Effects of land use and transportation on carbon sources and carbon sinks: A case study in Shenzhen, China

Zhang, Wenting; Huang, Bo; Luo, Dong

doi:10.1016/j.landurbplan.2013.09.014

Cited by 72 publications

(33 citation statements)

References 40 publications

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“…There has been some research into factors influencing land use carbon sink effects within highly urbanized areas. The effect of carbon sinks in urban ecosystems has been examined from the perspectives of climate factor 3 and climate change 4 , different land use types 5–12 and land use change 13 , land use management 14 , transportation activities 15 , locational conditions 16 , the level of urbanization 1 , and so on. The urbanization process extensively influences the quantity, types, and spatial distribution patterns of land use, with the carbon sink function of different land uses changing accordingly.…”

Section: Introductionmentioning

confidence: 99%

Influence of different geographical factors on carbon sink functions in the Pearl River Delta

Dong

Yang

2017

Sci Rep

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This study analyzed carbon fixation across different land use types in the Pearl River Delta to identify the influence of different geographical factors on carbon fixation ability. The methodology was based on interpreting land use data from TM imagery, MODIS13Q1 data, and climate data, using the improved CASA and GeogDetector models. The results show that: (1) From 2000 to 2013, the total carbon sink increased slightly, from 15.58 × 106 t to 17.52 × 106 t, being spatially low at the center and increasing outwards; (2) Proxy variables (topography and landform characteristics), influencing urbanization, significantly affect the carbon sink function of the Pearl River Delta region. The proportion of urban and other construction land showed increasing effect on the regional carbon sink each year. However, the spatial structure of land in the study area changed from complex to simple, with enhanced stability; consequently, the influence of landscape characteristics (landscape dominance and landscape perimeter area fractal dimension) on the regional carbon sink gradually decreased; (3) The influence of the same factors differed with different land use types. Slope and altitude were found to have the greatest influence on the carbon sink of cultivated land, while landscape perimeter area fractal dimension more significantly affected the forest carbon sink.

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Section: Introductionmentioning

confidence: 99%

Influence of different geographical factors on carbon sink functions in the Pearl River Delta

Dong

Yang

2017

Sci Rep

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“…Local residents intermingle with newcomers creating a varied society. Zhang et al (2014), CO 2 emitted during industrial fossil-fuel consumption and by the transportation sector has been gradually increasing in Shenzhen. -SQ has different kind of connections with other cities of the PRD, the global economy through Hong Kong, and mainland China (Fig.…”

Section: Sungang-quingshuihe Neighbourhood As the New Innovative Growmentioning

confidence: 99%

Planning Sungang-Quingshuihe neighbourhood for a new innovative growth centre of Shenzhen

Henk

Füge

Csomós

2015

IRASE

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Shenzhen is one of the most dynamically growing cities in the world with a population of more than 10 million. Situated in the Pearl River Delta (PRD) in China it is in the powerhouse of the global economy. Some decades ago Shenzhen was a small fi shing village only, however, after its designation as a Special Economic Zone (SEZ) the city has gone through rapid urbanization and industrial development. Therefore, currently, Shenzhen is one of the leading economic hubs of China, an important gateway of the large Chinese economy, and a sub-provincial administrative centre in the PRD.Sungang-Quingshuihe (SQ) is a neighbourhood of 2.5 square kilometres, in Louhu district in the east of Shenzhen. The landscape system of SQ has been largely destroyed and fragmented by developments. Our main goal is to redesign SQ neighbourhood for an innovative growth centre of Shenzhen. We envisage SQ as a liveable area with new and modern functions for international residents who work in higher education, information communication industry, medical services, R&D facilities of multinational corporations, and research-oriented start-up companies. In order to accomplish this vision it is required to design new transportation system, public buildings, housing, green corridors and parklands.

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“…CSW = W_solid × RDOC × fDOC, where R_carbon represents the average carbon emission per person per day (kg/(person·day)), a parameter estimated by sampling a large number of Chinese people; p represents the population of a particular area; E_industrial represents the annual industrial fossil coal consumption, which can be acquired directly from the Beijing Statistical Yearbook [90]; fcoal represents the carbon emission factor (t·C/t), which proved to be accessible and representative of the Chinese coal-based carbon emission factor [81]; Car_number represents the actual number of vehicles in a particular area; distance represents the driving distance of each vehicle per day (km/day), which is assumed to be 40 (the average commute time across all modes is expected to be pertinent because an increase in this variable is likely to lead to an increase in CO2 emissions (longer trips) in an urbanized area [95]; g represents the estimated amount of fuel combusted for each trip, in which the gasoline is combusted in a medium-freight vehicle (0.265 L/km) [93]; fgasoline represents the conversion factor for gasoline to g C (65.8 g·C/L), which is the parameter from the research on carbon emissions modeling at an urban neighborhood scale [93]; E_domestic represents the domestic electricity use; felectricity represents the conversion factor for electricity to standard coal, which is widely used in China; and W_solid represents the municipal solid waste production, which can also be acquired directly from the Beijing Statistical Yearbook [90]. RDOC is the ratio of biodegradable organic carbon to solid waste (the IPCC-recommended value for an East Asian country is 14% [94]); and fDOC is the actual decomposition ratio of the DOC (50% is the IPCC-recommended value [94]).…”

Section: Urban Carbon Emission Modelmentioning

confidence: 99%

“…To explain the spatial differences in the carbon sequestration and oxygen emission capacity, the spatial distribution of the carbon sequestration and oxygen emissions per unit area are displayed in Figures 4 and 5, respectively. The carbon density is influenced by the prevailing climate, temperature, illumination time, dominant vegetation, regional development, urbanization level, population density, and land use intensity [2,4,18,19,81,88]. Even a particular type of vegetation at one location may have variable biomass due to the environmental heterogeneity.…”

Section: Spatial Pattern Of Carbon Sequestration and Oxygen Emissionsmentioning

confidence: 99%

“…inventories method recommended by the IPCC [9,23,52,67]; statistical methods that use information from yearbooks, statistical data or other experimental site data [53,54,[68][69][70][71][72][73][74][75]; the GAINS-City integrated assessment model [76]; life-cycle assessment models [77]; economic input-output models [9,50,55,78,79], which can provide detailed inventories of main sources (e.g., energy production, agricultural activities, and waste treatment) [80]; carbon sink estimations with LULC data and empirical coefficients [81,82]; and other approaches. However, the eddy covariance method does not provide valuable partitioning information for CO2 emissions and cannot be used to identify specific carbon sources and sinks [65,68,83].…”

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confidence: 99%

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Evaluation of Carbon and Oxygen Balances in Urban Ecosystems Using Land Use/Land Cover and Statistical Data

Yin

Tian

et al. 2014

Sustainability

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Urban areas play an important role in the global carbon cycle, and human-induced carbon emissions from urban areas urgently need to be reduced. Therefore, understanding the relationship between carbon sources and sinks is the first step toward mitigating the effect of urban areas on climate change. Combined with the land use and land cover (LULC) empirical coefficients and statistical methods, urban carbon and oxygen balances in Beijing were evaluated. In this study, the carbon sequestration and oxygen emission capabilities of various LULC types were calculated, and the partitioning of carbon emissions and oxygen consumption in Beijing were estimated. The evaluation results indicated that the ecosystem services from the LULC in an area were not adequate to offset the urban carbon emissions and oxygen consumption. The areas with a high capacity for carbon sequestration and oxygen emissions were primarily distributed in the exurban districts of Beijing, and the carbon and oxygen balances in the exurban districts were superior to those of core urban areas. Industrial fossil fuel consumption dominated all of the human-induced carbon sources. The methods developed in this research were shown to be viable for the quantitative evaluation of urban ecosystem carbon and oxygen balances. OPEN ACCESSSustainability 2015, 7 196

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Effects of land use and transportation on carbon sources and carbon sinks: A case study in Shenzhen, China

Cited by 72 publications

References 40 publications

Influence of different geographical factors on carbon sink functions in the Pearl River Delta

Influence of different geographical factors on carbon sink functions in the Pearl River Delta

Planning Sungang-Quingshuihe neighbourhood for a new innovative growth centre of Shenzhen

Evaluation of Carbon and Oxygen Balances in Urban Ecosystems Using Land Use/Land Cover and Statistical Data

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