Search

The relationship between dense urban development, often represented by high-rise buildings, and its location vis-à-vis metro stations reflects the connection between transportation infrastructure and land use intensity. Existing literature on high-rise buildings has focused either on developed countries or on cities where urban and public transit developments have occurred in an uncoordinated manner. This paper examines the following questions: What is the spatial proximity and spatial correlation between high-rise buildings and metro stations in different stages of development in various parts of the city? What were some of the factors that resulted in the observed patterns? The results suggest that buildings constructed after 2000 and buildings within the urban core/Shanghai Proper districts had a greater spatial proximity to the metro stations. However, the spatial correlation, measured by the number of high-rise buildings within a 500-m buffer from the nearest metro stations and the time-distance to these stations, is stronger in the outer districts than in the urban core. These differences can be accounted for by Shanghai's stages of urban development, the existence of metro infrastructure when high-rise development was undertaken, and the city's land use policies. This case study sheds light on the relationship between high-density developments and metro systems in other large cities in China and other developing countries where rapid urban development coincides with the establishment of a comprehensive public transit system. • Investigate the relationship between high-density development and its location vis-à-vis metro stations. • Understand the different spatial distribution patterns of high-rise buildings between suburban districts and urban core. • Application of the spatial proximity and spatial correlation measures between high-rise buildings and metro transit. [ABSTRACT FROM AUTHOR]

Highlights • People choose LCT provided high population density and sufficient access to public transit. • Land-use diversity alone was not found to be significant in affecting LCT mode choice. • The proliferation of gated communities reduces connectivity and has a negative effect on LCT. Abstract Developing less auto-dependent urban forms and promoting low-carbon transportation (LCT) are challenges facing our cities. Previous literature has supported the association between neighborhood form and low-carbon travel behaviour. Several studies have attempted to measure neighborhood forms focusing on physical built-environment factors such as population and employment density and socio-economic conditions such as income and race. We find that these characteristics may not be sufficiently fine-grained to differentiate between neighborhoods in Chinese cities. This research assesses characteristics of neighborhood spatial configuration that may influence the choice of LCT modes in the context of dense Chinese cities. Urban-form data from 40 neighborhoods in Chengdu, China, along with a travel behaviour survey of households conducted in 2016, were used to generate several measures of land use diversity and accessibility for each neighborhood. We use principle component analysis (PCA) to group these variables into dimensions that could be used to classify the neighborhoods. We then estimate regression models of low-carbon mode choices such as walking, bicycling, and transit to better understand the significance of these built-environment differences at the neighbourhood level. We find that, first, members of households do choose to walk or bike or take transit to work provided there is relatively high population density and sufficient access to public transit and jobs. Second, land-use diversity alone was not found to be significant in affecting LCT mode choice. Third, the proliferation of gated communities was found to reduce overall spatial connectivity within neighborhoods and had a negative effect on choice of LCT. [ABSTRACT FROM AUTHOR]

Previous studies have frequently taken urban density as a surrogate for economic efficiency and applied composite scores such as urban intensity to assess the existing physical forms of towns. However, measures of intensity might nuance crude calculations of density while considering how such measures relate to future plans and the process of transformations. This paper used open source geospatial data and regulatory detailed planning to measure urban intensity of the existing and the planned. Spatial analytical techniques were applied to compute accessibility to destinations, building density, compactness of development, and diversity of land use function of sixteen specialty towns in China. The results showed that the regulatory detailed planning of these cases might not improve town planning measured by intensity in terms of spatial arrangement in the time horizon of 15–20 years. We found that well-integrated monocentric forms with the finer street network could potentially provide a more suitable spatial distribution for mid-sized towns measured by urban intensity, no matter whether the urban form is linear or center-spreading. Moreover, the comparison between the existing and the planned implies that the poly-centric urban form for mid-sized towns in China could end up with a lower score of urban intensity. We outline a framework of urban intensity measures that include analytical consideration of what is there now, planned to what is forthcoming, and conceptual in terms of time and space. • Differentiating urban intensity from density • Using urban block as the spatial unit of study is more accurate than a synthetic spatial grid. • Comparing existing and planned conditions of medium-sized towns • Evaluation and intervention of town planning policies [ABSTRACT FROM AUTHOR]

As the world's largest CH 4 emitter, China's CH 4 emissions contribute to climate change more than the amount emitted by many developed countries combined. The rapid growth of China's coal demand has important implications for CH 4 emissions from coal mining or coal mine methane (CMM) emissions. This paper aims to present an overview of bottom-up estimation of China's CMM emissions, including the trend in the last four decades and the limitations of current understanding on CH 4 emissions. Although characterized by significant differences in inventory compilation, statistically, the total CMM emissions rose from 4.64 to 16.41 Tg with a peak of 21.48 Tg from 1980 to 2016. Large discrepancies of inventory results existed in previous studies, which were affected by the coverage of emission sources, emission factors and activity-level data. The disagreements can be largely attributable to the emission factors of underground mining, which contain substantial variances in both spatial and temporal dimensions. To develop more reliable CMM inventories and make targeted mitigation measures, more attention should be paid to the transparency of the estimated results, coal statistics, on-site CMM emission factors, and the emissions from abandoned coal mines. As the leading CH 4 emission source in China, the estimations of CMM emissions urgently need to overcome existing and emerging challenges for compiling a consistent and accurate inventory. Unlabelled Image • We perform an overview of current bottom-up estimation of China's CMM emissions. • CMM emissions over 1980–2016 rose from 4.64 to 16.41 Tg with a peak of 21.48 Tg. • Inventory results were improved along with large discrepancies and disagreements. • We discuss the types of emission source, emission factors and activity-level data. • The limits of current understanding and future research prospects are provided. [ABSTRACT FROM AUTHOR]