Understanding temporal and spatial changes of O3 or NO2 concentrations combining multivariate data analysis methods and air quality transport models

Observations of HONO and its precursors between urban and its surrounding agricultural fields: The vertical transports, sources and contribution to OH

The insufficient study on vertical observations of main atmospheric reactive nitrogen oxides (NO2 and HONO) posed a great challenge to evaluate their intertransport between urban and agricultural areas, and to further learn the atmospheric nitrogen chemistry and the atmospheric oxidation capacity at high altitudes. A stereoscopic measurement campaign (satellite remote sensing, hyperspectral unmanned aerial vehicle (UAV) remote sensing and MAX-DOAS observation) was performed in a typical inland city Hefei and its surrounding agricultural fields from June to October 2022. Average aerosol vertical profiles exhibited a Gaussian shape above 100 m with maximum values of 0.67 km-1 and 0.55 km-1 at 300-400 m layer at Anhui University (AHU) and Changfeng (CF), respectively. The distinct layered structure was mainly attributed to regional transport. Average H2O and NO2 vertical profiles all showed a Gaussian shape and an exponential shape at AHU and CF, respectively. Moreover, the diurnal evolution of H2O profiles performed one peak and bi-peak patterns at AHU and CF, respectively, whereas the diurnal evolution of NO2 at two stations all exhibited bi-peak patterns attributed to vehicle emissions. Average HONO vertical profiles showed an exponential shape and a Gaussian shape at AHU and CF, respectively. Higher HONO (> 0.05 ppb) above 1.0 km at 14:00-16:00 was observed at CF. The transport flux analysis showed that the northern transport flux always larger than southern transport flux for aerosol and H2O. The maximum northern transport fluxes appeared at 300 m and surface for aerosol and H2O, respectively. It indicated that surrounding agricultural fields was an important source of atmospheric H2O of city. The southern transport flux was larger than northern transport flux for NO2, with a maximum net transport flux of 9.20 ppb m s-1 at 100 m. It demonstrated that NO2 transported from urban areas was an important source of NO2 in agricultural fields. For HONO, the southern transport flux was larger than northern transport flux under 100 m, whereas it was opposite above 100 m. It indicated that the HONO distributed at high altitudes at agricultural fields had potential to enhance the atmospheric oxidation capacity of urban area. The net horizontal transport fluxes of HONO of our defined cropland were 5.25 μg m-2 s-1 and -3.65 μg m-2 s-1 during non-fertilization and fertilization periods, respectively. It indicated that the cropland could obviously export HONO to surrounding atmosphere during the fertilization period. Deducing the contribution of direct emission, heterogeneous process was a major source of HONO at urban and agricultural areas. The average surface conversion rate of NO2-to-HONO (CHONO) was 0.01467 h-1, and this value decreased with the increase of height at urban station. While average surface CHONO was 0.0322 h-1 at agricultural fields, which was ~1.2-2.8 times higher than that at urban area. The CHONO at agricultural fields significantly increased with the increase of height. The average CHONO at 1.0 km was ~2.0-3.6 times higher than that at surface. That suggested that the heterogeneous process was the main HONO source at high altitudes at CF, and this process obviously correlated with aerosol and H2O. The higher OH production from HONO (P(OH)HONO) occurred at 0-200 m and 100-400 m with averaged values of 0.31 ppb h-1 and 0.39 ppb h-1 at AHU and CF, respectively. The high P(OH)HONO above 1.0 km at CF from September to October was strongly correlated with high O3 (> 80 ppb). This study emphasized the importance of the stereoscopic of HONO on the analysis of its distribution, evolution, source and atmospheric oxidizing contribution.

Regional Differences, Distribution Dynamics, and Convergence of Air Quality in Urban Agglomerations in China

The urban agglomeration (UA), with a high concentration of population and economy, represents an area with grievous air pollution. It is vital to examine the regional differences, distribution dynamics, and air quality convergence in UAs for sustainable development. In this study, we measured the air quality of ten UAs in China through the Air Quality Index (AQI). We analyzed regional differences, distribution dynamics, and convergence using Dagum’s decomposition of the Gini coefficient, kernel density estimation, and the convergence model. We found that: the AQI of China’s UAs shows a downward trend, and the index is higher in northern UAs than in southern UAs; the differences in air quality within UAs are not significant, but there is a gap between them; the overall difference in air quality tends to decrease, and regional differences in air quality are the primary contributor to the overall difference; the overall distribution and the distribution of each UA move rightward; the distribution pattern, ductility, and polarization characteristics are different, indicating that the air quality has improved and is differentiated between UAs; except for the Guanzhong Plain, the overall UA and each UA have obvious σ convergence characteristics, and each UA presents prominent absolute β convergence, conditional β convergence, and club convergence.