Carbon storage and sequestration by urban forests in Shenyang, China

Liu, Changfu; Li, Xiaoma

doi:10.1016/j.ufug.2011.03.002

Cited by 232 publications

(163 citation statements)

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“…Due to the presence of non-native trees and lack of European-specific equations for certain species, the remaining equations were from China (4% of subsampled trees (Liu & Li 2012)) and North America (35.7% of subsampled trees; (Jenkins et al 2003)). Overall, our growth rates are different from those reported by Jo and McPherson (1995), Iakovoglou et al (2002), and Lawrence et al (2012) for trees in the United States.…”

Section: Quercus Pubescensmentioning

confidence: 99%

“…Thus, in this study, annual gross carbon sequestration (kg/year) was estimated as the difference of C stored between year x (2011) and year x + 1 (2012) (Liu & Li 2012) and was determined using an individual tree's annual growth rate and predicted height increment as explained in the previous section. A report on municipal waste (ISPRA 2012) shows that the green waste biomass from urban vegetation mowing and urban tree pruning operations in the Trentino-Alto Adige/South Tyrol region was 15,705 t in 2009.…”

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Assessing urban tree carbon storage and sequestration in Bolzano, Italy

Russo

Escobedo

Timilsina

et al. 2014

International Journal of Biodiversity Science, Ecosystem Servic

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Recent climate change, environmental design, and ecological conservation policies require new and existing urban developments to mitigate and offset carbon dioxide emissions and for cities to become carbon neutral. Some North American models and tools are available and can be used to quantify the carbon offset function of urban trees. But, little information on urban tree carbon storage and sequestration exists from the European Southern Alps. Also, the use of these North American models in Europe has never been assessed. This study developed a protocol to quantify aboveground carbon (C) storage and sequestration using a subsample of urban trees in Bolzano, Italy, and assessed two existing and available C estimation models. Carbon storage and sequestration were estimated using city-specific dendrometrics and allometric biomass equations primarily from Europe and two other United States models; the UFORE (Urban Forest Effects Model) and the CUFR Tree Carbon Calculator (CTCC). The UFORE model carbon storage estimates were the lowest while the CUFR Tree Carbon Calculator (CTCC) C sequestration estimates were the highest. Results from this study can be used to plan, design, and manage urban forests in northern Italy to maximize C offset potential, provide ecosystem services, and for developing carbon neutral policies. Findings can also be used to predict greenhouse gas emissions from tree maintenance operations as well as estimating green waste yield from landscape maintenance activities and its use as biofuel and compost. Managers need to be aware that available models and methods can produce statistically different C storage and sequestration estimates.Keywords: i-Tree Eco; growth rates; allometric equations; ecosystem services; CTCC model Introduction Climate change is one of the most important and pressing environmental, economic, and security issues our world faces today (Barnett 2003;IPCC 2007;Karagiannis & Soldatos 2010). Urban areas are steadily growing throughout the world (Grimm et al. 2008) and by 2030 it is expected that 60% of the world's population will be living in cities (Rydin et al. 2012). Thus, as urban environments become more important as living space for humans, they are an increasing source of carbon emissions.Several studies in North America, China, and Australia (Brack 2002;Zhao et al. 2010;Dobbs et al. 2011;Martin et al. 2012;Roy et al. 2012), and more recently in the United Kingdom and Germany (Davies et al. 2011;Strohbach & Haase 2012;Strohbach et al. 2012), have shown that trees in urban environments remove carbon dioxide from the atmosphere through growth and photosynthesis, and store excess carbon as biomass in roots, stems, and branches. Indirectly, urban trees also reduce building energy used for cooling through their shade and climate amelioration effects, thereby reducing CO 2 emissions from decreased energy production (Akbari et al. 2001).The estimation of tree carbon sequestration depends on species types and their mortality and growth characteristics as well as their overall con...

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Section: Quercus Pubescensmentioning

confidence: 99%

mentioning

confidence: 99%

Assessing urban tree carbon storage and sequestration in Bolzano, Italy

Russo

Escobedo

Timilsina

et al. 2014

International Journal of Biodiversity Science, Ecosystem Servic

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“…Therefore, it is essential to better understand the carbon dynamics of urban ecosystem, rather than relying on the assumption of static carbon stocks. In other words, it is not very important to account for the proportion of total carbon stocks at a regional scale that is stored in urban areas (Liu and Li, 2012); instead, it is necessary to quantify gradient changes in terrestrial carbon stocks in response to urban land use and cover change (Patak et al, 2006;Alberti and Hutyra, 2009;Hutyra et al, 2011b;Ren et al, 2011;Zhang et al, 2012), which is vital for understanding the effectiveness of policy implementations for preservation of carbon stocks in urban areas.…”

Section: Introductionmentioning

confidence: 99%

Variation in ecosystem services across an urbanization gradient: A study of terrestrial carbon stocks from Changzhou, China

Liu³

et al. 2015

Ecological Modelling

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a b s t r a c tEcosystem services in urban areas are regarded as multiple environmental benefits fostered by urban-rural landscapes. A wide range of ecosystem services have been largely affected by land use and cover change in urban areas, leading to significant variation of ecosystem services, such as terrestrial carbon stocks across a gradient of urbanization. Urban areas are critical for terrestrial carbon dynamics owing to both considerable amount of biomass and soil carbon stored in cities and significant losses in carbon stocks from urban land use and cover change. We used Changzhou, a typical fast-growing city in China, as a case study, and estimated biomass and soil carbon stored in land covers using the InVEST model. We also quantified gradient changes in terrestrial carbon stocks in response to urban land use and cover change along two sample transects as a function of distance from the urban center. We found that carbon densities decreased with increasing intensity of urban development. Gradient transect analyses revealed an overall trend of increasing carbon stocks from the urban center to peri-urban areas as a direct result of land use and cover change driven by policy-oriented urban planning, which led to both infilling of empty areas within the urban center and sprawling of urban land toward peri-urban areas. As recent growth trends continue, the expansion of urban land markedly decreased areas previously dominated by green open spaces, making urban land use and cover change and losses in carbon stocks an increasingly important component of regional carbon dynamics. We proposed measures to mitigate these negative effects of urbanization on carbon stocks both for densely built-up areas and for rapidly urbanizing peri-urban areas.

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“…Conversely, the carbon storage level of cities is built upon large artificial and natural sinks like buildings, waste areas, living organisms, soils and vegetation [2,3]. Recent studies in the United States [4][5][6], Europe [2,7,8] and Asia [9,10] reveal that the storage capacity of urban trees represents an important urban carbon sink. For instance, Heath, et al [11] stated that 14% of the total amount of sequestration by forests in the U.S. is provided by urban forests and Davies et al [7] reports that 97.3% of the total carbon stored in above-ground vegetation in the city of Leicester, UK, was within trees.…”

Section: Introductionmentioning

confidence: 99%

“…Very high resolution multispectral images such as QuickBird enable a detailed separation of vegetation and non-vegetation, even in dense urban areas, and provide an important information source for further combined analysis with airborne LiDAR [10,[12][13][14]. Using airborne LiDAR data, tree carbon assessments have been successfully completed for an entire tree stock [15], and for single trees by using neighbored pixel information [16].…”

Section: Introductionmentioning

confidence: 99%

Using Airborne LiDAR and QuickBird Data for Modelling Urban Tree Carbon Storage and Its Distribution—A Case Study of Berlin

et al. 2014

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While CO2 emissions of cities are widely discussed, carbon storage in urban vegetation has been rarely empirically analyzed. Remotely sensed data offer considerable benefits for addressing this lack of information. The aim of this paper is to develop and apply an approach that combines airborne LiDAR and QuickBird to assess the carbon stored in urban trees of Berlin, Germany, and to identify differences between urban structure types. For a transect in the city, dendrometric parameters were first derived to estimate individual tree stem diameter and carbon storage with allometric equations. Field survey data were used for validation. Then, the individual tree carbon storage was aggregated at the level of urban structure types and the distribution of carbon storage was analysed. Finally, the results were extrapolated to the entire urban area. High accuracies of the detected tree locations were reached with 65.30% for all trees and 80.1% for dominant trees. The total carbon storage of the study area was 20,964.40 t (σ = 15,550.11 t). Its carbon density equaled 13.70 t/ha. A general center-to-periphery increase in carbon storage was identified along the transect. Our approach methods can be used by scientists and decision-makers to gain an empirical basis for the comparison of carbon storage capacities

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Carbon storage and sequestration by urban forests in Shenyang, China

Cited by 232 publications

References 35 publications

Assessing urban tree carbon storage and sequestration in Bolzano, Italy

Assessing urban tree carbon storage and sequestration in Bolzano, Italy

Variation in ecosystem services across an urbanization gradient: A study of terrestrial carbon stocks from Changzhou, China

Using Airborne LiDAR and QuickBird Data for Modelling Urban Tree Carbon Storage and Its Distribution—A Case Study of Berlin

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