Co-benefits of reducing PM_2.5 and improving visibility by COVID-19 lockdown in Wuhan

Atmospheric visibility, a direct indicator of air quality, has significantly deteriorated in China in recent years, negatively impacting traffic and public well-being. Despite substantial reductions in SO₂, NO_x, and PM_2.5 emissions since 2013, improvements in visibility have been less pronounced, particularly in winter. This discrepancy highlights the complex relationship between PM_2.5 concentration and visibility, influenced by aerosol chemical composition, hygroscopic properties, and meteorological conditions. Aerosol light extinction (β_ext), encompassing absorption and scattering, is the primary determinant of visibility. The major contributors to β_ext in Chinese megacities include organic matter, (NH₄)₂SO₄, and NH₄NO₃. High relative humidity (RH) enhances scattering by promoting SNA formation and hygroscopic growth. Previous temporary emission control measures during mega-events have shown varied success in improving visibility, suggesting that regional-scale controls may not always be effective. The COVID-19 lockdown in Wuhan provides a unique opportunity to examine the impact of drastic emission reductions on aerosol optical properties and visibility. This study analyzes online monitoring data from Wuhan, comparing pre-lockdown and lockdown periods, to investigate the impact of emission reductions on PM_2.5 concentration, aerosol optical properties, and visibility, and propose prioritized policies for effective co-regulation of PM_2.5 and visibility.

Numerous studies have documented the decline in visibility in China and its link to air pollution. Research has explored the role of aerosol chemical composition, particularly the contribution of sulfate-nitrate-ammonium (SNA) species and organic matter, in light extinction and visibility reduction. The impact of relative humidity on aerosol hygroscopicity and its influence on scattering efficiency has also been widely studied. Several studies investigated the effectiveness of temporary emission control measures during mega-events, with mixed results regarding visibility improvement. Recent research has explored the impact of the COVID-19 lockdowns on air quality, observing significant reductions in various pollutants, but the impact on aerosol optical properties and visibility remained less studied. This study builds upon this existing literature by focusing on the specific case of Wuhan during the strict lockdown, providing a detailed analysis of the co-benefits of PM_2.5 reduction and visibility improvement.

This study analyzed hourly online monitoring data from Wuhan, China, covering a pre-lockdown period (PLP, December 23, 2019 – January 22, 2020) and a lockdown period (LP, January 23, 2020 – February 22, 2020). The data included PM_2.5 mass concentrations, major chemical components (including water-soluble ions, organic carbon, elemental carbon, and trace elements), aerosol scattering and absorption coefficients (b_sp and b_ap), relative humidity (RH), visibility, and meteorological parameters. The PM_2.5 mass concentrations were measured using an oscillating balance method. Other parameters, such as gaseous components and meteorological parameters, were measured using various instruments. Data cleaning procedures were implemented to exclude data affected by fog, rain, dust, and inconsistencies. The mass scattering efficiency (MSE) and mass absorption efficiency (MAE) of major chemical components were estimated using multiple linear regression (MLR). Optical hygroscopicity (f(RH)) was calculated as the ratio of estimated ambient b_sp to measurements. The thermodynamic model ISORROPIA-II was employed to estimate aerosol water content (AWC) and conduct sensitivity tests. Statistical analyses, including linear and power function regressions, were performed to determine correlations and relationships between various parameters. The data were analyzed to examine the changes in PM2.5 concentrations, aerosol optical properties, and visibility during the lockdown, as well as to identify the key chemical components affecting visibility improvement. Sensitivity tests were used to determine the relative merits of controlling total nitrate (TNO₃) and NH_x emissions.

The COVID-19 lockdown in Wuhan resulted in a substantial reduction in PM_2.5 concentration (37.8%) and a remarkable increase in visibility (106.7%). The decrease in PM_2.5 was primarily driven by a significant reduction in NH₄NO₃ (24.8 µg m⁻³), accounting for 63.6% of the total PM_2.5 mass reduction. Both aerosol scattering (b_sp) and absorption (b_ap) coefficients decreased significantly during the lockdown. The PM_2.5 thresholds corresponding to a visibility of 10 km (PTV₁₀) varied from 54 to 175 µg m⁻³, decreasing with increasing RH. The lockdown elevated PTV₁₀ by 9–58 µg m⁻³, indicating that the improvement in visibility went beyond what could be solely attributed to the reduction in PM_2.5 and RH. This was partly due to the decrease in mass scattering efficiency (MSE) and optical hygroscopicity (f(RH)) of PM_2.5. NH₄NO₃ was identified as the most significant contributor to aerosol extinction, with its reduction during the lockdown resulting in a 30% decrease in its contribution to b_ext. The reduction in NH₄NO₃ also weakened its mutual promotion with aerosol water, leading to a decrease in aerosol water content (AWC) and further visibility improvement. Sensitivity analyses using the ISORROPIA-II model indicated that controlling TNO₃ was more effective in reducing PM_2.5 and improving visibility than NH_x control, unless NH_x reduction exceeded specific thresholds (11.7–17.5 µg m⁻³). Simulations suggested that a 51% reduction in TNO₃ or a 59% reduction in NH₃ could achieve PM_2.5 concentrations below 54 µg m⁻³, ensuring visibility above 10 km. Simultaneous reductions of NH₃ and TNO₃ did not significantly alter the reduction thresholds needed to achieve the target PM_2.5 concentration.

The findings of this study demonstrate the substantial co-benefits of reducing PM_2.5 and improving visibility through targeted emission controls. The unexpected COVID-19 lockdown provided a unique natural experiment showcasing the significant impact of reduced emissions on both PM_2.5 and visibility. The study highlights the importance of considering not only PM_2.5 mass concentration but also aerosol chemical composition, hygroscopic properties, and their interactions in determining visibility. The superior effectiveness of TNO₃ control over NH_x control in improving visibility, unless significant NH_x reductions are achieved, offers valuable insights for policymaking. The results indicate that reducing NH₄NO₃ is crucial for enhancing visibility improvement efficiency. This can be achieved by effectively controlling both NOx and NH₃ precursors. The study emphasizes the need for a holistic approach that integrates multi-pollutant controls, prioritizing TNO₃ reduction while considering the potential benefits of NH₃ control beyond a certain reduction threshold.

This study demonstrates the significant co-benefits of reducing PM_2.5 and improving visibility through targeted emission controls, particularly focusing on NH₄NO₃ reduction. The COVID-19 lockdown in Wuhan served as a compelling case study highlighting the positive impact of drastic emission reductions. The study's findings suggest that prioritizing TNO₃ reduction, while considering the potential benefits of NH₃ reduction beyond a certain threshold, is crucial for maximizing visibility improvement efficiency. Further research should investigate the long-term impacts of sustained emission control strategies on aerosol properties and visibility, and explore the interactions between different air pollutants and their impact on regional haze.

The study is limited to a specific location (Wuhan) and a specific time period (COVID-19 lockdown). The generalizability of the findings to other regions and seasons requires further investigation. The impact of meteorological factors on visibility is also not explicitly considered and is a limitation for the model. While the model incorporated a high number of parameters, secondary transformations may have been not fully accounted for in the thermodynamic model, limiting the complete precision of its predictions.