Based on provincial panel data of water footprint and grey water footprint, and with the help of data envelopment analysis model considering and without considering the unde- sirable output, this paper estimates the w...Based on provincial panel data of water footprint and grey water footprint, and with the help of data envelopment analysis model considering and without considering the unde- sirable output, this paper estimates the water resources utilization efficiency in China from 1997 to 2011. The spatial weighting matrix based on economy-spatial distance function is established to discuss spatial autocorrelation of water resources utilization efficiency. With the help of absolute/3-convergence model, this paper concludes that there exists/%convergence in the water resources utilization efficiency. Under the conditions of considering and without considering the undesirable output, it takes about 52.6 and 5.6 years respectively to achieve the extent of half of convergence. By mean of the spatial Durbin econometric model, this paper studies spatial spillover effects of the provincial water resources utilization efficiency in China. The results are as follows. 1） With considering and without considering the undesir- able output, there is significant spatial correlation in provincial water resource efficiency in China. 2） Under the two cases, the spatial autoregressive coefficients （p） are 0.278 and 0.507 respectively, at 1% significance level. There exist the spatial spillover effects of provin- cial water resources utilization efficiency. 3） With considering the undesirable output, these factors of the education funds, the transportation infrastructure, and the industrial and agri- cultural water consumption proportion have positive impacts. These factors of foreign direct investment, the industry value-added water consumption per ten thousand yuan, per capita water consumption, and the total precipitation have negative impacts. 4） Without considering the undesirable output, the factor of GDP per laborer has a greater positive significant influ- ence on the water resources utilization efficiency. However the facts of industry value-added water consumption in ten thousand yuan and the transportation infrastructure have no sig- nificant influence. 5） Regardless of undesirable output of water resources utilization efficiency the assessment of the present real water resources utilization in China will be distorted and policy-making will be misled. The water efficiency measure considering environmental factors （such as gray water footprint） is more reasonable.展开更多
Data show that carbon emissions are increasing due to human energy consumption associated with economic development. As a result, a great deal of attention has been focused on efforts to reduce this growth in carbon e...Data show that carbon emissions are increasing due to human energy consumption associated with economic development. As a result, a great deal of attention has been focused on efforts to reduce this growth in carbon emissions as well as to formulate policies to address and mitigate climate change. Although the majority of previous studies have explored the driving forces underlying Chinese carbon emissions, few have been carried out at the city-level because of the limited availability of relevant energy consumption statistics. Here, we utilize spatial autocorrelation, Markov-chain transitional matrices, a dynamic panel model, and system generalized distance estimation(Sys-GMM) to empirically evaluate the key determinants of carbon emissions at the city-level based on Chinese remote sensing data collected between 1992 and 2013. We also use these data to discuss observed spatial spillover effects taking into account spatiotemporal lag and a range of different geographical and economic weighting matrices. The results of this study suggest that regional discrepancies in city-level carbon emissions have decreased over time, which are consistent with a marked spatial spillover effect, and a ‘club' agglomeration of high-emissions. The evolution of these patterns also shows obvious path dependence, while the results of panel data analysis reveal the presence of a significant U-shaped relationship between carbon emissions and per capita GDP. Data also show that per capita carbon emissions have increased in concert with economic growth in most cities, and that a high-proportion of secondary industry and extensive investment growth have also exerted significant positive effects on city-level carbon emissions across China. In contrast, rapid population agglomeration, improvements in technology, increasing trade openness, and the accessibility and density of roads have all played a role in inhibiting carbon emissions. Thus, in order to reduce emissions, the Chinese government should legislate to inhibit the effects of factors that promote the release of carbon while at the same time acting to encourage those that mitigate this process. On the basis of the analysis presented in this study, we argue that optimizing industrial structures, streamlining extensive investment, increasing the level of technology, and improving road accessibility are all effective approaches to increase energy savings and reduce carbon emissions across China.展开更多
The Yangtze River Delta(YRD) is a region in China with a serious contradiction between economic growth and environmental pollution. Exploring the spatiotemporal effects and influencing factors of air pollution in the ...The Yangtze River Delta(YRD) is a region in China with a serious contradiction between economic growth and environmental pollution. Exploring the spatiotemporal effects and influencing factors of air pollution in the region is highly important for formulating policies to promote the high-quality development of urban industries. This study uses the spatial Durbin model(SDM) to analyze the local direct and spatial spillover effects of industrial transformation on air pollution and quantifies the contribution of each factor. From 2008 to 2018, there was a significant spatial agglomeration of industrial sulfur dioxide emissions(ISDE) in the YRD, and every 1% increase in ISDE led to a synchronous increase of 0.603% in the ISDE in adjacent cities. The industrial scale index(ISCI) and industrial structure index(ISTI), as the core factors of industrial transformation, significantly affect the emissions of sulfur dioxide in the YRD, and the elastic coefficients are 0.677 and-0.368, respectively. The order of the direct effect of the explanatory variables on local ISDE is ISCI>ISTI>foreign direct investment(FDI)>enterprise technological innovation(ETI)>environmental regulation(ER)> per capita GDP(PGDP). Similarly, the order of the spatial spillover effect of all variables on ISDE in adjacent cities is ISCI>PGDP>FDI>ETI>ISTI>ER, and the coefficients of the ISCI and ISTI are 1.531 and 0.113, respectively. This study contributes to the existing research that verifies the environmental Kuznets curve in the YRD, denies the pollution heaven hypothesis, indicates the Porter hypothesis, and provides empirical evidence for the formation mechanism of regional environmental pollution from a spatial spillover perspective.展开更多
In this study, we adopt kernel density estimation, spatial autocorrelation, spatial Markov chain, and panel quantile regression methods to analyze spatial spillover effects and driving factors of carbon emission inten...In this study, we adopt kernel density estimation, spatial autocorrelation, spatial Markov chain, and panel quantile regression methods to analyze spatial spillover effects and driving factors of carbon emission intensity in 283 Chinese cities from 1992 to 2013. The following results were obtained.(1) Nuclear density estimation shows that the overall average carbon intensity of cities in China has decreased, with differences gradually narrowing.(2) The spatial autocorrelation Moran's I index indicates significant spatial agglomeration of carbon emission intensity is gradually increasing; however, differences between regions have remained stable.(3) Spatial Markov chain analysis shows a Matthew effect in China's urban carbon emission intensity. In addition, low-intensity and high-intensity cities characteristically maintain their initial state during the transition period. Furthermore, there is a clear "Spatial Spillover" effect in urban carbon emission intensity and there is heterogeneity in the spillover effect in different regional contexts; that is, if a city is near a city with low carbon emission intensity, the carbon emission intensity of the first city has a higher probability of upward transfer, and vice versa.(4) Panel quantile results indicate that in cities with low carbon emission intensity, economic growth, technological progress, and appropriate population density play an important role in reducing emissions. In addition, foreign investment intensity and traffic emissions are the main factors that increase carbon emission intensity. In cities with high carbon intensity, population density is an important emission reduction factor, and technological progress has no significant effect. In contrast, industrial emissions, extensive capital investment, and urban land expansion are the main factors driving the increase in carbon intensity.展开更多
This paper makes an empirical analysis of the spatial spillover effect of regional economic growth by using Moran’s I and Spatial Durbin Model to study the input and output of technological progress, with the panel d...This paper makes an empirical analysis of the spatial spillover effect of regional economic growth by using Moran’s I and Spatial Durbin Model to study the input and output of technological progress, with the panel data of 21 prefecture-level cities in Guangdong Province from 2008 to 2017. The empirical results show that the spatial autocorrelation exists in the economic development of Guangdong Province, and both the input and output of scientific research innovation have a significant positive effect on the regional economic growth. Under the spatial contiguity weights matrix, the output of scientific research and innovation has a more obvious spillover effect on the economic growth of neighboring cities than the input of scientific research and innovation.展开更多
This paper examines the significance of spatial externalities for youths’ school-to-training transitions in Germany. For this purpose, it is necessary to address the methodological question of how an individual’s sp...This paper examines the significance of spatial externalities for youths’ school-to-training transitions in Germany. For this purpose, it is necessary to address the methodological question of how an individual’s spatial context has to be operationalized with respect to both its extent and the problem of spatial autocorrelation. Our analyses show that the “zone of influence” comprises of the whole of Germany, not only close-by districts, and that these effects differ between structurally weak and strong regions. Consequently, assuming that only close proximity affects individual outcomes may disregard relevant contextual influences, and for spatial models that require an a priori definition of the weights for spatial units, it may be erroneous to make a decision based on this assumption. Concerning spatial autocorrelation, we found that neglecting local spatial autocorrelation at the context level causes considerable bias to the estimates, especially for districts that are close to the home district.展开更多
为了寻求合理简化的流域地形指数水文模型TOPMODEL(Topographic Index model)用于大尺度的陆面模式,推导了土壤表层饱和导水率k0、衰减因子f和地下水补给速率R空间都可变的扩展的TOPMODEL,并将f空间非均匀分布的TOPMODEL与陆面模式SSiB...为了寻求合理简化的流域地形指数水文模型TOPMODEL(Topographic Index model)用于大尺度的陆面模式,推导了土壤表层饱和导水率k0、衰减因子f和地下水补给速率R空间都可变的扩展的TOPMODEL,并将f空间非均匀分布的TOPMODEL与陆面模式SSiB4耦合(SSiB4/GTOP)。通过耦合模型在f空间非均匀条件下进行实际流域的水文模拟,分析f空间非均匀对流域土壤湿度、蒸散发、地表径流、基流和总径流的影响。主要结论有:(1)k0和R的空间变化并不改变经典TOPMODEL原有关系式,只要定义新的地形指数,k0和R空间非均匀TOPMODEL与空间均匀的TOPMODEL并无区别;(2) f空间变化条件下由于局地的地下水埋深还与局地的f值有关,地形指数相同的区域具有水文相似性这一结论不再成立;(3)与f空间均匀的模拟结果相比较,f随海拔高度h i增加而线性减小使模拟的流域土壤湿度、地表径流和流域蒸散减小但使基流和总径流增加;(4) f空间非均匀对流域水文模拟结果有影响,但其影响明显小于流域地形因子的影响。展开更多
By using a new economic geography model of multi-region to study the impact of market scale on spatial economic structure,we find that the home market effect plays a key role in it.At different development periods,und...By using a new economic geography model of multi-region to study the impact of market scale on spatial economic structure,we find that the home market effect plays a key role in it.At different development periods,under external shocks such as transportation costs and so on,industry shares will change due to the distribution of market scale.The spatial economic structure will gradually evolve into such forms as single core or dual-core structure,especially"central collapse"will be found in the process.Such results can be used to analyze the practical problems,including the"central collapse"in the east,central and west regions of China,the structure of city clusters,etc.With the rapid development of transportation infrastructures,China will form a variety of development patterns on different spatial scales owing to home market effect.The regional convergence can be reached through reducing the economic distance and promoting agglomerative economies,which will help achieve regional coordinated development.展开更多
Due to the limitation of total amount of water resources, it is necessary to enhance water consumption efficiency to meet the increasing water demand of urbanizing China. Based on the panel data of 31 provinces in Chi...Due to the limitation of total amount of water resources, it is necessary to enhance water consumption efficiency to meet the increasing water demand of urbanizing China. Based on the panel data of 31 provinces in China in 1997-2013, we analyze the influencing factors of water consumption efficiency by spatial econometric models. Results show that, 1） Due to the notable spatial autocorrelation characteristics of water consumption efficiency among different provinces in China, general panel data regression model which previous studies often used may be improper to reveal its influencing factors. However, spatial Durbin model may best estimate their relationship. 2） Water consumption efficiency of a certain province may be influenced not only by its socio-economic and eco-environmental indicators, but also by water consumption efficiency in its neighboring provinces. Moreover, it may be influenced by the neighboring provinces＇ socio-economic and eco-environmental indicators. 3） For the macro average case of the 31 provinces in China, if water consumption efficiency in neighboring provinces increased 1%, water consumption efficiency of the local province would increase 0.34%. 4） Among the ten specific indicators we selected, per capita GDP and urbanization level of itself and its neighboring provinces have the most prominent positive effects on water consumption efficiency, and the indirect effects of neighboring provinces are much larger. Therefore, the spatial spillover effects of the economic development level and urbanization level are the primary influencing factors for improving China＇s water consump- tion efficiency. 5） Policy implications indicate that, to improve water consumption efficiency, each province should properly consider potential influences caused by its neighboring prov- inces, especially needs to enhance the economic cooperation and urbanization interaction with neighboring provinces.展开更多
Anomaly separation using geochemical data often involves operations in the frequency domain, such as filtering and reducing noise/signal ratios. Unfortunately, the abrupt edge truncation of an image along edges and ho...Anomaly separation using geochemical data often involves operations in the frequency domain, such as filtering and reducing noise/signal ratios. Unfortunately, the abrupt edge truncation of an image along edges and holes (with missing data) often causes frequency distribution distortion in the frequency domain. For example, bright strips are commonly seen in frequency distribution when using a Fourier transform. Such edge effect distortion may affect information extraction results; sometimes severely, depending on the edge abruptness of the image. Traditionally, edge effects are reduced by smoothing the image boundary prior to applying a Fourier transform. Zero-padding is one of the most commonly used smoothing methods. This simple method can reduce the edge effect to some degree but still distorts the image in some cases. Moreover, due to the complexity of geoscience images, which can include irregular shapes and holes with missing data, zero-padding does not always give satisfactory results. This paper proposes the use of decay functions to handle edge effects when extracting information from geoscience images. As an application, this method has been used in a newly developed multifractal method (S-A) for separating geochemical anomalies from background patterns. A geochemical dataset chosen from a mineral district in Nova Scotia, Canada was used to validate the method.展开更多
The spatial organization of the Chinese petrochemical industry was optimized according to the status of development of the industry employing linear programming and ArcGIS spatial analysis tools. We first identified t...The spatial organization of the Chinese petrochemical industry was optimized according to the status of development of the industry employing linear programming and ArcGIS spatial analysis tools. We first identified the indexes of the spatial organization of the petrochemical industry and established a comprehensive evaluation index system that in- cludes four major categories and 11 indicators. The weight of each index was then deter- mined by the analytical hierarchy process. Afterward, taking the 337 Chinese prefecture-level administrations as basic units and scientifically evaluating the potential comprehensive layout coefficients of the cities, 151 prefecture-level administrative units were selected as the basis for the choice of optimization sites with a linear programming model. Secondly, using the 151 prefecture-level administrative units and the maximum-coverage model, the optimal number and spatial distribution of refineries were identified for service radii of 100, 200 and 300 km. Thirdly, considering the actual distribution of China＇s refineries, general rules for the number of refinery layout points and objective values were summarized, and 52 refinery layout points were selected for China. Finally, with ArcGIS spatial analysis tools, the spatial effect of the 52 optimal refinery layout points was simulated for the service scope and socioeconomic factors respectively, and the GDP and population data for each refinery layout point were then ex- tracted within the service scope. On this basis and with estimation of the intensity of crude-oil consumption, final results were obtained for the optimal spatial organization of the Chinese refining capacity and ethylene production capacity.展开更多
基金National Social Science Foundation of China, No. 11BJY063 Program for New Century Excellent Talents in University, No.NECT-13-0844
文摘Based on provincial panel data of water footprint and grey water footprint, and with the help of data envelopment analysis model considering and without considering the unde- sirable output, this paper estimates the water resources utilization efficiency in China from 1997 to 2011. The spatial weighting matrix based on economy-spatial distance function is established to discuss spatial autocorrelation of water resources utilization efficiency. With the help of absolute/3-convergence model, this paper concludes that there exists/%convergence in the water resources utilization efficiency. Under the conditions of considering and without considering the undesirable output, it takes about 52.6 and 5.6 years respectively to achieve the extent of half of convergence. By mean of the spatial Durbin econometric model, this paper studies spatial spillover effects of the provincial water resources utilization efficiency in China. The results are as follows. 1） With considering and without considering the undesir- able output, there is significant spatial correlation in provincial water resource efficiency in China. 2） Under the two cases, the spatial autoregressive coefficients （p） are 0.278 and 0.507 respectively, at 1% significance level. There exist the spatial spillover effects of provin- cial water resources utilization efficiency. 3） With considering the undesirable output, these factors of the education funds, the transportation infrastructure, and the industrial and agri- cultural water consumption proportion have positive impacts. These factors of foreign direct investment, the industry value-added water consumption per ten thousand yuan, per capita water consumption, and the total precipitation have negative impacts. 4） Without considering the undesirable output, the factor of GDP per laborer has a greater positive significant influ- ence on the water resources utilization efficiency. However the facts of industry value-added water consumption in ten thousand yuan and the transportation infrastructure have no sig- nificant influence. 5） Regardless of undesirable output of water resources utilization efficiency the assessment of the present real water resources utilization in China will be distorted and policy-making will be misled. The water efficiency measure considering environmental factors （such as gray water footprint） is more reasonable.
基金National Natural Science Foundation of China,No.41601151Guangdong Natural Science Foundation,No.2016A030310149
文摘Data show that carbon emissions are increasing due to human energy consumption associated with economic development. As a result, a great deal of attention has been focused on efforts to reduce this growth in carbon emissions as well as to formulate policies to address and mitigate climate change. Although the majority of previous studies have explored the driving forces underlying Chinese carbon emissions, few have been carried out at the city-level because of the limited availability of relevant energy consumption statistics. Here, we utilize spatial autocorrelation, Markov-chain transitional matrices, a dynamic panel model, and system generalized distance estimation(Sys-GMM) to empirically evaluate the key determinants of carbon emissions at the city-level based on Chinese remote sensing data collected between 1992 and 2013. We also use these data to discuss observed spatial spillover effects taking into account spatiotemporal lag and a range of different geographical and economic weighting matrices. The results of this study suggest that regional discrepancies in city-level carbon emissions have decreased over time, which are consistent with a marked spatial spillover effect, and a ‘club' agglomeration of high-emissions. The evolution of these patterns also shows obvious path dependence, while the results of panel data analysis reveal the presence of a significant U-shaped relationship between carbon emissions and per capita GDP. Data also show that per capita carbon emissions have increased in concert with economic growth in most cities, and that a high-proportion of secondary industry and extensive investment growth have also exerted significant positive effects on city-level carbon emissions across China. In contrast, rapid population agglomeration, improvements in technology, increasing trade openness, and the accessibility and density of roads have all played a role in inhibiting carbon emissions. Thus, in order to reduce emissions, the Chinese government should legislate to inhibit the effects of factors that promote the release of carbon while at the same time acting to encourage those that mitigate this process. On the basis of the analysis presented in this study, we argue that optimizing industrial structures, streamlining extensive investment, increasing the level of technology, and improving road accessibility are all effective approaches to increase energy savings and reduce carbon emissions across China.
基金The Strategic Priority Research Program of the Chinese Academy of Sciences,No.XDA23020101National Natural Science Foundation of China,No.41901181。
文摘The Yangtze River Delta(YRD) is a region in China with a serious contradiction between economic growth and environmental pollution. Exploring the spatiotemporal effects and influencing factors of air pollution in the region is highly important for formulating policies to promote the high-quality development of urban industries. This study uses the spatial Durbin model(SDM) to analyze the local direct and spatial spillover effects of industrial transformation on air pollution and quantifies the contribution of each factor. From 2008 to 2018, there was a significant spatial agglomeration of industrial sulfur dioxide emissions(ISDE) in the YRD, and every 1% increase in ISDE led to a synchronous increase of 0.603% in the ISDE in adjacent cities. The industrial scale index(ISCI) and industrial structure index(ISTI), as the core factors of industrial transformation, significantly affect the emissions of sulfur dioxide in the YRD, and the elastic coefficients are 0.677 and-0.368, respectively. The order of the direct effect of the explanatory variables on local ISDE is ISCI>ISTI>foreign direct investment(FDI)>enterprise technological innovation(ETI)>environmental regulation(ER)> per capita GDP(PGDP). Similarly, the order of the spatial spillover effect of all variables on ISDE in adjacent cities is ISCI>PGDP>FDI>ETI>ISTI>ER, and the coefficients of the ISCI and ISTI are 1.531 and 0.113, respectively. This study contributes to the existing research that verifies the environmental Kuznets curve in the YRD, denies the pollution heaven hypothesis, indicates the Porter hypothesis, and provides empirical evidence for the formation mechanism of regional environmental pollution from a spatial spillover perspective.
基金National Natural Science Foundation of China,No.41601151Natural Science Foundation of Guangdong Province,No.2016A030310149Pearl River S&T Nova Program of Guangzhou(201806010187)
文摘In this study, we adopt kernel density estimation, spatial autocorrelation, spatial Markov chain, and panel quantile regression methods to analyze spatial spillover effects and driving factors of carbon emission intensity in 283 Chinese cities from 1992 to 2013. The following results were obtained.(1) Nuclear density estimation shows that the overall average carbon intensity of cities in China has decreased, with differences gradually narrowing.(2) The spatial autocorrelation Moran's I index indicates significant spatial agglomeration of carbon emission intensity is gradually increasing; however, differences between regions have remained stable.(3) Spatial Markov chain analysis shows a Matthew effect in China's urban carbon emission intensity. In addition, low-intensity and high-intensity cities characteristically maintain their initial state during the transition period. Furthermore, there is a clear "Spatial Spillover" effect in urban carbon emission intensity and there is heterogeneity in the spillover effect in different regional contexts; that is, if a city is near a city with low carbon emission intensity, the carbon emission intensity of the first city has a higher probability of upward transfer, and vice versa.(4) Panel quantile results indicate that in cities with low carbon emission intensity, economic growth, technological progress, and appropriate population density play an important role in reducing emissions. In addition, foreign investment intensity and traffic emissions are the main factors that increase carbon emission intensity. In cities with high carbon intensity, population density is an important emission reduction factor, and technological progress has no significant effect. In contrast, industrial emissions, extensive capital investment, and urban land expansion are the main factors driving the increase in carbon intensity.
文摘This paper makes an empirical analysis of the spatial spillover effect of regional economic growth by using Moran’s I and Spatial Durbin Model to study the input and output of technological progress, with the panel data of 21 prefecture-level cities in Guangdong Province from 2008 to 2017. The empirical results show that the spatial autocorrelation exists in the economic development of Guangdong Province, and both the input and output of scientific research innovation have a significant positive effect on the regional economic growth. Under the spatial contiguity weights matrix, the output of scientific research and innovation has a more obvious spillover effect on the economic growth of neighboring cities than the input of scientific research and innovation.
文摘This paper examines the significance of spatial externalities for youths’ school-to-training transitions in Germany. For this purpose, it is necessary to address the methodological question of how an individual’s spatial context has to be operationalized with respect to both its extent and the problem of spatial autocorrelation. Our analyses show that the “zone of influence” comprises of the whole of Germany, not only close-by districts, and that these effects differ between structurally weak and strong regions. Consequently, assuming that only close proximity affects individual outcomes may disregard relevant contextual influences, and for spatial models that require an a priori definition of the weights for spatial units, it may be erroneous to make a decision based on this assumption. Concerning spatial autocorrelation, we found that neglecting local spatial autocorrelation at the context level causes considerable bias to the estimates, especially for districts that are close to the home district.
文摘By using a new economic geography model of multi-region to study the impact of market scale on spatial economic structure,we find that the home market effect plays a key role in it.At different development periods,under external shocks such as transportation costs and so on,industry shares will change due to the distribution of market scale.The spatial economic structure will gradually evolve into such forms as single core or dual-core structure,especially"central collapse"will be found in the process.Such results can be used to analyze the practical problems,including the"central collapse"in the east,central and west regions of China,the structure of city clusters,etc.With the rapid development of transportation infrastructures,China will form a variety of development patterns on different spatial scales owing to home market effect.The regional convergence can be reached through reducing the economic distance and promoting agglomerative economies,which will help achieve regional coordinated development.
基金Major Projects of the National Natural Science Foundation of China, No.41590844 National Natural Science Foundation of China, No.41571156 Service Project on the Cultivation and Construction for the Characteristic Research Institute of the Chinese Academy of Sciences, No.TSYJS02
文摘Due to the limitation of total amount of water resources, it is necessary to enhance water consumption efficiency to meet the increasing water demand of urbanizing China. Based on the panel data of 31 provinces in China in 1997-2013, we analyze the influencing factors of water consumption efficiency by spatial econometric models. Results show that, 1） Due to the notable spatial autocorrelation characteristics of water consumption efficiency among different provinces in China, general panel data regression model which previous studies often used may be improper to reveal its influencing factors. However, spatial Durbin model may best estimate their relationship. 2） Water consumption efficiency of a certain province may be influenced not only by its socio-economic and eco-environmental indicators, but also by water consumption efficiency in its neighboring provinces. Moreover, it may be influenced by the neighboring provinces＇ socio-economic and eco-environmental indicators. 3） For the macro average case of the 31 provinces in China, if water consumption efficiency in neighboring provinces increased 1%, water consumption efficiency of the local province would increase 0.34%. 4） Among the ten specific indicators we selected, per capita GDP and urbanization level of itself and its neighboring provinces have the most prominent positive effects on water consumption efficiency, and the indirect effects of neighboring provinces are much larger. Therefore, the spatial spillover effects of the economic development level and urbanization level are the primary influencing factors for improving China＇s water consump- tion efficiency. 5） Policy implications indicate that, to improve water consumption efficiency, each province should properly consider potential influences caused by its neighboring prov- inces, especially needs to enhance the economic cooperation and urbanization interaction with neighboring provinces.
文摘Anomaly separation using geochemical data often involves operations in the frequency domain, such as filtering and reducing noise/signal ratios. Unfortunately, the abrupt edge truncation of an image along edges and holes (with missing data) often causes frequency distribution distortion in the frequency domain. For example, bright strips are commonly seen in frequency distribution when using a Fourier transform. Such edge effect distortion may affect information extraction results; sometimes severely, depending on the edge abruptness of the image. Traditionally, edge effects are reduced by smoothing the image boundary prior to applying a Fourier transform. Zero-padding is one of the most commonly used smoothing methods. This simple method can reduce the edge effect to some degree but still distorts the image in some cases. Moreover, due to the complexity of geoscience images, which can include irregular shapes and holes with missing data, zero-padding does not always give satisfactory results. This paper proposes the use of decay functions to handle edge effects when extracting information from geoscience images. As an application, this method has been used in a newly developed multifractal method (S-A) for separating geochemical anomalies from background patterns. A geochemical dataset chosen from a mineral district in Nova Scotia, Canada was used to validate the method.
基金China Postdoctoral Science Foundation, No.2011M500375 National Natural Science Foundation of China, No.40635026 Knowledge Innovation Program of the Chinese Academy of Sciences, No.KZCXZ-YW-Q10-4
文摘The spatial organization of the Chinese petrochemical industry was optimized according to the status of development of the industry employing linear programming and ArcGIS spatial analysis tools. We first identified the indexes of the spatial organization of the petrochemical industry and established a comprehensive evaluation index system that in- cludes four major categories and 11 indicators. The weight of each index was then deter- mined by the analytical hierarchy process. Afterward, taking the 337 Chinese prefecture-level administrations as basic units and scientifically evaluating the potential comprehensive layout coefficients of the cities, 151 prefecture-level administrative units were selected as the basis for the choice of optimization sites with a linear programming model. Secondly, using the 151 prefecture-level administrative units and the maximum-coverage model, the optimal number and spatial distribution of refineries were identified for service radii of 100, 200 and 300 km. Thirdly, considering the actual distribution of China＇s refineries, general rules for the number of refinery layout points and objective values were summarized, and 52 refinery layout points were selected for China. Finally, with ArcGIS spatial analysis tools, the spatial effect of the 52 optimal refinery layout points was simulated for the service scope and socioeconomic factors respectively, and the GDP and population data for each refinery layout point were then ex- tracted within the service scope. On this basis and with estimation of the intensity of crude-oil consumption, final results were obtained for the optimal spatial organization of the Chinese refining capacity and ethylene production capacity.
