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Huang Y.,Jimei University | Li F.,University of Chinese Academy of Sciences | Li F.,CAS Institute of Geographical Sciences and Natural Resources Research | Bai X.,Australian National University | And 2 more authors.
Environmental Science and Policy | Year: 2012

Coastal regions in China are undergoing rapid land use change, but little attention is paid to the implications of this change to local community. Assessment of vulnerability of coastal community to land use change is an important step for enhancing the understanding and decision-making to reduce such vulnerability. This article presents an analytical framework and associated indicator system to assess and compare vulnerability of communities to land use change in coastal areas, and present a case study in China applying this framework. The study includes quantification of Exposure Index (EI), Sensitivity Index (SI) and Adaptive Capacity Index (AI). EI is to measure intensity of land use. SI and AI are based on some socio-economic attributes of the native residents, as well as their view on environmental change and management. Based on the quantification of SI and AI, Vulnerability Index (VI) can be assessed and compared among different communities. This framework was applied in a case study in Maluan Bay, Xiamen, China. The area consists of four administrative, as rural communities in the 1980s, evolving into four distinctive communities with different policies and development modes. Comparison of EI and VI reveals large disparity among communities. Analysis demonstrated that vulnerability was not evenly distributed across communities, which might be linked to the different stage of transformation the community was undergoing. For the case areas, vulnerability tends to increase with the increase of exposure to land use change, but can peak off once the community start to benefit socio-economically from development. The most vulnerable community is the one where native residents lost their livelihood, but benefited a little from economic development. This may suggest the need for tailor-made policy responses to help them to benefit from development and aid their smooth integration into the city, only in this way can enhance adaptive capacity of coastal communities to use change of land and sea. © 2012 Elsevier Ltd.

Xu L.,Chinese Institute of Urban Environment | Xu L.,Xiamen Key Laboratory of Urban Metabolism | Gao P.,Xiamen City Appearance and Environmental Sanitation Management Office | Cui S.,Chinese Institute of Urban Environment | And 2 more authors.
Waste Management | Year: 2013

Accurate forecasting of municipal solid waste (MSW) generation is crucial and fundamental for the planning, operation and optimization of any MSW management system. Comprehensive information on waste generation for month-scale, medium-term and long-term time scales is especially needed, considering the necessity of MSW management upgrade facing many developing countries. Several existing models are available but of little use in forecasting MSW generation at multiple time scales. The goal of this study is to propose a hybrid model that combines the seasonal autoregressive integrated moving average (SARIMA) model and grey system theory to forecast MSW generation at multiple time scales without needing to consider other variables such as demographics and socioeconomic factors. To demonstrate its applicability, a case study of Xiamen City, China was performed. Results show that the model is robust enough to fit and forecast seasonal and annual dynamics of MSW generation at month-scale, medium- and long-term time scales with the desired accuracy. In the month-scale, MSW generation in Xiamen City will peak at 132.2 thousand tonnes in July 2015 - 1.5. times the volume in July 2010. In the medium term, annual MSW generation will increase to 1518.1 thousand tonnes by 2015 at an average growth rate of 10%. In the long term, a large volume of MSW will be output annually and will increase to 2486.3 thousand tonnes by 2020 - 2.5. times the value for 2010. The hybrid model proposed in this paper can enable decision makers to develop integrated policies and measures for waste management over the long term. © 2013 Elsevier Ltd.

Wang R.,Chinese Institute of Urban Environment | Wang R.,Xiamen Key Laboratory of Urban Metabolism | Liu W.,Chinese Institute of Urban Environment | Xiao L.,Chinese Institute of Urban Environment | And 3 more authors.
Energy Policy | Year: 2011

Following the announcement of the China's 2020 national target for the reduction of the intensity of carbon dioxide emissions per unit of GDP by 40-45% compared with 2005 levels, Chinese provincial governments prepared to restructure provincial energy policy and plan their contribution to realizing the State reduction target. Focusing on Fujian and Anhui provinces as case studies, this paper reviews two contrasting policies as a means for meeting the national reduction target. That of the coastal province of Fujian proposes to do so largely through the development of nuclear power, whilst the coal-rich province of Anhui proposes to do so through its energy consumption rate rising at a lower rate than that of the rise in GDP. In both cases renewable energy makes up a small proportion of their proposed 2020 energy structures. The conclusion discusses in depth concerns about nuclear power policy, energy efficiency, energy consumption strategy and problems in developing renewable energy. © 2011 Elsevier Ltd.

Sun Y.,Chinese Institute of Urban Environment | Wang R.,Chinese Institute of Urban Environment | Wang R.,Xiamen Key Laboratory of Urban Metabolism | Liu J.,Chinese Institute of Urban Environment | And 4 more authors.
Applied Energy | Year: 2013

Effective spatial planning is crucial for cost-effectively and sustainably developing biomass energy resources due to the diffuse nature of biomass and high transportation cost. Using the spatial analysis technology, economic models and scenario analysis, this paper presents a spatial planning framework to identify the appropriate developing areas of biomass energy at regional level. The methodology is applied in a case study of Fujian Province, China. Firstly, spatial distribution of two kinds of biomass resources and the technical potential, i.e. the amount of power generation from agricultural and forestry residues in each supply area, were estimated by incorporating the spatial data and the statistical data. The results indicate that total technical potential of agricultural and forestry residues is estimated at 25.13TWhy-1, equivalent to approximately 19% of total electricity consumption in Fujian in 2010. In the second step, the economic analysis assesses the cost of biomass generation for each supply area on the basis of current market conditions. Ranking of the supply areas is then performed by using the priority development index (PDI), which can measure the priority of each biomass supply area by combining several influencing indicators. Finally, the selection of supply areas for power plants can be carried out according to its order in PDI until the total planed capacity in the region is met. The priority of the subregions and the corresponding cost of biomass generation for different planning scenarios can be explicitly visualized. The methodology can be applied to a wide area and can support the local authorities to define and implement a strategy for future biomass energy development. © 2013 Elsevier Ltd.

Lin T.,Chinese Institute of Urban Environment | Lin T.,Xiamen Key Laboratory of Urban Metabolism | Xue X.,Xiamen University | Shi L.,Chinese Institute of Urban Environment | And 3 more authors.
Ocean and Coastal Management | Year: 2013

Islands are indispensable part of coastal ecosystem, and many inhabited islands in China are now facing increasing stress from urbanization. This paper examines the 100-year history of urban spatial expansion of Xiamen Island, China. The island's urban spatial expansion was analyzed by a land use changes matrix and a land use intensity index (LUII) with special focus on the last 30 years. The impacts of urban spatial expansion on the island ecosystem, in terms of ecosystem service and landscape pattern, were quantitatively studied. The results reveal that urban spatial expansion of Xiamen Island has utilized large areas of woodland, farmland, water area and coastal wetland, which caused continuous increase of LUII, the decrease in ecosystem service value, and significant fragmentation in the landscape pattern. Our study suggests landscape pattern analysis and ecosystem service valuation are two powerful tools that can ensure a holistic and integrative decision making in regulating spatial coastal urbanization. © 2012 Elsevier Ltd.

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