An integrated material metabolism model for stocks of urban road system in Beijing, China

Guo, Zhen; Hu, Dan; Zhang, Fuhua; Huang, Guolong; Xiao, Qiang

doi:10.1016/j.scitotenv.2013.10.041

Cited by 68 publications

(40 citation statements)

References 37 publications

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“…Many studies have focused on different methodologies to study the impact of human consumption on its environment. Some notable methods are materials inputs-outputs analysis, which is also known as the material flow analysis (MFA) method [9,10]; exergy analysis [10,11]; emergy analysis [12]; life cycle assessment (LCA [13][14][15][16][17]; ecological footprint (EF) [18][19][20][21]; urban metabolism (UM) [1,[22][23][24][25]; and Geographic Information System (GIS) and remote sensing (RS) techniques [26][27][28]. Among these, the ecological footprint quantification method, along with GIS and RS-based visualization techniques, has been getting more attention from different scientific communities in recent years [26][27][28][29][30].…”

Section: Introductionmentioning

confidence: 99%

Household Level Consumption and Ecological Stress in an Urban Area

Khan

Uddin

2018

Urban Science

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Rapid urbanization and human consumption are continuously threatening the balances of natural environmental systems. This study investigated the increasing stress on the natural environment from household consumption at the neighborhood level. We collected and analyzed household-level data of Ward 24 of the Khulna City Corporation (KCC) area to quantify and represent household consumption and entrenching stresses on the natural environment. We followed the component and direct method to determine the ecological footprint (demand). We also derived the biocapacity (supply) from the available bioproductive lands of the study area. Thus, the gap between demand and supply was identified and represented as a stress area through a Geographic Information System (GIS) mapping technique. We found that the per capita ecological footprint accounts for Ward 24 were about 0.7161 gha/capita for the year 2015. Moreover, the biocapacity for the same year was determined as 0.0144 gha/capita for Ward 24. The ecological demand for the household-based consumption of Ward 24 exceeded its ecological capacity by 49.73 times. We found that Ward 24 would require an area that was 162 times larger in order to support the present level of resource demand and waste sequestration. These study findings can play an essential role in policy formulation, ensuring the practices of environmental justice at the local scale.

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Section: Introductionmentioning

confidence: 99%

Household Level Consumption and Ecological Stress in an Urban Area

Khan

Uddin

2018

Urban Science

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“…A large difference (up to 40 times higher) can be seen in comparison to the Chinese cities (Huang et al., ). However, the difference might be actually smaller as indicated by another study, which for Beijing estimated the road stock per capita to 6 t (Guo et al., ). The study of the EU 25 countries showed a stock in roads of circa 80 t per capita (Wiedenhofer et al., ), which is twice as high as the figure estimated in the current study.…”

Section: Discussionmentioning

confidence: 93%

“…In previous research, MS has been estimated for single or multiple components of the built environment. For instance, Guo, Hu, Zhang, Huang, and Xiao (2014), in the case of Beijing, and Nguyen, Fishman, Miatto, and Tanikawa (2018), in the case of Vietnam, have investigated road networks only, and Kleemann, Lederer, Rechberger, and Fellner (2016), in the case of Vienna, and Ortlepp, Gruhler, and Schiller (2015), in the case of Germany, have investigated buildings only. The studies that have examined multiple components of the built environment (Han & Xiang, 2013;Huang, Han, & Chen, 2016;Tanikawa & Hashimoto, 2009;Tanikawa et al, 2015;Wiedenhofer et al, 2015) have indicated that the largest stock is accumulated in buildings that takes between 43 and 90% of the total MS depending on which and how many of the built environment components are analyzed.…”

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confidence: 99%

“…A few studies have focused on a country's prefectures (Fishman, Schandl, & Tanikawa, 2015;Han & Xiang, 2013) and others on multiple countries (Fishman et al, 2016;Fishman, Schandl, Tanikawa, Walker, & Krausmann, 2014;Wiedenhofer et al, 2015). Urban areas have received the most attention (Guo et al, 2014;Huang et al, 2016;Kleemann et al, 2016;Mesta et al, 2018;Reyna & Chester, 2015), which can be explained by the rapid urbanization trends at a global level (United Nations, 2014).…”

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confidence: 99%

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Spatial analysis of urban material stock with clustering algorithms: A Northern European case study

Gontia

Thuvander

Ebrahimi

et al. 2019

J of Industrial Ecology

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A large share of construction material stock (MS) accumulates in urban built environments. To attain a more sustainable use of resources, knowledge about the spatial distribution of urban MS is needed. In this article, an innovative spatial analysis approach to urban MS is proposed. Within this scope, MS indicators are defined at neighborhood level and clustered with k‐mean algorithms. The MS is estimated bottom‐up with (a) material‐intensity coefficients and (b) spatial data for three built environment components: buildings, road transportation, and pipes, using seven material categories. The city of Gothenburg, Sweden is used as a case study. Moreover, being the first case study in Northern Europe, the results are explored through various aspects (material composition, age distribution, material density), and, finally, contrasted on a per capita basis with other studies worldwide. The stock is estimated at circa 84 million metric tons. Buildings account for 73% of the stock, road transport 26%, and pipes 1%. Mineral‐binding materials take the largest share of the stock, followed by aggregates, brick, asphalt, steel, and wood. Per capita, the MS is estimated at 153 metric tons; 62 metric tons are residential, which, in an international context, is a medium estimate. Denser neighborhoods with a mix of nonresidential and residential buildings have a lower proportion of MS in roads and pipes than low‐density single‐family residential neighborhoods. Furthermore, single‐family residential neighborhoods cluster in mixed‐age classes and show the largest content of wood. Multifamily buildings cluster in three distinct age classes, and each represent a specific material composition of brick, mineral binding, and steel. Future work should focus on megacities and contrasting multiple urban areas and, methodologically, should concentrate on algorithms, MS indicators, and spatial divisions of urban stock.

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“…A large body of literature has been published on urbanization and its impact on carbon emissions from industrial energy use, transportation, household consumption, etc (Liu et al, 2011;Sun et al, 2014;Wang and Yang, 2014). Many of these studies have also addressed carbon accounting for anthropogenic components of urban areas such as buildings, landfills and urban road systems using Input-Output analyses, material flows and life cycle assessment (Dhakal, 2010;Guo et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Effects of land use and cover change on terrestrial carbon stocks in urbanized areas: a study from Changzhou, China

Wang

et al. 2015

Journal of Cleaner Production

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a b s t r a c tLand use and cover change is the key factor affecting terrestrial carbon stocks and their dynamics not only in regional ecosystems but also in urbanized areas. Using the typical fast-growing city of Changzhou, China as a case study, this paper explored the relationships between terrestrial carbon stocks and land cover within an urbanized area. The main objectives were to assess variation in biomass and soil carbon stocks across terrestrial land covers with different intensities of urban development, and quantify spatial distribution and dynamic variation of terrestrial carbon stocks in response to urban land use and cover change. On the basis of accurate spatial datasets derived from a series of Landsat TM images during the years 1986 to 2011 and reliable estimates of urban biomass and soil carbon stocks using the InVEST model, our results showed that carbon stocks per unit area in terrestrial land covers decreased with increasing intensity of urban development. Urban land use and cover change and sealing of the soil surface created hotspots for losses in carbon stocks. Total carbon stocks in Changzhou decreased by about 30% during the past 25 years, representing a 1.5% average annual decrease. We suggested potential policy measures to mitigate negative effects of land use and cover change on carbon stocks in urbanized areas.

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An integrated material metabolism model for stocks of urban road system in Beijing, China

Cited by 68 publications

References 37 publications

Household Level Consumption and Ecological Stress in an Urban Area

Household Level Consumption and Ecological Stress in an Urban Area

Spatial analysis of urban material stock with clustering algorithms: A Northern European case study

Effects of land use and cover change on terrestrial carbon stocks in urbanized areas: a study from Changzhou, China

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