Regional Chemical Transport Model Research Articles

Potential impact of shipping on air pollution in the Mediterranean region – a multimodel evaluation: comparison of photooxidants NO2 and O3

Abstract. Shipping has a significant share in the emissions of air pollutants such as NOx and particulate matter (PM), and the global maritime transport volumes are projected to increase further in the future. The major route for short sea shipping within Europe and the main shipping route between Europe and East Asia are found in the Mediterranean Sea. Thus, it is a highly frequented shipping area, and high levels of air pollutants with significant potential impacts from shipping emissions are observed at monitoring stations in many cities along the Mediterranean coast. The present study is part of the EU H2020 project SCIPPER (Shipping contribution to Inland Pollution Push for the Enforcement of Regulations). Five different regional chemistry transport models (CAMx – Comprehensive Air Quality Model with Extensions, CHIMERE, CMAQ, EMEP – European Monitoring and Evaluation Programme, LOTOS-EUROS) were used to simulate the transport, chemical transformation and fate of atmospheric pollutants in the Mediterranean Sea for 2015. Shipping emissions were calculated with the Ship Traffic Emission Assessment Model (STEAM) version 3.3.0, and land-based emissions were taken from the CAMS-REG v2.2.1 dataset for a domain covering the Mediterranean Sea at a resolution of 12 km × 12 km (or 0.1∘×0.1∘). All models used their standard setup for further input. The potential impact of ships was calculated with the zero-out method. The model results were compared to each other and to measured background data at monitoring stations. The model results differ regarding the time series and pattern but are similar concerning the overall underestimation of NO2 and overestimation of O3. The potential impact from ships on the total NO2 concentration was especially high on the main shipping routes and in coastal regions (25 % to 85 %). The potential impact from ships on the total O3 concentration was lowest in regions with the highest NO2 impact (down to −20%). CAMx and CHIMERE simulated the highest potential impacts of ships on the NO2 and O3 air concentrations. Additionally, the strongest correlation was found between CAMx and CHIMERE, which can be traced back to the use of the same meteorological input data. The other models used different meteorological input due to their standard setup. The CMAQ-, EMEP- and LOTOS-EUROS-simulated values were within one range for the NO2 and O3 air concentrations. Regarding simulated deposition, larger differences between the models were found when compared to air concentration. These uncertainties and deviations between models are caused by deposition mechanisms, which are unique within each model. A reliable output from models simulating ships' potential impacts can be expected for air concentrations of NO2 and O3.

CO2 Flux Inversion With a Regional Joint Data Assimilation System Based on CMAQ, EnKS, and Surface Observations

AbstractMost of China's carbon sink inversion research uses global atmospheric transport models to assimilate natural fluxes, which quantifies the biosphere and ocean carbon budget with a relative coarse spatial resolution and long timescale from a weekly or monthly perspective. Toward high‐resolution inversion of CO2 fluxes, a novel carbon flux forecast model was developed in this study, which was then further used to carry out carbon assimilation based on a regional chemical transport model (CMAQ) at higher spatial (64 × 64 km2) and temporal (1 hr) resolutions. An Ensemble Kalman Smoother was applied as the assimilation algorithm and further extended to assimilate surface CO2 observations. Concentrations and fluxes were simultaneously assimilated as state variables to help reduce the uncertainty in the initial CO2 fields with the joint data assimilation framework (JDAS). In general, the posterior fluxes reproduced the seasonal, daily and hourly variation effectively, demonstrating the ability to fully absorb and utilize observations. Moreover, the influence of the choice of assimilation window on the carbon flux inversion was assessed via sensitivity experiments, revealing 36 hr to be the optimum length. Evaluation of the prior and posterior flux simulations also indicated that JDAS offers reasonable improvements, making it suitable for fine‐scale flux optimization and estimation. In addition, the posterior biosphere estimation in mainland China (−682 TgC yr−1) tends to be the optimal mathematical solution under current sparse observation coverage with daytime photosynthetic uptake, which likely leads to the overestimation of the optimized CO2 sink. This study serves as a basis for future regional and urban assessment.

Anthropogenic NOx Emission Estimations over East China for 2015 and 2019 Using OMI Satellite Observations and the New Inverse Modeling System CIF-CHIMERE

The Chinese government introduced regulations to control emissions and reduce the level of NOx pollutants for the first time with the 12th Five-Year Plan in 2011. Since then, the changes in NOx emissions have been assessed using various approaches to evaluate the impact of the regulations. Complementary to the previous studies, this study estimates anthropogenic NOx emissions in 2015 and 2019 over Eastern China using as a reference the Hemispheric Transport of Air Pollution (HTAP) v2.2 emission inventory for 2010 and the new variational inversion system the Community Inversion Framework (CIF) interfaced with the CHIMERE regional chemistry transport model and OMI satellite observations. We also compared the estimated NOx emissions with the independent Multi-resolution Emission Inventory for China (MEIC) v1.3, from 2015. The inversions show a slight global decrease in NOx emissions (in 2015 and 2019 compared to 2010), mainly limited to the most urbanized and industrialized locations. In the locations such as Baotou, Pearl River Delta, and Wuhan, the estimations in 2015 compared to 2010 are consistent with the target reduction (10%) of the 12th Five-Year Plan. Comparisons between our emission estimates and MEIC emissions in 2015 suggest that our estimates likely underestimate the emission reductions between 2010 and 2015 in the most polluted locations of Eastern China. However, our estimates suggest that the MEIC inventory overestimates emissions in regions where MEIC indicates an increase of the emissions compared to 2010.

GENerator of reduced Organic Aerosol mechanism (GENOA v1.0): an automatic generation tool of semi-explicit mechanisms

Abstract. This paper describes the GENerator of reduced Organic Aerosol mechanism (GENOA) that produces semi-explicit mechanisms for simulating the formation and evolution of secondary organic aerosol (SOA) in air quality models. Using a series of predefined reduction strategies and evaluation criteria, GENOA trains and reduces SOA mechanisms from near-explicit chemical mechanisms (e.g., the Master Chemical Mechanism – MCM) under representative atmospheric conditions. As a consequence, these trained SOA mechanisms can preserve the accuracy of detailed gas-phase chemical mechanisms on SOA formation (e.g., molecular structures of crucial organic compounds, the effect of “non-ideality”, and the hydrophilic/hydrophobic partitioning of aerosols), with a size (in terms of reaction and species numbers) that is manageable for three-dimensional (3-D) aerosol modeling (e.g., regional chemical transport models). Applied to the degradation of sesquiterpenes (as β-caryophyllene) from MCM, GENOA builds a concise SOA mechanism (2 % of the MCM size) that consists of 23 reactions and 15 species, with 6 of them being condensable. The generated SOA mechanism has been evaluated regarding its ability to reproduce SOA concentrations under the varying atmospheric conditions encountered over Europe, with an average error lower than 3 %.

Effects of chemical boundary conditions on simulated O3 concentrations in China and their chemical mechanisms

Chemical boundary conditions (BCs) are important inputs for regional chemical transport models. In this study, we use the brute-force method (BFM), process analysis (PA) and response surface model (RSM) to quantify the effects of BCs on simulated O3 concentrations in different regions of China by the weather research and forecasting with chemistry (WRF–Chem) model. We combine the model with an integrated gas-phase reaction rate (IRR) tool to further analyze the changes in the O3 chemical mechanisms. Our results show that the simulated O3 concentrations in western cities are significantly affected by the O3 in the BCs (BC-O3), which can increase the maximum simulated O3 concentration, such as in Lanzhou (36.6 μg/m3, 26.3 %), Wuhai (30.1 μg/m3, 25.5 %) and Urumqi (50.7 μg/m3, 41.2 %). In contrast, O3 generation in the eastern region is dominated by emissions. Subsequently, we compare the reaction rate changes in O3 generation and consumption under the effects of BC-O3 in the western city of Urumqi and the eastern city of Beijing. The results show that in Beijing, the O3 concentration and the related chemical reaction rates undergo little change, while in Urumqi, the concentration and reaction rates have significant differences. The BC-O3 significantly accelerates the O3 photochemical reaction process in Urumqi, resulting in increased O3 generation and consumption reaction rates; additionally, there may be a chemical reaction pathway for the formation of O3: BC-O3 + NO → NO2 + hv → O + O2 → O3. BC-O3 transmission is the main pathway of changes in the simulated O3 concentration in the study area, and the chemical reactions between BC-O3 and local pollutants are primarily characterized by O3 consumption. In conclusion, the study shows the importance of BCs for regional model simulation while providing supporting information for O3 formation in model studies.

Comparison and evaluation of updates to WRF-Chem (v3.9) biogenic emissions using MEGAN

Abstract. Biogenic volatile organic compounds (BVOCs) emitted from the natural ecosystem are highly reactive and can thus impact air quality and aerosol radiative forcing. BVOC emission models (e.g., Model of Emissions of Gases and Aerosols from Nature – MEGAN) in global and regional chemical transport models still have large uncertainties in estimating biogenic trace gases because of uncertainties in emission activity factors, specification of vegetation type, and plant emission factors. This study evaluates a set of updates made to MEGAN v2.04 in the Weather Research and Forecasting model coupled with chemistry (WRF-Chem version 3.9). Our study considers four simulations for each update made to MEGAN v2.04: (i) a control run with no changes to MEGAN, (ii) a simulation with the emission activity factors modified following MEGAN v2.10, (iii) a simulation considering the changes to the plant functional type (PFT) emission factor, and (iv) a simulation with the isoprene emission factor calculated within the MEGAN module instead of being prescribed by the input database. We evaluate two regions, Europe and the southeastern United States, by comparing WRF-Chem results to ground-based monitoring observations in Europe (i.e., AirBase database) and aircraft observations obtained during the NOMADSS field campaign. We find that the updates to MEGAN v2.04 in WRF-Chem caused overpredictions in ground-based ozone concentrations in Europe and in isoprene mixing ratios compared to aircraft observations in the southeastern US. The update in emission activity factors caused the largest biases. These results suggest that further experimental and modeling studies should be conducted to address potential shortcomings in BVOC emission models.

Understanding the Simulated Ammonia Increasing Trend from 2008 to 2015 over Europe with CHIMERE and Comparison with IASI Observations

The objective of this study is to assess and understand the NH3 recent trends and to identify the key components driving its concentrations. We have simulated the seasonal cycle, the interannual variability, and the trends in NH3 vertical column densities (VCD) from 2008 to 2015 over Europe, with the CHIMERE regional chemistry–transport model. We have also confronted the simulations against the Infrared Atmospheric Sounding Interferometer (IASI) satellite observations. IASI often shows a strong maximum in summer in addition to the spring peak, whereas CHIMERE only shows a slight peak in summer some years. This result could point to a misrepresentation of the temporal profile of the NH3 emissions, i.e., to missing emission sources during summertime either due to more than expected fertilizer use or to increased volatilization under warmer conditions. The simulated NH3 VCDs present an increasing trend over continental Europe (+2.7 ± 1.0 %/yr) but also at the national scale for Spain, Germany, UK, France, and Poland. Sensitivity tests indicate that these simulated positive trends are mainly due to (i) the trends in NH3 emissions, found heterogeneous in the EMEP NH3 emissions with strong disparities depending on the country, and (ii) the negative trends in NOx and SOx emissions. The impact of reductions in NO2 and SO2 emissions on NH3 concentrations should therefore be taken into account in future policies. This simulated NH3 VCD increase at the European scale is confirmed by IASI-v3R satellite observations in spring and summer, when ammonia emissions strongly contribute to the annual budget in accordance with crop requirements. Nevertheless, there are remaining differences about the significance and magnitude between the simulated and observed trends at the national scale, and it warrants further investigation.

Approximating Three‐Dimensional (3‐D) Transport of Atmospheric Pollutants via Deep Learning

AbstractThe physical transport process is the bottleneck of the computational efficiency in regional chemical transport modeling. The issue will be worse with the smaller time step due to increased iterations required with finer spatial resolution at scale. Reported surrogates of the transport process are usually unfeasible according to integrated assessment of efficiency promotion, long‐term consistency, and spatial dimensions. This study intended to approximate the three‐dimensional (3‐D) transport process (including advection and diffusion) of a state‐of‐the‐art chemical transport model, that is, Models 3/Community Multiscale Air Quality (CMAQ), via the U‐Net structure of deep learning. Two temporal resolutions of models with 1‐hr and 5‐min were developed. Validation results indicated that single‐step R squared of both models were higher than 0.9, and the lifetime for continuous running was 400 and 1,000 steps for 1‐hr and 5‐min model, respectively. Meanwhile, the computational efficiency can be promoted with the maximum of 164 times for 1‐hr and 14 times for 5‐min resolution on one GPU. The 1‐hr deep learning surrogate could still achieve 12 times acceleration on the same CPU configurations of CMAQ, mainly through the end‐to‐end direct inferring rather than time step iterations. This study preliminarily proves the feasibility of the data‐driven approach in approximating the 3‐D complex transport process of atmospheric pollutants. Furthermore, computational efficiency can be efficiently improved while maintaining consistency and accuracy. Rapid transport simulation of different pollutants with wide concentration range can be expected, which will finally benefit the acceleration of whole chemical transport modeling.

Surface PM2.5 mass concentrations during the dry season over northern Thailand: Sensitivity to model aerosol chemical schemes and the effects on regional meteorology

Biomass burning emissions (agriculture and forest) are one of the major contributors to air pollution over Thailand during the hot-dry season (March–April) and aerosols from biomass burning can adversely affect the weather and produce health effects (respiratory disease, heart disease etc.). The present study investigated the sensitivity of aerosol chemistry schemes (Goddard Chemistry Aerosol Radiation and Transport, GOCART; Model for Simulating Aerosol Interactions and Chemistry, MOSAIC) on spatio-temporal distributions of simulated PM2.5 (particle sizes <2.5 μm) mass concentrations. Also, the study looked into the impact of PM2.5 on meteorology during an intense biomass burning period (15 March – 15 April 2019) using an online regional chemical transport model, Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). PM2.5 mass concentrations were observed over the northern regions of Thailand varying from 40 to 240 μg m−3. The simulations using GOCART and MOSAIC aerosol scheme were able to capture the spatio-temporal variations of PM2.5 mass concentrations in general. However, it underestimated the observation magnitudes by about 24% and 27%, respectively. In addition, the sensitivy of EDGAR-HTAP (Emission Database for Global Atmospheric Research collaboratively with the task force for Hemispheric Transport of Air Pollution) and CAMS-GLOB-ANT (Copernicus Atmosphere Monitoring Service Global) anthropogenic emission inventories on PM2.5 mass were investigated using the model. The simulated aerosol mass concentrations from EDGAR-HTAP found more realistic emissions when compared to CAMS-GLOB-ANT in most of the regions. The discrepancy in the simulation of aerosol mass concentrations could be attributed to uncertainties in the emission inventories, weak representation of secondary aerosol compositions, as well as the overestimation of wind speed and wet scavenging in the model. The study also investigated the influence of aerosols on meteorology by comparing a simulation with aerosol-radiation-interaction to a simulation without aerosol-radiation-interaction in the atmosphere during the time period. Significant changes in meteorological parameters were observed over regions having higher aerosol mass concentrations with a reduction of about 26% in solar insolation, 3.9% in near surface temperature, 21% in planetary boundary layer height and an increase of 13% in relative humidity.

Regional impacts of black carbon morphologies on shortwave aerosol–radiation interactions: a comparative study between the US and China

Abstract. Black carbon (BC) is one of the dominant absorbing aerosol species in the atmosphere. It normally has complex fractal-like structures due to the aggregation process during combustion. A wide range of aerosol–radiation interactions (ARIs) of BC have been reported throughout experimental and modeling studies. One reason for the large discrepancies among multiple studies is the application of the oversimplified spherical morphology for BC in ARI estimates. In current climate models, the Mie theory is commonly used to calculate the optical properties of spherical BC aerosols. Here, we employ a regional chemical transport model coupled with a radiative transfer code that utilizes the non-spherical BC optical simulations to re-evaluate the effects of particles' morphologies on BC shortwave ARI, and the wavelength range of 0.3–4.0 µm was considered. Anthropogenic activities and wildfires are two major sources of BC emissions. Therefore, we choose the typical polluted area in eastern China, which is dominated by anthropogenic emissions, and the fire region in the northwest US, which is dominated by fire emissions in this study. A 1-month simulation in eastern China and a 7 d simulation in the fire region in the northwest US were performed. The fractal BC model generally presents a larger clear-sky ARI compared to the spherical BC model. Assuming BC particles are externally mixed with other aerosols, the relative differences in the time-averaged clear-sky ARI between the fractal model with a fractal dimension (Df) of 1.8 and the spherical model are 12.1 %–20.6 % and 10.5 %–14.9 % for typical polluted urban cities in China and fire sites in the northwest US, respectively. Furthermore, the regional-mean clear-sky ARI is also significantly affected by the BC morphology, and relative differences of 17.1 % and 38.7 % between the fractal model with a Df of 1.8 and the spherical model were observed in eastern China and the northwest US, respectively. However, the existence of clouds would weaken the BC morphological effects. The time-averaged all-sky ARI relative differences between the fractal model with a Df of 1.8 and the spherical model are 4.9 %–6.4 % and 9.0 %–11.3 % in typical urban polluted cities and typical fire sites, respectively. Besides, for the regional-mean all-sky ARI, the relative differences between the fractal model and the spherical model are less than 7.3 % and 16.8 % in the polluted urban area in China and the fire region in the US, respectively. The results imply that current climate modeling may significantly underestimate the BC ARI uncertainties as the morphological effects on BC ARI are ignored in most climate models.

Source and variability of formaldehyde (HCHO) at northern high latitudes: an integrated satellite, aircraft, and model study

Abstract. Here we use satellite observations of formaldehyde (HCHO) vertical column densities (VCD) from the TROPOspheric Monitoring Instrument (TROPOMI), aircraft measurements, combined with a nested regional chemical transport model (GEOS-Chem at 0.5×0.625∘ resolution), to better understand the variability and sources of summertime HCHO in Alaska. We first evaluate GEOS-Chem with in-situ airborne measurements during the Atmospheric Tomography Mission 1 (ATom-1) aircraft campaign. We show reasonable agreement between observed and modeled HCHO, isoprene, monoterpenes and the sum of methyl vinyl ketone and methacrolein (MVK+MACR) in the continental boundary layer. In particular, HCHO profiles show spatial homogeneity in Alaska, suggesting a minor contribution of biogenic emissions to HCHO VCD. We further examine the TROPOMI HCHO product in Alaska in summer, reprocessed by GEOS-Chem model output for a priori profiles and shape factors. For years with low wildfire activity (e.g., 2018), we find that HCHO VCDs are largely dominated by background HCHO (58 %–71 %), with minor contributions from wildfires (20 %–32 %) and biogenic VOC emissions (8 %–10 %). For years with intense wildfires (e.g., 2019), summertime HCHO VCD is dominated by wildfire emissions (50 %–72 %), with minor contributions from background (22 %–41 %) and biogenic VOCs (6 %–10 %). In particular, the model indicates a major contribution of wildfires from direct emissions of HCHO, instead of secondary production of HCHO from oxidation of larger VOCs. We find that the column contributed by biogenic VOC is often small and below the TROPOMI detection limit, in part due to the slow HCHO production from isoprene oxidation under low NOx conditions. This work highlights challenges for quantifying HCHO and its precursors in remote pristine regions.

The contribution of emission sources to the future air pollution disease burden in China

Air pollution exposure is a leading public health problem in China. Despite recent air quality improvements, fine particulate matter (PM2.5) exposure remains large, the associated disease burden is substantial, and population ageing is projected to increase the susceptibility to disease. Here, we used emulators of a regional chemical transport model to quantify the impacts of future emission scenarios on air pollution exposure in China. We estimated how key emission sectors contribute to these future health impacts from air pollution exposure. We found that PM2.5 exposure declines in all scenarios across China over 2020–2050, with reductions of 15% under current air quality legislation, 36% when exploiting the full potential of air pollutant emission reduction technologies, and 39% when that technical mitigation potential is combined with emission controls for climate mitigation. However, population ageing means that the PM2.5 disease burden under current legislation (CLE) increases by 17% in 2050 relative to 2020. In comparison to CLE in 2050, the application of the best air pollution technologies provides substantial health benefits, reducing the PM2.5 disease burden by 16%, avoiding 536 600 (95% uncertainty interval, 95UI: 497 800–573 300) premature deaths per year. These public health benefits are mainly due to reductions in industrial (43%) and residential (30%) emissions. Climate mitigation efforts combined with the best air pollution technologies leads to an additional 2% reduction in the PM2.5 disease burden, avoiding 57 000 (95UI: 52 800–61 100) premature deaths per year. Up to 90% of the 2020–2050 reductions in PM2.5 exposure are already achieved by 2030, assuming efficient implementation and enforcement of currently committed air quality policies in key sectors. Achieving reductions in PM2.5 exposure and the associated disease burden after 2030 will require further tightening of emission limits for regulated sectors, addressing other sources including agriculture and waste management, and international coordinated action to mitigate air pollution across Asia.

Investigating sources of surface ozone in central Europe during the hot summer in 2018: High temperatures, but not so high ozone

The changing emissions and climate have largely influenced the contribution of different sources on surface ozone, while the relations between the emissions, meteorological conditions and ozone sources are highly uncertain. In this study we modeled the sources of surface ozone in central Europe in the summer (June–July–August) of 2018, one of the warmest summers in Europe, with the regional chemical transport model CAMx and its source apportionment tool OSAT. Additional simulations with the anthropogenic emissions in 2000 were performed as high-emission scenarios to investigate the effects of reduced emissions on ozone sources, and a specific analysis on the coupled effects from meteorology was conducted based on measurements and backward trajectory calculations at three Swiss sites. The model results indicate that the highest contribution to summer afternoon surface ozone in Europe in 2018 comes from the boundary import (65%), followed by off-road traffic (11%) and road traffic (8%). Compared to the case using 2000 emissions, the lower emissions in 2018 lead to lower ozone in most of the areas in Europe except for some urban areas and shipping routes, and the highest decrease is from the road traffic for both the whole domain and the Swiss sites. The backward trajectory analysis at Swiss sites in 2000 (base year), 2003 (the warmest year) and 2018 (the 3rd warmest year) show that 2018 is the year with the highest fraction of air mass from the high ozone areas (from east in southern Switzerland and from north in northern Switzerland). The results indicate that the reduced anthropogenic emissions are the main reason responsible for the reduced high level ozone in the hot summer in central Europe.

Evaluation of modelled LOTOS-EUROS with observational based PM10 source attribution

Due to its serious health impact particulate matter is one of the air pollutants subject to abatement policies. Information on the main sources responsible for high concentrations of pollutants is therefore crucial to enable effective policy measures. In this study we compared two different methods for attribution of particulate matter concentrations to different sources: A tagging approach within the regional chemistry transport model LOTOS-EUROS and an observational method using speciated particulate matter observations and Positive Matrix Factorisation (PMF). The methods have been applied for winter 2016/2017 over Eastern Germany where in wintertime high woodburning emissions, cold temperatures and regular easterly winds can lead to a build-up of pollutant concentrations. The comparison allows the validation of the modelled source attribution for a selection of source categories. The contributions for biomass and total combustion compare well between both methods providing trust in the determined contributions, applied emissions including their timing. The total contribution from combustion is estimated between 3.3-7.7 μg/m3 (PMF) and 3.3-7.2 μg/m3 (LOTOS-EUROS) for the 9 stations incorporated in the study. The temporal Pearson correlation coefficient ranges between 0.3-0.64 for total combustion and 0.34 and 0.7 for biomass combustion. The mean absolute contributions for traffic at background stations also compare well with most values between 1.5-2.0 μg/m3 for PMF and 1–1.6 μg/m3 for LOTOS-EUROS. A lack of correlation for this contribution however suggests that the model has difficulty in representing the source category traffic in a time consistent manner and developments are needed to improve the temporal distribution of the traffic emissions within the model. The modelled particulate matter concentrations displayed a 20–40% underestimation of the observed concentrations with an increasing bias during high pollution events. The underestimation showed a high correlation with the observed contribution from combustion and secondary particulate matter including ammonium sulfate and organic carbon suggesting that at least a part of the missing mass in LOTOS-EUROS is related to transformation of volatile combustion emissions, likely from solid fuels, to secondary particle mass and missing enhanced formation of sulfate. Implementation of these missing processes would help to improve the source attribution of particulate matter with the LOTOS-EUROS model.

Atmospheric measurements at Mt. Tai – Part I: HONO formation and its role in the oxidizing capacity of the upper boundary layer

Abstract. A comprehensive field campaign, with measurements of HONO and related parameters, was conducted in summer 2018 at the foot (150 m a.s.l.) and the summit (1534 m a.s.l.) of Mt. Tai (Shandong province, China). At the summit station, high HONO mixing ratios were observed (mean ± 1σ: 133 ± 106 pptv, maximum: 880 pptv), with a diurnal noontime peak (mean ± 1σ: 133 ± 72 pptv at 12:30 local time). Constraints on the kinetics of aerosol-derived HONO sources (NO2 uptake on the aerosol surface and particulate nitrate photolysis) were performed and discussed, which enables a better understanding of the interaction of HONO and aerosols, especially in the polluted North China Plain. Various evidence of air mass transport from the ground to the summit level was provided. Furthermore, daytime HONO formation from different paths and its role in radical production were quantified and discussed. We found that the homogeneous reaction NO + OH could only explain 8.0 % of the daytime HONO formation, resulting in strong unknown sources (Pun). Campaigned-averaged Pun was about 290 ± 280 pptv h−1, with a maximum of about 1800 pptv h−1. Aerosol-derived HONO formation mechanisms were not the major sources of Pun at the summit station. Their contributions to daytime HONO formation varied from negligible to moderate (similar to NO + OH), depending on the chemical kinetic parameters used. Coupled with sensitivity tests on the kinetic parameters used, the NO2 uptake on the aerosol surface and particulate nitrate photolysis contributed 1.5 %–19 % and 0.6 %–9.6 % of the observed Pun, respectively. Based on synchronous measurements at the foot and the summit station, an amount of field evidence was proposed to support the finding that the remaining majority (70 %–98 %) of Pun was dominated by the rapid vertical transport from the ground to the summit level and heterogeneous formation on the mountain surfaces during transport. HONO photolysis at the summit level initialized daytime photochemistry and still represented an essential OH source in the daytime, with a contribution of about one-quarter of O3. We provided evidence that ground-derived HONO played a significant role in the oxidizing capacity of the upper boundary layer through the enhanced vertical air mass exchange driven by mountain winds. The follow-up impacts should be considered in regional chemistry transport models.

Contribution of traffic-originated nanoparticle emissions to regional and local aerosol levels

Abstract. Sub-50 nm particles originating from traffic emissions pose risks to human health due to their high lung deposition efficiency and potentially harmful chemical composition. We present a modeling study using an updated European Aerosol Cloud Climate and Air Quality Interactions (EUCAARI) number emission inventory, incorporating a more realistic, empirically justified particle size distribution (PSD) for sub-50 nm particles from road traffic as compared with the previous version. We present experimental PSDs and CO2 concentrations, measured in a highly trafficked street canyon in Helsinki, Finland, as an emission factor particle size distribution (EFPSD), which was then used in updating the EUCAARI inventory. We applied the updated inventory in a simulation using the regional chemical transport model PMCAMx-UF over Europe for May 2008. This was done to test the effect of updated emissions at regional and local scales, particularly in comparison with atmospheric new particle formation (NPF). Updating the inventory increased the simulated average total particle number concentrations by only 1 %, although the total particle number emissions were increased to a 3-fold level. The concentrations increased up to 11 % when only 1.3–3 nm sized particles (nanocluster aerosol, NCA) were considered. These values indicate that the effect of updating overall is insignificant at a regional scale during this photochemically active period. During this period, the fraction of the total particle number originating from atmospheric NPF processes was 91 %; thus, these simulations give a lower limit for the contribution of traffic to the aerosol levels. Nevertheless, the situation is different when examining the effect of the update closer spatially or temporally or when focusing on the chemical composition or the origin of the particles. For example, the daily average NCA concentrations increased by a factor of several hundred or thousand in some locations on certain days. Overall, the most significant effects – reaching several orders of magnitude – from updating the inventory are observed when examining specific particle sizes (especially 7–20 nm), particle components, and specific urban areas. While the model still has a tendency to predict more sub-50 nm particles compared to the observations, the most notable underestimations in the concentrations of sub-10 nm particles are now overcome. Additionally, the simulated distributions now agree better with the data observed at locations with high traffic densities. The findings of this study highlight the need to consider emissions, PSDs, and composition of sub-50 nm particles from road traffic in studies focusing on urban air quality. Updating this emission source brings the simulated aerosol levels, particularly in urban locations, closer to observations, which highlights its importance for calculations of human exposure to nanoparticles.

Impact of shipping emissions on air pollution and pollutant deposition over the Barents Sea

Arctic warming leading to reduced summertime sea-ice is likely to lead to increased local shipping especially along the Northeast Passage near the northern coasts of Norway and Russia, which are shorter than the traditional southerly routes. Here, the regional chemistry-transport model WRF-Chem is used to examine the effects of shipping emissions on levels of air pollutants and deposition fluxes over the Barents Sea both for present-day and future conditions, based on a high growth scenario. Present-day shipping emissions are found to have already substantial effects on ozone concentrations, but limited effects on sulphate and nitrate aerosols. Predicted future changes in ozone are also important, particularly in regions with low nitrogen oxide concentrations, and results are sensitive to the way in which diversion shipping is distributed due to non-linear effects on photochemical ozone production. Whilst modest future increases in sulphate and nitrate aerosols are predicted, large enhancements in dry deposition of sulphur dioxide and wet deposition of nitrogen compounds to the Barents Sea are predicted. Such levels of future nitrogen deposition would represent a significant atmospheric source of oceanic nitrogen affecting sensitive marine ecosystems.

The Modeling Study about Impacts of Emission Control Policies for Chinese 14th Five-Year Plan on PM2.5 and O3 in Yangtze River Delta, China

The Chinese government has made great efforts to combat air pollution through the reductions in SO2, NOx and VOCs emissions, as part of its socioeconomic Five-Year Plans (FYPs). China aims to further reduce the emissions of VOCs and NOx by 10% in its upcoming 14th FYP (2021–2025). Here, we used a regional chemical transport model (e.g., WRF/CMAQ) to examine the responses of PM2.5 and O3 to emission control policies of the 14th FYP in the Yangtze River Delta (YRD) region. The simulation results under the 4 emission control scenarios in the 2 winter months in 2025 indicate that the average concentrations of city mean PM2.5 in 41 cities in the YRD were predicted to only decrease by 10% under both S1 and S1_E scenarios, whereas the enhanced emission control scenarios (i.e., S2_E and S3_E) could reduce PM2.5 in each city by more than 20%. The model simulation results for O3 in the 3 summer months in 2025 show that the O3 responses to the emission controls under the S1 and S1_E scenarios show different control effects on O3 concentrations in the YRD with the increase and decrease effects, respectively. The study found that both enhanced emission control scenarios (S2_E and S3_E) could decrease O3 in each city by more than 20% with more reductions in O3 under the S3_E emission control scenario because of its higher control strengths for both NOx and VOCs emissions. It was found that emission reduction policies for controlling high emission sectors of NOx and VOCs such as S2_E and S3_E were more effective for decreasing both PM2.5 and O3 in the YRD. This study shows that O3 controls will benefit from well-designed air pollution control strategies for reasonable control ratios of NOx and VOCs emissions.

Estimating NOx LOTOS-EUROS CTM Emission Parameters over the Northwest of South America through 4DEnVar TROPOMI NO2 Assimilation

In this work, we present the development of a 4D-Ensemble-Variational (4DEnVar) data assimilation technique to estimate NOx top-down emissions using the regional chemical transport model LOTOS-EUROS with the NO2 observations from the TROPOspheric Monitoring Instrument (TROPOMI). The assimilation was performed for a domain in the northwest of South America centered over Colombia, and includes regions in Panama, Venezuela and Ecuador. In the 4DEnVar approach, the implementation of the linearized and adjoint model are avoided by generating an ensemble of model simulations and by using this ensemble to approximate the nonlinear model and observation operator. Emission correction parameters’ locations were defined for positions where the model simulations showed significant discrepancies with the satellite observations. Using the 4DEnVar data assimilation method, optimal emission parameters for the LOTOS-EUROS model were estimated, allowing for corrections in areas where ground observations are unavailable and the region’s emission inventories do not correctly reflect the current emissions activities. The analyzed 4DEnVar concentrations were compared with the ground measurements of one local air quality monitoring network and the data retrieved by the satellite instrument Ozone Monitoring Instrument (OMI). The assimilation had a low impact on NO2 surface concentrations reducing the Mean Fractional Bias from 0.45 to 0.32, primordially enhancing the spatial and temporal variations in the simulated NO2 fields.

Evaluation of Biogenic Organic Aerosols in the Amazon Rainforest Using WRF‐Chem With MOSAIC

AbstractBiogenic secondary organic aerosol (BSOA) accounts for 70%–80% of submicron aerosol over the Amazon rainforest. However, uncertainties with regard to the chemical formation pathway, mass budget, and radiative impact of BSOA in the region still remain high. To address the issue, we used a regional chemistry transport model (WRF‐Chem‐MOSAIC) to evaluate the budget of BSOA in the Amazon forest during the wet season (March) of 2014 when the air mass was clean from influences from anthropogenic and biomass burning emissions. We found that the default model underestimated the surface concentration of submicron organic aerosol (OA) by 57% at a ground measurement site (T3). We subsequently updated the WRF‐Chem‐MOSAIC model by including SOA formation from isoprene epoxydiols (IEPOX‐SOA) and SOA aging schemes. The updated model reproduced the observed submicron OA concentration well with an overestimation of only 2.5%. With the updated model, we will show that IEPOX‐SOA accounts for 23% of surface submicron OA averaged over the entire Amazon rainforest. The modeled surface SOA (smaller than 2.5 μm in diameter) concentration in the Amazon region was about a factor of 14 larger than the global mean. Finally, a sensitivity study was conducted which showed that convective plumes can remove more than 40% of submicron OA below 5 km in the Amazon region. Overall, our study highlights the importance of IEPOX chemistry as well as the convective removal processes in the global SOA budget.