Chinas regional ecological environment is facing serious carbon emission problems, and it is necessary to promote environmental protection and low-carbon development through sustainable development monitoring. In today’s society, the monitoring of sustainable development of ecological carbon emissions in China has a high error rate and low accuracy, which greatly affects the protection of ecological environment in China. LSTM algorithm in neural network is an effective technology for monitoring ecological carbon emissions in China. In this paper, the LSTM algorithm is used to create a monitoring system, which greatly improves the accuracy of early monitoring of Chinas ecological environmental carbon emissions and timely detection of excessive carbon emissions, thus promoting environmental protection. Finally, the experimental results show that the LSTM algorithm is easier to operate and has higher accuracy, up to 96.69%.