Abstract
With the enforcement of emissions standards and fuel-economy standards in Mainland China, it is both important and interesting to see how these recent emissions reduction strategies affected the spatiotemporal patterns of emissions over the period 2011–2015, which have rarely been examined in previous studies. This study aimed to fill this gap by estimating and analyzing vehicle emissions patterns to support the development of emissions reduction strategies. We established emissions inventories for Mainland China and individual provinces using statistical data from official yearbooks. The aggregated results showed that emissions of greenhouse gas increased slowly and emissions of pollutants decreased sharply. The individual results showed that there was an imbalance in the distribution of emissions, with high total emissions and emissions per inhabitant in developed provinces and high emissions per unit GDP in developing provinces. Specifically, light passenger cars and heavy-duty trucks contributed more than 50% of emissions, and their emissions were statistically spatially auto-correlated, which might hint that there were inherent spatial clustering patterns among emissions. Thereafter, a self-organizing map was used to cluster individual provinces, and indicated that a few provinces can be clustered together according to the similarity of their emissions patterns. Finally, we found that the influences of socioeconomic factors on emissions varied across space, where emissions in northeastern provinces were more likely to be affected by population and those in southwestern provinces tended to be influenced by GDP. These findings are believed to be useful for the development of emissions reduction strategies for sustainable development.
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