Limitations in representation of physical processes prevent successful simulation of PM_2.5 during KORUS-AQ

High levels of fine particulate matter (PM2.5) pollution in East Asia often exceed local air quality standards. Observations from the Korea United States-Air Quality (KORUS-AQ) field campaign in May and June 2016 showed that development of extreme pollution (haze) occurred through a combination of long-range transport and favorable meteorological conditions that enhanced local production of PM2.5. Atmospheric models often have difficulty simulating PM2.5 chemical composition during haze, which is of concern for the development of successful control measures. We use observations from KORUS-AQ to examine the ability of the GEOS-Chem chemical transport model to simulate PM2.5 composition throughout the campaign and identify the mechanisms driving the pollution event. In the surface level, the model underestimates campaign average sulfate aerosol by −64 % but overestimates nitrate aerosol by 36 %. The largest underestimate in sulfate occurs during the pollution event in conditions of high relative humidity, where models typically struggle to generate the high concentrations due to missing heterogeneous chemistry in aerosol liquid water in the polluted boundary layer. Hourly surface observations show that the model nitrate bias is driven by an overestimation of the nighttime peak. In the model, nitrate formation is limited by the supply of nitric acid, which is biased by +100 % against aircraft observations. We hypothesize that this is due to a missing sink, which we implement here as a factor of five increase in dry deposition. We show that the resulting increased deposition velocity is consistent with observations of total nitrate as a function of photochemical age. The model does not account for factors such as the urban heat island effect or the heterogeneity of the built-up urban landscape resulting in insufficient model turbulence and surface area over the study area that likely results in insufficient dry deposition. Other species such as NH3 could be similarly affected but were not measured during the campaign. Nighttime production of nitrate is driven by NO2 hydrolysis in the model, while observations show that unexpectedly elevated nighttime ozone (not present in the model) should result in N2O5 hydrolysis as the primary pathway. The model is unable to represent nighttime ozone due to an overly rapid collapse of the afternoon mixed layer and excessive titration by NO. We attribute this to missing nighttime heating driving deeper nocturnal mixing that would be expected to occur in a city like Seoul. This urban heating is not considered in air quality models run at large enough scales to treat both local chemistry and long-range transport. Key model failures in simulating nitrate, mainly overestimated daytime nitric acid, incorrect representation of nighttime chemistry, and an overly shallow and insufficiently turbulent nighttime mixed layer, exacerbate the model’s inability to simulate the buildup of PM2.5 during haze pollution. To address the underestimate in sulfate most evident during the haze event, heterogeneous aerosol uptake of SO2 is added to the model which previously only considered aqueous production of sulfate from SO2 in cloud water. Implementing a simple parameterization of this chemistry improves the model abundance of sulfate but degrades the SO2 simulation implying that emissions are underestimated. We find that improving model simulations of sulfate has direct relevance to determining local vs. transboundary contributions to PM2.5. During the haze pollution event, the inclusion of heterogeneous aerosol uptake of SO2 decreases the fraction of PM2.5 attributable to long-range transport from 66 % to 54 %. Locally-produced sulfate increased from 1 % to 46 % of locally-produced PM2.5, implying that local emissions controls would have a larger effect than previously thought. However, this additional uptake of SO2 is coupled to the model nitrate prediction which affects the aerosol liquid water abundance and chemistry driving sulfate-nitrate-ammonium partitioning. An additional simulation of the haze pollution with heterogeneous uptake of SO2 to aerosol and simple improvements to the model nitrate simulation results in 30 % less sulfate due to 40 % less nitrate and aerosol water, and results in an underestimate of sulfate during the haze event. Future studies need to better consider the impact of model physical processes such as dry deposition and boundary layer mixing on the simulation of nitrate and the effect of improved nitrate simulations on the overall simulation of secondary inorganic aerosol (sulfate+nitrate+ammonium) in East Asia. Foreign emissions are rapidly changing, increasing the need to understand the impact of local emissions on PM2.5 in South Korea to ensure continued air quality improvements.

Evaluation of SO₂, SO₄²⁻ and an updated SO₂ dry deposition parameterization in the United Kingdom Earth System Model

In this study we evaluate simulated surface SO2 and sulfate (SO42-) concentrations from the United Kingdom Earth System Model (UKESM1) against observations from ground-based measurement networks in the USA and Europe for the period 1987–2014. We find that UKESM1 captures the historical trend for decreasing concentrations of atmospheric SO2 and SO42- in both Europe and the USA over the period 1987–2014. However, in the polluted regions of the eastern USA and Europe, UKESM1 over-predicts surface SO2 concentrations by a factor of 3 while under-predicting surface SO42- concentrations by 25 %–35 %. In the cleaner western USA, the model over-predicts both surface SO2 and SO42- concentrations by factors of 12 and 1.5 respectively. We find that UKESM1’s bias in surface SO2 and SO42- concentrations is variable according to region and season. We also evaluate UKESM1 against total column SO2 from the Ozone Monitoring Instrument (OMI) using an updated data product. This comparison provides information about the model's global performance, finding that UKESM1 over-predicts total column SO2 over much of the globe, including the large source regions of India, China, the USA, and Europe as well as over outflow regions. Finally, we assess the impact of a more realistic treatment of the model's SO2 dry deposition parameterization. This change increases SO2 dry deposition to the land and ocean surfaces, thus reducing the atmospheric loading of SO2 and SO42-. In comparison with the ground-based and satellite observations, we find that the modified parameterization reduces the model's over-prediction of surface SO2 concentrations and total column SO2. Relative to the ground-based observations, the simulated surface SO42- concentrations are also reduced, while the simulated SO2 dry deposition fluxes increase.

Ozone deposition impact assessments for forest canopies require accurate ozone flux partitioning on diurnal timescales

Dry deposition is an important sink of tropospheric ozone that affects surface concentrations and impacts crop yields, the land carbon sink, and the terrestrial water cycle. Dry deposition pathways include plant uptake via stomata and non-stomatal removal by soils, leaf surfaces, and chemical reactions. Observational studies indicate that ozone deposition exhibits substantial temporal variability that is not reproduced by atmospheric chemistry models due to a simplified representation of vegetation uptake processes in these models. In this study, we explore the importance of stomatal and non-stomatal uptake processes in driving ozone dry deposition variability on diurnal to seasonal timescales. Specifically, we compare two land surface ozone uptake parameterizations – a commonly applied big leaf parameterization (W89; Wesely, 1989) and a multi-layer model (MLC-CHEM) constrained with observations – to multi-year ozone flux observations at two European measurement sites (Ispra, Italy, and Hyytiälä, Finland). We find that W89 cannot reproduce the diurnal cycle in ozone deposition due to a misrepresentation of stomatal and non-stomatal sinks at our two study sites, while MLC-CHEM accurately reproduces the different sink pathways. Evaluation of non-stomatal uptake further corroborates the previously found important roles of wet leaf uptake in the morning under humid conditions and soil uptake during warm conditions. The misrepresentation of stomatal versus non-stomatal uptake in W89 results in an overestimation of growing season cumulative ozone uptake (CUO), a metric for assessments of vegetation ozone damage, by 18 % (Ispra) and 28 % (Hyytiälä), while MLC-CHEM reproduces CUO within 7 % of the observation-inferred values. Our results indicate the need to accurately describe the partitioning of the ozone atmosphere–biosphere flux over the in-canopy stomatal and non-stomatal loss pathways to provide more confidence in atmospheric chemistry model simulations of surface ozone mixing ratios and deposition fluxes for large-scale vegetation ozone impact assessments.

Assessment of the quality of atmospheric air in woodlands of natural areas based on the intensity analysis of the process of dry deposition of impurities on an artificial underlying surface

To assess the quality of atmospheric air, the authors propose to apply the process of dry deposition of impurities on an artificial underlying surface that binds impurities in contact with it. The mass of these impurities is calculated upon laboratory exposure, after being transferred to an aqueous solution. The ease of absorber fabrication and the low cost facilitate the monitoring of air pollution at various points in woodlands, where the stationary stations for air-pollution-monitoring are very difficult and costly to arrange. A large number of control points makes it possible to identify forest areas with the highest levels of air pollution. A dynamic air-quality study at one of the monitoring points is necessary and sufficient to determine the concentration of impurities. The authors surveyed an urban forest using the proposed method, and the survey results confirmed that areas with an elevated concentration of airborne nitrogen dioxide exist within the woodland. This can lead to soil eutrophication and changes in forest biodiversity at the species and ecosystem levels.

Examining the competing effects of contemporary land management vs. land cover changes on global air quality

Our work explores the impact of two important dimensions of land system changes, land use and land cover change (LULCC) as well as direct agricultural reactive nitrogen (Nr) emissions from soils, on ozone (O3) and fine particulate matter (PM2.5) in terms of air quality over contemporary (1992 to 2014) timescales. We account for LULCC and agricultural Nr emissions changes with consistent remote sensing products and new global emission inventories respectively estimating their impacts on global surface O3 and PM2.5 concentrations as well as Nr deposition using the GEOS-Chem global chemical transport model. Over this time period, our model results show that agricultural Nr emission changes cause a reduction of annual mean PM2.5 levels over Europe and northern Asia (up to −2.1 µg m−3) while increasing PM2.5 levels in India, China and the eastern US (up to +3.5 µg m−3). Land cover changes induce small reductions in PM2.5 (up to −0.7 µg m−3) over Amazonia, China and India due to reduced biogenic volatile organic compound (BVOC) emissions and enhanced deposition of aerosol precursor gases (e.g., NO2, SO2). Agricultural Nr emission changes only lead to minor changes (up to ±0.6 ppbv) in annual mean surface O3 levels, mainly over China, India and Myanmar. Meanwhile, our model result suggests a stronger impact of LULCC on surface O3 over the time period across South America; the combination of changes in dry deposition and isoprene emissions results in −0.8 to +1.2 ppbv surface ozone changes. The enhancement of dry deposition reduces the surface ozone level (up to −1 ppbv) over southern China, the eastern US and central Africa. The enhancement of soil NO emission due to crop expansion also contributes to surface ozone changes (up to +0.6 ppbv) over sub-Saharan Africa. In certain regions, the combined effects of LULCC and agricultural Nr emission changes on O3 and PM2.5 air quality can be comparable (>20 %) to anthropogenic emission changes over the same time period. Finally, we calculate that the increase in global agricultural Nr emissions leads to a net increase in global land area (+3.67×106km2) that potentially faces exceedance of the critical Nr load (>5 kg N ha−1 yr−1). Our result demonstrates the impacts of contemporary LULCC and agricultural Nr emission changes on PM2.5 and O3 in terms of air quality, as well as the importance of land system changes for air quality over multidecadal timescales.