scholarly journals Impact of Influencing Factors on CO2 Emissions in the Yangtze River Delta during Urbanization

2019 ◽  
Vol 11 (15) ◽  
pp. 4183 ◽  
Author(s):  
Yixi Xue ◽  
Jie Ren ◽  
Xiaohang Bi
Keyword(s):  
Co2 Emissions ◽  
Yangtze River ◽  
Energy Intensity ◽  
Yangtze River Delta ◽  
Gdp Per Capita ◽  
The Yangtze River ◽  
Per Capita ◽  
Urbanization Rate ◽  
The Yangtze River Delta

The Yangtze River Delta (YRD) is China’s largest urban agglomeration with a rapid urbanization process. This paper analyzes the dynamic relationship between urbanization rate, energy intensity, GDP per capita, and population with CO2 emissions in YRD over 1990–2011 based on the extended STIRPAT model, impulse response function, and variance decomposition. A support vector machine model was constructed to further predict the scenarios of YRD’s CO2 emissions from 2015–2020. The results show that YRD’s CO2 emissions continuously increased during the sample period and are predicted to increase over 2015–2020. Energy intensity is the most influential factor, both in the short and long term, and the total population contributes the least. However, the influencing magnitude of energy intensity tends to decrease in the long term. The increase of urbanization rate is still accompanied by the increase of CO2 emissions in YRD, but an inverted-U shape relationship between them may exist in the long term. The contribution of GDP per capita to CO2 emissions is higher than the population and urbanization rate, and its contribution rate for CO2 emissions is growing. The Kuznets curve does not exist in the current YRD.

scholarly journals Spatiotemporal Characteristics of Ecological Conditions and Its Response to Natural Conditions and Human Activities during 1990–2010 in the Yangtze River Delta, China

2018 ◽  
Vol 15 (12) ◽  
pp. 2910 ◽  
Author(s):  
Ziqi Meng ◽  
Min Liu ◽  
Qiannan She ◽  
Fang Yang ◽  
Lingbo Long ◽  
...  
Keyword(s):  
Influencing Factors ◽  
Human Activities ◽  
Yangtze River ◽  
Yangtze River Delta ◽  
The Yangtze River ◽  
Natural Conditions ◽  
Per Capita Gdp ◽  
Per Capita ◽  
Urbanization Rate ◽  
The Yangtze River Delta

The Yangtze River Delta (YRD) region, including Shanghai City and the Jiangsu and Zhejiang Provinces, is the largest metropolitan region in China. In the past three decades, the region has experienced an unprecedented process of rapid and massive urbanization, which has dramatically altered the landscape and detrimentally affected the ecological environments in the region. In this paper, we analyzed the spatiotemporal variations of ecological conditions (Eco_C) via a synthetic index with analytic hierarchy processes in the YRD during 1990–2010. The relative contributions of influencing factors, including two natural conditions (i.e., elevation (Elev) and land-sea gradient (Dis_coa)), three indicators of human activities (i.e., urbanization rate (Urb_rate), per capita GDP (Per_gdp), the percentage of secondary and tertiary industry employment (Per_ind)), to the total variance of regional Eco_C were also investigated. The results showed that: (1) The Eco_C over YRD region was “Moderately High”, which was better than the national average and demonstrated obvious spatial variations between south and north. There existed fluctuations and an overall increasing trend for Eco_C during the study period, with 20% of the area being deteriorated and 40% being improved. (2) The areas with elevation below 10 m was relatively poor in Eco_C, while the regions above 1000 m showed the best Eco_C and had the most obvious changes (9.33%) during the study period. (3) The selected five influencing factors could explain 91.0–94.4% of the Eco_C spatial variability. Elevation was the dominant factor for about 42.4–52.9%, while urbanization rate and per capita GDP were about 32.5% and 9.3%.

Anthropogenic CO2 emissions from a megacity in the Yangtze River Delta of China

2018 ◽  
Vol 25 (23) ◽  
pp. 23157-23169 ◽  
Author(s):  
Cheng Hu ◽  
Shoudong Liu ◽  
Yongwei Wang ◽  
Mi Zhang ◽  
Wei Xiao ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Yangtze River ◽  
Yangtze River Delta ◽  
River Delta ◽  
The Yangtze River ◽  
Anthropogenic Co2 ◽  
The Yangtze River Delta

scholarly journals Spatio-Temporal Variations of CO2 Emission from Energy Consumption in the Yangtze River Delta Region of China and Its Relationship with Nighttime Land Surface Temperature

2020 ◽  
Vol 12 (20) ◽  
pp. 8388
Author(s):  
Juchao Zhao ◽  
Shaohua Zhang ◽  
Kun Yang ◽  
Yanhui Zhu ◽  
Yuling Ma
Keyword(s):  
Surface Temperature ◽  
Co2 Emissions ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Yangtze River ◽  
Yangtze River Delta ◽  
The Yangtze River ◽  
Delta Region ◽  
Yangtze River Delta Region ◽  
The Yangtze River Delta

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.

Long-term trend of haze pollution and impact of particulate matter in the Yangtze River Delta, China

2013 ◽  
Vol 182 ◽  
pp. 101-110 ◽  
Author(s):  
Zhen Cheng ◽  
Shuxiao Wang ◽  
Jingkun Jiang ◽  
Qingyan Fu ◽  
Changhong Chen ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Yangtze River ◽  
Yangtze River Delta ◽  
River Delta ◽  
The Yangtze River ◽  
Term Trend ◽  
Haze Pollution ◽  
Long Term Trend ◽  
The Yangtze River Delta

scholarly journals Separating emission and meteorological contributions to long-term PM<sub>2.5</sub> trends over eastern China during 2000–2018

2021 ◽  
Vol 21 (12) ◽  
pp. 9475-9496
Author(s):  
Qingyang Xiao ◽  
Yixuan Zheng ◽  
Guannan Geng ◽  
Cuihong Chen ◽  
Xiaomeng Huang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Yangtze River ◽  
Eastern China ◽  
Yangtze River Delta ◽  
Meteorological Conditions ◽  
River Delta ◽  
The Yangtze River ◽  
The Yangtze River Delta ◽  
Meteorological Effects

Abstract. The contribution of meteorology and emissions to long-term PM2.5 trends is critical for air quality management but has not yet been fully analyzed. Here, we used the combination of a machine learning model, statistical method, and chemical transport model to quantify the meteorological impacts on PM2.5 pollution during 2000–2018. Specifically, we first developed a two-stage machine learning PM2.5 prediction model with a synthetic minority oversampling technique to improve the satellite-based PM2.5 estimates over highly polluted days, thus allowing us to better characterize the meteorological effects on haze events. Then we used two methods to examine the meteorological contribution to PM2.5: a generalized additive model (GAM) driven by the satellite-based full-coverage daily PM2.5 retrievals and the Weather Research and Forecasting/Community Multiscale Air Quality (WRF/CMAQ) modeling system. We found good agreements between GAM estimations and the CMAQ model estimations of the meteorological contribution to PM2.5 on a monthly scale (correlation coefficient between 0.53–0.72). Both methods revealed the dominant role of emission changes in the long-term trend of PM2.5 concentration in China during 2000–2018, with notable influence from the meteorological condition. The interannual variabilities in meteorology-associated PM2.5 were dominated by the fall and winter meteorological conditions, when regional stagnant and stable conditions were more likely to happen and when haze events frequently occurred. From 2000 to 2018, the meteorological contribution became more unfavorable to PM2.5 pollution across the North China Plain and central China but were more beneficial to pollution control across the southern part, e.g., the Yangtze River Delta. The meteorology-adjusted PM2.5 over eastern China (denoted East China in figures) peaked in 2006 and 2011, mainly driven by the emission peaks in primary PM2.5 and gas precursors in these years. Although emissions dominated the long-term PM2.5 trends, the meteorology-driven anomalies also contributed −3.9 % to 2.8 % of the annual mean PM2.5 concentrations in eastern China estimated from the GAM. The meteorological contributions were even higher regionally, e.g., −6.3 % to 4.9 % of the annual mean PM2.5 concentrations in the Beijing-Tianjin-Hebei region, −5.1 % to 4.3 % in the Fenwei Plain, −4.8 % to 4.3 % in the Yangtze River Delta, and −25.6 % to 12.3 % in the Pearl River Delta. Considering the remarkable meteorological effects on PM2.5 and the possible worsening trend of meteorological conditions in the northern part of China where air pollution is severe and population is clustered, stricter clean air actions are needed to avoid haze events in the future.

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