Unveiling the nexus and promoting integration of diverse factors: Prospects of big data-driven artificial intelligence technology in achieving carbon neutrality in Chongming District

Abstract

Climate change is one of the most pressing challenges facing the world today. The large amount of greenhouse gas emissions produced by human activities, especially the emission of carbon dioxide, is an important driving factor behind climate issues. Under the background of China’s “3060” decarbonization goal”, Chongming District in Shanghai is actively promoting the construction of a world-class ecological island and is committed to creating a carbon–neutral demonstration zone with global influence. However, Chongming District faces challenges as the mechanism of carbon-neutrality transition path remains unclear. The data related to evaluating carbon neutrality status are heterogeneous from multiple sources. It is difficult to effectively implement relevant evaluation and response measures, impeding the progress of its low-carbon transformation. In response to the aforementioned challenges, this paper will propose and discuss the potential methods based on the new generation of information technology, represented by big data and artificial intelligence. These technologies aim to facilitate the integration of diverse factors, including carbon, and explore the nexus among them, thus exploring pathways for low-carbon transformation, and ultimately achieving decarbonization goal in Chongming District. Hopefully, the research conducted in this paper will contribute to the efforts of China and the global community in addressing carbon-related challenges and advancing towards a more sustainable and low-carbon future.

Keywords

• New generation of information technology
• Big data
• Artificial intelligence
• Deep learning
• Multi-element nexus