China’s regional meteorological disaster loss analysis and evaluation based on grey cluster model

To evaluate the regional meteorological disaster loss of China, this paper analyzed the different types of meteorological disasters, including droughts, floods, tropical storms, snowstorms and hail disasters. Based on the analysis about Chinese geographical features, the historical characteristics of different meteorological disasters are analyzed. In particular, these meteorological disasters influence to agriculture production are discussed. According to the analysis of data from 2004 to 2010, we know that the distribution characteristics are very different about different disasters. Provinces like Heilongjiang, Liaoning, Jilin, Inner Mongolia, Gansu, Shanxi and Yunnan are serious affected areas of drought influence. And Anhui, Shandong, Jiangsu, Henan, Jiangxi, Hubei, Hunan, Guangxi, Sichuan and Heilongjiang are serious affected areas by floods and heavy rain. While Guangdong, Fujian, Zhejiang, Shanghai, Jiangsu and Shandong are mainly affected by tropical storms, Henan, Hebei, Hunan and Hubei are serious affected by snowstorms and hail disasters. Then, a novel method based on grey cluster model is constructed and combined with the regional meteorological disaster loss evaluation index system. A total of 31 provinces are considered to evaluate the integrated meteorological disaster losses. The results indicated that Beijing, Tianjin, Shanghai, Xizang, Qinghai and Ningxia belong to the lighter loss grey class. Jiangxi, Hubei, Hunan, Hainan, Sichuan and Gansu belong to the serious loss grey class. Other regions belong to the general loss grey class that the influence caused by meteorological disasters not better than the lighter loss grey class and not worst than the serious loss grey class.     

Global,regional and local: new firm formation and spatial restructuring in China’s apparel industry

The rise of China as the ‘world factory’ has been attributed to the export-oriented industrialization largely driven by some fundamental transformations unfolding in China’s economic, political and cultural arenas, since the Reform and Opening-Up policies. As production costs and competitive pressures both rise, the flexible business environment that export-led production used to embed in has undergone dramatic restructuring and this has further pushed forward new rounds of spatial restructuring and industrial relocation, especially in China’s highly export-oriented apparel industry. Using a large firm-level dataset on new firm formation, we show the articulation of global, regional and local factors are shaping the new firm formation pattern and industrial relocation in interactional and collective ways. The econometric estimations also indicate the ways in which and the extents to which these factors affect firm location choice are highly determined by firm-specific capability.     

Major contribution to carbon neutrality by China’s geosciences and geological technologies

In the context of global climate change, geosciences provide an important geological solution to achieve the goal of carbon neutrality, China’s geosciences and geological technologies can play an important role in solving the problem of carbon neutrality. This paper discusses the main problems, opportunities, and challenges that can be solved by the participation of geosciences in carbon neutrality, as well as China’s response to them. The main scientific problems involved and the geological work carried out mainly fall into three categories: (1) Carbon emission reduction technology (natural gas hydrate, geothermal, hot dry rock, nuclear energy, hydropower, wind energy, solar energy, hydrogen energy); (2) carbon sequestration technology (carbon capture and storage, underground space utilization); (3) key minerals needed to support carbon neutralization (raw materials for energy transformation, carbon reduction technology). Therefore, geosciences and geological technologies are needed: First, actively participate in the development of green energy such as natural gas, geothermal energy, hydropower, hot dry rock, and key energy minerals, and develop exploration and exploitation technologies such as geothermal energy and natural gas; the second is to do a good job in geological support for new energy site selection, carry out an in-depth study on geotechnical feasibility and mitigation measures, and form the basis of relevant economic decisions to reduce costs and prevent geological disasters; the third is to develop and coordinate relevant departments of geosciences, organize and carry out strategic research on natural resources, carry out theoretical system research on global climate change and other issues under the guidance of earth system science theory, and coordinate frontier scientific information and advanced technological tools of various disciplines. The goal of carbon neutrality provides new opportunities and challenges for geosciences research. In the future, it is necessary to provide theoretical and technical support from various aspects, enhance the ability of climate adaptation, and support the realization of the goal of carbon peaking and carbon neutrality.     

Internal spatial fix: China’s geographical solution to food supply and its limits

Over the past three decades, China has managed to maintain and even increase grain production in the context of rapid industrialization and urbanization through a process of internal spatial fix in which grain production is relocated to and concentrated in less developed inland regions. However, the fix created political and environmental problems that will undermine it in the future. Using national statistical data and two case studies, the paper demonstrates how the fix has been a result of complex interactions between central and local actors and is a key factor shaping China’s trajectories of food politics and agrarian transitions. It also reveals that confronting the underproduction crisis of food under capitalist accumulation China has first sought to produce sufficient grain within its national border rather than rely on overseas resources.     

Neighbourhood redevelopment and the making of a housing middle class: Can gentrification explain China’s spatial and social changes?

GeoJournal - This paper addresses the relationship between spatial change and social process in China. Studies in Anglo-American and European cities usually suggest middle classes move into a...     

China’s regional rainstorm floods disaster evaluation based on grey incidence multiple-attribute decision model

This paper deals with the problem of the estimation of rainstorm floods disaster. Based on the relevant historical disaster data of Yearbook of Meteorological Disasters in China (2005–2010), the initial disaster data of 31 provinces, municipalities and autonomous regions in mainland China (Hong Kong, Macao and Taiwan excluded) are processed into evaluation indices values. And then, the incidence degrees of disaster data are calculated. The disaster situation of rainstorm floods disaster for each region in mainland China from 2004 to 2009 is estimated by applied the grey incidence decision model of the dynamic multiple attribute. Simultaneously, the comprehensive quantitative assessment of the rainstorm and flood disaster of each region in mainland China nearly 6 years is conducted. According to the assessment results of 2004–2009 torrential rain and flood disaster in Chinese mainland, the level division of disaster loss is investigated. And the disaster loss of mainland China’s 31 provinces, municipalities and autonomous regions is divided into five levels in which the national flood disaster situation zoning maps are constructed. The results demonstrate that the evaluation method of rainstorm floods disaster is practical and effective.     

Bibliometric analysis of the scientific production on coastal communities’ social vulnerability to climate change and to the impact of extreme events

Natural Hazards - Bibliometric analysis is a quantitative evaluation method for scientific research aiming at measuring knowledge expressed as scientific publications in a given field. This paper...     

Study on temporal and spatial evolution of China’s oil supply and consumption

To begin with, energy flow chart is used to analyze the status of China’s oil supply and consumption. Moreover, the temporal and spatial evolution of the oil production and oil products consumption in China is studied based on the gravity model. Finally, the decoupling index combined with the log mean Divisia index method is used to explore the contribution of the factors which influence terminal oil product consumption in China over the period 1991–2010. This paper draws the following results: (1) China’s net oil import dependency soared from 7.5 % in 1993 to 58.63 % in 2010. (2) The center of gravity for crude oil production and oil products consumption is an overall movement toward the southwest. (3) The economic activity effect is the critical factor in the growth of oil products consumption in China. However, industrial energy intensity effect plays the dominant role in decreasing oil products consumption. (4) The value of the decoupling index represented a re-coupling effect in 1996–1997 and 2003–2004. The other time interval showed weak decoupling effect.     

Fairness of China’s provincial energy environment efficiency evaluation: empirical analysis using a three-stage data envelopment analysis model

China has become the world’s largest carbon emitter since 2007; thus, reducing future emission has become an arduous task. Calculating energy efficiency fairly is paramount for formulating energy policies, given the different development levels of provinces. This study employed a three-stage data envelopment analysis model that considered environmental constraints to evaluate the energy efficiency of China’s 30 provinces in 2015 and redefined traditional energy efficiency as energy environment efficiency which calculated under environmental constraints. Different factors, such as urban development level and industrial structure in relation to energy environment efficiency, were analyzed. Three main results were obtained. First, the average energy environment efficiency in 2015 was only 0.73, which showed that China has roughly 30% capacity for improvement in the future. Second, stochastic frontier analysis demonstrated that the industrial structure, energy consumption structure, and central heating systems exerted negative impacts, and the level of city design and the degree of openness exerted positive effects on energy environment efficiency. Third, capital, manpower, and the extent of industrial concentration in central and western regions should be increased to improve China’s energy environment efficiency.

     

China’s huge investment on water facilities: an effective adaptation to climate change, natural disasters, and food security

China’s huge investment on water infrastructure for sustainable water use, followed by recently frequent natural disasters, caused worldwide concerns, i.e., continuously published by Nature and Science. Most researchers emphasized challenges on this investment; yet, we argue that the 2011-plan, targeting reservoirs, wells, irrigation systems, inter-basin water transfer projects, is the most effective adaptation to climate change, drought and flooding, as well as food security. This provides a good case of water management and development, particularly for the current uneven water resources and food security by climate change.     

The impact of acid rain on China’s socioeconomic vulnerability

Acid rain has been a great threat to socioeconomic sustainable development of China; therefore, we develop an indicator system based on the sensitivity and adaptive capacity perspectives and employ the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) approach to investigate the impact of acid rain on socioeconomic vulnerability of China. Some empirical findings are obtained. First, there is significant provincial difference of socioeconomic vulnerability caused by acid rain in China. Specifically, Tibet, Qinghai, and Shanghai are the top three provinces with the largest vulnerability but Inner Mongolia, Xinjiang, and Jilin are bottom of the rankings. Second, adaptive capacity indicators overall appear more important than sensitivity indicators to measure the vulnerability of acid rain, and the most important indicators are population density and output value of agriculture, forestry, animal husbandry, and fishery while GDP per capita ranks the last. Third, upgrading energy structure and reducing outdated capacity in China prove to be effective means to mitigate vulnerability of acid rain, which has been validated in Guizhou and Hunan provinces. Finally, great attention should be attached to the population increase so as to curb the acid rain vulnerability, especially in Beijing and Tianjin. These results present a basis for future acid rain prevention planning and economic development in China.     

Industry market reaction to natural disasters: do firm characteristics and disaster magnitude matter?

This study investigates the factors that drive US industry sectors’ response to domestic natural disasters for the period 1987–2018. In general, our results show that not all local industry portfolios experience more negative impacts than non-local industries. We find that location does matter, but the nature of the industry itself is also important. Moreover, results for firm size show that big firms outperform small firms, across many industry settings. Finally, disaster severity analysis reveals that industries react differently to disasters of different magnitudes, and the response also varies across the different disaster measures. Our findings provide a basis for development of equity reaction prediction in the event of natural disasters, thus mitigating the disaster risk.

     

Susceptibility evaluation and mapping of China’s landslides based on multi-source data

Landslides are occurring more frequently in China under the conditions of extreme rainfall and changing climate, according to News reports. Landslide hazard assessment remains an international focus on disaster prevention and mitigation, and it is an important step for compiling and quantitatively characterizing landslide damages. This paper collected and analyzed the historical landslide events data of the past 60 years in China. Validated by the frequencies and distributions of landslides, nine key factors (lithology, convexity, slope gradient, slope aspect, elevation, soil property, vegetation coverage, flow, and fracture) are selected to construct landslide susceptibility (LS) empirical models by back-propagation artificial neural network method. By integrating landslide empirical models with surface multi-source geospatial and remote sensing data, this paper further performs a large-scale LS assessment throughout China. The resulting landslide hazard assessment map of China clearly illustrates the hot spots of the high landslide potential areas, mostly concentrated in the southwest. The study implements a complete framework of multi-source data collecting, processing, modeling, and synthesizing that fulfills the assessment of LS and provides a theoretical basis and practical guide for predicting and mitigating landslide disasters potentially throughout China.

     

Constructing a social vulnerability index to earthquake hazards using a hybrid factor analysis and analytic network process (F’ANP) model

Iran is a seismic prone country and has been host to a long series of devastating earthquakes which have resulted in heavy casualties and damages. In order to assess social vulnerability (SV) to earthquake hazards, this paper presents the development of a hybrid factor analysis and analytic network process model for aggregating vulnerability indicators into a composite index of SV to earthquake hazards. The proposed model is then applied in Iran as a case study. The proposed model uses factor analysis (FA) to extract the underlying dimensions of SV. The identified dimensions of SV and their primary variables are then entered into a network model in Analytic Network Process (ANP). The ANP is used to calculate the relative importance of different SV variables, taking into consideration the results obtained from FA and the possible interdependence between variables of the individual dimensions of SV. These weights are then used to compute the factor scores for the individual dimensions of SV and also the composite social vulnerability index (SOVI). The application of the proposed model to a real world case study and its validation show that it is a robust approach for constructing a composite SOVI. Its application to counties in Iran indicates that there exist severe regional differences in terms of SV to earthquake hazards. The pronounced regional variations in SV warrant special attention by both local authorities and the national government to reconsider current natural disaster management strategies.     

Identifying urban–rural differences in social vulnerability to natural hazards: a case study of China

Identifying and analyzing the urban–rural differences of social vulnerability to natural hazards is imperative to ensure that urbanization develops in a way that lessens the impacts of disasters and generate building resilient livelihoods in China. Using data from the 2000 and 2010 population censuses, this study conducted an assessment of the social vulnerability index (SVI) by applying the projection pursuit cluster model. The temporal and spatial changes of social vulnerability in urban and rural areas were then examined during China’s rapid urbanization period. An index of urban–rural differences in social vulnerability (SVI_D) was derived, and the global and local Moran’s I of the SVI_D were calculated to assess the spatial variation and association between the urban and rural SVI. In order to fully determine the impacts of urbanization in relation to social vulnerability, a spatial autoregressive model and Bivariate Moran’s I between urbanization and SVI were both calculated. The urban and rural SVI both displayed a steadily decreasing trend from 2000 to 2010, although the urban SVI was always larger than the rural SVI in the same year. In 17.5% of the prefectures, the rural SVI was larger than the urban SVI in 2000, but was smaller than the urban SVI in 2010. About 12.6% of the urban areas in the prefectures became less vulnerable than rural areas over the study period, while in more than 51.73% of the prefectures the urban–rural SVI gap decreased over the same period. The SVI_D values in all prefectures had a significantly positive spatial autocorrelation and spatial clusters were apparent. Over time, social vulnerability to natural hazards at the prefecture-level displayed a gathering–scattering pattern across China. Though a regional variation of social vulnerability developed during China’s rapid urbanization, the overall trend was for a steady reduction in social vulnerability in both urban and rural areas.

     

Coastal vulnerability to sea-level rise: a spatial–temporal assessment framework

The scientific community is confident that warming of the Earth’s climate is unequivocal. Sea-level rise, which poses potential threats to coastal areas, is one of the most recognised possible impacts of this climate change. The nonlinearities, complexities, and spatial and temporal lags are common characteristics of coastal processes driven by human and natural interaction. With the acknowledgement of the complexity and dynamic nature of coastal systems, this paper introduces a spatial–temporal assessment framework, for addressing both the temporal and spatial variations, when assessing the vulnerability of natural and human systems in coastal areas. The framework is based upon a combination of system dynamics (SD) modelling and geographical information systems by taking into account spatial (x, y, z) and temporal (t) dimensions. The strategy of the adopted approach is to use the loose coupling approach by which a spatial model component is incorporated into a SD model component through a data converter.     

Decoupling and decomposing analysis of construction industry’s energy consumption in China

Natural Hazards - The construction industry is one of the key industries for driving energy conservation in China. Decoupling of the construction industry development from energy consumption has...