Nitrate (NO₃⁻) has been the dominant and the least reduced chemical component of fine particulate matter (PM_2.5) since the stringent emission controls implemented in China in 2013. The formation pathways of NO₃⁻ vary seasonally and differ substantially in daytime vs. nighttime. They are affected by precursor emissions, atmospheric oxidation capacity, and meteorological conditions. Understanding NO₃⁻ formation pathways provides insights for the design of effective emission control strategies to mitigate NO₃⁻ pollution. In this study, the Community Multiscale Air Quality (CMAQ) model was applied to investigate the impact of regional transport, predominant physical processes, and different formation pathways to NO₃⁻ and total nitrate (TNO₃, i.e., HNO₃+ NO₃⁻) production in the Yangtze River Delta (YRD) region during the four seasons of 2017. NO${}_{\mathrm{3}}{}^{-}/$ PM_2.5 and NO${}_{\mathrm{3}}{}^{-}/$ TNO₃ are the highest in the winter, reaching 21 % and 94 %, respectively. The adjusted gas ratio (adjGR = ([NH₃]+ [NO₃⁻]$)/$ ([HNO₃]+ [NO₃⁻])) in the YRD is generally greater than 2 in the four seasons across most areas in the YRD, indicating that YRD is mostly in the NH₃-rich regime and that NO₃⁻ is limited by HNO₃ formation. Local emissions and regional transportation contribute to NO₃⁻ concentrations throughout the YRD region by 50 %–62 % and 38 %–50 %, respectively. The majority of the regional transport of NO₃⁻ concentrations is contributed by indirect transport (i.e., NO₃⁻ formed by transported precursors reacting with local precursors). Aerosol (AERO, including condensation, coagulation, new particle formation, and aerosol growth) processes are the dominant source of NO₃⁻ formation. In summer, NO₃⁻ formation is dominated by AERO and total transport (TRAN, sum of horizontal and vertical transport) processes. The OH + NO₂ pathway contributes to 60 %–83 % of the TNO₃ production, and the N₂O₅ heterogeneous (HET N₂O₅) pathway contributes to 10 %–36 % in the YRD region. HET N₂O₅ contribution becomes more important in cold seasons than warm seasons. Within the planetary boundary layer in Shanghai, the TNO₃ production is dominated by the OH + NO₂ pathway during the day (98 %) in the summer and spring and by the HET N₂O₅ pathway during the night (61 %) in the winter. Local contributions dominate the OH + NO₂ pathway for TNO₃ production during the day, while indirect transport dominates the HET N₂O₅ pathway at night.

Low-Cost Sensors (LCS) of fine particulate matter (PM_2.5) have been widely used to supplement regular air quality monitoring stations. However, the sensor output is impacted by environmental factors, especially relative humidity, and must be calibrated to yield estimates of concentrations. In this study, we evaluate the performance of a linear model and a generalized additive model (GAM) to calibrate the output of LCS PM_2.5 measurements in terms of different relative humidity levels. The method is based on co-located measurements from an LCS and a conventional reference monitor at two sites in an urban area in northern China. A stepwise variable selection of air pollutant concentrations and meteorological observations is used to select inputs to the model in order to improve the calibration ability. The results show that when relative humidity is below 75%, linear calibration of LCS PM_2.5 observations can output PM_2.5 mass concentrations close to the reference method with a correlation coefficient (R²) of 0.86. When relative humidity is above 75%, the GAM calibration model significantly outperforms the linear model, with an R² of approximately 0.83. Overall, the linear model exhibits good fitness in dry conditions, while the GAM captures PM_2.5 variations best in humid conditions. We conclude that low-cost PM_2.5 sensors are sensitive to relative humidity and that therefore condition-specific calibration methods need to be used to improve the quality of the data as well as to improve the match with reference measurements. Copyright © 2021 American Association for Aerosol Research