Recent developments in attaining carbon peaks and achieving carbon neutrality have had enormous effects on the world economy. Digitalization has been considered a viable way to curtail carbon emissions (CE) and promote sustainable economic development, but scant empirical studies investigate the link between digitalization and CE. In this context, this study constructs the digitalization index using the entropy value method and spatial Markov chain, and the spatial Durbin model is employed to analyze its impact mechanism and influence on urban CE in 265 prefecture-level cities and municipalities in China from 2011 to 2017. The results indicate that: (1) The overall development level of the digital economy (DE) posed a significant spatial effect on urban environmental pollution. However, the effect varies according to the different neighborhood backgrounds. (2) The DE impedes urban environmental deterioration directly and indirectly through the channels of industrial structure, inclusive finance, and urbanization. (3) The development of the DE significantly reduces pollution in cities belonging to urban agglomerations, while the development of the DE escalates emissions in nonurban agglomeration cities. Finally, based on the results, important policy implications are put forward to improve the environmental quality of cities.

Exploring a scientific and reasonable cross-regional carbon emission reduction path in China is essential to achieving sustainable development and the carbon neutrality target. This study constructs a simulation model of China’s cross-regional carbon emission reduction (CER) system and adopts a multi-agent approach to simulate cross-regional CER scenarios to predict the pathway. The conclusions are as follows: (1) under the national unified CER policy scenarios, carbon emissions are on a continuous growth trend with fast economic growth not matching emission reduction efforts in Scenario I. Scenario II has a lower economic scale, and carbon emissions peak in 2029. Scenario III has smooth economy and reaches the carbon emission peak in 2026. The economy of Scenario IV grows fast, carbon emissions grow slowly, and the peak does not appear in 2030. (2) In three scenarios with provinces as the main agent for CER, if provinces sacrifice the economy to strengthen CER, the peak of carbon emissions will appear in 2020. While the economy of non-synergistic and synergistic CER scenarios in each province is growing steadily, the peak in two modes is reached in 2026 and 2032. The peak is reached four years earlier in 2026 in the synergistic model and 2032 in the non-synergistic model, and the economic growth of some energy-intensive provinces slows down. (3) The synergistic low-carbon model is best for balancing economic development and carbon emission control. Policy recommendations are presented based on the above findings for China’s CER and sustainable development.

In recent years, the international environment has changed rapidly, and the uncertainty of the trade environment faced by enterprises has dramatically increased. As a major participant in world trade, the uncertainty of the trade environment has significantly impacted the daily business activities and various behaviors of Chinese manufacturing enterprises. Green technology innovation has also become an important tool for enterprises to enhance their sustainable development ability and improve their ability to cope with changes in the external environment. The change in the trade environment will affect the business development of enterprises. To face the change in the trade environment, enterprises often choose to improve their technology level and increase the added value of their products. In the context of sustainable development, green technology innovation has higher technical strength and is more in line with the requirements of international development, which is strong support for enterprises to cope with the change in the trade environment. However, the current literature is scant on the association between trade uncertainty and green innovation. In this context, this study used the data of Chinese manufacturing listed companies from 2011 to 2020 to empirically analyze the relationship between trade environment uncertainty (UTE) and green technology innovation (GTI) using panel data estimation methods and further explore the related heterogeneity and its impact on sustainable development. The results show that: (1) UTE has a significant positive impact on the GTI of enterprises, and the robustness test verifies these findings. Different kinds of UTE have different effects on enterprise GTI. UTE also has a positive impact on the independent GTI of enterprises. (2) Compared with non-state-owned enterprises, the GTI of state-owned enterprises is more vulnerable to the positive impact of UTE. (3) UTE significantly and negatively impacts enterprises’ business activities and further challenges enterprises’ sustainable development. However, the enterprise’s GTI behavior, especially the substantial GTI, helps mitigate the adverse impact of UTE on the company’s sustainable development. Finally, this paper provides targeted suggestions for enterprises to better cope with UTE and improve their sustainable development capabilities.