Impact of urban space on PM2.5 distribution: A multiscale and seasonal study in the Yangtze River Delta urban agglomeration.

Despite concerted efforts in emission control, air pollution control remains challenging. Urban planning has emerged as a crucial strategy for mitigating PM2.5 pollution. What remains unclear is the impact of urban form and their interactions with seasonal changes. In this study, base on the air quality monitoring stations in the Yangtze River Delta urban agglomeration, the relationship between urban spatial indicators (building morphology and land use) and PM2.5 concentrations was investigated using full subset regression and variance partitioning analysis, and seasonal differences were further analysed. Our findings reveal that PM2.5 pollution exhibits different sensitivities to spatial scales, with higher sensitivity to the local microclimate formed by the three-dimensional structure of buildings at the local scale, while land use exerts greater influence at larger scales. Specifically, land use indicators contributed sustantially more to the PM2.5 prediction model as buffer zone expand (from an average of 2.41% at 100 m range to 47.30% at 5000 m range), whereas building morphology indicators display an inverse trend (from an average of 13.84% at 100 m range to 1.88% at 5000 m range). These results enderscore the importance of considering building morphology in local-scale urban planning, where the increasing building height can significantly enhance the disperion of PM2.5 pollution. Conversely, large-scale urban planning should prioritize the mixed use of green spaces and construction lands to mitigate PM2.5 pollution. Moreover, the significant seasonal differences in the ralationship between urban spatical indicatiors and PM2.5 pollution were observed. Particularly moteworthy is the heightened association between forest, water indicators and PM2.5 concentrations in summer, indicating the urban forests may facilitate the formation of volatile compunds, exacerbating the PM2.5 pollution. Our study provides a theoretical basis for addressing scale-related challenges in urban spatial planning, thereby forstering the sustainable development of cities.

Seasonal to sub-seasonal variations of the Asian Tropopause Aerosols Layer affected by the deep convection, surface pollutants and precipitation.

The Asian Tropopause Aerosols Layer (ATAL) refers to an accumulation of aerosols in the upper troposphere and lower stratosphere during boreal summer over Asia, which has a fundamental impact on the monsoon system and climate change. In this study, we primarily analyze the seasonal to sub-seasonal variations of the ATAL and the factors potentially influencing those variations based on MERRA2 reanalysis. The ability of the reanalysis to reproduce the ATAL is well validated by CALIPSO observations from May to October 2016. The results reveal that the ATAL has a synchronous spatiotemporal pattern with the development and movement of the Asian Summer Monsoon. Significant enhancement of ATAL intensity is found during the prevailing monsoon period of July-August, with two maxima centered over South Asia and the Arabian Peninsula. Owing to the fluctuations of deep convection, the ATAL shows an episodic variation on a timescale of 7-12 days. Attribution analysis indicates that deep convection dominates the variability of the ATAL with a contribution of 62.7%, followed by a contribution of 36.6% from surface pollutants. The impact of precipitation is limited. The ATAL further shows a clear diurnal variation: the peak of ATAL intensity occurs from 17:30 to 23:30 local time (LT), when the deep convection becomes strongest; the minimum ATAL intensity occurs around 8:30 LT owing to the weakened deep convection and photochemical reactions in clouds. The aerosol components of the ATAL show different spatiotemporal patterns and imply that black carbon and organic carbon come mainly from India, whereas sulfate comes mainly from China during the prevailing monsoon period.

Molecular Characterization of Water-Soluble Brown Carbon Chromophores in Snowpack from Northern Xinjiang, China.

This study reports molecular-level characterization of brown carbon (BrC) attributed to water-soluble organic carbon in six snowpack samples collected from northern Xinjiang, China. The molecular composition and light-absorbing properties of BrC chromophores were unraveled by application of high-performance liquid chromatography (HPLC) coupled to a photodiode array (PDA) detector and high-resolution mass spectrometry. The chromophores were classified into five major types, that is, (1) phenolic/lignin-derivedcompounds, (2) flavonoids, (3) nitroaromatics, (4) oxygenated aromatics, and (5) other chromophores. Identified chromophores account for ∼23-64% of the total light absorption measured by the PDA detector in the wavelength range of 300-370 nm. In the representative samples from urban and remote areas, oxygenated aromatics and nitroaromatics dominate the absorption in the wavelengths below and above 320 nm, respectively. The highly polluted urban sample shows the most complex HPLC-PDA chromatogram, and more other chromophores contribute to the bulk absorption. Phenolic/lignin-derived compounds are the most light-absorbing species in the soil-influenced sample. Chromophores in two remote samples exhibit ultraviolet-visible features distinct from other samples, which are attributed to flavonoids. Identification of individual chromophores and quantitative analysis of their optical properties are helpful for elucidating the roles of BrC in snow radiative balance and photochemistry.

Snow albedo reductions induced by the internal/external mixing of black carbon and mineral dust, and different snow grain shapes across northern China.

Previous studies have indicated that black carbon (BC) potentially induces snow albedo reductions across northern China. However, the effects of other light-absorbing particles (LAPs, e.g., mineral dust, MD), snow grain shape, or BC-snow mixing state on snow albedo have been largely ignored. Here we evaluate the BC- and MD-induced snow albedo reductions and radiative forcings (RFs) using an updated Snow, Ice, and Aerosol Radiation radiative transfer model, considering all of the potential factors that can be derived from the field observations across northern China. The results highlight that the LAP-induced albedo reductions for nonspherical snow grains are 2%-30% less than those for spherical grains. Furthermore, BC-snow internal mixing can significantly enhance albedo reduction by a factor of 1.42-1.48 relative to external mixing, with snow grain radius ranging from 100 to 1000 µm. The mean regional BC + MD-induced snow albedo reductions are amplified by the increase of snow grain radius, ranging from 0.012 to 0.123 for fresh snow to 0.016-0.227 for old snow. Finally, we discuss the relative contributions of BC and MD to the albedo reductions and RFs, highlighting the dominant role of BC in reducing snow albedo across northern China.