Management implications of spatial–temporal variations of net anthropogenic nitrogen inputs (NANI) in the Yellow River Basin
It is an important content of environment management to accurately identify the time change and spatial distribution of net anthropogenic nitrogen inputs (NANI) in the river basin. In order to develop a unified management and diverse control strategy that fits the characteristics of the basin, this...
Gespeichert in:
| Veröffentlicht in: | Environmental science and pollution research international 2022-07, Vol.29 (35), p.52317-52335 |
|---|---|
| Hauptverfasser: | , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 52335 |
|---|---|
| container_issue | 35 |
| container_start_page | 52317 |
| container_title | Environmental science and pollution research international |
| container_volume | 29 |
| creator | Wu, Zening Jiang, Mengmeng Wang, Huiliang Di, Danyang Guo, Xi |
| description | It is an important content of environment management to accurately identify the time change and spatial distribution of net anthropogenic nitrogen inputs (NANI) in the river basin. In order to develop a unified management and diverse control strategy that fits the characteristics of the basin, this study establishes the NANI-S model combining the NANI model with the spatial autocorrelation analysis method, which is a quantification-analysis-control process, and takes the 70 prefecture-cities in the Yellow River Basin (YRB) as the study area. The result shows that (1) the NANI of YRB increased first and then decreased with an average NANI value of 6787.59 kg/(km
2
·a), showing that the overall N pollution situation of the YRB shows a trend of improvement in nitrogen (N) fertilizer input as the main source, and the average contribution rate was 47.45%. (2) There were obvious spatial differences in the NANI in the YRB because the global Moran’s I fluctuated between 0.67 and 0.78. Cities with high NANI clustered in the middle and lower reaches, while low NANI clustered in the upper reaches. (3) Improving fertilizer utilization rate and industrial and domestic sewage treatment capacity was the key point of N control. Based on the results, practical policy recommendations for water pollution management were constructed, which provides a scientific basis for pollution prevention and high-quality development in the basin. In addition, this analysis method can also be applied to other basin N management studies. |
| doi_str_mv | 10.1007/s11356-022-19440-3 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2637338100</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2637338100</sourcerecordid><originalsourceid>FETCH-LOGICAL-c408t-d1099329559e851bd02bf97c54ebc1c2cd15e7138fb07dd537eb82ec155d7a3c3</originalsourceid><addsrcrecordid>eNqFkc9uFSEUh4mxsdfqC7gwJG7qYpS_l2FZG7VN2poYXbgiDHPmlmYGRmBq3BjfwTf0Scr1Vpu40LDgAN_5AfkQekLJC0qIepkp5XLdEMYaqoUgDb-HVnRNRaOE1vfRitTdhnIh9tHDnK8IYUQz9QDtc8lkqwRZoW_nNtgNTBAK9tM8emeLjyHjOOA819qOP7__KDDNMdkRX9vk74AABdtQLlOc4waCdzj4krYl9mFeSsaHF0cXp8_rCpdLwJ9gHOMX_N5fQ8KvbPbhEdob7Jjh8e18gD6-ef3h-KQ5e_f29PjorHGCtKXpKdGaMy2lhlbSriesG7RyUkDnqGOupxIU5e3QEdX3kivoWgaOStkryx0_QIe73DnFzwvkYiafXX2ODRCXbJiiLZdyzdj_0TVXnLfVQEWf_YVexSWF-pFK6e1o9TaQ7SiXYs4JBjMnP9n01VBitiLNTqSpIs0vkYbXpqe30Us3Qf-n5be5CvAdkOtR2EC6u_sfsTddh6ox</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2696969892</pqid></control><display><type>article</type><title>Management implications of spatial–temporal variations of net anthropogenic nitrogen inputs (NANI) in the Yellow River Basin</title><source>SpringerLink Journals</source><creator>Wu, Zening ; Jiang, Mengmeng ; Wang, Huiliang ; Di, Danyang ; Guo, Xi</creator><creatorcontrib>Wu, Zening ; Jiang, Mengmeng ; Wang, Huiliang ; Di, Danyang ; Guo, Xi</creatorcontrib><description>It is an important content of environment management to accurately identify the time change and spatial distribution of net anthropogenic nitrogen inputs (NANI) in the river basin. In order to develop a unified management and diverse control strategy that fits the characteristics of the basin, this study establishes the NANI-S model combining the NANI model with the spatial autocorrelation analysis method, which is a quantification-analysis-control process, and takes the 70 prefecture-cities in the Yellow River Basin (YRB) as the study area. The result shows that (1) the NANI of YRB increased first and then decreased with an average NANI value of 6787.59 kg/(km
2
·a), showing that the overall N pollution situation of the YRB shows a trend of improvement in nitrogen (N) fertilizer input as the main source, and the average contribution rate was 47.45%. (2) There were obvious spatial differences in the NANI in the YRB because the global Moran’s I fluctuated between 0.67 and 0.78. Cities with high NANI clustered in the middle and lower reaches, while low NANI clustered in the upper reaches. (3) Improving fertilizer utilization rate and industrial and domestic sewage treatment capacity was the key point of N control. Based on the results, practical policy recommendations for water pollution management were constructed, which provides a scientific basis for pollution prevention and high-quality development in the basin. In addition, this analysis method can also be applied to other basin N management studies.</description><identifier>ISSN: 0944-1344</identifier><identifier>EISSN: 1614-7499</identifier><identifier>DOI: 10.1007/s11356-022-19440-3</identifier><identifier>PMID: 35258740</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Anthropogenic factors ; Aquatic Pollution ; Atmospheric Protection/Air Quality Control/Air Pollution ; autocorrelation ; basins ; Earth and Environmental Science ; Ecotoxicology ; Environment ; Environmental Chemistry ; Environmental Health ; Environmental management ; Environmental science ; Fertilizers ; Household wastes ; issues and policy ; Nitrogen ; Pollution abatement ; pollution control ; Pollution prevention ; Research Article ; River basins ; Rivers ; Sewage treatment ; Spatial analysis ; Spatial distribution ; Temporal variations ; Waste Water Technology ; Wastewater treatment ; Water Management ; Water pollution ; Water Pollution Control ; watersheds ; Yellow River</subject><ispartof>Environmental science and pollution research international, 2022-07, Vol.29 (35), p.52317-52335</ispartof><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022</rights><rights>2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.</rights><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c408t-d1099329559e851bd02bf97c54ebc1c2cd15e7138fb07dd537eb82ec155d7a3c3</citedby><cites>FETCH-LOGICAL-c408t-d1099329559e851bd02bf97c54ebc1c2cd15e7138fb07dd537eb82ec155d7a3c3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11356-022-19440-3$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11356-022-19440-3$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27903,27904,41467,42536,51297</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35258740$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Wu, Zening</creatorcontrib><creatorcontrib>Jiang, Mengmeng</creatorcontrib><creatorcontrib>Wang, Huiliang</creatorcontrib><creatorcontrib>Di, Danyang</creatorcontrib><creatorcontrib>Guo, Xi</creatorcontrib><title>Management implications of spatial–temporal variations of net anthropogenic nitrogen inputs (NANI) in the Yellow River Basin</title><title>Environmental science and pollution research international</title><addtitle>Environ Sci Pollut Res</addtitle><addtitle>Environ Sci Pollut Res Int</addtitle><description>It is an important content of environment management to accurately identify the time change and spatial distribution of net anthropogenic nitrogen inputs (NANI) in the river basin. In order to develop a unified management and diverse control strategy that fits the characteristics of the basin, this study establishes the NANI-S model combining the NANI model with the spatial autocorrelation analysis method, which is a quantification-analysis-control process, and takes the 70 prefecture-cities in the Yellow River Basin (YRB) as the study area. The result shows that (1) the NANI of YRB increased first and then decreased with an average NANI value of 6787.59 kg/(km
2
·a), showing that the overall N pollution situation of the YRB shows a trend of improvement in nitrogen (N) fertilizer input as the main source, and the average contribution rate was 47.45%. (2) There were obvious spatial differences in the NANI in the YRB because the global Moran’s I fluctuated between 0.67 and 0.78. Cities with high NANI clustered in the middle and lower reaches, while low NANI clustered in the upper reaches. (3) Improving fertilizer utilization rate and industrial and domestic sewage treatment capacity was the key point of N control. Based on the results, practical policy recommendations for water pollution management were constructed, which provides a scientific basis for pollution prevention and high-quality development in the basin. In addition, this analysis method can also be applied to other basin N management studies.</description><subject>Anthropogenic factors</subject><subject>Aquatic Pollution</subject><subject>Atmospheric Protection/Air Quality Control/Air Pollution</subject><subject>autocorrelation</subject><subject>basins</subject><subject>Earth and Environmental Science</subject><subject>Ecotoxicology</subject><subject>Environment</subject><subject>Environmental Chemistry</subject><subject>Environmental Health</subject><subject>Environmental management</subject><subject>Environmental science</subject><subject>Fertilizers</subject><subject>Household wastes</subject><subject>issues and policy</subject><subject>Nitrogen</subject><subject>Pollution abatement</subject><subject>pollution control</subject><subject>Pollution prevention</subject><subject>Research Article</subject><subject>River basins</subject><subject>Rivers</subject><subject>Sewage treatment</subject><subject>Spatial analysis</subject><subject>Spatial distribution</subject><subject>Temporal variations</subject><subject>Waste Water Technology</subject><subject>Wastewater treatment</subject><subject>Water Management</subject><subject>Water pollution</subject><subject>Water Pollution Control</subject><subject>watersheds</subject><subject>Yellow River</subject><issn>0944-1344</issn><issn>1614-7499</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqFkc9uFSEUh4mxsdfqC7gwJG7qYpS_l2FZG7VN2poYXbgiDHPmlmYGRmBq3BjfwTf0Scr1Vpu40LDgAN_5AfkQekLJC0qIepkp5XLdEMYaqoUgDb-HVnRNRaOE1vfRitTdhnIh9tHDnK8IYUQz9QDtc8lkqwRZoW_nNtgNTBAK9tM8emeLjyHjOOA819qOP7__KDDNMdkRX9vk74AABdtQLlOc4waCdzj4krYl9mFeSsaHF0cXp8_rCpdLwJ9gHOMX_N5fQ8KvbPbhEdob7Jjh8e18gD6-ef3h-KQ5e_f29PjorHGCtKXpKdGaMy2lhlbSriesG7RyUkDnqGOupxIU5e3QEdX3kivoWgaOStkryx0_QIe73DnFzwvkYiafXX2ODRCXbJiiLZdyzdj_0TVXnLfVQEWf_YVexSWF-pFK6e1o9TaQ7SiXYs4JBjMnP9n01VBitiLNTqSpIs0vkYbXpqe30Us3Qf-n5be5CvAdkOtR2EC6u_sfsTddh6ox</recordid><startdate>20220701</startdate><enddate>20220701</enddate><creator>Wu, Zening</creator><creator>Jiang, Mengmeng</creator><creator>Wang, Huiliang</creator><creator>Di, Danyang</creator><creator>Guo, Xi</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QL</scope><scope>7SN</scope><scope>7T7</scope><scope>7TV</scope><scope>7U7</scope><scope>7WY</scope><scope>7WZ</scope><scope>7X7</scope><scope>7XB</scope><scope>87Z</scope><scope>88E</scope><scope>88I</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8FL</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FRNLG</scope><scope>FYUFA</scope><scope>F~G</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K60</scope><scope>K6~</scope><scope>K9.</scope><scope>L.-</scope><scope>M0C</scope><scope>M0S</scope><scope>M1P</scope><scope>M2P</scope><scope>M7N</scope><scope>P64</scope><scope>PATMY</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>7X8</scope><scope>7S9</scope><scope>L.6</scope></search><sort><creationdate>20220701</creationdate><title>Management implications of spatial–temporal variations of net anthropogenic nitrogen inputs (NANI) in the Yellow River Basin</title><author>Wu, Zening ; Jiang, Mengmeng ; Wang, Huiliang ; Di, Danyang ; Guo, Xi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c408t-d1099329559e851bd02bf97c54ebc1c2cd15e7138fb07dd537eb82ec155d7a3c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Anthropogenic factors</topic><topic>Aquatic Pollution</topic><topic>Atmospheric Protection/Air Quality Control/Air Pollution</topic><topic>autocorrelation</topic><topic>basins</topic><topic>Earth and Environmental Science</topic><topic>Ecotoxicology</topic><topic>Environment</topic><topic>Environmental Chemistry</topic><topic>Environmental Health</topic><topic>Environmental management</topic><topic>Environmental science</topic><topic>Fertilizers</topic><topic>Household wastes</topic><topic>issues and policy</topic><topic>Nitrogen</topic><topic>Pollution abatement</topic><topic>pollution control</topic><topic>Pollution prevention</topic><topic>Research Article</topic><topic>River basins</topic><topic>Rivers</topic><topic>Sewage treatment</topic><topic>Spatial analysis</topic><topic>Spatial distribution</topic><topic>Temporal variations</topic><topic>Waste Water Technology</topic><topic>Wastewater treatment</topic><topic>Water Management</topic><topic>Water pollution</topic><topic>Water Pollution Control</topic><topic>watersheds</topic><topic>Yellow River</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wu, Zening</creatorcontrib><creatorcontrib>Jiang, Mengmeng</creatorcontrib><creatorcontrib>Wang, Huiliang</creatorcontrib><creatorcontrib>Di, Danyang</creatorcontrib><creatorcontrib>Guo, Xi</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Ecology Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Pollution Abstracts</collection><collection>Toxicology Abstracts</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Business Premium Collection (Alumni)</collection><collection>Health Research Premium Collection</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM Global</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Science Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>ProQuest One Business</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><jtitle>Environmental science and pollution research international</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wu, Zening</au><au>Jiang, Mengmeng</au><au>Wang, Huiliang</au><au>Di, Danyang</au><au>Guo, Xi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Management implications of spatial–temporal variations of net anthropogenic nitrogen inputs (NANI) in the Yellow River Basin</atitle><jtitle>Environmental science and pollution research international</jtitle><stitle>Environ Sci Pollut Res</stitle><addtitle>Environ Sci Pollut Res Int</addtitle><date>2022-07-01</date><risdate>2022</risdate><volume>29</volume><issue>35</issue><spage>52317</spage><epage>52335</epage><pages>52317-52335</pages><issn>0944-1344</issn><eissn>1614-7499</eissn><abstract>It is an important content of environment management to accurately identify the time change and spatial distribution of net anthropogenic nitrogen inputs (NANI) in the river basin. In order to develop a unified management and diverse control strategy that fits the characteristics of the basin, this study establishes the NANI-S model combining the NANI model with the spatial autocorrelation analysis method, which is a quantification-analysis-control process, and takes the 70 prefecture-cities in the Yellow River Basin (YRB) as the study area. The result shows that (1) the NANI of YRB increased first and then decreased with an average NANI value of 6787.59 kg/(km
2
·a), showing that the overall N pollution situation of the YRB shows a trend of improvement in nitrogen (N) fertilizer input as the main source, and the average contribution rate was 47.45%. (2) There were obvious spatial differences in the NANI in the YRB because the global Moran’s I fluctuated between 0.67 and 0.78. Cities with high NANI clustered in the middle and lower reaches, while low NANI clustered in the upper reaches. (3) Improving fertilizer utilization rate and industrial and domestic sewage treatment capacity was the key point of N control. Based on the results, practical policy recommendations for water pollution management were constructed, which provides a scientific basis for pollution prevention and high-quality development in the basin. In addition, this analysis method can also be applied to other basin N management studies.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>35258740</pmid><doi>10.1007/s11356-022-19440-3</doi><tpages>19</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0944-1344 |
| ispartof | Environmental science and pollution research international, 2022-07, Vol.29 (35), p.52317-52335 |
| issn | 0944-1344 1614-7499 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_2637338100 |
| source | SpringerLink Journals |
| subjects | Anthropogenic factors Aquatic Pollution Atmospheric Protection/Air Quality Control/Air Pollution autocorrelation basins Earth and Environmental Science Ecotoxicology Environment Environmental Chemistry Environmental Health Environmental management Environmental science Fertilizers Household wastes issues and policy Nitrogen Pollution abatement pollution control Pollution prevention Research Article River basins Rivers Sewage treatment Spatial analysis Spatial distribution Temporal variations Waste Water Technology Wastewater treatment Water Management Water pollution Water Pollution Control watersheds Yellow River |
| title | Management implications of spatial–temporal variations of net anthropogenic nitrogen inputs (NANI) in the Yellow River Basin |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-25T12%3A15%3A52IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Management%20implications%20of%20spatial%E2%80%93temporal%20variations%20of%20net%20anthropogenic%20nitrogen%20inputs%20(NANI)%20in%20the%20Yellow%20River%20Basin&rft.jtitle=Environmental%20science%20and%20pollution%20research%20international&rft.au=Wu,%20Zening&rft.date=2022-07-01&rft.volume=29&rft.issue=35&rft.spage=52317&rft.epage=52335&rft.pages=52317-52335&rft.issn=0944-1344&rft.eissn=1614-7499&rft_id=info:doi/10.1007/s11356-022-19440-3&rft_dat=%3Cproquest_cross%3E2637338100%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2696969892&rft_id=info:pmid/35258740&rfr_iscdi=true |