Search

Existing research rarely examines the subjective and objective built environment of river valley-type cities in relation to travel mode choice, particularly overlooking the heterogeneity among travelers in these cities. In this paper, based on questionnaire survey data and built environment data, terrain spatial perception (TSP) is introduced to expand the theory of planned behavior (TPB), and a Structural Equation Model (SEM) is established. Factor analysis and path analysis are conducted using SPSS and AMOS to estimate latent variables. An integrated model of SEM and random parameter Logit model (RPLM), which can not only analyze the psychological perception factors of commuters in river valley-type cities but also consider the heterogeneity of psychological perception, was constructed to analyze the impact of personal attributes, objective built environment factors, and psychological latent variables on the commuting mode choice behavior of public transport users in river valley-type cities. The results indicate that the five observation indicators corresponding to the proposed terrain spatial perception latent variables can better explain the terrain spatial perception of commuters in river valley-type cities. Different from plain cities, the subjective and objective built environment of river valley-type cities notably influence the travel behavior of commuters. Moreover, the parameters of terrain spatial perception follow a normal distribution, indicating that the sensitivity of different commuters to the terrain spatial perception of river valley-type cities is heterogeneous. The results of our study can provide a reference for alleviating traffic issues in valley cities. [ABSTRACT FROM AUTHOR]

As a representative city located in the Loess Plateau region of China, Lanzhou is affected by various environmental and engineering factors, such as precipitation, earthquake subsidence, and building construction, which all lead to frequent geological disasters. Obtaining information on land subsidence over a long time series helps us grasp the patterns of change in various types of ground hazard. In this paper, we present the results of using Interferometric Synthetic Aperture Radar (InSAR) to monitor land subsidence in the main urban area of Lanzhou from 26 October 2014 to 12 December 2021. The main influential factors leading to subsidence were analyzed and combined via machine learning simulation to assess the land subsidence risk grade distribution of a building unit. The results show that the annual average deformation rate in Lanzhou ranged from −18.74 to 12.78 mm/yr. Linear subsidence dominated most subsidence areas in Lanzhou during the monitoring period. The subsidence areas were mainly distributed along the Yellow River, the railway, and villages and towns on the edges of urban areas. The main areas where subsidence occurred were the eastern part of Chengguan District, the railway line in Anning District, and the southern parts of Xigu District and Qilihe urban area, accounting for 38.8, 43.5, 32.5, and 51.8% of the area of their respective administrative districts, respectively. The random forest model analysis results show that the factors influencing surface subsidence in Lanzhou were, in order of importance, precipitation, the distribution of faults, the lithology of strata, high-rise buildings, and the distance to the river and railway. Lanzhou experienced excessive groundwater drainage in some areas from 2015 to 2017, with a 1 m drop in groundwater and 14.61 mm surface subsidence in the most critical areas. At the same time, extensive subsidence occurred in areas with highly compressible loess ground and most railway sections, reaching a maximum of −11.68 mm/yr. More than half of the super-tall building areas also showed settlement funnels. The area at a very high risk of future subsidence in Lanzhou covers 22.02 km2, while the high-subsidence-risk area covers 54.47 km2. The areas at greatest risk of future subsidence are Chengguan District and Qilihe District. The city contains a total of 51,163 buildings in the very high-risk area, including about 44.57% of brick-and-timber houses, 51.36% of old housing, and 52.78% of super-tall buildings, which are at especially high risk of subsidence, threatening the lives and properties of the population. The deformation results reveal poor building safety in Lanzhou, providing an essential basis for future urban development and construction. [ABSTRACT FROM AUTHOR]

It is very common that taxi is used as a feeder mode to/from a metro station especially in third-tier cities of China. But research on taxi-metro integrated use is rather limited. This paper investigates the relationship between feeder-related built environment and taxi-metro integrated use by using taxi trajectory data in Lanzhou, China. Firstly, regression models are developed to explore the transfer distance of access/egress trips during peak hours. Then, the catchment area is delineated for collecting feeder-related environment variables. Finally, several negative binomial regressions are employed to examine the relationships between feeder-related built environment and taxi-metro integrated use during peak hours on weekdays. The results reveal that (a) people prefer to use taxi as feeder mode for metro access during morning peak hours and for metro egress during evening peak hours; (b) the transfer distance of taxi-metro integrated use is about 3.8 km; (c) higher mixed land use generates more taxi-metro integrated use during evening peak hours. Higher proportion of residential land use attracts more taxi-metro integrated use for metro access during morning peak hours. Those findings will help transport planners to develop tailored land-use interventions to improve transit accessibility and promote the sustainable multimodal travel. [ABSTRACT FROM AUTHOR]

In order to improve the accuracy of air pollution management and promote the efficiency of coordinated inter-regional prevention and control, this study analyzes the interaction of O3 in Qilihe District, Lanzhou City, China. Data used for analysis was obtained from 63 air quality monitoring stations between November 2017 and October 2018. This paper uses complex network theory to describe the network structure characteristics of O3 pollution spatial correlation. On this basis, the node importance method is used to mine the sub-network with the highest spatial correlation in the O3 network, and use transfer entropy theory to analyse the interaction of pollutants between regions. The results show that the O3 area of Qilihe District, Lanzhou City can be divided into three parts: the urban street community type areas in urban areas, the township and village type areas in mountain areas and the scattered areas represented by isolated nodes. An analysis of the mutual influence of O3 between each area revealed that the impact of O3 on each monitoring station in adjacent areas will vary considerably. Therefore these areas cannot be governed as a whole, and the traditional extensive management measures based on administrative divisions cannot be used to replace all other regional governance measures. There is the need to develop a joint prevention and control mechanism tailored to local conditions in order to improve the accuracy and efficiency of O3 governance. [ABSTRACT FROM AUTHOR]

Analyzing the spatial relationship between humans and water is crucial for regional development and water allocation schemes, particularly in the face of extreme water scarcity in the Yellow River Basin. A quantitative evaluation model of surface water resource accessibility (SWRA) has been developed, with rural settlements serving as the research unit. This model is built upon three key dimensions: topography, distance, and surface water resources within the Yellow River Basin. The results show that: (1) The SWRA range spans from 0.13 to 0.88, with an average value of 0.47 and a standard deviation of 0.05. Higher SWRA values are concentrated in the eastern and western regions, while lower values are predominantly found in the central area. (2) The gradient of SWRA across the 12 catchments, from low to high, is as follows: Sanmenxia station, Lanzhou station, Shizuishan station, Longmen station, Tongguan station, Toudaoguai station, Xiaolangdi station, Huayuankou station, Lijin station, Gaocun station, Ai Shan station, and Tangnaihai station. (3) At the city scale, the SWRA values are generally higher in the eastern areas of 10 cities, with one exception being higher in the west. Conversely, in the western areas of nine cities, the SWRA values are lower. The remaining cities exhibit SWRA values at a medium level. The correlation coefficient between primary industry gross domestic product (GDP) and SWRA is 0.271 (N = 56, Sig = 0.043, in 0.05 level, the correlation is significant), which confirms that SWRA serves as a factor influencing GDP and is appropriately designed for assessing water accessibility. Consequently, managers can utilize SWRA results to make informed decisions regarding regional development and water allocation. [ABSTRACT FROM AUTHOR]

The present study investigates the dynamic evolution characteristics of urban spatial morphology by analyzing real road network data from 2000, 2010, and 2020, along with nighttime lighting data employing spatial analysis methods and spatial syntax models. Accordingly, two separate dimensions of urban morphology: internal and external, are covered. First, the integration and synergy of interior morphology features are analyzed using spatial syntactic modeling. Subsequently, the spatial compactness, fractal dimension, and level of center of gravity shift of the city are assessed by combining the nighttime lighting data with the earlier dataset. This analysis facilitated the deep exploration of the spatiotemporal evolution of the city's external morphology. Building upon this foundation, the interaction between the "internal and external" domains was analyzed further. The main findings of the study reveal a synchronous pattern of urban expansion throughout the evolution of urban spatial morphology. Furthermore, the urban form was observed to undergo a progressive transformation, transitioning from a "single core" morphology to a "primary and secondary double core" morphology. Over time, this development progressed and evolved into a "belt-like multi-core" structure. Additionally, the coupling characteristics further validate the relationship between the structure of the road network and the urban morphology in river valley-type cities. In particular, accessibility of dense and horizontally distributed transportation network was found to significantly influence the spatial development of these cities. As observed, the findings provides valuable insights into understanding the characteristics of internal and external associations regarding urban spatial patterns. [ABSTRACT FROM AUTHOR]

The spatial characteristics of element flow and its spillover are important topics in economics, sociology, and geography, and significant to the promotion of the coordinated development of urban agglomerations. To study element flow in the Lanxi urban agglomeration and its effect to economic development, the spatial network characteristics and economic spillover effect were studied using the methods of spatial network analysis, the spatial Durbin model, and spatial effect decomposition. The results showed that (1) the scale of element flow in the Lanxi urban agglomeration is in an unbalanced distribution state, the scale of element flow in Lanzhou and Xining is higher than that in surrounding cities, and the connection between surrounding cities is also higher than that between other cities; (2) the network structure of element flow in the Lanxi urban agglomeration is relatively intensive, with Lanzhou and Xining as the center of element concentration, which indicates an obvious 'center periphery' structure, and gradually spreads from the core area to the surrounding areas; and (3) the element concentration level of the Lanxi urban agglomeration has a significant positive spillover effect, which plays a significant role in driving the development of surrounding cities. Other factors, such as the social consumption level, have significant direct effects, whereas the industrial structure and residents' income have significant direct and spillover effects, and are the main factors that affect the coordinated development of the regional economy. [ABSTRACT FROM AUTHOR]

Ecotourism is vital for coordinating regional ecological protection with socio-economic development. The Gansu section of the Yellow River Basin is a typical ecologically fragile area in China, and it holds a distinctive position in ecological protection and high-quality development. This study explores spatial differentiation in ecotourist perceptions and their distinct effects on ecotourist satisfaction, revisitation, and recommendation. It uses four cities (Gannan, Linxia, Lanzhou, and Baiyin) in the Gansu section of the Yellow River (mainstream) as examples, employing a questionnaire survey to collect ecotourists' perception data and applying a random forest model and one-way ANOVA for analysis. It was found that: (1) rich ecotourism potential exists in the Gansu section of the Yellow River Basin as an ecologically fragile area; (2) there is spatial differentiation in ecotourist perceptions, and among the four regions, Baiyin stands out for its nature and atmosphere perception, and Lanzhou excels in accessibility and service perception; (3) spatial disparities exist in the influencing factors of ecotourist satisfaction, revisitation, and recommendation. Ecotourists in districts with unique natural resources, such as Gannan and Baiyin, prioritize nature perception, whereas districts with abundant natural resources and an established foundation for ecotourism development, such as Linxia and Lanzhou, emphasize service and atmosphere perception. This study constructs a new research framework to explore spatial variations in ecotourists' perceptions, assisting ecotourism destinations to meet the needs of ecotourists from the supply side, and presents distinctive strategies and recommendations for the development of ecotourism in similar ecologically fragile areas. [ABSTRACT FROM AUTHOR]

This study analyzed the differences in ozone (O3) sensitivity in four different urban areas in China from February 2019 to January 2020 based on data on various near-surface pollutants from passive multi-axis differential optical absorption spectroscopy (MAX-DOAS) sites and nearby China National Environmental Monitoring Center (CNEMC) sites. Across the four cities, the nitrogen dioxide (NO2) and formaldehyde (HCHO) concentrations varied seasonally. Xianghe consistently displayed the lowest NO2 levels, suggesting reduced emissions compared to other cities. Guangzhou, a city with a robust economy and a high level of vehicle ownership, exhibited higher concentrations in spring. Summer brought elevated HCHO levels in Guangzhou, Xianghe, and Shenyang due to intensified photochemical processes. Autumn and winter showed higher HCHO concentrations in Guangzhou and Xianghe compared to Lanzhou and Shenyang. Overall, Guangzhou recorded the highest annual averages, due to its developed economy, while Xianghe's lower NO2 levels were offset by the elevated HCHO due to higher O3 values. The analysis delved into primary and secondary HCHO sources across seasons and used carbon monoxide (CO) and O3 data. Xianghe showcased the dominance of secondary sources in summer and autumn, while Lanzhou was characterized by primary dominance throughout the year. Shenyang mirrored Xianghe's evolution due to industrial emissions. In Guangzhou, due to the high levels of vehicular traffic and sunlight conditions, secondary sources predominantly influenced HCHO concentrations. These findings highlight the interplay between primary and secondary emissions in diverse urban settings. This study explored O3 sensitivity variations across seasons. Xianghe exhibited a balanced distribution among volatile organic compound (VOC)-limited conditions, nitrogen oxide (NOx)-limited conditions, and transitional influences. Lanzhou was mainly affected by VOC-limited conditions in winter and NOx-limited conditions in other seasons. Shenyang's sensitivity varied with the seasons and was primarily influenced by transitions between VOCs and NOx in autumn and NOx-limited conditions otherwise. Guangzhou experienced varied influences. During periods of high O3 pollution, all regions were affected by NOx-limited conditions, indicating the necessity of NOx monitoring in these areas, especially during summer in all regions and during autumn in Xianghe and Guangzhou. [ABSTRACT FROM AUTHOR]

[Display omitted] • The study used the NDDF model to measure the efficiency of urban pollution reduction and carbon synergistic governance. • We identified the spatial aggregation patterns of urban pollution reduction and carbon synergistic governance efficiency. • We compared the magnitude of the drivers of urban pollution reduction and carbon synergistic governance efficiency. • There is an east-high and west-low development pattern of carbon mitigation. • The findings suggest enhancement of the capability of urban coordinated governance in carbon mitigation. This paper is based on the construction of the evaluation system of urban pollution reduction and carbon reduction synergistic governance efficiency indicators. Firstly, we used the NDDF model to measure the efficiency of urban pollution reduction and carbon reduction synergistic governance. We then used the ArcGIS technology and spatial autocorrelation method to explore its spatial distribution pattern, and the spatial econometric model is used to explore its driving factors. The results show that from 2006 to 2020, the synergistic governance efficiency of Chinese cities in terms of pollution reduction and carbon reduction is in a state of continuous improvement, with an increase of 38.07 per cent in 2020 compared with 2006, and overall the synergistic governance efficiency of cities in terms of pollution reduction and carbon reduction shows a pattern of development in which the east is high and the west is low, but there is a tendency for the gap to narrow from one year to the next. There is a positive spatial aggregation of urban pollution reduction and carbon synergistic governance efficiency, which is further shown by the Lisa aggregation diagram that the spatial aggregation of urban pollution reduction and carbon synergistic governance efficiency in China is characterized by urban agglomerations, with the high and high aggregation zones being concentrated in the central and eastern urban agglomerations, such as the urban agglomerations of the middle reaches of the Yangtze River and Guangdong-Fujian-Zhejiang, and the low and low aggregation zones being concentrated in the western urban agglomerations, such as the Lanzhou-Western urban agglomerations and the Guanzhong Plain urban agglomerations. The results of the SDM model indicate that the efficiency of urban pollution reduction and carbon synergistic governance can significantly promote the process of pollution reduction and carbon synergistic governance in neighboring areas. The six drivers, namely, industrial structure, economic development level, innovation level, urbanization rate, population size and foreign direct investment, all have a significant impact on the efficiency of urban pollution reduction and carbon synergistic governance in a local area. The spatial spillover effects of the remaining variables, except for urbanization rate, on the efficiency of urban pollution reduction and carbon synergistic governance are significantly negative. Based on this, corresponding countermeasures are proposed to improve the synergistic governance of urban pollution reduction and carbon reduction. [ABSTRACT FROM AUTHOR]

Brown carbon (BrC) aerosol could impact atmospheric radiative forcing and play a crucial role in atmospheric photochemistry. In this study, fine particulate matter (PM 2.5) filter samples were collected synchronously in four major cities in northwestern China during the winter season (December 2019–January 2020): Lanzhou (LZ), Xining (XN), Yinchuan (YC), and Ürümqi (UR), which are represented as energy-producing and heavy manufacturing cities in China. The primary aim of the study is to explore the optical properties, sources, and chemical processes of water-soluble BrC (WS-BrC). The average mass absorption efficiency at 365 nm (MAE 365) of WS-BrC at these four cities was 1.24 ± 0.19 m 2 g -1 (XN), 1.19 ± 0.12 m 2 g -1 (LZ), 1.07 ± 0.23 m 2 g -1 (YC), and 0.78 ± 0.16 m 2 g -1 (UR). The properties of WS-BrC were further investigated by an acid–base titration experiment. The results showed that the MAE 365 values in all cities increased with higher pH values (2–11), while the fluorescence intensities of water extracts fluctuated with pH values, being stronger under both highly acidic and basic conditions. The sensitivity to pH variation was most pronounced in the WS-BrC samples from YC and LZ, indicating the important contribution of acid or base functional group compounds in these locations. Additionally, the study revealed significant photo-enhancement (LZ) or photo-bleaching (YC and UR) phenomena of WS-BrC in different cities. These results suggest that the sources and/or chemical processes of WS-BrC varied among the cities. The sources and chemical processes of WS-BrC were further explored by a combination of parallel factor analysis (PARAFAC) on excitation–emission matrix (EEM) spectra of WS-BrC and positive matrix factorization analysis (PMF) on high-resolution mass spectra of water-soluble organic aerosol (WSOA). Six PARAFAC components were identified, including three humic-like substances (HULIS; two less oxygenated (LO) HULIS and one highly oxygenated (HO) HULIS), two protein-like or phenol-like substances (PLS), and one undefined substance. Four PMF factors were identified, including a water-soluble primary OA (WS-POA), a less oxidized oxygenated OA associated with coal combustion-induced WSOA (LO-OOA), and two highly oxidized oxygenated OAs resulting from photochemical oxidation and aqueous-phase oxidation transformations (HO-OOA1 and HO-OOA2). WS-POA was determined to be the most significant source of light absorption, accounting for 30 %–60 % based on multiple linear regression models, and it showed a significant correlation with PLS and LO-HULIS components. The loss of light absorption of WS-POA was found to occur through its conversion to LO-OOA and HO-OOAs through photochemical or aqueous reactions, with HO-OOAs being significantly correlated with the HO-HULIS component. These processes can be clearly illustrated by integrating optical properties and chemical composition using a Van Krevelen diagram and an EEM plot. [ABSTRACT FROM AUTHOR]

Air pollution prevention and control is an important way to eliminate haze, and air quality prediction can provide predictive information for air pollution prevention and people's health. Therefore, it is of great practical usefulness to establish a scientific and effective air quality prediction model. Combined forecasting is a popular statistical method for air pollution forecasting, which generally includes two steps of individual model selection and weight determination. This research introduces LASSO for individual models selection, and ELM to establish a nonlinear combined forecasting model, named CEEMD-LASSO-ELM. LASSO can not only select individual models, but also avoids the possible collinearity between the selected individual models. Daily air quality index (AQI) series of Guangzhou, Kunming, Lanzhou and Hulunbuir are selected to verify the feasibility and effectiveness of the proposed CEEMD-LASSO-ELM model. Combined with CEEMD, seven comparative models are Random-ELM, Rank-ELM, Random-LR, Rank-LR, LASSO-GRNN, LASSO-PSOGSASVR and LASSO-LR. The data analysis shows that the proposed CEEMD-LASSO-ELM model has better prediction accuracy and stronger generalization ability. Taking Lanzhou as an example, the MAPE of CEEMD-LASSO-ELM model is 1.813% lower than that of the seven comparative models on average. [ABSTRACT FROM AUTHOR]

The evaluation of the effectiveness of emergency shelters is a key task to improve disaster response capacity and reduce loss of life and property. Most previous studies, however, neglect the heterogeneity of evacuation capacity across age groups. The objective of this study is to develop an age-integrated method for evaluating the effectiveness of emergency shelters. The age-integrated method considers travel time decay effects, competition effects among emergency shelters, and heterogeneity in evacuation capacity of different age groups. Based on the real road network, we apply the proposed method to evaluate the effectiveness of emergency shelters from the perspective of accessibility and potential crowdedness under 20, 40, and 60-min scenarios in the main urban area of Lanzhou, which has a high proportion of vulnerable populations. The results indicate that (1) accessibility is poor in densely populated areas, whereas sparsely populated suburbs have relatively high accessibility, where large shelters are more easily found; (2) accessibility from the central regions to the suburbs gradually increases, with this difference becoming significant in the 60-min scenario; (3) the Gini coefficient of accessibility for the three scenarios is above 0.6; (4) differences in accessibility and potential crowdedness (a strong negative correlation between them) should be considered to achieve an effective layout of emergency shelters. The findings of this study provide new insights into studying the effectiveness of emergency shelters considering different groups in the context of the severe aging phenomenon, as well as a scientific basis a scientific basis for future shelter development. [ABSTRACT FROM AUTHOR]

With the rapid development of the economy, urbanization and industrialization gradually become an important driving force of groundwater chemical evolution. In this study, Lanzhou City, which is one of the biggest industrial cities in northwest China, was selected to investigate the impacts of city development on groundwater quality. Several hydrochemical methods together with principal component analysis (PCA) were used for the hydrochemistry evolution characteristics and sensitive factors of groundwater chemistry in different urban functional areas of Lanzhou City. The results show that 96% of the groundwater in the study area cannot meet the groundwater quality standards of China. The main factors affecting the quality are SO42−, TDS, total hardness, Mg2+ and Na+. Urbanization and industrialization lead to further deterioration of the already naturally high TDS groundwater. NO3−, Cl− and NH4+ are the characteristic factors of human input sources for commercial residential areas; total Fe and NO3− are the characteristic factors of new urban areas in the urban-rural junction; and SO42−, NO3−, Cl−, Total Fe, Mn2+, F−, I−, Pb2+, Cr6+ and As3+ are the characteristic factors of industrial areas. Domestic sewage infiltration and manure infiltration are the main driving factors of groundwater quality deterioration in commercial residential areas. Nitrate fertilizer infiltration and sewage irrigation are the main factors leading to the increase in nitrate nitrogen in groundwater in the new urban area. Industrial wastewater leakage and organic pollution that promote the dissolution of minerals in the aquifer (the dissolution of fluorine-containing minerals and reductive dissolution of iron manganese oxides) are the main driving factors for the deterioration of groundwater quality in the petrochemical industrial area. [ABSTRACT FROM AUTHOR]

The major reason that the fully automated generalization of residential areas has not been achieved to date is that it is difficult to acquire the knowledge that is required for automated generalization and for the calculation of spatial similarity degrees between map objects at different scales. Furthermore, little attention has been given to generalization methods with a scale reduction that is larger than two-fold. To fill this gap, this article develops a hybrid approach that combines two existing methods to generalize residential areas that range from 1:10,000 to 1:50,000. The two existing methods are Boffet's method for free space acquisition and kernel density analysis for city hotspot detection. Using both methods, the proposed approach follows a knowledge-based framework by implementing map analysis and spatial similarity measurements in a multiscale map space. First, the knowledge required for residential area generalization is obtained by analyzing multiscale residential areas and their corresponding contributions. Second, residential area generalization is divided into two subprocesses: free space acquisition and urban area outer boundary determination. Then, important parameters for the two subprocesses are obtained through map analysis and similarity measurements, reflecting the knowledge that is hidden in the cartographer's mind. Using this acquired knowledge, complete generalization steps are formed. The proposed approach is tested using multiscale datasets from Lanzhou City. The experimental results demonstrate that our method is better than the traditional methods in terms of location precision and actuality. The approach is robust, comparatively insensitive to the noise of the small buildings beyond urban areas, and easy to implement in GIS software. [ABSTRACT FROM AUTHOR]