scholarly journals Driving forces of temporal-spatial differences in CO2 emissions at the city level for China’s transport sector

2021 ◽  
Author(s):  
Yuxiang Liu ◽  
Songyuan Yang ◽  
Xianmei Liu ◽  
Pibin Guo ◽  
Keyong Zhang
Keyword(s):  
Influencing Factors ◽  
Driving Forces ◽  
Income Effect ◽  
Transport Sector ◽  
Temporal Perspective ◽  
Intensity Effect ◽  
Spatial Decomposition ◽  
Spatial Differences ◽  
Temporal And Spatial ◽  
Main Factor

AbstractThe paper aims to investigate the influencing factors that drive the temporal and spatial differences of CO2 emissions for the transportation sector in China. For this purpose, this study adopts a Logistic Mean Division Index (LMDI) model to explore the driving forces of the changes for the transport sector’s CO2 emissions from a temporal perspective during 2000–2017 and identifies the key factors of differences in the transport sector’s CO2 emissions of China’s 15 cities in four key years (i.e., 2000, 2005, 2010, and 2017) using a multi-regional spatial decomposition model (M-R). Based on the empirical results, it was found that the main forces for affecting CO2 emissions of the transport sector are not the same as those from temporal and spatial perspectives. Temporal decomposition results show that the income effect is the dominant factor inducing the increase of CO2 emissions in the transport sector, while the transportation intensity effect is the main factor for curbing the CO2 emissions. Spatial decomposition results demonstrate that income effect, energy intensity effect, transportation intensity effect, and transportation structure effect are important factors which result in enlarging the differences in city-level CO2 emissions. In addition, the less-developed cities and lower energy efficiency cities have greater potential to reduce CO2 emissions of the transport sector. Understanding the feature of CO2 emissions and the influencing factors of cities is critical for formulating city-level mitigation strategies of the transport sector in China. Overall, it is expected that the level of economic development is the main factor leading to the differences in CO2 emissions from a spatial-temporal perspective.

scholarly journals Determinizing the contributions of human activities and climate change on greening in the Beijing–Tianjin–Hebei Region, China

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Wei Cao ◽  
Dan Wu ◽  
Lin Huang ◽  
Mei Pan ◽  
Taoli Huhe
Keyword(s):  
Climate Change ◽  
Human Activities ◽  
Driving Forces ◽  
Vegetation Coverage ◽  
Agricultural Activities ◽  
Positive Effects ◽  
Nonlinear Responses ◽  
Spatial Differences ◽  
Temporal And Spatial ◽  
Region Scale

AbstractChina accounts for 25% of the global greening. There are temporal and spatial differences of China’s greening and intrinsic driving forces. Thus, it is crucial to determinize the contributions of human activities and climate change on greening at region scale. The Beijing–Tianjin–Hebei Region (BTHR) is one of the most active areas with human activities in China. It is necessary to explore negative or positive impacts of human activities on the regional greening or browning under climate change. A time series of annual vegetation coverage from satellite data was selected to quantify regional greening in the BTHR from 2000 to 2019 and their responses to climate change and human activities. Results showed generally widespread greening over the last 20 years at an average increased rate of 0.036 decade−1 in vegetation coverage (P < 0.01). Overall warmer and wetter climate across the BTHR were positively correlated with regional greening. The positive effects of human activities on greening accounted for 48.4% of the BTHR, especially the benefits of ecological restoration projects and the agricultural activities. Increases in vegetation coverage had resulted from the combined effects of climate change and human activities. Climate change had a stronger influence on vegetation coverage than human activities. Contributions of climate change to greening and browning was about 74.1% and < 20%, respectively. The decrease in vegetation coverage was mainly the results of the inhibition of human activities. More detailed socioeconomic and anthropogenic datasets are required for further analysis. Further research consideration would focus on the nonlinear responses of vegetation to climate change.

scholarly journals The Spatio-Temporal Analysis of Urban-Rural Coordinated Development and Its Driving Forces in Yangtze River Delta

Land ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 495
Author(s):  
Daizhong Tang ◽  
Mengyuan Mao ◽  
Jiangang Shi ◽  
Wenwen Hua
Keyword(s):  
Influencing Factors ◽  
Yangtze River ◽  
Driving Forces ◽  
Yangtze River Delta ◽  
River Delta ◽  
Urban Agglomeration ◽  
System Level ◽  
Actual State ◽  
Coordinated Development ◽  
Urban Rural

This paper conducts an analytical study on the urban-rural coordinated development (URCD) in the Yangtze River Delta urban agglomeration (YRDUA), and uses data from 2000–2015 of 27 central cities to study the spatial and temporal evolution patterns of URCD and to discover the influencing factors and driving forces behind it through PCA, ESDA and spatial regression models. It reveals that URCD of the YRDUA shows an obvious club convergence phenomenon during the research duration. The regions with high-level URCD gather mainly in the central part of the urban agglomeration, while the remaining regions mostly have low-level URCD, reflecting the regional aggregation phenomenon of spatial divergence. At the same time, we split URCD into efficiency and equity: urban-rural efficient development (URED) also exhibits similar spatiotemporal evolution patterns, but the patterns of urban-rural balanced development (URBD) show some variability. Finally, by analyzing the driving forces in major years during 2000–2015, it can be concluded that: (i) In recent years, influencing factors such as government financial input and consumption no longer play the main driving role. (ii) Influencing factors such as industrialization degree, fixed asset investment and foreign investment even limit URCD in some years. The above results also show that the government should redesign at the system level to give full play to the contributing factors depending on the actual state of development in different regions and promote the coordinated development of urban and rural areas. The results of this study show that the idea of measuring URCD from two dimensions of efficiency and equity is practical and feasible, and the spatial econometric model can reveal the spatial distribution heterogeneity and time evolution characteristics of regional development, which can provide useful insights for urban-rural integration development of other countries and regions.

scholarly journals TEMPERATURE-SENSITIVE MUTATIONS OF THE NOTCH LOCUS IN DROSOPHILA MELANOGASTER

Genetics ◽  
1975 ◽  
Vol 81 (1) ◽  
pp. 143-162 ◽  
Author(s):  
David L Shellenbarger ◽  
J Dawson Mohler
Keyword(s):  
Temperature Shift ◽  
Temperature Sensitive ◽  
Spatial Differences ◽  
Region Temperature ◽  
Complex Locus ◽  
Notch Locus ◽  
Temporal And Spatial ◽  
Chemical Conditions ◽  
Interallelic Complementation ◽  
The Right

ABSTRACT Temperature-conditional mutations of the Notch locus were characterized in an attempt to understand the organization of a "complex locus" and the control of its function in development. Among 21 newly induced Notch alleles, about one-half are temperature-conditional for some effects, and three are temperature-sensitive for viability. One temperature-sensitive lethal, l(1)Nts1, is functionally non-complementing for all known effects of Notch locus mutations and maps at a single site within the locus. Among the existing alleles involved in complex patterns of interallelic complementation, Ax59d5 is found to be temperature-sensitive, while fag, spl, and l(1)N are temperature-independent. Whereas temperature-sensitive alleles map predominantly to the right-most fifth of the locus, fag, spl, and l(1)N are known to map to the left of this region. Temperature-shift experiments demonstrate that fag, spl, and l(1)N cause defects at specific, non-overlapping times in development.—We conclude (1) that the Notch locus is a single cistron (responsible for a single functional molecule, presumably a polypeptide); (2) that the right-most fifth of the locus is, at least in part, the region involved in coding for the Notch product; (3) that the complexity of interallelic complementation is a developmental effect of mutations that cause defects at selected times and spaces, and that complementation occurs because the mutant defects are temporally and spatially non-overlapping; and (4) that mutants express selected defects due to critical temporal and spatial differences in the chemical conditions controlling the synthesis or function of the Notch product. The complexity of the locus appears to reside in controlling the expression (synthesis or function) of the Notch product in development.

scholarly journals A Decomposition Analysis of the Korean Manufacturing Sector: Monetary vs. Physical Outputs

2021 ◽  
Vol 13 (11) ◽  
pp. 6192
Author(s):  
Junghwan Lee ◽  
Jinsoo Kim
Keyword(s):  
Energy Consumption ◽  
Energy Use ◽  
Driving Forces ◽  
Manufacturing Sector ◽  
Decomposition Analysis ◽  
Primary Energy ◽  
Intensity Effect ◽  
Activity Effect ◽  
Index Decomposition ◽  
Output Indicator

This study analyzes the changes in energy consumption of the Korean manufacturing sector using the index decomposition analysis (IDA) method. To capture the production effect based on actual physical activities, we applied the activity revaluation (AR) approach in the analysis. We also developed energy consumption data in terms of primary energy supply to consider conversion loss in the energy sector to avoid any distortions in the intensity effect. The analysis covers every manufacturing subsector in Korea over the period between 2006 and 2018. Combining two distinctive approaches from the previous literature, the AR approach and primary energy-based analysis gives us helpful findings for a climate policy. First, the overall activity effect estimated from the physical output indicator is lower than that from the monetary output indicator. The monetary indicator shows that the share of energy-intensive industries decreases, whereas the physical indicator shows the opposite. Second, in terms of energy efficiency, the intensity effect is estimated as an increasing factor of energy use, whereas inversed results are shown when we use the monetary indicator. Lastly, unlike the previous studies, the AR approach results indicate that Korean manufacturing sectors have been shifting toward an energy-intensive, so it is hard to anticipate positive intensity effects, which means decreasing energy consumption factor, for a while. These results support why analyzing the driving forces of energy consumption through the AR approach and primary energy base is highly recommended.

scholarly journals Grey Relational Grade Based Quantitative Analysis of the Factors Influencing the Load Characteristics of A Power Grid

2018 ◽  
Vol 53 ◽  
pp. 01012 ◽  
Author(s):  
Wei Pan ◽  
Caijia Lei ◽  
Wei Jia ◽  
Hui Gao ◽  
Binghua Fang
Keyword(s):  
Quantitative Analysis ◽  
Influencing Factors ◽  
Power Grid ◽  
Grey System Theory ◽  
Grey System ◽  
Factors Affecting ◽  
Grey Relational Grade ◽  
Load Characteristics ◽  
Grey Relational ◽  
Main Factor

Regarding analysis of load characteristics of a power grid, there are multiple factors that influence the variation of load characteristics. Among these factors, the influence of different ones on the change of load characteristic is somewhat different, thus the degree of influence of various factors needs to be quantified to distinguish the main and minor factors of load characteristics. Based on this, the grey relational analysis in the grey system theory is employed as the basis of mathematical model in this paper. Firstly, the main factors affecting the load characteristics of a power grid are analysed. Then, the principle of quantitative analysis of the influencing factors by using grey relational grade is introduced. Lastly, the load of Guangzhou power grid is selected as the research object, thereby the main factor of temperature affecting the load characteristics is quantitatively analysed, such that the correlation between temperature and load is established. In this paper, by investigating the influencing factors and the degree of influence of load characteristics, the law of load characteristics changes can be effectively revealed, which is of great significance for power system planning and dispatching operation.

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