Assessing the progress and spatial patterns of sustainable eco-environmental development based on the 2030 Agenda for SDGs in China

ABSTRACT

The eco-environment is fundamental for human survival and development. To gain insight into Chinese eco-environmental challenges, a scientific and quantifying assessment of sustainable eco-environmental development (SED) is essential and can guide policy development and implementation. However, systematic methods for assessing progress towards achieving SED are lacking based on the 2030 Agenda for the Sustainable Development Goals (SDGs). Therefore, we developed a systematic method to quantify SED progress at the provincial level in China. In the proposed method, the SED indicator framework was developed to align with the global indicator framework (GIF), adopting clear statistical definitions for each indicator and the criteria of data selection at provincial levels in China. A four-level method of identifying the upper and lower bounds of the indicator values was proposed to normalise them to a standard scale of 0–100. The SED index and three composite indices were aggregated by the arithmetic means of the individual scores for assessing overall SED progress. A spatial autocorrelation analysis was used to explore the spatial patterns of the SED index scores. The results showed that all provinces except Shandong and Hebei had relatively good performances in achieving SED. Most provinces performed better in terms of the water area eco-environment than they do in terms of the air and terrestrial eco-environments. In addition, some provinces showed a positive spatial autocorrelation pattern on the SED index scores, and the high-value (low-value) aggregation regions were mainly concentrated in Western (East) China. These results provide a richer understanding of the challenges for SED faced by each province in China.

KEYWORDS:

• Eco-environment
• sustainable development
• 2030 agenda
• spatial statistics
• spatial patterns

Acknowledgements

This study was jointly supported by the Open Topic of Hunan Key Laboratory of Remote Sensing Monitoring of Ecological Environment in Dongting Lake area (No: DTH Key Lab. 2022-13), the Scientific Research Fund of Hunan Provincial Education Department (No. 21C0154), National Natural Science Foundation of China (No. 41930650), and the Natural Science Foundation of Hunan, China (No. 2021JJ30245).

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The work was supported by the  Open Topic of Hunan Key Laboratory of Remote Sensing Monitoring of Ecological Environment in Dongting Lake area [2022-13], the Scientific Research Fund of Hunan Provincial Education Department [21C0154], National Natural Science Foundation of China [41930650], and the Natural Science Foundation of Hunan, China [No. 2021JJ30245].