Articles | Volume 22, issue 16
https://doi.org/10.5194/acp-22-10677-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-22-10677-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
23 Aug 2022
Research article |
| 23 Aug 2022
| 23 Aug 2022
Evaluation of the WRF and CHIMERE models for the simulation of PM2.5 in large East African urban conurbations
School of Civil Engineering, University of Birmingham, Birmingham, UK
School of Geography, Earth and Environmental Sciences (GEES), University of Birmingham, Birmingham, UK
Michael Burrow
School of Civil Engineering, University of Birmingham, Birmingham, UK
Andrew Quinn
School of Civil Engineering, University of Birmingham, Birmingham, UK
Eloise A. Marais
Department of Geography, University College London, London, UK
Ajit Singh
School of Geography, Earth and Environmental Sciences (GEES), University of Birmingham, Birmingham, UK
David Ng'ang'a
Institute of Nuclear Science and Technology, University of Nairobi, Nairobi, Kenya
Michael J. Gatari
Institute of Nuclear Science and Technology, University of Nairobi, Nairobi, Kenya
Francis D. Pope
School of Geography, Earth and Environmental Sciences (GEES), University of Birmingham, Birmingham, UK
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Andrea Mazzeo, Christian Pfrang, and Zaheer Ahmad Nasir
EGUsphere, https://doi.org/10.5194/egusphere-2025-783, https://doi.org/10.5194/egusphere-2025-783, 2025
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Indoor air pollution is a serious public health risk. There is an urgent need to understand how various sources contribute to air pollution over time in homes, workplaces, vehicles, and recreational areas. The InAPI tool is built on a database of indoor air pollutants in the UK. It organizes information about pollutants, environments, and activities, and provides data on indoor pollutant levels and their emission rates. This is crucial to guide future research in managing indoor air quality.
Yugo Kanaya, Roberto Sommariva, Alfonso Saiz-Lopez, Andrea Mazzeo, Theodore K. Koenig, Kaori Kawana, James E. Johnson, Aurélie Colomb, Pierre Tulet, Suzie Molloy, Ian E. Galbally, Rainer Volkamer, Anoop Mahajan, John W. Halfacre, Paul B. Shepson, Julia Schmale, Hélène Angot, Byron Blomquist, Matthew D. Shupe, Detlev Helmig, Junsu Gil, Meehye Lee, Sean C. Coburn, Ivan Ortega, Gao Chen, James Lee, Kenneth C. Aikin, David D. Parrish, John S. Holloway, Thomas B. Ryerson, Ilana B. Pollack, Eric J. Williams, Brian M. Lerner, Andrew J. Weinheimer, Teresa Campos, Frank M. Flocke, J. Ryan Spackman, Ilann Bourgeois, Jeff Peischl, Chelsea R. Thompson, Ralf M. Staebler, Amir A. Aliabadi, Wanmin Gong, Roeland Van Malderen, Anne M. Thompson, Ryan M. Stauffer, Debra E. Kollonige, Juan Carlos Gómez Martin, Masatomo Fujiwara, Katie Read, Matthew Rowlinson, Keiichi Sato, Junichi Kurokawa, Yoko Iwamoto, Fumikazu Taketani, Hisahiro Takashima, Monica Navarro Comas, Marios Panagi, and Martin G. Schultz
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-566, https://doi.org/10.5194/essd-2024-566, 2025
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The first comprehensive dataset of tropospheric ozone over oceans/polar regions is presented, including 77 ship/buoy and 48 aircraft campaign observations (1977–2022, 0–5000 m altitude), supplemented by ozonesonde and surface data. Air masses isolated from land for 72+ hours are systematically selected as essentially oceanic. Among the 11 global regions, they show daytime decreases of 10–16% in the tropics, while near-zero depletions are rare, unlike in the Arctic, implying different mechanisms.
Ryan Hossaini, David Sherry, Zihao Wang, Martyn P. Chipperfield, Wuhu Feng, David E. Oram, Karina E. Adcock, Stephen A. Montzka, Isobel J. Simpson, Andrea Mazzeo, Amber A. Leeson, Elliot Atlas, and Charles C.-K. Chou
Atmos. Chem. Phys., 24, 13457–13475, https://doi.org/10.5194/acp-24-13457-2024, https://doi.org/10.5194/acp-24-13457-2024, 2024
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DCE (1,2-dichloroethane) is an industrial chemical used to produce PVC (polyvinyl chloride). We analysed DCE production data to estimate global DCE emissions (2002–2020). The emissions were included in an atmospheric model and evaluated by comparing simulated DCE to DCE measurements in the troposphere. We show that DCE contributes ozone-depleting Cl to the stratosphere and that this has increased with increasing DCE emissions. DCE’s impact on stratospheric O3 is currently small but non-zero.
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This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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William J. Collins, Fiona M. O'Connor, Rachael E. Byrom, Øivind Hodnebrog, Patrick Jöckel, Mariano Mertens, Gunnar Myhre, Matthias Nützel, Dirk Olivié, Ragnhild Bieltvedt Skeie, Laura Stecher, Larry W. Horowitz, Vaishali Naik, Gregory Faluvegi, Ulas Im, Lee T. Murray, Drew Shindell, Kostas Tsigaridis, Nathan Luke Abraham, and James Keeble
Atmos. Chem. Phys., 25, 9031–9060, https://doi.org/10.5194/acp-25-9031-2025, https://doi.org/10.5194/acp-25-9031-2025, 2025
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We used 7 climate models that include atmospheric chemistry and find that in a scenario with weak controls on air quality, the warming effects (over 2015 to 2050) of decreases in ozone-depleting substances and increases in air quality pollutants are approximately equal and would make ozone the second highest contributor to warming over this period. We find that for stratospheric ozone recovery, the standard measure of climate effects underestimates a more comprehensive measure.
Nana Wei, Eloise A. Marais, Gongda Lu, Robert G. Ryan, and Bastien Sauvage
Atmos. Chem. Phys., 25, 7925–7940, https://doi.org/10.5194/acp-25-7925-2025, https://doi.org/10.5194/acp-25-7925-2025, 2025
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This study uses reactive nitrogen observations from NASA DC-8 research aircraft and the In-service Aircraft for a Global Observing System (IAGOS) campaigns to characterize reactive nitrogen seasonality and composition in the global upper troposphere and to diagnose the greatest knowledge gaps from comparison to a state-of-the-science model, GEOS-Chem, that need to be resolved for climate, nitrogen cycle, and air pollution assessments.
Andrea Mazzeo, Christian Pfrang, and Zaheer Ahmad Nasir
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Indoor air pollution is a serious public health risk. There is an urgent need to understand how various sources contribute to air pollution over time in homes, workplaces, vehicles, and recreational areas. The InAPI tool is built on a database of indoor air pollutants in the UK. It organizes information about pollutants, environments, and activities, and provides data on indoor pollutant levels and their emission rates. This is crucial to guide future research in managing indoor air quality.
Beata Opacka, Trissevgeni Stavrakou, Jean-François Müller, Isabelle De Smedt, Jos van Geffen, Eloise A. Marais, Rebekah P. Horner, Dylan B. Millet, Kelly C. Wells, and Alex B. Guenther
Atmos. Chem. Phys., 25, 2863–2894, https://doi.org/10.5194/acp-25-2863-2025, https://doi.org/10.5194/acp-25-2863-2025, 2025
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Vegetation releases biogenic volatile organic compounds, while soils and lightning contribute to the natural emissions of nitrogen oxides into the atmosphere. These gases interact in complex ways. Using satellite data and models, we developed a new method to simultaneously optimize these natural emissions over Africa in 2019. Our approach resulted in an increase in natural emissions, supported by independent data indicating that current estimates are underestimated.
Yugo Kanaya, Roberto Sommariva, Alfonso Saiz-Lopez, Andrea Mazzeo, Theodore K. Koenig, Kaori Kawana, James E. Johnson, Aurélie Colomb, Pierre Tulet, Suzie Molloy, Ian E. Galbally, Rainer Volkamer, Anoop Mahajan, John W. Halfacre, Paul B. Shepson, Julia Schmale, Hélène Angot, Byron Blomquist, Matthew D. Shupe, Detlev Helmig, Junsu Gil, Meehye Lee, Sean C. Coburn, Ivan Ortega, Gao Chen, James Lee, Kenneth C. Aikin, David D. Parrish, John S. Holloway, Thomas B. Ryerson, Ilana B. Pollack, Eric J. Williams, Brian M. Lerner, Andrew J. Weinheimer, Teresa Campos, Frank M. Flocke, J. Ryan Spackman, Ilann Bourgeois, Jeff Peischl, Chelsea R. Thompson, Ralf M. Staebler, Amir A. Aliabadi, Wanmin Gong, Roeland Van Malderen, Anne M. Thompson, Ryan M. Stauffer, Debra E. Kollonige, Juan Carlos Gómez Martin, Masatomo Fujiwara, Katie Read, Matthew Rowlinson, Keiichi Sato, Junichi Kurokawa, Yoko Iwamoto, Fumikazu Taketani, Hisahiro Takashima, Monica Navarro Comas, Marios Panagi, and Martin G. Schultz
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-566, https://doi.org/10.5194/essd-2024-566, 2025
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DCE (1,2-dichloroethane) is an industrial chemical used to produce PVC (polyvinyl chloride). We analysed DCE production data to estimate global DCE emissions (2002–2020). The emissions were included in an atmospheric model and evaluated by comparing simulated DCE to DCE measurements in the troposphere. We show that DCE contributes ozone-depleting Cl to the stratosphere and that this has increased with increasing DCE emissions. DCE’s impact on stratospheric O3 is currently small but non-zero.
Rebekah P. Horner, Eloise A. Marais, Nana Wei, Robert G. Ryan, and Viral Shah
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Nitrogen oxides (NOx ≡ NO + NO2) affect tropospheric ozone and the hydroxyl radical, influencing climate and atmospheric oxidation. To address the lack of routine observations of NOx, we cloud slice satellite observations of NO2 to derive a new dataset of global vertical profiles of NO2. We evaluate our data against in situ aircraft observations and use these data to critique the contemporary understanding of tropospheric NOx, as simulated by the GEOS-Chem model.
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Surface morphology is critical for enhanced performance in thin films. However, there is limited understanding regarding the accurate control of thin-film morphology. This work provides a systematic way of optimizing different parameters to achieve the desired surface morphologies. Key parameters for controlling thin-film morphology have been identified. Using these parameters, a systematic design schedule for electrosprayed thin films with different surface morphologies has been developed.
Leonard Kirago, Örjan Gustafsson, Samuel Mwaniki Gaita, Sophie L. Haslett, Michael J. Gatari, Maria Elena Popa, Thomas Röckmann, Christoph Zellweger, Martin Steinbacher, Jörg Klausen, Christian Félix, David Njiru, and August Andersson
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This study provides ground-observational evidence that supports earlier suggestions that savanna fires are the main emitters and modulators of carbon monoxide gas in Africa. Using isotope-based techniques, the study has shown that about two-thirds of this gas is emitted from savanna fires, while for urban areas, in this case Nairobi, primary sources approach 100 %. The latter has implications for air quality policy, suggesting primary emissions such as traffic should be targeted.
Sophie A. Mills, Adam Milsom, Christian Pfrang, A. Rob MacKenzie, and Francis D. Pope
Atmos. Meas. Tech., 16, 4885–4898, https://doi.org/10.5194/amt-16-4885-2023, https://doi.org/10.5194/amt-16-4885-2023, 2023
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Pollen grains are important components of the atmosphere and have the potential to impact upon cloud processes via their ability to help in the formation of rain droplets. This study investigates the hygroscopicity of two different pollen species using an acoustic levitator. Pollen grains are levitated, and their response to changes in relative humidity is investigated. A key advantage of this method is that it is possible study pollen shape under varying environmental conditions.
Robert G. Ryan, Eloise A. Marais, Eleanor Gershenson-Smith, Robbie Ramsay, Jan-Peter Muller, Jan-Lukas Tirpitz, and Udo Frieß
Atmos. Chem. Phys., 23, 7121–7139, https://doi.org/10.5194/acp-23-7121-2023, https://doi.org/10.5194/acp-23-7121-2023, 2023
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We describe the first data retrieval from a newly installed instrument providing measurements of vertical profiles of air pollution over Central London during heatwaves in summer 2022. We use these observations with surface air quality network measurements to support interpretation that an exponential increase in biogenic emissions of isoprene during heatwaves provides the limiting ingredient for severe ozone pollution, leading to non-compliance with the national ozone air quality standard.
Dimitrios Bousiotis, David C. S. Beddows, Ajit Singh, Molly Haugen, Sebastián Diez, Pete M. Edwards, Adam Boies, Roy M. Harrison, and Francis D. Pope
Atmos. Meas. Tech., 15, 4047–4061, https://doi.org/10.5194/amt-15-4047-2022, https://doi.org/10.5194/amt-15-4047-2022, 2022
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In the last decade, low-cost sensors have revolutionised the field of air quality monitoring. This paper extends the ability of low-cost sensors to not only measure air pollution, but also to understand where the pollution comes from. This "source apportionment" is a critical step in air quality management to allow for the mitigation of air pollution. The techniques developed in this paper have the potential for great impact in both research and industrial applications.
Marios Panagi, Roberto Sommariva, Zoë L. Fleming, Paul S. Monks, Gongda Lu, Eloise A. Marais, James R. Hopkins, Alastair C. Lewis, Qiang Zhang, James D. Lee, Freya A. Squires, Lisa K. Whalley, Eloise J. Slater, Dwayne E. Heard, Robert Woodward-Massey, Chunxiang Ye, and Joshua D. Vande Hey
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-379, https://doi.org/10.5194/acp-2022-379, 2022
Revised manuscript not accepted
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A dispersion model and a box model were combined to investigate the evolution of VOCs in Beijing once they are emitted from anthropogenic sources. It was determined that during the winter time the VOC concentrations in Beijing are driven predominantly by sources within Beijing and by a combination of transport and chemistry during the summer. Furthermore, the results in the paper highlight the need for a season specific policy.
Tony Bush, Nick Papaioannou, Felix Leach, Francis D. Pope, Ajit Singh, G. Neil Thomas, Brian Stacey, and Suzanne Bartington
Atmos. Meas. Tech., 15, 3261–3278, https://doi.org/10.5194/amt-15-3261-2022, https://doi.org/10.5194/amt-15-3261-2022, 2022
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Poor air quality is a human health risk which demands high-spatiotemporal-resolution monitoring data to manage. Low-cost air quality sensors present a convenient pathway to delivering these needs, compared to traditional methods, but bring methodological challenges which can limit operational ability. In this study within Oxford, UK, we develop machine learning methods to improve the quality of low-cost sensors for NO2, PM10 (particulate matter) and PM2.5 and demonstrate their effectiveness.
Aileen B. Baird, Edward J. Bannister, A. Robert MacKenzie, and Francis D. Pope
Biogeosciences, 19, 2653–2669, https://doi.org/10.5194/bg-19-2653-2022, https://doi.org/10.5194/bg-19-2653-2022, 2022
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Forest environments contain a wide variety of airborne biological particles (bioaerosols) important for plant and animal health and biosphere–atmosphere interactions. Using low-cost sensors and a free-air carbon dioxide enrichment (FACE) experiment, we monitor the impact of enhanced CO2 on airborne particles. No effect of the enhanced CO2 treatment on total particle concentrations was observed, but a potential suppression of high concentration bioaerosol events was detected under enhanced CO2.
Richard J. Pope, Rebecca Kelly, Eloise A. Marais, Ailish M. Graham, Chris Wilson, Jeremy J. Harrison, Savio J. A. Moniz, Mohamed Ghalaieny, Steve R. Arnold, and Martyn P. Chipperfield
Atmos. Chem. Phys., 22, 4323–4338, https://doi.org/10.5194/acp-22-4323-2022, https://doi.org/10.5194/acp-22-4323-2022, 2022
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Nitrogen oxides (NOx) are potent air pollutants which directly impact on human health. In this study, we use satellite nitrogen dioxide (NO2) data to evaluate the spatial distribution and temporal evolution of the UK official NOx emissions inventory, with reasonable agreement. We also derived satellite-based NOx emissions for several UK cities. In the case of London and Birmingham, the NAEI NOx emissions are potentially too low by >50%.
Leigh R. Crilley, Louisa J. Kramer, Francis D. Pope, Chris Reed, James D. Lee, Lucy J. Carpenter, Lloyd D. J. Hollis, Stephen M. Ball, and William J. Bloss
Atmos. Chem. Phys., 21, 18213–18225, https://doi.org/10.5194/acp-21-18213-2021, https://doi.org/10.5194/acp-21-18213-2021, 2021
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Nitrous acid (HONO) is a key source of atmospheric oxidants. We evaluate if the ocean surface is a source of HONO for the marine boundary layer, using measurements from two contrasting coastal locations. We observed no evidence for a night-time ocean surface source, in contrast to previous work. This points to significant geographical variation in the predominant HONO formation mechanisms in marine environments, reflecting possible variability in the sea-surface microlayer composition.
Dimitrios Bousiotis, Francis D. Pope, David C. S. Beddows, Manuel Dall'Osto, Andreas Massling, Jakob Klenø Nøjgaard, Claus Nordstrøm, Jarkko V. Niemi, Harri Portin, Tuukka Petäjä, Noemi Perez, Andrés Alastuey, Xavier Querol, Giorgos Kouvarakis, Nikos Mihalopoulos, Stergios Vratolis, Konstantinos Eleftheriadis, Alfred Wiedensohler, Kay Weinhold, Maik Merkel, Thomas Tuch, and Roy M. Harrison
Atmos. Chem. Phys., 21, 11905–11925, https://doi.org/10.5194/acp-21-11905-2021, https://doi.org/10.5194/acp-21-11905-2021, 2021
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Formation of new particles is a key process in the atmosphere. New particle formation events arising from nucleation of gaseous precursors have been analysed in extensive datasets from 13 sites in five European countries in terms of frequency, nucleation rate, and particle growth rate, with several common features and many differences identified. Although nucleation frequencies are lower at roadside sites, nucleation rates and particle growth rates are typically higher.
Gongda Lu, Eloise A. Marais, Tuan V. Vu, Jingsha Xu, Zongbo Shi, James D. Lee, Qiang Zhang, Lu Shen, Gan Luo, and Fangqun Yu
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-428, https://doi.org/10.5194/acp-2021-428, 2021
Revised manuscript not accepted
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Emission controls were imposed in Beijing-Tianjin-Hebei in northern China in autumn-winter 2017. We find that regional PM2.5 targets (15 % decrease relative to previous year) were exceeded. Our analysis shows that decline in precursor emissions only leads to less than half (43 %) the improved air quality. Most of the change (57 %) is due to interannual variability in meteorology. Stricter emission controls may be necessary in years with unfavourable meteorology.
Dimitrios Bousiotis, Ajit Singh, Molly Haugen, David C. S. Beddows, Sebastián Diez, Killian L. Murphy, Pete M. Edwards, Adam Boies, Roy M. Harrison, and Francis D. Pope
Atmos. Meas. Tech., 14, 4139–4155, https://doi.org/10.5194/amt-14-4139-2021, https://doi.org/10.5194/amt-14-4139-2021, 2021
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Measurement and source apportionment of atmospheric pollutants are crucial for the assessment of air quality and the implementation of policies for their improvement. This study highlights the current capability of low-cost sensors in source identification and differentiation using clustering approaches. Future directions towards particulate matter source apportionment using low-cost OPCs are highlighted.
Karn Vohra, Eloise A. Marais, Shannen Suckra, Louisa Kramer, William J. Bloss, Ravi Sahu, Abhishek Gaur, Sachchida N. Tripathi, Martin Van Damme, Lieven Clarisse, and Pierre-F. Coheur
Atmos. Chem. Phys., 21, 6275–6296, https://doi.org/10.5194/acp-21-6275-2021, https://doi.org/10.5194/acp-21-6275-2021, 2021
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We find satellite observations of atmospheric composition generally reproduce variability in surface air pollution, so we use their long record to estimate air quality trends in major UK and Indian cities. Our trend analysis shows that pollutants targeted with air quality policies have not declined in Delhi and Kanpur but have in London and Birmingham, with the exception of a recent and dramatic increase in reactive volatile organics in London. Unregulated ammonia has increased only in Delhi.
Eloise A. Marais, John F. Roberts, Robert G. Ryan, Henk Eskes, K. Folkert Boersma, Sungyeon Choi, Joanna Joiner, Nader Abuhassan, Alberto Redondas, Michel Grutter, Alexander Cede, Laura Gomez, and Monica Navarro-Comas
Atmos. Meas. Tech., 14, 2389–2408, https://doi.org/10.5194/amt-14-2389-2021, https://doi.org/10.5194/amt-14-2389-2021, 2021
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Nitrogen oxides in the upper troposphere have a profound influence on the global troposphere, but routine reliable observations there are exceedingly rare. We apply cloud-slicing to TROPOMI total columns of nitrogen dioxide (NO2) at high spatial resolution to derive near-global observations of NO2 in the upper troposphere and show consistency with existing datasets. These data offer tremendous potential to address knowledge gaps in this oft underappreciated portion of the atmosphere.
Dimitrios Bousiotis, James Brean, Francis D. Pope, Manuel Dall'Osto, Xavier Querol, Andrés Alastuey, Noemi Perez, Tuukka Petäjä, Andreas Massling, Jacob Klenø Nøjgaard, Claus Nordstrøm, Giorgos Kouvarakis, Stergios Vratolis, Konstantinos Eleftheriadis, Jarkko V. Niemi, Harri Portin, Alfred Wiedensohler, Kay Weinhold, Maik Merkel, Thomas Tuch, and Roy M. Harrison
Atmos. Chem. Phys., 21, 3345–3370, https://doi.org/10.5194/acp-21-3345-2021, https://doi.org/10.5194/acp-21-3345-2021, 2021
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New particle formation events from 16 sites over Europe have been studied, and the influence of meteorological and atmospheric composition variables has been investigated. Some variables, like solar radiation intensity and temperature, have a positive effect on the occurrence of these events, while others have a negative effect, affecting different aspects such as the rate at which particles are formed or grow. This effect varies depending on the site type and magnitude of these variables.
Cited articles
Alduchov, O. A. and Eskridge, R. E.: Improved Magnus Form Approximation of
Saturation Vapor Pressure, J. Appl. Meteorol., 35, 601–609,
https://doi.org/10.1175/1520-0450(1996)035<0601:IMFAOS>2.0.CO;2, 1996.
Amegah, A. K. and Agyei-Mensah, S.: Urban air pollution in Sub-Saharan
Africa: Time for action, Environ. Pollut., 220, 738–743,
https://doi.org/10.1016/j.envpol.2016.09.042, 2017.
Anav, A., Menut, L., Khvorostyanov, D., and VİOvy, N.: Impact of
tropospheric ozone on the Euro-Mediterranean vegetation, Glob. Change
Biol., 17, 2342–2359, https://doi.org/10.1111/j.1365-2486.2010.02387.x, 2011.
Assamoi, E.-M. and Liousse, C.: A new inventory for two-wheel vehicle
emissions in West Africa for 2002, Atmos. Environ., 44, 3985–3996, https://doi.org/10.1016/j.atmosenv.2010.06.048, 2010.
Avis, W. and Khaemba, W.: Vulnerability and air pollution, University of Birmingham & African Centre for Technology Studies, Literary review March 2018,
https://static1.squarespace.com/static/5a6b5aad12abd97ed4679071/t/5e01ed93d42a33512e317cc5/1577184664458/ASAP+-+East+Africa+-+BVulnerability+and+Bair+pollution+Rapid+Lit+Review+Final-2.pdf (last access: 23 May 2021), 2018.
Barnard, J.: An evaluation of the FAST-J photolysis algorithm for predicting
nitrogen dioxide photolysis rates under clear and cloudy sky conditions,
Atmos. Environ., 38, 3393–3403, https://doi.org/10.1016/j.atmosenv.2004.03.034,
2004.
Bessagnet, B., Pirovano, G., Mircea, M., Cuvelier, C., Aulinger, A., Calori, G., Ciarelli, G., Manders, A., Stern, R., Tsyro, S., García Vivanco, M., Thunis, P., Pay, M.-T., Colette, A., Couvidat, F., Meleux, F., Rouïl, L., Ung, A., Aksoyoglu, S., Baldasano, J. M., Bieser, J., Briganti, G., Cappelletti, A., D'Isidoro, M., Finardi, S., Kranenburg, R., Silibello, C., Carnevale, C., Aas, W., Dupont, J.-C., Fagerli, H., Gonzalez, L., Menut, L., Prévôt, A. S. H., Roberts, P., and White, L.: Presentation of the EURODELTA III intercomparison exercise – evaluation of the chemistry transport models' performance on criteria pollutants and joint analysis with meteorology, Atmos. Chem. Phys., 16, 12667–12701, https://doi.org/10.5194/acp-16-12667-2016, 2016.
Bian, H. and Prather, M.: Fast-J2: accurate simulation of stratospheric
photolysis in global chemical models, J. Atmos. Chem, 41, 281–296,
https://doi.org/10.1023/A:1014980619462, 2002.
Bockarie, A. S., Marais, E. A., and MacKenzie, A. R.: Air Pollution and
Climate Forcing of the Charcoal Industry in Africa, Environ. Sci. Technol., 54,
13429–13438, https://doi.org/10.1021/acs.est.0c03754, 2020.
Boylan, J. W. and Russell, A. G.: PM and light extinction model performance
metrics, goals, and criteria for three-dimensional air quality models,
Atmos. Environ., 40, 4946–4959, https://doi.org/10.1016/j.atmosenv.2005.09.087,
2006.
Brauer, M., Amann, M., Burnett, R. T., Cohen, A., Dentener, F., Ezzati, M.,
Henderson, S. B., Krzyzanowski, M., Martin, R. V., Van Dingenen, R., van
Donkelaar, A., and Thurston, G. D.: Exposure assessment for estimation of
the global burden of disease attributable to outdoor air pollution, Environ.
Sci. Technol., 46, 652–660, https://doi.org/10.1021/es2025752, 2012.
Burroughs Peña, M. S. and Rollins, A.: Environmental Exposures and
Cardiovascular Disease: A Challenge for Health and Development in Low- and
Middle-Income Countries, Cardiol. Clin., 35, 71–86,
https://doi.org/10.1016/j.ccl.2016.09.001, 2017.
Carter, W. P. L.: Development of the SAPRC-07 chemical mechanism,
Atmos. Environ., 44, 5324–5335, https://doi.org/10.1016/j.atmosenv.2010.01.026,
2010.
Collins, W., Rasch, P., Boville, B., Hack, J., McCaa, J., Williamson, D.,
Kiehl, J., and Briegleb, B.: Description of the NCAR Community Atmosphere
Model (CAM 3.0), NCAR Tech Notes, https://www.cesm.ucar.edu/models/atm-cam/docs/description/description.pdf (last access: 18 October 2021), 2004.
Crippa, M., Guizzardi, D., Muntean, M., Schaaf, E., Dentener, F., van Aardenne, J. A., Monni, S., Doering, U., Olivier, J. G. J., Pagliari, V., and Janssens-Maenhout, G.: Gridded emissions of air pollutants for the period 1970–2012 within EDGAR v4.3.2, Earth Syst. Sci. Data, 10, 1987–2013, https://doi.org/10.5194/essd-10-1987-2018, 2018.
Dalal, S., Beunza, J. J., Volmink, J., Adebamowo, C., Bajunirwe, F.,
Njelekela, M., Mozaffarian, D., Fawzi, W., Willett, W., Adami, H. O., and
Holmes, M. D.: Non-communicable diseases in sub-Saharan Africa: what we know
now, Int. J. Epidemiol., 40, 885–901, https://doi.org/10.1093/ije/dyr050, 2011.
deSouza, P., Nthusi, V., Klopp, J., Shaw, b.e, Ho, W., Saffell, J., Jones, R., and Ratti, C.: A Nairobi experiment in using low cost air quality monitors,
Clean Air Journal, 27, 12–42,
https://doi.org/10.17159/2410-972X/2017/v27n2a6, 2017.
Egondi, T., Kyobutungi, C., Ng, N., Muindi, K., Oti, S., van de Vijver, S.,
Ettarh, R., and Rocklov, J.: Community perceptions of air pollution and
related health risks in Nairobi slums, Int. J. Environ. Res. Pub. He., 10,
4851–4868, https://doi.org/10.3390/ijerph10104851, 2013.
EPA: Revised Air Quality Standards for particle pollution and updates to the Air
Quality Index (AQI):
https://www.epa.gov/sites/default/files/2016-04/documents/2012_aqi_factsheet.pdf (last access: 12 May 2022), 2012.
FEWS NET: Poor rainfall across East Africa has increased rainfall deficits amid drought conditions, https://fews.net/east-africa/seasonal-monitor/march-2022, last access: 12 May 2022.
Gaita, S. M., Boman, J., Gatari, M. J., Pettersson, J. B. C., and Janhäll, S.: Source apportionment and seasonal variation of PM2.5 in a Sub-Saharan African city: Nairobi, Kenya, Atmos. Chem. Phys., 14, 9977–9991, https://doi.org/10.5194/acp-14-9977-2014, 2014.
Gatari, M. J., Kinney, P. L., Yan, B., Sclar, E., Volavka-Close, N., Ngo, N.
S., Mwaniki Gaita, S., Law, A., Ndiba, P. K., Gachanja, A., Graeff, J., and
Chillrud, S. N.: High airborne black carbon concentrations measured near
roadways in Nairobi, Kenya, Transport. Res. D-Tr. E., 68, 99–109, https://doi.org/10.1016/j.trd.2017.10.002, 2019.
Guenther, A., Karl, T., Harley, P., Wiedinmyer, C., Palmer, P. I., and Geron, C.: Estimates of global terrestrial isoprene emissions using MEGAN (Model of Emissions of Gases and Aerosols from Nature), Atmos. Chem. Phys., 6, 3181–3210, https://doi.org/10.5194/acp-6-3181-2006, 2006.
Hauglustaine, D. A., Hourdin, F., Jourdain, L., Filiberti, M. A., Walters,
S., Lamarque, J. F., and Holland, E. A.: Interactive chemistry in the
Laboratoire de Météorologie Dynamique general circulation model:
Description and background tropospheric chemistry evaluation, J.
Geophys. Res.-Atmos., 109, D04314, https://doi.org/10.1029/2003jd003957, 2004.
Haywood, J. M., Pelon, J., Formenti, P., Bharmal, N., Brooks, M., Capes, G.,
Chazette, P., Chou, C., Christopher, S., Coe, H., Cuesta, J., Derimian, Y.,
Desboeufs, K., Greed, G., Harrison, M., Heese, B., Highwood, E. J., Johnson,
B., Mallet, M., Marticorena, B., Marsham, J., Milton, S., Myhre, G.,
Osborne, S. R., Parker, D. J., Rajot, J. L., Schulz, M., Slingo, A.,
Tanré, D., and Tulet, P.: Overview of the Dust and Biomass-burning
Experiment and African Monsoon Multidisciplinary Analysis Special Observing
Period-0, J. Geophys. Res., 113, D00C17, https://doi.org/10.1029/2008jd010077, 2008.
Hong, S. Y., Dudhia, J., and Chen, S. H.: A revised approach to ice
microphysical processes for the bulk parameterization of clouds and
precipitation, Mon. Weather Rev., 132, 103–120, https://doi.org/10.1175/1520-0493(2004)132<0103:ARATIM>2.0.CO;2, 2004.
Hong, S. Y., Noh, Y., and Dudhia, J.: A new vertical diffusion package with an
explicit treatment of entrainment processes, Mon. Weather Rev., 134, 2318–2341, https://doi.org/10.1175/MWR3199.1,
2006.
Institut Pierre-Simon Laplace, Ecole Polytechnique, INERIS, CNRS:
CHIMERE: A multi-scale chemistry-transport model for atmospheric composition analysis and forecast, [data set], https://www.lmd.polytechnique.fr/chimere/2020_getcode.php, last access:
15 August 2022.
Kerandi, N., Arnault, J., Laux, P., Wagner, S., Kitheka, J., and Kunstmann,
H.: Joint atmospheric-terrestrial water balances for East Africa: a
WRF-Hydro case study for the upper Tana River basin, Theor. Appl.
Climatol., 131, 1337–1355, https://doi.org/10.1007/s00704-017-2050-8, 2017.
Kerandi, N. M., Laux, P., Arnault, J., and Kunstmann, H.: Performance of the
WRF model to simulate the seasonal and interannual variability of
hydrometeorological variables in East Africa: a case study for the Tana
River basin in Kenya, Theor. Appl. Climatol., 130, 401–418, https://doi.org/10.1007/s00704-016-1890-y, 2016.
Kinney, P. L., Gichuru, M. G., Volavka-Close, N., Ngo, N., Ndiba, P. K.,
Law, A., Gachanja, A., Gaita, S. M., Chillrud, S. N., and Sclar, E.: Traffic
Impacts on PM2.5 Air Quality in Nairobi, Kenya, Environ. Sci. Policy, 14,
369–378, https://doi.org/10.1016/j.envsci.2011.02.005, 2011.
Kume, A., Charles, K., Berehane, Y., Anders, E., and Ali, A.: Magnitude and
variation of traffic air pollution as measured by CO in the City of Addis
Ababa, Ethiopia, Ethiop. J. Health Dev., 24, 156–166,
https://doi.org/10.4314/ejhd.v24i3.68379, 2010.
Lacaux, J. P., Brustet, J. M., Delmas, R., Menaut, J. C., Abbadie, L., Bonsang, B., Cachier, H., Baudet, J., Andreae, M. O., and Helas, G.: Biomass burning in the
tropical savannas of Ivory Coast: An overview of the field experiment Fire
of Savannas (FOS/DECAFE 91), J. Atmos. Chem., 22, 195–216, https://doi.org/10.1007/BF00708189, 1995.
Li, C., Martin, R. V., van Donkelaar, A., Boys, B. L., Hammer, M. S., Xu, J.
W., Marais, E. A., Reff, A., Strum, M., Ridley, D. A., Crippa, M., Brauer,
M., and Zhang, Q.: Trends in Chemical Composition of Global and Regional
Population-Weighted Fine Particulate Matter Estimated for 25 Years, Environ.
Sci. Technol., 51, 11185–11195, https://doi.org/10.1021/acs.est.7b02530, 2017.
Liousse, C., Guillaume, B., Grégoire, J. M., Mallet, M., Galy, C., Pont, V., Akpo, A., Bedou, M., Castéra, P., Dungall, L., Gardrat, E., Granier, C., Konaré, A., Malavelle, F., Mariscal, A., Mieville, A., Rosset, R., Serça, D., Solmon, F., Tummon, F., Assamoi, E., Yoboué, V., and Van Velthoven, P.: Updated African biomass burning emission inventories in the framework of the AMMA-IDAF program, with an evaluation of combustion aerosols, Atmos. Chem. Phys., 10, 9631–9646, https://doi.org/10.5194/acp-10-9631-2010, 2010.
Liousse, C., Assamoi, E., Criqui, P., Granier, C., and Rosset, R.:
Explosive growth in African combustion emissions from 2005 to 2030,
Environ. Res. Lett., 9, 035003,
https://doi.org/10.1088/1748-9326/9/3/035003, 2014.
Loosmore, G. A. and Cederwall, R. T.: Precipitation scavenging of
atmospheric aerosols for emergency response applications: testing an updated
model with new real-time data, Atmos. Environ., 38, 993–1003,
https://doi.org/10.1016/j.atmosenv.2003.10.055, 2004.
Mailler, S., Menut, L., Khvorostyanov, D., Valari, M., Couvidat, F., Siour, G., Turquety, S., Briant, R., Tuccella, P., Bessagnet, B., Colette, A., Létinois, L., Markakis, K., and Meleux, F.: CHIMERE-2017: from urban to hemispheric chemistry-transport modeling, Geosci. Model Dev., 10, 2397–2423, https://doi.org/10.5194/gmd-10-2397-2017, 2017.
Marais, E. A. and Wiedinmyer, C.: Air Quality Impact of Diffuse and
Inefficient Combustion Emissions in Africa (DICE-Africa), Environ. Sci. Technol., 50, 10739–10745, https://doi.org/10.1021/acs.est.6b02602, 2016.
Marais, E. A., Silvern, R. F., Vodonos, A., Dupin, E., Bockarie, A. S.,
Mickley, L. J., and Schwartz, J.: Air Quality and Health Impact of Future
Fossil Fuel Use for Electricity Generation and Transport in Africa, Environ.
Sci. Technol., 53, 13524–13534, https://doi.org/10.1021/acs.est.9b04958, 2019.
Markakis, K., Valari, M., Perrussel, O., Sanchez, O., and Honore, C.: Climate-forced air-quality modeling at the urban scale: sensitivity to model resolution, emissions and meteorology, Atmos. Chem. Phys., 15, 7703–7723, https://doi.org/10.5194/acp-15-7703-2015, 2015.
Mazzeo, A.:
Anthropogenic emission inventory DICE-EDGAR data for the year 2013, UBIRA E-Data [data set],
https://doi.org/10.25500/edata.bham.00000695, 2021.
Mazzeo, A., Huneeus, N., Ordoñez, C., Orfanoz-Cheuquelaf, A., Menut, L.,
Mailler, S., Valari, M., van der Gon, H. D., Gallardo, L., and Muñoz,
R.: Impact of residential combustion and transport emissions on air
pollution in Santiago during winter, Atmos. Environ., 190, 195–208,
2018.
Mbewu, A. and Mbanya, J. C.: Cardiovascular Disease, in: Disease and Mortality in Sub-Saharan Africa, edited by: Jamison, D. T., Feachem, R. G., and Makgoba, M. W., 2nd edition, Washington (DC), The International Bank for Reconstruction and Development/The World Bank, chap. 21, https://www.ncbi.nlm.nih.gov/books/NBK2294/
(last access: 12 January 2021), 2006.
MetOffice: Integrated Data Archive System (MIDAS) Land and Marine Surface
Stations Data (1853–current), http://catalogue.ceda.ac.uk/uuid/220a65615218d5c9cc9e4785a3234bd0 (last access: 12 February 2019), 2012.
Met Office UK:
Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations Data (1853–current), [data set], http://catalogue.ceda.ac.uk/uuid/220a65615218d5c9cc9e4785a3234bd0,
last access: 12 February 2019.
Nenes, A., Pilinis, C., and Pandis, S.: Isorropia: a new thermodynamic model
for inorganic multicomponent atmospheric aerosols, Aquat. Geochem., 4,
123–152, https://doi.org/10.1023/A:1009604003981, 1998.
Ngo, N. S., Gatari, M., Yan, B., Chillrud, S. N., Bouhamam, K., and Kinneym,
P. L.: Occupational exposure to roadway emissions and inside informal
settlements in sub-Saharan Africa: A pilot study in Nairobi, Kenya, Atmos.
Environ., 111, 179–184, https://doi.org/10.1016/j.atmosenv.2015.04.008, 2015.
Ogega, O. M., Wanjohi, H. N., and Mbugua, J.: Exploring the Future of Nairobi National Park in a Changing Climate and Urban Growth. The Geography of Climate Change Adaptation in Urban Africa, 249–272,
https://doi.org/10.1007/978-3-030-04873-0_9, 2019.
openAFRICA:
https://open.africa/dataset/kenya-administrative-boundaries/resource/b5bee56d-b7cb-4f23-8f2b-356ca0044bf3 (last access: 25 May 2021),
2018.
Pai, S. J., Heald, C. L., Pierce, J. R., Farina, S. C., Marais, E. A., Jimenez, J. L., Campuzano-Jost, P., Nault, B. A., Middlebrook, A. M., Coe, H., Shilling, J. E., Bahreini, R., Dingle, J. H., and Vu, K.: An evaluation of global organic aerosol schemes using airborne observations, Atmos. Chem. Phys., 20, 2637–2665, https://doi.org/10.5194/acp-20-2637-2020, 2020.
Parkin, D. M., Sitas, F., Chirenje, M., Stein, L., Abratt, R., and Wabinga,
H.: Part I: Cancer in Indigenous Africans–burden, distribution, and
trends, Lancet Oncol., 9, 683–692, https://doi.org/10.1016/S1470-2045(08)70175-X, 2008.
Petkova, E. P., Jack, D. W., Volavka-Close, N. H., and Kinney, P. L.:
Particulate matter pollution in African cities, Air Qual. Atmos.
Hlth., 6, 603–614, https://doi.org/10.1007/s11869-013-0199-6,
2013.
Pohl, B., Crétat, J., and Camberlin, P.: Testing WRF capability in
simulating the atmospheric water cycle over Equatorial East Africa, Clim.
Dynam., 37, 1357–1379, https://doi.org/10.1007/s00382-011-1024-2, 2011.
Pope, F. D., Gatari, M., Ng'ang'a, D., Poynter, A., and Blake, R.: Airborne particulate matter monitoring in Kenya using calibrated low-cost sensors, Atmos. Chem. Phys., 18, 15403–15418, https://doi.org/10.5194/acp-18-15403-2018, 2018.
Powers, J. G., Klemp, J. B., Skamarock, W. C., Davis, C. A., Dudhia, J., Gill,
D. O., Coen, J. L., Gochis, D. J., Ah madov, R., Peckham, S. E., Grell, G. A.,
Michalakes, J., Trahan, S., Benjamin, S. G., Alexander, C. R., Di mego, G. J.,
Wang, W., Schwartz, C. S., Romine, G. S., Liu, Z., Snyder, C., Chen, F.,
Barlage, M. J., Yu, W., and Duda, M. G.: The weather research and forecasting
model: overview, system efforts, and future directions, B. Am. Meteorol.
Soc., 98, 1717–1737,
https://doi.org/10.1175/BAMS-D-15-00308.1, 2017.
Pun, B. K., Seigneur, C., and Lohman, K.: Modeling secondary organic aerosol
formation via multiphase partitioning with molecular data, Environ. Sci.
Technol., 40, 4722–4731, https://doi.org/10.1021/es0522736,
2006.
Real, E. and Sartelet, K.: Modeling of photolysis rates over Europe: impact on chemical gaseous species and aerosols, Atmos. Chem. Phys., 11, 1711–1727, https://doi.org/10.5194/acp-11-1711-2011, 2011.
Schwander, S., Okello, C. D., Freers, J., Chow, J. C., Watson, J. G., Corry,
M., and Meng, Q.: Ambient particulate matter air pollution in Mpererwe
District, Kampala, Uganda: a pilot study, J. Environ. Public Health, 2014,
763934, https://doi.org/10.1155/2014/763934, 2014.
Seinfeld, J. H. and Pandis, S. N.: Atmospheric chemistry and physics: from air
pollution to climate change, edited by: Sons, J. W., ISBN 978-1-118-94740-1, 2016.
Singh, A., Avis, W. R., and Pope, F. D.: Visibility as a proxy for air
quality in East Africa, Environ. Res. Lett., 15, 084002, https://doi.org/10.1088/1748-9326/ab8b12, 2020.
Singh, A., Ng'ang'a, D., Gatari, M., Kidane, A. W., Alemu, Z., Derrick, N.,
Webster, M. J., Bartington, S., Thomas, N., Avis, W. R., and Pope, F.: Air
quality assessment in three East African cities using calibrated low-cost
sensors with a focus on road-based hotspots, Environ. Res.
Commun., 3, 075007, https://doi.org/10.1088/2515-7620/ac0e0a, 2021.
Skamarock, W., Klemp, J., Dudhia, J., Gill, D., Barker, D., Duda, M., Huang, X., Wang, W., and Powers, J.: A description of the advanced research WRF version 3, NCAR, https://www2.mmm.ucar.edu/wrf/users/download/get_sources.html (last access: 14 September 2021), 2008.
Teklay, A., Dile, Y. T., Asfaw, D. H., Bayabil, H. K., and Sisay, K.:
Impacts of land surface model and land use data on WRF model simulations of
rainfall and temperature over Lake Tana Basin, Ethiopia, Heliyon, 5, e02469, https://doi.org/10.1016/j.heliyon.2019.e02469, 2019.
Telford, P. J., Abraham, N. L., Archibald, A. T., Braesicke, P., Dalvi, M., Morgenstern, O., O'Connor, F. M., Richards, N. A. D., and Pyle, J. A.: Implementation of the Fast-JX Photolysis scheme (v6.4) into the UKCA component of the MetUM chemistry-climate model (v7.3), Geosci. Model Dev., 6, 161–177, https://doi.org/10.5194/gmd-6-161-2013, 2013.
Tewari, M., Chen, F., Wang, W., Dudhia, J., LeMone, M. A., Mitchell, K., Ek, M.,
Gayno, G., Wegiel, J., and Cuenca, R. H.: Implementation and verification of
the unified NOAH land surface model in the WRF model. InProceedings of the
20th Conference on Weather Analysis and Forecasting, 16th Conference on
Numerical Weather Prediction, Seattle, 14.2A, https://ams.confex.com/ams/84Annual/techprogram/paper_69061.htm, last access: 10 January 2004.
Thompson, A. M., Witte, J. C., Hudson, R. D., Guo, H., Herman, J. R., and Fujiwara,
M.: Tropical tropospheric ozone and biomass burning, Science, 291, 2128–2132, https://doi.org/10.1126/science.291.5511.2128, 2001.
Trewhela, B., Huneeus, N., Munizaga, M., Mazzeo, A., Menut, L., Mailler, S.,
Valari, M., and Ordoñez, C.: Analysis of exposure to fine particulate
matter using passive data from public transport, Atmos. Environ.,
215, 116878, https://doi.org/10.1016/j.atmosenv.2019.116878, 2019.
UN-Habitat: New Urban Agenda: http://habitat3.org/wp-content/uploads/NUA-English.pdf (last access: 11 June 2022), 2017.
UNEP: City of Nairobi Environment Outlook, https://wedocs.unep.org/handle/20.500.11822/8738 (last access: 27 April 2022), 2009.
UNEP: World Population Prospects, https://population.un.org/wpp/ (last access: 23 June 2021), 2019.
Valari, M. and Menut, L.: Transferring the heterogeneity of surface
emissions to variability in pollutant concentrations over urban areas
through a chemistry-transport model, Atmos. Environ., 44, 3229–3238, https://doi.org/10.1016/j.atmosenv.2010.06.001, 2010.
Van Leer, B.: Towards the ultimate conservative difference scheme. V. A
second-order sequel to Godunov's method, J. Computat. Phys.,
32, 101–136, https://doi.org/10.1016/0021-9991(79)90145-1, 1979.
van Loon, M., Vautard, R., Schaap, M., Bergström, R., Bessagnet, B.,
Brandt, J., Builtjes, P. J. H., Christensen, J. H., Cuvelier, C., Graff, A.,
Jonson, J. E., Krol, M., Langner, J., Roberts, P., Rouil, L., Stern, R.,
Tarrasón, L., Thunis, P., Vignati, E., White, L., and Wind, P.:
Evaluation of long-term ozone simulations from seven regional air quality
models and their ensemble, Atmos. Environ., 41, 2083–2097, https://doi.org/10.1016/j.atmosenv.2006.10.073, 2007.
van Vliet, E. D. S., and Kinney, P. L.: Impacts of roadway emissions on urban particulate
matter concentrations in sub-Saharan Africa: new evidence from Nairobi,
Kenya, Environ. Sci. Lett., 2, 045028,
https://doi.org/10.1088/1748-9326/2/4/045028, 2007.
Vautard, R., Builtjes, P. H. J., Thunis, P., Cuvelier, C., Bedogni, M.,
Bessagnet, B., Honoré, C., Moussiopoulos, N., Pirovano, G., and Schaap,
M.: Evaluation and intercomparison of Ozone and PM10 simulations by several
chemistry transport models over four European cities within the CityDelta
project, Atmos. Environ., 41, 173–188, https://doi.org/10.1016/j.atmosenv.2006.07.039, 2007.
Voulgarakis, A., Savage, N. H., Wild, O., Carver, G. D., Clemitshaw, K. C., and Pyle, J. A.: Upgrading photolysis in the p-TOMCAT CTM: model evaluation and assessment of the role of clouds, Geosci. Model Dev., 2, 59–72, https://doi.org/10.5194/gmd-2-59-2009, 2009.
WHO: WHO Air quality guidelines for particulate matter, ozone, nitrogen
dioxide and sulfur dioxide, Technical Document, Document Number WHO/SDE/PHE/OEH/06.02, https://apps.who.int/iris/handle/10665/69477 (last access: 18 December 2020), 2005.
WHO: Burden of disease from ambient air pollution for 2012: https://era.org.mt/wp-content/uploads/2019/05/Burden-of-disease-from-Ambient-Air-Pollution-for-2012.pdf (last access: 21 April 2022), 2012.
WHO: Ambient Air Pollution: A global assessment of exposure and burden of
disease, https://www.who.int/publications/i/item/9789241511353 (last access: 30 May 2022), 2016.
Wild, O., Zhu, X., and Prather, J.: Fast-J: Accurate simulation of the in-
and below cloud photolysis in tropospheric chemical models, J. Atmos. Chem,
37, 245–282, https://doi.org/10.1023/A:1006415919030, 2000.
World Bank Open Data: World Bank open global development data, https://data.worldbank.org/, last access: 11 June 2022.
Wu, W.-S., Purser, R. J., and Parrish, D. F.: Three-dimensional variational
analysis with spatially inhomogeneous covariances, Mon. Weather Rev., 130,
2905–2916, https://doi.org/10.1175/1520-0493(2002)130<2905:TDVAWS>2.0.CO;2, 2002.
Zhang, L., Gong, S., Padro, J., and Barrie, L.: A size-segregated particle
dry deposition scheme for an atmospheric aerosol module, Atmos.
Environ., 35, 549–560,
https://doi.org/10.1016/S1352-2310(00)00326-5, 2001.
Zyryanov, D., Foret, G., Eremenko, M., Beekmann, M., Cammas, J.-P., D'Isidoro, M., Elbern, H., Flemming, J., Friese, E., Kioutsioutkis, I., Maurizi, A., Melas, D., Meleux, F., Menut, L., Moinat, P., Peuch, V.-H., Poupkou, A., Razinger, M., Schultz, M., Stein, O., Suttie, A. M., Valdebenito, A., Zerefos, C., Dufour, G., Bergametti, G., and Flaud, J.-M.: 3-D evaluation of tropospheric ozone simulations by an ensemble of regional Chemistry Transport Model, Atmos. Chem. Phys., 12, 3219–3240, https://doi.org/10.5194/acp-12-3219-2012, 2012.
Short summary
A modelling system for meteorology and chemistry transport processes, WRF–CHIMERE, has been tested and validated for three East African conurbations using the most up-to-date anthropogenic emissions available. Results show that the model is able to reproduce hourly and daily temporal variabilities in aerosol concentrations that are close to observations in both urban and rural environments, encouraging the adoption of numerical modelling as a tool for air quality management in East Africa.
A modelling system for meteorology and chemistry transport processes, WRF–CHIMERE, has been...
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