Assessment of submicron aerosol liquid water content and mass-based growth factors in South Asian outflow over the Indian Ocean

Aerosol-bound water, a ubiquitous and abundant component of atmospheric aerosols, has an impact on regional climate, visibility, human health, the hydrological cycle, and atmospheric chemistry. Yet, the intricate relationship between aerosol liquid water (ALWC) and chemical composition and relative humidity (RH) was not well understood. The present study explores ALWC derived from the ISORROPIA II model using real-time, high-resolution data of non-refractory submicron chemical species and meteorological parameters (temperature and RH) collected over the Indian Ocean as part of the ICARB (Integrated Campaign for Aerosols, Gases, and Radiation Budget)-2018 experiment. Results show that ALWC values over the South Eastern Arabian Sea (SEAS) were found to be higher by 4-6 times than those observed over the Equatorial Indian Ocean (EIO) due to a large decrease in aerosol loading from SEAS to EIO. ALWC peaked in the early morning hours (4:00-7:00), with greater values during the nighttime and lower values during the daytime across SEAS, which is comparable with RH variation. While the ratio of organics-to-SO42- mass fraction linearly decreased with increasing mass-based growth factors (MGFs) over EIO, such a scenario was not observed over SEAS. The latitudinal gradient of mass fraction of ALWC had shown a decrease towards EIO, consistent with organic fraction. The extinction coefficient of the dry mass of submicron particles is noticeably increased by 40 % by ALWC over SEAS and EIO. Moreover, ALWC could enhance the aerosol negative forcing by an average of 66 % (64 %) over SEAS (EIO) at the top of the atmosphere during the cruise period. These inferences imply that ALWC is the key factor in assessing the role of aerosols on atmospheric radiative forcing. Overall, the present study highlights the serious need to consider the ALWC in climate forcing simulations, particularly in moist tropical environments where their effect can be significant.

Aerosol liquid water content of PM2.5 and its influencing factors in Beijing, China

Aerosol liquid water content (ALWC) has important influences on atmospheric radiation and aerosol chemical processes. In this work, the changes in ALWC of PM_2.5 were investigated over four seasons based on hourly monitoring of inorganic water-soluble ions and their gaseous precursors using the thermodynamic model ISORROPIA II. The results showed that the ALWC concentrations exhibited pronounced seasonal (autumn > summer > spring > winter) and diurnal variation characteristics. The sensitivity tests indicated that ALWC depended strongly on TSO₄ (total sulfate (gas and aerosols) expressed as equivalent H₂SO₄), followed by TNO₃ (total nitrate (gas and aerosols) expressed as equivalent HNO₃). The relatively low concentration of TCl (total chloride (gas and aerosols) expressed as equivalent HCl) limit its importance in the atmosphere. ALWC showed exponential growth features as a function RH in all four seasons. RH became the most influential factor on the variation of ALWC when RH exceeded 80% in all seasons. The seasonal average data showed that the ALWC increased from 2.92 μg·m^-3 to 75.83 μg·m^-3 when ambient RH increased from 30% to 90%, the associated sulfate, nitrate, and ammonium (abbreviated as SNA) mass fraction in PM_2.5 rose from 0.39 to 0.58 in the atmosphere. The ALWC facilitated the formation of SNA through gas-particle conversion and partitioning. The self-amplifying processes between ALWC and SNA enhanced aerosol formation. By modeling ALWC under different seasonal atmospheric scenarios, it was found that reductions in chemical species could reduce ALWC concentrations in different degrees. Based on the current emission conditions, controlling excess NH₃ emission could effectively reduce ALWC to a maximum of 45.71% in summer, indicating that NH₃ control was crucial for reducing ALWC and PM_2.5 concentrations under high levels of SO₄^2- and NO₃^-.

Quantification of Atmospheric Ammonia Concentrations: A Review of Its Measurement and Modeling

Ammonia (NH3), the most prevalent alkaline gas in the atmosphere, plays a significant role in PM2.5 formation, atmospheric chemistry, and new particle formation. This paper reviews quantification of [NH3] through measurements, satellite-remote-sensing, and modeling reported in over 500 publications towards synthesizing the current knowledge of [NH3], focusing on spatiotemporal variations, controlling processes, and quantification issues. Most measurements are through regional passive sampler networks. [NH3] hotspots are typically over agricultural regions, such as the Midwest US and the North China Plain, with elevated concentrations reaching monthly averages of 20 and 74 ppbv, respectively. Topographical effects dramatically increase [NH3] over the Indo-Gangetic Plains, North India and San Joaquin Valley, US. Measurements are sparse over oceans, where [NH3] ≈ a few tens of pptv, variations of which can affect aerosol formation. Satellite remote-sensing (AIRS, CrIS, IASI, TANSO-FTS, TES) provides global [NH3] quantification in the column and at the surface since 2002. Modeling is crucial for improving understanding of NH3 chemistry and transport, its spatiotemporal variations, source apportionment, exploring physicochemical mechanisms, and predicting future scenarios. GEOS-Chem (global) and FRAME (UK) models are commonly applied for this. A synergistic approach of measurements↔satellite-inference↔modeling is needed towards improved understanding of atmospheric ammonia, which is of concern from the standpoint of human health and the ecosystem.

Characterization of Atmospheric PM2.5 Inorganic Aerosols Using the Semi-Continuous PPWD-PILS-IC System and the ISORROPIA-II

A semi-continuous monitoring system, a parallel plate wet denuder and particle into liquid sampler coupled with ion chromatography (PPWD-PILS-IC), was used to measure the hourly precursor gases and water-soluble inorganic ions in ambient particles smaller than 2.5 µm in diameter (PM2.5) for investigating the thermodynamic equilibrium of aerosols using the ISORROPIA-II thermodynamic equilibrium model. The 24-h average PPWD-PILS-IC data showed very good agreement with the daily data of the manual 5 L/min porous-metal denuder sampler with R2 ranging from 0.88 to 0.98 for inorganic ions (NH4+, Na+, K+, NO3−, SO42−, and Cl−) and 0.89 to 0.98 for precursor gases (NH3, HNO3, HONO, and SO2) and slopes ranging from 0.94 to 1.17 for ions and 0.87 to 0.95 for gases, respectively. In addition, the predicted ISORROPIA-II results were in good agreement with the hourly observed data of the PPWD-PILS-IC system for SO42− (R2 = 0.99 and slope = 1.0) and NH3 (R2 = 0.97 and slope = 1.02). The correlation of the predicted results and observed data was further improved for NH4+ and NO3− with the slope increasing from 0.90 to 0.96 and 0.95 to 1.09, respectively when the HNO2 and NO2− were included in the total nitrate concentration (TN = [NO3−] + [HNO3] + [HONO] + [NO2−]). The predicted HNO3 data were comparable to the sum of the observed [HNO3] and [HONO] indicating that HONO played an important role in the thermodynamic equilibrium of ambient PM2.5 aerosols but has not been considered in the ISORROPIA-II thermodynamic equilibrium model.

The Acidity of Atmospheric Particles and Clouds

Acidity, defined as pH, is a central component of aqueous chemistry. In the atmosphere, the acidity of condensed phases (aerosol particles, cloud water, and fog droplets) governs the phase partitioning of semi-volatile gases such as HNO3, NH3, HCl, and organic acids and bases as well as chemical reaction rates. It has implications for the atmospheric lifetime of pollutants, deposition, and human health. Despite its fundamental role in atmospheric processes, only recently has this field seen a growth in the number of studies on particle acidity. Even with this growth, many fine particle pH estimates must be based on thermodynamic model calculations since no operational techniques exist for direct measurements. Current information indicates acidic fine particles are ubiquitous, but observationally-constrained pH estimates are limited in spatial and temporal coverage. Clouds and fogs are also generally acidic, but to a lesser degree than particles, and have a range of pH that is quite sensitive to anthropogenic emissions of sulfur and nitrogen oxides, as well as ambient ammonia. Historical measurements indicate that cloud and fog droplet pH has changed in recent decades in response to controls on anthropogenic emissions, while the limited trend data for aerosol particles indicates acidity may be relatively constant due to the semi-volatile nature of the key acids and bases and buffering in particles. This paper reviews and synthesizes the current state of knowledge on the acidity of atmospheric condensed phases, specifically particles and cloud droplets. It includes recommendations for estimating acidity and pH, standard nomenclature, a synthesis of current pH estimates based on observations, and new model calculations on the local and global scale.

Current and Future Responses of Aerosol pH and Composition in the U.S. to Declining SO2 Emissions and Increasing NH3 Emissions

Aerosol pH can affect gas-particle partitioning of semivolatile species, secondary aerosol formation, aerosol water uptake and growth, acid deposition, and, potentially, aerosol toxicity. Despite its importance, aerosol pH projected in the near future has not been addressed explicitly while investigating the response of aerosol concentrations to emission regulations. In this study, we apply CMAQ to simulate aerosol pH in 2011 and 2050 across the continental U.S. We also assess the influence of two major emission trends, declining SO₂ emissions and rising NH₃ emissions, with a set of sensitivity simulations. Our results show that the aerosols will remain acidic with average pH typically ranging from 0.5 to 3.5 in 2050. Further reducing domestic SO₂ emissions does not significantly decrease aerosol acidity, even if SO₂ emissions were reduced to preindustrial levels because of the nonlinear response of SO₄^2- concentration to SO₂ emissions, and the semivolatile NH₃-NH₄⁺ buffering effect. Aerosol pH response to NH₃ emission increase will remain minor. Consequently, future fine particulate matter control efficiency will not be undercut by additional nitrate aerosol formation even if SO₂ emissions from industry and electricity generation are aggressively controlled, although areas will see some substitution leading to nitrate increases if NO_x emissions are not reduced.

METHODS FOR ATTRIBUTING AMBIENT AIR POLLUTANTS TO EMISSION SOURCES

▪ Abstract  Six methods for attributing ambient pollutants to emission sources are reviewed: emissions analysis, trend analysis, tracer studies, trajectory analysis, receptor modeling, and dispersion modeling. The ranges of applicability, types of information provided, limitations, performance capabilities, and areas of active research of the different methods are compared. For primary, nonreactive pollutants whose effects of concern occur on a global scale, an accounting of emissions rates by source type and location largely characterizes source contributions. For other pollutants or smaller spatial scales, accurate estimates of emissions are needed for identifying the emissions reduction potentials of possible control measures and as inputs to dispersion models. Emission levels are frequently known with factor-of-two accuracy or worse, and improved estimates are needed for dispersion modeling. The analysis of regional or urban-scale trends in emissions and ambient pollutant concentrations can provide qualitative information on source contributions, but quantitative results are limited by the confounding influence of variations in meteorology and uncertainties in the areas over which emissions affect concentrations. Tracer studies are useful for quantifying dispersion characteristics of plumes, qualitatively characterizing transport directions, and providing empirical data for evaluating trajectory and dispersion models. Data are usually temporally limited to a short study period, typically do not provide information on vertical pollutant distributions, and are most applicable to the transport of primary, nonreactive pollutants. Trajectory analyses are routinely used to estimate atmospheric transport directions. Trajectory errors of about 20% of travel distance are considered typical of the better models and data sets. Receptor models use measurements of ambient pollutant concentrations to quantify the contributions of different source types to primary particulate matter or volatile organic compounds, or to characterize source-region contributions to a single pollutant. Accuracy rates of ∼30% are often achieved when quantifying the contributions from different types of emission sources. Dispersion models are well-suited for estimating quantitative source-receptor relationships, as the effects of individual emission sources or source regions can be studied. Lagrangian and Gaussian dispersion models are computationally efficient and can simulate the transport of nonreactive primary or linear secondary species. Eulerian models are computationally intensive but lend themselves to the simulation of nonlinear chemistry. Careful evaluation of modeling accuracy is needed for a model application to fulfill its potential for source attribution. Accuracy can be evaluated through a combination of performance evaluation, sensitivity analysis, diagnostic evaluation, and corroborating analyses.