Increasing Nonfossil Fuel Contributions to Atmospheric Nitrate in Urban China from Observation to Prediction.

China's nitrogen oxide (NO) emissions have undergone significant changes over the past few decades. However, nonfossil fuel NO emissions are not yet well constrained in urban environments, resulting in a substantial underestimation of their importance relative to the known fossil fuel NO emissions. We developed an approach using machine learning that is accurate enough to generate a long time series of the nitrogen isotopic composition (δN) of atmospheric nitrate using high-level accuracies of air pollutants and meteorology data. Air temperature was found to be the critical driver of the variation of nitrate δN at daily resolution based on this approach, while significant reductions of aerosol and its precursor emissions played a key role in the change of nitrate δN on the yearly scale. Predictions from this model found a significant decrease in nitrate δN in Chinese megacities (Beijing and Guangzhou as representative cities in the north and south, respectively) since 2013, implying an enhanced contribution of nonfossil fuel NO emissions to nitrate aerosols (up to 22%-26% in 2021 from 18%-22% in 2013 quantified by an isotope mixing model), as confirmed by the Weather Research and Forecasting model coupled with online chemistry (WRF-Chem) simulation. Meanwhile, the declining contribution in coal combustion (34%-39% in 2013 to 31%-34% in 2021) and increasing contribution of natural gas combustion (11%-14% in 2013 to 14%-17% in 2021) demonstrated the transformation of China's energy structure from coal to natural gas. This approach provides missing records for exploring long-term variability in the nitrogen isotope system and may contribute to the study of the global reactive nitrogen biogeochemical cycle.