Assessment of the Ecological Environmental Impact of Huizhou’s Urban Built-up Area Using the STIRPAT Model
- DOI
- 10.2991/978-2-38476-297-2_118How to use a DOI?
- Keywords
- STIRPAT Model; Ecological Environmental Impact; Multivariate Nonlinear Regression
- Abstract
This study systematically assesses the ecological environmental impact of Huizhou’s urban built-up area based on the extended STIRPAT model. Through multivariate nonlinear regression analysis, we quantified the impact of population, economy, and technology on the ecological environment. The results show that per capita consumption level, energy consumption structure, per capita building area, and per household population all have significant positive impacts on the ecological environment. The model fit is excellent, with an R-squared value of 0.902 and an adjusted R-squared value of 0.875, and the F-statistic is 33.14 with a high level of significance. The study reveals the key roles of consumption level and energy structure in environmental impact, providing important references for local governments to formulate scientific environmental management policies. Future research can further explore the specific mechanisms of each factor to enhance urban ecological environment management.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Jing Wang AU - Shuhong Peng PY - 2024 DA - 2024/10/31 TI - Assessment of the Ecological Environmental Impact of Huizhou’s Urban Built-up Area Using the STIRPAT Model BT - Proceedings of the 2024 8th International Seminar on Education, Management and Social Sciences (ISEMSS 2024) PB - Atlantis Press SP - 980 EP - 985 SN - 2352-5398 UR - https://doi.org/10.2991/978-2-38476-297-2_118 DO - 10.2991/978-2-38476-297-2_118 ID - Wang2024 ER -