scholarly journals Evaluation and Factor Analysis of Industrial Carbon Emission Efficiency Based on “Green-Technology Efficiency”—The Case of Yangtze River Basin, China

Land ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1408
Author(s):  
Jingyi Wang ◽  
Kaisi Sun ◽  
Jiupai Ni ◽  
Deti Xie
Keyword(s):  
River Basin ◽  
Yangtze River ◽  
Carbon Emission ◽  
Stochastic Frontier Analysis ◽  
Yangtze River Basin ◽  
Green Technology ◽  
Frontier Analysis ◽  
Industrial Carbon ◽  
Emission Efficiency ◽  
Carbon Productivity

In the context of low-carbon development, effectively improving carbon emission efficiency is an inevitable requirement for achieving sustainable economic and social development. Based on panel data of 11 provinces and municipalities in the Yangtze River Basin (YRB), ranging from 2000 to 2019, this paper uses green-technology efficiency to measure industrial carbon emission efficiency via stochastic frontier analysis (SFA) incorporated with carbon productivity. This provides a comprehensive analytical framework for assessing the carbon emission efficiency, quantitatively measuring the reduction potential, and clarifying the incentive channels. The results are as follows: (1) The industrial carbon emission efficiency (ICEE) of YRB presents an increasing trend. Although differences in emission efficiency among provinces and municipalities are narrowing, their emission efficiency is still prominently imbalanced. (2) The potential for reducing industrial carbon emissions in this region shows an upward-to-downward trend. The decline in such potential of each province and municipality in recent years indicates that further reduction is becoming more difficult. (3) Effective means to improve ICEE are to improve the level of industrialization, promote technological innovation in industrial low-carbonization, and raise industrial productivity. Meanwhile, the significant spatial spillover effect of ICEE further emphasizes the necessity of strengthening the coordination of carbon reduction policies in YRB. The research in this paper adds a new perspective to the evaluation of ICEE and also provides reference and technical support for the government to enhance ICEE and formulate green and sustainable development policies.

scholarly journals Carbon Storage Change Analysis and Emission Reduction Suggestions under Land Use Transition: A Case Study of Henan Province, China

2021 ◽  
Vol 18 (4) ◽  
pp. 1844
Author(s):  
Dongyang Xiao ◽  
Haipeng Niu ◽  
Jin Guo ◽  
Suxia Zhao ◽  
Liangxin Fan
Keyword(s):  
Land Use ◽  
River Basin ◽  
Yangtze River ◽  
Carbon Emission ◽  
Yellow River ◽  
Yangtze River Basin ◽  
Yellow River Basin ◽  
River Basins ◽  
Henan Province ◽  
Huai River

The significant spatial heterogeneity among river basin ecosystems makes it difficult for local governments to carry out comprehensive governance for different river basins in a special administrative region spanning multi-river basins. However, there are few studies on the construction of a comprehensive governance mechanism for multi-river basins at the provincial level. To fill this gap, this paper took Henan Province of China, which straddles four river basins, as the study region. The chord diagram, overlay analysis, and carbon emission models were applied to the remote sensing data of land use to analyze the temporal and spatial patterns of carbon storage caused by land-use changes in Henan Province from 1990 to 2018 to reflect the heterogeneity of the contribution of the four basins to human activities and economic development. The results revealed that food security land in the four basins decreased, while production and living land increased. Ecological conservation land was increased over time in the Yangtze River Basin. In addition, the conversion from food security land to production and living land was the common characteristic for the four basins. Carbon emission in Henan increased from 134.46 million tons in 1990 to 553.58 million tons in 2018, while its carbon absorption was relatively stable (1.67–1.69 million tons between 1990 and 2018). The carbon emitted in the Huai River Basin was the main contributor to Henan Province’s total carbon emission. The carbon absorption in Yellow River Basin and Yangtze River Basin had an obvious spatial agglomeration effect. Finally, considering the current need of land spatial planning in China and the goal of carbon neutrality by 2060 set by the Chinese government, we suggested that carbon sequestration capacity should be further strengthened in Yellow River Basin and Yangtze River Basin based on their respective ecological resource advantages. For future development in Hai River Basin and Huai River Basin, coordinating the spatial allocation of urban scale and urban green space to build an ecological city is a key direction to embark upon.

scholarly journals Study on Dynamic Total Factor Carbon Emission Efficiency in China’s Urban Agglomerations

2020 ◽  
Vol 12 (7) ◽  
pp. 2675
Author(s):  
Fan Zhang ◽  
Gui Jin ◽  
Junlong Li ◽  
Chao Wang ◽  
Ning Xu
Keyword(s):  
Pearl River Delta ◽  
Yangtze River ◽  
Carbon Emission ◽  
Yangtze River Delta ◽  
River Delta ◽  
Pearl River ◽  
Low Carbon ◽  
Frontier Analysis ◽  
Urban Agglomerations ◽  
Emission Efficiency

The scale effect of urbanization on improving carbon emission efficiency and achieving low-carbon targets is an important topic in urban research. Using dynamic panel data from 64 prefecture-level cities in four typical urban agglomerations in China from 2006 to 2016, this paper constructed a stochastic frontier analysis model to empirically measure the city-level total-factor carbon emission efficiency index (TCEI) at different stages of urbanization and to identify rules governing its spatiotemporal evolution. We quantitatively analyzed the influences and functional characteristics of TCEI in the four urban agglomerations of Pearl River Delta, Beijing-Tianjin-Hebei, the Yangtze River Delta, and Chengdu-Chongqing. Results show that the TCEI at different stages of urbanization in these urban agglomerations is increasing year by year. The overall city-level TCEI was ranked as follows: Pearl River Delta > Beijing-Tianjin-Hebei > Yangtze River Delta > Chengdu-Chongqing. Improvements in the level of economic development and urbanization will help achieve low-carbon development in a given urban agglomeration. The optimization of industrial structure and improvement of ecological environment will help curb carbon emissions. This paper provides decision-making references for regional carbon emission reduction from optimizing industrial and energy consumption structures and improving energy efficiency.

scholarly journals Spatiotemporal Pattern of Pine Wilt Disease in the Yangtze River Basin

Forests ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 731
Author(s):  
Zhuoqing Hao ◽  
Jixia Huang ◽  
Yantao Zhou ◽  
Guofei Fang
Keyword(s):  
River Basin ◽  
Yangtze River ◽  
Yangtze River Basin ◽  
Pine Wilt Disease ◽  
Wilt Disease ◽  
Spatiotemporal Pattern ◽  
Pinewood Nematode ◽  
The Yangtze River ◽  
Pine Wilt ◽  
The Yangtze River Basin

The Yangtze River Basin is among the river basins with the strongest strategic support and developmental power in China. As an invasive species, the pinewood nematode (PWN) Bursaphelenchus xylophilus has introduced a serious obstacle to the high-quality development of the economic and ecological synchronization of the Yangtze River Basin. This study analyses the occurrence and spread of pine wilt disease (PWD) with the aim of effectively managing and controlling the spread of PWD in the Yangtze River Basin. In this study, statistical data of PWD-affected areas in the Yangtze River Basin are used to analyse the occurrence and spread of PWD in the study area using spatiotemporal visualization analysis and spatiotemporal scanning statistics technology. From 2000 to 2018, PWD in the study area showed an “increasing-decreasing-increasing” trend, and PWD increased explosively in 2018. The spatial spread of PWD showed a “jumping propagation-multi-point outbreak-point to surface spread” pattern, moving west along the river. Important clusters were concentrated in the Jiangsu-Zhejiang area from 2000 to 2015, forming a cluster including Jiangsu and Zhejiang. Then, from 2015–2018, important clusters were concentrated in Chongqing. According to the spatiotemporal scanning results, PWD showed high aggregation in the four regions of Zhejiang, Chongqing, Hubei, and Jiangxi from 2000 to 2018. In the future, management systems for the prevention and treatment of PWD, including ecological restoration programs, will require more attention.

scholarly journals Seasonal Rainfall Forecasts for the Yangtze River Basin in the Extreme Summer of 2020

2021 ◽  
Author(s):  
Philip E. Bett ◽  
Gill M. Martin ◽  
Nick Dunstone ◽  
Adam A. Scaife ◽  
Hazel E. Thornton ◽  
...  
Keyword(s):  
Linear Regression ◽  
River Basin ◽  
Yangtze River ◽  
Asian Summer Monsoon ◽  
Yangtze River Basin ◽  
Early Summer ◽  
Lead Times ◽  
Seasonal Forecasts ◽  
June July ◽  
The Impact

AbstractSeasonal forecasts for Yangtze River basin rainfall in June, May–June–July (MJJ), and June–July–August (JJA) 2020 are presented, based on the Met Office GloSea5 system. The three-month forecasts are based on dynamical predictions of an East Asian Summer Monsoon (EASM) index, which is transformed into regional-mean rainfall through linear regression. The June rainfall forecasts for the middle/lower Yangtze River basin are based on linear regression of precipitation. The forecasts verify well in terms of giving strong, consistent predictions of above-average rainfall at lead times of at least three months. However, the Yangtze region was subject to exceptionally heavy rainfall throughout the summer period, leading to observed values that lie outside the 95% prediction intervals of the three-month forecasts. The forecasts presented here are consistent with other studies of the 2020 EASM rainfall, whereby the enhanced mei-yu front in early summer is skillfully forecast, but the impact of midlatitude drivers enhancing the rainfall in later summer is not captured. This case study demonstrates both the utility of probabilistic seasonal forecasts for the Yangtze region and the potential limitations in anticipating complex extreme events driven by a combination of coincident factors.

scholarly journals Assessing the adequacy of bias corrected IMERG satellite precipitation estimates using extended mixture distribution mapping method over Yangtze River basin

2018 ◽  
Vol 246 ◽  
pp. 01096
Author(s):  
Qiumei Ma ◽  
Lihua Xiong ◽  
Chong-Yu Xu ◽  
Shenglian Guo
Keyword(s):  
River Basin ◽  
Yangtze River ◽  
Extreme Values ◽  
Yangtze River Basin ◽  
Mixture Distribution ◽  
Mapping Method ◽  
Generalized Pareto ◽  
Precipitation Estimates ◽  
Distribution Mapping ◽  
Emd Method

Satellite precipitation estimates (SPE) product with high spatiotemporal resolution is a potential alternative to traditional ground-based gauge precipitation. However, SPE is frequently biased due to its indirect measurement, and thus bias correction is necessary before applying to a specific region. An improved distribution mapping method, i.e., Extended Mixture Distribution (EMD) of censored Gamma and generalized Pareto distributions, was established. The advantage of EMD method is that it describes both moderate and extreme values well and carries on the traditional censored, shifted Gamma distribution to combine the precipitation occurrence/non-occurrence events together. Then the EMD method was applied to the Integrated Multi-satellitE Retrievals for GPM product (IMERG) as statistical post-processing over Yangtze River basin. The Version-2 Gridded dataset of daily Surface Precipitation from China Meteorological Administration (GSP-CMA) was taken as reference. The adequacy of bias corrected IMERG precipitation was assessed and the results showed that (1) the Root Mean Squared Error and Relative Bias between bias-corrected IMERG precipitation and reference are significantly reduced relative to the raw IMERG estimates; (2) the performance of extreme values of IMERG in Yangtze River basin is enhanced since both the under- and over-estimation of the raw IMERG are compromised, due to the generalized Pareto distribution introduced in EMD which is enable to describe the extreme value distribution. This highlights the improved distribution mapping method, EMD is flexible and robust to bias correct the IMERG precipitation to obtain higher accuracy of SPE despite the coarse resolution of reference.

scholarly journals Using the Global Hydrodynamic Model and GRACE Follow-On Data to Access the 2020 Catastrophic Flood in Yangtze River Basin

2021 ◽  
Vol 13 (15) ◽  
pp. 3023
Author(s):  
Jinghua Xiong ◽  
Shenglian Guo ◽  
Jiabo Yin ◽  
Lei Gu ◽  
Feng Xiong
Keyword(s):  
River Basin ◽  
Hydrodynamic Model ◽  
Yangtze River ◽  
Large Scale ◽  
Yangtze River Basin ◽  
The Yangtze River ◽  
Ecosystem Monitoring ◽  
Catastrophic Flood ◽  
Basin Scale ◽  
The Yangtze River Basin

Flooding is one of the most widespread and frequent weather-related hazards that has devastating impacts on the society and ecosystem. Monitoring flooding is a vital issue for water resources management, socioeconomic sustainable development, and maintaining life safety. By integrating multiple precipitation, evapotranspiration, and GRACE-Follow On (GRAFO) terrestrial water storage anomaly (TWSA) datasets, this study uses the water balance principle coupled with the CaMa-Flood hydrodynamic model to access the spatiotemporal discharge variations in the Yangtze River basin during the 2020 catastrophic flood. The results show that: (1) TWSA bias dominates the overall uncertainty in runoff at the basin scale, which is spatially governed by uncertainty in TWSA and precipitation; (2) spatially, a field significance at the 5% level is discovered for the correlations between GRAFO-based runoff and GLDAS results. The GRAFO-derived discharge series has a high correlation coefficient with either in situ observations and hydrological simulations for the Yangtze River basin, at the 0.01 significance level; (3) the GRAFO-derived discharge observes the flood peaks in July and August and the recession process in October 2020. Our developed approach provides an alternative way of monitoring large-scale extreme hydrological events with the latest GRAFO release and CaMa-Flood model.

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