Abstract
The rapid development of industrialization and urbanization has resulted in a large amount of carbon dioxide (CO2) emissions, which are closely related to the long-term stability of urban surface temperature and the sustainable development of cities in the future. However, there is still a lack of research on the temporal and spatial changes of CO2 emissions in long-term series and their relationship with land surface temperature. In this study, Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) data, Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) composite data, energy consumption statistics data and nighttime land surface temperature are selected to realize the spatial informatization of long-term series CO2 emissions in the Yangtze River Delta region, which reveals the spatial and temporal dynamic characteristics of CO2 emissions, spatial autocorrelation distribution patterns and their impacts on nighttime land surface temperature. According to the results, CO2 emissions in the Yangtze River Delta region show an obvious upward trend from 2000 to 2017, with an average annual growth rate of 6.26%, but the growth rate is gradually slowing down. In terms of spatial distribution, the CO2 emissions in that region have significant regional differences. Shanghai, Suzhou and their neighboring cities are the main distribution areas with high CO2 emissions and obvious patch distribution patterns. From the perspective of spatial trend, the areas whose CO2 emissions are of significant growth, relatively significant growth and extremely significant growth account for 8.78%, 4.84% and 0.58%, respectively, with a spatial pattern of increase in the east and no big change in the west. From the perspective of spatial autocorrelation, the global spatial autocorrelation index of CO2 emissions in the Yangtze River Delta region in the past 18 years has been greater than 0.66 (p < 0.01), which displays significant positive spatial autocorrelation characteristics, and the spatial agglomeration degree of CO2 emissions continues to increase from 2000 to 2010. From 2000 to 2017, the nighttime land surface temperature in that region showed a warming trend, and the areas where CO2 emissions are positively correlated with nighttime land surface temperature account for 88.98%. The increased CO2 emissions lead to, to a large extent, the rise of nighttime land surface temperature. The research results have important theoretical and practical significance for the Yangtze River Delta region to formulate a regional emission reduction strategy.
Highlights
As the largest developing country in the 21st century, China has experienced the progressive transformation from planned economy to market economy and achieved a surprising economic growth over the past 30 years [1]
In terms of data acquisition, energy consumption statistics come from the NTaatbiolen5a.lCBourrreelaautioonf cSoteaffitisciteicnsts, DofMCOSP2 /eOmLisSsidoantsaancodmthee fmroamximthuemN, maitnioimnaulmOacnedanaviceraangde nAigthmttoimspeheric Admliannidstsruartfiaocne otefmthpeerUatnuirtee.d States, and National Polar-orbiting Partnership (NPP)/Visible Infrared Imaging Radiometer Suite (VIIRS) data come from the National Geophysical Data pCreoncteesrsYoienfagrt,htehUeNSndCLiSaEtetTaadmnpadSxrtoatceessNS.sCAiLnSElglTatminhsidencaarbroiNevSdLCeSEodTuaamntteadaanccacnorYbdeeianorgbttaoiNSnthCLeedSETeafmxrneiadsextionfgcNShcCoLarSrErgTeaemcn.tidIinonnthmNeSeLaCtSshEpToaemdncedtaonof fndigahtat light d2a0ta0,0whic0h.3i7s6s*i*mple a0n.2d84fe*a*sible
This paper calculates the CO2 emissions in the Yangtze River Delta region based on energy consumption statistics, and combines night lighting data to realize the spatial informatization of CO2 emissions in a long time series, which can solve the defect of insufficient energy consumption statistics at the municipal level
Summary
As the largest developing country in the 21st century, China has experienced the progressive transformation from planned economy to market economy and achieved a surprising economic growth over the past 30 years [1]. Based on the DMSPOLS and NPP/VIIRS data, this research explores the spatio-temporal characteristics of serialized CO2 emissions on the municipal level with a longer duration, in order to determine the objective of emission reduction for the local governments and provide scientific basis for the preparation of a regional strategy for emission reduction. To cope with the huge pressure of emission reduction and enhance the sustainable development of cities, the scientific and precise analysis on the temporal and spatial variation of CO2 emissions in the Yangtze River Delta and its relationship with the nighttime land surface temperature may determine the objective of emission reduction for the local governments and provide the theoretical basis and data support for the improvement of the urban ecological environment. Pearson’s correlation coefficient was used to analyze the relationship between CO2 emissions and night surface temperature
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