Articles | Volume 14, issue 8
https://doi.org/10.5194/gmd-14-5001-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-5001-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
iNRACM: incorporating 15N into the Regional Atmospheric Chemistry Mechanism (RACM) for assessing the role photochemistry plays in controlling the isotopic composition of NOx, NOy, and atmospheric nitrate
Huan Fang
Department of Earth, Atmospheric, and Planetary Sciences, Purdue University, West Lafayette, IN, USA
Wendell W. Walters
Institute for Environment and Society, Brown University, Providence RI, USA
David Mase
Department of Earth, Atmospheric, and Planetary Sciences, Purdue University, West Lafayette, IN, USA
Department of Earth, Atmospheric, and Planetary Sciences, Purdue University, West Lafayette, IN, USA
Department of Chemistry, Purdue University, West Lafayette, IN, USA
Related authors
Huan Fang and Greg Michalski
Geosci. Model Dev., 15, 4239–4258, https://doi.org/10.5194/gmd-15-4239-2022, https://doi.org/10.5194/gmd-15-4239-2022, 2022
Short summary
Short summary
A new emission input dataset that incorporates nitrogen isotopes has been used in the CMAQ (Community Multiscale Air Quality) modeling system simulation to qualitatively analyze the changes in δ15N values, due to the dispersion, mixing, and transport of the atmospheric NOx emitted from different sources. The dispersion, mixing, and transport of the atmospheric NOx were based on the meteorology files generated from the WRF (Weather Research and Forecasting) model.
Huan Fang and Greg Michalski
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-322, https://doi.org/10.5194/gmd-2020-322, 2020
Publication in GMD not foreseen
Short summary
Short summary
A new emission input dataset that incorporates nitrogen isotopes has been developed to simulate isotope tracers in air pollution. The NOx emission from different sources simulated by Sparse Matrix Operator Kerner Emissions (SMOKE) were replicated using 15N. The dataset is able to predict δ15N variations in NOx that are similar to those observed in aerosol and gases in the troposphere.
Wendell W. Walters, Masayuki Takeuchi, Nga L. Ng, and Meredith G. Hastings
Geosci. Model Dev., 17, 4673–4687, https://doi.org/10.5194/gmd-17-4673-2024, https://doi.org/10.5194/gmd-17-4673-2024, 2024
Short summary
Short summary
The study introduces a novel chemical mechanism for explicitly tracking oxygen isotope transfer in oxidized reactive nitrogen and odd oxygen using the Regional Atmospheric Chemistry Mechanism, version 2. This model enhances our ability to simulate and compare oxygen isotope compositions of reactive nitrogen, revealing insights into oxidation chemistry. The approach shows promise for improving atmospheric chemistry models and tropospheric oxidation capacity predictions.
Claire Bekker, Wendell W. Walters, Lee T. Murray, and Meredith G. Hastings
Atmos. Chem. Phys., 23, 4185–4201, https://doi.org/10.5194/acp-23-4185-2023, https://doi.org/10.5194/acp-23-4185-2023, 2023
Short summary
Short summary
Nitrate is a critical component of the atmosphere that degrades air quality and ecosystem health. We have investigated the nitrogen isotope compositions of nitrate from deposition samples collected across the northeastern United States. Spatiotemporal variability in the nitrogen isotope compositions was found to track with nitrate formation chemistry. Our results highlight that nitrogen isotope compositions may be a robust tool for improving model representation of nitrate chemistry.
Heejeong Kim, Wendell W. Walters, Claire Bekker, Lee T. Murray, and Meredith G. Hastings
Atmos. Chem. Phys., 23, 4203–4219, https://doi.org/10.5194/acp-23-4203-2023, https://doi.org/10.5194/acp-23-4203-2023, 2023
Short summary
Short summary
Atmospheric nitrate has an important impact on human and ecosystem health. We evaluated atmospheric nitrate formation pathways in the northeastern US utilizing oxygen isotope compositions, which indicated a significant difference between the phases of nitrate (i.e., gas vs. particle). Comparing the observations with model simulations indicated that N2O5 hydrolysis chemistry was overpredicted. Our study has important implications for improving atmospheric chemistry model representation.
Wendell W. Walters, Madeline Karod, Emma Willcocks, Bok H. Baek, Danielle E. Blum, and Meredith G. Hastings
Atmos. Chem. Phys., 22, 13431–13448, https://doi.org/10.5194/acp-22-13431-2022, https://doi.org/10.5194/acp-22-13431-2022, 2022
Short summary
Short summary
Atmospheric ammonia and its products are a significant source of urban haze and nitrogen deposition. We have investigated the seasonal source contributions to a mid-sized city in the northeastern US megalopolis utilizing geospatial statistical analysis and novel isotopic constraints, which indicate that vehicle emissions were significant components of the urban-reduced nitrogen budget. Reducing vehicle ammonia emissions should be considered to improve ecosystems and human health.
Huan Fang and Greg Michalski
Geosci. Model Dev., 15, 4239–4258, https://doi.org/10.5194/gmd-15-4239-2022, https://doi.org/10.5194/gmd-15-4239-2022, 2022
Short summary
Short summary
A new emission input dataset that incorporates nitrogen isotopes has been used in the CMAQ (Community Multiscale Air Quality) modeling system simulation to qualitatively analyze the changes in δ15N values, due to the dispersion, mixing, and transport of the atmospheric NOx emitted from different sources. The dispersion, mixing, and transport of the atmospheric NOx were based on the meteorology files generated from the WRF (Weather Research and Forecasting) model.
Jiajue Chai, Jack E. Dibb, Bruce E. Anderson, Claire Bekker, Danielle E. Blum, Eric Heim, Carolyn E. Jordan, Emily E. Joyce, Jackson H. Kaspari, Hannah Munro, Wendell W. Walters, and Meredith G. Hastings
Atmos. Chem. Phys., 21, 13077–13098, https://doi.org/10.5194/acp-21-13077-2021, https://doi.org/10.5194/acp-21-13077-2021, 2021
Short summary
Short summary
Nitrous acid (HONO) derived from wildfire emissions plays a key role in controlling atmospheric oxidation chemistry. However, the HONO budget remains poorly constrained. By combining the field-observed concentrations and novel isotopic composition (N and O) of HONO and nitrogen oxides (NOx), we quantitatively constrained the relative contribution of each pathway to secondary HONO production and the relative importance of major atmospheric oxidants (ozone versus peroxy) in aged wildfire smoke.
Huan Fang and Greg Michalski
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-322, https://doi.org/10.5194/gmd-2020-322, 2020
Publication in GMD not foreseen
Short summary
Short summary
A new emission input dataset that incorporates nitrogen isotopes has been developed to simulate isotope tracers in air pollution. The NOx emission from different sources simulated by Sparse Matrix Operator Kerner Emissions (SMOKE) were replicated using 15N. The dataset is able to predict δ15N variations in NOx that are similar to those observed in aerosol and gases in the troposphere.
Wendell W. Walters, Linlin Song, Jiajue Chai, Yunting Fang, Nadia Colombi, and Meredith G. Hastings
Atmos. Chem. Phys., 20, 11551–11567, https://doi.org/10.5194/acp-20-11551-2020, https://doi.org/10.5194/acp-20-11551-2020, 2020
Short summary
Short summary
This article details new field observations of the nitrogen stable isotopic composition of ammonia emitted from vehicles conducted in the US and China. Vehicle emissions of ammonia may be a significant source to urban regions with important human health and environmental implications. Our measurements have indicated a consistent isotopic signature from vehicle ammonia emissions. The nitrogen isotopic composition of ammonia may be a useful tool for tracking vehicle emissions.
Jianghanyang Li, Xuan Zhang, John Orlando, Geoffrey Tyndall, and Greg Michalski
Atmos. Chem. Phys., 20, 9805–9819, https://doi.org/10.5194/acp-20-9805-2020, https://doi.org/10.5194/acp-20-9805-2020, 2020
Short summary
Short summary
Nitrogen isotopic compositions of atmospheric reactive nitrogen are widely used to infer their sources. However, the reactions between NO and NO2 strongly impact their isotopes, which was not well understood. We conducted a series of experiments in an atmospheric simulation chamber to determine the isotopic effects of (1) direct isotopic exchange between NO and NO2 and (2) the isotopic fractionations during NOx photochemistry, then developed an equation to quantify the overall isotopic effect.
G. Michalski, S. K. Bhattacharya, and G. Girsch
Atmos. Chem. Phys., 14, 4935–4953, https://doi.org/10.5194/acp-14-4935-2014, https://doi.org/10.5194/acp-14-4935-2014, 2014
Related subject area
Atmospheric sciences
Incorporating Oxygen Isotopes of Oxidized Reactive Nitrogen in the Regional Atmospheric Chemistry Mechanism, version 2 (ICOIN-RACM2)
A general comprehensive evaluation method for cross-scale precipitation forecasts
Implementation of a Simple Actuator Disk for Large-Eddy Simulation in the Weather Research and Forecasting Model (WRF-SADLES v1.2) for wind turbine wake simulation
WRF-PDAF v1.0: implementation and application of an online localized ensemble data assimilation framework
Implementation and evaluation of diabatic advection in the Lagrangian transport model MPTRAC 2.6
An improved and extended parameterization of the CO2 15 µm cooling in the middle and upper atmosphere (CO2_cool_fort-1.0)
Development of a multiphase chemical mechanism to improve secondary organic aerosol formation in CAABA/MECCA (version 4.7.0)
Application of regional meteorology and air quality models based on the microprocessor without interlocked piped stages (MIPS) and LoongArch CPU platforms
Investigating ground-level ozone pollution in semi-arid and arid regions of Arizona using WRF-Chem v4.4 modeling
An objective identification technique for potential vorticity structures associated with African easterly waves
Importance of microphysical settings for climate forcing by stratospheric SO2 injections as modeled by SOCOL-AERv2
Assessment of surface ozone products from downscaled CAMS reanalysis and CAMS daily forecast using urban air quality monitoring stations in Iran
Open boundary conditions for atmospheric large-eddy simulations and their implementation in DALES4.4
Efficient and stable coupling of the SuperdropNet deep-learning-based cloud microphysics (v0.1.0) with the ICON climate and weather model (v2.6.5)
Three-dimensional variational assimilation with a multivariate background error covariance for the Model for Prediction Across Scales – Atmosphere with the Joint Effort for Data assimilation Integration (JEDI-MPAS 2.0.0-beta)
FUME 2.0 – Flexible Universal processor for Modeling Emissions
DEUCE v1.0: a neural network for probabilistic precipitation nowcasting with aleatoric and epistemic uncertainties
Evaluation of multi-season convection-permitting atmosphere – mixed-layer ocean simulations of the Maritime Continent
Investigating the impact of coupling HARMONIE-WINS50 (cy43) meteorology to LOTOS-EUROS (v2.2.002) on a simulation of NO2 concentrations over the Netherlands
Balloon drift estimation and improved position estimates for radiosondes
Emission ensemble approach to improve the development of multi-scale emission inventories
What is the relative impact of nudging and online coupling on meteorological variables, pollutant concentrations and aerosol optical properties?
Diagnosing drivers of PM2.5 simulation biases in China from meteorology, chemical composition, and emission sources using an efficient machine learning method
Validation and analysis of the Polair3D v1.11 chemical transport model over Quebec
Assimilation of GNSS tropospheric gradients into the Weather Research and Forecasting (WRF) model version 4.4.1
Identifying atmospheric rivers and their poleward latent heat transport with generalizable neural networks: ARCNNv1
Assessing acetone for the GISS ModelE2.1 Earth system model
Bergen metrics: composite error metrics for assessing performance of climate models using EURO-CORDEX simulations
A dynamic approach to three-dimensional radiative transfer in subkilometer-scale numerical weather prediction models: the dynamic TenStream solver v1.0
Evaluation and development of surface layer scheme representation of temperature inversions over boreal forests in Arctic wintertime conditions
Modelling wind farm effects in HARMONIE–AROME (cycle 43.2.2) – Part 1: Implementation and evaluation
Analytical and adaptable initial conditions for dry and moist baroclinic waves in the global hydrostatic model OpenIFS (CY43R3)
Challenges of constructing and selecting the “perfect” boundary conditions for the large-eddy simulation model PALM
A machine learning approach for evaluating Southern Ocean cloud radiative biases in a global atmosphere model
Decision Support System version 1.0 (DSS v1.0) for air quality management in Delhi, India
How non-equilibrium aerosol chemistry impacts particle acidity: the GMXe AERosol CHEMistry (GMXe–AERCHEM, v1.0) sub-submodel of MESSy
A grid model for vertical correction of precipitable water vapor over the Chinese mainland and surrounding areas using random forest
MEXPLORER 1.0.0 – a mechanism explorer for analysis and visualization of chemical reaction pathways based on graph theory
Evaluating CHASER V4.0 global formaldehyde (HCHO) simulations using satellite, aircraft, and ground-based remote sensing observations
Advances and prospects of deep learning for medium-range extreme weather forecasting
An overview of the Western United States Dynamically Downscaled Dataset (WUS-D3)
cloudbandPy 1.0: an automated algorithm for the detection of tropical–extratropical cloud bands
PyRTlib: an educational Python-based library for non-scattering atmospheric microwave radiative transfer computations
Deep learning applied to CO2 power plant emissions quantification using simulated satellite images
Sensitivity of the WRF-Chem v4.4 simulations of ozone and formaldehyde and their precursors to multiple bottom-up emission inventories over East Asia during the KORUS-AQ 2016 field campaign
Optimising urban measurement networks for CO2 flux estimation: a high-resolution observing system simulation experiment using GRAMM/GRAL
Assessment of climate biases in OpenIFS version 43r3 across model horizontal resolutions and time steps
High-resolution multi-scaling of outdoor human thermal comfort and its intra-urban variability based on machine learning
Effects of vertical grid spacing on the climate simulated in the ICON-Sapphire global storm-resolving model
Development of the tangent linear and adjoint models of the global online chemical transport model MPAS-CO2 v7.3
Wendell W. Walters, Masayuki Takeuchi, Nga L. Ng, and Meredith G. Hastings
Geosci. Model Dev., 17, 4673–4687, https://doi.org/10.5194/gmd-17-4673-2024, https://doi.org/10.5194/gmd-17-4673-2024, 2024
Short summary
Short summary
The study introduces a novel chemical mechanism for explicitly tracking oxygen isotope transfer in oxidized reactive nitrogen and odd oxygen using the Regional Atmospheric Chemistry Mechanism, version 2. This model enhances our ability to simulate and compare oxygen isotope compositions of reactive nitrogen, revealing insights into oxidation chemistry. The approach shows promise for improving atmospheric chemistry models and tropospheric oxidation capacity predictions.
Bing Zhang, Mingjian Zeng, Anning Huang, Zhengkun Qin, Couhua Liu, Wenru Shi, Xin Li, Kefeng Zhu, Chunlei Gu, and Jialing Zhou
Geosci. Model Dev., 17, 4579–4601, https://doi.org/10.5194/gmd-17-4579-2024, https://doi.org/10.5194/gmd-17-4579-2024, 2024
Short summary
Short summary
By directly analyzing the proximity of precipitation forecasts and observations, a precipitation accuracy score (PAS) method was constructed. This method does not utilize a traditional contingency-table-based classification verification; however, it can replace the threat score (TS), equitable threat score (ETS), and other skill score methods, and it can be used to calculate the accuracy of numerical models or quantitative precipitation forecasts.
Hai Bui, Mostafa Bakhoday-Paskyabi, and Mohammadreza Mohammadpour-Penchah
Geosci. Model Dev., 17, 4447–4465, https://doi.org/10.5194/gmd-17-4447-2024, https://doi.org/10.5194/gmd-17-4447-2024, 2024
Short summary
Short summary
We developed a new wind turbine wake model, the Simple Actuator Disc for Large Eddy Simulation (SADLES), integrated with the widely used Weather Research and Forecasting (WRF) model. WRF-SADLES accurately simulates wind turbine wakes at resolutions of a few dozen meters, aligning well with idealized simulations and observational measurements. This makes WRF-SADLES a promising tool for wind energy research, offering a balance between accuracy, computational efficiency, and ease of implementation.
Changliang Shao and Lars Nerger
Geosci. Model Dev., 17, 4433–4445, https://doi.org/10.5194/gmd-17-4433-2024, https://doi.org/10.5194/gmd-17-4433-2024, 2024
Short summary
Short summary
This paper introduces and evaluates WRF-PDAF, a fully online-coupled ensemble data assimilation (DA) system. A key advantage of the WRF-PDAF configuration is its ability to concurrently integrate all ensemble states, eliminating the need for time-consuming distribution and collection of ensembles during the coupling communication. The extra time required for DA amounts to only 20.6 % per cycle. Twin experiment results underscore the effectiveness of the WRF-PDAF system.
Jan Clemens, Lars Hoffmann, Bärbel Vogel, Sabine Grießbach, and Nicole Thomas
Geosci. Model Dev., 17, 4467–4493, https://doi.org/10.5194/gmd-17-4467-2024, https://doi.org/10.5194/gmd-17-4467-2024, 2024
Short summary
Short summary
Lagrangian transport models simulate the transport of air masses in the atmosphere. For example, one model (CLaMS) is well suited to calculating transport as it uses a special coordinate system and special vertical wind. However, it only runs inefficiently on modern supercomputers. Hence, we have implemented the benefits of CLaMS into a new model (MPTRAC), which is already highly efficient on modern supercomputers. Finally, in extensive tests, we showed that CLaMS and MPTRAC agree very well.
Manuel López-Puertas, Federico Fabiano, Victor Fomichev, Bernd Funke, and Daniel R. Marsh
Geosci. Model Dev., 17, 4401–4432, https://doi.org/10.5194/gmd-17-4401-2024, https://doi.org/10.5194/gmd-17-4401-2024, 2024
Short summary
Short summary
The radiative infrared cooling of CO2 in the middle atmosphere is crucial for computing its thermal structure. It requires one however to include non-local thermodynamic equilibrium processes which are computationally very expensive, which cannot be afforded by climate models. In this work, we present an updated, efficient, accurate and very fast (~50 µs) parameterization of that cooling able to cope with CO2 abundances from half the pre-industrial values to 10 times the current abundance.
Felix Wieser, Rolf Sander, Changmin Cho, Hendrik Fuchs, Thorsten Hohaus, Anna Novelli, Ralf Tillmann, and Domenico Taraborrelli
Geosci. Model Dev., 17, 4311–4330, https://doi.org/10.5194/gmd-17-4311-2024, https://doi.org/10.5194/gmd-17-4311-2024, 2024
Short summary
Short summary
The chemistry scheme of the atmospheric box model CAABA/MECCA is expanded to achieve an improved aerosol formation from emitted organic compounds. In addition to newly added reactions, temperature-dependent partitioning of all new species between the gas and aqueous phases is estimated and included in the pre-existing scheme. Sensitivity runs show an overestimation of key compounds from isoprene, which can be explained by a lack of aqueous-phase degradation reactions and box model limitations.
Zehua Bai, Qizhong Wu, Kai Cao, Yiming Sun, and Huaqiong Cheng
Geosci. Model Dev., 17, 4383–4399, https://doi.org/10.5194/gmd-17-4383-2024, https://doi.org/10.5194/gmd-17-4383-2024, 2024
Short summary
Short summary
There is relatively limited research on the application of scientific computing on RISC CPU platforms. The MIPS architecture CPUs, a type of RISC CPUs, have distinct advantages in energy efficiency and scalability. The air quality modeling system can run stably on the MIPS and LoongArch platforms, and the experiment results verify the stability of scientific computing on the platforms. The work provides a technical foundation for the scientific application based on MIPS and LoongArch.
Yafang Guo, Chayan Roychoudhury, Mohammad Amin Mirrezaei, Rajesh Kumar, Armin Sorooshian, and Avelino F. Arellano
Geosci. Model Dev., 17, 4331–4353, https://doi.org/10.5194/gmd-17-4331-2024, https://doi.org/10.5194/gmd-17-4331-2024, 2024
Short summary
Short summary
This research focuses on surface ozone (O3) pollution in Arizona, a historically air-quality-challenged arid and semi-arid region in the US. The unique characteristics of this kind of region, e.g., intense heat, minimal moisture, and persistent desert shrubs, play a vital role in comprehending O3 exceedances. Using the WRF-Chem model, we analyzed O3 levels in the pre-monsoon month, revealing the model's skill in capturing diurnal and MDA8 O3 levels.
Christoph Fischer, Andreas H. Fink, Elmar Schömer, Marc Rautenhaus, and Michael Riemer
Geosci. Model Dev., 17, 4213–4228, https://doi.org/10.5194/gmd-17-4213-2024, https://doi.org/10.5194/gmd-17-4213-2024, 2024
Short summary
Short summary
This study presents a method for identifying and tracking 3-D potential vorticity structures within African easterly waves (AEWs). Each identified structure is characterized by descriptors, including its 3-D position and orientation, which have been validated through composite comparisons. A trough-centric perspective on the descriptors reveals the evolution and distinct characteristics of AEWs. These descriptors serve as valuable statistical inputs for the study of AEW-related phenomena.
Sandro Vattioni, Andrea Stenke, Beiping Luo, Gabriel Chiodo, Timofei Sukhodolov, Elia Wunderlin, and Thomas Peter
Geosci. Model Dev., 17, 4181–4197, https://doi.org/10.5194/gmd-17-4181-2024, https://doi.org/10.5194/gmd-17-4181-2024, 2024
Short summary
Short summary
We investigate the sensitivity of aerosol size distributions in the presence of strong SO2 injections for climate interventions or after volcanic eruptions to the call sequence and frequency of the routines for nucleation and condensation in sectional aerosol models with operator splitting. Using the aerosol–chemistry–climate model SOCOL-AERv2, we show that the radiative and chemical outputs are sensitive to these settings at high H2SO4 supersaturations and how to obtain reliable results.
Najmeh Kaffashzadeh and Abbas-Ali Aliakbari Bidokhti
Geosci. Model Dev., 17, 4155–4179, https://doi.org/10.5194/gmd-17-4155-2024, https://doi.org/10.5194/gmd-17-4155-2024, 2024
Short summary
Short summary
This paper assesses the capability of two state-of-the-art global datasets in simulating surface ozone over Iran using a new methodology. It is found that the global model data need to be downscaled for regulatory purposes or policy applications at local scales. The method can be useful not only for the evaluation but also for the prediction of other chemical species, such as aerosols.
Franciscus Liqui Lung, Christian Jakob, A. Pier Siebesma, and Fredrik Jansson
Geosci. Model Dev., 17, 4053–4076, https://doi.org/10.5194/gmd-17-4053-2024, https://doi.org/10.5194/gmd-17-4053-2024, 2024
Short summary
Short summary
Traditionally, high-resolution atmospheric models employ periodic boundary conditions, which limit simulations to domains without horizontal variations. In this research open boundary conditions are developed to replace the periodic boundary conditions. The implementation is tested in a controlled setup, and the results show minimal disturbances. Using these boundary conditions, high-resolution models can be forced by a coarser model to study atmospheric phenomena in realistic background states.
Caroline Arnold, Shivani Sharma, Tobias Weigel, and David S. Greenberg
Geosci. Model Dev., 17, 4017–4029, https://doi.org/10.5194/gmd-17-4017-2024, https://doi.org/10.5194/gmd-17-4017-2024, 2024
Short summary
Short summary
In atmospheric models, rain formation is simplified to be computationally efficient. We trained a machine learning model, SuperdropNet, to emulate warm-rain formation based on super-droplet simulations. Here, we couple SuperdropNet with an atmospheric model in a warm-bubble experiment and find that the coupled simulation runs stable and produces reasonable results, making SuperdropNet a viable ML proxy for droplet simulations. We also present a comprehensive benchmark for coupling architectures.
Byoung-Joo Jung, Benjamin Ménétrier, Chris Snyder, Zhiquan Liu, Jonathan J. Guerrette, Junmei Ban, Ivette Hernández Baños, Yonggang G. Yu, and William C. Skamarock
Geosci. Model Dev., 17, 3879–3895, https://doi.org/10.5194/gmd-17-3879-2024, https://doi.org/10.5194/gmd-17-3879-2024, 2024
Short summary
Short summary
We describe the multivariate static background error covariance (B) for the JEDI-MPAS 3D-Var data assimilation system. With tuned B parameters, the multivariate B gives physically balanced analysis increment fields in the single-observation test framework. In the month-long cycling experiment with a global 60 km mesh, 3D-Var with static B performs stably. Due to its simple workflow and minimal computational requirements, JEDI-MPAS 3D-Var can be useful for the research community.
Michal Belda, Nina Benešová, Jaroslav Resler, Peter Huszár, Ondřej Vlček, Pavel Krč, Jan Karlický, Pavel Juruš, and Kryštof Eben
Geosci. Model Dev., 17, 3867–3878, https://doi.org/10.5194/gmd-17-3867-2024, https://doi.org/10.5194/gmd-17-3867-2024, 2024
Short summary
Short summary
For modeling atmospheric chemistry, it is necessary to provide data on emissions of pollutants. These can come from various sources and in various forms, and preprocessing of the data to be ingestible by chemistry models can be quite challenging. We developed the FUME processor to use a database layer that internally transforms all input data into a rigid structure, facilitating further processing to allow for emission processing from the continental to the street scale.
Bent Harnist, Seppo Pulkkinen, and Terhi Mäkinen
Geosci. Model Dev., 17, 3839–3866, https://doi.org/10.5194/gmd-17-3839-2024, https://doi.org/10.5194/gmd-17-3839-2024, 2024
Short summary
Short summary
Probabilistic precipitation nowcasting (local forecasting for 0–6 h) is crucial for reducing damage from events like flash floods. For this goal, we propose the DEUCE neural-network-based model which uses data and model uncertainties to generate an ensemble of potential precipitation development scenarios for the next hour. Trained and evaluated with Finnish precipitation composites, DEUCE was found to produce more skillful and reliable nowcasts than established models.
Emma Howard, Steven Woolnough, Nicholas Klingaman, Daniel Shipley, Claudio Sanchez, Simon C. Peatman, Cathryn E. Birch, and Adrian J. Matthews
Geosci. Model Dev., 17, 3815–3837, https://doi.org/10.5194/gmd-17-3815-2024, https://doi.org/10.5194/gmd-17-3815-2024, 2024
Short summary
Short summary
This paper describes a coupled atmosphere–mixed-layer ocean simulation setup that will be used to study weather processes in Southeast Asia. The set-up has been used to compare high-resolution simulations, which are able to partially resolve storms, to coarser simulations, which cannot. We compare the model performance at representing variability of rainfall and sea surface temperatures across length scales between the coarse and fine models.
Andrés Yarce Botero, Michiel van Weele, Arjo Segers, Pier Siebesma, and Henk Eskes
Geosci. Model Dev., 17, 3765–3781, https://doi.org/10.5194/gmd-17-3765-2024, https://doi.org/10.5194/gmd-17-3765-2024, 2024
Short summary
Short summary
HARMONIE WINS50 reanalysis data with 0.025° × 0.025° resolution from 2019 to 2021 were coupled with the LOTOS-EUROS Chemical Transport Model. HARMONIE and ECMWF meteorology configurations against Cabauw observations (52.0° N, 4.9° W) were evaluated as simulated NO2 concentrations with ground-level sensors. Differences in crucial meteorological input parameters (boundary layer height, vertical diffusion coefficient) between the hydrostatic and non-hydrostatic models were analysed.
Ulrich Voggenberger, Leopold Haimberger, Federico Ambrogi, and Paul Poli
Geosci. Model Dev., 17, 3783–3799, https://doi.org/10.5194/gmd-17-3783-2024, https://doi.org/10.5194/gmd-17-3783-2024, 2024
Short summary
Short summary
This paper presents a method for calculating balloon drift from historical radiosonde ascent data. The drift can reach distances of several hundred kilometres and is often neglected. Verification shows the beneficial impact of the more accurate balloon position on model assimilation. The method is not limited to radiosondes but would also work for dropsondes, ozonesondes, or any other in situ sonde carried by the wind in the pre-GNSS era, provided the necessary information is available.
Philippe Thunis, Jeroen Kuenen, Enrico Pisoni, Bertrand Bessagnet, Manjola Banja, Lech Gawuc, Karol Szymankiewicz, Diego Guizardi, Monica Crippa, Susana Lopez-Aparicio, Marc Guevara, Alexander De Meij, Sabine Schindlbacher, and Alain Clappier
Geosci. Model Dev., 17, 3631–3643, https://doi.org/10.5194/gmd-17-3631-2024, https://doi.org/10.5194/gmd-17-3631-2024, 2024
Short summary
Short summary
An ensemble emission inventory is created with the aim of monitoring the status and progress made with the development of EU-wide inventories. This emission ensemble serves as a common benchmark for the screening and allows for the comparison of more than two inventories at a time. Because the emission “truth” is unknown, the approach does not tell which inventory is the closest to reality, but it identifies inconsistencies that require special attention.
Laurent Menut, Bertrand Bessagnet, Arineh Cholakian, Guillaume Siour, Sylvain Mailler, and Romain Pennel
Geosci. Model Dev., 17, 3645–3665, https://doi.org/10.5194/gmd-17-3645-2024, https://doi.org/10.5194/gmd-17-3645-2024, 2024
Short summary
Short summary
This study is about the modelling of the atmospheric composition in Europe during the summer of 2022, when massive wildfires were observed. It is a sensitivity study dedicated to the relative impacts of two modelling processes that are able to modify the meteorology used for the calculation of the atmospheric chemistry and transport of pollutants.
Shuai Wang, Mengyuan Zhang, Yueqi Gao, Peng Wang, Qingyan Fu, and Hongliang Zhang
Geosci. Model Dev., 17, 3617–3629, https://doi.org/10.5194/gmd-17-3617-2024, https://doi.org/10.5194/gmd-17-3617-2024, 2024
Short summary
Short summary
Numerical models are widely used in air pollution modeling but suffer from significant biases. The machine learning model designed in this study shows high efficiency in identifying such biases. Meteorology (relative humidity and cloud cover), chemical composition (secondary organic components and dust aerosols), and emission sources (residential activities) are diagnosed as the main drivers of bias in modeling PM2.5, a typical air pollutant. The results will help to improve numerical models.
Shoma Yamanouchi, Shayamilla Mahagammulla Gamage, Sara Torbatian, Jad Zalzal, Laura Minet, Audrey Smargiassi, Ying Liu, Ling Liu, Forood Azargoshasbi, Jinwoong Kim, Youngseob Kim, Daniel Yazgi, and Marianne Hatzopoulou
Geosci. Model Dev., 17, 3579–3597, https://doi.org/10.5194/gmd-17-3579-2024, https://doi.org/10.5194/gmd-17-3579-2024, 2024
Short summary
Short summary
Air pollution is a major health hazard, and chemical transport models (CTMs) are valuable tools that aid in our understanding of the risks of air pollution at both local and regional scales. In this study, the Polair3D CTM of the Polyphemus air quality modeling platform was set up over Quebec, Canada, to assess the model’s capability in predicting key air pollutant species over the region, at seasonal temporal scales and at regional spatial scales.
Rohith Thundathil, Florian Zus, Galina Dick, and Jens Wickert
Geosci. Model Dev., 17, 3599–3616, https://doi.org/10.5194/gmd-17-3599-2024, https://doi.org/10.5194/gmd-17-3599-2024, 2024
Short summary
Short summary
Global Navigation Satellite Systems (GNSS) provides moisture observations through its densely distributed ground station network. In this research, we assimilate a new type of observation called tropospheric gradient observations, which has never been incorporated into a weather model. We develop a forward operator for gradient-based observations and conduct an assimilation impact study. The study shows significant improvements in the model's humidity fields.
Ankur Mahesh, Travis A. O'Brien, Burlen Loring, Abdelrahman Elbashandy, William Boos, and William D. Collins
Geosci. Model Dev., 17, 3533–3557, https://doi.org/10.5194/gmd-17-3533-2024, https://doi.org/10.5194/gmd-17-3533-2024, 2024
Short summary
Short summary
Atmospheric rivers (ARs) are extreme weather events that can alleviate drought or cause billions of US dollars in flood damage. We train convolutional neural networks (CNNs) to detect ARs with an estimate of the uncertainty. We present a framework to generalize these CNNs to a variety of datasets of past, present, and future climate. Using a simplified simulation of the Earth's atmosphere, we validate the CNNs. We explore the role of ARs in maintaining energy balance in the Earth system.
Alexandra Rivera, Kostas Tsigaridis, Gregory Faluvegi, and Drew Shindell
Geosci. Model Dev., 17, 3487–3505, https://doi.org/10.5194/gmd-17-3487-2024, https://doi.org/10.5194/gmd-17-3487-2024, 2024
Short summary
Short summary
This paper describes and evaluates an improvement to the representation of acetone in the GISS ModelE2.1 Earth system model. We simulate acetone's concentration and transport across the atmosphere as well as its dependence on chemistry, the ocean, and various global emissions. Comparisons of our model’s estimates to past modeling studies and field measurements have shown encouraging results. Ultimately, this paper contributes to a broader understanding of acetone's role in the atmosphere.
Alok K. Samantaray, Priscilla A. Mooney, and Carla A. Vivacqua
Geosci. Model Dev., 17, 3321–3339, https://doi.org/10.5194/gmd-17-3321-2024, https://doi.org/10.5194/gmd-17-3321-2024, 2024
Short summary
Short summary
Any interpretation of climate model data requires a comprehensive evaluation of the model performance. Numerous error metrics exist for this purpose, and each focuses on a specific aspect of the relationship between reference and model data. Thus, a comprehensive evaluation demands the use of multiple error metrics. However, this can lead to confusion. We propose a clustering technique to reduce the number of error metrics needed and a composite error metric to simplify the interpretation.
Richard Maier, Fabian Jakub, Claudia Emde, Mihail Manev, Aiko Voigt, and Bernhard Mayer
Geosci. Model Dev., 17, 3357–3383, https://doi.org/10.5194/gmd-17-3357-2024, https://doi.org/10.5194/gmd-17-3357-2024, 2024
Short summary
Short summary
Based on the TenStream solver, we present a new method to accelerate 3D radiative transfer towards the speed of currently used 1D solvers. Using a shallow-cumulus-cloud time series, we evaluate the performance of this new solver in terms of both speed and accuracy. Compared to a 3D benchmark simulation, we show that our new solver is able to determine much more accurate irradiances and heating rates than a 1D δ-Eddington solver, even when operated with a similar computational demand.
Julia Maillard, Jean-Christophe Raut, and François Ravetta
Geosci. Model Dev., 17, 3303–3320, https://doi.org/10.5194/gmd-17-3303-2024, https://doi.org/10.5194/gmd-17-3303-2024, 2024
Short summary
Short summary
Atmospheric models struggle to reproduce the strong temperature inversions in the vicinity of the surface over forested areas in the Arctic winter. In this paper, we develop modified simplified versions of surface layer schemes widely used by the community. Our modifications are used to correct the fact that original schemes place strong limits on the turbulent collapse, leading to a lower surface temperature gradient at low wind speeds. Modified versions show a better performance.
Jana Fischereit, Henrik Vedel, Xiaoli Guo Larsén, Natalie E. Theeuwes, Gregor Giebel, and Eigil Kaas
Geosci. Model Dev., 17, 2855–2875, https://doi.org/10.5194/gmd-17-2855-2024, https://doi.org/10.5194/gmd-17-2855-2024, 2024
Short summary
Short summary
Wind farms impact local wind and turbulence. To incorporate these effects in weather forecasting, the explicit wake parameterization (EWP) is added to the forecasting model HARMONIE–AROME. We evaluate EWP using flight data above and downstream of wind farms, comparing it with an alternative wind farm parameterization and another weather model. Results affirm the correct implementation of EWP, emphasizing the necessity of accounting for wind farm effects in accurate weather forecasting.
Clément Bouvier, Daan van den Broek, Madeleine Ekblom, and Victoria A. Sinclair
Geosci. Model Dev., 17, 2961–2986, https://doi.org/10.5194/gmd-17-2961-2024, https://doi.org/10.5194/gmd-17-2961-2024, 2024
Short summary
Short summary
An analytical initial background state has been developed for moist baroclinic wave simulation on an aquaplanet and implemented into OpenIFS. Seven parameters can be controlled, which are used to generate the background states and the development of baroclinic waves. The meteorological and numerical stability has been assessed. Resulting baroclinic waves have proven to be realistic and sensitive to the jet's width.
Jelena Radović, Michal Belda, Jaroslav Resler, Kryštof Eben, Martin Bureš, Jan Geletič, Pavel Krč, Hynek Řezníček, and Vladimír Fuka
Geosci. Model Dev., 17, 2901–2927, https://doi.org/10.5194/gmd-17-2901-2024, https://doi.org/10.5194/gmd-17-2901-2024, 2024
Short summary
Short summary
Boundary conditions are of crucial importance for numerical model (e.g., PALM) validation studies and have a large influence on the model results, especially when studying the atmosphere of real, complex, and densely built urban environments. Our experiments with different driving conditions for the large-eddy simulation model PALM show its strong dependency on boundary conditions, which is important for the proper separation of errors coming from the boundary conditions and the model itself.
Sonya L. Fiddes, Marc D. Mallet, Alain Protat, Matthew T. Woodhouse, Simon P. Alexander, and Kalli Furtado
Geosci. Model Dev., 17, 2641–2662, https://doi.org/10.5194/gmd-17-2641-2024, https://doi.org/10.5194/gmd-17-2641-2024, 2024
Short summary
Short summary
In this study we present an evaluation that considers complex, non-linear systems in a holistic manner. This study uses XGBoost, a machine learning algorithm, to predict the simulated Southern Ocean shortwave radiation bias in the ACCESS model using cloud property biases as predictors. We then used a novel feature importance analysis to quantify the role that each cloud bias plays in predicting the radiative bias, laying the foundation for advanced Earth system model evaluation and development.
Gaurav Govardhan, Sachin D. Ghude, Rajesh Kumar, Sumit Sharma, Preeti Gunwani, Chinmay Jena, Prafull Yadav, Shubhangi Ingle, Sreyashi Debnath, Pooja Pawar, Prodip Acharja, Rajmal Jat, Gayatry Kalita, Rupal Ambulkar, Santosh Kulkarni, Akshara Kaginalkar, Vijay K. Soni, Ravi S. Nanjundiah, and Madhavan Rajeevan
Geosci. Model Dev., 17, 2617–2640, https://doi.org/10.5194/gmd-17-2617-2024, https://doi.org/10.5194/gmd-17-2617-2024, 2024
Short summary
Short summary
A newly developed air quality forecasting framework, Decision Support System (DSS), for air quality management in Delhi, India, provides source attribution with numerous emission reduction scenarios besides forecasts. DSS shows that during post-monsoon and winter seasons, Delhi and its neighboring districts contribute to 30 %–40 % each to pollution in Delhi. On average, a 40 % reduction in the emissions in Delhi and the surrounding districts would result in a 24 % reduction in Delhi's pollution.
Simon Rosanka, Holger Tost, Rolf Sander, Patrick Jöckel, Astrid Kerkweg, and Domenico Taraborrelli
Geosci. Model Dev., 17, 2597–2615, https://doi.org/10.5194/gmd-17-2597-2024, https://doi.org/10.5194/gmd-17-2597-2024, 2024
Short summary
Short summary
The capabilities of the Modular Earth Submodel System (MESSy) are extended to account for non-equilibrium aqueous-phase chemistry in the representation of deliquescent aerosols. When applying the new development in a global simulation, we find that MESSy's bias in modelling routinely observed reduced inorganic aerosol mass concentrations, especially in the United States. Furthermore, the representation of fine-aerosol pH is particularly improved in the marine boundary layer.
Junyu Li, Yuxin Wang, Lilong Liu, Yibin Yao, Liangke Huang, and Feijuan Li
Geosci. Model Dev., 17, 2569–2581, https://doi.org/10.5194/gmd-17-2569-2024, https://doi.org/10.5194/gmd-17-2569-2024, 2024
Short summary
Short summary
In this study, we have developed a model (RF-PWV) to characterize precipitable water vapor (PWV) variation with altitude in the study area. RF-PWV can significantly reduce errors in vertical correction, enhance PWV fusion product accuracy, and provide insights into PWV vertical distribution, thereby contributing to climate research.
Rolf Sander
Geosci. Model Dev., 17, 2419–2425, https://doi.org/10.5194/gmd-17-2419-2024, https://doi.org/10.5194/gmd-17-2419-2024, 2024
Short summary
Short summary
The open-source software MEXPLORER 1.0.0 is presented here. The program can be used to analyze, reduce, and visualize complex chemical reaction mechanisms. The mathematics behind the tool is based on graph theory: chemical species are represented as vertices, and reactions as edges. MEXPLORER is a community model published under the GNU General Public License.
Hossain Mohammed Syedul Hoque, Kengo Sudo, Hitoshi Irie, Yanfeng He, and Md Firoz Khan
EGUsphere, https://doi.org/10.22541/essoar.169903618.82717612/v2, https://doi.org/10.22541/essoar.169903618.82717612/v2, 2024
Short summary
Short summary
Using multi-platform observations, we validated global formaldehyde (HCHO) simulations from a chemistry transport model. HCHO is a crucial intermediate of the chemical catalytic cycle that governs the ozone formation in the troposphere. The model was capable of replicating the observed spatiotemporal variability in HCHO. In a few cases, the model capability was limited. This is attributed to the uncertainties in the observations and the model parameters.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 2347–2358, https://doi.org/10.5194/gmd-17-2347-2024, https://doi.org/10.5194/gmd-17-2347-2024, 2024
Short summary
Short summary
In the last decades, weather forecasting up to 15 d into the future has been dominated by physics-based numerical models. Recently, deep learning models have challenged this paradigm. However, the latter models may struggle when forecasting weather extremes. In this article, we argue for deep learning models specifically designed to handle extreme events, and we propose a foundational framework to develop such models.
Stefan Rahimi, Lei Huang, Jesse Norris, Alex Hall, Naomi Goldenson, Will Krantz, Benjamin Bass, Chad Thackeray, Henry Lin, Di Chen, Eli Dennis, Ethan Collins, Zachary J. Lebo, Emily Slinskey, Sara Graves, Surabhi Biyani, Bowen Wang, Stephen Cropper, and the UCLA Center for Climate Science Team
Geosci. Model Dev., 17, 2265–2286, https://doi.org/10.5194/gmd-17-2265-2024, https://doi.org/10.5194/gmd-17-2265-2024, 2024
Short summary
Short summary
Here, we project future climate across the western United States through the end of the 21st century using a regional climate model, embedded within 16 latest-generation global climate models, to provide the community with a high-resolution physically based ensemble of climate data for use at local scales. Strengths and weaknesses of the data are frankly discussed as we overview the downscaled dataset.
Romain Pilon and Daniela I. V. Domeisen
Geosci. Model Dev., 17, 2247–2264, https://doi.org/10.5194/gmd-17-2247-2024, https://doi.org/10.5194/gmd-17-2247-2024, 2024
Short summary
Short summary
This paper introduces a new method for detecting atmospheric cloud bands to identify long convective cloud bands that extend from the tropics to the midlatitudes. The algorithm allows for easy use and enables researchers to study the life cycle and climatology of cloud bands and associated rainfall. This method provides insights into the large-scale processes involved in cloud band formation and their connections between different regions, as well as differences across ocean basins.
Salvatore Larosa, Domenico Cimini, Donatello Gallucci, Saverio Teodosio Nilo, and Filomena Romano
Geosci. Model Dev., 17, 2053–2076, https://doi.org/10.5194/gmd-17-2053-2024, https://doi.org/10.5194/gmd-17-2053-2024, 2024
Short summary
Short summary
PyRTlib is an attractive educational tool because it provides a flexible and user-friendly way to broadly simulate how electromagnetic radiation travels through the atmosphere as it interacts with atmospheric constituents (such as gases, aerosols, and hydrometeors). PyRTlib is a so-called radiative transfer model; these are commonly used to simulate and understand remote sensing observations from ground-based, airborne, or satellite instruments.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 17, 1995–2014, https://doi.org/10.5194/gmd-17-1995-2024, https://doi.org/10.5194/gmd-17-1995-2024, 2024
Short summary
Short summary
Our research presents an innovative approach to estimating power plant CO2 emissions from satellite images of the corresponding plumes such as those from the forthcoming CO2M satellite constellation. The exploitation of these images is challenging due to noise and meteorological uncertainties. To overcome these obstacles, we use a deep learning neural network trained on simulated CO2 images. Our method outperforms alternatives, providing a positive perspective for the analysis of CO2M images.
Kyoung-Min Kim, Si-Wan Kim, Seunghwan Seo, Donald R. Blake, Seogju Cho, James H. Crawford, Louisa K. Emmons, Alan Fried, Jay R. Herman, Jinkyu Hong, Jinsang Jung, Gabriele G. Pfister, Andrew J. Weinheimer, Jung-Hun Woo, and Qiang Zhang
Geosci. Model Dev., 17, 1931–1955, https://doi.org/10.5194/gmd-17-1931-2024, https://doi.org/10.5194/gmd-17-1931-2024, 2024
Short summary
Short summary
Three emission inventories were evaluated for East Asia using data acquired during a field campaign in 2016. The inventories successfully reproduced the daily variations of ozone and nitrogen dioxide. However, the spatial distributions of model ozone did not fully agree with the observations. Additionally, all simulations underestimated carbon monoxide and volatile organic compound (VOC) levels. Increasing VOC emissions over South Korea resulted in improved ozone simulations.
Sanam Noreen Vardag and Robert Maiwald
Geosci. Model Dev., 17, 1885–1902, https://doi.org/10.5194/gmd-17-1885-2024, https://doi.org/10.5194/gmd-17-1885-2024, 2024
Short summary
Short summary
We use the atmospheric transport model GRAMM/GRAL in a Bayesian inversion to estimate urban CO2 emissions on a neighbourhood scale. We analyse the effect of varying number, precision and location of CO2 sensors for CO2 flux estimation. We further test the inclusion of co-emitted species and correlation in the inversion. The study showcases the general usefulness of GRAMM/GRAL in measurement network design.
Abhishek Savita, Joakim Kjellsson, Robin Pilch Kedzierski, Mojib Latif, Tabea Rahm, Sebastian Wahl, and Wonsun Park
Geosci. Model Dev., 17, 1813–1829, https://doi.org/10.5194/gmd-17-1813-2024, https://doi.org/10.5194/gmd-17-1813-2024, 2024
Short summary
Short summary
The OpenIFS model is used to examine the impact of horizontal resolutions (HR) and model time steps. We find that the surface wind biases over the oceans, in particular the Southern Ocean, are sensitive to the model time step and HR, with the HR having the smallest biases. When using a coarse-resolution model with a shorter time step, a similar improvement is also found. Climate biases can be reduced in the OpenIFS model at a cheaper cost by reducing the time step rather than increasing the HR.
Ferdinand Briegel, Jonas Wehrle, Dirk Schindler, and Andreas Christen
Geosci. Model Dev., 17, 1667–1688, https://doi.org/10.5194/gmd-17-1667-2024, https://doi.org/10.5194/gmd-17-1667-2024, 2024
Short summary
Short summary
We present a new approach to model heat stress in cities using artificial intelligence (AI). We show that the AI model is fast in terms of prediction but accurate when evaluated with measurements. The fast-predictive AI model enables several new potential applications, including heat stress prediction and warning; downscaling of potential future climates; evaluation of adaptation effectiveness; and, more fundamentally, development of guidelines to support urban planning and policymaking.
Hauke Schmidt, Sebastian Rast, Jiawei Bao, Amrit Cassim, Shih-Wei Fang, Diego Jimenez-de la Cuesta, Paul Keil, Lukas Kluft, Clarissa Kroll, Theresa Lang, Ulrike Niemeier, Andrea Schneidereit, Andrew I. L. Williams, and Bjorn Stevens
Geosci. Model Dev., 17, 1563–1584, https://doi.org/10.5194/gmd-17-1563-2024, https://doi.org/10.5194/gmd-17-1563-2024, 2024
Short summary
Short summary
A recent development in numerical simulations of the global atmosphere is the increase in horizontal resolution to grid spacings of a few kilometers. However, the vertical grid spacing of these models has not been reduced at the same rate as the horizontal grid spacing. Here, we assess the effects of much finer vertical grid spacings, in particular the impacts on cloud quantities and the atmospheric energy balance.
Tao Zheng, Sha Feng, Jeffrey Steward, Xiaoxu Tian, David Baker, and Martin Baxter
Geosci. Model Dev., 17, 1543–1562, https://doi.org/10.5194/gmd-17-1543-2024, https://doi.org/10.5194/gmd-17-1543-2024, 2024
Short summary
Short summary
The tangent linear and adjoint models have been successfully implemented in the MPAS-CO2 system, which has undergone rigorous accuracy testing. This development lays the groundwork for a global carbon flux data assimilation system, which offers the flexibility of high-resolution focus on specific areas, while maintaining a coarser resolution elsewhere. This approach significantly reduces computational costs and is thus perfectly suited for future CO2 geostationery and imager satellites.
Cited articles
Aldener, M., Brown, S. S., Stark, H., Williams, E. J., Lerner, B. M.,
Kuster, W. C., Goldan, P. D., Quinn, P. K., Bates, T. S., Fehsenfeld, F. C.,
and Ravishankara, A. R.: Reactivity and loss mechanisms of NO3 and
N2O5 in a polluted marine environment: Results from in situ
measurements during New England Air Quality Study 2002, J. Geophys. Res.,
111, D23S73, https://doi.org/10.1029/2006JD007252, 2006.
Andreae, M. O. and Crutzen, P. J.: Atmospheric aerosols: biogeochemical
sources and role in atmospheric chemistry, Science, 276, 1052–1058,
1997.
Anttila, T., Kiendler-Scharr, A., Tillmann, R., and Mentel, T. F.: On the
reactive uptake of gaseous compounds by organic-coated aqueous aerosols:
Theoretical analysis and application to the heterogeneous hydrolysis of
N2O5, J. Phys. Chem. A, 110, 10435–10443, 2006.
Atkinson, R.: Gas-phase tropospheric chemistry of organic-compounds – a
review, Atmos. Environ., 24, 1–41, https://doi.org/10.1016/0960-1686(90)90438-s, 1990.
Atkinson, R.: Atmospheric chemistry of VOCs and NOx, Atmos. Environ.,
34, 2063–2101, 2000.
Atkinson, R., Baulch, D. L., Cox, R. A., Hampson Jr., R. F., Kerr, J. A.,
and Troe, J.: Evaluated kinetic and photochemical data for atmospheric
chemistry supplement-iv – IUPAC subcommittee on gas kinetic data evaluation
for atmospheric chemistry, J. Phys. and Chem. Ref. Data, 21, 1125–1568,
https://doi.org/10.1063/1.555918, 1992.
Bauer, S. E., Koch, D., Unger, N., Metzger, S. M., Shindell, D. T., and Streets, D. G.: Nitrate aerosols today and in 2030: a global simulation including aerosols and tropospheric ozone, Atmos. Chem. Phys., 7, 5043–5059, https://doi.org/10.5194/acp-7-5043-2007, 2007.
Bertram, T. H. and Thornton, J. A.: Toward a general parameterization of N2O5 reactivity on aqueous particles: the competing effects of particle liquid water, nitrate and chloride, Atmos. Chem. Phys., 9, 8351–8363, https://doi.org/10.5194/acp-9-8351-2009, 2009.
Bigeleisen, J.: Second-Order Sum Rule for the Vibrations of Isotopic
Molecules and the Second Rule of the Mean, J. Chem. Phys., 28, 694–699,
1958.
Bigeleisen, J. and Mayer, M. G.: Calculation of Equilibrium Constants for
Isotopic Exchange Reactions, J. Chem. Phys., 15, 261–267, 1947.
Bigeleisen, J. and Wolfsberg, M.: Theoretical and experimental aspects of
isotope effects in chemical kinetics, Adv. Chem. Phys., 1, 15–76, 1958.
Blake, G. A., Liang, M. C., Morgan, C. G., and Yung, Y. L.: A
born-oppenheimer photolysis model of N2O fractionation, Geophys. Res.
Lett., 30, 58/51–58/54, 2003.
Bloss, W. J., Evans, M. J., Lee, J. D., Sommariva, R., Heard, D. E., and
Pilling, M. J.: The oxidative capacity of the troposphere: Coupling of field
measurements of OH and a global chemistry transport model, Faraday Discuss.,
130, 425–436, 2005.
Brimblecombe, P., Hara, H., Houle, D., and Novak, M.: Acid Rain –
Deposition to Recovery, Springer, 2007.
Brown, L. L. and Begun, G. M.: Nitrogen isotopic fractionation between
nitric acid and the oxides of nitrogen, J. Chem. Phys., 30, 1206–1209,
1959.
Brown, S. S., Burkholder, J. B., Talukdar, R. K., and Ravishankara, A. R.:
Reaction of hydroxyl radical with nitric acid: insights into its mechanism,
J. Phys. Chem. A, 105, 1605–1614, 2001.
Brown, S. S., Ryerson, T. B., Wollny, A. G., Brock, C. A., Peltier, R.,
Sullivan, A. P., Weber, R. J., Dube, W. P., Trainer, M., Meagher, J. F.,
Fehsenfeld, F. C., and Ravishankara, A. R.: Variability in nocturnal
nitrogen oxide processing and its role in regional air quality, Science,
311, 67–70, 2006.
Bruning-Fann, C. S., and Kaneene, J. B.: The Effects of Nitrate, Nitrite
and N-Nitroso Compounds on Human Health – A Review, Vet. Human Toxic.,
35, 521–538, 1993.
Cai, R., Yang, D., Fu, Y., Wang, X., Li, X., Ma, Y., Hao, J., Zheng, J., and Jiang, J.: Aerosol surface area concentration: a governing factor in new particle formation in Beijing, Atmos. Chem. Phys., 17, 12327–12340, https://doi.org/10.5194/acp-17-12327-2017, 2017.
Cao, Z., Zhou, X., Ma, Y., Wang, L., Wu, R., Chen, B., and Wang, W.: The
Concentrations, Formations, Relationships and Modeling of Sulfate, Nitrate
and Ammonium (SNA) Aerosols over China, Aerosol Air Quality Res., 17,
84–97, https://doi.org/10.4209/aaqr.2016.01.0020, 2017.
Chai, J. and Hastings, M. G.: Collection Method for Isotopic Analysis of
Gaseous Nitrous Acid, Anal. Chem., 90, 830–838,
https://doi.org/10.1021/acs.analchem.7b03561, 2018.
Chang, W. L., Bhave, P. V., Brown, S. S., Riemer, N., Stutz, J., and
Dabdub, D.: Heterogeneous Atmospheric Chemistry, Ambient Measurements, and
Model Calculations of N2O5: A Review, Aero. Sci. Tech., 45,
665–695, 2011.
Charlson, R. J., Schwartz, S. E., Hales, J. M., Cess, R. D., Coakley, J. J.,
Hansen, J. E., and Hofmann, D. J.: Climate Forcing by Anthropogenic
Aerosols, Science, 255, 423–430, 1992.
Chen, W. T., Liao, H., and Seinfeld, J. H.: Future climate impacts of
direct radiative forcing of anthropogenic aerosols, tropospheric ozone, and
long-lived greenhouse gases, J. Geophys. Res., 112, D14209, https://doi.org/10.1029/2006JD00805, 2007.
Davis, J. M., Bhave, P. V., and Foley, K. M.: Parameterization of N2O5 reaction probabilities on the surface of particles containing ammonium, sulfate, and nitrate, Atmos. Chem. Phys., 8, 5295–5311, https://doi.org/10.5194/acp-8-5295-2008, 2008.
Day, D. A., Dillon, M. B., Wooldridge, P. J., Thornton, J. A., Rosen, R. S.,
Wood, E. C., and Cohen, R. C.: On alkyl nitrates, O3, and the “missing
NOy”, J. Geophys. Res., 108, 4501, https://doi.org/10.1029/2003jd003685, 2003.
DeMore, W. B., Sander, S. P., Golden, D. M., Hampson, R. F., Kurylo, M. J.,
Howard, C. J., Ravishankara, A. R., Kolb, C. E., and Molina, M. J.:
Chemical kinetics and photochemical data for use in stratospheric modeling,
Eval. 11, Natl. Aeronaut. and Space Admin., Jet Propul. Lab., 1994.
Dentener, F. J. and Crutzen, P. J.: Reaction of nitrogen pentoxide on
tropospheric aerosols: Impact on the global distributions of NOx,
ozone, and hydroxyl, J. Geophys. Res., 98, 7149–7163, 1993.
Diem, J. E. and Comrie, A. C.: Allocating anthropogenic pollutant
emissions over space: application to ozone pollution management, J.
Environ. Manag., 63, 425–447, 2001.
Du, E., Fenn, M. E., De Vries, W., and Ok, Y. S.: Atmospheric nitrogen
deposition to global forests: Status, impacts and management options,
Environ. Poll., 250, 1044–1048, https://doi.org/10.1016/j.envpol.2019.04.014, 2019.
Elliott, E. M., Kendall, C., Wankel, S. D., Burns, D. A., Boyer, E. W.,
Harlin, K., Bain, D. J., and Butler, T. J.: Nitrogen isotopes as indicators
of NOx source contributions to atmospheric nitrate deposition across the
Midwestern and northeastern United States, Environ. Sci. Technol., 41,
7661–7667, 2007.
Elliott, E. M., Kendall, C., Boyer, E. W., Burns, D. A., Lear, G. G.,
Golden, H. E., Harlin, K., Bytnerowicz, A., Butler, T. J., and Glatz, R.:
Dual nitrate isotopes in dry deposition: Utility for partitioning NOx
source contributions to landscape nitrogen deposition, J. Geophys. Res., 114, G04020, https://doi.org/10.1029/2008JG000889,
2009.
Elliott, E. M., Yu, Z., Cole, A. S., and Coughlin, J. G.: Isotopic advances
in understanding reactive nitrogen deposition and atmospheric processing,
Sci. Total Environ., 662, 393–403, https://doi.org/10.1016/j.scitotenv.2018.12.177,
2019.
Fang, H.: iNRACM: Incorporating 15N into the Regional Atmospheric Chemistry Mechanism (RACM) for assessing the role photochemistry plays in controlling the isotopic composition of NOx, NOy, and atmospheric nitrate (Version 1.0), Zenodo [code], https://doi.org/10.5281/zenodo.3834921, 2020.
Felix, J. D. and Elliott, E. M.: Isotopic composition of passively
collected nitrogen dioxide emissions: Vehicle, soil and livestock source
signatures, Atmos. Environ., 92, 359–366, https://doi.org/10.1016/j.atmosenv.2014.04.005,
2014.
Felix, J. D., Elliott, E. M., and Shaw, S. L.: Nitrogen Isotopic
Composition of Coal-Fired Power Plant NOx: Influence of Emission
Controls and Implications for Global Emission Inventories, Environ. Sci.
Technol., 46, 3528–3535, 2012.
Felix, J. D., Elliott, E. M., Avery, G. B., Kieber, R. J., Mead, R. N.,
Willey, J. D., and Mullaugh, K. M.: Isotopic composition of nitrate in
sequential Hurricane Irene precipitation samples: implications for changing
NOx sources, Atmos. Environ., 106, 191–195, 2015.
Fibiger, D. L., and Hastings, M. G.: First Measurements of the Nitrogen
Isotopic Composition of NOx from Biomass Burning, Environ. Sci. Technol.,
50, 11569–11574, https://doi.org/10.1021/acs.est.6b03510, 2016.
Finlayson-Pitts, B. J. and Pitts Jr., J. N.: Chemistry of the Upper and
Lower Atmosphere, Academic Press, San Diego, 2000.
Fowler, D., Coyle, M., Skiba, U., Sutton, M. A., Cape, J., Reis, S.,
Sheppard, L. J., Jenkins, A., Grizzetti, B., Galloway, J. N., Vitousek, P.,
Leach, A., Bouwman, A. F., Butterbach-Bahl, K., Dentener, F., Stevenson, D.,
Amann, M., and Voss, M.: The global nitrogen cycle in the twenty-first
century, Phil. T. Roy. Soc. B, 368, 20130164, https://doi.org/10.1098/rstb.2013.0164, 2013.
Freyer, H. D.: Seasonal variation of 15N/14N ratios in atmospheric
nitrate species, Tellus B, 43, 30–44, 1991.
Freyer, H. D., Kley, D., Volz-Thomas, A., and Kobel, K.: On the interaction
of isotopic exchange processes with photochemical-reactions in atmospheric
oxides of nitrogen, J. Geophys. Res., 98, 14791–14796,
https://doi.org/10.1029/93jd00874, 1993.
Galloway, J. N., Dentener, F. J., Capone, D. G., Boyer, E. W., Howarth, R.
W., Seitzinger, S. P., Asner, G. P., Cleveland, C. C., Green, P. A.,
Holland, E. A., Karl, D. M., Michaels, A. F., Porter, J. H., Townsend, A.
R., and Vorosmarty, C. J.: Nitrogen cycles: past, present, and future,
Biogeochemistry, 70, 153–226, 2004.
Golden, D. M. and Smith, G. P.: Reaction of OH + NO2+ M: A new
view, J. Phys. Chem. A, 104, 3991–3997, 2000.
Hall, J. V., Winer, A. M., Kleinman, M. T., Lurmann, F. W., Brajer, V., and
Colome, S. D.: Valuing the Health Benefits of Clean Air, Science, V255,
812–817, 1992.
Hastings, M. G., Sigman, D. M., and Lipschultz, F.: Isotopic evidence for
source changes of nitrate in rain at Bermuda, J. Geophys. Res.-Atmos.,
108, 4790, https://doi.org/10.1029/2003JD003789, 2003.
Hastings, M. G., Jarvis, J. C., and Steig, E. J.: Anthropogenic impacts on nitrogen
isotopes of ice-core nitrate, Science, 324, 1288–1288, 2009.
Hastings, M. G., Casciotti, K. L., and Elliott, E. M.: Stable Isotopes as
Tracers of Anthropogenic Nitrogen Sources, Deposition, and Impacts,
Elements, 9, 339–344, 2013.
Heaton, T. H. E.: 15N/14N ratios of nitrate and ammonium in rain
at Pretoria, South Africa, Atmos. Environ., 21, 843–852, 1987.
Hegglin, M. I., Brunner, D., Peter, T., Hoor, P., Fischer, H., Staehelin, J., Krebsbach, M., Schiller, C., Parchatka, U., and Weers, U.: Measurements of NO, NOy, N2O, and O3 during SPURT: implications for transport and chemistry in the lowermost stratosphere, Atmos. Chem. Phys., 6, 1331–1350, https://doi.org/10.5194/acp-6-1331-2006, 2006.
Horowitz, L. W., Liang, J., Gardner, G. M., and Jacob, D. J.: Export of
reactive nitrogen from North America during summertime: sensitivity to
hydrocarbon chemistry, J. Geophys. Res., 103, 13451–13476, 1998.
Houlton, B. Z., Boyer, E., Finzi, A. C., Galloway, J., Leach, A., Liptzin,
D., Melillo, J., Rosenstock, T. S., Sobota, D., and Townsend, A. R.:
Intentional versus unintentional nitrogen use in the United States: trends,
efficiency and implications, Biogeochemistry, 114, 11–23, 2013.
Hoyle, C. R., Boy, M., Donahue, N. M., Fry, J. L., Glasius, M., Guenther, A., Hallar, A. G., Huff Hartz, K., Petters, M. D., Petäjä, T., Rosenoern, T., and Sullivan, A. P.: A review of the anthropogenic influence on biogenic secondary organic aerosol, Atmos. Chem. Phys., 11, 321–343, https://doi.org/10.5194/acp-11-321-2011, 2011.
Hudman, R. C., Moore, N. E., Mebust, A. K., Martin, R. V., Russell, A. R., Valin, L. C., and Cohen, R. C.: Steps towards a mechanistic model of global soil nitric oxide emissions: implementation and space based-constraints, Atmos. Chem. Phys., 12, 7779–7795, https://doi.org/10.5194/acp-12-7779-2012, 2012.
Kastler, J. and Ballschmiter, K.: Bifunctional alkyl nitrates–trace
constituents of the atmosphere, J. Anal. Chem., 360,
812–816, 1998.
Kuang, C., Riipinen, I., Sihto, S.-L., Kulmala, M., McCormick, A. V., and McMurry, P. H.: An improved criterion for new particle formation in diverse atmospheric environments, Atmos. Chem. Phys., 10, 8469–8480, https://doi.org/10.5194/acp-10-8469-2010, 2010.
Lajtha, K. and Jones, J.: Trends in cation, nitrogen, sulfate and hydrogen
ion concentrations in precipitation in the United States and Europe from
1978 to 2010: a new look at an old problem, Biogeochemistry, 116, 303–334,
https://doi.org/10.1007/s10533-013-9860-2, 2013.
Lee, S. H., Uin, J., Guenther, A. B., de Gouw, J. A., Yu, F. Q., Nadykto, A.
B., Herb, J., Ng, N. L., Koss, A., Brune, W. H., Baumann, K., Kanawade, V.
P., Keutsch, F. N., Nenes, A., Olsen, K., Goldstein, A., and Ouyang, Q.:
Isoprene suppression of new particle formation: Potential mechanisms and
implications, J. Geophys. Res., 121, 14621–14635, 2016.
Lelieveld, J., Butler, T. M., Crowley, J. N., Dillon, T. J., Fischer, H.,
Ganzeveld, L., Harder, H., Lawrence, M. G., Martinez, M., Taraborrelli, D.,
and Williams, J.: Atmospheric oxidation capacity sustained by a tropical
forest, Nature, 452, 737–740, 2008.
Liang, M. C., Blake, G. A., and Yung, Y. L.: A semianalytic model for
photo-induced isotopic fractionation in simple molecules, J. Geophys. Res.,
109, D10308, https://doi.org/10.1029/2004JD004539, 2004.
Ma, J., Liu, Y., Han, C., Ma, Q., Liu, C., and He, H.: Review of
heterogeneous photochemical reactions of NOy on aerosol – A possible
daytime source of nitrous acid (HONO) in the atmosphere, J. Environ. Sci. China,
25, 326–334, https://doi.org/10.1016/s1001-0742(12)60093-x, 2013.
Madronich, S.: Photodissociation in the atmosphere: 1. Actinic flux and the
effects of ground reflections and clouds, J. Geophys. Res., 92,
9740–9752, 1987.
McMurry, P. H., Fink, M., Sakurai, H., Stolzenburg, M. R., Mauldin, R. L.,
Smith, J., Eisele, F., Moore, K., Sjostedt, S., Tanner, D., Huey, L. G.,
Nowak, J. B., Edgerton, E., and Voisin, D.: A criterion for new particle
formation in the sulfur-rich Atlanta atmosphere, J. Geophys. Res., 110, D22S02, https://doi.org/:10.1029/2005JD005901,
2005.
Michalski, G., Jost, R., Sugny, D., Joyeux, M., and Thiemens, M.:
Dissociation energies of six NO2 isotopologues by laser induced
fluorescence and zero point energy of some triatomic molecules, J. Chem.
Phys., 121, 7153–7161, 2004.
Miller, C. E. and Yung, Y. L.: Photo-induced isotopic fractionation, J. Geophys. Res., 105, 29039–29051, 2000.
Monks, P. S.: Gas-phase radical chemistry in the troposphere, Chem. Soc. Rev., 34, 376–395, https://doi.org/10.1039/b307982c, 2005.
Moore, H.: The isotopic composition of ammonia, nitrogen dioxide and nitrate
in the atmosphere, Atmos. Environ., 11, 1239–1243, 1977.
Morino, Y., Kondo, Y., Takegawa, N., Miyazaki, Y., Kita, K., Komazaki, Y.,
Fukuda, M., Miyakawa, T., Moteki, N., and Worsnop, D. R.: Partitioning of
HNO3 and particulate nitrate over Tokyo: Effect of vertical mixing, J. Geophys. Res., 111, D15215, https://doi.org/10.1029/2005jd006887, 2006.
Pan, Y., Tian, S., Liu, D., Fang, Y., Zhu, X., Gao, M., Gregory, G. R., Michalski, G., Huang, X., and Wang, Y.:
Source Apportionment of Aerosol Ammonium in an Ammonia-Rich Atmosphere: An
Isotopic Study of Summer Clean and Hazy Days in Urban Beijing, J. Geophys. Res., 123, 5681–5689, https://doi.org/10.1029/2017jd028095, 2018.
Paulot, F., Ginoux, P., Cooke, W. F., Donner, L. J., Fan, S., Lin, M.-Y., Mao, J., Naik, V., and Horowitz, L. W.: Sensitivity of nitrate aerosols to ammonia emissions and to nitrate chemistry: implications for present and future nitrate optical depth, Atmos. Chem. Phys., 16, 1459–1477, https://doi.org/10.5194/acp-16-1459-2016, 2016.
Pilegaard, K.: Processes regulating nitric oxide emissions from soils, Philos.
T. R. Soc. B, 368, 20130126, https://doi.org/10.1098/rstb.2013.0126, 2013.
Platt, U. F., Winer, A. M., Biermann, H. W., Atkinson, R., and Pitts, J.
N.: Measurement of Nitrate Radical Concentrations in Continental Air, Environ.
Sci. Technol., 18, 365–369, 1984.
Prinn, R. G.: The cleansing capacity of the atmosphere, Ann. Rev. Env.
Res., 28, 29–57, 2003.
Pusede, S. E., Duffey, K. C., Shusterman, A. A., Saleh, A., Laughner, J. L., Wooldridge, P. J., Zhang, Q., Parworth, C. L., Kim, H., Capps, S. L., Valin, L. C., Cappa, C. D., Fried, A., Walega, J., Nowak, J. B., Weinheimer, A. J., Hoff, R. M., Berkoff, T. A., Beyersdorf, A. J., Olson, J., Crawford, J. H., and Cohen, R. C.: On the effectiveness of nitrogen oxide reductions as a control over ammonium nitrate aerosol, Atmos. Chem. Phys., 16, 2575–2596, https://doi.org/10.5194/acp-16-2575-2016, 2016.
Pye, H. O. T., Chan, A. W. H., Barkley, M. P., and Seinfeld, J. H.: Global modeling of organic aerosol: the importance of reactive nitrogen (NOx and NO3), Atmos. Chem. Phys., 10, 11261–11276, https://doi.org/10.5194/acp-10-11261-2010, 2010.
Richet, P., Bottinga, Y., and Javoy, M.: Review of hydrogen, carbon,
nitrogen, oxygen, sulfur, and chlorine stable isotope fractionation among
gaseous molecules, Annu. Rev. Earth Planet. Sci., 5, 65–110, 1977.
Riemer, N., Vogel, H., Vogel, B., Schell, B., Ackermann, I., Kessler, C.,
and Hass, H.: Impact of the heterogeneous hydrolysis of N2O5 on
chemistry and nitrate aerosol formation in the lower troposphere under
photosmog conditions, J. Geophys. Res., 108, 4144,
https://doi.org/10.1029/2002JD002436, 2003.
Riemer, N., Vogel, H., Vogel, B., Anttila, T., Kiendler-Scharr, A., and
Mentel, T. F.: Relative importance of organic coatings for the heterogeneous
hydrolysis of N2O5 during summer in Europe, J. Geophys. Res.,
114, https://doi.org/10.1029/2008JD011369, 2009.
Riha, K. M.: The use of stable isotopes to constrain the nitrogen cycle,
PhD Dissertation, Purdue University, West Lafayette, IN, 2013.
Roehl, C. M., Orlando, J. J., Tyndall, G. S., Shetter, R. E., Vazquez, G.
J., Cantrell, C. A., and Calvert, J. G.: Temperature-dependence of the
quantum yields for the photolysis of NO2 near the dissociation limit,
J. Phys. Chem., 98, 7837–7843, https://doi.org/10.1021/j100083a015, 1994.
Romer, P. S., Duffey, K. C., Wooldridge, P. J., Allen, H. M., Ayres, B. R., Brown, S. S., Brune, W. H., Crounse, J. D., de Gouw, J., Draper, D. C., Feiner, P. A., Fry, J. L., Goldstein, A. H., Koss, A., Misztal, P. K., Nguyen, T. B., Olson, K., Teng, A. P., Wennberg, P. O., Wild, R. J., Zhang, L., and Cohen, R. C.: The lifetime of nitrogen oxides in an isoprene-dominated forest, Atmos. Chem. Phys., 16, 7623–7637, https://doi.org/10.5194/acp-16-7623-2016, 2016.
Rose, L. A., Yu, Z., Bain, D. J., and Elliott, E. M.: High resolution,
extreme isotopic variability of precipitation nitrate, Atmos. Environ., 207,
63–74, 2019.
Savard, M. M., Cole, A., Smirnoff, A., and Vet, R.: δ15N
values of atmospheric N species simultaneously collected using sector-based
samplers distant from sources–Isotopic inheritance and fractionation, Atmos. Environ., 162, 11–22, 2017.
Seinfeld, J. H. and Pandis, S. N.: Atmospheric composition,
global cycles, and lifetimes, Atmospheric chemistry and
physics: From air pollution to climate change, 2, 98–101, 1998.
Seinfeld, J. H. and Pandis, S. N.: Atmospheric Chemistry and Physics: from
air pollution to climate change, John Wiley & Sons, 2016.
Sharma, H. D., Jervis, R. E., and Wong, K. Y.: Isotopic exchange reactions
in nitrogen oxides, J. Phys. Chem., 74, 923–933, 1970.
Shrivastava, M., Cappa, C. D., Fan, J. W., Goldstein, A. H., Guenther, A.
B., Jimenez, J. L., Kuang, C., Laskin, A., Martin, S. T., Ng, N. L., Petaja,
T., Pierce, J. R., Rasch, P. J., Roldin, P., Seinfeld, J. H., Shilling, J.,
Smith, J. N., Thornton, J. A., Volkamer, R., Wang, J., Worsnop, D. R.,
Zaveri, R. A., Zelenyuk, A., and Zhang, Q.: Recent advances in understanding
secondary organic aerosol: Implications for global climate forcing, Rev.
Geophys., 55, 509–559, 2017.
Snyder, J. A., Hanway, D., Mendez, J., Jamka, A. J., and Tao, F. M.: A
density functional theory study of the gas-phase hydrolysis of dinitrogen
pentoxide, J. Phys. Chem. A, 103, 9355–9358, 1999.
Spak, S. N. and Holloway, T.: Seasonality of speciated aerosol transport
over the Great Lakes region, J. Geophys. Res., 114, D08302, https://doi.org/10.1029/2008JD010598, 2009.
Srivastava, R. K., Neuffer, W., Grano, D., Khan, S., Staudt, J. E., and
Jozewicz, W.: Controlling NOx emission from industrial sources, Environ.
Prog., 24, 181–197, 2005.
Stockwell, W. R., Middleton, P., Chang, J. S., and Tang, X.: The second
generation regional acid deposition model chemical mechanism for regional
air quality modeling, J. Geophys. Res., 95, 16343–16367, 1990.
Stockwell, W. R., Kirchner, F., Kuhn, M., and Seefeld, S.: A new mechanism
for regional atmospheric chemistry modeling, J. Geophys. Res., 102,
25847–25879, 1997.
Urey, H. C.: Thermodynamic properties of isotopic substances, J. Chem. Soc.,
562–581, 1947.
Vandaele, A. C., Hermans, C., Fally, S., Carleer, M., Colin, R., Merienne,
M. F., Jenouvrier, A., and Coquart, B.: High-resolution Fourier transform
measurement of the NO2 visible and near-infrared absorption cross
sections: Temperature and pressure effects, J. Geophys. Res., 107, 4348,
https://doi.org/10.1029/2001jd000971, 2002.
Van Hook, W. A., Rebelo, L. P. N., and Wolfsberg, M.: An interpretation of
the vapor phase second virial coefficient isotope effect: Correlation of
virial coefficient and vapor pressure isotope effects, J. Phys. Chem. A,
105, 9284–9297, https://doi.org/10.1021/jp004302z, 2001.
Walters, W. W. and Michalski, G.: Theoretical calculation of nitrogen
isotope equilibrium exchange fractionation factors for various NOy
molecules, Geochim. Cosmochim. Ac., 164, 284–297,
https://doi.org/10.1016/j.gca.2015.05.029, 2015.
Walters, W. W. and Michalski, G.: Ab initio study of nitrogen and
position-specific oxygen kinetic isotope effects in the NO + O3
reaction, J. Chem. Phys., 145, 224311, https://doi.org/10.1063/1.4968562, 2016.
Walters, W. W., Goodwin, S. R., and Michalski, G.: Nitrogen Stable Isotope
Composition of Vehile Emitted NOx, Environ. Sci. Technol., 49,
2278–2285, 2015a.
Walters, W. W., Tharp, B. D., Fang, H., Kozak, B. J., and Michalski, G.:
Nitrogen Isotope Composition of Thermally Produced NOx from Various
Fossil-Fuel Combustion Sources, Environ. Sci. Technol., 49, 11363–11371,
https://doi.org/10.1021/acs.est.5b02769, 2015b.
Walters, W. W., Simonini, D. S., and Michalski, G.: Nitrogen isotope
exchange between NO and NO2 and its implications for 15N
variations in tropospheric NOx and atmospheric nitrate, Geophys. Res.
Lett., 43, 440–448, https://doi.org/10.1002/2015gl066438, 2016.
Walters, W. W., Fang, H., and Michalski, G.: Summertime diurnal variations
in the isotopic composition of atmospheric nitrogen dioxide at a small
midwestern United States city, Atmos. Environ., 179, 1–11,
https://doi.org/10.1016/j.atmosenv.2018.01.047, 2018.
Wolfsberg, M.: Note on secondary isotope effects in reaction rates, J. Chem.
Phys., 33, 2–6, https://doi.org/10.1063/1.1731078, 1960.
Wolfsberg, M., Van Hook, W. A., and Paneth, P.: Isotope effects on
equilibrium constants of chemical reactions; transition state theory of
isotope effects, in: Isotope Effects, Springer, Dordrecht, 77–137, 2010.
Yu, Z. and Elliott, E. M.: Novel method for nitrogen isotopic analysis of
soil-emitted nitric oxide, Environ. Sci. Technol., 51, 6268–6278, 2017.
Yung, Y. L. and Miller, C. E.: Isotopic fractionation of
stratospheric nitrous oxide, Science, 278, 1778–1780, 1997.
Yvon, S. A., Plane, J. M. C., Nien, C. F., Cooper, D. J., and Saltzman, E. S.:
Interaction between nitrogen and sulfur cycles in the polluted marine
boundary layer, J. Geophys. Res.-Atmos., 101,
1379–1386, 1996.
Zhang, Y., Vijayaraghavan, K., Wen, X. Y., Snell, H. E., and Jacobson, M.
Z.: Probing into regional ozone and particulate matter pollution in the
United States: 1. A 1-year CMAQ simulation and evaluation using surface and
satellite data, J. Geophys. Res., 114, D22304, https://doi.org/10.1029/2009JD011898, 2009.
Short summary
A new photochemical reaction scheme that incorporates nitrogen isotopes has been developed to simulate isotope tracers in air pollution. The model contains 16 N compounds, and 96 reactions involving N used in the Regional Atmospheric Chemistry Mechanism (RACM) were replicated using 15N in a new mechanism called iNRACM. The model is able to predict d15N variations in NOx, HONO, and HNO3 that are similar to those observed in aerosol and gases in the troposphere.
A new photochemical reaction scheme that incorporates nitrogen isotopes has been developed to...