Mapping Social Vulnerability to Air Pollution: A Case Study of the Yangtze River Delta Region, China

Yi, Ge; Zhang, Haibo; Dou, Wenbin; Chen, Wenfang; Ning, Liu; Yuan, Wang; Shi, Yulin; Rao, Wenxin

doi:10.3390/su9010109

Cited by 24 publications

(15 citation statements)

References 53 publications

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“…More detailed steps were illustrated in our previous paper: Mapping Social Vulnerability to Air Pollution: A Case Study of the Yangtze River Delta Region, China [19]. (2) With the relational data retrieved from the Baidu Index, the new dimension (connectivity) of social vulnerability (labelled as SVI connectivity ) was calculated according Equation (2).…”

Section: Methodsmentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

“…The attribute data were collected from the 6th National Population Census of China (2010), the Jiangsu Statistical Yearbook, the Shanghai Statistical Yearbook, and the Zhejiang Statistical Yearbook, as well as the 2010 China Civil Affairs Statistical Yearbook. Referencing our similar previous study in the YRD area [19], nineteen indicators were finally selected for assessing social vulnerability after removing indicators for their high correlation, and included: Population density, Urban Resident, Female, Children, Elderly, Ethnicity, Illiterate, Poor, Unemployment Rate, Employees in the Second Sector, Employees in Mining, Employees in Construction, GDP in the Second Industry, Per GDP, Educated, Beds in Hospitals, Physicians in Hospital, Employees in Management Sector, and Green Space Coverage.…”

Section: Datamentioning

confidence: 99%

“…As one important aspect of vulnerability, social vulnerability refers to the predisposition and inner state of individuals, organizations, or societies that affect the way they withstand adverse impacts from disruptive events such as natural hazards, climate change, or other dangerous incidences [18][19][20]. In essence, social vulnerability is a by-product of social stratification and social inequalities among different communities and different places from the built environment [21][22][23].…”

Section: Literature Review: Conceptual Basis and Evolution Of Vulneramentioning

confidence: 99%

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A New Framework for Understanding Urban Social Vulnerability from a Network Perspective

Dou

Zhang

2017

Sustainability

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Rapid urbanization in China has strengthened the connection and cooperation among cities and has also led urban residents to be more vulnerable in adverse environmental conditions. Vulnerability research has been an important foundation in urban risk management. To make cities safe and resilient, it is also necessary to integrate the connection among cities into a vulnerability assessment. Therefore, this paper proposed a new conceptual framework for urban social vulnerability assessment based on network theory, where a new dimension of social vulnerability (connectivity) was added into the framework. Using attribute data, the traditional social vulnerability index of a city (SVI node ) was calculated via the projection pursuit cluster (PPC) model. With the relational data retrieved from the Baidu search index, a new dimension (connectivity) of social vulnerability (SVI connectivity ) was evaluated. Finally, an integrated social vulnerability index (SVI urban ) was measured combined with SVI node and SVI connectivity . This method was applied in the Yangtze River Delta region of China, where the top three high values of SVI node belonged to the cities of Taizhou (Z), Jiaxing, and Huzhou. The three lowest cities were Hangzhou, Nanjing, and Shanghai. For SVI urban , the social vulnerability of cities in different hierarchies behaved differently. For Hierarchies 2 and 3, when compared to SVI node , the SVI urban was significantly reduced. However, the variation between SVI node and SVI urban in Hierarchy 4 was slight. Furthermore, an increase for the city of Taizhou (J) in its social vulnerability was achieved after connecting to the network. Huzhou, in Hierarchy 5, increased its social vulnerability the most when adding connectivity in the social vulnerability assessment. Based on the results of our case study, a conclusion was drawn that network connectivity had an influence on social vulnerability. However, when connectivity was strong enough, it could help cities to mitigate their traditional social vulnerability, whereas a loose connection in the network aggregated their traditional social vulnerability. Hence, the latter should be emphasized in future urban risk management.

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Section: Methodsmentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

Section: Literature Review: Conceptual Basis and Evolution Of Vulneramentioning

confidence: 99%

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A New Framework for Understanding Urban Social Vulnerability from a Network Perspective

Dou

Zhang

2017

Sustainability

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“…With the data envelopment analysis method (DEA), Huang et al explored multidimensional flood vulnerability [67]. Ge applied the projection pursuit cluster (PPC) method to quantify the social vulnerability of the Yangtze River Delta in China [13,52].…”

Section: Introductionmentioning

confidence: 99%