基于DOM光谱数据对城市河道复杂污染成因的精细解析

马海川; 任诚; 毛云飞; 周科帆; 竺汉涛; 段酿明; 罗艺; 于旭彪

doi:10.13205/j.hjgc.202502003

基于DOM光谱数据对城市河道复杂污染成因的精细解析

doi: 10.13205/j.hjgc.202502003

1. 宁波大学土木工程与地理环境学院, 浙江宁波 315000;
2. 宁波市城市排水有限公司, 浙江宁波 315000;
3. 浙江农林大学环境与资源学院, 杭州 311300

基金项目:

宁波市重大科技任务攻关项目(2022Z241)

宁波市重大科技任务攻关项目(2021Z104)

国家自然科学基金项目(41977152)

宁波市公益性科技计划项目(2022S115)

详细信息

作者简介:
马海川(2000-),男,硕士研究生,主要研究方向为流域水污染溯源。mhc939@outlook.com

通讯作者:
于旭彪(1981-),男,教授,主要研究方向为水污染控制理论与技术。yuxubiao@nbu.edu.cn

计量
- 文章访问数: 126
- HTML全文浏览量: 31
- PDF下载量: 5
- 被引次数: 0
出版历程
- 收稿日期: 2024-07-04
- 录用日期: 2024-12-20
- 修回日期: 2024-11-09

Fine resolution of complex pollution sources in urban river channels based on DOM spectral data

1. School of Civil & Environmental Engineering and Geography Science, Ningbo University, Ningbo 315000, China;
2. Ningbo Urban Drainage Co., Ltd., Ningbo 315000, China;
3. School of Environmental and Resource Sciences, Zhejiang A&F University, Hangzhou 311300, China

摘要

摘要: 城市河道水质提升面临水体流动性差、污染源影响复杂等系列问题,是现阶段水环境提升工作中的难点之一。为了实现对城市河道污染成因的精细解析,保障治理策略的精准可靠,以宁波市典型城市河道为例,运用三维荧光-平行因子技术(EEM-PARAFAC)分析水体溶解性有机质(DOM)组成特征,探讨城市河道水体污染的季节性差异,及在复杂污染条件下的快速溯源机制。结果表明:该河道表现为高营养盐污染特征,氨氮、总氮和总磷的平均浓度分别为(2.53±1.16),(6.17±1.57),(0.40±0.15) mg/L,而少雨季节水体中营养盐的平均浓度是多雨季节的1.44~1.72倍。表征DOM腐殖化程度的HIX和SUVA₂₅₄指示少雨季节水体中自生源污染物累积明显,而营养盐浓度与类蛋白质荧光组分(r=0.07, P>0.05)的相关性远低于类腐殖质荧光组分(r=0.58, P<0.001),表明农业面源等污染的程度显著高于生活污水的影响,这与近年来该市持续的截污纳管措施密切相关。进一步地,通过比对主要污染物与EEM-PARAFAC荧光组分的时空分布差异,确认了上游河段氮、磷浓度异常升高与农田尾水排放的直接关联,排除了下游居民区河段污染物升高的生活污水影响可能,体现出DOM光谱数据作为辅助污染成因判定的重要意义。鉴于DOM光谱数据所含有的丰富污染源信息和其简便的测试过程,该研究可对我国城市河道水质改善提供切实可靠支撑。
- 溶解性有机质 /
- EEM-PARAFAC技术 /
- 城市河道污染 /
- 污染源解析 /
- 水质管理
Abstract: Improving urban river water quality is fraught with challenges, such as poor water flow and complex pollution sources, making it a significant difficulty in current water environment enhancement efforts. To achieve a nuanced analysis of the causes of urban river pollution and ensure the precision and reliability of remediation strategies, this study focused on a typical urban river in Ningbo City. Employing three-dimensional fluorescence-parallel factor analysis (EEM-PARAFAC) to examine the composition characteristics of dissolved organic matter (DOM) in the water, this research investigated the seasonal variations in urban river pollution and the rapid source-tracing mechanisms under complex pollution conditions. The findings revealed that the river exhibited high nutrient pollution, with average concentrations of ammonia nitrogen, total nitrogen, and total phosphorus at (2.53±1.16), (6.17±1.57), and (0.40±0.15) mg/L, respectively. During the dry season, the average nutrient concentrations in the water were 1.44 to 1.72 times higher than those in the wet season. Indicators of DOM humification degree, HIX, and SUVA₂₅₄, suggested a significant accumulation of autochthonous pollutants in the water during the dry season. The correlation between nutrient salts concentrations and protein-like fluorescent components (r=0.07, P > 0.05) was much lower than that with humic-like fluorescent components (r=0.58, P<0.001). This indicated that agricultural non-point source pollution was significantly higher than the impact of domestic sewage, closely linked to the ongoing implementation of sewage interception measures in recent years. Moreover, by comparing the spatial and temporal distribution differences of major pollutants and EEM-PARAFAC fluorescent components, it was confirmed that the abnormal increase in nitrogen and phosphorus concentrations in the upstream river section was directly related to the discharge of farmland tailwater, eliminating the possibility of domestic sewage influencing the downstream residential river section. This underscored the importance of DOM spectral data in assisting the determination of pollution causes. Given the extensive pollution source information contained in DOM spectral data and its straightforward testing process, the research can provide substantial support for improving the water quality of urban rivers in China.
- dissolved organic matter /
- EEM-PARAFAC technology /
- river pollution /
- pollution source apportionment /
- water quality management

HTML全文

参考文献(55)

[1]	潘世兵, 曹利平, 张建立. 中国水质管理的现状、问题及挑战[J]. 水资源保护, 2005(2): 59-62. PAN S B, CAO L P, ZHANG J L. The status, problems, and challenges of water quality management in China[J]. Water Resources Protection, 2005 (2): 59-62.
[2]	杨柳. 长三角典型区域城镇化对平原河网水系及其调蓄能力的影响[D]. 南京:南京大学, 2017. YANG L. The impact of urbanization in typical areas of the Yangtze River Delta on the water system of the plain river network and its regulation capacity[D]. Nanjing: Nanjing University, 2017.
[3]	纪桂霞, 任振兴, 杨继柏. 城市河道水体富营养化污染特征分析[J]. 上海理工大学学报, 2022, 44(5): 502-507. JI G X, REN Z X, YANG J B. Analysis of eutrophication pollution characteristics in urban river water[J]. Journal of Shanghai University of Science and Technology, 2022, 44(5): 502-507.
[4]	陈玉辉. 典型城市黑臭河道治理后的富营养化分析与预测研究[D]. 上海:华东师范大学, 2013. CHEN Y H. Analysis and prediction of eutrophication after the treatment of typical urban black-odor rivers[D]. Shanghai: East China Normal University, 2013.
[5]	KHANDELWAL A, CASTILLO T, GONZÁLEZ-PINZÓN R. Development of the Navigator: a Lagrangian sensing system to characterize surface freshwater ecosystems[J]. Water Research, 2023, 245: 120577.
[6]	KWON Y S, PYO J, KWON Y H, et al. Drone-based hyperspectral remote sensing of cyanobacteria using vertical cumulative pigment concentration in a deep reservoir[J]. Remote Sensing of Environment, 2020, 236: 111517.
[7]	陈超, 张洪星, 张海涛, 等. 多方法协同的水下排污口排查技术体系应用[J]. 环境工程, 2024,42(5):139-146. CHEN C, ZHANG H X, ZHANG H T, et al. Application of multi-method collaborative underwater sewage outfall detection technology system[J]. Environmental Engineering, 2024,42(5):139-146.
[8]	HE J, WU X, ZHI G, et al. Fluorescence characteristics of DOM and its influence on water quality of rivers and lakes in the Dianchi Lake basin[J]. Ecological Indicators, 2022, 142: 109088.
[9]	ZHOU Y, HE D, HE C, et al. Spatial changes in molecular composition of dissolved organic matter in the Yangtze River Estuary: implications for the seaward transport of estuarine DOM[J]. Science of the Total Environment, 2021, 759: 143531.
[10]	LIN H, BARTLETT S L, GUO L. Distinct variations in fluorescent DOM components along a trophic gradient in the lower Fox River-Green Bay as characterized using one-sample PARAFAC approach[J]. Science of The Total Environment, 2023, 902: 165891.
[11]	BAI Y, ZHANG S, MU E, et al. Characterizing the spatiotemporal distribution of dissolved organic matter (DOM) in the Yongding River Basin: insights from flow regulation[J]. Journal of Environmental Management, 2023, 325: 116476.
[12]	DERRIEN M, YANG L, HUR J. Lipid biomarkers and spectroscopic indices for identifying organic matter sources in aquatic environments: a review[J]. Water Research, 2017, 112: 58-71.
[13]	RETELLETTI BROGI S, HA S Y, KIM K, et al. Optical and molecular characterization of dissolved organic matter (DOM) in the Arctic ice core and the underlying seawater (Cambridge Bay, Canada): implication for increased autochthonous DOM during ice melting[J]. Science of the Total Environment, 2018, 627: 802-811.
[14]	LOZOVIK P A, MOROZOV A K, ZOBKOV M B, et al. Allochthonous and autochthonous organic matter in surface waters in Karelia[J]. Water Resources, 2007, 34(2): 204-216.
[15]	LIU Q, JIANG Y, TIAN Y, et al. Impact of land use on the DOM composition in different seasons in a subtropical river flowing through a region undergoing rapid urbanization[J]. Journal of Cleaner Production, 2019, 212: 1224-1231.
[16]	ZHANG Y, ZHANG B, HE Y, et al. DOM as an indicator of occurrence and risks of antibiotics in a city-river-reservoir system with multiple pollution sources[J]. Science of the Total Environment, 2019, 686: 276-289.
[17]	MENG F, HUANG G, YANG X, et al. Identifying the sources and fate of anthropogenically impacted dissolved organic matter (DOM) in urbanized rivers[J]. Water Research, 2013, 47(14): 5027-5039.
[18]	刘传旸, 柴一荻, 徐宪根, 等. 南方某河水质荧光指纹特征及污染溯源[J]. 光谱学与光谱分析, 2021, 41(7): 2142-2147. LIU C Y, CHAI Y D, XU X G, et al. Fluorescence fingerprint characteristics of water quality and pollution tracing in a southern river[J]. Spectroscopy and Spectral Analysis, 2021, 41(7): 2142-2147.
[19]	STEDMON C A, MARKAGER S, BRO R. Tracing dissolved organic matter in aquatic environments using a new approach to fluorescence spectroscopy[J]. Marine Chemistry, 2003, 82(3): 239-254.
[20]	位梦姣. 基于水化学特征和荧光指纹的污染物源解析方法研究及其应用[D]. 杨凌:西北农林科技大学, 2020. WEI M J. Study on pollution source analysis methods based on water chemical characteristics and fluorescence fingerprints and their applications[D]. Yangling: Northwest A&F University, 2020.
[21]	褚克坚, 仇凯峰, 贾永志, 等. 长江下游丘陵库群河网地区城市水生态文明评价指标体系研究[J]. 四川环境, 2015, 34(6): 44-51. CHU K J, QIU K F, JIA Y Z, et al. Study on the evaluation index system of urban water ecological civilization in the hilly reservoir river network area of the lower Yangtze River[J]. Sichuan Environment, 2015, 34(6): 44-51.
[22]	陈梦倢, 徐国津, 高占国, 等. "十三五"期间宁波市生态环境质量状况及变化趋势[J]. 中国环境监测, 2023, 39(1): 38-44. CHEN M Q, XU G J, GAO Z G, et al. Ecological environment quality status and trends of change in Ningbo City during the "13th Five-Year Plan" period[J]. China Environmental Monitoring, 2023, 39(1): 38-44.
[23]	宁波市水利局.2022宁波市水资源公报[R]. 2023. Ningbo Water Resources Bureau. 2022 Ningbo City Water Resources Bulletin[R].2023.
[24]	宁波市水利局.2023宁波市水资源公报[R].2024. Ningbo Water Resources Bureau. 2023 Ningbo City Water Resources Bulletin[R]. 2024.
[25]	国家环境保护总局. 水和废水监测分析方法[M]. 4版. 北京:中国环境科学出版社,2002. State Environmental Protection Administration. Water and wastewater monitoring analysis methods[M]. 4th edition.Beijing: China Environmental Science Press, 2002.
[26]	HUGUET A, VACHER L, RELEXANS S, et al. Properties of fluorescent dissolved organic matter in the Gironde Estuary[J]. Organic Geochemistry, 2009, 40(6): 706-719.
[27]	WEISHAAR J L, AIKEN G R, BERGAMASCHI B A, et al. Evaluation of specific ultraviolet absorbance as an indicator of the chemical composition and reactivity of dissolved organic carbon[J]. Environmental Science & Technology, 2003, 37(20): 4702-4708.
[28]	MORRIS D M, GEMEINHARDT T R, GOSCH N J C, et al. Water quality during two high-flow years on the lower Missouri River: the effects of reservoir and tributary contributions[J]. River Research and Applications, 2014, 30(8): 1024-1033.
[29]	王瑞, 代丹, 张弛, 等. 太湖不同介质电导率时空变化特征[J]. 环境科学, 2019, 40(10): 4469-4477. WANG R, DAI D, ZHANG C, et al. Spatiotemporal variation characteristics of electrical conductivity in different media of Taihu Lake[J]. Environmental Science, 2019, 40(10): 4469-4477.
[30]	ZHENG L, SONG Z, MENG P, et al. Seasonal characterization and identification of dissolved organic matter (DOM) in the Pearl River, China[J]. Environmental Science and Pollution Research, 2016, 23(8): 7462-7469.
[31]	朱秋丽. 基于BP神经网络—模糊数学的汾河太原城区段黑臭评价研究[D]. 太原:太原理工大学, 2010. ZHU Q L. Evaluation of Black-odor Condition in the Fen River Taiyuan Urban Section Based on BP Neural Network and Fuzzy Mathematics[D]. Taiyuan: Taiyuan University of Technology, 2010.
[32]	MURPHY K R, STEDMON C A, WENIG P, et al. OpenFluor-an online spectral library of auto-fluorescence by organic compounds in the environment[J]. Analytical Methods, 2014, 6(3): 658-661.
[33]	GUÉGUEN C, CUSS C W, CASSELS C J, et al. Absorption and fluorescence of dissolved organic matter in the waters of the Canadian Arctic Archipelago, Baffin Bay, and the Labrador Sea[J]. Journal of Geophysical Research: Oceans, 2014, 119(3): 2034-2047.
[34]	YAMASHITA Y, SCINTO L J, MAIE N, et al. Dissolved organic matter characteristics across a subtropical wetland’s landscape: application of optical properties in the assessment of environmental dynamics[J]. Ecosystems, 2010, 13(7): 1006-1019.
[35]	STEDMON C A, MARKAGER S. Tracing the production and degradation of autochthonous fractions of dissolved organic matter by fluorescence analysis[J]. Limnology and Oceanography, 2005, 50(5): 1415-1426.
[36]	OSBURN C L, STEDMON C A. Linking the chemical and optical properties of dissolved organic matter in the Baltic-North Sea transition zone to differentiate three allochthonous inputs[J]. Marine Chemistry, 2011, 126(1/2/3/4): 281-294.
[37]	YAMASHITA Y, BOYER J N, JAFFÉ R. Evaluating the distribution of terrestrial dissolved organic matter in a complex coastal ecosystem using fluorescence spectroscopy[J]. Continental Shelf Research, 2013, 66: 136-144.
[38]	BHATTACHARYA R, OSBURN C L. Chromophoric dissolved organic matter composition and load from a coastal river system under variable flow regimes[J]. Science of the Total Environment, 2021, 760: 143414.
[39]	FELLMAN J B, HOOD E, SPENCER R G M. Fluorescence spectroscopy opens new windows into dissolved organic matter dynamics in freshwater ecosystems: a review[J]. Limnology and Oceanography, 2010, 55(6): 2452-2462.
[40]	KOWALCZUK P, TILSTONE G H, ZABLOCKA M, et al. Composition of dissolved organic matter along an Atlantic Meridional Transect from fluorescence spectroscopy and parallel factor analysis[J]. Marine Chemistry, 2013, 157: 170-184.
[41]	BRYM A, PAERL H W, MONTGOMERY M T, et al. Optical and chemical characterization of base-extracted particulate organic matter in coastal marine environments[J]. Marine Chemistry, 2014, 162: 96-113.
[42]	STEDMON C A, THOMAS D N, GRANSKOG M, et al. Characteristics of dissolved organic matter in baltic coastal sea ice: allochthonous or autochthonous origins?[J]. Environmental Science & Technology, 2007, 41(21): 7273-7279.
[43]	MURPHY K R, RUIZ G M, DUNSMUIR W T M, et al. Optimized parameters for fluorescence-based verification of ballast water exchange by ships[J]. Environmental Science & Technology, 2006, 40(7): 2357-2362.
[44]	YANG L, HONG H, CHEN C T A, et al. Chromophoric dissolved organic matter in the estuaries of populated and mountainous Taiwan[J]. Marine Chemistry, 2013, 157: 12-23.
[45]	YANG L Y, CHENG Q, ZHUANG W E, et al. Seasonal changes in the chemical composition and reactivity of dissolved organic matter at the land-ocean interface of a subtropical river[J]. Environmental Science and Pollution Research, 2019, 26(24): 24595-24608.
[46]	MA Y, MAO R, LI S. Hydrological seasonality largely contributes to riverine dissolved organic matter chemical composition: insights from EEM-PARAFAC and optical indicators[J]. Journal of Hydrology, 2021, 595: 125993.
[47]	OHNO T. Fluorescence inner-filtering correction for determining the humification index of dissolved organic matter[J]. Environmental Science & Technology, 2002, 36(4): 742-746.
[48]	宋庆斌, 王政, 陈明龙, 等. 基于有色溶解性有机质(CDOM)解析陆源污染物在东海区域的分布特征[J]. 环境科学学报, 2021, 41(5): 1950-1959. SONG Q B, WANG Z, CHEN M L, et al. Analysis of terrestrial pollutants’ distribution characteristics in the East China Sea region based on colored dissolved organic matter (CDOM)[J]. Acta Scientiae Circumstantiae, 2021, 41(5): 1950-1959.
[49]	徐力刚, 王晓龙, 崔锐, 等. 不同农业种植方式对土壤中硝态氮淋失的影响研究[J]. 土壤, 2012, 44(2): 225-231. XU L G, WANG X L, CUI R, et al. Study on the effect of different agricultural planting methods on nitrate nitrogen leaching loss in soil[J]. Soil, 2012, 44(2): 225-231.
[50]	LUSK M G, TOOR G S. Biodegradability and molecular composition of dissolved organic nitrogen in urban stormwater runoff and outflow water from a stormwater retention pond[J]. Environmental Science & Technology, 2016, 50(7): 3391-3398.
[51]	SINGH S, DUTTA S, INAMDAR S. Land application of poultry manure and its influence on spectrofluorometric characteristics of dissolved organic matter[J]. Agriculture, Ecosystems & Environment, 2014, 193: 25-36.
[52]	张甫娜. 南方沿海某市污水收集系统提质增效对策研究[D]. 哈尔滨: 哈尔滨工业大学, 2019. ZHANG F N. Research on Countermeasures for Improving the Quality and Efficiency of the Sewage Collection System in a Coastal City in Southern China[D]. Harbin: Harbin Institute of Technology, 2019.
[53]	王齐磊. 三峡库区典型农业小流域溶解性有机质(DOM)的地球化学特征分析[D]. 重庆:西南大学, 2016. WANG Q L. Geochemical Characteristic Analysis of Dissolved Organic Matter (DOM) in Typical Agricultural Small Watersheds in the Three Gorges Reservoir Area[D]. Chongqing: Southwest University, 2016.
[54]	朱弈, 陈浩, 丁国平, 等. 城镇与城郊污染河道中DOM成分分布与影响因素[J]. 环境科学, 2021, 42(11): 5264-5274. ZHU Y, CHEN H, DING G P, et al. Distribution and influencing factors of DOM components in polluted urban and suburban rivers[J]. Environmental Science, 2021, 42(11): 5264-5274.
[55]	余浩, 杨凯, 王晓, 等. 基于三维荧光-平行因子分析和自组织神经网络分析汛期上游来水对新汴河上覆水影响[J]. 环境化学, 2023, 42(12): 4384-4391. YU H, YANG K, WANG X, et al. Impact of upstream runoff during flood season on the overlying water of the Xinbian River based on three-dimensional fluorescence-parallel factor analysis and self-organizing neural network analysis[J]. Environmental Chemistry, 2023, 42(12): 4384-4391.