2023
DOI: 10.1016/j.eiar.2023.107165
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Impact of National Industrial Relocation Demonstration Zones (NIRDZs) policy on urban carbon emissions in China

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Cited by 20 publications
(2 citation statements)
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“…As of December 2020, China had 93 EIPs distributed across all mainland provinces except Tibet and Qinghai [23]. The construction of EIPs is promoted by the central government through pilot projects, where local governments must voluntarily apply for provincial-level EIPs, which are then reviewed and approved by the central government to decide on the pilot national EIPs in different cities [28]. The incremental implementation nature allows for evaluating the effectiveness of EIP policies by comparing trends before and after policy implementation.…”
Section: Introductionmentioning
confidence: 99%
“…As of December 2020, China had 93 EIPs distributed across all mainland provinces except Tibet and Qinghai [23]. The construction of EIPs is promoted by the central government through pilot projects, where local governments must voluntarily apply for provincial-level EIPs, which are then reviewed and approved by the central government to decide on the pilot national EIPs in different cities [28]. The incremental implementation nature allows for evaluating the effectiveness of EIP policies by comparing trends before and after policy implementation.…”
Section: Introductionmentioning
confidence: 99%
“…A study on CEs in the field of LULUCF in the Vietnam mainland applied 10 years of land cover change data (2002-2012) as sources, processed those data with a specific software (ALU, v2014), and estimated the CEs based on the quality control and quality assurance work [37]. Some typical related research on CEs, land-use changing characteristics, and NST are listed in Table 1 [32][33][34][35][38][39][40][41][42][43]. A large number of previous works demonstrated the promising future and high efficiency of methods for land-use CEs calculation and relative correlation analysis based on the remote sensing (RS) data classification and the statistical data analysis via software processing.…”
Section: Introductionmentioning
confidence: 99%