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快速城市化区河流温室气体排放的时空特征及驱动因素
引用本文:刘婷婷,王晓锋,袁兴中,龚小杰,侯春丽.快速城市化区河流温室气体排放的时空特征及驱动因素[J].环境科学,2019,40(6):2827-2839.
作者姓名:刘婷婷  王晓锋  袁兴中  龚小杰  侯春丽
作者单位:长江上游湿地科学研究重庆市重点实验室,重庆401331;重庆师范大学地理与旅游学院,重庆 401331;长江上游湿地科学研究重庆市重点实验室,重庆401331;重庆师范大学地理与旅游学院,重庆 401331;重庆大学煤矿灾害动力学与控制国家重点实验室,重庆400030;重庆大学资源及环境科学学院,重庆400030;长江上游湿地科学研究重庆市重点实验室,重庆401331;重庆师范大学生命科学学院,重庆401331
基金项目:国家自然科学基金项目(41807321);重庆市基础研究与前沿探索项目(cstc2018jcyjAX0672);重庆市教委研究项目(KJQN201800530);重庆师范大学博士科研启动项目(17XLB023)
摘    要:河流是大气温室气体重要的排放源,近十多年来全球城市化导致河流生态系统各要素发生改变,对河流水体温室气体排放产生影响.为研究快速城市化区不同土地利用方式下河流温室气体排放的时空特征及其影响因素,采用薄边界层模型法,于2014年9月(秋季)和12月(冬季)及2015年3月(春季)和6月(夏季)的晴天对重庆市区内梁滩河干、支流水体pCO_2、CH_4、N_2O溶存浓度进行监测.结果表明,梁滩河干、支流水体pCO_2范围为(23. 38±34. 89)~(1395. 33±55. 45) Pa、CH_4溶存浓度范围(65. 09±28. 09)~(6 021. 36±94. 36) nmol·L~(-1)、N_2O溶存浓度范围为(29. 47±5. 16)~(510. 28±18. 34)nmol·L~(-1); CO_2、CH_4和N_2O排放通量分别为-6. 1~786. 9、0. 31~27. 62和0. 06~1. 08 mmol·(m~2·d)~(-1);流域水体温室气体浓度空间格局与快速城市化带来的污染负荷空间梯度吻合,干流温室气体浓度与通量从上游向下游均呈先增加后降低,在城市化速度最快的中游出现峰值,其中城市河段CO_2和CH_4浓度约为非城市河段的2倍,同时支流水体自上游农业区向下游城市区呈显著增加;由于受到降雨、温度、外源输入的综合影响,河流CO_2排放通量呈秋季冬季夏季春季的季节模式,CH_4排放通量春季最高夏季最低,N_2O排放通量季节差异不显著.流域水体碳、氮含量均较高,水体CO_2的产生和排放不受生源要素限制,但受水温、pH、DO、叶绿素a等生物代谢因子影响; CH_4的产生和排放受水体碳、氮、磷含量和外源污水输入的共同驱动; N_2O的产生和排放主要受高N_2O浓度的城市污水排放影响.本研究认为流域快速城市化加快了河流水体温室气体排放,形成排放热源,因此城市河流温室气体排放对全球河流排放通量的贡献可能被忽视,在未来研究中应受到更多关注.

关 键 词:温室气体  快速城市化区  污染性河流  时空特征  影响因素
收稿时间:2018/10/26 0:00:00
修稿时间:2019/1/2 0:00:00

Spatial-temporal Characteristics and Driving Factors of Greenhouse Gas Emissions from Rivers in a Rapidly Urbanizing Area
LIU Ting-ting,WANG Xiao-feng,YUAN Xing-zhong,GONG Xiao-jie and HOU Chun-li.Spatial-temporal Characteristics and Driving Factors of Greenhouse Gas Emissions from Rivers in a Rapidly Urbanizing Area[J].Chinese Journal of Environmental Science,2019,40(6):2827-2839.
Authors:LIU Ting-ting  WANG Xiao-feng  YUAN Xing-zhong  GONG Xiao-jie and HOU Chun-li
Institution:Chongqing Key Laboratory of Wetland Science Research of the Upper Yangtze River, Chongqing 401331, China;College of Geography and Tourism, Chongqing Normal University, Chongqing 401331, China,Chongqing Key Laboratory of Wetland Science Research of the Upper Yangtze River, Chongqing 401331, China;College of Geography and Tourism, Chongqing Normal University, Chongqing 401331, China,Chongqing Key Laboratory of Wetland Science Research of the Upper Yangtze River, Chongqing 401331, China;College of Geography and Tourism, Chongqing Normal University, Chongqing 401331, China;State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing University, Chongqing 400030, China;College of Resource and Environmental Science, Chongqing University, Chongqing 400030, China,Chongqing Key Laboratory of Wetland Science Research of the Upper Yangtze River, Chongqing 401331, China;College of Geography and Tourism, Chongqing Normal University, Chongqing 401331, China and Chongqing Key Laboratory of Wetland Science Research of the Upper Yangtze River, Chongqing 401331, China;College of Life Sciences, Chongqing Normal University, Chongqing 401331, China
Abstract:Rivers play an important role in greenhouse gas emissions. Over the past decade, because of global urbanization trends, rapid land use changes have led to changes in river ecosystems that have had a stimulating effect on the greenhouse gas production and emissions. Presently, there is an urgent need for assessments of the greenhouse gas concentrations and emissions in watersheds. Therefore, this study was designed to evaluate river-based greenhouse gas emissions and their spatial-temporal features as well as possible impact factors in a rapidly urbanizing area. The specific objectives were to investigate how river greenhouse gas concentrations and emission fluxes are responding to urbanization in the Liangtan River, which is not only the largest sub-basin but also the most polluted one in Chongqing City. The thin layer diffusion model method was used to monitor year-round concentrations of pCO2, CH4, and N2O in September and December 2014, and March and June 2015. The pCO2 range was (23.38±34.89)-(1395.33±55.45) Pa, and the concentration ranges of CH4 and N2O were (65.09±28.09)-(6021.36±94.36) nmol·L-1 and (29.47±5.16)-(510.28±18.34) nmol·L-1, respectively. The emission fluxes of CO2, CH4, and N2O, which were calculated based on the method of wind speed model estimations, were -6.1-786.9, 0.31-27.62, and 0.06-1.08 mmol·(m2·d)-1, respectively. Moreover, the CO2 and CH4 emissions displayed significant spatial differences, and these were roughly consistent with the pollution load gradient. The greenhouse gas concentrations and fluxes of trunk streams increased and then decreased from upstream to downstream, and the highest value was detected at the middle reaches where the urbanization rate is higher than in other areas and the river is seriously polluted. As for branches, the greenhouse gas concentrations and fluxes increased significantly from the upstream agricultural areas to the downstream urban areas. The CO2 fluxes followed a seasonal pattern, with the highest CO2 emission values observed in autumn, then successively winter, summer, and spring. The CH4 fluxes were the highest in spring and the lowest in summer, while N2O flux seasonal patterns were not significant. Because of the high carbon and nitrogen loads in the basin, the CO2 products and emissions were not restricted by biogenic elements, but levels were found to be related to important biological metabolic factors such as the water temperature, pH, DO, and chlorophyll a. The carbon, nitrogen, and phosphorus content of the water combined with sewage input influenced the CH4 products and emissions. Meanwhile, N2O production and emissions were mainly found to be driven by urban sewage discharge with high N2O concentrations. Rapid urbanization accelerated greenhouse gas emissions from the urban rivers, so that in the urban reaches, CO2/CH4 fluxes were twice those of the non-urban reaches, and all over the basin N2O fluxes were at a high level. These findings illustrate how river basin urbanization can change aquatic environments and aggravate allochthonous pollution inputs such as carbon, nitrogen, and phosphorus, which in turn can dramatically stimulate river-based greenhouse gas production and emissions; meanwhile, spatial and temporal differences in greenhouse gas emissions in rivers can lead to the formation of emission hotspots.
Keywords:greenhouse gases  rapidly urbanization areas  polluted river  spatial-temporal characteristics  influence factors
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