The pollutant nitrogen dioxide (NO2), a tracer for fossil fuel combustion from transportation and industry and commonplace in urban areas, is associated with a growing number of adverse health outcomes. Many of its sources as well as NO2 concentrations themselves are often highest within marginalized and minoritized communities in the United States (U.S.) and throughout the world. The short lifetime and spectral properties of NO2 allow for high-fidelity, space-based measurements, and the increasingly high spatial resolution and complete geographic coverage of satellite-derived NO2 provided by current instruments, such as the TROPOsphere Monitoring Instrument (TROPOMI), attest to recent advances in our ability to surveil NO2 from space.
Here, we highlight how remotely-sensed observations of NO2 or estimates of NO2 that incorporate satellite data can reveal the extent, sources, and impacts of these disparities. To these points, we show how communities of color in the U.S. face significantly higher levels of NO2 by a factor of ~2.1 than majority white, non-Hispanic communities and trace back this disproportionate exposure to particular NO2 sources such as light- and heavy-duty transportation and the rapidly-growing e-commerce and warehousing industry. These inequitable exposures are associated with a large burden of disease—including an estimated 115,000 new cases of pediatric asthma annually in the U.S.—disproportionately borne by marginalized communities. Despite the concerted efforts of policymakers to reduce these health disparities, we find that the magnitude of disparities has grown in recent years.
We discuss how new geostationary instruments with complete daytime coverage, such as Tropospheric Emissions: Monitoring of Pollution (TEMPO), may reveal different disparities in NO2 exposure compared with polar-orbiting instruments such as TROPOMI that provide only a single early afternoon snapshot of NO2 levels. We also broaden our exploration of urban air quality, health, and equity to the global scale and discuss how global marginalized communities may face similar, disproportionate exposure to this pollutant as they do within the U.S. Overall, these satellite-enabled insights can spur and inform policies that would not only reduce urban pollution but could have outsized benefits for overburdened communities, and we discuss how actions such as adopting more stringent air quality or engine standards can reduce NO2 emissions and targeted cleanup of emission sources within these overburdened communities could reduce these long-standing disparities.
How to cite: Kerr, G. H., Anenberg, S. C., Chen, L., Goldberg, D. L., Huber, D. E., Meyer, M., and Miller, J.: Clean air for some: How satellite-measured NO2 reveals sources and impacts of and equitable solutions to long-standing disparities, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7478, https://doi.org/10.5194/egusphere-egu25-7478, 2025.
Air pollution is one the great challenges facing urban environments today, with 99% of the global population living in areas where air pollution concentrations are deemed “unsafe” according to the WHO air quality guidelines. Air pollution is also a typically wicked problem. We know there are inequities in exposure to air pollution and the resources available to address it; a heterogeneous nature to the sources and dispersion of pollution; and an array of solutions available to stakeholders. There are synergies between air quality solutions and actions for climate, health, equity and social wellbeing, yet siloed thinking in decision-making is limiting the outcomes of air pollution action. Systems approaches offer opportunities to overcome siloed thinking.
In collaboration with the World Economic Forum, we used structured decision-making as a novel engagement tool to gain systems insights into the synergies, barriers and opportunities facing stakeholders. We invited a diverse array of stakeholders from across urban systems to collaborate in a problem solving workshop, in which we adapted the structured decision making process for systems insights into urban air quality actions. The aim of the workshop was to understand the synergies and conflicts between stakeholders, and to identify the actions that stakeholders believe are feasible and provide co-benefits for climate, health and social wellbeing.
With 24 participants from 15 countries, we gathered the insights from NGOs, Academia, Industry and Policy from sectors such as transport, health, environment and technology. The group agreed on common goals that drive their work: “human health and well-being”, "equity" and "planetary health and climate". In response to these, they identified over 100 solutions and highlighted the importance of transport and data related solutions, including air quality monitoring , modelling and transparency. The perceived feasibility of transport solutions was varied, however despite this “public transport” and “climate and health promoting transport” were recommended as some of the top co-created actions by stakeholders. Key barriers to action included lack of data (access, quality and awareness), challenges of siloed thinking and collaboration and misinformation and disinformation. There was a call from stakeholders for enhanced cross collaboration and systems approaches, but a lack of suggestions of how to practically implement this.
The process of identifying and agreeing on common goals and co-creating corresponding solutions can help break siloes of decision making and help promote optimal systems-based solutions. There is a clear need for further understanding into how we integrate systems thinking into real world decision making, especially in low and middle income regions where the application of systems thinking is currently understudied.
How to cite: Cowell, N., Kirk, A., Weller, R., and de Nazelle, A.: Breaking siloes of decision making for effective and systematic air quality solutions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1218, https://doi.org/10.5194/egusphere-egu25-1218, 2025.
In the United States, PM2.5 and NOx pollution disproportionately burden communities of color and of lower income. However, such information is lacking when it comes to hazardous air pollutants (HAPs) like toxic volatile organic compounds, for which city-wide measurements are more challenging and thus are not available in routine observations.
In this study, we use the highest spatially resolved (~2 km) airborne measurements of emissions and concentrations ever reported of HAPs while covering a whole megacity, and combine these observations with US Census information. We observe higher concentrations and emissions of 17 measured HAPs – such as benzene, naphthalene, and p-chlorobenzotrifluoride (PCBTF) – in California-designated Disadvantaged Communities and census tracts with low-income Hispanics and Asians. While concentrations were on average 32 ± 5% higher for low-income Hispanics compared to high-income non-Hispanic whites, emissions were even 107 ± 21% higher - indicating the proximity of low-income Hispanics to localized emission sources. Low-income Hispanics and Asians share an unequal burden from traffic-related emissions, with benzene, nitrogen oxides (NOx ), and carbon monoxide (CO) concentrations up to 60% higher. However, in Disadvantaged Communities and census tracts with large Hispanic populations (>50%), we observe toluene-to-benzene emission ratios above 3, pointing to inequalities in other HAPs primarily caused by non-traffic emission sources such as industry and solvents. In these communities, regulatory inventories also significantly underestimate the observed emissions. We find that efforts to address HAP inequalities and environmental justice concerns in Los Angeles will need to consider contributions from volatile chemical products, which represent a growing source of emissions driving inequalities in impacted communities.
How to cite: Pfannerstill, E. Y., Ofodile, J., Pusede, S. E., Ivey, C. E., Arata, C., and Goldstein, A. H.: Inequality in hazardous volatile organic compound (VOC) emissions and concentrations measured over Los Angeles, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11546, https://doi.org/10.5194/egusphere-egu25-11546, 2025.
Long-term exposure to air pollution is a major global public health threat. However, the health burden due to air pollution exposure is unequal. In cities, ethnic minorities experience the most severe exposures and adverse health outcomes to air pollution, particularly from traffic. Exposure to traffic-related air pollution is associated with childhood-onset asthma and adult premature mortality. Contemporary data of the location and size of the disparities to determine and address inequities in exposure and health burdens is not readily available for all cities. Here we address this dataset by deriving surface concentrations of nitrogen dioxide (NO2) as proxy for traffic-related air pollution for London at fine spatial scales (~400 m). This is achieved by oversampling 5 years of TROPOspheric Monitoring Instrument (TROPOMI) tropospheric NO2 column data from its nadir resolution of ~5.6 km x 3.5 km. We then subtract off a uniform free-tropospheric NO2 column of 50 pptv determined from cloud-sliced vertically resolved TROPOMI data to isolate the boundary layer. These boundary layer columns are then converted to surface concentrations using an exponential relationship between the TROPOMI boundary layer column and midday mean in-situ network measurements. Midday concentrations are converted to 24-hour concentrations using a midday-to-24h ratio of 1.30, which is calculated from surface network sites in the Greater London Area (GLA). The TROPOMI-derived 24-hour mean surface NO2 concentrations reproduce the NO2 observed by the surface network. We use 2021 census data at the finest resolution for three out of five high-level ethnic groups defined by the UK census: Asian, Black and White. To calculate the health burden, we use borough level baseline mortality rates, the finest scale available, which range between 44 and 2818 per 100,000, and an exposure response coefficient of 1.023 per 10 µg m-3 annual mean NO2 as recommended by the UK’s Committee on the Medical Effects of Air Pollutants (COMEAP). We find premature mortality rates due to traffic-related pollution exposure for each ethnic group exhibit similar spatial variation across the city, with highest mortality in central and central northwest London. The average GLA premature mortality rate is worst for the Black population (59 per 100,000), then the Asian population (57 per 100,000) and least severe for the White population (56 per 100,000), reflecting the ethnic injustices in air pollution exposure. Work is underway to identify specific census-tract areas with the most severe disparities that require immediate regulatory actions and to quantify the disparities in childhood asthma instances across the city. We aim to expand this investigation to four other major UK cities with the greatest traffic-related pollution emissions, according to the UK National Atmospheric Emission Inventory (NAEI). These are Birmingham, Leeds, Manchester and Glasgow.
How to cite: Gershenson-Smith, E., Marais, E. A., Vohra, K., and Horner, R. P.: Using high-resolution TROPOMI NO2 columns to assess health disparities in NO2 exposure across London, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10552, https://doi.org/10.5194/egusphere-egu25-10552, 2025.
The estimation of human exposure to air pollution presents well-known methodological challenges. Two major challenges are incorporating population activity and accounting for outdoor pollutant concentrations infiltrating indoor environments. These aspects are often overlooked in current exposure assessments at urban and regional scales, introducing biases that result in non-representative exposure estimates and associated health effects.
In this study, we present a method for regional dynamic exposure estimation by integrating population activity and the infiltration of air pollutants into indoor environments. Using the time-microenvironment-activity concept in combination with open-source datasets for the spatial and temporal distribution of the European population, our framework generates grids of population activity across different microenvironments (home, work, schools, transport, etc.) with a spatial resolution of 1x1 km2 and a temporal resolution of 1 hour for all of Europe. Each microenvironment is assigned seasonal, literature-based outdoor-to-indoor infiltration factors. The resulting dynamic population grids can be created for any urban or regional to domain in Europe and can be applied to air pollutant concentrations derived from any air quality model that match these domains.
To illustrate the impact of regional dynamic exposure estimates compared to static estimates (based on residential addresses), we combined the dynamic population activity data with a high-resolution (1x1 km2) gridded dataset of PM2.5 concentrations across Greece from 2015 to 2022. This dataset was produced using a recently developed and extensively evaluated Random Forest modeling approach to downscale regional to urban pollutant concentrations specifically for Greece. Initial results reveal that regional-scale dynamic estimates incorporating population activity resulted in >10% higher mean exposure to PM2.5 compared to exposure estimates based on static populations but can vary significantly between different microenvironments. These findings suggest that current population exposure estimates to ambient air pollution across Europe are likely to be underestimated.
How to cite: Ramacher, M. O. P., Kakouri, A., Athanasopoulou, E., and Matthias, V.: Advancing Regional Air Pollution Exposure Assessment: Revealing Underestimated Long-Term Exposure to PM2.5 in Greece, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7968, https://doi.org/10.5194/egusphere-egu25-7968, 2025.
Household and ambient air pollution (HAAP) pose a major global health risk, contributing to over six million premature deaths annually and significantly diminishing quality of life. We examine macro-level socio-economic, environmental, energy, and health determinants of HAAP mortality rates across 150 countries. While prior research often focuses on micro-level factors or single-country analyses, our study provides one of the first comprehensive global assessments, incorporating a wide array of indicators. Our findings highlight critical pathways to reducing HAAP-related deaths. Increased rural access to clean cooking fuels and higher healthcare expenditure emerge as pivotal solutions, while rurality amplifies mortality risks. Advanced economies exhibit greater resilience to HAAP mortality, whereas emerging and developing economies remain highly vulnerable, with notable disparities among them. Contrary to conventional assumptions, males face higher HAAP mortality risks than females, a pattern supported by descriptive statistics and global GIS mapping of predicted probabilities from regression models. Our results are robust across alternative models and consistent over time. To contextualise these findings, we integrate evidence from prior country-specific case studies, bridging local insights with global trends. This research advances understanding of progress toward UN Sustainable Development Goals (SDGs 3, 5, and 7) and provides useful insights for policymakers to mitigate HAAP mortality risks and improve living conditions globally.
How to cite: Mahadeo, S. M. R. and Seenath, A.: Household and ambient air pollution mortality risk: global insights from macro-level indicators, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5146, https://doi.org/10.5194/egusphere-egu25-5146, 2025.
China has launched the national emissions trading system (ETS) and intends to form a novel mechanism to control provincial carbon emissions. While previous studies have separately analyzed the impacts of ETS and provincial reduction targets on welfare and air quality, how the potential integration of these approaches would impact welfare and air quality-related health remains underexplored. In this study, we employ an integrated modeling framework to compare the economic impacts and health outcomes associated with PM2.5 and ozone under three provincial control mechanisms, all targeting the same national total carbon emissions in 2035. Our findings indicate that ETS improves national welfare by at least 0.12% compared to the conventional provincial control mechanism (PRO_CAP). The partitioned carbon regulation mechanism (PART_REG), which applies national ETS to power and energy-intensive industry sectors while assigning reduction targets to other sectors at the provincial level, achieves 85% of the welfare improvement observed under an ideal mechanism with comprehensive ETS coverage (FULL_ETS). Compared to PRO_CAP, ETS redistributes CO2 and co-emitted air pollutant emissions from northern to southern China, improving air quality in northern provinces but worsening it in central and southern provinces. National premature deaths increase by 32,700 (95% CI: 23,200—41,600) and 44,800 (95% CI: 31,400—57,600) under the PART_REG and FULL_ETS scenario, respectively, compared to the RPO_CAP scenario. When comparing the changes in welfare and monetized health impact, ETS remains cost-effective nationally compared to RPO_CAP, with a median net benefit estimate of US$6.6 billion under the PART_REG—20% larger than that under the FULL_ETS. The northern and southeastern coastal provinces experience net positive benefits, while some central provinces face net negative benefits.
How to cite: Li, M., Peng, H., Zhang, D., Wan, F., and Zhang, X.: Provincial economic and air quality-related health impacts of China’s potential partitioned carbon regulation, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18004, https://doi.org/10.5194/egusphere-egu25-18004, 2025.
Methane is a potent greenhouse gas which has substantially contributed to climate change since the pre-industrial era, second only in importance to carbon dioxide. Due to its short atmospheric lifetime and high global warming potential, methane emissions have disproportionately large impacts on near-term climate change. Beyond its direct role as a greenhouse gas, methane also has other important implications for climate, human health, air quality and vegetation, largely due to its impact on tropospheric ozone. Thus, reducing methane emissions has been identified as a key policy lever for delaying the worst impacts of near-term climate change with expected co-benefits for health and air quality. The most notable of these efforts is the Global Methane Pledge which aims to achieve a 30% reduction in global anthropogenic methane emissions by 2030 as compared to 2020. And yet, in many respects, methane mitigation has been overlooked relative to other climate mitigation strategies. Existing modelling evidence for the estimating the potential climate benefits of methane mitigation rely extensively on idealised climate emulators or comprehensive modelling studies based on a limited number of models and ensemble members. Both approaches have important limitations. Hence, there is a pressing need for a co-ordinated intermodel comparison project which uses state-of-the-art ESMs in which all modelling groups prescribe identical reductions in methane concentrations or emissions, all modelling groups use the same baseline scenario, and sufficient ensemble members are simulated to investigate the broader climate and health impacts of methane mitigation. MethaneMIP has been envisioned to undertake these tasks.
In this talk I will introduce the MethaneMIP protocol and the two new methane reduction scenarios ‘Technical Measures’ and ‘Ambitious’, which are both branched from SSP2-4.5 and cover the period 2020-2050. The overarching aim of MethaneMIP is to provide a policy-relevant state-of-the-art estimate of the climate and health impacts of methane mitigation, and a robust quantification of the uncertainties, as well as furthering our understanding of methane’s role in the climate system. Over ten modelling centres from across the world are participating in MethaneMIP, with simulations for the core MethaneMIP experiments currently underway. For the first time, I will present the preliminary results of MethaneMIP as pertaining to the research questions it was set up to address, including: What are the best estimates of the expected climate and health benefits of plausible methane mitigation by mid-century? Which near-term climate events projected to occur may be delayed or avoided by curbing methane emissions? What are potential impacts of successful implementation of the Global Methane Pledge? When should we expect the climate or health signal from reduced methane to be detectable in the presence of internal variability? I will finish by discussing the implications of MethaneMIP for climate policy, as well as introducing the flagship emissions-driven MethaneMIP simulations which will be performed later this year.
How to cite: England, M., Shindell, D., O'Connor, F., Smith, C., Xu, Y., Chuan, F., Gaubert, B., Law, R., Ziehn, T., Jöckel, P., Winterstein, F., Kleinen, T., Naik, V., Cussac, M., Graff, L. S., Olivié, D., and Sigmond, M.: An introduction to MethaneMIP: investigating the climate and health benefits of methane mitigation using Earth System Models, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4867, https://doi.org/10.5194/egusphere-egu25-4867, 2025.
As urban temperatures rise and the demand for urban densification increases, climate adaptation has become a significant concern for policymakers. However, we face a challenge in today's data-rich environment: How can we effectively manage the vast amounts of information available to make informed decisions for our cities and communities? Accordingly, urban agglomerations in Germany are struggling in allocating measures.
In collaboration with the federal state of Hesse, we have developed a data-driven decision-making method to address two critical questions: Which locations should we focus on for heat mitigation and the protection of cool oases? And which climate adaptation measures are most suitable for each location?
Our method consists of four steps:
- Identification of Hot Spots and Cold Spots: We identify universal hot and cold spots that consistently experience high or low temperatures during both day and night. This assessment is based on various temperature metrics that capture heat stress and imbalances in surface heat fluxes, which we harmonize using a 100 m grid. We validate our findings using local climate zones and CORINE land cover data.
- Prioritization of Locations: We prioritize hot and cold spots using a merit- and penalty-based system. Rather than focusing solely on the hottest areas, we emphasize locations where heat impacts vulnerable populations or disrupts cooling patterns over broader regions.
- Assessment of Mitigation Potentials: Each grid cell is evaluated for its deficits and potentials for climate adaptation using a multitude of contextual data. This includes detailed land cover information obtained from high-resolution aerial imagery segmentation, along with green and blue indicators (such as NDVI, green volume, and water availability), and settlement structure (e.g., types of historic urban centers or single family housing).
- Suitability of Adaptation Measures: Based on the results from steps 2 and 3, we rank the suitability of various adaptation measures (e.g., green facades, increased tree coverage) for each grid cell using a second merit- and penalty-based system.
In a close loop with practitioners from local to regional authorities, this integrated approach enables us not only to identify areas in need of climate action, but also to recommend specific, actionable measures. By leveraging data at this level of detail and scale, we facilitate informed, targeted climate adaptation strategies.
How to cite: Benz, S. A., Jehling, M., Krikau, S., Wursthorn, S., and Keller, S.: From temperature observations to mitigation measures: Data-driven approaches to multi-scale climate adaptation in Hesse, Germany, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17122, https://doi.org/10.5194/egusphere-egu25-17122, 2025.
Anthropogenic emissions alter atmospheric composition and therefore the climate, with implications for air pollution- and climate-related human health. Mortality attributable to air pollution and non-optimal temperature is a major concern, which is subject to change in the future under different climate change and socioeconomic scenarios. We use model outputs from the recent Intergovernmental Panel on Climate Change multi-institution simulations to assess future changes in mortality attributable to long-term exposure to both non-optimal temperature and air pollution. We show that, under a moderate scenario (SSP2-4.5), end-of-century mortality could quadruple from present-day values to around 30 (confidence level 95%:12-53) million/year, potentially reaching 44 million/year in a more pessimistic scenario (SSP5-8.5). While pollution-related mortality is projected to increase five-fold by the end of the century in a moderate scenario, temperature-related mortality will experience a seven-fold rise, making non-optimal temperature exposure more important than air pollution as health risk factor for at least 20% of the world's population. Population aging emerges as the primary driver of increased mortality, countering efforts to improve air quality and mitigate climate change. These findings underscore the urgency not only to improve air quality but, more importantly, to simultaneously implement more effective climate change policies to prevent significant loss of lives in the future.
How to cite: Pozzer, A., Steffens, B., Proestos, Y., Sciare, J., Akritidis, D., Chowdhury, S., Burkart, K., and Bacer, S.: Atmospheric health burden across the century and the accelerating impact of temperature compared to pollution, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4224, https://doi.org/10.5194/egusphere-egu25-4224, 2025.
Climate change and air pollution are interrelated challenges with profound implications for public health, equity, and resilience in Europe. This study investigates relationships between climate, air quality, and health across European countries (2005-2020) as part of the DataNord/Healthy Planet project. Using reanalysis, remote sensing, and observed datasets (ERA5-Land, MERRA-2, Sentinel-5P, MODIS, OMI, EDGAR v6, EEA health assessments), we employed machine learning and statistical analysis to identify significant warming trends (temperature anomaly: +0.90°C), regional variability in precipitation (e.g., Cyprus: -28% to +15%) and other variables. Air quality improvements varied regionally, e.g., NO2 and PM2.5 concentrations decreased >50% in Sweden, while NO2 increased in Cyprus (+17%) and O3 in Belgium (+21%), reflecting differences in policy effectiveness and local conditions. Context-specific correlations between climate and pollution (-0.86 to 0.79) reflected local variations in meteorological and emission factors. Health assessments revealed substantial reductions in premature mortality, especially from PM2.5 (Estonia: -93%) and NO2 (Germany: -53%, Spain: -58%). Our findings emphasize the need for integrated climate-air quality policies targeting regional challenges. We recommend implementing region-specific emission reduction targets based on local vulnerability indices, supported by enhanced monitoring networks and targeted interventions in areas showing slower progress.
How to cite: Shafeeque, M., Glöckner, F. O., Hänzelmann, S., Nagrani, R., Naaouf, N., Buck, C., and Ahrens, W.: Climate, Air Quality, and Health Inequities in Europe: Evidence-Based Policy Implications, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-363, https://doi.org/10.5194/egusphere-egu25-363, 2025.
Nitrogen dioxide (NO2), a priority pollutant and an indicator for Traffic-Related Air Pollution (TRAP), poses significant health risks including childhood-onset asthma and premature mortality. Routine measurements of NO2 are severely limited in Pretoria and Johannesburg, two large cities in the industrialised Highveld of South Africa that experience severe air pollution due to road traffic. We use tropospheric columns of NO2 observed with the TROPOMI instrument for 2019 and simulated NO2 vertical profiles for the same year from the very high spatial resolution (~6 km) CAMx model driven with a locally developed emissions inventory to estimate ground-level NO2. Near traffic-roadside ground stations, yearly averaged satellite-derived NO2 ranges from 9 to 68 µg/m³, far in excess of the threshold for harm. Satellite-derived values agree with ground stations where sampling conditions are consistent, but validation is limited to a few sites. Underway is the use of the satellite-derived NO2 to attribute asthma incidences and premature mortality to exposure to NO2 and TRAP using state-of-knowledge exposure-response coefficients and Global Burden of Disease baseline rates of mortality and asthma incidences to motivate action to address severe air pollution in the industrialised Highveld.
Keywords
TRAP, Health Impact, satellite-derived, mortality burden, asthma, anthropogenic emissions, South Africa
How to cite: Sepuru, T. K., Marais, E. A., Naidoo, M., Vohra, K., Gershenson-Smith, E., and Garland, R. M.: Impact of nitrogen dioxide pollution on paediatric asthma and premature mortality in South Africa, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-560, https://doi.org/10.5194/egusphere-egu25-560, 2025.
Introduction
Historically, intense underground mining for precious metals was the backbone of the South African economy for many decades. However, due to changing rent value of the targeted material and a shift in focus of the core economic activities, a number of small legacy mining towns are scattered across South Africa.
In this project, PM2.5 particulates were sampled at two points in Welkom. A residential area and the industrial area, 5.8 Km South of the residential site. A comparison for their total PM2.5, BC, UV-PM and trace elemental composition, sources and geographical origins was performed. The main objective of the study was to determine the air quality in a legacy mining town where past activities, more recent developments and spatial priorities contribute to the sources and matrix of the air pollutants.
Methods
Sampling was performed by gravimetric methods, with PM2.5 and the constituent elements analysed by XRF. The source apportionment and back trajectory transport was performed on EPA-PMF and HYSPLIT models respectively. A total of 75 samples were collected with 5 duplicates per site. Statistical analysis included descriptive statistics, Spearman’s Rank correlation and Kruskal-Wallis test for seasonality.
Results
The annual mean PM2.5 level for the 12-month study period was 14.7 µg.m-3 (11.6 – 66) at the Industrial area and 6.34 µg.m-3 (6.34 – 23.4) at the Residential Site. The daily PM2.5 WHO guidelines (15 µg.m-3) and the daily PM2.5 South African NAAQS (40 µg.m-3) were exceeded on 27 and 5 days of the 75 days, respectively, at the industrial and residential sites. The sum of the trace elements per 12-month period was 2.3 µg.m-3 and 1.5 µg.m-3 and these constitute 12.4% and 10% of the total PM2.5 per year. Of interest is that Cl and K were present at both sites, Mn was present at the residential site and P was present at the industrial only. Although 26% of wind trajectories are from the Westerly direction, the highest recorded particulates are from the Northerly direction with 19% of wind trajectories. The highest three recordings for PM2.5 for the industrial site was 66.1, 61 and 56 µg.m-3 on the 23 August, 6 June and 12 July 2022 respectively. From the NNE and Easterly directions. At the Industrial site, the highest average concentration (19.9 µg.m-3) recorded for a cluster was from the Northern direction over 13 days despite the cluster from the easterly direction recording 30 days (15.2 µg.m-3).
Conclusion
New spatial development priorities such as rezoning for industrial activities that are currently upwind of the residential sites present new air quality challenges to legacy ‘extractional’ towns such as Welkom in South Africa.
How to cite: Howlett-Downing, C. and Wichmann, J.: A comparative air quality and spatial planning study between two sites in a legacy mining town, Welkom, South Africa 2022-2023, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-798, https://doi.org/10.5194/egusphere-egu25-798, 2025.
Achieving the United nations 2030 Sustainable Development Goals (SDGs) remains a significant challenge, necessitating urgent and prioritized strategies. Among the various challenges, air pollution continues to pose one of the most substantial threats to the SDGs due to its widespread adverse effects on human health and ecosystems. However, the connections between air pollution and the SDGs have often been overlooked. This study reveals that out of the 169 SDG targets, 71 are adversely impacted by air pollution, while only 6 show potential positive effects. In China, two major atmospheric nitrogen pollutants, ammonia and nitrogen oxides, resulted in an economic loss of 400 billion United States Dollar (USD) in 2020, which could be reduced by 33% and 34% by 2030, respectively. It would enhance the progress towards SDGs in China by 14%, directly contributing to the achievement of SDGs 1 to 6 and 11 to 15. This improvement is estimated to yield overall benefits totaling 119 billion USD, exceeded the total implementation cost of 82 billion USD with ammonia as the preferential mitigation target. This study underscores the importance of robust scientific evidence in integrated policies aimed at aligning improvements in environmental quality with the priorities of sustainable development.
How to cite: Zhou, Y., Zhang, X., Zhang, C., Chen, B., and Gu, B.: Mitigating air pollution benefits multiple sustainable development goals in China, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2439, https://doi.org/10.5194/egusphere-egu25-2439, 2025.
Long-term exposure to elevated PM2.5 concentrations (fine particulate matter with a diameter smaller than 2.5 micrometers) poses a significant human health risk, contributing to excess mortality. Global estimates suggest that approximately 4–9 million excess deaths annually are attributable to PM2.5, with China accounting for about one-third of these fatalities. Since the start of the 21st century, China has undergone exceptional industrialization and urbanization, resulting in hundreds of millions of urban residents being exposed to poor air quality. Recognizing the severity of the issue, Chinese authorities began implementing a series of successive control measures in 2006 to address unprecedented levels of atmospheric pollution. The research presented here, based on satellite observations and a combination of novel trend and mortality analysis methods, highlights the significant achievements of Chinese policies in mitigating the sharp rise in PM2.5 levels. Our results indicate that the reduction of PM2.5 at the levels of 2018–2019 (pre-COVID) prevented more than one million excess deaths annually and avoided an average reduction in life expectancy of over one year. We suggest that maintaining emission reductions at the current rate could drastically diminish the PM2.5-related health burden within the next two decades.
How to cite: Georgoulias, A. K., Lelieveld, J., Klingmüller, K., Akritidis, D., Pozzer, A., Alexandri, G., Bilal, M., Cheng, Y., Su, H., and Zanis, P.: Health gains from particulate air pollution controls in China, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2884, https://doi.org/10.5194/egusphere-egu25-2884, 2025.
Exposure to particulate matter less than 2.5 micrometres in diameter (PM2.5) is the leading environmental risk factor for the global burden of disease and is associated with tens of thousands of deaths in the UK each year. Across the UK, legal compliance and progress towards the PM2.5 targets set out in the Environment Act, are measured using a network of fixed monitoring sites as part of the Automated Urban and Rual Network (AURN) across the country.
Over the last two decades, significant progress has been made in the reduction of PM2.5 concentrations across the UK. However, larger than expected decreases in PM2.5 have been observed recently across the UK. Temporal trends in PM2.5 concentrations across UK sites all show annual reductions in concentrations since 2018 with large reductions across the early part of 2019, before UK and European COVID-19 lockdowns in 2020.
This work utilises the AURN and complementary networks that measure gas-phase PM2.5 precursors including volatile organic compounds and ammonia as well as both inorganic and organic aerosol components. The aim is to investigate the potential drivers of recent reductions in PM2.5 concentrations across the UK to evaluate if the reductions are due to anthropogenic or natural drivers. These drivers could include emission reductions, changes in transboundary sources and atmospheric chemical pathways, as well as the effect of local and regional weather and climate. This analysis will inform assessment of whether the observed reductions may be a transient response to changes in the economy and commodity prices, changes in weather patterns, or whether the reductions represent change that is likely to be sustained. This has implications for both progress towards reducing the health burden of air pollution and future air quality policy.
How to cite: Bryant, D. J., Lewis, A. C., and Moller, S. J.: Investigating drivers of recent reductions in PM2.5 concentrations across the UK, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3541, https://doi.org/10.5194/egusphere-egu25-3541, 2025.
Nitrogen oxides (NOx = NO + NO2) are critical atmospheric pollutants with significant implications for human health and are key precursors of ozone and nitrate aerosols. Anthropogenic emissions primarily from sectors such as transportation, industry, and fossil fuel combustion are the main sources of NOx. The temperate regions of the Northern Hemisphere, which host most industrialized countries and densely populated areas, account for 60~70% of global anthropogenic NOx emissions. As the harmful effects of air pollution gain global attention, nations have implemented various clean energy policies to address these threats. Effective monitoring of anthropogenic NOx emissions and control policies relies on accurate, long-term emission inventories. However, existing “bottom-up” inventories suffer from delays in data compilation, making it difficult to timely and accurately monitor the spatiotemporal variations of NOx emissions. This study presents an effective top-down inversion framework using TROPOMI satellite NO2 observations combined with the GEOS-Chem atmospheric chemical transport model to assess recent NOx emissions. The framework employs a mass balance principle and a two-step inversion approach, extending anthropogenic NOx emissions in the Northern Hemisphere into 2022 and optimizing emissions from 2019 to 2022 for the temperate regions. Our results show a 1.68% decrease in NOx emissions in 2020, followed by a 5.72% rebound in 2021. The recovery in China was faster than in other regions, surpassing 2019 levels by July 2020. In 2022, emissions declined across all regions, driven primarily by the Omicron variant, energy shortages, and clean energy policies. By integrating satellite observations, atmospheric modeling, and emission inversion techniques, our study contributes to the growing body of knowledge on how emissions evolve in response to global disruptions.
How to cite: Mao, Y., Jiang, F., Ju, W., Wang, H., Feng, S., and Jia, M.: Spatiotemporal Trends in Anthropogenic NOx Emissions in the Northern Hemisphere: Insights from Satellite Observations and Atmospheric Modeling, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3661, https://doi.org/10.5194/egusphere-egu25-3661, 2025.
Long term exposure to fine particulate matter (PM2.5) is a major health risk associated with excess mortality. Ambient PM2.5 concentrations at a given location are subject not only to local pollution but also to that transported from other regions. To unravel the contribution of local and cross-border pollution to the PM2.5 related excess mortality of each country around the world, numerous simulations are carried out with the chemistry general circulation model EMAC (ECHAM5/MESSy for Atmospheric Chemistry), removing each time the anthropogenic emissions of a country. The simulations are performed at a T106 horizontal resolution (equivalent to 1.1 x 1.1 degree at the equator) for the year 2015, while the anthropogenic emissions of each country are based on CEDS (Community Emissions Data System, 2020-v1). Mortality calculations are performed applying the FUSION exposure-response function, with country-level population and mortality rates obtained from the GBD (Global Burden of Disease). We find that local pollution is the main driver of PM2.5 related excess mortality in China and India, while cross-border pollution is responsible for at least one out of two excess deaths attributable to PM2.5 in many European countries. Our results reveal the limits of health-driven mitigation, supporting policy makers to design and implement actions at both national and international levels.
How to cite: Akritidis, D. and Pozzer, A.: Unraveling the health impacts of local and cross-border air pollution, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4374, https://doi.org/10.5194/egusphere-egu25-4374, 2025.
Air quality and climate change are of the dominant challenges for Islandic ecosystems in Mediterranean region. This work studies the air quality and the impact of meteorological conditions in pollution levels of Chalki Island, a small island that is located in the climatic sensitive region of southeastern Aegean basin. The analysis was conducted during a low touristic activity period that covers the days from 24th of November 2023 to 3rd of March 2024. Hourly recording of PM2.5, O3 and SO2 as well as meteorological factors of temperature (T) and relative humidity (HR) from a mobile air quality monitoring system (Haz-Scanner™ Model HIM-6000) which is located in the center of city in combination with meteorological parameters (precipitation, planetary boundary height, atmospheric pressure, wind speed and direction) available from the last generation of ECMWF reanalysis dataset (ERA5) are used for the analysis. The calculation of Air Quality Index (AQI) for the studied pollutants shows that PM2.5 is the dominant factor that determines the air quality in the city center of Chalki. The majority of days is classified in “good” and “moderate” air quality classes (in terms of AQI). Additionally, the analysis shows that climate conditions significantly affect the concentration of pollutants. In particular, the higher height of planetary boundary layer (PBL) and increased ventilation coefficient (as a measure of the dispersive capability) are related to improved air quality conditions. The temperature and relative humidity conditions lead to improved climate sense for the mean population (in terms of Discomfort Index; DI<21). Finally, AQI is positive correlated to DI values (corr. Coef: 0.4) indicating a synergy of degraded air quality and discomfort conditions on human health.
How to cite: Logothetis, I., Giakoumakis, G., Mitsotakis, A., and Grammelis, P.: Air pollution and the impact of meteorological factors in air quality of Chalki Island during a winter period of 2023-2024, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5695, https://doi.org/10.5194/egusphere-egu25-5695, 2025.
Air pollution is a significant environmental issue affecting human health, with growing evidence linking it to chronic diseases such as Type 2 Diabetes Mellitus (T2DM). T2DM has become a major global health concern, with its prevalence and incidence rising at an alarming rate. This metabolic disorder, characterized by chronic hyperglycemia due to insulin resistance or insufficient insulin production, has traditionally associated with factors such as obesity, sedentary lifestyles, and dietary habits. However, recent research highlights that environmental exposures, particularly to air pollutants, may significantly contribute to the development and progression of the disease. Particulate matter (PM2.5) and nitrogen dioxide (NO2) have been shown to trigger systemic inflammation, oxidative stress, and endothelial dysfunction—key mechanisms in insulin resistance and beta-cell impairment. These findings emphasize the need to consider air pollution as an emerging and modifiable risk factor for diabetes.
However, the relationship between air pollution and T2DM remains underexplored, with limited studies establishing robust exposure-response relationships. Understanding the exposure-response relationship is crucial for accurately estimating the disease burden attributable to air pollution and guiding public health interventions. this study aims to establish the exposure-response function that relates the concentration of two air pollutants (NO2 and PM2.5) to the hazard ratio associated with acquiring T2DM, based on various cohort studies conducted worldwide. To achieve this, a methodology using nonlinear function adjustments will be employed, fitting a specific function dependent on four parameters to a scatter plot of pollutant concentration and hazard ratio data pairs extracted from available cohort studies. Once the specific form of this exposure-response function is determined, it will be applied to the domain of Europe using atmospheric concentrations for the period 1991-2020, obtaining the risk ratio for each cell. From there, the incidence of air pollution on T2DM will be estimated for each age group.
The results indicate a significant nonlinear relationship between air pollution exposure and T2DM incidence, with higher risks observed in areas with elevated levels of NO2 and PM2.5 (specifically, in large European cities and central Europe due to traffic and industrial activities mainly). The results show that NO2 air pollution is responsible for 4,693,000 [4,285,000 – 4,946,000 95% CI] cases of T2DM per year, representing an incidence of 0.64% [0.58 – 0.67 95% CI] relative to the total population of the study area. For PM2.5, the total number of annual cases rises to 5,009,000 [3,957,000 – 6,452,000 95% CI], accounting for an incidence of T2DM of 0.68% [0.54 – 0.87 95% CI] considering the population in the target area. The analysis revealed that PM2.5, despite lower concentrations compared to NO2, had a higher impact on T2DM incidence, especially at lower exposure levels. The findings underscore the need for stringent air quality regulations, particularly in urban and industrial regions, to mitigate the health impacts of air pollution.
How to cite: Jiménez-Guerrero, P., Ríos-Moreno, A., and Tarín-Carrasco, P.: Quantifying the Burden of Air Pollution on Type 2 Diabetes Mellitus in Europe, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6068, https://doi.org/10.5194/egusphere-egu25-6068, 2025.
Rapid urbanization and high population densities in Latin American cities pose significant challenges for air quality monitoring, particularly for fine particulate matter (PM2.5), recognized as the foremost health risk for urban populations. This study leverages satellite data and machine learning to estimate the spatial-temporal variability of PM2.5 in the Santiago City Metropolitan Area (Chile), providing critical data to enhance public health policies and address environmental injustices.
Our methodology encompassed four stages: data preprocessing, model architecture selection and construction, model validation, and spatial mapping of PM2.5 concentrations. Initially, we processed PM2.5 data from 12 ground monitoring stations (period 2015 to 2024), integrating it with meteorological data (ERA-5), land cover and NDVI products (MODIS), as well as aerosol products from MERRA-2. We employed a variety of modeling techniques, such as Decision Trees, Treebag, Random Forest, and Extreme Gradient Boosting (XGB). The XGB model was ultimately selected for its superior performance metrics (i.e., higher R2 and lower RMSE).
The XGB model captured a significant range of PM2.5 concentrations across Santiago for the test period (2023-2024), with winter months showing the highest levels, peaking at 75 µg/m³ in June 2023. In contrast, the lowest concentrations occurred from February to April and from October to December, with a minimum of 10 µg/m³ in November. The 1 km² resolution maps revealed a pronounced gradient of PM2.5 concentrations from the west (the Coastal Mountain range) to the east (the Andes Mountain range), negatively correlated with elevation. Densely populated communes such as Quinta Normal and Lo Espejo, which have lower socioeconomic standings, recorded the highest average PM2.5 concentrations (67 to 63 µg/m³). In contrast, wealthier and less densely populated areas like Lo Barnechea and Vitacura exhibited lower concentrations (21 to 23 µg/m³). By identifying how socioeconomic disparities intersect with environmental risks, this study provides a solid foundation for policymakers to formulate interventions that not only improve air quality but also promote social equity.
How to cite: Diez, S. and Urquiza, J.: Exploring PM2.5 dynamics in Santiago, Chile: how satellite data and machine learning could inform environmental policy, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14015, https://doi.org/10.5194/egusphere-egu25-14015, 2025.
Unequal exposure to air pollution is a systemic issue in the UK. What makes it further challenging to address are the inconsistencies in location and size of these disparities based on the air pollutant and chosen attribute: emissions, exposure or health burden. Missing is a comprehensive assessment in UK air pollution disparities from all three perspectives to inform policy. In this study, we explore how the location and size of disparities evolve from investigating disparities in air pollutant precursor emissions to that in exposure and health burdens.
Here, we use a 2-model setup to simulate meteorology and atmospheric composition over the UK at a spatial resolution of 9 km x 9 km for 2019. The meteorology is simulated using the WRF (Weather Research and Forecasting) model and atmospheric chemistry and transport processes using the CMAQ (Community Multi-scale Air Quality) model. The CMAQ model is updated with the most up-to-date chemistry mechanism CRACMM (Community Regional Atmospheric Chemistry Multiphase Mechanism) and is driven with air pollutant precursor emissions from the UK National Atmospheric Emissions Inventory (NAEI).
Modelled surface concentrations of health-harming fine particles (PM2.5) and nitrogen dioxide (NO2) are evaluated against observations from the extensive national and local ground-based monitoring networks and are then applied to health risk assessment models to quantify PM2.5-attributable premature mortality and NO2-attributable asthma incidences. The emissions (primary PM2.5 and NOx), exposure and attributable health burdens are then used with demographic datasets to examine disparities in these. Work is underway to compare inequities in urban versus rural landscape in the UK. Findings from this comprehensive evaluation of inequities will be used to inform stakeholders to create targeted interventions and action plans.
How to cite: Vohra, K. and Bloss, W.: A Comprehensive Assessment of Disparities in UK Air Pollutant Emissions, Exposure, and Health Burden to Inform Policy, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18940, https://doi.org/10.5194/egusphere-egu25-18940, 2025.
Traffic-related air pollution is one of the major sources of exposure in urban areas and an increasingly important contributor to anthropogenic emissions in lower and middle-income countries. Due to a rapid rise in the motor fleet owing to population growth, economic development, the expansion of metropolitan areas, and the increasing dependence on motor vehicles because of changes in land use, the concerns about the health effects of traffic-related air pollutants (TRAPs) have greatly increased. In the light of limited evidence in the Indian context, the present research work involved conducting a crossover panel study on a group of healthy adults in Delhi (security guards on a university campus; sample size ~ 40) to understand the short-term effect of PM2.5 (particles having aerodynamic diameter less than 2.5 microns) and their chemical components on acute changes in cardiovascular health. The study improved the exposure estimates by real-time monitoring of PM2.5 mass, its chemical components like ions and trace metals, black carbon (BC) and size-resolved particle number concentration in a traffic microenvironment instead of using ambient concentrations as a proxy to traffic exposure. The participants were administered questionnaires to gather the background data about socio-economic status, secondary exposures or prevailing health conditions and any potential confounders. The ECG holter systems were used to monitor the real-time changes in heart rate variability (HRV) parameters, which are an indicator of cardiac activity (both time-domain (SDNN- standard deviation of normal-to-normal; pNN50- percent normal-to-normal intervals > 50ms; rMSSD- root mean square of successive differences between normal heart beats) and frequency domain (HF- high frequency; LF- low frequency and LF/HF ratio) were monitored). Mixed models were used to quantify the associations between TRAPs and HRV parameters. A significant decline was observed in all the HRV indices with an increase in the pollutant concentrations. The highest decline in HRV with respect to particle size was observed for the particles with a diameter between 0.03-0.1 µm with negligible change in particles with dia. > 1µm. Similarly, amongst the PM2.5 constituents, BC showed the highest decline in HRV, followed by nitrates and sulfates. The study emphasized the need to study exposures in specific microenvironments due to differences in the pollutant concentrations and composition with respect to ambient. It also highlighted the need to investigate the micro-physical and chemical characteristics of PM2.5 because of their potential to have greater health impacts as compared to the total PM2.5 concentrations.
How to cite: Jain, K. and Habib, G.: Assessing Short-Term Cardiovascular Effects of PM2.5 and Its Components in a Traffic Microenvironment: A Crossover Panel Study in Urban India, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20428, https://doi.org/10.5194/egusphere-egu25-20428, 2025.
We use ensemble climate simulations over Minnesota with the Weather Research and Forecasting (WRF) model to compute downscaled versions of the comprehensive global climate projections for the 20-year periods 2040-2059, 2060-2079, and 2080-2099. We also perform model integrations over the historical period of 1995-2014 in order to assess any systematic model uncertainties.
These projections build on our previous results at 10-km resolution, but now we use a higher 4-km horizontal resolution over Minnesota nested in a 20-km grid over the contiguous USA and southern Canada with 38 vertical levels in the atmosphere and a sophisticated representation of the many lakes that exist in Minnesota.
Our final results will show a more detailed representation of the ongoing warming for individual counties in Minnesota in all seasons, especially in winter. We expect conditions near the end of the 21st century that are significantly different from current climate. Our results will influence regional decision-making related to agriculture, infrastructure, water resources, and other sectors.
How to cite: Liess, S., Roop, H., Twine, T., Fernandez, A., Dolma, D., Gorman, J., Meyer, N., Farris, A., and Neff, P.: Fine-scale Climate Projections over Minnesota for the 21st Century , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20465, https://doi.org/10.5194/egusphere-egu25-20465, 2025.
Coal and lignite mining, along with thermal power generation, are major contributors to air pollution, posing significant risks to human health and the environment. India, ranking fifth globally in coal reserves, is the second-largest producer, consumer, and importer of coal. Currently, 533 active coal mines and 20 lignite mines operate in the country, of which 249 coal mines and all lignite mines are opencast. Approximately 180 coal-based and 9 lignite-based thermal power stations contribute to meeting ~77% of India's energy demands. According to research by the Global Burden of Disease regarding the present state of air pollution, there were an astounding 1.67 million air pollution-related deaths in India alone in 2019. Most of these deaths, or over 0.98 million, were caused by ambient particulate air pollution such as PM2.5. Long-term PM2.5 exposure is associated with adverse health effects, including Chronic Obstructive Pulmonary Disease (COPD)—the third leading cause of mortality globally—contributing to substantial financial burdens. In this study, we evaluated PM2.5concentrations at 10 locations in and around the Neyveli Lignite Mine, India’s largest opencast lignite mine, for over two years (March 2020–February 2022). The mean annual PM2.5 concentrations across the study locations were 41.08 μg/m³ (Year 1) and 41.42 μg/m³ (Year 2), exceeding Indian NAAQS, US EPA, and WHO air quality standards. Meteorological data were obtained from the NCEP-NCAR Reanalysis 1 dataset, and air mass back trajectory clusters were analysed using NOAA’s HYSPLIT model. Conditional Bivariate Probability Function (CBPF) and Potential Source Contribution Function (PSCF) plots were generated to identify potential PM2.5 sources. CBPF 75th percentile plots revealed significant pollution events from the south and southeast directions at wind speeds >4 miles/hour. PSCF 75th percentile plots indicated long-range PM2.5 transport from the Bay of Bengal (summer and winter), the Arabian Sea (monsoon), and nearby urban areas (post-monsoon). Using the Multiple-Path Particle Dosimetry (MPPD) model, PM2.5 deposition in the human respiratory system (Yeh/Schum 5-Lobe) was estimated for exposure scenarios of 8 hours/day, 5 days/week, over a year. The total deposition fraction was 0.8238, with the head region contributing the highest deposition (68.28%), followed by the pulmonary (23.56%) and tracheobronchial regions (8.16%). Health impact assessment using WHO’s AirQ+ software estimated COPD hospitalisations attributable to PM2.5. The Estimated Attributable Proportion (EAP), Excess Attributable Cases (EAC), and Estimated Attributable Cases per 100,000 Population (EACP) ranged from 6.57%–6.63%, 1,085–1,095, and 1,026.35–1,035.59, respectively. The financial burden of COPD, evaluated using the Cost of Illness (COI) and Value of Statistical Life (VSL) methods, was 43.23–43.62 million INR (COI) and 1,768,474 INR (VSL). These results highlight the significant health and economic impacts of PM2.5 exposure, emphasising the critical need for targeted air quality interventions and sustainable practices. Moving forward, these preliminary findings will be expanded through receptor modelling to provide a more detailed source apportionment, offering valuable insights for enhancing air quality through focused interventions and strategies.
How to cite: Mitra, S. and Nagendra, S.: Assessing PM2.5 Exposure and Health Risks in a Mining and Thermal Powerplant Township in Southern India: Impacts on Air Quality and Public Health, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-21565, https://doi.org/10.5194/egusphere-egu25-21565, 2025.
