Regional Chemical Transport Model Research Articles

Sensitivity of PBL parameterizations on PM10 and ozone simulation using chemical transport model WRF-Chem over a sub-tropical urban airshed in India

Meteorology plays vital role in predicting air quality parameters in regional chemical transport models. WRF-Chem is one such chemical transport model that includes various physics and chemistry options for simulating ozone and PM10 concentrations. In this study, WRF-Chem model was used to compare the performance of different Planetary Boundary Layer (PBL) parameterization namely, the Yonsei University (YSU) and Asymmetric Convective Model v2 (ACM2) PBL schemes, over the Delhi megacity urban airshed. Surface observations were used for comparisons and evaluating model performance for both meteorological and air quality variables. The ACM2 PBL scheme resulted in better model performance for simulating ozone and PM10 concentrations along with an improvement in temperature and wind speeds due to incorporation of both local and non-local characteristics. The dependency of ozone and PM10 concentrations on meteorological parameters temperature and wind speed were studied. The influence of PBL height and ventilation coefficient on model performance was analysed as dispersion of pollutants strongly depend on these factors. The PBL height was highly over estimated during evening hours which was also reflected in the corresponding ventilation coefficient values. Even though ACM2 PBL scheme was concluded as the best PBL scheme for the study region, it still requires significant improvement for simulating air quality parameters. Further, ozone and PM10 concentrations were scrutinized for varying ranges of temperature and wind speed. Model performance for ozone and PM10 concentrations was good for temperature values below 40 °C and wind speed ≤8 m/s. A poor model performance was observed for regions with high wind speed values. Even though certain limitations were observed in the model evaluation of PBL height and high wind speed values, WRF-Chem model can be effectively employed for simulating ozone and PM10 concentrations giving due considerations to limitations on high temperature and high wind speed regime.

Low-carbon energy generates public health savings in California

Abstract. California's goal to reduce greenhouse gas (GHG) emissions to a level that is 80 % below 1990 levels by the year 2050 will require adoption of low-carbon energy sources across all economic sectors. In addition to reducing GHG emissions, shifting to fuels with lower carbon intensity will change concentrations of short-lived conventional air pollutants, including airborne particles with a diameter of less than 2.5 µm (PM2.5) and ozone (O3). Here we evaluate how business-as-usual (BAU) air pollution and public health in California will be transformed in the year 2050 through the adoption of low-carbon technologies, expanded electrification, and modified activity patterns within a low-carbon energy scenario (GHG-Step). Both the BAU and GHG-Step statewide emission scenarios were constructed using the energy–economic optimization model, CA-TIMES, that calculates the multi-sector energy portfolio that meets projected energy supply and demand at the lowest cost, while also satisfying scenario-specific GHG emissions constraints. Corresponding criteria pollutant emissions for each scenario were then spatially allocated at 4 km resolution to support air quality analysis in different regions of the state. Meteorological inputs for the year 2054 were generated under a Representative Concentration Pathway (RCP) 8.5 future climate. Annual-average PM2.5 and O3 concentrations were predicted using the modified emissions and meteorology inputs with a regional chemical transport model. In the final phase of the analysis, mortality (total deaths) and mortality rate (deaths per 100 000) were calculated using established exposure-response relationships from air pollution epidemiology combined with simulated annual-average PM2.5 and O3 exposure. Net emissions reductions across all sectors are −36 % for PM0.1 mass, −3.6 % for PM2.5 mass, −10.6 % for PM2.5 elemental carbon, −13.3 % for PM2.5 organic carbon, −13.7 % for NOx, and −27.5 % for NH3. Predicted deaths associated with air pollution in 2050 dropped by 24–26 % in California (1537–2758 avoided deaths yr−1) in the climate-friendly 2050 GHG-Step scenario, which is equivalent to a 54–56 % reduction in the air pollution mortality rate (deaths per 100 000) relative to 2010 levels. These avoided deaths have an estimated value of USD 11.4–20.4 billion yr−1 based on the present-day value of a statistical life (VSL) equal to USD 7.6 million. The costs for reducing California GHG emissions 80 % below 1990 levels by the year 2050 depend strongly on numerous external factors such as the global price of oil. Best estimates suggest that meeting an intermediate target (40 % reduction in GHG emissions by the year 2030) using a non-optimized scenario would reduce personal income by USD 4.95 billion yr−1 (−0.15 %) and lower overall state gross domestic product by USD 16.1 billion yr−1 (−0.45 %). The public health benefits described here are comparable to these cost estimates, making a compelling argument for the adoption of low-carbon energy in California, with implications for other regions in the United States and across the world.

Evaluation of modeling NO<sub>2</sub> concentrations driven by satellite-derived and bottom-up emission inventories using in situ measurements over China

Abstract. Chemical transport models together with emission inventories are widely used to simulate NO2 concentrations over China, but validation of the simulations with in situ measurements has been extremely limited. Here we use ground measurements obtained from the air quality monitoring network recently developed by the Ministry of Environmental Protection of China to validate modeling surface NO2 concentrations from the CHIMERE regional chemical transport model driven by the satellite-derived DECSO and the bottom-up MIX emission inventories. We applied a correction factor to the observations to account for the interferences of other oxidized nitrogen compounds (NOz), based on the modeled ratio of NO2 to NOz. The model accurately reproduces the spatial variability in NO2 from in situ measurements, with a spatial correlation coefficient of over 0.7 for simulations based on both inventories. A negative and positive bias is found for the simulation with the DECSO (slope = 0.74 and 0.64 for the daily mean and daytime only) and the MIX (slope = 1.3 and 1.1) inventories, respectively, suggesting an underestimation and overestimation of NOx emissions from corresponding inventories. The bias between observed and modeled concentrations is reduced, with the slope dropping from 1.3 to 1.0 when the spatial distribution of NOx emissions in the DECSO inventory is applied as the spatial proxy for the MIX inventory, which suggests an improvement of the distribution of emissions between urban and suburban or rural areas in the DECSO inventory compared to that used in the bottom-up inventory. A rough estimate indicates that the observed concentrations, from sites predominantly placed in the populated urban areas, may be 10–40 % higher than the corresponding model grid cell mean. This reduces the estimate of the negative bias of the DECSO-based simulation to the range of −30 to 0 % on average and more firmly establishes that the MIX inventory is biased high over major cities. The performance of the model is comparable over seasons, with a slightly worse spatial correlation in summer due to the difficulties in resolving the more active NOx photochemistry and larger concentration gradients in summer by the model. In addition, the model well captures the daytime diurnal cycle but shows more significant disagreement between simulations and measurements during nighttime, which likely produces a positive model bias of about 15 % in the daily mean concentrations. This is most likely related to the uncertainty in vertical mixing in the model at night.

Ubiquitous influence of wildfire emissions and secondary organic aerosol on summertime atmospheric aerosol in the forested Great Lakes region

Abstract. Long-range aerosol transport affects locations hundreds of kilometers from the point of emission, leading to distant particle sources influencing rural environments that have few major local sources. Source apportionment was conducted using real-time aerosol chemistry measurements made in July 2014 at the forested University of Michigan Biological Station near Pellston, Michigan, a site representative of the remote forested Great Lakes region. Size-resolved chemical composition of individual 0.5–2.0 µm particles was measured using an aerosol time-of-flight mass spectrometer (ATOFMS), and non-refractory aerosol mass less than 1 µm (PM1) was measured with a high-resolution aerosol mass spectrometer (HR-AMS). The field site was influenced by air masses transporting Canadian wildfire emissions and urban pollution from Milwaukee and Chicago. During wildfire-influenced periods, 0.5–2.0 µm particles were primarily aged biomass burning particles (88 % by number). These particles were heavily coated with secondary organic aerosol (SOA) formed during transport, with organics (average O∕C ratio of 0.8) contributing 89 % of the PM1 mass. During urban-influenced periods, organic carbon, elemental carbon–organic carbon, and aged biomass burning particles were identified, with inorganic secondary species (ammonium, sulfate, and nitrate) contributing 41 % of the PM1 mass, indicative of atmospheric processing. With current models underpredicting organic carbon in this region and biomass burning being the largest combustion contributor to SOA by mass, these results highlight the importance for regional chemical transport models to accurately predict the impact of long-range transported particles on air quality in the upper Midwest, United States, particularly considering increasing intensity and frequency of Canadian wildfires.

Coupling of organic and inorganic aerosol systems and the effect on gas-particle partitioning in the southeastern US.

Several models were used to describe the partitioning of ammonia, water, and organic compounds between the gas and particle phases for conditions in the southeastern US during summer 2013. Existing equilibrium models and frameworks were found to be sufficient, although additional improvements in terms of estimating pure-species vapor pressures are needed. Thermodynamic model predictions were consistent, to first order, with a molar ratio of ammonium to sulfate of approximately 1.6 to 1.8 (ratio of ammonium to 2× sulfate, RN/2S ≈ 0.8 to 0.9) with approximately 70% of total ammonia and ammonium (NHx) in the particle. Southeastern Aerosol Research and Characterization Network (SEARCH) gas and aerosol and Southern Oxidant and Aerosol Study (SOAS) Monitor for AeRosols and Gases in Ambient air (MARGA) aerosol measurements were consistent with these conditions. CMAQv5.2 regional chemical transport model predictions did not reflect these conditions due to a factor of 3 overestimate of the nonvolatile cations. In addition, gas-phase ammonia was overestimated in the CMAQ model leading to an even lower fraction of total ammonia in the particle. Chemical Speciation Network (CSN) and aerosol mass spectrometer (AMS) measurements indicated less ammonium per sulfate than SEARCH and MARGA measurements and were inconsistent with thermodynamic model predictions. Organic compounds were predicted to be present to some extent in the same phase as inorganic constituents, modifying their activity and resulting in a decrease in [H+]air (H+ in μgm−3 air), increase in ammonia partitioning to the gas phase, and increase in pH compared to complete organic vs. inorganic liquid–liquid phase separation. In addition, accounting for nonideal mixing modified the pH such that a fully interactive inorganic–organic system had a pH roughly 0.7 units higher than predicted using traditional methods (pH = 1.5 vs. 0.7). Particle-phase interactions of organic and inorganic compounds were found to increase partitioning towards the particle phase (vs. gas phase) for highly oxygenated (O : C≥0.6) compounds including several isoprene-derived tracers as well as levoglu-cosan but decrease particle-phase partitioning for low O: C, monoterpene-derived species.

Impact of parameterization choices on the restitution of ozone deposition over vegetation

Ozone is a potentially phyto-toxic air pollutant, which can cause leaf damage and drastically alter crop yields, causing serious economic losses around the world. The VULNOZ (VULNerability to OZone in Anthropised Ecosystems) project is a biology and modeling project that aims to understand how plants respond to the stress of high ozone concentrations, then use a set of models to (i) predict the impact of ozone on plant growth, (ii) represent ozone deposition fluxes to vegetation, and finally (iii) estimate the economic consequences of an increasing ozone background the future.In this work, as part of the VULNOZ project, an innovative representation of ozone deposition to vegetation was developed and implemented in the CHIMERE regional chemistry-transport model. This type of model calculates the average amount of ozone deposited on a parcel each hour, as well as the integrated amount of ozone deposited to the surface at the regional or country level. Our new approach was based on a refinement of the representation of crop types in the model and the use of empirical parameters specific to each crop category. The results obtained were compared with a conventional ozone deposition modeling approach, and evaluated against observations from several agricultural areas in France. They showed that a better representation of the distribution between stomatal and non-stomatal ozone fluxes was obtained in the empirical approach, and they allowed us to produce a new estimate of the total amount of ozone deposited on the subtypes of vegetation at the national level.

Accounting for CO2 variability over East Asia with a regional joint inversion system and its preliminary evaluation

A regional surface carbon dioxide (CO2) flux inversion system, the Tan-Tracker-Region, was developed by incorporating an assimilation scheme into the Community Multiscale Air Quality (CMAQ) regional chemical transport model to resolve fine-scale CO2 variability over East Asia. The proper orthogonal decomposition-based ensemble four-dimensional variational data assimilation approach (POD-4DVar) is the core algorithm for the joint assimilation framework, and simultaneous assimilations of CO2 concentrations and surface CO2 fluxes are applied to help reduce the uncertainty in initial CO2 concentrations. A persistence dynamical model was developed to describe the evolution of the surface CO2 fluxes and help avoid the “signal-to-noise” problem; thus, CO2 fluxes could be estimated as a whole at the model grid scale, with better use of observation information. The performance of the regional inversion system was evaluated through a group of single-observation-based observing system simulation experiments (OSSEs). The results of the experiments suggest that a reliable performance of Tan-Tracker-Region is dependent on certain assimilation parameter choices, for example, an optimized window length of approximately 3 h, an ensemble size of approximately 100, and a covariance localization radius of approximately 320 km. This is probably due to the strong diurnal variation and spatial heterogeneity in the fine-scale CMAQ simulation, which could affect the performance of the regional inversion system. In addition, because all observations can be artificially obtained in OSSEs, the performance of Tan-Tracker-Region was further evaluated through different densities of the artificial observation network in different CO2 flux situations. The results indicate that more observation sites would be useful to systematically improve the estimation of CO2 concentration and flux in large areas over the model domain. The work presented here forms a foundation for future research in which a thorough estimation of CO2 flux variability over East Asia could be performed with the regional inversion system.

Pre-monsoon air quality over Lumbini, a world heritage site along the Himalayan foothills

Abstract. Lumbini, in southern Nepal, is a UNESCO world heritage site of universal value as the birthplace of Buddha. Poor air quality in Lumbini and surrounding regions is a great concern for public health as well as for preservation, protection and promotion of Buddhist heritage and culture. We present here results from measurements of ambient concentrations of key air pollutants (PM, BC, CO, O3) in Lumbini, first of its kind for Lumbini, conducted during an intensive measurement period of 3 months (April–June 2013) in the pre-monsoon season. The measurements were carried out as a part of the international air pollution measurement campaign; SusKat-ABC (Sustainable Atmosphere for the Kathmandu Valley – Atmospheric Brown Clouds). The main objective of this work is to understand and document the level of air pollution, diurnal characteristics and influence of open burning on air quality in Lumbini. The hourly average concentrations during the entire measurement campaign ranged as follows: BC was 0.3–30.0 µg m−3, PM1 was 3.6–197.6 µg m−3, PM2. 5 was 6.1–272.2 µg m−3, PM10 was 10.5–604.0 µg m−3, O3 was 1.0–118.1 ppbv and CO was 125.0–1430.0 ppbv. These levels are comparable to other very heavily polluted sites in South Asia. Higher fraction of coarse-mode PM was found as compared to other nearby sites in the Indo-Gangetic Plain region. The ΔBC ∕ ΔCO ratio obtained in Lumbini indicated considerable contributions of emissions from both residential and transportation sectors. The 24 h average PM2. 5 and PM10 concentrations exceeded the WHO guideline very frequently (94 and 85 % of the sampled period, respectively), which implies significant health risks for the residents and visitors in the region. These air pollutants exhibited clear diurnal cycles with high values in the morning and evening. During the study period, the worst air pollution episodes were mainly due to agro-residue burning and regional forest fires combined with meteorological conditions conducive of pollution transport to Lumbini. Fossil fuel combustion also contributed significantly, accounting for more than half of the ambient BC concentration according to aerosol spectral light absorption coefficients obtained in Lumbini. WRF-STEM, a regional chemical transport model, was used to simulate the meteorology and the concentrations of pollutants to understand the pollutant transport pathways. The model estimated values were ∼ 1. 5 to 5 times lower than the observed concentrations for CO and PM10, respectively. Model-simulated regionally tagged CO tracers showed that the majority of CO came from the upwind region of Ganges Valley. Model performance needs significant improvement in simulating aerosols in the region. Given the high air pollution level, there is a clear and urgent need for setting up a network of long-term air quality monitoring stations in the greater Lumbini region.

Possible climatic implications of high-altitude black carbon emissions

Abstract. On account of its strong absorption of solar and terrestrial radiation, black carbon (BC) aerosol is known to impact large-scale systems, such as the Asian monsoon and the Himalayan glaciers, in addition to affecting the thermal structure of the lower atmosphere. While most studies focus on the near-surface abundance and impacts of BC, our study examines the implications of sharp and confined layers of high BC concentration (called elevated BC layers) at altitudes more than 4 km over the Indian region using the online regional chemistry transport model (WRF-Chem) simulations. These elevated BC layers were revealed in the recent in situ measurements using high-altitude balloons carried out on 17 March 2010, 8 January 2011 and 25 April 2011. Our study demonstrates that high-flying aircraft (with emissions from the regionally fine-tuned MACCity inventory) are the most likely cause of these elevated BC layers. Furthermore, we show that such aircraft-emitted BC can be transported to upper tropospheric or lower stratospheric heights ( ∼ 17 km) aided by the strong monsoonal convection occurring over the region, which is known to overshoot the tropical tropopause, leading to the injection of tropospheric air mass (along with its constituent aerosols) into the stratosphere. We show observational evidence for such an intrusion of tropospheric BC into the stratosphere over the Indian region using extinction coefficient and particle depolarisation ratio data from CALIOP Lidar on-board the CALIPSO satellite. We hypothesise that such intrusions of BC into the lower stratosphere and its consequent longer residence time in the stratosphere have significant implications for stratospheric ozone, especially considering the already reported ozone-depleting potential of BC.

Quantifying black carbon deposition over the Greenland ice sheet from forest fires in Canada

AbstractBlack carbon (BC) concentrations observed in 22 snowpits sampled in the northwest sector of the Greenland ice sheet in April 2014 have allowed us to identify a strong and widespread BC aerosol deposition event, which was dated to have accumulated in the pits from two snow storms between 27 July and 2 August 2013. This event comprises a significant portion (57% on average across all pits) of total BC deposition over 10 months (July 2013 to April 2014). Here we link this deposition event to forest fires burning in Canada during summer 2013 using modeling and remote sensing tools. Aerosols were detected by both the Cloud‐Aerosol Lidar with Orthogonal Polarization (on board CALIPSO) and Moderate Resolution Imaging Spectroradiometer (Aqua) instruments during transport between Canada and Greenland. We use high‐resolution regional chemical transport modeling (WRF‐Chem) combined with high‐resolution fire emissions (FINNv1.5) to study aerosol emissions, transport, and deposition during this event. The model captures the timing of the BC deposition event and shows that fires in Canada were the main source of deposited BC. However, the model underpredicts BC deposition compared to measurements at all sites by a factor of 2–100. Underprediction of modeled BC deposition originates from uncertainties in fire emissions and model treatment of wet removal of aerosols. Improvements in model descriptions of precipitation scavenging and emissions from wildfires are needed to correctly predict deposition, which is critical for determining the climate impacts of aerosols that originate from fires.

Volatility-resolved source apportionment of primary and secondary organic aerosol over Europe

A three-dimensional regional chemical transport model (Particulate Matter Comprehensive Air Quality Model with Extensions, PMCAMx) was applied over Europe combined with a source apportionment algorithm, the Particulate Source Apportionment Technology (PSAT), in order to quantify the sources which contribute to the primary and secondary organic aerosol (OA) during different seasons. The PSAT algorithm was first extended to allow the quantification of the sources of OA as a function of volatility. The most significant OA sources during May were biogenic, while during February residential wood combustion and during September wildfires dominated. The contributions of the various sources have strong spatial dependence. Wildfires were significant OA sources (38% of the OA) for Russia during September, but had a much lower impact (5%) in Scandinavia. The above results are in general consistent with the findings of the CARBOSOL project for selected sites in Europe. For remote sites such as Finokalia in Crete, more than 90% of the OA has undergone two or more generations of oxidation for all seasons. This highly processed oxidized OA is predicted to also dominate over much of Europe during the summer and fall. The first generation SOA is predicted to represent 20–30% of the OA in central and northern Europe during these photochemically active periods.

Large biogenic contribution to boundary layer O3‐CO regression slope in summer

AbstractStrong correlation between O3 and CO was observed during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER‐AQ) aircraft experiment in July 2011 over the Washington‐Baltimore area. The observed correlation does not vary significantly with time or altitude in the boundary layer. The observations are simulated well by a regional chemical transport model. We analyze the model results to understand the factors contributing to the observed O3‐CO regression slope, which has been used in past studies to estimate the anthropogenic O3 production amount. We trace separately four different CO sources: primary anthropogenic emissions, oxidation of anthropogenic volatile organic compounds, oxidation of biogenic isoprene, and transport from the lateral and upper model boundaries. Modeling analysis suggests that the contribution from biogenic isoprene oxidation to the observed O3‐CO regression slope is as large as that from primary anthropogenic CO emissions. As a result of decrease of anthropogenic primary CO emissions during the past decades, biogenic CO from oxidation of isoprene is increasingly important. Consequently, observed and simulated O3‐CO regression slopes can no longer be used directly with an anthropogenic CO emission inventory to quantify anthropogenic O3 production over the United States. The consistent enhancement of O3 relative to CO observed in the boundary layer, as indicated by the O3‐CO regression slope, provides a useful constraint on model photochemistry and emissions.

The effect of entrainment through atmospheric boundary layer growth on observed and modeled surface ozone in the Colorado Front Range

AbstractOzone concentrations at the Earth's surface are controlled by meteorological and chemical processes and are a function of advection, entrainment, deposition, and net chemical production/loss. The relative contributions of these processes vary in time and space. Understanding the relative importance of these processes controlling surface ozone concentrations is an essential component for designing effective regulatory strategies. Here we focus on the diurnal cycle of entrainment through atmospheric boundary layer (ABL) growth in the Colorado Front Range. Aircraft soundings and surface observations collected in July/August 2014 during the DISCOVER‐AQ/FRAPPÉ (Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality/Front Range Air Pollution and Photochemistry Éxperiment) campaigns and equivalent data simulated by a regional chemical transport model are analyzed. Entrainment through ABL growth is most important in the early morning, fumigating the surface at a rate of ~5 ppbv/h. The fumigation effect weakens near noon and changes sign to become a small dilution effect in the afternoon on the order of −1 ppbv/h. The chemical transport model WRF‐Chem (Weather Research and Forecasting Model with chemistry) underestimates ozone at all altitudes during this study on the order of 10–15 ppbv. The entrainment through ABL growth is overestimated by the model in the order of 0.6–0.8 ppbv/h. This results from differences in boundary layer growth in the morning and ozone concentration jump across the ABL top in the afternoon. This implicates stronger modeled fumigation in the morning and weaker modeled dilution after 11:00 LT.

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.

CMAQ simulation of atmospheric CO2 concentration in East Asia: Comparison with GOSAT observations and ground measurements

Satellite observations are widely used in global CO2 assimilations, but their quality for use in regional assimilation systems has not yet been thoroughly determined. Validation of satellite observations and model simulations of CO2 is crucial for carbon flux inversions. In this study, we focus on evaluating the uncertainties of model simulations and satellite observations. The atmospheric CO2 distribution in East Asia during 2012 was simulated using a regional chemical transport model (RAMS-CMAQ) and compared with both CO2 column density (XCO2) from the Gases Observing SATellite (GOSAT) and CO2 concentrations from the World Data Centre for Greenhouse Gases (WDCGG). The results indicate that simulated XCO2 is generally lower than GOSAT XCO2 by 1.19 ppm on average, and their monthly differences vary from 0.05 to 2.84 ppm, with the corresponding correlation coefficients ranging between 0.1 and 0.67. CMAQ simulations are good to capture the CO2 variation as ground-based observations, and their correlation coefficients are from 0.62 to 0.93, but the average value of CMAQ simulation is 2.4 ppm higher than ground-based observation. Thus, we inferred that the GOSAT retrievals may overestimate XCO2, which is consistent with the validation of GOSAT XCO2 using Total Carbon Column Observing Network measurements. The near-surface CO2 concentration was obviously overestimated in GOSAT XCO2. Compared with the relatively small difference between CMAQ and GOSAT XCO2, the large difference in CO2 near surface or their vertical profiles indicates more improvements are needed to reduce the uncertainties in both satellite observations and model simulations.

Nitrate transboundary heavy pollution over East Asia in winter

Abstract. High PM2. 5 concentrations of around 100 µg m−3 were observed twice during an intensive observation campaign in January 2015 at Fukuoka (33.52° N, 130.47° E) in western Japan. These events were analyzed comprehensively with a regional chemical transport model and synergetic ground-based observations with state-of-the-art measurement systems, which can capture the behavior of secondary inorganic aerosols (SO42−, NO3−, and NH4+). The first episode of high PM2. 5 concentration was dominated by NO3− (type N) and the second episode by SO42− (type S). The concentration of NH4+ (the counterion for SO42− and NO3−) was high for both types. A sensitivity simulation in the chemical transport model showed that the dominant contribution was from transboundary air pollution for both types. To investigate the differences between these types further, the chemical transport model results were examined, and a backward trajectory analysis was used to provide additional information. During both types of episodes, high concentrations of NO3− were found above China, and an air mass that originated from northeast China reached Fukuoka. The travel time from the coastline of China to Fukuoka differed between types: it was 18 h for type N and 24 h for type S. The conversion ratio of SO2 to SO42− (Fs) was less than 0.1 for type N, but reached 0.3 for type S as the air mass approached Fukuoka. The higher Fs for type S was related to the higher relative humidity and the concentration of HO2, which produces H2O2, the most effective oxidant for the aqueous-phase production of SO42−. Analyzing the gas ratio as an indicator of the sensitivity of NO3− to changes in SO42− and NH4+ showed that the air mass over China was NH3-rich for type N, but almost NH3-neutral for type S. Thus, although the high concentration of NO3− above China gradually decreased during transport from China to Fukuoka, higher NO3− concentrations were maintained during transport owing to the lower SO42− for type N. In contrast, for type S, the production of SO42− led to the decomposition of NH4NO3, and more SO42− was transported. Notably, the type N transport pattern was limited to western Japan, especially the island of Kyushu. Transboundary air pollution dominated by SO42− (type S) has been recognized as a major pattern of pollution over East Asia. However, our study confirms the importance of transboundary air pollution dominated by NO3−, which will help refine our understanding of transboundary heavy PM2. 5 pollution in winter over East Asia.

Aerosol–radiation interaction modelling using online coupling between the WRF 3.7.1 meteorological model and the CHIMERE 2016 chemistry-transport model, through the OASIS3-MCT coupler

Abstract. The presence of airborne aerosols affects the meteorology as it induces a perturbation in the radiation budget, the number of cloud condensation nuclei and the cloud micro-physics. Those effects are difficult to model at regional scale as regional chemistry-transport models are usually driven by a distinct meteorological model or data. In this paper, the coupling of the CHIMERE chemistry-transport model with the WRF meteorological model using the OASIS3-MCT coupler is presented. WRF meteorological fields along with CHIMERE aerosol optical properties are exchanged through the coupler at a high frequency in order to model the aerosol–radiation interactions. The WRF-CHIMERE online model has a higher computational burden than both models run separately in offline mode (up to 42 % higher). This is mainly due to some additional computations made within the models such as more frequent calls to meteorology treatment routines or calls to optical properties computation routines. On the other hand, the overall time required to perform the OASIS3-MCT exchanges is not significant compared to the total duration of the simulations. The impact of the coupling is evaluated on a case study over Europe, northern Africa, the Middle East and western Asia during the summer of 2012, through comparisons of the offline and two online simulations (with and without the aerosol optical properties feedback) to observations of temperature, aerosol optical depth (AOD) and surface PM10 (particulate matter with diameters lower than 10 µm) concentrations. The result shows that using the optical properties feedback induces a radiative forcing (average forcing of −4.8 W m−2) which creates a perturbation in the average surface temperatures over desert areas (up to 2.6° locally) along with an increase in both AOD and PM10 concentrations.

Particulate matter air pollution in Europe in a +2 °C warming world

In the framework of the IMPACT2C project, we have evaluated the future European particulate matter concentrations under the influence of climate change and anthropogenic emission reductions. To do so, 30-year simulations for present and future scenarios were performed with an ensemble of four regional Chemical Transport Models. +2 °C scenarios were issued from different regional climate simulations belonging to the CORDEX experiment (RCP4.5 scenario). Comparing present day simulations to observations shows that these simulations meet the requested quality criteria even if some biases do exist. Also, we showed that using regional climate models instead of meteorological reanalysis was not critical for the quality of our simulations. Present day as well as future scenarios show the large variability between models associated with different meteorology and process parameterizations. Future projections of PM concentrations show a large reduction of PM10 and PM2.5 concentrations in a +2 °C climate over the European continent (especially over Benelux), which can be mostly attributed to emission reduction policies. Under a current legislation scenario, annual PM10 could be reduced by between 1.8 and 2.9 μg m−3 (14.1–20.4%). If maximum technologically feasible emission reductions were implemented, further reductions of 1.4–1.9 μg m−3 (18.6–20.9%) are highlighted. Changes due to a +2 °C warming, in isolation from emission changes, are in general much weaker (−1.1 to +0.4 μg m−3,-0.3 to +5.1% for annual PM10 averaged over the European domain). Even if large differences exist between models, we have determined that the decrease of PM over Europe associated with emission reduction is a robust result. The patterns of PM changes resulting from climate change (for example the increase of PM over Spain and southern France and the decrease of PM10 over eastern Europe) are also robustly predicted even if its amplitude remains weak compared to changes associated with emission reductions.

Air pollution impacts due to petroleum extraction in the Norwegian Sea during the ACCESS aircraft campaign

Emissions from oil/gas extraction activities in the Arctic are already important in certain regions and may increase as global warming opens up new opportunities for industrial development. Emissions from oil/gas extraction are sources of air pollutants, but large uncertainties exist with regard to their amounts and composition. In this study, we focus on detailed investigation of emissions from oil/gas extraction in the Norwegian Sea combining measurements from the EU ACCESS aircraft campaign in July 2012 and regional chemical transport modeling. The goal is to (1) evaluate emissions from petroleum extraction activities and (2) investigate their impact on atmospheric composition over the Norwegian Sea. Numerical simulations include emissions for permanently operating offshore facilities from two datasets: the TNO-MACC inventory and emissions reported by Norwegian Environment Agency (NEA). It was necessary to additionally estimate primary aerosol emissions using reported emission factors since these emissions are not included in the inventories for our sites. Model runs with the TNO-MACC emissions are unable to reproduce observations close to the facilities. Runs using the NEA emissions more closely reproduce the observations although emissions from mobile facilities are missing from this inventory. Measured plumes suggest they are a significant source of pollutants, in particular NOx and aerosols. Sensitivities to NOx and NMVOC emissions show that, close to the platforms, O3 is sensitive to NOx emissions and is much less sensitive to NMVOC emissions. O3 destruction, via reaction with NO, dominates very close to the platforms. Far from the platforms, oil/gas facility emissions result in an average daytime O3 enhancement of +2% at the surface. Larger enhancements are predicted at noon ranging from +7% at the surface to +15% at 600 m. Black carbon is the aerosol species most strongly influenced by petroleum extraction emissions. The results highlight significant uncertainties in emissions related to petroleum extraction emissions in the Arctic.

Capability and Remaining Issues of Regional Chemical Transport Models

Capability and Remaining Issues of Regional Chemical Transport Models