• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

2000-2019 年长江经济带人为氮负荷的变化及其驱动因素。

Variations and its driven factors of anthropogenic nitrogen loads in the Yangtze River Economic Belt during 2000-2019.

机构信息

National Marine Data and Information Service, Ministry of Natural Resources, Tianjin, 300171, China.

Center for Environmental Remediation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.

出版信息

Environ Sci Pollut Res Int. 2023 Jan;30(2):2450-2468. doi: 10.1007/s11356-022-21943-y. Epub 2022 Aug 5.

DOI:10.1007/s11356-022-21943-y
PMID:35931850
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9362473/
Abstract

Since the millennium, China has economically taken off with rapid urbanization, and anthropogenic nitrogen emission intensity has undergone remarkable changes. To better understand the impact of urbanization on anthropogenic nitrogen, this study calculated the spatio-temporal heterogeneity of anthropogenic nitrogen in the Yangtze River Economic Belt (YREB) since 2000, based on the estimation, using obstacle analysis to quantify the driving of industry and agriculture on N growth and using the gray model to analyze the impact of urbanization on N changes. Additionally, using the environmental pressure model to predict the future N load. The results indicated N load in the YREB increased rapidly from 21.4 Tg in 2001 to a peak of 24.5 Tg in 2012 and then decreased to 22.2 Tg in 2019. Although N flux gradually increased from the west to the east of the YREB, the growth rate had an opposite trend with a negative growth in the eastern region. Hotspots are mainly concentrated in urban agglomerations, which contributed to ~ 60% N load of the YREB, and the YREB contributed to ~ 90% N load of the Yangtze River Basin. Obstacle degree scores indicated wastewater was a major industrial driver of N growth before 2010, and then became waste gas; increased mechanization and fertilizer control effectively reduced nitrogen emissions during agricultural development. The gray analysis of urbanization indicated urban population, industry, and services had the strongest correlation with N load changes. Scenario simulations suggest N loads of the YREB remain at a high level by 2030; however, there are still opportunities to effectively control N growth through high technological innovation and reducing the proportion of industry under an enormous population. This research contributes to a better understanding of the impact of urbanization on anthropogenic nitrogen and helps developing countries to precisely control nitrogen hotspots and sources.

摘要

自千年之交以来,中国经济腾飞,城市化进程迅速推进,人为氮排放强度发生了显著变化。为了更好地了解城市化对人为氮的影响,本研究基于估算,采用障碍分析量化工业和农业对氮增长的驱动作用,利用灰色模型分析城市化对氮变化的影响,并利用环境压力模型预测未来氮负荷,计算了 2000 年以来长江经济带(YREB)人为氮的时空异质性。结果表明,YREB 的氮负荷从 2001 年的 21.4Tg 迅速增加到 2012 年的峰值 24.5Tg,然后下降到 2019 年的 22.2Tg。尽管氮通量从 YREB 的西部逐渐增加到东部,但增长率呈相反趋势,东部地区呈负增长。热点主要集中在城市群,对 YREB 的氮负荷贡献了约 60%,而 YREB 对长江流域的氮负荷贡献了约 90%。障碍度得分表明,废水在 2010 年前是氮增长的主要工业驱动因素,然后变成废气;农业发展中,机械化和化肥控制的增加有效地减少了氮排放。城市化的灰色分析表明,城市人口、工业和服务业与氮负荷变化的相关性最强。情景模拟表明,到 2030 年,YREB 的氮负荷仍将处于较高水平;然而,通过高技术创新和降低庞大人口下工业的比例,仍有机会有效控制氮的增长。本研究有助于更好地了解城市化对人为氮的影响,并有助于发展中国家精确控制氮热点和来源。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8936/9362473/637511869069/11356_2022_21943_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8936/9362473/d44f2431690d/11356_2022_21943_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8936/9362473/b49bdba4fbb1/11356_2022_21943_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8936/9362473/c6213ec1b2a0/11356_2022_21943_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8936/9362473/9270cfb7c58f/11356_2022_21943_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8936/9362473/9d3ad0dbe550/11356_2022_21943_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8936/9362473/259026b344e2/11356_2022_21943_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8936/9362473/4c0cf5324582/11356_2022_21943_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8936/9362473/40417d715d50/11356_2022_21943_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8936/9362473/637511869069/11356_2022_21943_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8936/9362473/d44f2431690d/11356_2022_21943_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8936/9362473/b49bdba4fbb1/11356_2022_21943_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8936/9362473/c6213ec1b2a0/11356_2022_21943_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8936/9362473/9270cfb7c58f/11356_2022_21943_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8936/9362473/9d3ad0dbe550/11356_2022_21943_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8936/9362473/259026b344e2/11356_2022_21943_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8936/9362473/4c0cf5324582/11356_2022_21943_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8936/9362473/40417d715d50/11356_2022_21943_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8936/9362473/637511869069/11356_2022_21943_Fig9_HTML.jpg

相似文献

1
Variations and its driven factors of anthropogenic nitrogen loads in the Yangtze River Economic Belt during 2000-2019.2000-2019 年长江经济带人为氮负荷的变化及其驱动因素。
Environ Sci Pollut Res Int. 2023 Jan;30(2):2450-2468. doi: 10.1007/s11356-022-21943-y. Epub 2022 Aug 5.
2
Input-Output Efficiency of Water-Energy-Food and Its Driving Forces: Spatial-Temporal Heterogeneity of Yangtze River Economic Belt, China.水-能源-粮食的投入产出效率及其驱动力:中国长江经济带的时空异质性
Int J Environ Res Public Health. 2022 Jan 25;19(3):1340. doi: 10.3390/ijerph19031340.
3
Spatiotemporal variations and determinants of water pollutant discharge in the Yangtze River Economic Belt, China: A spatial econometric analysis.中国长江经济带水污染物排放的时空变化及其决定因素:空间计量经济学分析。
Environ Pollut. 2021 Feb 15;271:116320. doi: 10.1016/j.envpol.2020.116320. Epub 2020 Dec 17.
4
What is the spatiotemporal relationship between urbanization and ecosystem services? A case from 110 cities in the Yangtze River Economic Belt, China.城市化与生态系统服务之间的时空关系是什么?来自中国长江经济带 110 个城市的案例。
J Environ Manage. 2022 Nov 1;321:115709. doi: 10.1016/j.jenvman.2022.115709. Epub 2022 Aug 27.
5
Spatio-temporal evolution mechanism and dynamic simulation of nitrogen and phosphorus pollution of the Yangtze River economic Belt in China.中国长江经济带氮磷污染的时空演化机制与动态模拟
Environ Pollut. 2024 Sep 15;357:124402. doi: 10.1016/j.envpol.2024.124402. Epub 2024 Jun 19.
6
Research on Green Total Factor Productivity of Yangtze River Economic Belt Based on Environmental Regulation.基于环境规制的长江经济带绿色全要素生产率研究。
Int J Environ Res Public Health. 2021 Nov 22;18(22):12242. doi: 10.3390/ijerph182212242.
7
Green Total-Factor Energy Efficiency of Construction Industry and Its Driving Factors: Spatial-Temporal Heterogeneity of Yangtze River Economic Belt in China.中国长江经济带建筑业全要素能源效率及其驱动因素的时空分异。
Int J Environ Res Public Health. 2022 Aug 12;19(16):9972. doi: 10.3390/ijerph19169972.
8
Efficient population size of urban agglomerations in the Yangtze River Economic Belt from a financial perspective.从金融视角看长江经济带城市群的有效人口规模。
PLoS One. 2024 Sep 27;19(9):e0311090. doi: 10.1371/journal.pone.0311090. eCollection 2024.
9
"Green" economic development in China: quantile regression evidence from the Yangtze River Economic Belt.中国的“绿色”经济发展:来自长江经济带的分位数回归证据。
Environ Sci Pollut Res Int. 2022 Aug;29(40):60572-60583. doi: 10.1007/s11356-022-20197-y. Epub 2022 Apr 14.
10
Impact of Industrial Structure Upgrading on Green Total Factor Productivity in the Yangtze River Economic Belt.产业结构升级对长江经济带绿色全要素生产率的影响。
Int J Environ Res Public Health. 2022 Mar 21;19(6):3718. doi: 10.3390/ijerph19063718.