Polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs) are persistent organic pollutants that affect human health. This study aimed to quantify the concentrations of 17 PCDDs/PCDFs congeners in ambient air in the urban environment of Kuala Lumpur and their potential risk to humans. PM_2.5 and TSP were collected on quartz microfibre using separate high-volume samplers, whereas the gaseous phase and passive samples were captured on polyurethane between December 2021 and October 2022. The results show the Ʃ17PCDD/PCDF concentration in ambient air is 736 ± 375 fg WHO-TEQ m^-3, whereas PM_2.5, TSP, and gaseous phase concentrations are 223 ± 161 fg WHO-TEQ m^-3, 337 ± 213 fg WHO-TEQ m^-3 and 507 ± 273 fg WHO-TEQ m^-3, respectively. The hepta- and octa-group congeners dominated up to 80% of the Ʃ17PCDDs/PCDFs and are more likely to bind with the particle phase than the gaseous phase. The Ʃ17PCDDs/PCDFs displayed a significant difference between gaseous and particle concentrations (p <0.001). Exposure to the gaseous phase of Ʃ17PCDDs/PCDFs resulted in a greater inhalation lifetime cancer risk (1.58E06-5.28E-06). This study found that the toxic equivalent (TEQ) concentrations are dominant in the gaseous phase, while cancer risks from exposure to PCDDs/PCDFs in the air are tolerable in children and adults.

How to cite: Latif, M. T., Zain, S. M. S., Mohd Hanif, N., Khan, M. F., and Myilravanan, J.: Concentrations of polychlorinated dibenzo-p-dioxins and dibenzofurans in Kuala Lumpur urban environment and their potential risk to human health, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20552, https://doi.org/10.5194/egusphere-egu24-20552, 2024.

Earth system models (ESMs) participating in the latest Coupled Model Intercomparison Project Phase 6 (CMIP6) simulate various components of fine particulate matter (PM_2.5) as major climate forcers. Yet the model performance for PM_2.5 components remains little evaluated due in part to lack of observational data. Here, we evaluate near-surface concentrations of PM_2.5 and its five main components over China as simulated by fourteen CMIP6 models, including organic carbon (OC, available in 14 models), black carbon (BC, 14 models), sulfate (14 models), nitrate (4 models), and ammonium (5 models). For this purpose, we collect observational data between 2000 and 2014 from a satellite-based dataset for total PM_2.5 and from 2469 measurement records in the literature for PM_2.5 components. Seven models output total PM_2.5 concentrations, and they all underestimate the observed total PM_2.5 over eastern China, with GFDL-ESM4 (–1.5%) and MPI-ESM-1-2-HAM (–1.1%) exhibiting the smallest biases averaged over the whole country. The other seven models, for which we recalculate total PM_2.5 from the available components output, underestimate the total PM_2.5 concentrations, partly because of the missing model representations of nitrate and ammonium. Concentrations of the five individual components are underestimated in almost all models, except that sulfate is overestimated in MPI-ESM-1-2-HAM by 12.6% and in MRI-ESM2-0 by 24.5%. The underestimation is the largest for OC (by –71.2% to –37.8% across the 14 models) and the smallest for BC (–47.9% to –12.1%). The multi-model mean (MMM) reproduces fairly well the observed spatial pattern for OC (R = 0.51), sulfate (R = 0.57), nitrate (R = 0.70) and ammonium (R = 0.75), yet the agreement is poorer for BC (R = 0.39). The varying performances of ESMs on total PM_2.5 and its components have important implications for the modeled magnitude and spatial pattern of aerosol radiative forcing.

How to cite: Ren, F., Lin, J., Adeniran, J. A., Wang, J., Martin, R. V., van Donkelaar, A., Hammer, M. S., Horowitz, L. W., Turnock, S. T., Oshima, N., Zhang, J., Bauer, S., Tsigaridis, K., Seland, Ø., Nabat, P., Neubauer, D., Strand, G., van Noije, T., Le Sager, P., and Takemura, T. and the ACM Group: Evaluation of CMIP6 model simulations of PM2.5 and its components over China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3748, https://doi.org/10.5194/egusphere-egu24-3748, 2024.

We explore the wide spread in projections of African mid-century anthropogenic air pollution levels, and associated health impacts, resulting from the large diversity in available future emission pathways for the region.

While emissions of aerosols and their precursors have declined in some regions, first in North America and Europe, more recently in China, many low- and middle-income countries, including much of Africa, are increasing their emissions and are projected to continue to do so with future industrialization, although the evolution depends in socioeconomic and technological factors. This is likely to drive changes in climate hazards as well as deterioration of air quality, increasing risks for under-resourced, vulnerable populations. The impacts of African aerosols on regional temperature, hydroclimate, and extreme events are, however, less well studied and quantified than for other historical emission hotspots. Moreover, very limited data availability and distinct regional characteristics of sources result in high uncertainties in estimates of African emissions. This uncertainty translates into future projections, which exhibit a striking spread in magnitudes and trends. For instance, available estimates for emissions of sulfur dioxide and black carbon in 2050 differ by up to 70% and 90% between the Shared Socioeconomic Pathways (SSPs) and scenarios developed for the UN Environmental Programme’s (UNEP) Integrated Assessment of Air Pollution and Climate Change in Africa.

Here we explore implications of this spread for downstream modeled quantities of relevance for climate and health impact assessments. We use emissions from 10 different pathways as input to the chemical transport model OsloCTM3 and simulate the distribution of anthropogenic aerosols across the African continent in 2050. The associated impact on premature mortality is calculated. Preliminary results show surface PM2.5 concentrations differing by up to a factor 2 between the highest and lowest scenario when averaged over the African continents, with markedly higher local spread. Sub-continental differences are substantial, pointing to the need to consider Africa in more geographical detail than often done.

How to cite: Lund, M. T., Amooli, J. A., Chowdhury, S., Johansen, A. N., Samset, B. H., and Westervelt, D. M.: An uncertain future for anthropogenic aerosols in Africa, and their climate and health impacts, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15079, https://doi.org/10.5194/egusphere-egu24-15079, 2024.

The climatic implications of regional aerosol and precursor emissions reductions implemented to protect human health are poorly understood. However, quantitative estimates of climate responses to emission perturbations are needed by the climate assessment and impacts community. The Regional Aerosol Model Intercomparison Project (RAMIP) project builds on recent CMIP5 and CMIP6-era studies to help address this knowledge gap. Briefly, RAMIP will use contrasting SSP aerosol emissions (SO2, BC, OC) scenarios (SSP3-7.0 and SSP1-2.6) to isolate the impact of realistic, near term aerosol changes on climate and air quality over rapidly developing regions of South Asia, East Asia, and Africa, and over North America and Europe. At least 9 CMIP6-generation global climate models are contributing to this new MIP, which uniquely focuses on specific regional aerosol emissions changes rather than simultaneous global changes. This presentation will specifically present the first results from several participating models in RAMIP, namely the NASA Goddard Institute for Space Studies (GISS) ModelE, UKESM, CESM2, and NorESM. All Tier 1 simulations of RAMIP are included, with 10 ensembles for each simulation. Initial analysis at the time of writing confirms the anticipated changes in aerosol optical depth, downwelling shortwave radiation, and aerosol mass concentration over each of the regions. The warming response to a decrease in SO2, BC, and OC is strongest in the US and Europe perturbation simulations, both globally and regionally, with Arctic warming up to 0.3 K due to a removal of US and European anthropogenic aerosol emissions alone; however, even emissions from regions more remote to the Arctic, such as South Asian aerosols, can significantly warm the Arctic up to 0.2 K. In most regions, temperatures are most sensitive to emissions perturbations within that region. Arctic warming is the most robust model response across the regional aerosol emissions perturbations. 

How to cite: Westervelt, D., Zhang, Y., Amooli, J. A., Tsigaridis, K., Nazarenko, L., Samset, B., Wilcox, L., and Allen, R.: Enhanced aerosol-induced near-term Arctic warming due to remote regional aerosol perturbations in RAMIP, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20722, https://doi.org/10.5194/egusphere-egu24-20722, 2024.

     Regional aerosol simulation biases in climate models have been noted since the CMIP5 era. The biases can cause noticeable error in the radiative forcing estimations. In this research, we investigate the aerosol optical depth (AOD) biases over China from 2002 to 2015 in nine climate models that participate the Aerosol and Chemistry Model Intercomparison Project (AerChemMIP) of CMIP6. The AerChemMIP ensemble mean is high biased over four populated regions in winter and low biased in two populated regions compared to the MODIS satellite retrievals. The patterns of model biases were persistent over years. Large inter-model spread is found in the high AOD regions. We decompose AOD to the product of emission rate, lifetime and mass extinction coefficient such that the AOD biases can be attributed to the errors of each term and their cross error term. The error of each term is analyzed by first regressing to several observable predictors, such as precipitation, Angström exponent, and relative humidity, followed by constraining the predictors by observational or reanalysis data. The results show that error due to emission dominates for many models, followed by lifetime and MEC errors. Furthermore, we argue that for regional analysis, due to imbalance between emission and removal fluxes, the removal/emission ratio should be further constrained by observations. This study provides a diagnosis for climate models to improve their simulation in aerosol loading on regional scale by optimizing the modeling of meteorology as well as aerosol properties and life cycle. 

How to cite: Fan, T., Liu, X., Wu, C., and Gao, Y.: Observational Constrained Attribution of Regional Aerosol Simulation Biases in the AerChemMIP models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3279, https://doi.org/10.5194/egusphere-egu24-3279, 2024.

Aerosol-cloud interactions (ACI) is a key uncertainty in our ability to forecast future climate. Robust evidences of aerosol-induced modifications to the structure and lifetime of both, rain bearing and non-rain bearing clouds has emerged from satellite observations across the globe in last two decades. These observations were also substantiated by many process-level simulation studies using weather models at cloud resolving scales in last decade. Thus, the significance of ACI at process scale on short-term meteorological perturbations is well agreed. However, the role of aerosol-cloud interactions on trends at climate scale is not evident yet. For example, if cloud occurrence is increasing over India, it is not clear if there is any substantial role of ACI in comparison to other governing factors. Here, we will present our analysis on the association of ACI with the recent trends in clouds, temperature and rainfall over India using satellite observations and global climate model simulations.

First, we will discuss data analysis of simulations from CMIP5 models, to quantify the importance of ACI on extreme climate indices over Indian monsoon region. The climate models were grouped based on whether the models represent only aerosol-radiation interactions (REM_ADE) or the full suite of aerosol-radiation-cloud interactions (REM_ALL). Compared to REM_ADE, including all aerosol effects significantly improves the model skills in simulating the observed historical trends of all three climate indices over India. Specifically, AIE enhances dry days and reduces wet days in India in the historical period, consistent with the observed changes. However, by the middle and end of the 21st century, there is a relative decrease in dry days and an increase in wet days and precipitation intensity. Further, we will also illustrate unprecedented satellite evidences of aerosol induced positive trends in marine cloud occurrences and surface temperature during pre-monsoon over the Bay of Bengal (BOB) region. In last 15 years, increased aerosol emissions over North India have led to an increase in aerosol loading till 3 km over the BOB outflow region in monsoon onset period. The elevated aerosol loading stabilizes the lower troposphere over the region in recent years and leads the low-level cloud occurrences (below 3 km) to increase in recent years by ~20%. Incidentally, the sea surface over entire BOB is steadily warming under climate change except the pollution outflow region, suggesting potential contributing to the observed non-intuitive cooling trends in sea surface temperatures.

Our findings underscore the crucial role of ACI in trends and future projections of the Indian hydroclimate and emphasizes the crucial need for improved aerosol representations in coupled models for accurate predictions of regional climate change over South Asia.

How to cite: sarangi, C., Rai, P., Kant, S., Nair, A., Kuiry, S., Wilcox, E., and Leung, R.: Aerosol-cloud interactions constrain climatic trends in rainfall and temperature of India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-832, https://doi.org/10.5194/egusphere-egu24-832, 2024.

Current extremes within regional water cycles, extensive drought periods and torrential flooding, are   associated in literature and media to first indicators of greenhouse gas driven climate change. Indeed, they are among major threats to be expected from climate change model results. The main obvious physical process behind such global warming water cycle extremes, is the temperature dependent water vapor content of air (Clausius Clapeyron, 1834, CC) and it’s increase by ~ 7% per degree C. Naturally the water vapor input into the atmosphere via evapotranspiration is dependent on shortwave radiation reaching the surface, a process controlled partially by fine particles, partially by clouds. Here the ultrafine, invisible, fraction of the aerosols is becoming important.

Ultrafine particles (UFP) acting as cloud condensation nuclei (CCN) are the driving force behind cloud modification and changing rainfall patterns. However, the sources and budgets of anthropogenic primary and secondary particles were not well known. Based on airborne measurements we identified as a major contribution modern fossil fuel flue gas cleaning techniques to cause a doubling of global primary UFP number emissions. The subsequent enhancement of CCN numbers has several side effects. It’s changing the size of the cloud droplets and delays raindrop formation, suppressing certain types of rainfall and increasing the residence time of water vapor in the atmosphere. This additional latent energy reservoir is directly available for invigoration of rainfall extremes. Additionally it’s a further contribution to the column density of water vapor as a greenhouse gas and important for the infrared radiation budget. The localized but ubiquitous fossil fuel related UFP emissions and their role in the hydrological cycle, may thus contribute to regional or continental climate trends, such as increasing drought and flooding, observed within recent decades.

We discuss the impact of the ultrafine fraction on the hydrological cycle and its historical timeline. Ultrafine particles (UFP) initially don’t interact with radiation like fine ones. However, a significant increase of the ultrafine particle burden may serve similar to CC to more water vapor molecules, respectively more latent energy in the troposphere, especially in the altitude range of convective clouds. We also discuss the origin of the majority of UFP, whether a simple dependence of ultrafine particles on the atmospheric sulphur load is a reasonable and valid assumption and what should be taken additionally into account for future UFP szenarios.

Junkermann, W. & Hacker, J., 2022, Unprecedented levels of ultrafine particles, major sources, and the hydrological cycle, Nature Scientific Reports, 12:7410 https://doi.org/10.1038/s41598-022-11500-5

Junkermann, W. (2022). Ultrafine particle emissions in the Mediterranean region. In F. Dulac, S. Sauvage, & E. Hamonou (Eds.), Atmospheric chemistry in the Mediterranean region (Vol. 2, From air pollutant sources to impacts). Springer, 21 pp. https://doi.org/10.5445/IR/1000154173

How to cite: Junkermann, W. and Hacker, J.: Invisible, overlooked, climate relevant? Unprecedented levels of ultrafine particles and the hydrological cycle, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20286, https://doi.org/10.5194/egusphere-egu24-20286, 2024.

The process of new particle formation from gas-phase precursors holds significant importance in Earth's atmosphere and introduces a notable source of uncertainty in climate change predictions. The growth of freshly formed molecular clusters should in theory be crucial for the climate impact of new particle formation, influencing the survival probability of these particles exponentially and determining their ability to act as cloud condensation nuclei. However, defining the fundamental aspects of nanoparticle growth is intricate. It involves a complex interplay of condensational and reactive vapor uptake, aerosol coagulation, sink processes, and a diverse array of potential gaseous precursors. Observational nanoparticle growth rates, derived from the evolution of the particle-size distribution, portray growth as a collective phenomenon. However, models often interpret these rates at a single-particle level, integrating them into simplified size-distribution representations (Stolzenburg et al., 2023). dditionally, many models only consider a limited subset of condensable vapors, while recent experimental observations identify an increasing number of potential contributors to new particle growth.

Our objective here is to bridge the gap between experimental and modeling studies on nanoparticle growth. We compare three large-scale models (NorESM, ECHAM, and TM5) regarding their sensitivity to organic nanoparticle growth processes. Surprisingly, we find a much lower sensitivity than anticipated from box models. Through the inclusion of a sectional scheme into NorESM, we demonstrate that representing the complexity of size distribution dynamics leads to significantly different cloud condensation nuclei (CCN) levels. Furthermore, our results suggest that, on regional scales, sensitivity to organic growth is much higher. Inclusion of additional growth processes and/or a scaling of condensable vapor concentrations could yield a significantly altered climate response. In turn, comprehensive experimental observations from e.g. the open oceans are still lacking and we show that continental data exhibit surprisingly little variation in measured particle growth rates. The latter indicates limited sensitivity in current experimental approaches and potential unaccounted multi-phase chemistry in the growth process.

Consequently, we propose specific guidance for future research to address questions regarding the buffered climate response in large-scale models and the unexpectedly low variation observed in global growth measurements. We advocate for more sensitivity studies and improved model-measurement comparisons.

References:

Stolzenburg, D., Cai, R., Blichner, S. M., Kontkanen, J., Zhou, P., Makkonen, R., Kerminen, V.-M., Kulmala, M., and Kangasluoma, J.: Atmospheric nanoparticle growth, Rev. Mod. Phys., 95, 045002, https://doi.org/10.1103/RevModPhys.95.045002, 2023.

How to cite: Stolzenburg, D., Cai, R., Blichner, S., Kontkanen, J., Zhou, P., Makkonen, R., Kerminen, V.-M., Kulmala, M., Riipinen, I., and Kangasluoma, J.: Aligning experimental and model perspectives on atmospheric nanoparticle growth, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7692, https://doi.org/10.5194/egusphere-egu24-7692, 2024.

South Africa, with its industrialised economy, faces unique air pollution challenges. Our study investigates aerosol composition and absorption in the Highveld region. Understanding aerosol absorption is critical as it affects climate, air quality, and public health. Aerosol absorption in the lower atmosphere affects the evolution of the boundary layer and the dispersion of pollutants, which in turn affects air quality and public health. Aerosol filter samples (PM₁₀ fractions) were collected from residential, traffic, and industrial sites during the dry season. Chemical analyses, including X-ray fluorescence, thermo-optical analysis, and ion chromatography, were carried out to determine elemental species, carbonaceous species, and water-soluble ions, respectively. Based on this, a mass closure calculation was performed to define the contribution of five major aerosol components. The calculated aerosol mass concentrations were in good agreement with the measurements (Normalised Mean Bias, NMB < 7%). No significant variation in PM₁₀ concentration was observed between site types. Mineral dust appeared to be the main contributor to PM₁₀, varying from about 48%-60% at different sites, followed by organic matter (OM, 22%-35%), secondary inorganic aerosols (SIA, 9%-12%), elemental carbon (EC, 4%-7%), and sea salt (ss, 1%-2%).

Aerosol spectral absorption was obtained from multi-wavelength absorbance analysis (MWAA) measurements at 375, 407, 532, 635, and 850 nm. High absorption was measured in the following order: industrial> residential> traffic sites. The estimated absorption Ångström exponent (AAE) varied from 0.8 to 2 at different sites, indicating the contribution of several sources. At 850 nm absorption correlates well with EC as expected (r = 0.85). The obtained mass absorption efficiency (8 m²/g) is in line with expectations. Specific tracers were used to determine the contribution of the main absorbing aerosol components - black carbon (BC), brown organic carbon (BrC) from incomplete biomass combustion, and mineral dust - using correlations between estimated mass and measured absorption. Preliminary results indicate that although BC is the major contributor to absorption, accounting for 30%-60% absorption at 375 nm, followed by BrC 10%-50%, the contribution of the less absorbing but more abundant mineral dust is not negligible and can range from 2% to 50% in different samples. These results underline the complexity of aerosols in the region and their high absorption properties, and the need for a comprehensive understanding of its various components to accurately assess its impact.

How to cite: Baldo, C., Language, B., Isolabella, T., Vernocchi, V., Massabò, D., Di Biagio, C., Van Zyl, P., Piketh, S., and Formenti, P.: Apportionment of absorption in complex aerosols in South Africa, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16012, https://doi.org/10.5194/egusphere-egu24-16012, 2024.

This effort is dedicated to construction of a relational database and an interactive web system that organizes and communicates aerosol optical and microphysical characteristics assembled in the Table of Aerosol Optics (TAO) community repository. The TAO project (https://science.larc.nasa.gov/mira-wg/topics/tao/) is an extension of historical efforts (e.g., Shettle and Fenn, 1979; d’Almeida et al., 1991; Koepke et al., 1997; Hess et al., 1998) on providing libraries of aerosol characteristics for applications in global chemical transport modeling and remote sensing. Aerosol characteristics such as size distribution, complex refractive index, shape, mixing state, extinction, absorption, single-scatter albedo, lidar ratio, etc. are provided for different aerosol types, wavelengths, be originated from laboratory measurements, in situ or remote sensing observations. Combination of aerosol characteristics, their origins, types, spectral domains, computational techniques used for single-scatter properties become quickly very complex and is expected to evolve in future. The open access and interactive principles of TAO implies increasing complexity of its database structure that requires involvement of dedicated computer science technics for its organization and management. The relational database conception, for instance, is widely used in many domains that require such data organization and naturally appropriates to TAO. The relational database consists in structuring the data in multiple tables, with so-called primary or foreign keys that relates between entity types, parameters and their value in unique or multiple connections. We therefore started development of tools for uploading of the TAO data into the format of relational database and creation of a web interface for an interactive communication with the community. This work is expected to be presented as complimentary to a more general presentation about the TAO project by G. L. Schuster and gather valuable feedbacks from modelers, in situ and remote sensing experts on the data needs, convenient exchange formats and potential applications.

How to cite: Derimian, Y., Ducos, F., Lesueur, P., and Schuster, G. L.: Relational database construction for Table of Aerosol Optics, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20865, https://doi.org/10.5194/egusphere-egu24-20865, 2024.