Revisiting the dynamics of gaseous ammonia and ammonium aerosols during the COVID-19 lockdown in urban Beijing using machine learning models.

The concentration of atmospheric ammonia (NH3) in urban Beijing substantially decreased during the COVID-19 lockdown (24 January to 3 March 2020), likely due to the reduced human activities. However, quantifying the impact of anthropogenic interventions on NH3 dynamics is challenging, as both meteorology and chemistry mask the real changes in observed NH3 concentrations. Here, we applied machine learning techniques based on random forest models to decouple the impacts of meteorology and emission changes on the gaseous NH3 and ammonium aerosol (NH4+) concentrations in Beijing during the lockdown. Our results showed that the meteorological conditions were unfavorable during the lockdown and tended to cause an increase of 8.4 % in the NH3 concentration. In addition, significant reductions in NOx and SO2 emissions could also elevate NH3 concentrations by favoring NH3 gas-phase partitioning. However, the observed NH3 concentration significantly decreased by 35.9 % during the lockdown, indicating a significant reduction in emissions or enhanced chemical sinks. Rapid gas-to-particle conversion was indeed found during the lockdown. Thus, the observed reduced NH3 concentrations could be partially explained by the enhanced transformation into NH4+. Therefore, the sum of NH3 and NH4+ (collectively, NHx) is a more reliable tracer than NH3 or NH4+ alone to estimate the changes in NH3 emissions. Compared to that under the scenario without lockdowns, the NHx concentration decreased by 26.4 %. We considered that this decrease represents the real decrease in NH3 emissions in Beijing due to the lockdown measures, which was less of a decrease than that based on NH3 only (35.9 %). This study highlights the importance of considering chemical sinks in the atmosphere when applying machine learning techniques to link the concentrations of reactive species with their emissions.

Substantial nitrogen oxides emission reduction from China due to COVID-19 and its impact on surface ozone and aerosol pollution.

A top-down approach was employed to estimate the influence of lockdown measures implemented during the COVID-19 pandemic on NOx emissions and subsequent influence on surface PM2.5 and ozone in China. The nation-wide NOx emission reduction of 53.4% due to the lockdown in 2020 quarter one in China may represent the current upper limit of China's NOx emission control. During the Chinese New Year Holiday (P2), NOx emission intensity in China declined by 44.7% compared to the preceding 3 weeks (P1). NOx emission intensity increased by 20.3% during the 4 weeks after P2 (P3), despite the unchanged NO2 column. It recovered to 2019 level at the end of March (P4). The East China (22°N - 42°N, 102°E - 122°E) received greater influence from COVID-19. Overall NOx emission from East China for 2020 first quarter is 40.5% lower than 2019, and in P4 it is still 22.9% below the same period in 2019. The 40.5% decrease of NOx emission in 2020 first quarter in East China lead to 36.5% increase of surface O3 and 12.5% decrease of surface PM2.5. The elevated O3 promotes the secondary aerosol formation through heterogeneous pathways. We recommend that the complicated interaction between PM2.5 and O3 should be considered in the emission control strategy making process in the future.

[Source Apportionment of Atmospheric Ammonia: Sensitivity Test Based on Stable Isotope Analysis in R Language].

Ammonia (NH3) is an important precursor of fine particles and nitrogen deposition. It is critical to identify and quantify the sources of NH3 before the implementation of a mitigation strategy. Stable isotope analysis in R (SIAR) has potential with regard to the source apportionment of NH3, but its reliability is closely related to the signatures (δ15N-NH3) of emission sources. Based on SIAR, we found that the agricultural contribution varied significantly with mean δ15N-NH3 values of endmember input. In contrast, both the contributions of fossil fuel and NH3 slip showed low sensitivity against the change of endmember input. Moreover, the agricultural contribution changed by about 20% due to the variations in agricultural endmember mean values. Such a change is five times that due to the variations in endmember standard deviation values. Notably, regardless of the number of input sources tested, "non-agricultural source" was the dominant source of NH3 during hazy days in January 2013 in Beijing. Since various agricultural sources showed large variations in δ15N-NH3, future studies should focus on the endmember signatures of agricultural sources to further reduce the uncertainty in SIAR-based NH3 source apportionment.

[Concurrent Measurement of Wet and Bulk Deposition of Trace Metals in Urban Beijing].

To characterize the dry and wet deposition of atmospheric trace elements in urban Beijing, both active and passive samplers were used to collect bulk and wet sedimentation samples between May 2014 and April 2015.The concentrations of 19 trace elements (Na, Mg, Al, K, Ca, V, Cr, Mn, Fe, Cu, Zn, As, Se, Mo, Cd, Sb, Tl, Th, and U) in the samples were analyzed by inductively coupled plasma mass spectrometry (ICP-MS). The results show that the concentrations of metals in bulk deposition samples[7160.68 µg·L-1 (Ca)-0.02 µg·L-1 (Th)] were generally higher than those in wet deposition samples[4237.74 µg·L-1 (Ca)-0.01 µg·L-1 (Th)], but the enrichment factors of each metal in the two kinds of samples were less different. Of note, the enrichment factors of Cu, As, Tl, Zn, Cd, Se, and Sb were all larger than 100, thus indicating that these heavy metals were mainly from anthropogenic sources. The statistical analysis of the air mass trajectory shows that the precipitation chemistry in urban Beijing is mainly affected by southward air flows. The air mass originating from the southwest region always had higher concentrations of Ca, Mg, Fe, Al, Cu, Mo, U, and Th, whereas the air mass from the south had higher concentrations of K, Zn, Mn, Sb, Cd, and Tl. During the observation period, the bulk deposition fluxes of metals varied from 3591.35 mg·(m2·a)-1 (Ca)-0.01 mg·(m2·a)-1 (Th), and wet deposition fluxes varied from 1847.78 mg·(m2·a)-1 (Ca)-0.01 mg·(m2·a)-1 (Th). The dry deposition fluxes of the 19 metals varied from 1743.57 mg·(m2·a)-1 (Ca)-0.01 mg·(m2·a)-1 (Th). The particle size has important implications in the evaluation of the relative importance of dry deposition versus wet deposition during the scavenging of trace elements in air.

Improved Inversion of Monthly Ammonia Emissions in China Based on the Chinese Ammonia Monitoring Network and Ensemble Kalman Filter.

Ammonia (NH3) emission inventories are an essential input in chemical transport models and are helpful for policy-makers to refine mitigation strategies. However, current estimates of Chinese NH3 emissions still have large uncertainties. In this study, an improved inversion estimation of NH3 emissions in China has been made using an ensemble Kalman filter and the Nested Air Quality Prediction Modeling System. By first assimilating the surface NH3 observations from the Ammonia Monitoring Network in China at a high resolution of 15 km, our inversion results have provided new insights into the spatial and temporal patterns of Chinese NH3 emissions. More enhanced NH3 emission hotspots, likely associated with industrial or agricultural sources, were captured in northwest China, where the a posteriori NH3 emissions were more than twice the a priori emissions. Monthly variations of NH3 emissions were optimized in different regions of China and exhibited a more distinct seasonality, with the emissions in summer being twice those in winter. The inversion results were well-validated by several independent datasets that traced gaseous NH3 and related atmospheric processes. These findings highlighted that the improved inversion estimation can be used to advance our understanding of NH3 emissions in China and their environmental impacts.