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2020—2022年全国入海河流总氮浓度时空特征
引用本文:解鑫,李文攀,李晓明,霍晓芹,葛淼,王蕾.2020—2022年全国入海河流总氮浓度时空特征[J].中国环境监测,2023,39(6):90-97.
作者姓名:解鑫  李文攀  李晓明  霍晓芹  葛淼  王蕾
作者单位:中国地质大学(北京)水资源与环境学院, 北京 100083;中国环境监测总站, 国家环境保护环境监测质量控制重点实验室, 北京 100012;重庆市生态环境监测中心, 重庆 400120;陕西省环境监测中心站, 陕西 西安 710000
摘    要:根据全国230个入海河流断面2020—2022年总氮质量浓度监测数据,基于时间序列统计方法和空间聚类方法,分析了总氮浓度的时空分布特征。结果显示:2020—2022年全国入海河流总氮年均质量浓度逐年上升,从(3.24±2.20)mg/L上升到(3.92±3.30)mg/L;年内总氮浓度呈现冬高夏低、春秋居中的V形季节变化规律。空间聚类分析表明:总氮质量浓度从北到南可分为4个有较明显差异的区域,分别为北方高值区(包括辽东丘陵西部、辽西丘陵、山东丘陵),北方次高值区(包括环渤海京津冀地区、苏北平原),华东区(包括长江中下游平原区、上海市、浙江省、福建省),华南区(包括广东省、广西壮族自治区、海南省)。总氮年均质量浓度分布为北方高值区>北方次高值区>华东区>华南区。北方高值区的过高总氮浓度对全国总氮浓度均值提供了超比例的贡献。同时,北方高值区和北方次高值区贡献了2020—2023年全国总氮浓度92%的增幅。此外,从空间分布上看,越往北,总氮浓度的V形季节变化规律越明显。

关 键 词:入海河流  总氮  时空分布  聚类分析
收稿时间:2023/6/8 0:00:00
修稿时间:2023/7/27 0:00:00

Spatiotemporal Characteristics of Total Nitrogen Concentrations in Rivers Entering the Sea of China from 2020 to 2022
XIE Xin,LI Wenpan,LI Xiaoming,HUO Xiaoqin,GE Miao,WANG Lei.Spatiotemporal Characteristics of Total Nitrogen Concentrations in Rivers Entering the Sea of China from 2020 to 2022[J].Environmental Monitoring in China,2023,39(6):90-97.
Authors:XIE Xin  LI Wenpan  LI Xiaoming  HUO Xiaoqin  GE Miao  WANG Lei
Institution:School of Water Resources and Environment, China University of Geosciences, Beijing 100083, China;State Environmental Protection Key Laboratory of Quality Control in Environmental Monitoring, China National Environmental Monitoring Center, Beijing 100012, China;Chongqing Ecological and Environmental Monitoring Center, Chongqing 400120, China; Shaanxi Environmental Monitoring Center, Xi''an 710000, China
Abstract:Based on the monitoring data of 230 sections of rivers entering the sea (RES) across China from 2020 to 2022,the temporal and spatial distribution characteristics of total nitrogen (TN) concentration were analyzed using time series statistical methods and spatial clustering methods. The results showed that the annual average TN concentration of RES across China increased year by year from (3.24±2.20) mg/L to (3.92±3.30) mg/L in 2020-2022. During the year,the TN concentration showed a V-shaped seasonal change pattern,which was high in winter,low in summer,and medium in spring and autumn. Spatial clustering analysis showed that the TN concentration could be divided into four distinct regions from north to south,namely,the northern high-value area (BGZQ),including the western Liaodong Hills,Liaoxi Hills,and Shandong Hills,the northern secondary high area (BCGZQ),including Circum-Bohai Sea,Beijing-Tianjin-Hebei region,and northern Jiangsu Plain,the east China (HDQ) area,including Yangtze River Delta and Fujian,the south China area (HNQ),including Guangdong,Guangxi and Hainan. The annual average TN concentration distribution was BGZQ > BCGZQ > HDQ> HNQ. The excessively high TN concentration in BGZQ contributed disproportionately to the average across China. Meanwhile,the two northern areas contributed 92% of the increase in TN across the country from 2020 to 2022. In addition,the seasonal V-shaped periodic pattern within the year was also more pronounced from south to north as the northern region was the main reason for the V-shaped in the RES across China.
Keywords:rivers entering the sea  total nitrogen  temporal and spatial distribution characteristics  spatial clustering analysis
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