dissolved organic matter,associated closely with the total nitrogen,total phosphorus,biochemical oxygen demand(BOD),chemical oxygen demand(COD)in waters,can be used to mornitor and assess water pollution quickly.The dissolved organic matter plays an important role in nutrient’s biogeochemical cycling in aquatic ecosystms.It could affect the microbial activity dirctly or indirectly,alters the toxicity and bioavailability of heavy metals and links with the transformations of carbon,phosphorus,nitrogen and sulfur.In this study,spatio-temporal variations of dissolved organic matter in water of inflow rivers FL,HB,QY,ZH and NF along Chaohu Watershed were analyzed by using the methods of ultraviolet-visible absorption spectrum(UV-vis)and three-dimensional excitation emission matrix fluorescence spectroscopy combined with parallel factor analysis(EEM-PARAFAC).We obtained the following results and conclusions.(1)The specific ultraviolet absorbance at 254 nm(SUVA254)of DOM in NF River was lower than those in other rivers,while the spectral slope ratio(SR)of NF River was higher than that of HB River.It showed that the inputs of urban runoff reduced the aromaticity of DOM in the water of NF River,but has little effects on their molecular weight.Four humic-like components(C1-C4)include the terrestrial organic matter(C1,C3,and C4),products from microbial degradations(C2)and two protein-like components(C5 and C6)were identified as the main sources of DOM in those Inflow Rivers along Chaohu Watershed.The highest fluorescence index(FI)and biological index(BIX)and lowest humification index(HIX)of DOM indicated main autochthonous sources for the DOM in NF River.The dissolved organic carbon(DOC)and DOM fluorescence components in the river waters varied spatially along with their flow direction.The DOM in waters of FL,HB,QY,and ZH Rivers was from inputs of soil runoff,while that of NF River was mainly from the urban runoff and wastewater treatment plant effluents.(2)There was no seasonal difference in the absorption coefficientα(355)of DOM in HB and NF rivers.SUVA254 values of HB and NF Rivers in high flow period was lower than those in low and normal flow periods,due to the high photodegradation that reduces the aromaticity of DOM during the high flow period.There was no seasonal difference for SR(molecular weight)in HB and NF Rivers.Humic-like components(C1),photodegradation products of terrestrial substance(C3)and two protein-like components(C2 and C4)were identified for the DOM in HB and NF Rivers.No difference for C1 between HB and NF indicated that terrestrial sources were stable during three periods.The protein-like component C2 in NF was higher than that in HB River without seasonal difference,likely associated with stable inputs from wastewater treatment plant effluent.The photodegradation products C3 in NF River showed significant difference seasonally,indicted that terrestrial sources were more sensitive to ray radiation.The protein-like component C4 in HB and NF Rivers during the low water period was higher than those during the high and normal water period,due to the high temperature and thus the metabolism of microorganisms in those periods.The fluorescence components in HB and NF River correlated significant with phosphorus and nitrogen only during low flow period.
Keywords/Search Tags:Chaohu Watershed, Dissolved organic matter, Land use, Ultraviolet-visible spectrum, Parallel factor analysis
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