Contributions of Traffic and Industrial Emission Reductions to the Air Quality Improvement after the Lockdown of Wuhan and Neighboring Cities Due to COVID-19

Wuhan was locked down from 23 January to 8 April 2020 to prevent the spread of the novel coronavirus disease 2019 (COVID-19). Both public and private transportation in Wuhan and its neighboring cities in Hubei Province were suspended or restricted, and the manufacturing industry was partially shut down. This study collected and investigated ground monitoring data to prove that the lockdowns of the cities had significant influences on the air quality in Wuhan. The WRF-CMAQ (Weather Research and Forecasting-Community Multiscale Air Quality) model was used to evaluate the emission reduction from transportation and industry sectors and associated air quality impact. The results indicate that the reduction in traffic emission was nearly 100% immediately after the lockdown between 23 January and 8 February and that the industrial emission tended to decrease by about 50% during the same period. The industrial emission further deceased after 9 February. Emission reduction from transportation and that from industry was not simultaneous. The results imply that the shutdown of industry contributed significantly more to the pollutant reduction than the restricted transportation.

China pollutant discharge permits as a link between total emission control and water quality: a pilot study of the pesticide industry

The deficiency of China's current pollution discharge permit system lies in the failure to improve the water quality effectively. This paper discusses the premise that the water quality of a water environmental functional zone (WEFZ) is mostly affected by industrial pollution sources. By reviewing the related policy, we noted the link between total emission control, effluent limitations and pollutant discharge permits to configure a practical framework for pollutant discharge permits based on water quality. China's pollutant discharge permit system provides an administrative foundation for reducing polluters' total emissions at the scale of the WEFZ, and it is best implemented through the imposition of limitations on polluters to identify the related treatment technology levels. Owing to the importance of limitations, the methodology of limitation classification and the related treatment technology classification are presented for the pesticide industry. Additionally, a comprehensive analysis of the pollutant reduction potential for the pesticide industry is conducted to determine the current level of sewage treatment. More importantly, this study offers an innovative way to investigate pollutant reduction potential and provides an example that may be useful to other key industries.

Modeling and Optimization of Integrated Energy System for Renewable Power Penetration considering Carbon and Pollutant Reduction Systems

To address climate change and environmental pollution, an increasing number of renewable energy source generations are connected to the grid; meanwhile, the need for carbon capture and pollutant reduction for traditional energy has increased in urgency. In this study, the dispatch problem for an integrated energy system (IES) is expanded considering renewable penetration, carbon capture, and pollutant reduction. First of all, detailed models of carbon and pollutants reductions systems are set up. Specifically, the carbon capture system’s characteristics, which contribute more flexibility for the conventional power plants, are clarified. In addition, the treatment process of pollutants containing SO2 and NOx is elaborated. Moreover, the structure of an evolutionary IES containing pollutants treatment, battery and thermal energy storage, and carbon capture and storage systems are put forward. On this basis, the model of IES for renewable energy penetration and environmental protection considering the constraint of pollutant ultra-low emissions is set up. Finally, the simulation results show that the proposed approach can improve renewable energy penetration and restrain carbon and pollutants emissions.

Insights into the Pollutant Removal Performance of Stormwater Green Infrastructures: A Case Study of Detention Basins and Retention Ponds

The quality of water has deteriorated due to urbanization and the occurrence of urban stormwater runoff. To solve this problem, this study investigated the pollutant reduction effects from the geometric and hydrological factors of green infrastructures (GIs) to more accurately design GI models, and evaluated the factors that are required for such a design. Among several GIs, detention basins and retention ponds were evaluated. This study chose the inflow, outflow, total suspended solids (TSS), total phosphorus (TP), watershed area, GI area (bottom area in detention basins and permanent pool surface area in retention ponds), and GI volume (in both detention basins and retention ponds) for analysis and applied both ordinary least squares (OLS) regression and multiple linear regression (MLR). The geometric factors do not vary within each GI, but there may be a bias due to the number of stormwater events. To solve this problem, three methods that involved randomly extracting data with a certain range and excluding outliers were applied to the models. The accuracies of these OLS and MLR models were analyzed through the percentage bias (PBIAS), Nash-Sutcliffe efficiency (NSE), and RMSE-observations standard deviation ratio (RSR). The results of this study suggest that models which consider the influent concentration combined with the hydrological and GI geometric parameters have better correlations than models that consider only a single parameter.

Modeling for Mitigating Storm Water Unban Flooding and Water Quality Issues by Using Small Serial Dams: A Case Study of the City of San Angelo

<p>The City of San Angelo has been imposed on urban flooding and no-point source pollution and develop storm water monitoring and modeling project for managing these storm water issues. This study focuses on the stormwater peak flow reduction and water pollutant improvement by using small serial retention structures. The storm water data collected are utilized to verify storm water and event mean concentration in SWMM model. The verified SWMM that has range from 0.6 to 0.8 of coefficient of determination is modeled to evaluate small serial dams for reducing peak flow and water quality loading. Small serial dams explain the 26%~55.3% peak flow reduction and 53.2%~93.7% water pollutant removal percent. Sensitivity analysis results for three kinds of orifice sizes provide that smaller size increases the hydraulic retention and reduces the peak flow than other bigger size while the bigger size shows effective water pollutant reduction than small size.</p>