Heating is a key procedure in producing sesame paste. The effects of microwave heating and conventional roasting on the physicochemical features, protein profiles, and volatile compounds of black sesame pastes made of black sesame seeds from Burma and China were evaluated in this study. All heating treatments decreased the moisture contents of black sesame pastes, and roasting yielded lower moisture levels, although with similar chroma (p < 0.05). The samples subjected to microwave heating had remarkably lower peroxide values than those heated with roasting (p < 0.05). Chinese microwave-heated samples had a higher nitrogen solubility index than roasting (p < 0.05). Both microwave and roasting increased the contents of the volatiles notably. SDS-PAGE showed that the intensity of the 2-15 kDa band decreased markedly after heating and nearly diminished for roasting samples, suggesting that roasting was more remarkable for the promotion to the protein aggregation. The results indicated that the quality traits of black sesame paste not only depend on the heating methods, but also the heating power/temperature and duration, and the source of the materials.
Nitrogen oxides (NOx ≡ NO + NO2) play a central role in air pollution. Super-emitters present unique opportunities for emission mitigation in China and beyond. They comprise intensive industrial facilities (e.g., power or chemical plants), less than 1 × 1 km2 with high NOx plumes, dominating localized concentrations within a limited geographical scope. However, identification of super-emitters typically challenges emission mitigation due to insufficient spatiotemporal resolution. Here we map NOx emissions using an efficient, super-resolution (1 × 1 km2) inverse model based on whole-year TROPOMI satellite observations. Our map offers unique insights on nationwide NOx super-emitters. We resolve 1625 super-emitters in virtually every corner in China, even in remote and mountainous zones, which we trace back to either an industrial hotspot or a cluster (i.e., an industrial park). A state-of-the-art bottom-up emission inventory MEICv1.3 largely (67%) agrees with our results within a factor of two for cities. However, that inventory does not identify these super-emitters, particularly underestimating one-third of the emissions by at least an order of magnitude. Even, nearly up to three-quarter super-emitters are found to be displaced or missing. Moreover, traditional top-down inverse methods do not effectively detect such super-emitters. Here we show it is necessary to address the NOx budget by revisiting super-emitters on a large scale. Integrating the results we obtain here with a multi-tiered observation system can lead to identification and mitigation of anomalous NOx emissions.
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