To control power plant emissions, an accurate emission inventory of high spatiotemporal resolutions is needed for analyzing plant pollutions and formulating specific policies accordingly. However, existing datasets relied on average emission factors, due to lacking actual measurements. The used emission factors are not the results of measurements, but rather proxied using broad technology classes. Assumptions and sensitive parameters are made when compiling the emission factors, therefore high uncertainties do exist. To overcome this issue, we for the first time gathered real monitoring data from the newly built CEMS network (i.e., nationwide, unit-level, real-time stack concentrations of PM, SO2, and NOX from Chinese power plants for 2014-2017) and then developed a new Chinese power emission dataset.
The construction of the CEAP dataset has been a long journey, taking more than three years to complete. In particular, we made great effort in the pre-processing of CEMS data, carefully reviewing each observation via a data visualization, analyzing missing, null, and invalid values to find the hidden reasons and treating them according to relevant rules. Furthermore, we have conducted a set of uncertainty analyses and verified the robustness and reliability of our estimates.
The CEAP dataset, which is publicly and freely available through a dedicated figshare repository (https://doi.org/10.6084/m9.figshare.c.4813653.v3), provides nationwide, plant-level, and dynamic PM, SO2, and NOX emissions from China’s power plant for 2014-2017. In addition, the CEAP dataset encompasses rich information regarding fuel use, operating capacity, geographic distribution, etc. for each power plant. Please see Tang et al. (2020), Air pollution emissions from Chinese power plants based on the continuous emission monitoring systems network. Scientific Data, 7: 325.
The CEAP dataset can be used to evaluate the mitigation effect of recent clean air policies on power emissions. For example, using the CEAP dataset, we have conducted an ex post analysis on the efficacy of the ultra-low emissions (ULE) standard policy, which had ambitious levels (surpassing those of all other countries), finding early compliance of Chinese coal-fired power plants. We further detailed the technologies and mechanisms used to meet the ULE standards and the determinants of compliance, providing insights into future policy making. Please see Tang et al. (2019), Substantial emission reductions from Chinese power plants after the introduction of ultra-low emissions standards. Nature Energy, 4: 929-938.
Furthermore, the CEAP database can be used to investigate air quality improvements and the associated health benefits in China over the past years and to improve the modelling accuracy by offering nationwide, unit-based and high-frequency power emission inventories. In addition, the CEMS-based estimation method can be also extended to other countries seeking to understand and reduce their power emissions. In fact, the Chinese CEMS network covers both air and water pollutants from different industrial sectors, with air pollutants from the power sector just as one small part. We plan to extend the CEAP database and produce a multisector dataset in the near future. Such a dataset can be used to identify the top pollution sources in China and to design corresponding policies for addressing the severe environmental pollution.
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