Economic Regions In China Research Articles

Comparison of aerosol hygroscopicity and mixing state between winter and summer seasons in Pearl River Delta region, China

Hygroscopic properties of aerosol particles are important for determining aerosol size distributions, and thus determining scattering and absorption coefficients at ambient atmospheric conditions. In this study, hygroscopic properties of aerosol particles at an urban site in Guangzhou, China, were measured using a Hygroscopic Tandem Differential Mobility Analyzer (H-TDMA) system during the winter and the summer. The results show that the urban aerosols were composed of more-hygroscopic, less-hygroscopic and non-hygroscopic particles. For less-hygroscopic particles of 40–200nm in diameter, the hygroscopic parameter κLH was around 0.15. For more-hygroscopic particles, the κMH was from 0.290 to 0.339 with a particle size from 40 to 200nm. For non-hygroscopic particles, the κNH was about 0.015. It was found that the number fraction of less-hygroscopic particles (NFLH) was correlated with the atmospheric oxidation which can be presented by OC/EC. This paper attributed the larger NFLH in winter to the higher value of OC/EC (3.0). Such conditions may lead to more formation of less-hygroscopic particles. Backward trajectories cluster analysis shows that there is a certain link between air mass origin and aerosol hygroscopicity, but it seems to be independent of the level of pollution. The difference of NFNH indicates that the mixing state of aerosol particles can also be affected by air mass origin. Diurnal variations in aerosol hygroscopic parameters in both seasons show that during daytime, aerosol particles tend to have a low degree of external mixing or quasi-internal mixing, resulting in a higher NFMH and a larger κmean; during nighttime and early mornings, they tend to be mixed externally, resulting in a lower NFMH and a smaller κmean. This can be attributed to atmospheric aging effect and evolution of mixing layer height and implies that soot (non-hygroscopic) particles present to a large extent as internal mixtures by the time they leave the urban environment. Hence, only assuming a constant mixing state of soot particles, such as pure external or internal for the regional climate model and air quality model is still not realistic and may lead to uncertainties for the Pearl River Delta (PRD) region which is one of the three major economic regions in China. Comparing the diurnal variation of NFNH in both seasons, it seems that such a diurnal cycle was mainly related to the differences in evolution of mixing layer between two seasons. Such quantitative hygroscopic properties of sub-micro particles are essential in assessing their impact on weather–climate effect and atmospheric visibility.

The marine industrial competitiveness of blue economic regions in China

Enhancing competitiveness of China's marine industry has become an urgent theoretical and practical issue for the Chinese government. This study creates a new competitiveness evaluation index system for China's marine industry that measures comprehensive capacity, industrial output capacity, research capacity and environmental protection capacity. The study analyses marine industrial competitiveness during 2006–2012 and classifies China's 11 major coastal regions into three competitive tiers. It is found that competitiveness of China's marine industry originates from its research capacity, followed by comprehensive capacity, industrial output capacity and environmental protection capacity. The analysis and tier classification show that marine industrial competitiveness is strong in Guangdong, Shandong and Shanghai. Tianjin, Zhejiang, Fujian, Liaoning and Jiangsu are moderately competitive. Hebei, Guangxi and Hainan are weakly competitive. Moreover, results show that strongly competitive regions did little to assist marine industrial competitiveness of neighbouring regions. The study offers policy suggestions to enhance marine industrial competitiveness in China's blue economic regions on the basis of these findings.

Finding community structure in spatially constrained complex networks

One feature discovered in the study of complex networks is community structure, in which vertices are gathered into several groups where more edges exist within groups than between groups. Many approaches have been developed for identifying communities; these approaches essentially segment networks based on topological structure or the attribute similarity of vertices, while few approaches consider the spatial character of the networks. Many complex networks are spatially constrained such that the vertices and edges are embedded in space. In geographical space, nearer objects are more related than distant objects. Thus, the relations among vertices are defined not only by the links connecting them but also by the distance between them. In this article, we propose a geo-distance-based method of detecting communities in spatially constrained networks to identify communities that are both highly topologically connected and spatially clustered. The algorithm is based on the fast modularity maximisation (CNM) algorithm. First, we modify the modularity to geo-modularity Qgeo by introducing an edge weight that is the inverse of the geographic distance to the power of n. Then, we propose the concept of a spatial clustering coefficient as a measure of clustering of the network to determine the power value n of the distance. The algorithm is tested with China air transport network and BrightKite social network data-sets. The segmentation of the China air transport network is similar to the seven economic regions of China. The segmentation of the BrightKite social network shows the regionality of social groups and identifies the dynamic social groups that reflect users’ location changes. The algorithm is useful in exploring the interaction and clustering properties of geographical phenomena and providing timely location-based services for a group of people.

Origin and Outbreak of HIV-1 CRF55_01B Among MSM in Shenzhen, China

Origin and Outbreak of HIV-1 CRF55_01B Among MSM in Shenzhen, China

Automated Techniques for Quantification of Coastline Change Rates using Landsat Imagery along Caofeidian, China

This paper focuses on automated extraction and monitoring of coastlines by remote sensing techniques using multi-temporal Landsat imagery along Caofeidian, China. Caofeidian, as one of the active economic regions in China, has experienced dramatic change due to enhanced human activities, such as land reclamation. These processes have caused morphological changes of the Caofeidian shoreline. In this study, shoreline extraction and change analysis are researched. An algorithm based on image texture and mathematical morphology is proposed to automate coastline extraction. We tested this approach and found that it's capable of extracting coastlines from TM and ETM+ images with little human modifications. Then, the detected coastline vectors are imported into Arcgis software, and the Digital Shoreline Analysis System (DSAS) is used to calculate the change rate (the end point rate and linear regression rate). The results show that in some parts of the research area, remarkable coastline changes are observed, especially the accretion rate. The abnormal accretion is mostly attributed to the large-scale land reclamation during 2003 and 2004 in Caofeidian. So we can conclude that various construction projects, especially the land reclamation project, have made Caofeidian shorelines change greatly, far above the normal.

An empirical analysis on the housing prices in the Pearl River Delta Economic Region of China

As the region with the fastest and highest level of economic growth in China, the instability of the Pearl River Delta Economic Region's (PRDER) housing prices has always been a social focus. In order to make housing price stabilization policies effective, more research is required about China's housing market mechanism and the influential factors of housing prices. China used to be a socialist economy since 1949. Deng Xiaoping began China's economic reform and introduced market principles in 1978. Since then China's housing had undergone transition from socialist system to market economy. After 1998, China had housing market economy. This paper aims to understand the housing price behaviour of newly transformed housing market economy of China by analysing the influential factors of China's housing prices compared to that of conventional market economy. This study established a fixed-effect model of panel data and conducts empirical analysis on the influential factors of housing prices in nine cities in the PRDER by adopting the least squares dummy variable method. Because access to China's housing markets data is extremely limited, collecting reliable and consistent housing market data at city level was the biggest challenge in this research. We successfully compiled local housing market data at city level including housing sales price index of the nine cities, number of resident (registered and non-registered-but-long-stay residents), GDP per capita, residential sales area, annual investment on housing development land purchasing cost, and so forth. The analysis confirms that China's housing market follows a market mechanism. Demand is the major driver of housing prices, housing supply tends to lower the housing prices, and land cost is positively correlated with housing prices. Since cities grow with continuing urbanization and industrialization, housing supply policy seems required to effectively stabilize the housing price.

Factors Affecting Regional Per-Capita Carbon Emissions in China Based on an LMDI Factor Decomposition Model

China is considered to be the main carbon producer in the world. The per-capita carbon emissions indicator is an important measure of the regional carbon emissions situation. This study used the LMDI factor decomposition model–panel co-integration test two-step method to analyze the factors that affect per-capita carbon emissions. The main results are as follows. (1) During 1997, Eastern China, Central China, and Western China ranked first, second, and third in the per-capita carbon emissions, while in 2009 the pecking order changed to Eastern China, Western China, and Central China. (2) According to the LMDI decomposition results, the key driver boosting the per-capita carbon emissions in the three economic regions of China between 1997 and 2009 was economic development, and the energy efficiency was much greater than the energy structure after considering their effect on restraining increased per-capita carbon emissions. (3) Based on the decomposition, the factors that affected per-capita carbon emissions in the panel co-integration test showed that Central China had the best energy structure elasticity in its regional per-capita carbon emissions. Thus, Central China was ranked first for energy efficiency elasticity, while Western China was ranked first for economic development elasticity.

Regional variation of energy-related industrial CO2 emissions mitigation in China

This paper analyzes the reasons for regional variations in industrial CO2 emissions mitigation. First, regional industrial CO2 emissions during the “11th Five-Year Plan” period are calculated based on the presented method. Then a two-level perfect decomposition method, LMDI, is used to find the nature of the factors that influence the changes in energy-related industrial CO2 emissions in nine economic regions in China. The changes of industrial CO2 emissions are decomposed into energy emission factor effect, energy structure effect, energy intensity effect, industrial structure effect and economic output effect. As the results suggest, rapid growth of industry is the most important factor responsible for the increase in CO2 emissions. The adjustment of both industrial structure and energy structure contributes to the increase of CO2 emissions slightly. Energy consumption per unit GDP is the most important measure of CO2 emissions and the energy emission factor by itself also makes a weeny contribution to CO2 reduction as a result of electricity generation efficiency enhancement.

Spatial Variation and Space Optimization of the Development of China’s Circular Economy

China＇s circular economy is still at the initial stage, whose development has many difficulties and problems requir- ing immediate resolution theoretically and practically. Due to the differences of regions on the scale of land, endowment of resources, economic basis and cultural background, the devel- opmental levels and capabilities of circular economy are inevi- tably different. Based on establishing the indicator system for assessing the developmental level of regional circular economy, spatial variation of China＇s circular economy is measured by the quantitative measurement using principal component analysis, and the existing problems are also analyzed and discussed. On one hand, the differences of the development capability of the circular economy of different provinces （cities） are profound in China; （!）Difference between the first category （strong） and the second category （relatively strong） is 1.1264 points. Difference between the second category and the third category （relatively weak） is 0.3867 points. Difference between the third category and the fourth category （weak） is 1.0238 points. Differencebetween the tlrst category and the tourtla category reaches up to 2.0869 points. Average difference between the area where the developmental level of circular economy is relatively strong and the area where the developmental level of circular economy is relatively weak is 1.3617 points. （~）The differences of the dis- tribution of the areas, with different development capability of circular economy, which are located in the three economic regions of China, are also profound. The regions with a relatively strong development capability of circular economy are mainly located in the eastern economic area, which account for 22.58% of the whole regions, while only account for 12.90% in the middle and western economic areas. On the contrary, the regions with a relatively weak development capability of circular economy account for 48.39% in the middle and western area, while ac- count for 16.13% in the eastern area. On the other hand, among regions with different development capability of circular econ- omy, the regions with a relatively weak development capability of circular economy are in a dominant position, which accountfor 64.52% of all the provinces （cities）, which indicates that the development of the China＇s circular economy still has a long way to go. Though certain achievements have been made in the development of China＇s circular economy, in general, there are still some obstacles to be tacked in the development of China＇s circular economy which require the economic, legal and administrative methods.

An Analysis of Temporal Evolution of NDVI in Various Vegetation-Climate Regions in Inner Mongolia, China

Inner Mongolia is an important ecological barrier in northern China. The vegetation coverage and changes in the region will directly affect many important economic regions in China. In this paper, based on the long time series NOAA/AVHRR NDVI dataset and vegetation-climate regions map in Inner Mongolia, we utilized the Mann - Kendall non-parametric test to analyze vegetation change treads in different vegetation-climatic regions from 1982 to 2006. The results showed that different vegetation-climate regions had different vegetation change treads. Therein, Central and Western parts of Inner Mongolia had an ascending trend, while, the eastern part had a descending trend. Inner Mongolia span different climatic regions, and plants lived there had various adaptive capacities under different environments. Therefore, its change trends also were quite different. All these illustrate that, under the background of climate change, the sensibility of vegetation are significant different and some plants in different regions have showed their adaptive capacities.

Epidemiology and clinical phenomenology for Parkinson's disease with pain and fatigue

We conducted a cross-sectional analysis with 901 Parkinson's disease (PD) patients in China to understand the epidemiological characteristics of PD pain among Chinese patients. In addition, we searched PubMed and the China Hospital Knowledge Database for epidemiological studies of pain and fatigue among PD patients from 1999 to 2011 to understand the prevalence of these symptoms around the world and associated clinical features. The 901 PD cases were recruited from 42 university affiliated hospitals randomly selected from seven provincial capitals across four economic regions of China. We documented motor and non-motor symptoms via clinical examinations and questionnaire surveys. Using logistic regression models, we evaluated factors that were associated with PD pain among these Chinese patients. Of the 901 Chinese patients, 269 (29.9%) had PD-related pain. After adjusting for confounders, only dyskinesias (OR = 2.66) and depression (OR = 2.88) were independently associated with PD pain. The literature search identified a total of 16 eligible studies on PD-pain and 19 on PD fatigue with various tools for symptom assessment. The data suggest a crude prevalence of 33.7% for PD pain in Asia and 79.4% in Northern Europe; the prevalence for PD fatigue was 35.4% in Northern Europe and 59.1% in Western Europe. Interestingly, Northern-European PD patients reported the highest prevalence of pain, but the lowest prevalence of fatigue. These studies suggest that motor complications and depression are likely key predictors for PD pain, while disease severity, depression and sleep disturbance are associated with PD fatigue. More studies with standardized methods would be needed to better understand the prevalence of PD pain and fatigue across various regions of the world.

Science & Technology Input and Economic Growth: An Empirical Analysis Based on the Three Major Coastal Economic Regions of China

Abstract There is close relationship between science & technology inputs and economic growth. Based on the data of science & technology input and economic growth, the paper makes the econometric models analysis on the economic growth and science & technology input of the three major coastal economic regions of China. The paper analyzes and compares the contribution rate of science & technology inputs to economic growth of the three major economic regions.

An Assessment of Low-Carbon Efficiency Evaluation in the Prospect of Environmental Optimization

From the prospect of environmental optimization the paper establishes a two-dimensional structure of low-carbon efficiency model firstly, with which the different efficiency of economic development comes down to four models. Then the paper builds evaluation index system on low-carbon by taking the CCR model of DEA method as the main analysis approach. On the basis of the above the paper researches on the ecological economy efficiency of 7 economic regions in China from the three levels，namely economic growth efficiency, environmental optimization efficiency and low-carbon efficiency. Eventually, through index evaluation process on the development situation of the above-mentioned economic regions from 2006 and 2007 this article puts forward strategic development policy recommendations advices for the derived results.

Spatial Autocorrelation Analysis on Regional Economic Disparity of Northeast Economic Region in China

Popular regional inequality indexes such as variation coefficient and Gini coefficient can only reveal overall inequal-it),, and have limited ability in revealing spatial dependence or spatial agglomeration.Recently some methods of exploratory spatial data analysis such as spatial autocorrelation have provid-ed effective tools to analyze spatial agglomeration and cluster, which can reveal the pattern of regional inequality.This article attempts to use spatial autocorrelation at county level to get refined spatial pattern of regional disparity in Chinese northeast economic region over 2000-2006 (2001 absent).The result in-dicates that the basic trend of regional economy is an increasing concentration of growth among counties in northeast economic region, and there are two geographical clusters of poorer coun-ties including the counties in western Liaoning Province and adjacent counties in Inner Mongolia, poorer counties of Heihe, Qiqihar and Suihua in Heilongjiang Province.This article also reveals that we can use the methods of exploratory spatial data analysis as the supplementary analysis methods in regional eco-nomic analysis.

Migration, Changes of City-Region Structure and Implications for Planning Practices and Regional Development Policies in the Yangtze River Delta Area in China

The Yangtze River Delta Area (YRDA), especially Metropolitan Shanghai, is undoubtedly the leading economic region in China, and it has become one of the most important population convergence areas. It is also widely considered as the sixth largest urban agglomeration in the world. Concluding that migration is the most important aspect of population dynamics in YRDA, the author studies two important forms of internal migration: migration into or out of YRDA, and migration among different cities within YRDA. The paper explores how both forms of migration jointly influence the population distribution among cities and determine the changes of the city-region structure. Furthermore, the paper makes a demographic projection of the future evolution of the area based on estimates of urban-specific fertility, mortality, and net migration. The author suggests that it is necessary to adopt migration-led development strategy and polices in YRDA, in the context of the national population redistribution and achieving a balanced urban–rural development. The author also suggests that it should strike a good balance between migration and regional sustainability. Furthermore, the author suggests that differential development strategies should be advocated for different cities within YRDA, and it is necessary to strengthen regional coordination system for achieving an integrated regional development strategy in the area.

Ecological analysis of an emerging urban landscape pattern—desakota: a case study in Suzhou, China

Recent scholarly efforts to investigate the conventional wisdom of urban transition and conceptualize the distinct patterns of urbanization emerging in China, simply referred to as “desakota”, have not yielded any conclusive validation. The possible existence of “desakota” is significant for landscape ecology and regional science research in that it challenges long cherished Western notions concerning the separation of urban processes from rural processes and the spatial uniqueness of the respective landscapes. This paper examines physical evidence of desakota from land use changes and tempo-spatial dynamics of desakota development in the lower Yangtze River Delta—one of the most populous and rapidly growing economic regions in China. The paper uses satellite data in 1990, 1995 and 2000 to spectrally disaggregate such rural landscape patterns as urban construction expanding from existing commercial and industrial centers, rural non-agricultural construction, special large infrastructure construction, and crop cultivation. The paper inspects one transect (60 km long and 12 km wide) cutting across Suzhou City in south and Changshu City in north. The transect is divided into four segments to investigate quantitative changes of land types between the two cities over time. The paper applies landscape ecological metrics to analyze tempo-spatial patterns of desakota changes in terms of counts, densities, shapes, compositions, spatial relationships and diversities. The paper concludes: (1) desakota occurred in Suzhou area before 1990 and witnessed two phases of development, dramatic expansion between 1990 and 1995 and consolidation during 1995–2000; (2) desakota dynamics show distinct spatial patterns, new growth of large and specialized urban districts dominant in the vicinity of large cities (Suzhou) and incremental expansion of existing urban places in small cities and rural areas; and (3) landscape metrics are very informative in discerning dynamics and patterns of land use and land cover changes and different metrics vary in descriptive power and sensitivity.

Urbanization in the Pearl River Delta Economic Zone, China

The Pearl River Delta Economic Zone (PRDEZ) is one of the most vigorous economic regions in China, and even in the world. Since the economic reform and opening up to the outside world, PRDEZ has been undergoing rapid urban expansion. based on a large number of investigative data, three indices (expansion coefficient of urban land, harmonious coefficient between population and cropland, and benefit coefficient of urban land) were designed and used to discuss the interrelationships between urbanization, economy and land use. The results suggest that urbanization is not the main reason for a reduction in cropland in the study area. In contrast, urbanization has the following advantages: 1) Urbanization of the rural population favours the release of land from rural residential area; 2) Urbanization can help to improve the city's agglomeration effect in terms of both population and economy; 3) Urbanization can contribute to improving the degree of intensification of land use; and 4) Urbanization can help to improve land-use efficiency. Therefore, urbanization may be an effective way to solve the contradiction between 'more population and much less land' in the study area.