Formation mechanism and control strategy for particulate nitrate in China

Role of gas-particle conversion of ammonia in haze pollution under ammonia-rich environment in Northern China and prospects of effective emission reduction

As an important precursor of secondary inorganic aerosols (SIAs), ammonia (NH3) plays a key role in fine particulate matter (PM2.5) formation. In order to investigate its impacts on haze formation in the North China Plain (NCP) during winter, NH3 concentrations were observed at a high-temporal resolution of 1 min by using the SP-DOAS in Tai'an from December 2021 to February 2022. During the observation period, the average NH3 concentration was 11.84 ± 5.9 ppbv, and it was determined as an ammonia-rich environment during different air quality conditions. Furthermore, the average concentrations of sulfate (SO42-), nitrate (NO3-) and ammonium (NH4+) were 9.54 ± 5.97 μg/m3, 19.09 ± 14.18 μg/m3 and 10.72 ± 6.53 μg/m3, respectively. Under the nitrate-dominated atmospheric environment, aerosol liquid water content (ALWC) was crucial for NH3 particle transformation during haze aggravation, and the gas-particle partitioning of ammonia played an important role in the SIAs formation. The reconstruction of the molecular composition further indicated that ammonium nitrate (NH4NO3) plays a dominant role in the increase of PM2.5 during haze events. Consequently, future efforts to mitigate fine particulate pollution in this region should focus on controlling NH4NO3 levels. In ammonia-rich environments, NO3- formation is more dependent on the concentration of nitric acid (HNO3). The sensitive analysis of TNO3 (HNO3 + NO3-) and NHX (NH3 + NH4+) reduction using the thermodynamic model suggested that the NO3- concentration decreases linearly with the reduction of TNO3. And the concentration of NO3- decreases rapidly only when NHX is reduced by 50-60 %. Reducing NOX emissions is the most effective way to alleviate nitrate pollution in this region.

Spatiotemporal changes in fine particulate matter and ozone in the oasis city of Korla, northeastern Tarim Basin of China

Air pollution is a serious environmental health concern for humans and other living organisms. This study analyzes the spatial and temporal characteristics of air pollutant concentrations, changes in the degree of pollution, and the wavelet coherence of the air quality index (AQI) with pollutants in various monitoring stations. The analysis is based on long-term time series data (January 2016 to December 2023) of air pollutants (PM2.5, PM10, and O3) from Korla, an oasis city in the northeastern part of the Tarim Basin, China. The concentrations of PM2.5, PM10, and O3 in Korla showed a cyclical trend from 2016 to 2023; PM10 concentrations exhibited all-season exceedance and PM2.5 exhibited exceedance only in spring. PM2.5 and PM10 showed a seasonal distribution of spring > winter > fall > summer; O3 concentrations showed a seasonal distribution of summer > spring > fall > winter. Strong positive wavelet coherence between PM and Air Quality Index (AQI) data series suggests that the AQI data series can effectively characterize fluctuating trends in PM concentrations. Moreover, PM10 levels IV and VI were maintained at approximately 10%, indicating that sand and dust have a substantial influence on air quality and pose potential threats to the health of urban inhabitants. Based on the results of this study, future efforts must strengthen relative countermeasures for sand prevention and control, select urban greening species with anti-pollution capabilities, rationally expand urban green spaces, and restrict regulations for reducing particulate matter emissions within city areas.

Unveiling global land fine- and coarse-mode aerosol dynamics from 2005 to 2020 using enhanced satellite-based monthly inversion data

Accurate fine-mode and coarse-mode aerosol knowledge is crucial for understanding their impacts on the climate and Earth's ecosystems. However, current satellite-based Fine-Mode Aerosol Optical Depth (FAOD) and Coarse-Mode Aerosol Optical Depth (CAOD) methods have drawbacks including inaccuracies, low spatial coverage, and limited temporal duration. To overcome these issues, we developed new global-scale FAOD and CAOD from 2005 to 2020 using a novel deep learning model capable of the synergistic retrieval of two aerosol sizes. After validation with the aerosol robotic network (AERONET) and sky radiometer network (SKYNET), the new monthly FAOD and CAOD showed significant improvements in accuracy and spatial coverage. From 2005 to 2020, the new data showed that China had the greatest decrease in FAOD and CAOD. In contrast, India and South Latin America had a significant increase in FAOD versus North Africa in CAOD. FAOD in the regions of Argentina, Paraguay, and Uruguay in South America have shown an upward trend. The results reveal that FAOD and CAOD display distinct patterns of change in the same regions, particularly on the west coast of the United States where FAOD is increasing, while CAOD is decreasing. Aside from the year 2020 due to the global COVID-19 pandemic, the analysis showed that although China has seen at least an +85% increase in energy consumption and urban expansion in 2019 compared to 2005 due to the needs of development and construction, the implementation of China's air pollution control policies has led to a significant decrease in FAOD (-46%) and CAOD (-65%) after 2013. This research enriches our comprehension of global fine and coarse aerosol patterns, additional investigations are needed to determine the potential global implications of these changes.

Nitrogen and oxygen isotope characteristics, formation mechanism, and source apportionment of nitrate aerosols in Wuhan, Central China

Understanding the sources and formation mechanisms of nitrate in PM2.5 is important for effective and precise prevention and control of particulate matter pollution. In this study, we detected stable nitrogen and oxygen isotope signatures of NO- 3 (expressed as δ15N-NO- 3 and δ18O-NO3-) in PM2.5 samples in Wuhan, the largest city in central China. The sources and formation pathways of NO3- were quantitatively analyzed using the modified version of the Bayesian isotope mixing (MixSIR) model, and the regional transport characteristics of NO3- were analyzed using the hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) model and concentration-weighted trajectory (CWT) method. The results showed that NO3- significantly contributed to the ambient PM2.5 pollution and its driving effect increased with the gradient of pollution level. The average δ15N-NO3- and δ18O-NO3- values were 4.7 ± 0.9 ‰ and 79.7 ± 2.9 ‰, respectively. δ15N-NO3- and δ18O-NO3- were more enriched in winter and increased dramatically in heavily polluted days. The reaction pathway of NO2 + OH dominated nitrate formation in summer, while the reaction pathway of N2O5+ H2O dominated in other seasons and contributed more in polluted days than clean days. The contributions of vehicle emission, coal combustion, biomass burning, biogenic soil emission, and ship emission sources to NO3- were 26.4 %, 23.4 %, 22.8 %, 15.3 %, and 12.1 %, respectively. In addition to local emissions, air mass transport from the northern China had a significant impact on particulate NO3- in Wuhan. Overall, we should pay special attention to vehicle and ship emissions and winter coal combustion emissions in future policymaking.