<mets:mets OBJID="eprint_13553" LABEL="Eprints Item" xsi:schemaLocation="http://www.loc.gov/METS/ http://www.loc.gov/standards/mets/mets.xsd http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-3.xsd" xmlns:mets="http://www.loc.gov/METS/" xmlns:mods="http://www.loc.gov/mods/v3" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><mets:metsHdr CREATEDATE="2024-01-01T22:01:19Z"><mets:agent ROLE="CUSTODIAN" TYPE="ORGANIZATION"><mets:name>IIASA Repository</mets:name></mets:agent></mets:metsHdr><mets:dmdSec ID="DMD_eprint_13553_mods"><mets:mdWrap MDTYPE="MODS"><mets:xmlData><mods:titleInfo><mods:title>Time and space model of urban pollution migration: Economy-energy-environment nexus network</mods:title></mods:titleInfo><mods:name type="personal"><mods:namePart type="given">G.</mods:namePart><mods:namePart type="family">Liu</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:name type="personal"><mods:namePart type="given">Z.</mods:namePart><mods:namePart type="family">Yang</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:name type="personal"><mods:namePart type="given">B.D.</mods:namePart><mods:namePart type="family">Fath</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:name type="personal"><mods:namePart type="given">L.</mods:namePart><mods:namePart type="family">Shi</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:name type="personal"><mods:namePart type="given">S.</mods:namePart><mods:namePart type="family">Ulgiati</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:abstract>In recent years, news of “cancer villages” in the Huaihe River Basin filled front and back pages of newspapers and generated elevated concern among readers. This study aims to understand the relationship between the “cancer villages” and the “large cities” around them. A gravity model is constructed to analyze the correlation between “big cities” and “cancer villages” in terms of indices involving economic connections and pollution frequency. Direct and indirect environmental relationships between large cities and “cancer villages” are analyzed using ecological network analysis, in particular the utility analysis method. Results of the pollution-utility analysis showed that cities distant from “cancer villages” can also affect the county through indirect connections. Based on the pollution utility relationship, we found that “cancer villages” both affect and are affected by cities through indirect feedback relationships. It can be inferred that “cancer villages” have a high incidence of malignant disease not only because of the pollution from its surrounding cities but also because of the influence of far-away cities through a network of interactions. In this way, the pollution of “cancer villages” may be heightened with harmful consequences to population health. Considering these indirect connections, not all of the “cancer villages” are able to reduce their pollution by transferring it to another city or county because it can return through indirect pathways. The best approach would be to lower the pollution generation in the first place in order to prevent its impacts, as well as to at least partially mitigate them through more effective medical care.</mods:abstract><mods:originInfo><mods:dateIssued encoding="iso8601">2017-01-15</mods:dateIssued></mods:originInfo><mods:originInfo><mods:publisher>Elsevier</mods:publisher></mods:originInfo><mods:genre>Article</mods:genre></mets:xmlData></mets:mdWrap></mets:dmdSec><mets:amdSec ID="TMD_eprint_13553"><mets:rightsMD ID="rights_eprint_13553_mods"><mets:mdWrap MDTYPE="MODS"><mets:xmlData><mods:useAndReproduction>
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