Bike-and-Rail promoting in Xi’an city

2015 ◽  
pp. 47-50
Keyword(s):  
Xi’An City

scholarly journals Evaluation of the Equity and Regional Management of Some Urban Green Space Ecosystem Services: A Case Study of Main Urban Area of Xi’an City

Forests ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 813
Author(s):  
Hui Dang ◽  
Jing Li ◽  
Yumeng Zhang ◽  
Zixiang Zhou
Keyword(s):  
Ecosystem Services ◽  
Carbon Sequestration ◽  
Urban Areas ◽  
Green Space ◽  
Well Being ◽  
Urban Green Space ◽  
Green Spaces ◽  
Deposition Flux ◽  
Urban Green ◽  
Xi’An City

Urban green spaces can provide many types of ecosystem services for residents. An imbalance in the pattern of green spaces leads to an inequality of the benefits of such spaces. Given the current situation of environmental problems and the basic geographical conditions of Xi’an City, this study evaluated and mapped four kinds of ecosystem services from the perspective of equity: biodiversity, carbon sequestration, air purification, and climate regulation. Regionalization with dynamically constrained agglomerative clustering and partitioning (REDCAP) was used to obtain the partition groups of ecosystem services. The results indicate that first, the complexity of the urban green space community is low, and the level of biodiversity needs to be improved. The dry deposition flux of particulate matter (PM2.5) decreases from north to south, and green spaces enhance the adsorption of PM2.5. Carbon sequestration in the south and east is higher than that in the north and west, respectively. The average surface temperature in green spaces is lower than that in other urban areas. Second, urban green space resources in the study area are unevenly distributed. Therefore, ecosystem services in different areas are inequitable. Finally, based on the regionalization of integrated ecosystem services, an ecosystem services cluster was developed. This included 913 grid spaces, 12 partitions, and 5 clusters, which can provide a reference for distinct levels of ecosystem services management. This can assist urban managers who can use these indicators of ecosystem service levels for planning and guiding the overall development pattern of green spaces. The benefits would be a maximization of the ecological functions of green spaces, an improvement of the sustainable development of the city, and an improvement of people’s well-being.

scholarly journals The Tapio Decoupling Principle and Key Strategies for Changing Factors of Chinese Urban Carbon Footprint Based on Cloud Computing

2021 ◽  
Vol 18 (4) ◽  
pp. 2101
Author(s):  
Min Shang ◽  
Ji Luo
Keyword(s):  
Economic Growth ◽  
Cloud Computing ◽  
Carbon Footprint ◽  
Driving Factors ◽  
City Size ◽  
Series Data ◽  
Marginal Effect ◽  
Low Carbon ◽  
The Impact ◽  
Xi’An City

The expansion of Xi’an City has caused the consumption of energy and land resources, leading to serious environmental pollution problems. For this purpose, this study was carried out to measure the carbon carrying capacity, net carbon footprint and net carbon footprint pressure index of Xi’an City, and to characterize the carbon sequestration capacity of Xi’an ecosystem, thereby laying a foundation for developing comprehensive and reasonable low-carbon development measures. This study expects to provide a reference for China to develop a low-carbon economy through Tapio decoupling principle. The decoupling relationship between CO2 and driving factors was explored through Tapio decoupling model. The time-series data was used to calculate the carbon footprint. The auto-encoder in deep learning technology was combined with the parallel algorithm in cloud computing. A general multilayer perceptron neural network realized by a parallel BP learning algorithm was proposed based on Map-Reduce on a cloud computing cluster. A partial least squares (PLS) regression model was constructed to analyze driving factors. The results show that in terms of city size, the variable importance in projection (VIP) output of the urbanization rate has a strong inhibitory effect on carbon footprint growth, and the VIP value of permanent population ranks the last; in terms of economic development, the impact of fixed asset investment and added value of the secondary industry on carbon footprint ranks third and fourth. As a result, the marginal effect of carbon footprint is greater than that of economic growth after economic growth reaches a certain stage, revealing that the driving forces and mechanisms can promote the growth of urban space.

scholarly journals Current and Future Land Use Characters of a National Central City in Eco-Fragile Region—A Case Study in Xi’an City Based on FLUS Model

Land ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 286
Author(s):  
Dingrao Feng ◽  
Wenkai Bao ◽  
Meichen Fu ◽  
Min Zhang ◽  
Yiyu Sun
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Urban Development ◽  
Urban Expansion ◽  
Land Use Patterns ◽  
Use Patterns ◽  
Pattern Change ◽  
Land Use Dynamics ◽  
The Future ◽  
Xi’An City

Land use change plays a key role in terrestrial systems and drives the process of ecological pattern change. It is important to investigate the process of land use change, predict land use patterns, and reveal the characteristics of land use dynamics. In this study, we adopted the Markov model and future land use (FLUS) model to predict the future land use conditions in Xi’an city. Furthermore, we investigated the characteristics of land use change from a novel perspective, i.e., via establishment of a complex network model. This model captured the characteristics of the land use system during different periods. The results indicated that urban expansion and cropland loss played an important role in land use pattern change. The future gravity center of urban development moved along the opposite direction to that from 2000 to 2015 in Xi’an city. Although the rate of urban expansion declined in the future, urban expansion remained the primary driver of land use change. The primary urban development directions were east-southeast (ENE), north-northeast (NNE) and west-southwest (WSW) from 1990 to 2000, 2000 to 2015, and 2015 to 2030, respectively. In fact, cropland played a vital role in land use dynamics regarding all land use types, and the stability of the land use system decreased in the future. Our study provides future land use patterns and a novel perspective to better understand land use change.

Increased Income, Energy Choice and Environment Sustainable Development : Based on the Survey in Western Mountainous Areas in China

2011 ◽  
Vol 361-363 ◽  
pp. 1606-1609
Author(s):  
Xiu Jun Tai
Keyword(s):  
Sustainable Development ◽  
Rural Households ◽  
Shaanxi Province ◽  
Western China ◽  
Energy Structure ◽  
Mountainous Areas ◽  
Additional Insight ◽  
The Relationship ◽  
Xi’An City ◽  
Energy Choice

The relationship between increasing income of rural households and energy choice is explored. Previous studies have been equivocal because they ignored the consideration of out-migration, which is a distinctive characteristic of present China . This study provides additional insight by considering income structure and energy structure of rural households in western China. The research was conducted in Zhouzhi County in the jurisdiction of Xi’an city, Shaanxi Province, China. Through questionnaire survey, 1074 rural households’ detailed information about their livelihoods were obtained. After descriptive statistics analysis and econometrics model analysis, we provide evidence that migration income plays a important role when rural households choosing modern energy such as electricity or gas, which shows higher income housholds like to choose cleaner but expensive energy. We also find out-migration can reduce family firewood consumption, transforming the use of firewood to other cleaner forms of energy, which can keep the ecological environment sustainable development.

Research on Applied-Information Technology with PM2.5 Generation and Evolution Model Based on BP Neural Network

2014 ◽  
Vol 1003 ◽  
pp. 226-229 ◽  
Author(s):  
Ying Hong Xie ◽  
Xiao Wei Han ◽  
Qi Li
Keyword(s):  
Neural Network ◽  
Information Technology ◽  
Neural Network Model ◽  
Bp Neural Network ◽  
Influence Factors ◽  
Evolution Model ◽  
Good Reliability ◽  
Bp Neural Network Model ◽  
Near Future ◽  
Xi’An City

In this paper, BP neural network model is used to establish the occurrence and evolution model of PM2.5 in an area in Xi'an city. In the model, wind, humidity, season, SO2,NO2,PM10, CO,O3 (in one hour ) and O3 (in eight hours ) and other influence factors are all considered. The model has good reliability, it can accurately forecast the value of PM2.5 and its variation in the near future, which can provide the basis for the PM2.5 control.

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