In 2014, China introduced an ultra-low emissions (ULE) standards policy for renovating coal-fired power-generating units to limit SO2, NOX and PM emissions to 35, 50 and 10 mg m-3 , respectively. The ULE standard policy had ambitious levels (surpassing those of all other countries) and implementation timeline. We estimate emission reductions associated with the ULE policy by constructing a nationwide, unit-level, hourly-frequency emissions dataset using data from a continuous emission monitoring systems network covering 96-98% of Chinese thermal power capacity during 2014-2017. We find that between 2014 and 2017 China's annual power emissions of SO2, NOX and PM dropped by 65%, 60% and 72%, respectively. Our estimated emissions using actual monitoring data are 18-92% below other recent estimates. We detail the technologies used to meet the ULE standards and the determinants of compliance, underscoring the importance of ex-post evaluation and providing insights for other countries wishing to reduce their power emissions.

Surface water quality models can be useful tools to simulate and predict the levels, distributions, and risks of chemical pollutants in a given water body. The modeling results from these models under different pollution scenarios are very important components of environmental impact assessment and can provide a basis and technique support for environmental management agencies to make right decisions. Whether the model results are right or not can impact the reasonability and scientificity of the authorized construct projects and the availability of pollution control measures. We reviewed the development of surface water quality models at three stages and analyzed the suitability, precisions, and methods among different models. Standardization of water quality models can help environmental management agencies guarantee the consistency in application of water quality models for regulatory purposes. We concluded the status of standardization of these models in developed countries and put forward available measures for the standardization of these surface water quality models, especially in developing countries.

To meet the growing electricity demand, China’s power generation sector has become an increasingly large source of air pollutants. Specific control policymaking needs an inventory reflecting the overall, heterogeneous, time-varying features of power plant emissions. Due to the lack of comprehensive real measurements, existing inventories rely on average emission factors that suffer from many assumptions and high uncertainty. This study is the first to develop an inventory of particulate matter (PM), SO2 and NOX emissions from power plants using systematic actual measurements monitored by China’s continuous emission monitoring systems (CEMS) network over 96–98% of the total thermal power capacity. With nationwide, source-level, real-time CEMS-monitored data, this study directly estimates emission factors and absolute emissions, avoiding the use of indirect average emission factors, thereby reducing the level of uncertainty. This dataset provides plant-level information on absolute emissions, fuel uses, generating capacities, geographic locations, etc. The dataset facilitates power emission characterization and clean air policy-making, and the CEMS-based estimation method can be employed by other countries seeking to regulate their power emissions.

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