Abstract
Exploring the allometric relationship between carbon emission and economic development can provide guidance for policy-makers who hope to accelerate carbon emission reduction and achieve high-quality development. First, based on the established DMSP/OLS and NPP/VIIRS nighttime light datasets, this study simulated the carbon emissions of the Yangtze River Delta from 2000 to 2020. Second, our research analyzed the spatiotemporal evolution characteristics of carbon emissions. Third, adopting allometric growth model, we explored the allometric relationship between economic development and carbon emissions in Yangtze River Delta. The main conclusions are as follows. First, four prediction models, namely, linear fitting, support vector machine, random forest, and CNN-BiLSTM deep learning, were compared to simulate the accuracy of carbon emissions. Consequently, the CNN-BiLSTM deep learning estimation model presented the best accuracy. Second, both the carbon emissions in YRD as a whole showed an increasing trend, with the largest growth rate appearing in Shanghai and the smallest growth rate occurring in Lishui. Moreover, the high-carbon emission areas were mainly distributed in the core city cluster, which are enclosed by Shanghai, Nanjing, and Hangzhou. Finally, the allometric relationship between economic development and carbon emissions was dominated by one-level negative during the sample period, and the relative growth rate of carbon emissions is lower than that of the economic development, which made the YRD at a basic coordinate stage of weak expansion of economy.
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Data availability
The datasets used during the current study are available from the first author on reasonable request.
References
Azomahou T, Laisney F, Van Nguyen P (2006) Economic development and CO2 emissions: a nonparametric panel approach. J Public Econ 90(6–7):1347–1363
Cai B, Guo H, Cao L, Guan D, Bai H (2018) Local strategies for China’s carbon mitigation: an investigation of Chinese city-level CO2 emissions. J Clean Prod 178:890–902
Cao ZY, Wu ZF, Kuang YQ (2015) Saturation correction method of DMSP/OLS nighttime lights image based on compound exponential model. J Geo-Inform Sci 17(9):1092–1102
Chang SZ, Wang ZM, Mao D (2020) Mapping the essential urban land use in Changchun by applying random forest and multi-source geospatial data. Remote Sens 12(15):2488
Chen HX, Zhang XL, Wu RW (2020) Revisiting the environmental Kuznets curve for city-level CO2 emissions: based on corrected NPP- VIIRS nighttime light data in China. J Clean Prod 268:121575
Chen J, Zhang W, Song L, Wang Y (2022) The coupling effect between economic development and the urban ecological environment in Shanghai port. Sci Total Environ 841:156734
Cheng YQ, Wang ZY, Zhang SZ (2013) Spatial econometric analysis of carbon emission intensity and its driving factors from energy consumption in China. Acta Geographica Sinica 68(10):1418–1431
Doll CNH, Muller JP, Elvidge CD (2000) Night-time imagery as a tool for global mapping of socioeconomic parameters and greenhouse gas emissions. AMBIO: J Human Environ 29(3):157–162
Elvidge CD, Baugh KE, Dietz JB (1999) Radiance calibration of DMSP-OLS low-light imaging data of human settlements. Remote Sens Environ 68(1):77–88
Elvidge CD, Imhoff ML, Baugh KE (2001) Night time lights of the world: 1994–1995. ISPRS J Photogramm Try Remote Sens 56(2):81–99
Elvidge CD, Sutton PC, Ghosh T (2009) A global poverty map derived from satellite data. Comput Geosci 35(8):1652–1660
Feng F, Ye AZ (2013) Does the relationship between economic development and CO2 emissions in China follow EKC hypothesis? A test based on semiparametric panel data model. Forecasting 32(3):8–12
Friedl B, Getzner M (2003) Determinants of CO2 emissions in a small open economy. Economics 45(1):133–148
Gao Y, Wang H, Wang P (2013) Population spatial processing for Chinese coastal zones based on census and multiple night light data. Resour Sci 35(12):2517–2523
Ghosh T, Elvidge CD, Sutton PC (2010) Creating a global grid of distributed fossil fuel CO2 emissions from nighttime satellite imagery. Energies 3(12):1895–1913
Han XD, Zhou Y, Wang SX (2012) GDP spatialization in China based on DMSP/OLS data and land use data. Remote Sens Technol Appl 27(3):396–405
He CY, Ma Q, Li T (2012) Spatiotemporal dynamics of electric power consumption in Chinese Mainland from 1995 to 2008 modeled using DMSP/OLS stable nighttime lights data. J Geog Sci 22(1):125–136
Jiang L, He SX, Zhong ZQ (2019) Revisiting environmental Kuznets curve for carbon dioxide emissions: the role of trade. Struct Chang Econ Dyn 50:245–257
Le HP, Ozturk I (2020) The impacts of globalization, financial development, government expenditures, and institutional quality on CO2 emissions in the presence of environmental Kuznets curve. Environ Sci Pollut Res 27:22680–22697
Lei M, Yin ZH, Yu XW (2017) Carbon-weighted economic development performance and driving force analysis: evidence from China. Energy Policy 111:179–192
Liu LW, Chen CX, Zhao YF (2015a) China’s carbon-emissions trading: overview, challenges and future. Renew Sustain Energy Rev 49:254–266
Liu Z, Guan DB, Moore S (2015b) Steps to China’s carbon peak. Nature 522(7556):279–281
Liu CL, Wang T, Guo QB (2016) Temporal allometry and its mechanism on CO2 emissions from urban—transport in Wuhan City. Soft Sci 30(12):49–53, 79
Lu Q, Liu HB, Wang JT (2020) Multiscale analysis on spatiotemporal dynamics of energy consumption CO2 emissions in China: utilizing the integrated of DMSP-OLS and NPP-VIIRS nighttime light datasets. Sci Total Environ 703:134394
Pan JH, Zhang YN (2021) Spatiotemporal patterns of energy carbon footprint and decoupling effect in China. Acta Geogr Sin 76(1):206–222
Shi KF, Yu BL, Zhou YY (2019) Spatiotemporal variations of CO2 emissions and their impact factors in China: a comparative analysis between the provincial and prefectural levels. Appl Energy 233–234:170–181
Shi KF, Shen JW, Wu YZ (2021) Carbon dioxide (CO2) emissions from the service industry, traffic, and secondary industry as revealed by the remotely sensed nighttime light data. Int J Digit Earth 14(11):1514–1527
Su YX, Chen XZ, Ye YY (2013) The characteristics and mechanisms of carbon emissions from energy consumption in China using DMSP / OLS night light imageries. Acta Geogr Sin 68(11):1513–1526
Sun Y, Zhang Y, Liu XM (2020) Driving factors of urban transportation CO2 emission in Beijing —an analysis based on the urban development perspective. Urban Environ Stud 1:81–95
Wang SJ, Huang YY (2019) Spatial spillover effect and driving forces of carbon emission intensity at city level in China. Acta Geogr Sin 74(6):1131–1148
Wang SJ, Su YX, Zhao YB (2018) Regional inequality, spatial spillover effects and influencing factors of China’s city-level energy-related carbon emissions. Acta Geogr Sin 73(3):414–428
Wang SJ, Gao S, Huang YY (2020) Spatio-temporal evolution and trend prediction of urban carbon emission performance in China based on super-efficiency SBM model. Acta Geogr Sin 75(6):1316–1330
Wise M, Calvin K, Thomson A (2009) Implications of limiting CO2 concentrations for land use and energy. Science 324:1183–1186
Wu H, Gu SZ, Guan XL (2013) Analysis on relationship between carbon emissions from fossil energy consumption and economic growth in China. J Nat Resour 28(3):381–390
Wu JS, Niu Y, Peng J (2014) Research on energy consumption dynamic among prefecture level cities in China based on DMSP/OLS nighttime light. Geogr Res 33(4):625–634
Xu WX, Liang JZ (2020) Saturation correction method of DMSP/OLS nighttime lights image based on compound exponential model. Journal of Geo-Information Science 22(11):2227–2237
Xu Q, Dong YX, Yang R (2019) Temporal and spatial differences in carbon emissions in the Pearl River Delta based on multi-resolution emission inventory modeling. J Clean Prod 214:615–622
Yu DH, Zhang MZ (2016) Resolution of “the heterogeneity difficulty” and re-verification of the carbon emission EKC: based on the country grouping test under the threshold regression. China Indust Econ 7:57–73
Zhang GX, Gao XL, Wang YL (2014) Measurement, coordination and evolution of energy conservation and emission reduction policies in China: based on the research of the policy data from 1978 to 2013. Resour Environ 24(12):62–73
Zhao JC, Ji GX, Yue YL (2019) Spatio-temporal dynamics of urban residential CO2 emissions and their driving forces in China using the integrated two nighttime light datasets. Appl Energy 235:612–624
Zhao M, Zhou YY, Li XC (2020) Building a series of consistent night-time light data (1992–2018) in Southeast Asia by integrating DMSP-OLS and NPP-VIIRS. IEEE Trans Geosci Remote Sens 58(3):1843–1856
Zhou Y, Smith SJ, Elvidge CD (2014) A cluster-based method to map urban area from DMSP/OLS nightlights. Remote Sens Environ 147:173–185
Zhuo L, Zhang X, Zheng J (2015) An EVI-based method to reduce saturation of DMSP/OLS nighttime light data. Acta Geographica Sinica 70(8):1339–135
Zuo C, Gong W, Gao Z (2022) Correlation analysis of CO2 concentration based on DMSP-OLS and NPP-VIIRS integrated data. Remote Sens 14:4181
Funding
This work was supported by the Key University Science Research Project of Anhui Province (grant nos. KJ2020A0724, KJ2021A1078, KJ2021A1079, and zrjz2021021), the Key Research Projects of Provincial Humanities and Social Sciences in Colleges and Universities (grant nos. SK2021A0687 and 2022AH051063), and Chuzhou science and technology guiding plan project (grant no. 2021ZD007).
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J.X. wrote the manuscript of this article; Q.L. put forward the original idea; J.X. provided the research methodologies. N.R., F.H., W.J., Y.L., and W.M. collected the data on the carbon emissions.
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Xu, J., Liu, Q., Ruan, N. et al. The allometric relationship between carbon emission and economic development in Yangtze River Delta: fusion of multi-source remote sensing nighttime light data. Environ Sci Pollut Res 30, 120120–120136 (2023). https://doi.org/10.1007/s11356-023-30692-5
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DOI: https://doi.org/10.1007/s11356-023-30692-5