Articles | Volume 16, issue 1
https://doi.org/10.5194/gmd-16-1-2023
© Author(s) 2023. 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-16-1-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
02 Jan 2023
Model evaluation paper |
| 02 Jan 2023
| 02 Jan 2023
Towards an improved representation of carbonaceous aerosols over the Indian monsoon region in a regional climate model: RegCM
Sudipta Ghosh
Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, New Delhi, India
Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, New Delhi, India
Centre of Excellence for Research on Clean Air, Indian Institute of
Technology Delhi, New Delhi, India
Sushant Das
Earth System Physics Section, International Centre for Theoretical
Physics (ICTP), Trieste, Italy
Nicole Riemer
Department of Atmospheric Sciences, University of Illinois at
Urbana-Champaign, Urbana, IL, USA
Graziano Giuliani
Earth System Physics Section, International Centre for Theoretical
Physics (ICTP), Trieste, Italy
Dilip Ganguly
Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, New Delhi, India
Chandra Venkataraman
Department of Chemical Engineering, Indian Institute of Technology
Bombay, Mumbai, India
Filippo Giorgi
Earth System Physics Section, International Centre for Theoretical
Physics (ICTP), Trieste, Italy
Sachchida Nand Tripathi
Department of Civil Engineering, Indian Institute of Technology
Kanpur, Kanpur, India
Srikanthan Ramachandran
Space and Atmospheric Sciences Division, Physical Research Laboratory, Ahmedabad, India
Thazhathakal Ayyappen Rajesh
Space and Atmospheric Sciences Division, Physical Research Laboratory, Ahmedabad, India
Harish Gadhavi
Space and Atmospheric Sciences Division, Physical Research Laboratory, Ahmedabad, India
Atul Kumar Srivastava
Indian Institute of Tropical Meteorology, New Delhi Branch, New Delhi, India
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Vimal Jose Vazhathara, Ravi Kumar Kunchala, Sajeev Philip, Jaswant Rathore, Dilip Ganguly, Sagnik Dey, Tomoki Nakayama, Yutaka Matsumi, and Prabir K. Patra
Atmos. Chem. Phys., 26, 6929–6949, https://doi.org/10.5194/acp-26-6929-2026, https://doi.org/10.5194/acp-26-6929-2026, 2026
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To address the lack of continuous ground-based CO2 measurements in the Indo-Gangetic Plain, we started ground-based measurements of atmospheric CO2 concentrations, for the very first time at Sonipat within the IGP. Based on these measurements, we examined the seasonal and diurnal patterns of atmospheric CO2. We found that the interplay of anthropogenic emissions, biospheric fluxes, and prevailing meteorology contributes to the observed high seasonal and diurnal variability of atmospheric CO2.
Moetasim Ashfaq, Erika Coppola, Chris Lennard, Claas Teichmann, Deeksha Rastogi, Elias Massoud, Erasmo Buonomo, Eun-Soon Im, George Zittis, Jason P. Evans, Jesus Fernandez, Katherine J. Evans, Maria Leidinice da Silva, Marianna Adinolfi, Melissa Bukovsky, Rosmeri Porfirio da Rocha, Shabeh ul Hasson, Silvina A. Solman, Stefan Sobolowski, Sushant Das, Swen Brands, Tereza Cavazos, Thanh Ngo-Duc, and Xuejie Gao
EGUsphere, https://doi.org/10.5194/egusphere-2026-2649, https://doi.org/10.5194/egusphere-2026-2649, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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Producing reliable regional climate projections requires carefully selecting which global climate models drive them. We developed a transparent and reproducible framework to identify a balanced, representative subset of models for the Coordinated Regional Climate Downscaling Experiment, a major international effort to generate high-resolution climate projections worldwide. While designed for this initiative, the framework is broadly applicable to other models sub-selection efforts.
Xiaotian Xu, Jeffrey Henry Curtis, Matthew West, and Nicole Riemer
EGUsphere, https://doi.org/10.5194/egusphere-2026-2354, https://doi.org/10.5194/egusphere-2026-2354, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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This study examines how common simplifications in atmospheric models affect predictions of particles that form cloud droplets. Using a detailed simulation that tracks individual particles, we compare it with simplified approaches. We find that these simplifications can produce seemingly accurate results because different errors cancel each other. However, this masks incorrect physical processes. Including surfactants effect improves predictions, highlighting a pathway to better climate modeling.
Jintu Borah, Deepali Kushwaha, Sachchida Nand Tripathi, and Rajesh M. Hegde
EGUsphere, https://doi.org/10.5194/egusphere-2026-1103, https://doi.org/10.5194/egusphere-2026-1103, 2026
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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Accurate sectoral emission forecasting is challenging due to the multi-component nature of air quality data. This work addresses the gap by combining time-series decomposition with ensemble learning to enhance predictive performance. The work proposes a sector-specific emission forecasting method that uses source-apportioned, speciated PM2.5 concentration data from three locations. The framework enables robust quantification of sectoral emissions for new incoming speciated datasets.
Vasu Singh, Dilip Ganguly, Jaswant Rathore, Lokesh Kumar Sahu, Ravi K. Kunchala, and Sagnik Dey
EGUsphere, https://doi.org/10.5194/egusphere-2026-1428, https://doi.org/10.5194/egusphere-2026-1428, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Each post-monsoon season, northern India faces severe air pollution, especially around Delhi, largely linked to crop residue burning and stagnant weather. We measured air pollution in Sonipat, northwest of Delhi, along the pathway of incoming smoke. Fine particle levels were extremely high and mainly made of carbon-rich particles from crop burning and solid fuels. Much of this pollution formed before reaching Delhi, showing regional sources drive the city’s severe haze.
Samuel G. Frederick, Matin Mohebalhojeh, Jeffrey H. Curtis, Matthew West, and Nicole Riemer
Atmos. Chem. Phys., 26, 4863–4883, https://doi.org/10.5194/acp-26-4863-2026, https://doi.org/10.5194/acp-26-4863-2026, 2026
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We show with detailed computer simulations that spatial patterns of emissions strongly affect aerosols and their ability to seed clouds. Highly variable emissions can raise cloud-forming particle concentrations in the boundary layer by up to 25 %. Because clouds regulate climate and precipitation, these findings underscore the need to represent realistic emission patterns to improve climate predictions.
Yicen Liu, Jian Wang, and Nicole Riemer
EGUsphere, https://doi.org/10.5194/egusphere-2026-1724, https://doi.org/10.5194/egusphere-2026-1724, 2026
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Airborne particles affect clouds, climate, and air quality, but it is difficult to determine how their chemical components are mixed within individual particles. We tested a method that estimates this mixing from water-uptake measurements using detailed computer simulations. The method works well in many cases, but can overestimate particle mixing when moderately water-attracting material exists in separate particle types. We then applied this uncertainty framework to long-term observations.
Davender Sethi, Akanksha Lakra, Ambasht Kumar, Shoubhik Chakraborty, Himadri Sekhar Bhowmik, Vaishali Jain, and Sachchida Nand Tripathi
EGUsphere, https://doi.org/10.5194/egusphere-2026-595, https://doi.org/10.5194/egusphere-2026-595, 2026
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Breathe easier in the world's most polluted region—the Indo-Gangetic Plain of South Asia, home to Lucknow, India! Our mobile lab zipped through neighborhoods to uncover hidden air pollution patterns. Nearby traffic and factories mix with distant haze, fueling particle growth that worsens smog—especially at night. These insights pinpoint exact hotspots, empowering smarter fixes to clear the air and safeguard families' health in fast-growing cities.
Karin Stegelius, Pauline Thompson, Pia Karbiener, Piotr Markuszewski, Andre S. H. Prevot, Sachchida N. Tripathi, Claudia Mohr, Liine Heikkinen, Krishnakant Budhavant, and Sophie L. Haslett
EGUsphere, https://doi.org/10.5194/egusphere-2026-914, https://doi.org/10.5194/egusphere-2026-914, 2026
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High-time-resolution observations in the Maldives indicate that submicron aerosol over the northern Indian Ocean is primarily composed of inorganic sulfate and highly oxidised organic matter, indicative of aged continental outflow. The consistent composition across various air mass origins, alongside identification of sulfur-containing organics, underscores the influence of long-range transport and sulfate-driven secondary chemistry on regional aerosol characteristics and their climate impacts.
Yijia Sun, Ann M. Fridlind, Israel Silber, Nicole Riemer, and Daniel A. Knopf
Geosci. Model Dev., 19, 1581–1617, https://doi.org/10.5194/gmd-19-1581-2026, https://doi.org/10.5194/gmd-19-1581-2026, 2026
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The role of Arctic clouds in the regional climate remains uncertain due to insufficient understanding of the amount of liquid droplets and ice crystals present in these clouds. An aerosol-cloud model is employed to examine the role of different aerosol types and freezing parameterizations on the number of ice crystals. The choice of freezing parameterization significantly changes the number of ice crystals impacting the interpretation of the evolution and warming effect of Arctic clouds.
Oscar H. Díaz-Ibarra, Samuel G. Frederick, Jeffrey H. Curtis, Zachary D'Aquino, Peter A. Bosler, Lekha Patel, Cosmin Safta, Matthew West, and Nicole Riemer
Geosci. Model Dev., 19, 1281–1299, https://doi.org/10.5194/gmd-19-1281-2026, https://doi.org/10.5194/gmd-19-1281-2026, 2026
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We developed TChem-atm, a new open-source tool for simulating atmospheric chemistry and aerosols. As models become more detailed, traditional methods are too slow. TChem-atm runs on both standard processors and graphics processors, making these simulations faster and more efficient. The tool provides a foundation for next-generation models that improve predictions of air quality and climate.
Shoubhik Chakraborty, Sachchida Nand Tripathi, Davender Sethi, Akanksha Lakra, Ambasht Kumar, Pranjal Kumar Srivastava, Nihal Thukarama Rao, Avnish Tripathi, and Purushottam Kar
EGUsphere, https://doi.org/10.5194/egusphere-2025-5677, https://doi.org/10.5194/egusphere-2025-5677, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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This paper proposes a novel source apportionment paradigm that predicts the relative contributions of different air-pollution sources using a machine-learning framework applied to data obtained from low-cost sensor units. A key strength of this approach is its ability to support a dense network of low-cost sensor units spanning wide geographical areas and providing source apportionment results in real time, thus helping policymakers take regulatory action to curb air pollution in real time.
Eric Martial Yao, Fabien Solmon, Marcellin Adon, Claire Delon, Corinne Galy-Lacaux, Graziano Giuliani, Bastien Sauvage, and Véronique Yoboue
Atmos. Chem. Phys., 25, 12101–12136, https://doi.org/10.5194/acp-25-12101-2025, https://doi.org/10.5194/acp-25-12101-2025, 2025
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As climate change and human activities intensify in Africa, understanding how air pollution, climate, and natural cycles interact is crucial. This study explores how nitrogen oxide emissions from African soils, especially in dry regions, contribute to atmospheric pollution. By using a climate-chemistry model, we show that considering these emissions improves predictions of nitrogen dioxide, nitric acid and ozone, although some discrepancies remain compared to observations.
Wenhan Tang, Sylwester Arabas, Jeffrey H. Curtis, Daniel A. Knopf, Matthew West, and Nicole Riemer
EGUsphere, https://doi.org/10.5194/egusphere-2025-4326, https://doi.org/10.5194/egusphere-2025-4326, 2025
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We studied how aerosol particles help form ice in clouds. Using new theory and detailed computer simulations, we found that the way different materials are mixed within these particles has a strong impact on how much ice forms. When ice-forming material is spread across all particles, more droplets freeze than when it is only in a few. This result means that to better predict clouds and climate, models need to account for how particle materials are mixed.
Harish Shivraj Gadhavi, Akanksha Arora, Chaithanya Jain, Mahesh Kumar Sha, Frank Hase, Matthias Max Frey, Srikanthan Ramachandran, and Achuthan Jayaraman
Atmos. Meas. Tech., 18, 4497–4514, https://doi.org/10.5194/amt-18-4497-2025, https://doi.org/10.5194/amt-18-4497-2025, 2025
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We measured carbon dioxide (CO₂) and methane (CH₄) over South India using a ground-based spectrometer and compared the results with satellite data from GOSAT (Greenhouse gases Observing SATellite; Japan) and OCO-2 (Orbiting Carbon Observatory-2; NASA, USA). The satellite data have good accuracy and precision for estimating emissions. A computer model showed that changes in methane levels are influenced more by background levels than by local sources.
Zhenyu Zhang, Jing Li, Huizheng Che, Yueming Dong, Oleg Dubovik, Thomas Eck, Pawan Gupta, Brent Holben, Jhoon Kim, Elena Lind, Trailokya Saud, Sachchida Nand Tripathi, and Tong Ying
Atmos. Chem. Phys., 25, 4617–4637, https://doi.org/10.5194/acp-25-4617-2025, https://doi.org/10.5194/acp-25-4617-2025, 2025
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We used ground-based remote sensing data from the Aerosol Robotic Network to examine long-term trends in aerosol characteristics. We found aerosol loadings generally decreased globally, and aerosols became more scattering. These changes are closely related to variations in aerosol compositions, such as decreased anthropogenic emissions over East Asia, Europe, and North America; increased anthropogenic sources over northern India; and increased dust activity over the Arabian Peninsula.
Ashutosh K. Shukla, Sachchida N. Tripathi, Shamitaksha Talukdar, Vishnu Murari, Sreenivas Gaddamidi, Manousos-Ioannis Manousakas, Vipul Lalchandani, Kuldeep Dixit, Vinayak M. Ruge, Peeyush Khare, Mayank Kumar, Vikram Singh, Neeraj Rastogi, Suresh Tiwari, Atul K. Srivastava, Dilip Ganguly, Kaspar Rudolf Daellenbach, and André S. H. Prévôt
Atmos. Chem. Phys., 25, 3765–3784, https://doi.org/10.5194/acp-25-3765-2025, https://doi.org/10.5194/acp-25-3765-2025, 2025
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Our study delves into the elemental composition of aerosols at three sites across the Indo-Gangetic Plain (IGP), revealing distinct patterns during pollution episodes. We found significant increases in chlorine (Cl)-rich and solid fuel combustion (SFC) sources, indicating dynamic emission sources, agricultural burning impacts, and meteorological influences. Surges in Cl-rich particles during cold periods highlight their role in particle growth under high-relative-humidity conditions.
Zhouyang Zhang, Jiandong Wang, Jiaping Wang, Nicole Riemer, Chao Liu, Yuzhi Jin, Zeyuan Tian, Jing Cai, Yueyue Cheng, Ganzhen Chen, Bin Wang, Shuxiao Wang, and Aijun Ding
Atmos. Chem. Phys., 25, 1869–1881, https://doi.org/10.5194/acp-25-1869-2025, https://doi.org/10.5194/acp-25-1869-2025, 2025
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Black carbon (BC) exerts notable warming effects. We use a particle-resolved model to investigate the long-term behavior of the BC mixing state, revealing its compositions, coating thickness distribution, and optical properties all stabilize with a characteristic time of less than 1 d. This study can effectively simplify the description of the BC mixing state, which facilitates the precise assessment of the optical properties of BC aerosols in global and chemical transport models.
Chimurkar Navinya, Taveen Singh Kapoor, Gupta Anurag, Chandra Venkataraman, Harish C. Phuleria, and Rajan K. Chakrabarty
Atmos. Chem. Phys., 24, 13285–13297, https://doi.org/10.5194/acp-24-13285-2024, https://doi.org/10.5194/acp-24-13285-2024, 2024
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Brown carbon (BrC) aerosols show an order-of-magnitude variation in their light absorption strength. Our understanding of BrC from real-world biomass burning remains limited, complicating the determination of its radiative impact. Our study reports absorption properties of BrC emitted from four major biomass burning sources using field measurements in India. It develops an absorption parameterization for BrC and examines the spatial variability in BrC's absorption strength across India.
Jeffrey H. Curtis, Nicole Riemer, and Matthew West
Geosci. Model Dev., 17, 8399–8420, https://doi.org/10.5194/gmd-17-8399-2024, https://doi.org/10.5194/gmd-17-8399-2024, 2024
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This paper introduces a numerical method for simulating particle-based aerosol transport in atmospheric models. We detail the various numerical properties of the advection order method and demonstrate its implementation in a 3D weather prediction model (WRF) for the first time. Particle-based techniques improve the accuracy of aerosol size and composition predictions, which are key for aerosol–cloud and aerosol–radiation interactions.
Nanhong Xie, Tijian Wang, Xiaodong Xie, Xu Yue, Filippo Giorgi, Qian Zhang, Danyang Ma, Rong Song, Beiyao Xu, Shu Li, Bingliang Zhuang, Mengmeng Li, Min Xie, Natalya Andreeva Kilifarska, Georgi Gadzhev, and Reneta Dimitrova
Geosci. Model Dev., 17, 3259–3277, https://doi.org/10.5194/gmd-17-3259-2024, https://doi.org/10.5194/gmd-17-3259-2024, 2024
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For the first time, we coupled a regional climate chemistry model, RegCM-Chem, with a dynamic vegetation model, YIBs, to create a regional climate–chemistry–ecology model, RegCM-Chem–YIBs. We applied it to simulate climatic, chemical, and ecological parameters in East Asia and fully validated it on a variety of observational data. Results show that RegCM-Chem–YIBs model is a valuable tool for studying the terrestrial carbon cycle, atmospheric chemistry, and climate change on a regional scale.
Nishant Ajnoti, Hemant Gehlot, and Sachchida Nand Tripathi
Atmos. Meas. Tech., 17, 1651–1664, https://doi.org/10.5194/amt-17-1651-2024, https://doi.org/10.5194/amt-17-1651-2024, 2024
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This research focuses on the optimal placement of hybrid instruments (sensors and monitors) to maximize satisfaction function considering population, PM2.5 concentration, budget, and other factors. Two algorithms are developed in this study: a genetic algorithm and a greedy algorithm. We tested these algorithms on various regions. The insights of this work aid in quantitative placement of air quality monitoring instruments in large cities, moving away from ad hoc approaches.
Piyushkumar N. Patel, Jonathan H. Jiang, Ritesh Gautam, Harish Gadhavi, Olga Kalashnikova, Michael J. Garay, Lan Gao, Feng Xu, and Ali Omar
Atmos. Chem. Phys., 24, 2861–2883, https://doi.org/10.5194/acp-24-2861-2024, https://doi.org/10.5194/acp-24-2861-2024, 2024
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Global measurements of cloud condensation nuclei (CCN) are essential for understanding aerosol–cloud interactions and predicting climate change. To address this gap, we introduced a remote sensing algorithm that retrieves vertically resolved CCN number concentrations from airborne and spaceborne lidar systems. This innovation offers a global distribution of CCN concentrations from space, facilitating model evaluation and precise quantification of aerosol climate forcing.
Wei Huang, Cheng Wu, Linyu Gao, Yvette Gramlich, Sophie L. Haslett, Joel Thornton, Felipe D. Lopez-Hilfiker, Ben H. Lee, Junwei Song, Harald Saathoff, Xiaoli Shen, Ramakrishna Ramisetty, Sachchida N. Tripathi, Dilip Ganguly, Feng Jiang, Magdalena Vallon, Siegfried Schobesberger, Taina Yli-Juuti, and Claudia Mohr
Atmos. Chem. Phys., 24, 2607–2624, https://doi.org/10.5194/acp-24-2607-2024, https://doi.org/10.5194/acp-24-2607-2024, 2024
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We present distinct molecular composition and volatility of oxygenated organic aerosol particles in different rural, urban, and mountain environments. We do a comprehensive investigation of the relationship between the chemical composition and volatility of oxygenated organic aerosol particles across different systems and environments. This study provides implications for volatility descriptions of oxygenated organic aerosol particles in different model frameworks.
Susanna Strada, Andrea Pozzer, Graziano Giuliani, Erika Coppola, Fabien Solmon, Xiaoyan Jiang, Alex Guenther, Efstratios Bourtsoukidis, Dominique Serça, Jonathan Williams, and Filippo Giorgi
Atmos. Chem. Phys., 23, 13301–13327, https://doi.org/10.5194/acp-23-13301-2023, https://doi.org/10.5194/acp-23-13301-2023, 2023
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Water deficit modifies emissions of isoprene, an aromatic compound released by plants that influences the production of an air pollutant such as ozone. Numerical modelling shows that, during the warmest and driest summers, isoprene decreases between −20 and −60 % over the Euro-Mediterranean region, while near-surface ozone only diminishes by a few percent. Decreases in isoprene emissions not only happen under dry conditions, but also could occur after prolonged or repeated water deficits.
Matthias Kohl, Jos Lelieveld, Sourangsu Chowdhury, Sebastian Ehrhart, Disha Sharma, Yafang Cheng, Sachchida Nand Tripathi, Mathew Sebastian, Govindan Pandithurai, Hongli Wang, and Andrea Pozzer
Atmos. Chem. Phys., 23, 13191–13215, https://doi.org/10.5194/acp-23-13191-2023, https://doi.org/10.5194/acp-23-13191-2023, 2023
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Knowledge on atmospheric ultrafine particles (UFPs) with a diameter smaller than 100 nm is crucial for public health and the hydrological cycle. We present a new global dataset of UFP concentrations at the Earth's surface derived with a comprehensive chemistry–climate model and evaluated with ground-based observations. The evaluation results are combined with high-resolution primary emissions to downscale UFP concentrations to an unprecedented horizontal resolution of 0.1° × 0.1°.
Costanza Del Gobbo, Renato R. Colucci, Giovanni Monegato, Manja Žebre, and Filippo Giorgi
Clim. Past, 19, 1805–1823, https://doi.org/10.5194/cp-19-1805-2023, https://doi.org/10.5194/cp-19-1805-2023, 2023
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We studied atmosphere–cryosphere interaction during the last phase of the Last Glacial Maximum in the Alpine region, using a high-resolution regional climate model. We analysed the climate south and north of the Alps, using a detailed map of the Alpine equilibrium line altitude (ELA) to study the mechanism that sustained the Alpine glaciers at 21 ka. The Genoa low and a mild Mediterranean Sea led to frequent snowfall in the southern Alps, thus preserving the glaciers and lowering the ELA.
Sophie L. Haslett, David M. Bell, Varun Kumar, Jay G. Slowik, Dongyu S. Wang, Suneeti Mishra, Neeraj Rastogi, Atinderpal Singh, Dilip Ganguly, Joel Thornton, Feixue Zheng, Yuanyuan Li, Wei Nie, Yongchun Liu, Wei Ma, Chao Yan, Markku Kulmala, Kaspar R. Daellenbach, David Hadden, Urs Baltensperger, Andre S. H. Prevot, Sachchida N. Tripathi, and Claudia Mohr
Atmos. Chem. Phys., 23, 9023–9036, https://doi.org/10.5194/acp-23-9023-2023, https://doi.org/10.5194/acp-23-9023-2023, 2023
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In Delhi, some aspects of daytime and nighttime atmospheric chemistry are inverted, and parodoxically, vehicle emissions may be limiting other forms of particle production. This is because the nighttime emissions of nitrogen oxide (NO) by traffic and biomass burning prevent some chemical processes that would otherwise create even more particles and worsen the urban haze.
Vaishali Jain, Nidhi Tripathi, Sachchida N. Tripathi, Mansi Gupta, Lokesh K. Sahu, Vishnu Murari, Sreenivas Gaddamidi, Ashutosh K. Shukla, and Andre S. H. Prevot
Atmos. Chem. Phys., 23, 3383–3408, https://doi.org/10.5194/acp-23-3383-2023, https://doi.org/10.5194/acp-23-3383-2023, 2023
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This research chemically characterises 173 different NMVOCs (non-methane volatile organic compounds) measured in real time for three seasons in the city of the central Indo-Gangetic basin of India, Lucknow. Receptor modelling is used to analyse probable sources of NMVOCs and their crucial role in forming ozone and secondary organic aerosols. It is observed that vehicular emissions and solid fuel combustion are the highest contributors to the emission of primary and secondary NMVOCs.
Hazel Vernier, Neeraj Rastogi, Hongyu Liu, Amit Kumar Pandit, Kris Bedka, Anil Patel, Madineni Venkat Ratnam, Buduru Suneel Kumar, Bo Zhang, Harish Gadhavi, Frank Wienhold, Gwenael Berthet, and Jean-Paul Vernier
Atmos. Chem. Phys., 22, 12675–12694, https://doi.org/10.5194/acp-22-12675-2022, https://doi.org/10.5194/acp-22-12675-2022, 2022
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The chemical composition of the stratospheric aerosols collected aboard high-altitude balloons above the summer Asian monsoon reveals the presence of nitrate/nitrite. Using numerical simulations and satellite observations, we found that pollution as well as lightning could explain some of our observations.
Yu Yao, Jeffrey H. Curtis, Joseph Ching, Zhonghua Zheng, and Nicole Riemer
Atmos. Chem. Phys., 22, 9265–9282, https://doi.org/10.5194/acp-22-9265-2022, https://doi.org/10.5194/acp-22-9265-2022, 2022
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Investigating the impacts of aerosol mixing state on aerosol optical properties has a long history from both the modeling and experimental perspective. In this study, we used particle-resolved simulations as a benchmark to determine the error in optical properties when using simplified aerosol representations. We found that errors in single scattering albedo due to the internal mixture assumptions can have substantial effects on calculating aerosol direct radiative forcing.
Varun Kumar, Stamatios Giannoukos, Sophie L. Haslett, Yandong Tong, Atinderpal Singh, Amelie Bertrand, Chuan Ping Lee, Dongyu S. Wang, Deepika Bhattu, Giulia Stefenelli, Jay S. Dave, Joseph V. Puthussery, Lu Qi, Pawan Vats, Pragati Rai, Roberto Casotto, Rangu Satish, Suneeti Mishra, Veronika Pospisilova, Claudia Mohr, David M. Bell, Dilip Ganguly, Vishal Verma, Neeraj Rastogi, Urs Baltensperger, Sachchida N. Tripathi, André S. H. Prévôt, and Jay G. Slowik
Atmos. Chem. Phys., 22, 7739–7761, https://doi.org/10.5194/acp-22-7739-2022, https://doi.org/10.5194/acp-22-7739-2022, 2022
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Here we present source apportionment results from the first field deployment in Delhi of an extractive electrospray ionization time-of-flight mass spectrometer (EESI-TOF). The EESI-TOF is a recently developed instrument capable of providing uniquely detailed online chemical characterization of organic aerosol (OA), in particular the secondary OA (SOA) fraction. Here, we are able to apportion not only primary OA but also SOA to specific sources, which is performed for the first time in Delhi.
Pawan Gupta, Prakash Doraiswamy, Jashwanth Reddy, Palak Balyan, Sagnik Dey, Ryan Chartier, Adeel Khan, Karmann Riter, Brandon Feenstra, Robert C. Levy, Nhu Nguyen Minh Tran, Olga Pikelnaya, Kurinji Selvaraj, Tanushree Ganguly, and Karthik Ganesan
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-140, https://doi.org/10.5194/amt-2022-140, 2022
Revised manuscript not accepted
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The use of low-cost sensors in air quality monitoring has been gaining interest across all walks of society. We present the results of evaluations of the PurpleAir against regulatory-grade PM2.5. The results indicate that with proper calibration, we can achieve bias-corrected PM2.5 data using PA sensors. Our study also suggests that pre-deployment calibrations developed at local or regional scales are required for the PA sensors to correct data from the field for scientific data analysis.
Matthew L. Dawson, Christian Guzman, Jeffrey H. Curtis, Mario Acosta, Shupeng Zhu, Donald Dabdub, Andrew Conley, Matthew West, Nicole Riemer, and Oriol Jorba
Geosci. Model Dev., 15, 3663–3689, https://doi.org/10.5194/gmd-15-3663-2022, https://doi.org/10.5194/gmd-15-3663-2022, 2022
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Progress in identifying complex, mixed-phase physicochemical processes has resulted in an advanced understanding of the evolution of atmospheric systems but has also introduced a level of complexity that few atmospheric models were designed to handle. We present a flexible treatment for multiphase chemical processes for models of diverse scale, from box up to global models. This enables users to build a customized multiphase mechanism that is accessible to a much wider community.
Himadri Sekhar Bhowmik, Ashutosh Shukla, Vipul Lalchandani, Jay Dave, Neeraj Rastogi, Mayank Kumar, Vikram Singh, and Sachchida Nand Tripathi
Atmos. Meas. Tech., 15, 2667–2684, https://doi.org/10.5194/amt-15-2667-2022, https://doi.org/10.5194/amt-15-2667-2022, 2022
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This study presents comparisons between online and offline measurements of both refractory and non-refractory aerosol. This study shows differences between the measurements, related to either the limitations of the instrument (e.g., aerosol mass spectrometer only observing non-refractory aerosol) or known interferences with the technique (e.g., volatilization or reactions). The findings highlight the measurement methods' accuracy and imply the particular type of measurements needed.
Chandan Sarangi, TC Chakraborty, Sachchidanand Tripathi, Mithun Krishnan, Ross Morrison, Jonathan Evans, and Lina M. Mercado
Atmos. Chem. Phys., 22, 3615–3629, https://doi.org/10.5194/acp-22-3615-2022, https://doi.org/10.5194/acp-22-3615-2022, 2022
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Transpiration fluxes by vegetation are reduced under heat stress to conserve water. However, in situ observations over northern India show that the strength of the inverse association between transpiration and atmospheric vapor pressure deficit is weakening in the presence of heavy aerosol loading. This finding not only implicates the significant role of aerosols in modifying the evaporative fraction (EF) but also warrants an in-depth analysis of the aerosol–plant–temperature–EF continuum.
Erika Coppola, Paolo Stocchi, Emanuela Pichelli, Jose Abraham Torres Alavez, Russell Glazer, Graziano Giuliani, Fabio Di Sante, Rita Nogherotto, and Filippo Giorgi
Geosci. Model Dev., 14, 7705–7723, https://doi.org/10.5194/gmd-14-7705-2021, https://doi.org/10.5194/gmd-14-7705-2021, 2021
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In this work we describe the development of a non-hydrostatic version of the regional climate model RegCM4-NH, implemented to allow simulations at convection-permitting scales of <4 km for climate applications. The new core is described, and three case studies of intense convection are carried out to illustrate the model performances. Comparison with observations is much improved with respect to with coarse grid runs. RegCM4-NH offers a promising tool for climate investigations at a local scale.
Zhonghua Zheng, Matthew West, Lei Zhao, Po-Lun Ma, Xiaohong Liu, and Nicole Riemer
Atmos. Chem. Phys., 21, 17727–17741, https://doi.org/10.5194/acp-21-17727-2021, https://doi.org/10.5194/acp-21-17727-2021, 2021
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Aerosol mixing state is an important emergent property that affects aerosol radiative forcing and aerosol–cloud interactions, but it has not been easy to constrain this property globally. We present a framework for evaluating the error in aerosol mixing state induced by aerosol representation assumptions, which is one of the important contributors to structural uncertainty in aerosol models. Our study provides insights into potential improvements to model process representation for aerosols.
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Short summary
Accurate representation of aerosols in climate models is critical for minimizing the uncertainty in climate projections. Here, we implement region-specific emission fluxes and a more accurate scheme for carbonaceous aerosol ageing processes in a regional climate model (RegCM4) and show that it improves model performance significantly against in situ, reanalysis, and satellite data over the Indian subcontinent. We recommend improving the model performance before using them for climate studies.
Accurate representation of aerosols in climate models is critical for minimizing the uncertainty...
