The rising impact of urbanization-caused CO2 emissions on terrestrial vegetation

Yang, Songxi; Yang, Jian; Shi, Shuo; Song, Shalei; Luo, Yi; Du, Lina

doi:10.1016/j.ecolind.2023.110079

Cited by 16 publications

(5 citation statements)

References 59 publications

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“…Moreover, the temporal and vertical resolutions of the lidar observation data are 1 s and 7.5 m, respectively. The overlap of the lidar system is 150 m. Further instrumental details on the parameters can be found in previous studies [33,34]. In total, 132 days of experimental data were collected from June 2015 to June 2016, and the lidar data were averaged into hourly profiles.…”

Section: Lidar Datamentioning

confidence: 99%

A Cluster Analysis Approach for Nocturnal Atmospheric Boundary Layer Height Estimation from Multi-Wavelength Lidar

Zhu

Zhou

et al. 2023

Atmosphere

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The atmospheric boundary layer provides useful information about the accumulation and diffusion of pollutants. As a fast method, remote sensing techniques are used to retrieve the atmospheric boundary layer height (ABLH). Atmospheric detection lidar has been widely applied for retrieving the ABLH by providing information on the vertical distribution of aerosols. However, these previous algorithms that rely on gradient change are susceptible to residual layers. Contrary to the use of gradient change to retrieve ABLH, in this paper, we propose using a cluster analysis approach through multifunction lidar remote sensing techniques due to its increasing availability. The clustering algorithm for multi-wavelength lidar data can be divided into two parts: characteristic signal selection and selection of the classifier. First, since the separability of each type of signal is different, careful selection of the input characteristic signal is important. We propose using Fourier transform for all the observed signals; the most suitable characteristic signal can be determined based on the dispersion degree of the signal in the frequency domain. Then, the performances of four common classifiers (K-means method, Gaussian mixture model, hierarchical cluster method (HCM), and density-based spatial clustering of applications with noise) are evaluated by comparing with the radiosonde measurements from June 2015 to June 2016. The results show that the performance of the HCM classifier is the best under all states (R2 = 0.84 and RMSE = 0.18 km). The findings obtained here offer insight into ABLH remote sensing technology.

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Section: Lidar Datamentioning

confidence: 99%

A Cluster Analysis Approach for Nocturnal Atmospheric Boundary Layer Height Estimation from Multi-Wavelength Lidar

Zhu

Zhou

et al. 2023

Atmosphere

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“…The study found that URPOP raised CO2 emissions, but the FDI inflows minimized this effect. Yang et al (2023) studied terrestrial vegetation economies to examine the impact of URPOP on the environment from 2009 to 2018. The study explored that the URPOP contributed to CO2 emissions in the atmosphere of about 3.93 ppm.…”

Section: Review Of Literaturementioning

confidence: 99%

Analyzing the Impact of Urbanization on Carbon Dioxide Emissions: Fresh Evidence from Pakistan

Asghar,

ur Rehman,

Salman

2023

Forman J. econ. stud.

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Over several decades, unplanned urbanization is increasing CO2 emissions due to higher energy demand from industrial activities, transportation, and waste management. The present study assesses the link between urbanization and CO2 emissions in Pakistan from 1985 to 2020 by controlling FDI, access to electricity, and institution quality. The empirical results are estimated by using the ARDL approach while causality is extracted through the Granger Causality test. The empirical findings depict that urbanization leads to CO2 emissions. Furthermore, institutional quality declines CO2 emissions, while FDI and access to electricity significantly increase CO2 emissions. The Granger Causality results indicate a bidirectional causality between electricity access and CO2 emissions. At the same time, CO2 emissions and urbanization show unidirectional causality. The study suggests that Pakistan needs to promote an environment-friendly energy consumption pattern

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“…However, it is important to note that the methane concentrations obtained by satellites mainly consist of molar fractions of methane in the atmospheric columnaveraged dry air (Schneising et al, 2019), which may not precisely reflect ground-level methane levels (Shi et al, 2021;Shi et al, 2023). Considering the high concentration of human production and living space on the ground, it is necessary to acquire ground methane concentration data for monitoring sources and changes in methane (Yang et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

Improved Gaussian regression model for retrieving ground methane levels by considering vertical profile features

He,

Zheng,

Zhao

et al. 2024

Front. Earth Sci.

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Atmospheric methane is one of the major greenhouse gases and has a great impact on climate change. To obtain the polluted levels of atmospheric methane in the ground-level range, this study used satellite observations and vertical profile features derived by atmospheric chemistry model to estimate the ground methane concentrations in first. Then, the improved daily ground-level atmospheric methane concentration dataset with full spatial coverage (100%) and 5-km resolution in mainland China from 2019 to 2021 were retrieved by station-based observations and gaussian regression model. The overall estimated deviation between the estimated ground methane concentrations and the WDCGG station-based measurements is less than 10 ppbv. The R by ten-fold cross-validation is 0.93, and the R2 is 0.87. The distribution of the ground-level methane concentrations in the Chinese region is characterized by high in the east and south, and low in the west and north. On the time scale, ground-level methane concentration in the Chinese region is higher in winter and lower in summer. Meanwhile, the spatial and temporal distribution and changes of ground-level methane in local areas have been analyzed using Shandong Province as an example. The results have a potential to detect changes in the distribution of methane concentration.

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The rising impact of urbanization-caused CO2 emissions on terrestrial vegetation

Cited by 16 publications

References 59 publications

A Cluster Analysis Approach for Nocturnal Atmospheric Boundary Layer Height Estimation from Multi-Wavelength Lidar

A Cluster Analysis Approach for Nocturnal Atmospheric Boundary Layer Height Estimation from Multi-Wavelength Lidar

Analyzing the Impact of Urbanization on Carbon Dioxide Emissions: Fresh Evidence from Pakistan

Improved Gaussian regression model for retrieving ground methane levels by considering vertical profile features

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