Measuring County Resilience After the 2008 Wenchuan Earthquake

Abstract

The catastrophic earthquake that struck Sichuan Province, China, in 2008 caused serious damage to Wenchuan County and surrounding areas in southwestern China. In recent years, great attention has been paid to the resilience of the affected area. This study applied the resilience inference measurement (RIM) model to quantify and validate the community resilience of 105 counties in the impacted area. The RIM model uses cluster analysis to classify counties into four resilience levels according to the exposure, damage, and recovery conditions. The model then applies discriminant analysis to quantify the influence of socioeconomic characteristics on the county's resilience. Analysis results show that counties located at the epicenter had the lowest resilience, but counties immediately adjacent to the epicenter had the highest resilience capacities. Counties that were farther away from the epicenter returned to normal resiliency quickly. Socioeconomic variables-including sex ratio, per capita GDP, percent of ethnic minority, and medical facilities-were identified as the most influential characteristics influencing resilience. This study provides useful information to improve county resilience to earthquakes and support decision making for sustainable development.

Influence of Social-economic Activities on Air Pollutants in Beijing, China

“…5 The highest grey relational degree is the influence of TerIndO (Tertiary Industrial Output) on PM 2.5 , which is 0.96. Most of the socio-economic indicators (11 of 15) have high relational degree on PM 2.5 , near or above 0.8, except GDP (Gross Regional Domestic Product), ECPG (Energy consumption per GDP unit), SaleLGP (Sales of Liquefied Petroleum Gas), and Road (Kilometers of Urban Road).…”

“…With China's economic rise a large number of industrial activities such as railways, highways and building construction have resulted in an increase in atmospheric particles and dust haze components of PM 2. 5 . It has been suggested that these sources, together with cer-tain weather conditions would result in a concentration of local pollutants [37,38].…”

“…The air pollution level in Beijing is already significantly exceeding the upper limit of the air quality guidelines from WHO. Air pollution in Beijing is stuck in the worst status after decades of rapid economic growth with loose environmental regulation [4,5]. Faced with potential future extreme influence and damage on human and living condition within Beijing, we need to address some questions such as: a) would the socioeconomic activities have a significant effect on the air pollution in Beijing; b) which socio-economic activities would contribute most to the air quality in Beijing.…”

Measuring Recovery to Build up Metrics of Flood Resilience Based on Pollutant Discharge Data: A Case Study in East China

“…Using external measurement (e.g., post-disaster population increase, indicator of building reconstruction, etc.) represents a useful approach to validate the choice of variables [8,16]. The term recovery is widely used in the conceptualizations of disaster resilience [17].…”

“…It is within the context that recovery outcomes can serves as a resource and practical lessons to inform communities of the key intrinsic factors that contribute to disaster resilience [27]. Therefore, some measures tend to focus on response and recovery outcome after the damaging events for the validation of resilience measurement [8,16,28]. Based on these empirical works, useful recovery indicators and models have proved to be important decision support tools for increasing disaster resilience and reducing disaster vulnerability.…”