The carbon cycle is a main driver of global change [1
]. The expanding mass-energy exchange on the land surface has accelerated the asymmetry of the carbon cycle. More carbon emissions and less carbon absorption has resulted in increasingly negative impacts on the global climate and environment [2
]. In addition to natural factors, global warming is closely related to CO2
(carbon dioxide) emissions produced by human socio-economic activities [5
]. According to the IPCC (Intergovernmental Panel on Climate Change) 5th Assessment Report, approximately 816 ± 124 Gt CO2
of anthropogenic CO2
emissions have not been absorbed and remain in the atmosphere, probably resulting in the observed warming since the mid-20th century. Improving the carbon sequestration of terrestrial ecosystems and reducing greenhouse gas emissions are internationally recognized as two of the crucial ways to mitigate climate change [7
]. As centres of economic activities, population migration, and energy consumption, urban areas play a significant role in addressing CO2
emissions and global climate change [9
], particularly in rapidly developing countries [10
]. It has been reported that 2% of the global land in urban areas includes more than 50% of the world’s population and approximately 75% of the global carbon emissions [12
]. Thus, examination of the carbon budget in rapidly expanding urban regions is necessary.
Under the government’s reform and opening-up policies since 1978, China is undergoing rapid urbanization, industrial processes and land-use/-cover change. Built-up land, where highly populated, has dramatically expanded and occupied large areas of ecological land, especially in coastal regions [14
]. The process has threatened China’s sustainable development and the long-term stability of the global climate, which has raised global concerns [17
]. As the expansion rate is still rapidly accelerating and has increasingly high carbon emissions intensity, China is encountering intense pressure to reduce its CO2
]. Yangtze River Delta (YRD), Pearl River Delta (PRD) and Beijing–Tianjin–Hebei (BTH) are three of the coastal urban agglomerations in China. As population growth and economic development are concentrated, these regions contribute most to CO2
release with significant land-use and land-cover change [19
]. Zha et al. found that CO2
release is higher in urban land than in rural land [22
concentration would increase when forestry lands convert to agriculture [23
]. Meanwhile, the three urban agglomerations are distinguished by different natural conditions and socio-economic development. For natural conditions, YRD locates by China’s greatest river with mild climate; climate is dry in BTH with worse vegetation growth; while vegetation carbon fixation is the best in PRD with synchronous rain and heat. For socio-economic development, the urbanization process is rapid, and urban development is quite even in YRD; BTH shows lower urban industrial land-use efficiency; and city clusters are most obvious in PRD [24
]. It is significant and feasible to discuss how the natural and man-made factors affect the carbon sources and sinks for possible low carbon development strategies in the three urban agglomerations. There is an impressive and growing literature regarding carbon sources and sinks in these three urban agglomerations [19
]. However, currently, there seem to be no comparable studies that present the same methodology and same data source.
Different data sources have been collected to examine carbon sources and sinks, including field measurements, government statistics and optical remote sensing data. Morton and Andreas attempted to improve the field measurement of the net ecosystem exchange CO2
flux to identify peatlands acting as either a net CO2
uptake or release [30
]. Using field measurements, many studies have focused on carbon flux calculation to explore carbon sources and sinks in different single ecosystems of a specific type, but these studies are limited in data size and field scale and fail to be directly compared [31
]. Rahman and Kashem provided the possibility to examine the relationships between carbon emissions, energy consumption and industrial growth in Bangladesh using economic data from the Word Development Indicator and the Central Bank of Bangladesh [33
]. Socio-economic statistics published by governments has enabled the use of a top-down method to estimate carbon emissions, but the lack of spatial distribution and the inconsistency of the statistics quality lead to lower data mining accessibility and comparability [34
Distinctly advantageous for detecting spatial-temporal variation and capturing data at a large scale, data from remote sensing aids research on carbon source and sink more objectively and effectively. It is remote-sensing capabilities that a large number of researchers have previously focused on in studying carbon sources and sinks. Chuai et al. examined the net ecosystem production (NEP) trend, an indicator of whether an ecosystem can fix or release carbon from or into the atmosphere using Moderate Resolution Imaging Spectroradiometer data, meteorological data, and soil organic carbon data [35
]. Abdalla and Fadul assessed the relationship between green cover and carbon emissions from cars using remote-sensing data from Landsat and Quick Bird satellites [36
]. Meng et al. used nighttime light imagery and statistical energy data to estimate CO2
]. All of these studies either targeted the entirety of China or separately investigated only one of the regions for NEP or carbon emissions. It is still missing that a comprehensive analysis of carbon budgets examination for both socially and physically derived carbon in spatial dimension.
Our overall objective was the presentation of an analytical framework to study the spatial and temporal pattern of regional carbon budgets in the three urban agglomerations. By unifying the spatial-temporal resolution of carbon source and sink data, attempts are made to compare carbon budgets in different urban agglomerations to enhance the understanding of the natural-human dual structure of carbon effects. Then, a scientific basis for policy-making is provided for viable CO2 emission mitigation policies. The next section addresses the study areas and data sources. The third section introduces the study methods, including urban information extraction, NEP calculation, carbon emission calculation, carbon budgets calculation and spatial statistics. Then we come to the results on the urban expansion characteristics, carbon budgets statistics and spatial patterns of the three urban agglomerations. Finally, we discuss and draw conclusions.
2. Study Areas and Data Sources
YRD, PRD and BTH are three of the coastal urban agglomerations in China (Figure 1
), which contribute most to CO2
emissions with significant land-use and land-cover change. Occupying a very important strategic position in China’s modernization and opening up, the YRD is composed of 26 cities, including the Shanghai city and another 25 cities of the Jiangsu, Zhejiang, and Anhui provinces. The PRD is formed mainly by 14 cities of the Guangdong Province in Southern China, characterized by economic vitality and technological innovation. BTH, in Northern China, is the political and cultural centre of the nation, including the cities of Beijing and Tianjin and the whole of Hebei Province.
The annual Moderate Resolution Imaging Spectroradiometer(MODIS) net primary productivity (NPP) data from 2000 to 2013 used in this study were downloaded from the Numerical Terradynamic Simulation Group (NTSG) at the University of Montana (http://www.ntsg.umt.edu/
). The dataset is in a TIF format and has a resolution of 30-arcsec (approximately 1-km). A detailed description of the NPP model calculation process can be obtained from Zhang et al. [38
]. The accuracy of the product has been validated as being consistent with field-observed NPP data [39
]. We extracted the global map with the overlay of the study areas. Meteorological data (precipitation and temperature) observed at 745 national basic meteorological stations in China were provided by the China Meteorological Data website (http://data.cma.cn/)
. The 2000–2013 annual nighttime light images originated from the Operational Linescan System (OLS) aboard the American Defense Meteorological Satellite (DMSP). These images were downloaded from the National Geophysical Data Center (NGDC) affiliated with the American National Oceanic and Atmospheric Administration (NOAA) (https://www.ngdc.noaa.gov/
). The product contains cloud-free average radiance values that have undergone an outlier removal process to remove fires and other ephemeral lights; grey values range from 1–63, and the resolution is 30 arcsec (approximately 1 km). As nighttime light data slightly vary from different sensors, we adopted the pre-processing approach from Cao to conduct data fusion, image segmentation, irradiance calibration and coordinate translation [40
]. The annual energy consumption data of 30 provinces in China from 2000 to 2013 were collected from the China Energy Statistical Yearbook. Maps in the article were all made by using ArcGIS [9.3], (http://www.esri.com/software/arcgis
Studies on the NEP and energy consumption as important indicators to understand the natural-human dual structure of carbon effects are not new [56
]. The NEP and energy consumption calculations in this study have been effectively verified by previous studies [35
]. Compared with previous studies, however, carbon budget estimations in this study have advantages. By unifying the spatial resolution (approximately 1 km), we provided the possibility to generate a carbon budget comparison in a locally regional scale, which is our main contribution different from other research.
BTH has the lowest NEP level and a high Moran’s I level because of its relatively dry environment that prevents vegetation growth [35
]. In view of its vulnerable ecology, a favourable policy on ecological protection should be adopted here, particularly in the location where the NEP is low. Carbon emission here is the highest of the three urban agglomerations and highly concentrated in the core zone. Industry should be optimized and upgraded to reduce carbon emission. For example, the iron and steel industry is a main carbon source, and its energy efficiency should be improved [60
]. In the spatial allocation of urban planning, there is no doubt that Beijing and Tianjin are the core cities, which should be given greater roles in stimulating the development of surrounding areas. By the urban expansion pattern analysis, development could well be southward and seaward. In the north and the west where the carbon sink occurs, ecological conservation should be a priority to expand the regional eco-capacity.
The YRD has a high NEP and Moran’s I levels, indicating good vegetation growth status and moderate climatic conditions in the whole region [35
]. The YRD has a high urbanization rate and a low level of carbon emission concentration. The YRD plays a leading role in Chinese economic growth, and considerable energy is needed for economic growth and social development [62
]. The main industries of the YRD include electronic equipment manufacturing, transportation equipment manufacturing, electricity supply, ferrous metal smelting and processing, chemical materials and products manufacturing, and light industry such as the textile industry [63
]. With flourishing tertiary industries and high-tech secondary industries, the ecological and environmental condition is better than that in BTH. However, the urban areas are expanding too rapidly, resulting in the destruction of rural arable land and natural resources [64
]; thus, limiting construction land and using land more intensively should be a focus in this region. Shanghai is the core city, whose radiative effects are well exerted throughout the whole region. Nanjing and Hangzhou, sub-centres of the urban agglomeration, can more comprehensively develop to be a powerful force for regional development [65
]. For the part in Anhui with a low NEP and unbalanced carbon emission, balanced development, industrial upgrading and ecological protection is required, on the prospect of integrating into the Yangtze River Area [66
]. In northern coastal areas, such as Yancheng and Nantong, with high NEPs but also high carbon sources, industry improvement should be particularly considered.
The PRD has a high NEP level and low Moran’s I level because of the unbalanced vegetation growth status [35
]. Urbanization occurred greatly according to policy guidance. For example, the coordinate development program released in 2004 deferred the local urban expansion [67
], while the Asian Games in Guangzhou in 2011 greatly promoted urban land use in the surrounding regions [68
]. The highest urban patch size suggests construction land clusters, such as new districts and development zones, which occupy too much land and exhibit low-efficiency utilization [69
]. At the forefront of China’s reform and opening up, the PRD has become the largest global manufacturing base. The PRD has undergone manufacturing relocation because of severe land and labour shortages, as well as rising rent costs in urban core zones, such as Shenzhen and Guangzhou downtown areas [70
]. Balanced economic development should be a focus here because the development gap between the south-central areas and other locations is great, with significant characteristics of a regional layer structure [71
]. Guangzhou, Shenzhen and Zhuhai are the absolute poles in this region, and their radiative effects should be given full priority. Other locations, such as Huizhou, Heyuan and Shanwei, can properly develop tourism with green hills and waters to bridge the economic gap [73
]. Although the ecological and environmental conditions are fine, a protective policy should be assured, particularly in the west.
As the three urban agglomerations underwent rapid urban expansion between 2000 and 2013, it became urgent to optimize the urban size and structure and bring about positive economic and social impacts. Consistent with the urban planning policy, a balance should be sought between construction land for economic development and other land for ecological protection in the three urban agglomerations. For BTH, a regional synergetic strategy should be implemented, particularly in the promotion of joint industries and cooperative ecological protection. The YRD, which has world-class development prospects, should focus on limiting construction land and optimizing resource allocation. The PRD, the whole region in the same province, should realize integration development with a unified advantage.
BTH, YRD and PRD are three of the coastal urban agglomerations in China. As population growth and economic development have been concentrated in these regions during the past 20 years, these regions are typical developed regions in China. We presented an analytical framework to study the spatial and temporal pattern of regional carbon budgets in the three regions and made a comparison. By unifying the spatial-temporal resolution of carbon source and sink data, we made it possible to compare carbon budgets in different urban agglomerations. The adoption of the carbon effect study in these three regions is representative of other developing countries, which is supposed to be generalized to the other carbon budgets’ calculation in a locally regional scale. But some problems remain to be solved. For example, parameters used in NEP calculations should be proved to be reliable or adjustable and can be extended to other regions. So, additional research ought to be conducted to test the practical application of the analytical framework.
In conclusion, as discussed above, urban expansion and carbon source and sink patterns are different among these three regions. The built-up area in BTH gradually expanded and combined with the surrounding clusters. Carbon liabilities are the most evident in BTH, with its ecological vulnerability and carbon-intensive industries. The built-up area in the YRD rapidly grew and generated many new urban core zones. Despite good ecological status, carbon emissions and liabilities in the YRD show high spatial aggregation. There is great polarization in the carbon budget pattern of the PRD between the urban core zone and its periphery. Nevertheless, industrial growth, regional equilibrium and ecological protection are common goals. Therefore, a land-use policy in the whole of the three urban agglomerations should be sought to balance the construction land for economic development and other land for ecological protection.