Spatiotemporal differences in and influencing effects of per-capita carbon emissions in China based on population-related factors.

Sci Rep · 2023 · PMC10656470 · PMID 37978206

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an increasing trendno p-value reported

The height of the kernel density curve of the regions in class 1 generally showed an increasing trend, and the width widened.

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highly significantno p-value reported

Therefore, studying the spatiotemporal differences in carbon emissions is highly significant for narrowing the governance gap and ensuring balanced development in all regions.

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