Regional Atmospheric Chemistry Model Research Articles

Modeling the contribution of leads to sea spray aerosol in the high Arctic

Abstract. Elongated open-water areas in sea ice (leads) release sea spray particles to the atmosphere. However, there is limited knowledge on the amount, properties and drivers of sea spray emitted from leads, and no existing parameterization of this process is available for use in models. In this work, we use measurements of aerosol fluxes from Nilsson et al. (2001) to produce an estimate of the location, timing and amount of sea spray emissions from leads at the scale of the Arctic Ocean for 1 year. Lead fractions are derived using sea ice data sets from numerical models and satellite detection. The proposed parameterization estimates that leads account for 0.3 %–9.8 % of the annual sea salt aerosol number emissions in the Arctic Ocean regions where sea ice concentration is greater than 80 %. Assuming similar size distributions to those from emissions from the open ocean, leads account for 30 %–85 % of mass emissions in sea ice regions. The total annual mass of sea salt emitted from leads, 0.1–2.1 Tg yr−1, is comparable to the mass of sea salt aerosol transported above sea ice from the open ocean, according to the MERRA-2 reanalysis. In addition to providing the first estimates of possible upper and lower bounds of sea spray emissions from leads, the conceptual model developed in this work is implemented and tested in the regional atmospheric chemistry model WRF-Chem. Given the estimates obtained in this work, the impact of sea spray from leads on Arctic clouds and radiative budget needs to be further explored.

Modeling Novel Aqueous Particle and Cloud Chemistry Processes of Biomass Burning Phenols and Their Potential to Form Secondary Organic Aerosols.

Phenols emitted from biomass burning contribute significantly to secondary organic aerosol (SOA) formation through the partitioning of semivolatile products formed from gas-phase chemistry and multiphase chemistry in aerosol liquid water and clouds. The aqueous-phase SOA (aqSOA) formed via hydroxyl radical (•OH), singlet molecular oxygen (1O2*), and triplet excited states of organic compounds (3C*), which oxidize dissolved phenols in the aqueous phase, might play a significant role in the evolution of organic aerosol (OA). However, a quantitative and predictive understanding of aqSOA has been challenging. Here, we develop a stand-alone box model to investigate the formation of SOA from gas-phase •OH chemistry and aqSOA formed by the dissolution of phenols followed by their aqueous-phase reactions with •OH, 1O2*, and 3C* in cloud droplets and aerosol liquid water. We investigate four phenolic compounds, i.e., phenol, guaiacol, syringol, and guaiacyl acetone (GA), which represent some of the key potential sources of aqSOA from biomass burning in clouds. For the same initial precursor organic gas that dissolves in aerosol/cloud liquid water and subsequently reacts with aqueous phase oxidants, we predict that the aqSOA formation potential (defined as aqSOA formed per unit dissolved organic gas concentration) of these phenols is higher than that of isoprene-epoxydiol (IEPOX), a well-known aqSOA precursor. Cloud droplets can dissolve a broader range of soluble phenols compared to aqueous aerosols, since the liquid water contents of aerosols are orders of magnitude smaller than cloud droplets. Our simulations suggest that highly soluble and reactive multifunctional phenols like GA would predominantly undergo cloud chemistry within cloud layers, while gas-phase chemistry is likely to be more important for less soluble phenols. But in the absence of clouds, the condensation of low-volatility products from gas-phase oxidation followed by their reversible partitioning to organic aerosols dominates SOA formation, while the SOA formed through aqueous aerosol chemistry increases with relative humidity (RH), approaching 40% of the sum of gas and aqueous aerosol chemistry at 95% RH for GA. Our model developments of biomass-burning phenols and their aqueous chemistry can be readily implemented in regional and global atmospheric chemistry models to investigate the aqueous aerosol and cloud chemistry of biomass-burning organic gases in the atmosphere.

Characterizing Ozone Sensitivity to Urban Greening in Los Angeles Under Current Day and Future Anthropogenic Emissions Scenarios

AbstractCities are simultaneously implementing urban greening and reducing anthropogenic emissions to combat climate change, but these strategies can have complex and potentially counteracting effects on regional atmospheric chemistry. Urban greening can increase emissions of volatile organic compounds (BVOCs), while climate change mitigation strategies reduce co‐emitted pollutants such as nitrogen oxides (NOx). The nonlinear relationship between ozone (O3) and BVOC and NOx concentrations makes it crucial to investigate potential interactions between urban greening and anthropogenic emissions reductions. Here, we use regional atmospheric chemistry modeling to assess O3 sensitivity to a 50% increase in urban vegetation in the Los Angeles Basin. We evaluated potential interactions between urban greening and climate change mitigation by running urban greening simulations with current day and future anthropogenic emissions that reflect renewable energy adoption and electrification in Los Angeles, CA. Our model results show that urban greening increased daily maximum 8‐hr ozone concentrations with higher increases modeled under current day anthropogenic emissions. Urban greening had complex effects on hourly O3 concentrations, with increased O3 concentrations up to 0.95 ppb during the day following increased biogenic emissions and reduced urban O3 concentrations up to 0.41 ppb at night following reduced ventilation of NOx. Under the future anthropogenic emissions scenario, reductions in NOx somewhat mitigated the daytime O3 penalties of urban greening but also dampened nighttime O3 reductions. Our results suggest that urban greening will likely have regional O3 penalties if new vegetation is high isoprene emitting, even as NOx emissions are drastically reduced following climate change mitigation.

Triple oxygen isotope composition of combustion sulfate

The estimated contribution of “primary” combustion sulfate to the total atmospheric sulfate flux is inconsistent, hindering our interpretation of the atmospheric “missing sulfate”. We expect combustion sulfate to inherit the characteristic triple oxygen isotope composition of air O2 to variable degrees. To test the hypothesis, we extracted sulfate from soot samples collected from 48 residential chimneys throughout China. The mean sulfate's Δ′17O0.5305 and δ18O values are −0.27 ± 0.06‰ and 12.8 ± 3.6‰, respectively, and the Δ′17O0.5305 and δ18O values correlate negatively and extend to air O2's triple oxygen isotope composition as an endmember, suggesting that combustion sulfate is generated dominantly by S(IV) multiphase oxidation via O2 in the plume, with possible additional pathways through •OH in aqueous films or droplets and NO2 at soot surface. Oxygen sources (i.e., air O2, fuel, ambient moisture) and oxidation kinetics determine the triple oxygen isotope composition of combustion sulfate. The characterization of combustion sulfate's triple isotope composition helps to improve global and regional atmospheric sulfur chemistry models.

The Fire Inventory from NCAR version 2.5: an updated global fire emissions model for climate and chemistry applications

Abstract. We present the Fire Inventory from National Center for Atmospheric Research (NCAR) version 2.5 (FINNv2.5), a fire emissions inventory that provides publicly available emissions of trace gases and aerosols for various applications, including use in global and regional atmospheric chemistry modeling. FINNv2.5 includes numerous updates to the FINN version 1 framework to better represent burned area, vegetation burned, and chemicals emitted. Major changes include the use of active fire detections from the Visible Infrared Imaging Radiometer Suite (VIIRS) at 375 m spatial resolution, which allows smaller fires to be included in the emissions processing. The calculation of burned area has been updated such that a more rigorous approach is used to aggregate fire detections, which better accounts for larger fires and enables using multiple satellite products simultaneously for emissions estimates. Fuel characterization and emissions factors have also been updated in FINNv2.5. Daily fire emissions for many trace gases and aerosols are determined for 2002–2019 (Moderate Resolution Imaging Spectroradiometer (MODIS)-only fire detections) and 2012–2019 (MODIS + VIIRS fire detections). The non-methane organic gas emissions are allocated to the species of several commonly used chemical mechanisms. We compare FINNv2.5 emissions against other widely used fire emissions inventories. The performance of FINNv2.5 emissions as inputs to a chemical transport model is assessed with satellite observations. Uncertainties in the emissions estimates remain, particularly in Africa and South America during August–October and in southeast and equatorial Asia in March and April. Recommendations for future evaluation and use are given.

Effects of Non‐Photosynthetic Vegetation on Dust Emissions

AbstractMineral dust is among the top contributors to global aerosol loads. Ability of non‐photosynthetic vegetation (NPV) to suppress dust emission has been widely acknowledged but a realistic representation of NPV has not been tested with regional‐to‐global scale models. In this study, we implemented a satellite‐based total vegetation data set, which included NPV, into a regional atmospheric chemistry model and conducted simulations for the year 2016 over the conterminous United States. To test the response of dust simulations to the NPV coverage, we conducted a control simulation incorporating only the photosynthetic vegetation (PV). Simulated dust emissions decrease by 10%–70% over most of the southwestern US from spring to autumn due to NPV. Reductions in dust concentrations are the largest in spring, which attenuate the overpredictions of fine soil concentrations, but accentuate the underpredictions in summer. Overall, the mean errors and correlations of annual simulations are slightly improved with NPV. NPV modulates dust emissions mainly by sheltering the surface and increasing the threshold velocity through drag partitioning. Moreover, we investigated the effect of vegetation height and addressed its uncertainties through a series of sensitivity tests. We observed that a 50% variation in predefined vegetation heights results in small changes in soil concentrations over majority of southwestern US, but causes up to 30% changes at local hotspots. This study highlights the significance of including NPV into the dust model and points out the importance of validation of total vegetation datasets as well as more realistic representation of vegetation heights and seasonality.

High-Resolution Ammonia Emissions from Nitrogen Fertilizer Application in China during 2005–2020

The accurate estimation of ammonia emission is essential for quantifying secondary inorganic aerosol formation and reactive nitrogen deposition. During the last decades, both fertilizer type and the total amount of nitrogen fertilizer in China have changed, while the resulting changes in ammonia emissions and their spatio-temporal variations are unclear. In this study, we compile a long-term (2005–2020) high-resolution ammonia emission inventory for synthetic fertilizer in China with bottom-up method. We parameterized emissions factors (EFs) considering the impacts of soil properties, method of fertilizer application, fertilizer type, crop type, ambient temperature and wind speed. Meanwhile, the monthly nitrogen fertilizer application is calculated by detailed information on crop-specific fertilizer application practices. For the spatial distribution, the ammonia emissions from fertilizer mostly concentrate in eastern and southwestern China, coincident with the high density of agriculture activity and population in these regions. For the seasonal variation, the ammonia emissions from fertilizer application peak in spring and summer because of dense fertilizer application and high ambient temperature. For the long-term trend, we estimate that the emissions from synthetic fertilizer increased from 5.38 Tg in 2005 to 5.53 Tg in 2008 and remained nearly unchanged during 2008–2012, then decreased to 3.96 Tg in 2020. Urea, ammonium bicarbonate (ABC) and nitrogenous compound fertilizer are major fertilizer types used in China. Despite the increased use of nitrogen fertilizer, ammonia emissions remained stable throughout 2008–2012 with the declined use of ABC. This stable period also reflects ammonia emission increases in western China, offsetting the decreases in eastern China. Furthermore, our emission inventory provides a monthly estimation at a spatial resolution of 0.1 degrees, which can be applied to global and regional atmospheric chemistry model simulations.

Improvement of stomatal resistance and photosynthesis mechanism of Noah-MP-WDDM (v1.42) in simulation of NO<sub>2</sub> dry deposition velocity in forests

Abstract. Rapid urbanisation and economic development in China have led to a dramatic increase in nitrogen oxide (NO2) emissions, causing serious atmospheric nitrogen pollution and relatively high levels of nitrogen deposition. However, despite the importance of nitrogen deposition, dry deposition processes in forested areas are still insufficiently represented in current global and regional atmospheric chemistry models, which constrains our understanding and prediction of spatial and temporal patterns of nitrogen transport in forest ecosystems in southern China. The offline 1-D community Noah land surface model with multi-parameterisation options (Noah-MP) is coupled with the WRF-Chem dry deposition module (WDDM) and is applied to further understand and identify the key processes that affect forest canopy dry deposition. The canopy stomatal resistance mechanism and the nitrogen-limiting scheme for photosynthesis in Noah-MP-WDDM are modified to improve the simulation of reactive nitrogen oxide dry deposition velocity. This study finds that the combined improved stomatal resistance mechanism and nitrogen-limiting scheme for photosynthesis (BN-23) agree better with the observed NO2 dry deposition velocity, with the mean bias being reduced by 50.1 %. At the same time, by comparing the different mechanisms of the two processes of canopy stomatal resistance and leaf nitrogen-limiting factors, this study also finds that the diurnal changes in dry deposition velocity simulated by each regional model present four sets of distributions. This is mainly due to the different ways that each integrated mechanism handles the opening and closing of stomata at noon and the way the nitrogen-limiting factor acts.

Cropland nitrogen dioxide emissions and effects on the ozone pollution in the North China plain

Soil nitrogen dioxide (NOX = NO2 + NO) emissions have been measured and estimated to be the second most significant contributor to the NOX burden following the fossil fuel combustion source globally. NOX emissions from croplands are subject to being underestimated or overlooked in air pollution simulations of regional atmospheric chemistry models. With constraints of ground and space observations of NO2, the WRF-Chem model is used to investigate the cropland NOX emission and its contribution to the near-surface ozone (O3) pollution in North China Plain (NCP) during a growing season as a case study. Model simulations have revealed that the cropland NOX emissions are underestimated by around 80% without constraints of satellite measured NO2 column densities. The biogenic NOX source is estimated to account for half of the anthropogenic NOX emissions in the NCP during the growing season. Additionally, the cropland NOX source contributes around 5.0% of the maximum daily average 8h O3 concentration and 27.7% of NO2 concentration in the NCP. Our results suggest the agriculture NOX emission exerts non-negligible impacts on the summertime air quality and needs to be considered when designing emission abatement strategies.

Evaluation of the coupled high-resolution atmospheric chemistry model system MECO(n) using in situ and MAX-DOAS NO<sub>2</sub> measurements

Abstract. We present high spatial resolution (up to 2.2×2.2 km2) simulations focussed over south-west Germany using the online coupled regional atmospheric chemistry model system MECO(n) (MESSy-fied ECHAM and COSMO models nested n times). Numerical simulation of nitrogen dioxide (NO2) surface volume mixing ratios (VMRs) are compared to in situ measurements from a network with 193 locations including background, traffic-adjacent and industrial stations to investigate the model's performance in simulating the spatial and temporal variability of short-lived chemical species. We show that the use of a high-resolution and up-to-date emission inventory is crucial for reproducing the spatial variability and resulted in good agreement with the measured VMRs at the background and industrial locations with an overall bias of less than 10 %. We introduce a computationally efficient approach that simulates diurnal and daily variability in monthly-resolved anthropogenic emissions to resolve the temporal variability of NO2. MAX-DOAS (Multiple AXis Differential Optical Absorption Spectroscopy) measurements performed at Mainz (49.99∘ N, 8.23∘ E) were used to evaluate the simulated tropospheric vertical column densities (VCDs) of NO2. We propose a consistent and robust approach to evaluate the vertical distribution of NO2 in the boundary layer by comparing the individual differential slant column densities (dSCDs) at various elevation angles. This approach considers details of the spatial heterogeneity and sensitivity volume of the MAX-DOAS measurements while comparing the measured and simulated dSCDs. The effects of clouds on the agreement between MAX-DOAS measurements and simulations have also been investigated. For low elevation angles (≤8∘), small biases in the range of −14 % to +7 % and Pearson correlation coefficients in the range of 0.5 to 0.8 were achieved for different azimuth directions in the cloud-free cases, indicating good model performance in the layers close to the surface. Accounting for diurnal and daily variability in the monthly-resolved anthropogenic emissions was found to be crucial for the accurate representation of time series of measured NO2 VMR and dSCDs and is particularly critical when vertical mixing is suppressed, and the atmospheric lifetime of NO2 is relatively long.

Mineral dust and fossil fuel combustion dominate sources of aerosol sulfate in urban Peru identified by sulfur stable isotopes and water-soluble ions

High sulfur emissions in the Central Andes have in the past been attributed to active volcanoes and numerous copper smelting facilities in the region. This study evaluates the contribution of these sources on Arequipa, Peru through an evaluation of aerosol sulfate δ34S values and water-soluble ions (WSI). The anthropogenic and natural sources of particulate pollution were determined by aerosol filter sampling from four different locations (urban, suburban, industrial, and rural) providing a view of the spatial variability of aerosols within the city. Sulfate (avg. 2.97 μm/m3) is the most abundant ion species in the aerosols sampled contributing on average 20% of the molar mass. Ion composition profiles between sampling sites are very similar indicating common sources and high contributions of mobilized local surface salt to the aerosols in this desert region. The regional atmospheric chemistry model (RACM) 0-D run for the area confirms that emissions from fuel combustion sources alone cannot account for the high concentrations of sulfate observed. A combination of the RACM results, WSI data, and a Bayesian δ34S isotope mixing model determined that the majority of aerosol sulfates in the area are from mineral dust adding to fossil fuel combustion sources. Mineral dust entrainment in the region is likely elevated by the close proximity of open-pit mining and unpaved roads near the city. Marine organic aerosols and smelting located along the Pacific contribute little to Arequipa's aerosol sulfate concentration. While the influence of volcanic sulfate (9% on average) is low, overall natural sulfate (dust, volcanic, and DMS) accounts for 43% of the aerosol sulfate. Therefore, even though the local environment creates high sulfate background levels, a reduction of sulfate aerosol pollution would be possible if fossil fuel emissions were reduced.

WRF-GC (v1.0): online coupling of WRF (v3.9.1.1) and GEOS-Chem (v12.2.1) for regional atmospheric chemistry modeling – Part 1: Description of the one-way model

Abstract. We developed the WRF-GC model, an online coupling of the Weather Research and Forecasting (WRF) mesoscale meteorological model and the GEOS-Chem atmospheric chemistry model, for regional atmospheric chemistry and air quality modeling. WRF and GEOS-Chem are both open-source community models. WRF-GC offers regional modellers access to the latest GEOS-Chem chemical module, which is state of the science, well documented, traceable, benchmarked, actively developed by a large international user base, and centrally managed by a dedicated support team. At the same time, WRF-GC enables GEOS-Chem users to perform high-resolution forecasts and hindcasts for any region and time of interest. WRF-GC uses unmodified copies of WRF and GEOS-Chem from their respective sources; the coupling structure allows future versions of either one of the two parent models to be integrated into WRF-GC with relative ease. Within WRF-GC, the physical and chemical state variables are managed in distributed memory and translated between WRF and GEOS-Chem by the WRF-GC coupler at runtime. We used the WRF-GC model to simulate surface PM2.5 concentrations over China during 22 to 27 January 2015 and compared the results to surface observations and the outcomes from a GEOS-Chem Classic nested-China simulation. Both models were able to reproduce the observed spatiotemporal variations of regional PM2.5, but the WRF-GC model (r=0.68, bias =29 %) reproduced the observed daily PM2.5 concentrations over eastern China better than the GEOS-Chem Classic model did (r=0.72, bias =55 %). This was because the WRF-GC simulation, nudged with surface and upper-level meteorological observations, was able to better represent the pollution meteorology during the study period. The WRF-GC model is parallelized across computational cores and scales well on massively parallel architectures. In our tests where the two models were similarly configured, the WRF-GC simulation was 3 times more efficient than the GEOS-Chem Classic nested-grid simulation due to the efficient transport algorithm and the Message Passing Interface (MPI)-based parallelization provided by the WRF software framework. WRF-GC v1.0 supports one-way coupling only, using WRF-simulated meteorological fields to drive GEOS-Chem with no chemical feedbacks. The development of two-way coupling capabilities, i.e., the ability to simulate radiative and microphysical feedbacks of chemistry to meteorology, is under way. The WRF-GC model is open source and freely available from http://wrf.geos-chem.org (last access: 10 July 2020).

Impact of the Emission Control of Diesel Vehicles on Black Carbon (BC) Concentrations over China

In order to reduce black carbon (BC) emissions from diesel vehicles, a regional atmospheric chemistry model (WRF-Chem) was used to investigate the effects of installing a high-efficiency device for vehicle exhaust control, a diesel particulate filter (DPF), on diesel vehicles in China. To reduce the uncertainty of estimation, three sensitivity experiments were designed and conducted for different emission scenarios. The first experiment uses the standard black carbon emissions of diesel vehicles without engaging in any emission control actions (referred to as CTRL), and the other two experiments were conducted using different DPF devices to reduce BC emissions by 65% (CASE1) and 39% (CASE2), respectively. The results show that the model simulation reasonably represents the measured BC concentrations. The highest BC concentrations occurred in large cities of the North China Plain (NCP) and present important seasonal variations. The results suggest that the reduction in diesel vehicle emissions has great benefits for reducing BC pollution not only in winter but also in other seasons. Sensitivity studies show that in CASE1, the average BC concentrations decreased about ~6% in January and by more than 10% in the other seasons. The greatest reduction exceeded 50%. In CASE2, the average BC concentrations decreased by about ~3.5% in January and by more than 7% in the other seasons. This study suggests that adding DPF to a diesel vehicle can have a significant influence on reducing BC concentrations in China. Thus, this study provides a practical basis by which diesel vehicle emissions can be reduced.

Rapid reduction in black carbon emissions from China: evidence from 2009–2019 observations on Fukue Island, Japan

Abstract. A long-term, robust observational record of atmospheric black carbon (BC) concentrations at Fukue Island for 2009–2019 was produced by unifying the data from a continuous soot monitoring system (COSMOS) and a Multi-Angle Absorption Photometer (MAAP). This record was then used to analyze emission trends from China. We identified a rapid reduction in BC concentrations of (-5.8±1.5) % yr−1 or −48 % from 2010 to 2018. We concluded that an emission change of (-5.3±0.7) % yr−1, related to changes in China of as much as −4.6 % yr−1, was the main underlying driver. This evaluation was made after correcting for the interannual meteorological variability (IAV) by using the regional atmospheric chemistry model simulations from the Weather Research and Forecasting (WRF) and Community Multiscale Air Quality (CMAQ) models (collectively WRF/CMAQ) with the constant emissions. This resolves the current fundamental disagreements about the sign of the BC emissions trend from China over the past decade as assessed from bottom-up emission inventories. Our analysis supports inventories reflecting the governmental clean air actions after 2010 (e.g., MEIC1.3, ECLIPSE versions 5a and 6b, and the Regional Emission inventory in ASia (REAS) version 3.1) and recommends revisions to those that do not (e.g., Community Emissions Data System – CEDS). Our estimated emission trends were fairly uniform across seasons but diverse among air mass origins. Stronger BC reductions, accompanied by a reduction in carbon monoxide (CO) emissions, occurred in regions of south-central East China, while weaker BC reductions occurred in north-central East China and northeastern China. Prior to 2017, the BC and CO emissions trends were both unexpectedly positive in northeastern China during winter months, which possibly influenced the climate at higher latitudes. The pace of the estimated emissions reduction over China surpasses the Shared Socioeconomic Pathways (SSPs with reference to SSP1, specifically) scenarios for 2015–2030, which suggests highly successful emission control policies. At Fukue Island, the BC fraction of fine particulate matter (PM2.5) also steadily decreased over the last decade. This suggests that reductions in BC emissions started without significant delay when compared to other pollutants such as NOx and SO2, which are among the key precursors of scattering PM2.5.

Critical contribution of south Asian residential emissions to atmospheric black carbon over the Tibetan plateau

Black carbon (BC) over the Tibetan Plateau (TP), both in the air and deposited on the surface of snow and ice, has been shown to accelerate the retreat of mountain glaciers. Previous study indicated that South Asian anthropogenic emissions primarily contributed to atmospheric loading of BC over the TP, it is essential to further identify the major sector in South Asia and provide guidance for potential mitigation strategies. In this study, the regional atmospheric chemistry model WRF-Chem was run for an entire year. The results suggested that residential BC emissions from South Asia contributed the largest (25.8% in summer and 44.8% in winter) to BC concentrations over the TP compared to other anthropogenic emission sectors in the region. Furthermore, significant seasonal variability existed in the transport process of residential BC from South Asia to the TP. The South Asia monsoon during summer and the mountain-valley wind system during spring could transport South Asian residential BC across the Himalayas to the TP. However, the higher transportation flux along 30°N indicated that the transport was mainly influenced by westerly winds, implying that residential emissions from northern India were the critical source of BC aerosols over the TP. A further assessment of emission control strategies suggested that reducing emissions from South Asian residential sources can effectively reduce BC concentrations over the TP, which may potentially alleviate the TP's accelerating glacier melting.

Exploring the economy-wide effects of agriculture on air quality and health: Evidence from Europe

Agricultural emissions strongly contribute to fine particulate matter pollution (PM2.5) and associated effects on human health. Environmentally-extended input-output models and a regional atmospheric chemistry model (WRF-Chem) were combined to conduct an economy-wide assessment of air pollution and pre-mature mortality in the European Union (EU), associated with a 20% increase in the final demand for the output of the agricultural sector. Model results revealed significant differences in air pollution originating from agricultural growth across the 28 EU countries (EU-28). The highest impact of agricultural growth on PM2.5 concentrations occur over the Northern Balkan countries (Bulgaria and Romania) and northern Italy. However, the highest excess mortality rates in the EU-28 due to changes in emissions and enhanced PM2.5 concentrations are observed in Malta, Greece, Spain and Cyprus. The least affected countries are mostly located in the northern part of Europe, with the exception of the Scandinavian Countries, which have relatively good air quality under current conditions. Our integrated modelling framework results highlight the importance of capturing both the direct and indirect air pollution emissions of economic sectors via upstream supply chains and underscore the non-linear response of surface PM2.5 levels and their health impacts to emission fluxes.

Modelling the physical multiphase interactions of HNO<sub>3</sub> between snow and air on the Antarctic Plateau (Dome C) and coast (Halley)

Abstract. Emissions of nitrogen oxide (NOx = NO + NO2) from the photolysis of nitrate (NO3−) in snow affect the oxidising capacity of the lower troposphere especially in remote regions of high latitudes with little pollution. Current air–snow exchange models are limited by poor understanding of processes and often require unphysical tuning parameters. Here, two multiphase models were developed from physically based parameterisations to describe the interaction of nitrate between the surface layer of the snowpack and the overlying atmosphere. The first model is similar to previous approaches and assumes that below a threshold temperature, To, the air–snow grain interface is pure ice and above To a disordered interface (DI) emerges covering the entire grain surface. The second model assumes that air–ice interactions dominate over all temperatures below melting of ice and that any liquid present above the eutectic temperature is concentrated in micropockets. The models are used to predict the nitrate in surface snow constrained by year-round observations of mixing ratios of nitric acid in air at a cold site on the Antarctic Plateau (Dome C; 75°06′ S, 123°33′ E; 3233 m a.s.l.) and at a relatively warm site on the Antarctic coast (Halley; 75°35′ S, 26°39′ E; 35 m a.s.l). The first model agrees reasonably well with observations at Dome C (Cv(RMSE) = 1.34) but performs poorly at Halley (Cv(RMSE) = 89.28) while the second model reproduces with good agreement observations at both sites (Cv(RMSE) = 0.84 at both sites). It is therefore suggested that in winter air–snow interactions of nitrate are determined by non-equilibrium surface adsorption and co-condensation on ice coupled with solid-state diffusion inside the grain, similar to Bock et al. (2016). In summer, however, the air–snow exchange of nitrate is mainly driven by solvation into liquid micropockets following Henry's law with contributions to total surface snow NO3− concentrations of 75 and 80 % at Dome C and Halley, respectively. It is also found that the liquid volume of the snow grain and air–micropocket partitioning of HNO3 are sensitive to both the total solute concentration of mineral ions within the snow and pH of the snow. The second model provides an alternative method to predict nitrate concentration in the surface snow layer which is applicable over the entire range of environmental conditions typical for Antarctica and forms a basis for a future full 1-D snowpack model as well as parameterisations in regional or global atmospheric chemistry models.

Impacts of Atmospheric Nitrogen Deposition on Surface Waters of the Western North Atlantic Mitigated by Multiple Feedbacks

AbstractThe impacts of atmospheric nitrogen deposition (AND) on the chlorophyll and nitrogen dynamics of surface waters in the western North Atlantic (25°N–45°N, 65°W–80°W) are examined with a biogeochemical ocean model forced with a regional atmospheric chemistry model (Community Multiscale Air Quality, CMAQ). CMAQ simulations with year‐specific emissions reveal the existence of a “hot spot” of AND over the Gulf Stream. The impact of the hot spot on the oceanic biogeochemistry is mitigated in three ways by physical and biogeochemical processes. First, AND significantly contributes to surface oceanic nitrogen concentrations only during the summer period, when the stratification is maximal and the background nitrogen inventories are minimal. Second, the increase in summer surface nitrate concentrations is accompanied by a reduction in upward nitrate diffusion at the base of the surface layer. This negative feedback partly cancels the nitrogen enrichment from AND. Third, gains in biomass near the surface force a shoaling of the euphotic layer and a reduction of about 5% in deep primary production and biomass on the continental shelf. Despite these mitigating processes, the impacts of AND remain substantial. AND increases surface nitrate concentrations in the Gulf Stream region by 14% during the summer (2% on average over the year). New primary production increases by 22% in this region during summer (8% on average). Although these changes may be difficult to distinguish from natural variability in observations, the results support the view that AND significantly enhances local carbon export.

Regional modelling of polycyclic aromatic hydrocarbons: WRF-Chem-PAH model development and East Asia case studies

Abstract. Polycyclic aromatic hydrocarbons (PAHs) are hazardous pollutants, with increasing emissions in pace with economic development in East Asia, but their distribution and fate in the atmosphere are not yet well understood. We extended the regional atmospheric chemistry model WRF-Chem (Weather Research Forecast model with Chemistry module) to comprehensively study the atmospheric distribution and the fate of low-concentration, slowly degrading semivolatile compounds. The WRF-Chem-PAH model reflects the state-of-the-art understanding of current PAHs studies with several new or updated features. It was applied for PAHs covering a wide range of volatility and hydrophobicity, i.e. phenanthrene, chrysene and benzo[a]pyrene, in East Asia. Temporally highly resolved PAH concentrations and particulate mass fractions were evaluated against observations. The WRF-Chem-PAH model is able to reasonably well simulate the concentration levels and particulate mass fractions of PAHs near the sources and at a remote outflow region of East Asia, in high spatial and temporal resolutions. Sensitivity study shows that the heterogeneous reaction with ozone and the homogeneous reaction with the nitrate radical significantly influence the fate and distributions of PAHs. The methods to implement new species and to correct the transport problems can be applied to other newly implemented species in WRF-Chem.

Estimation of atmospheric aging time of black carbon particles in the polluted atmosphere over central-eastern China using microphysical process analysis in regional chemical transport model

Mixing state of black carbon (BC) particles has significant impacts on their radiative forcing, visibility impairment and the ability in modifying cloud formation. In this study, an aging scheme of BC particles using prognostic variables based on aerosol microphysics was incorporated into a regional atmospheric chemistry model, Nested Air Quality Prediction Modeling System with Advanced Particle Microphysics (NAQPMS + APM), to investigate the temporal and spatial variations in aging time scale of BC particles in polluted atmosphere over central-eastern China. The model results show that the aging time scale has a clear diurnal variation with a lower value in the daytime and a higher value in the nighttime. The shorter aging time scale in the daytime is due to condensation aging associated with intense photochemical reaction while the longer aging time scale in the nighttime is due to coagulation aging, which is much slower than that due to condensation. In Beijing, the aging time scale is 2 h or less in the surface layer in daytime, which is far below the fixed 1.2 days used in many models. As a result, the fraction of hydrophilic BC particles by the new scheme is larger than that by the scheme with fixed aging time scale though the mean aging time scale by the new scheme is much larger than 1.2 days. Hydrophilic fraction of BC particles increases with the increase of height. Over central-eastern China, the averaged aging time scale calculated by the new scheme is in the range from 12 h to 7 days, with higher values in regions far from the source areas. Hydrophilic fraction of BC particles is more than 90% at the higher levels in polluted atmosphere. Difference of simulated BC concentration with internal mixing and microphysical aging is within 5%, indicating that the assumption of internal mixing for BC particles to respond to in-cloud scavenging is more appropriate than the external mixing assumption in polluted atmosphere over central-eastern China.