India struggles with frequent exceedances of the ambient air quality standard for particulate matter, ozone and benzene. The situation in the Indo-Gangetic plain (IGP) is particularly severe during post monsoon and winter season.

We show that despite strong governmental efforts to make clean energy accessible and affordable, residential solid fuel usage is still the largest source of particulate matter pollution and carcinogenic benzene in India. Particularly cow dung as a cooking and heating fuel contributes disproportionally to the residential sector emissions and India’s air quality challenge. In addition, crop residue burning, open burning of waste, solid fuel usage in industrial boilers, and power generation units also contribute significantly to the particulate matter and benzene emissions over the region. In urban agglomerations, transport sector emissions aggravate the already poor air quality further.

In this talk we present several recently updated gridded emission inventories with detailed VOC speciation for these air pollution sources. We also look at future projection under different Shared Socioeconomic Pathways (SSPs) for several sources.

We focus on the most polluted part of the year, namely post-monsoon and winter season, to evaluate and compare these updated emission inventories against other available emission inventories and measurements studies. We find that that existing inventories tend to underestimate the magnitude of residential sector emissions and their strong seasonality. The use of solid fuels for heating purposes results in a strong temperature induced emission feedback that can aggravate the wintertime fog. Existing inventories also underestimate the magnitude of crop residue burning emissions and lack open waste burning as a source.

A combination of measurement-based assessments and emission inventories for different air quality intervention strategies are used to evaluate a number of possible air quality interventions for their potential impact. We specifically look at the sectoral coupling between the residential sector, waste management, crop residue management, and the transport sector to propose interventions that maximize air quality gains.

How to cite: Sinha, B., Hakkim, H., Sharma, G., Chaudhary, P., Kumar, A., Pawar, H., Chandra, P. B., and Sinha, V.: Can India leapfrog into a clean air future – perspectives from measurements, source-receptor modelling and emission inventories, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8342, https://doi.org/10.5194/egusphere-egu23-8342, 2023.

Pollution is a major problem in developing countries.  There has been much studies on water pollution and its relation to communicable diseases with little attention to air pollution.  Air quality problem in sub-Saharan Africa is pervasive due to lack of awareness and paucity of reliable data.  The lack of reliable data has limited our underestanding and quantification of its impact on the population.  To address this problem, the the Centre for Atmospheric Research, Nigeria, and the Alliance for Education, Science, Engineering and Design in Africa of the Penn State University collaborated to densify air quality monitoring networks in Nigeria.  The programme has succeeded in deploying over 70 monitoring networks across the country within the last two years. Using data from the network, the impact of air quality especially in relation to diseases have been assessed within Nigeria.   This approach has revealed significant association between air quality and COVID-19 infections.  Furthermore, the available data has helped in understanding the sources of air pollution in different regions of the country.  This is helping in formulating environmental policy, planning, and monitoring for reduction of air pollution.  In this presentation, the progress and challenges in the densification of air quality monitoring stations across the country will be presented.

How to cite: Ogunjo, S., Rabiu, B., Fuwape, I., Jenkins, G., and Obafaye, A.: Densification of air quality monitoring in Nigeria: Progress and challenges, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11895, https://doi.org/10.5194/egusphere-egu23-11895, 2023.

Exposure to ambient PM_2.5 is the leading environmental health risk in India. An efficient air quality management plan requires a consistent and long-term database at high spatial and temporal scale. We have developed a satellite-based PM_2.5 data for India by filling the gaps in satellite AOD to complement the paucity in ground monitoring. The average population-weighted exposure during 2017-2021 was estimated as 52.5 μg/m³, 18.1% lower than the estimates without adjusting for the sampling gaps. The annually averaged mortality burden attributable to ambient PM_2.5 exposure during this period was estimated to be 0.45 million (95% UI: 0.36-0.55), 0.27 million (95% UI: 0.22-0.33) and 0.24 million (95% UI: 0.19-0.28) for low, medium and high sociodemographic index states, respectively. If the sampling gaps in satellite AOD is not filled, the health burden in India would be overestimated by 0.1 million (95% UI: 0.07-0.13).  We demonstrated  use of this satellite data in various air quality management practices. We have delineated 9 to 11 major seasonal air sheds in India using k-means clustering. We have found that the number of days daily PM_2.5 exceeding the national standard have decreased during 2017 to 2021 in all air sheds. We have identified the potential sites for future expansion of the ground network under the National Clean Air Program. We examined the representativeness of the existing ground monitors in the non-attainment cities. These lessons learned in India could be valuable for other developing countries with limited or no ground monitoring.   

How to cite: Dey, S., Kumar, A., Katoch, V., Imam, F., Sarkar, D., and Sharma, K.: Application of satellite data in air quality management: Lessons learned in India, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2495, https://doi.org/10.5194/egusphere-egu23-2495, 2023.

Rapid economic growth with ongoing urbanization trends has led to exponential growth in global transport demand, especially in Asia. The growing vehicle population in India is one of the major contributors to congestion and air pollution causing related health and climate risks in urban areas. In this study, we assessed the impact of motor vehicles on near-road air pollution using roadway tunnel and roadside measurements under real-world traffic conditions based on speed, type of roads, vehicle types (LDV: light duty vehicles, HDDV: heavy-duty diesel vehicles), and fuel composition (gasoline and diesel vehicles). Portable real-time and gravimetric instruments were used to measure emissions from high-speed urban traffic (at Freeway tunnel: all LDV fleet), low-speed creeping traffic (at LBS road: 5% HDDVs and rest LDV fleet), and idling traffic (at Mulund toll plaza: 8% HDDVs and rest LDV fleet) in Mumbai city, and high-speed inter-city traffic (at Kamshet-I tunnel on Mumbai-Pune expressway: 20% HDDV and 80% LDV), covering both peak and off-peak traffic hours. A very small fraction of electric vehicles was also observed in the fleet at LBS road and Toll plaza. Simultaneous measurements were also carried out at an urban background location in Powai, Mumbai. All measured gaseous (CO₂, CO, NO_2, and VOCs) and particulate (PM_2.5 and BC) pollutants at the roadsides and the tunnels were 1.2 to 3.8 times higher than in the background. Total fine carbonaceous species, comprising of elemental carbon (EC) and organic carbon (OC) accounted for up to 47%(±5%) of total PM_2.5, highest in the inter-city traffic which could be attributed to its high HDDV and super-emitter fraction followed by the urban idling traffic which had significant HDDV fraction. The OC/EC ratio was 1.8 (± 0.3), highest in the high-speed urban traffic with all light-duty vehicles (LDV) fleet, and the higher HDDV fraction in the inter-city traffic attributed to the low OC/EC ratio of 0.7 (±0.4).  The water-soluble organic carbon (WSOC) fraction that affects aerosol hygroscopicity accounted for up to 70% of the total OC. WSOC was found highest during the afternoon period at the roadsides as well as the background site indicating the contribution of other sources, including photochemical processes. Our study finds that while the near-road emission levels are inevitably higher due to the significant contribution from on-road vehicles, the emission profiles vary significantly depending on the vehicle and fuel composition. Higher HDDV fraction and super-emitters in the fleet contributed to 2.8 folds of higher EC concentrations.  These findings can help in making informed policy decisions towards urban vehicle emission control and monitoring by focusing on targeted vehicles that are polluting disproportionately more than the rest of the vehicles.

How to cite: Debbarma, S., Lal, B., and Phuleria, H. C.: Near road urban air pollution due to vehicular traffic: Effect of real-world driving conditions and vehicle composition, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1617, https://doi.org/10.5194/egusphere-egu23-1617, 2023.

How to cite: Sitati, C.: In-kitchen aerosol exposure in Korogocho informal settlement in Nairobi, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2211, https://doi.org/10.5194/egusphere-egu23-2211, 2023.

Air pollution is one of the leading risk factors for poor health in Africa, resulting in millions of premature deaths and economic losses. Of particular interest is exposure to fine particulate matter (PM_2.5) which is the driver for a majority of deaths across the continent. However, PM monitoring, and by extension, ground-level data on PM_2.5 is very limited; this limits our understanding of the widespread societal and health impacts linked to PM pollution. The robustness of low-cost PM sensors and their ability to report in situ data in tropical environments via internet-based platforms as well as relative affordability has created the opportunity to employ low-cost sensors (LCS) for air quality monitoring but calibration methodologies and the usefulness of the high-temporal resolution data for source identification remain a challenge. Increasingly, local governments in African countries are also turning to low-cost sensors to monitor air quality. In this study, two Airnote PM monitors were colocated with reference-grade Teledyne PM mass monitor T640 for ~4 weeks at the University of Ghana, Accra to establish their performance using a simplified data correction methodology - multiple linear regression (MLR) model. A split ratio of 80% and 20% was used to train and test the populated Airnote PM_2.5 data respectively based on measurements from Teledyne T640 with temperature and relative humidity values from the Airnote monitor. Sectoral and calendar analysis with wind component data were used to triangulate the sources of PM_2.5. We observed a high consistency between the two Airnote monitors. Hourly and 24-hour average PM_2.5 values ranged from 25 to 95 μg/m3, and 29 to 54 μg/m3 respectively, and in most cases, were significantly higher than the WHO Air Quality Guideline. MLR using Pearson’s correlation analysis improved the out-of-the-box quality of low-cost Airnote PM_2.5 data; the R² improved from 0.69 to 0.84 and the mean absolute error from 11.75 to 4.20 μg/m3 respectively. Also, the MLR correction model was found to improve the Airnote PM_2.5 data quality for higher relative humidity (between 50 and 90%) but not lower. PM_2.5 pollution was local and from N, NE and SW winds for the raw, corrected and Teledyne PM mass monitor T640 measurements. Together, these results indicate that with appropriate corrections, low-cost PM sensors can generate the much needed data for air pollution research and mitigation in areas with limited air quality monitoring and data.

How to cite: Hodoli, C. G., Amoah, A., Buer Boyetey, D., Mead, I., Coulon, F., Pant, P., Ivey, C. E., Owusu Tawiah, V., Nimoo, J., Morladza, J.-T., Raheja, G., Amedofu, M., Allison Hughes, F., Kowu, N., Appoh, E., Essien, B., Malings, C., and Westervelt, D. M.: Enhancing the spatial and temporal resolution of air quality monitoring in low – and middle-income countries using low-cost sensors, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3903, https://doi.org/10.5194/egusphere-egu23-3903, 2023.

Emission inventory is an important tool for air quality management. Jakarta as a capital city of Indonesia has a very high air pollution as a result of urban activities from various anthropogenic sources. This study aims to conduct emission inventory and emission spatial distribution of NO_X, CO, PM_2.5, PM₁₀, NMVOC, BC, and SO₂ from anthropogenic sources in Jakarta from 2015 to 2030, using 2015 as a baseline year. The results from this study can be very important to improve the emission data for Jakarta and contribute to the global emission model. This result can also be used for air quality management and lesson learnt cases for other regions in South East Asian countries.   Emissions of these pollutants were calculated using GAINS (Greenhouse gas Air pollution INteractions and Synergies) model, considering implementation of emission standards for transport and stationary combustion sources as well as policies stimulating accelerated electrification of vehicle fleets and vehicle scrapping programs. The impact of current policies to emission reduction was also evaluated in this study. The total 2015 emissions of NO_X, CO, PM_2.5, PM₁₀, NMVOC, BC and SO₂ were estimated at around 53 kt, 144 kt, 4.6 kt, 6 kt, 48.6 kt, 1.2 kt, and 20 kt, respectively. The biggest contribution for NOx, CO, BC and NMVOC emissions originated from road transportation sector which contributed about 57%, 93% and 75%, 96% respectively, while for SO₂, industrial combustion contributed about 67%. Heavy duty vehicles contribute the most NO_x and BC emissions in the transport sector, while motorcycles emit the most CO. Meanwhile PM_2.5 and PM₁₀ in Jakarta are mostly emitted from road transportation and industrial combustion sectors, which contributed around 43%-46% for each sector. Heavy duty vehicles were still the highest contributor of PM_2.5 emission in the transport sector. In addition to air pollutants, GHG (CO2 eq) emission was also calculated in this study and the results indicating that the main contributor in 2015 were road transport  and power & heating plant which contributed 34% and 32 % respectively.  Based on emission spatial distribution, the highest concentration of all pollutants was found in the central of Jakarta, where traffic activities are very busy. Policy implementation could effectively reduce pollution levels in Jakarta. The accelerated implementation of electric vehicles, stringent emission standards, and transport management measures like electronic road pricing could significantly contribute to the reduction of PM_2.5, PM₁₀ as well as BC.

Keywords: Emission inventory, pollutants, power plant, industry, residential and commercial, PM_2.5, NOx, SO₂, NMVOC, GAINS.

How to cite: Lestari, P., Arrohman, M. K., Damayanti, S., and Klimont, Z.: Emissions Inventory of Air Pollutants from Anthropogenic Sources in Jakarta, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6686, https://doi.org/10.5194/egusphere-egu23-6686, 2023.

Over the past decade the air pollution problem in the bowl-shaped Kathmandu Valley in Nepal – South Asia’s Mini-Mexico City – has become one of the most studied in the region.  Several international field campaigns resulted  50+ journal papers, while three separate networks now provide live air quality data to policymakers and the public.  They valley’s air pollution meteorology, emissions, ozone chemistry, aerosol chemical composition, health impacts, and the role of pollution transport have all been studied in detail.  At the same time, interdisciplinary task forces have laid out clear regulatory priorities and action plans for the Kathmandu Valley. 

Yet except for a decline in coarse dust (due to more roads getting paved), air quality has not improved in the Kathmandu Valley. Regulatory interventions have mostly been spontaneous, devoid of expert inputs, and short-lived.  There exists today sufficient scientific understanding to design a sophisticated regulatory framework that would respond to changing situations in real time to maintain the valley’s air quality.  But today that is just a dream.  

As a front-row participant in the design of the field campaigns in the Kathmandu Valley, in policy making, and most recently in alternative politics, the author has unique insights into challenges that need to be overcome for there to be serious government action to clean up the Kathmandu Valley’s air.  At EGU he will share his insights into which scientific results did or did not end up being useful in shaping the public policy narrative, and why.  He will conclude his presentation by taking the lessons from the Kathmandu Valley from the past decade to provide general principals for other cities with air pollution problems but little data.

How to cite: Panday, A.: The Kathmandu Valley as a science-policy laboratory: When science is insufficient to achieve clean air, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8285, https://doi.org/10.5194/egusphere-egu23-8285, 2023.

Air quality over North Eastern region of Pakistan is rapidly worsening over the years, especially over Lahore and adjacent areas reporting world record levels of pollutant concentrations including highest particulate matter (PM) levels during the autumn and winter seasons. Meteorological parameter plays an important role in extreme pollution episodes. In order to study the impact of meteorological condition such as planetary boundary layer (PBL) an intensive PBL measurements were conducted over Lahore from October 2019 to March 2021 using LUFT CHM15K Ceilometer LIDAR. The impacts of PBL structure on heavy haze pollution and the relationship with PM2.5 concentrations were studied. The boundary layer height drops clearly during winter period (December 2019 and 2020, usually lower than 500m. The PM2.5 concentrations increases when the PBL drops and vice versa. Key finding in this study is that the dynamics of the Planetary Boundary Layer (PBL) change significantly during heavily polluted days during intense autumn / winter smog periods, which indicates the role of aerosols in influencing meteorological conditions, besides having other impacts in the region of study.   

How to cite: Shahid, I. and Shahzad, M. I.: Impact of planetary boundary layer in dense haze /smog event over South Asian Mega City; Lahore Pakistan, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11384, https://doi.org/10.5194/egusphere-egu23-11384, 2023.

Increasing awareness of air pollution requires access to timely and reliable air quality data and information, and yet many African cities lack effective air quality monitoring infrastructure, largely because of the resource constraints of establishing and managing a continuous monitoring network. Low-cost sensor platforms have the potential to close the air quality data gaps in resource-strained settings such as Africa, but the continued lack of accessible and reliable infrastructure for data management is a major hindrance to effective air quality management.

Moreso, managing a large Internet of Things (IoT)-based sensor network can be complex, and the demand for a case-specific and highly customizable platform, coupled with its conceptualization & implementation complexities, renders most existing IoT platforms ineffective. There is a need for a platform infrastructure for continuous support and management of air quality data with a high spatial and temporal resolution to facilitate sophisticated analysis; while taking care of the associated structural challenges of low-cost sensors.  The AirQo platform, a robust could-native software is a novel communityaware digital platform for managing large-scale air quality networks, applicable in resource-strained environments. This customisable and scalable platform attempts to address the data access challenges, with capabilities to become a ‘one-stop centre’ for management of other third party IoT sensor networks. Different interfaces through mobile application, web-based dashbord and platform cater for diverse data needs. The robust approach enables decision makers and other stakeholder communities have access to timely and quality assured air quality data. Using a set of metrics, user-experiece can be computed and compared with existing IoT management platforms. Software design considerations including (1) Multi-tenancy, (2) Data pipeline, (2) Sharded Database Cluster, (3) Microservices architecture, (4) Containerized deployment, and (5) Interoperability are recommended to support replication in other use-cases.

How to cite: Okure, D., Ogenrwot, D., Nsimbe, N., Muyama, L., Adong, P., Sserunjogi, R., Bbaale, M., and Bainomugisha, E.: Data management in resource-limited settings: Unpacking the role of robust digital solutions for air quality data management in African cities., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16697, https://doi.org/10.5194/egusphere-egu23-16697, 2023.

In this study, Ceilometer measurements of attenuated backscatter coefficient over Delhi-NCR during monsoon (June-September) and post-monsoon (October-November) of 2022 are analyzed to determine cloud base height (CBH) and atmospheric boundary layer (ABL) height. The derived CBH and ABL height are used to assess the impact of low clouds (CBH < 2km) and ABL height on regional air quality. The Ceilometer measurements are augmented by ERA5 reanalysis dataset of hourly averaged CBH and ABL height and radiosonde measurements. The aerosol loading over Delhi-NCR is derived using Moderate Resolution Imaging Spectroradiometer (MODIS) Terra aerosol optical depth (AOD) measurements and Dusttrack retrieved particulate matter with aerodynamic diameter ≤ 10 µm (PM₁₀) concentrations. We also used Ceilometer measurements for non-cloudy days to interpolate missing PM₁₀ values during the study period. To evaluate the dilution and diffusion of pollutants, we calculated ventilation coefficient from ABL height and wind speed data.

The results reveal that out of the total measurements during monsoon season, 41% cloud occurrence was observed, out of which 24% of clouds were low-level clouds. In post-monsoon season, cloud occurrence was low (nearly 12%), out of which 40% of clouds were low-level clouds. The ABL results show that during monsoon season, average ABL height was 0.85±0.6 km and during post-monsoon, it was 0.53±0.45 km. The seasonal difference is not only noted in the average values but also in the growth of ABL with full growth of ABL happening 2 hours later in post-monsoon season than monsoon season. The MODIS derived AOD results show average AOD values of 0.72±0.29 and 0.97±0.54 in monsoon and post-monsoon season respectively.

The comparison of PM₁₀ & AOD values indicate that during the cloudy days, both PM₁₀ values and AOD values were higher suggesting the abundance of cloud nuclei which could facilitate low cloud formation. For cloudy days, the correlation of observed CBH of low clouds with PM₁₀ and AOD shows a strong negative correlation (-0.78 and -0.83 respectively) suggesting that under same atmospheric thermodynamic conditions, CBH lowers under polluted conditions. The seasonal characteristics show that this tendency is predominant in post-monsoon than monsoon which might require further investigation. We observed strong negative correlation of ABL height with PM₁₀ and AOD (-0.84 and -0.89 respectively) during the study period. The derived ventilation coefficient shows a strong negative correlation with PM₁₀ and AOD values (-0.67 and -0.69 respectively). Both seasons showed similar characteristics indicating that the dissipation of pollutants depends more on ABL during both the seasons. However, substantiation of the diffusion and dilution processes over Delhi-NCR may require further investigation with different meteorological conditions. This will be added to this study along with the impact of clouds and ABL on different size distributions of aerosols. In conclusion, we used advanced instrumentation to study the interlinkages of atmospheric vertical structure with air quality. Our findings are relevant for the Indo Gangetic Plain (IGP) having population more than 400 million and can be applied to other places in the global south experiencing high pollution episodes often linked to unfavourable meteorology.

How to cite: Rathore, J. and Ganguly, D.: Impact of low clouds and boundary layer height on regional air quality over Delhi-NCR, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5925, https://doi.org/10.5194/egusphere-egu23-5925, 2023.

The National Green Tribunal (NGT) was established in accordance with the National Green Tribunal Act, 2010. NGT is the specialized judicial body, consisting of technical members and judicial members, constituted for adjudicating environmental cases and reducing the burden of litigation in other courts in the country. In matters involving air pollution, anyone seeking relief or compensation for environmental damage concerning issues included in the Air (Prevention and Control of Pollution) Act of 1981 may approach the tribunal. Before the establishment of the NGT, the country’s apex court played a vital role in delivering land-mark decisions concerning air pollution. The objective of the current study is to assess if the involvement of technical experts in the tribunal has improved the redressal mechanism. The judgments were reviewed in SCC online’s case finder and NGT official portal. The methodology involved analyzing cases decided by the NGT for five indicators that signal the use of technical expertise in decision-making. These indicators are (i) scientific/ technical content of the ratio decidendi, (ii) technical investigation of the case directly by NGT, including site visits by its technical experts, (iii) Assessment of technical reports directly by NGT, without the help of external experts (iv) insistence by NGT on studies using latest techniques as part of the investigation (v) Evaluating reversal of NGT verdict following the Supreme Court appeal on technical grounds. In general, this study assesses the role of the scientific experts as decision-makers in the environmental redress process. Reported cases, supported by existing literature show that scientific experts had a significant policy impact, which is crucial in air quality management. A guideline document, similar to the Environmental crime investigation manual of INTERPOL can improve the situation further by helping the investigator choose the suitable approach for a given scenario. 

How to cite: Sekar, A., Samad, M. S. A., and Varghese, G. K.: Has the redressal mechanism for air pollution-related cases in India evolved since the inception of the National Green Tribunal?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11184, https://doi.org/10.5194/egusphere-egu23-11184, 2023.

Presently, 17 out of 30 Indian cities are ranked worst in air quality around the globe due to high emissions of fine particulate matter, PM_2.5 (particles less than 2.5 µm diameter). These particles can reach deeper into the lungs and cause serious health problems, including cardiovascular obstructive pulmonary disease, lung cancer, stroke, and asthma. To take prompt actions towards mitigating and controlling the adverse effects of air pollution, it is important to monitor the ambient air quality regularly and at the neighbourhood level. However, the distribution of the regulatory central ambient air quality monitoring stations (CAAQMS) in India is sparse, and many states and cities lack any regulatory stationary monitors (RSMs). Conventional air quality monitoring techniques are inefficient and incapable of mapping PM_2.5 at a sub-Km level. The heterogeneity of PM_2.5 concentrations at large-scale and high spatial resolution has numerous applications in epidemiological studies, detecting hotspots within neighbourhoods and implementing policy interventions at local, regional and city levels. Therefore, an integrated monitoring framework is needed to fill gaps in the existing air quality measurements. This study proposes a tribrid approach of using the low-cost sensor (LCS) network to supplement the RSMs in generating more ground-truth PM_2.5 concentrations along with high-resolution micro-satellite imageries (PlanetScope, ~3m/pixel) to estimate and generate the PM_2.5 concentration maps at the sub-Km level (~500m by 500m). In the present study, an extensive LCS network of 70 nodes deployed at optimally selected locations within and around the boundaries of Lucknow city, Uttar Pradesh, India, along with six existing RSMs for one year (December 2021 onwards). It has increased monitoring ten folds at a moderate cost, covering remote urban and rural areas. The locations of these LCS and RSMs (76 nodes) have been used to precisely extract the daily (every day Dec 2021-2022) high-resolution satellite imageries by forming the area of interest (AOI) of size 224 by 224-pixel around the node while keeping the node in the middle of AOI. These imageries have been labelled with the ground truth PM_2.5  values from the nodes with geographical location and meteorological parameters such as relative humidity, atmospheric temperature, and barometric pressure. These labelled data are then fed into a deep learning CNN-RT-RF (Convolutional neural network- random trees-random forest) joint model to predict PM_2.5 at sub-Km level, which provides RMSE~ 2.74 and 7.50 for training and test data, respectively. The study further compares model performance with existing datasets of Delhi and Beijing. The results show that the predicted PM_2.5 using satellite imagery shows a strong co-relation with LCS and RSMs network and thus can be used as a soft sensor for large-scale monitoring. This study is the first study to integrate LCS sensor data with microsatellite imagery, leveraging over costly, conventional methods using machine learning approaches.

How to cite: Tripathi, S., Jain, V., Mukherjee, A., Banerjee, S., Rai, P., and Madhwal, S.: Predicting PM2.5 based on micro-satellite imagery and low-cost sensor network using CNN-RT-RF Joint Model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12426, https://doi.org/10.5194/egusphere-egu23-12426, 2023.

Long-term measurements of the composition and mass concentration of particulate matter (PM) are essential for source apportionment, epidemiological studies, and air quality trends. Over the past ten years, the Aerosol Chemical Speciation Monitor (ACSM) has been widely used for long-term, in situ, high time resolution measurements. However, to date there are limited measurements with these instruments in Africa and South/Southeast Asia. The measurements that have been made in these regions suggest the presence of varied and complex sources. Current ACSMs have unit mass resolution (UMR), which impacts detection limits and separation and identification of ions, limiting source apportionment. Here, we present a new instrument, the Time-of-Flight ACSM with eXtended resolution (TOF-ACSM-X) with updated analysis software (Tofware) to allow for high-resolution peak fitting. The TOF-ACSM-X has a mass resolution of ~2000 m/Δm, which is approximately an order of magnitude higher than the other versions of the ACSM. This enhanced resolution improves ammonium detection limits by approximately 2-orders of magnitude, from ~0.200 μg m^-3 to ~0.008 μg m^-3 (TOF-ACSM versus TOF-ACSM-X, respectively), for 15-minute integration times. Intercomparisons of the TOF-ACSM-X with other measurements show improved performance in source apportionment and elemental analysis.

How to cite: Croteau, P., Nault, B., Canagaratna, M., Fortner, E., Lambe, A., Stark, H., Sueper, D., Werden, B., Williams, A., Williams, L., Worsnop, D., and Jayne, J.: Enhanced Quantification and Source Apportionment Capabilities of a New Higher-Resolution Aerosol Chemical Speciation Monitor for Long-Term Measurements of Non-Refractory Aerosol, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9929, https://doi.org/10.5194/egusphere-egu23-9929, 2023.

Non-methane hydrocarbons (NMHCs) are important precursors of tropospheric ozone and secondary organic aerosols (SOAs). The air quality in South Asia is rapidly deteriorating due to increasing pollution levels, and transporting these pollutants to pristine regions in the Himalayas also exacerbates the problem. Despite this, air quality studies are very limited in South Asia, particularly in remote Himalayan regions. This study presents first time, a comprehensive analysis of light NMHCs (C₂-C₅) at the central Himalayas mountain site (Nainital; 29.37°N, 79.45°E, 1958 m a.m.s.l.) and an Indo Gangetic Plain (IGP) site (Haldwani; 29.22°N 79.51°E, 554 m a.m.s.l.). Observations were made from January 2017 to December 2020 using a Thermal Desorption Gas Chromatograph equipped with Flame Ionization Detectors (TD-GC-FID). The continuous online observations showed diurnal variation in light-NMHCs with higher values in the daytime throughout the year except for the summer/monsoon months. The mixing levels of alkanes, alkenes and alkynes vary from the lowest level of 1.96±0.77 ppbv, 0.29±0.06 ppbv, and 0.22±0.20ppbv respectively, to the highest levels of 4.43±0.84 ppbv, 1.03±0.39 ppbv, and 0.75±0.40ppbv in November, respectively. However, an IGP site showed much higher levels at nighttime than in the daytime, where alkanes, alkenes and alkyne showed 19.24±0.24 ppbv, 2.88±1.76 ppbv, 1.41±1.21 ppbv levels during winter and 13.41±9.33 ppbv,1.88±1.65 ppbv, 0.67±0.59 ppbv. Among eight light-NMHCs, the observed levels of ethane, ethylene, propane, n-butane and acetylene were highest during winter and spring and minimum in summer/monsoon at both sites. Ethane is most dominant at the Himalayan site, while propane is at the IGP site. The investigation of the natural logarithmic ratio between two different pairs (ln([n-butane]/[ethane]) to ln([i-butane]/[ethane]) and ln([Propane]/[ethane]) to ln([n-butane]/[ethane]) suggested the role of oxidation of OH mechanism for light-NMHCs removal in the atmosphere at both the sites and globally compared results showed a heterogeneous nature of these light NMHCs in the atmosphere. There is a strong inter-correlation among ethane, i-butane, propane, and n-butane acetylene, which supports the influence of natural gas, LPG leakage and biomass burning. Additionally, a good correlation of combustion tracer carbon monoxide (CO) with ethane, propane, and acetylene reconfirmed that biomass burning is the source of these light-NMHCs at the central Himalayas site, especially during spring. The OH reactivity, ozone formation potential (OFP) and secondary organic aerosol potential (SOAP) is also studied. The OH-reactivity is minimal at a mountain site compared to an IGP site. Propylene (25%-30) and ethylene (10-25%) strongly contributed to OH-reactivity. Both sites have maximum OFP during the winter and a minimum. The OFP during the summer/monsoon for all the seasons. Propylene (23%-35%) and ethylene (18- 22%) are species dominated by OFP throughout the year at both sites. SOAP showed wintertime maxima and springtime minima with the dominance of propylene (35%-45%) and i-butane (15%-38%) at the Himalayan site, whereas propylene (%) and n-butane (%) dominance at the IGP site. Further, these datasets can be used to develop emission inventories and validate various chemical transport models. The results from these studies are also useful for policymakers in formulating and implementing effective emission reduction strategies. 

How to cite: Rajwar, M., Naja, M., Lal, S., Venkataramani, S., Rawat, P., and Tiwari, R. K.: Light-NMHCs in the Central Himalayas and associated IGP Region: Role in Ozone and Secondary Organic Aerosols-Formation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15034, https://doi.org/10.5194/egusphere-egu23-15034, 2023.

Air pollutants are a major by-product of urbanisation and motorisation of society. In lower and upper middle-income Asian countries, in cities with rapid population growth such as Malaysia, traffic emissions are responsible for almost 90% of urban air pollution, so cycling or walking outdoor can be a major route of exposure for active commuters. Our study aims to examine the association between traffic-related air pollution and cardiorespiratory health symptoms among pedestrian and cyclists in a university campus located in Selangor, Malaysia.  PM_2.5 concentrations were monitored using SidePak Personal Aerosol Monitor AM510 on weekday morning cycling and walking commutes into designated high and low-traffic areas nearby campus roadsides. Volunteers cycled (n=21) and walked (n=30) for about 60-minutes in high and low-traffic cycling and walking routes respectively. The cardiorespiratory health status of blood pressure and lung function were measured before, immediately after, after 15 minutes and after 1 hour of volunteers’ commutes. The average commute exposure to PM_2.5 was determined, and the inhaled dosage was estimated. Results showed that pedestrian are exposed to higher PM_2.5 levels than cyclists traveling in the same high-traffic areas. However, the inhalation dose per kilometre travelled, D_L (µg/km) for cyclist was observed higher compared to the pedestrian due to the ventilation rate of physical activity. We also observed that there were increase in the systolic blood pressure and lung function (force-vital capacity-FVC) of pedestrians after the exposure to high PM_2.5 concentrations at high traffic walking routes (61.6 ± 14.6 µg/m³). PM_2.5 concentrations while walking in the university campus were approximately three times higher compared to cities in Europe (26 μg m⁻³). Our observation techniques can be applied in resource-constrained countries with heavy traffic emissions that may have an impact on the health of active commuters. To characterise the exposure patterns of other traffic-related air pollutant surrogates (such as soot/black carbon and nitrogen dioxide) and their influence on acute and chronic health outcomes in different Asian traffic microenvironments, further research based on the results of our study is needed.

How to cite: Ezani, E., Ab Razak, N. I., Uding Rangga, J., Saidi, H. I., and Dhandaphani, S.: Traffic-related Air Pollution (TRAP) and Its Exposure to Cardiorespiratory Outcomes to Active Commuters in a University Outdoor Environment, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17038, https://doi.org/10.5194/egusphere-egu23-17038, 2023.

In the coming decades, a large increase in population is expected to occur on the African continent, leading to a doubling of the current population, which will reach 2.5 billion by 2050. At the same time, the African continent is experiencing substantial economic growth. As a result, air pollution and greenhouse gas emissions will increase considerably with expected health impacts on the African population. The impact of wildfires also needs to be carefully assessed. Will the frequency of fire episodes increase? And how will this perturbation compare with anthropogenic emissions in urban areas? In the decades ahead, Africa’s contribution to climate change and air pollution will become increasingly important.  

Time has come to address the changing role of Africa in understanding and quantifying global environmental change.  What can we learn from the new TROPOMI satellite data for Africa, in combination with emerging modelling efforts including the MUSICA development at NCAR and the development of inverse modelling techniques? How can we deal with the lack of surface observations in many areas of Africa?

We will show several recent achievements related to Africa, using space observations and modeling approaches as a contribution towards the development of an integrated community effort to better characterize air quality and climate-related processes in this continent.  This presentation will mainly focus on the potential of the use of TROPOMI data for Africa Research.

How to cite: Levelt, P., Stein, D., Martinez, S.-E., Tang, W., Worden, H., Emmons, L., Gaubert, B., Eskes, H., van der A, R., and Veefkind, P.: Investigating expanding air pollution and climate change on the African continent using TROPOMI data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10385, https://doi.org/10.5194/egusphere-egu23-10385, 2023.

Quality-controlled long-term measurements of atmospheric composition are central in identifying the sources and processes that are most important for air quality in a particular environment. In South Africa, continuous measurements of various atmospheric constituents have been carried out at the Welgegund measurement station since May 2010 in close collaboration between North-West University, Finnish Meteorological Institute and University of Helsinki. Welgegund is a regionally representative continental site approx. 100 km west of Johannesburg with no local sources. Before Welgegund, measurements were operated at Marikana village, which is an urban location with large industrial point sources in the vicinity. At both sites measurements included particulate matter smaller than 10 µm in diameter (PM10), black carbon (BC) and trace gases (SO₂, NO, NO_x, O₃, CO) among others.

Numerous industrial point sources surrounding Johannesburg result in elevated NO_x and SO₂ levels in the region, but these concentrations remain below air quality standards. On the other hand, PM10 does exceed 50 µg m³ rather frequently and more often at Marikana than at Welgegund. However, strong correlation with CO suggests that the periods of elevated PM10 are related to incomplete combustion rather than the industrial emissions at both locations. At Marikana the major source appears to be domestic heating during winter time, while at Welgegund landscape fires seem more important. Also, O₃ exceeds air quality standards frequently at both sites and the highest O₃ cases appear to be linked with landscape fires. Furthermore, our observations suggest that O₃ formation is not NO_x-limited but rather VOC-limited.

How to cite: Vakkari, V., Jaars, K., Josipovic, M., Kulmala, M., Laakso, L., Petäjä, T., and van Zyl, P. G.: Air quality studies using long-term observations at Welgegund, South Africa, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8742, https://doi.org/10.5194/egusphere-egu23-8742, 2023.

Night-time oxidation significantly affects concentrations of both primary and secondary air pollutants but is poorly constrained over South Asia. Here, we investigate the chemistry, formation and abundance of Stabilized Criegee Intermediates (SCI) in the summertime air of the Indo-Gangetic Plain using measurements of its precursors and sinks. This includes ethene, propene, 1-butene, cis-2-butene, trans-2-butene, 1-pentene, cis-2-pentene, trans-2-pentene, and 1-hexene for which this work also reports the first summertime dataset from the IGP. Ethene, propene, and 1-butene were the highest ambient alkenes in both summer and winter. Morning and noon-time concentrations in summer were ~5.6 and ~3.3 times higher relative to winter, suggesting stronger alkene emission sources in summer. Applying chemical steady-state to the measured precursors, the average calculated SCI concentrations were 4.5 (± 3.8) × 10³ molecules cm^-3, with Z-CH₃CHOO (55 %) as the major SCI. SCI production rates drove ambient SCI with Z-RCHOO (35 %) and α-pinene derived PINOO (34 %) as the largest contributors to the SCI production rate of 7.8 × 10⁵ molecules cm^-3 s^-1. Peak SCI occurred during evenings. All SCI loss was dominated (>70 %) by unimolecular decomposition or reactions with water vapour. Pollution events influenced by crop biomass fires resulted in significantly elevated SCI production (2.1 times higher relative to non-polluted periods) reaching as high as (7.4 ± 2.5) × 10⁵ molecules cm^-3 s^-1. Among individual SCI species, Z-CH₃CHOO was highest in all the plume events with a contribution of at least ~41 % and among alkenes, trans-2-butene was the highest contributor to P(SCI) in plume events with values ranging from 22-32 %. SCIs dominated the night-time oxidation of sulphur dioxide with rates as high as 1.5 (± 1.3) × 10⁴ molecules cm^-3 s^-1at midnight, suggesting this pathway could be a significant source of fine mode sulphate aerosols over the Indo-Gangetic Plain, especially during summertime pollution episodes.

How to cite: Shabin, M., Kumar, A., Hakkim, H., Rudich, Y., and Sinha, V.: Stabilized Criegee Intermediates are important nocturnal oxidants in the summertime air of the Indo-Gangetic Plain., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8038, https://doi.org/10.5194/egusphere-egu23-8038, 2023.

In Thailand—the fourth most polluted nation in Southeast Asia—air pollution is estimated to take an average three years off people’s lives. While all of Thailand’s 68 million people live in areas that exceed the World Health Organization’s (WHO) guidelines for airborne fine particulate matter less than 2.5 microns (PM_2.5), Bangkok and Chiang Mai in particular (the focus of this study) are among the provinces carrying the highest health burden.

Currently, while the science behind air pollution is unequivocal, its public representation is, with official accounts perpetuating existing inequities by narrowly determining how crises are defined and selectively narrating who is impacted by them—pushing civil society voices to the fringes of public conversations on air pollution. To decenter this inequity, this study uses innovative participatory futures methods to gather civil society perspectives on the plausible, possible, and probable future solutions to air pollution and its impact on people’s health as well as social and economic implications on wellbeing. This is to ensure that civil society perspectives on solutions inform future advocacy, policy, and programmatic recommendations for addressing air pollution.

This research proposes to use modelling and air quality forecasting (the Stockholm Environment Institute’s Low Emissions Analysis Platform, Integrated Benefits Calculator) to create four sets of projections for air pollution 30 years from now (in 2053) that will then form the basis for four futures scenarios to be presented to civil society study participants as a direct form of citizen engagement.

Based on modelling results, scientists, subject matter experts, and civil society stakeholders will be engaged in online scenario-building workshops to create four futures scenarios. For instance, health, economic, political, and social implications will be generated from workshop dialogue, informed by model projections, and used to construct imaginary narratives within each of the four futures scenarios (that will then serve as the basis for the futures visioning interviews with civil society participants). Final scenarios will include depictions of social, economic, and health standards for Thai people in 2053. Once the four scenarios have been developed and stress tested, online individual participatory futures interviews will be conducted with civil society participants based in Bangkok and Chiang Mai (n=20 per city to reach an inductive thematic saturation point for primary data collection), using a blend of purposive (selective) sampling and snowball sampling methods. The University of Hawaii’s Manoa Futures Visioning Process and Krishnan’s decolonial futures/foresight framework will be employed to ensure an equitable and participant-centered approach.

Data collection and analysis will be completed by the start of the EGU General Assembly in April 2023; the AS5.13 session will be used to share experiences and lessons learned through integrating climate modelling with citizen science within this study to inform potential regional futures work within South and Southeast Asia (and beyond). Results from the study will inform the work that the Thailand Clean Air Network is doing regarding air quality policy advocacy in Thailand, among other avenues.

How to cite: Perry, K., Lulitanonda, W., Supasa, T., Junlakarn, S., and Tuladhar, B.: Climate modelling and futures scenarios: Civil society perceptions of and proposed solutions for air pollution’s effects on health and wellbeing in two Thai cities, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17264, https://doi.org/10.5194/egusphere-egu23-17264, 2023.

A small fraction (5-10 %) of PM_2.5 (fine particulate matter, with aerodynamic diameter ≤ 2.5 µm) mass constitutes trace elements (TEs) and plays an important role in controlling human health, ecological systems and air quality. TE/groups of TE are used as tracers to identify specific PM sources, predominantly due to their persistence and stability in the atmosphere. As a part of the COALESCE network ambient aerosol measurement campaign, 24-h integrated collocated PM_2.5 filter sampling was carried out for 2019 in all the three distinctly different geographical locations in India, viz., Bhopal, Mesra and Mysuru, and 15 TE concentrations were analyzed using Energy Dispersive X-Ray Fluorescence. For all sites, annual mean sulfur contributed highest (~7 %) to PM_2.5 mass among all analyzed elements followed by silicon (~3 %). Elements from multiple sources exhibited differentiable seasonal variations like crustal origin elements peaked during the pre-monsoon season, while other anthropogenic activities driven elements increased during the winter and post- monsoon seasons. Spatial heterogeneity of elements between the sites was examined using statistical tools like coefficient of divergence and spearman correlation coefficient (SCC), and revealed that they had different sources/source regions or were processed differently in the atmosphere. Further, SCC coupled with hierarchical clustering analysis categorized the data set into three common groups to yield likely sources of TEs that included crustal and mineral dust; biomass burning; non-exhaust traffic emissions and industrial sources, for all three locations. The computed dry deposition flux of both crustal (3377.41 ± 3224.65 µg m^-2 d^-1 to 27.83 ± 21.91 µg m^-2 d^-1) and non-crustal elements (53.47 ± 78.57 µg m^-2 d^-1 to 0.72 ± 0.59 µg m^-2 d^-1) was in compliance with modeled deposition flux for the entire Northern Indian Ocean and were similar to the fluxes over different regions across the globe. The United States Environment Protection Agency health risk assessment method in all sites revealed that the route of exposure of metals was highest via inhalation pathway for both adults and children, followed by dermal contact and ingestion. Total potential non-carcinogenic health risk for all pathways were below safe level (Hazard Quotient < 1) for Bhopal and Mysuru, and above safe level (Hazard Quotient > 1) for Mesra. These findings suggest that the non-carcinogenic adverse effects from multi-elemental exposure to PM_2.5 was greater in Mesra, than other two sites and might be due to influence of elemental pollutants from more dominant sources of agricultural burning and industrial activities in this region (1). On the other hand, the carcinogenic risk of all metal exposure was within acceptable limits (1×10^-6 – 1×10^-4), through all three pathways in all the sites. Overall, the multiple site analysis presented in this study provides information on spatiotemporal patterns, dry deposition fluxes of elements in ambient PM, in addition to potential human health risks upon exposure to these species.

1.Maheshwarkar, Prem, et al. "Understanding the influence of meteorology and emission sources on PM2. 5 mass concentrations across India: first results from the COALESCE network." Journal of Geophysical Research: Atmospheres 127.4 (2022): e2021JD035663.

How to cite: Haswani, D., Raman, R. S., Yadav, K., Dhandapani, A., Jawed, I., Kumar, R. N., Sanyasihally Vasanth Kumar, L. P., Yogesh, A., Murthy, S., and Lokesh, K. S.: Study of aerosol trace elements over three COALESCE network locations in India: Spatio-temporal variability, dry deposition and health risks, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6113, https://doi.org/10.5194/egusphere-egu23-6113, 2023.

Understanding polluting sources, for improving Air Quality (AQ) levels at the city/airshed level is required to solve the air pollution challenge. Scientific evidence like Emission Inventory (EI); identification of efficient technologies; implementation roadmap; and cost and resources required, are needed to develop clean air strategies.

This study considered 76 Non-Attainment (NA) cities in India, for developing EI at an airshed level. Various polluting sectors and activities were identified. Data from various sources and ground surveys were used to generate evidence. The EI was developed for the base year 2019 for 4 pollutants– Particulate Matter (PM₁₀ and PM_2.5), Sulphur dioxide (SO₂), and oxides of Nitrogen (NO_X). Based on the city EI, sector-specific technologies and control measures were identified and prioritized using Techno-Economic Assessment (TEA) and the emission reduction potential. Gap Analysis was conducted to identify sectoral targets for reducing emissions.

The Emission load varied for types of cities (tier I, II, or III) based on landscape, and anthropogenic activities. It was observed that city-level PM_2.5 emissions from three sectors - transportation (tailpipe: 30%-50%; road dust: 8%-17%); domestic (14%-30%); and Industries (6%-29%) were high for all the cities. In a few cities, heavy industries within the city boundary dominated the industrial share in the city’s total PM_2.5 emission load (34%-88%). Hence, heavy industries were excluded from the analysis to better understand the city's emission level. The study helped to understand the city vs airshed emission load. In 46% of the cities, it was found that the airshed emission load (excluding city emission) was high due to the presence of heavy industries.

Using TEA, the study estimated the associated cost of the identified control measures feasible for implementation at the city level. The required cost was based on the existing gaps in the current infrastructure needs of the city. In tier 2 cities, the transportation sector required heavy infrastructure. Capital investment, for transportation, was estimated between INR 300 – 800 Cr on measures such as a) improving public transportation, b) LNG for freight transport, and c) replacing older vehicles. However, in tier 3 cities increasing LPG connections and strategies to reduce solid fuel usage (advanced chullah’s) were found to be critical interventions, which required investment of less than 50cr. The study also carried out emission reduction scenarios till 2030. In comparison to the business-as-usual scenario, under a high emission reduction scenario, PM_2.5 emission reduction for tier 2 cities were up to 45%, and for tier 3 cities up to 54%. The study found that developing clean air strategies need to adopt an airshed approach.

How to cite: Singh, P., Banerjee, A., Kumar, U., Tiwari, A., Gautam, H., and Mishra, S.: Emission Inventories for 76 Cities In India for Clean Air Strategies, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6701, https://doi.org/10.5194/egusphere-egu23-6701, 2023.

Limited actionable data is one of the main constraints for urban local bodies and regulatory agencies to improve air quality. Emission inventories and source apportionment are important components of air quality management. However, they provide limited information about the location of pollution sources and how the sources are changing dynamically. To overcome these limitations, a field reconnaissance survey and hyperlocal monitoring through low-cost sensors were conducted for one of the hotspots in Delhi. Field reconnaissance survey helps identify and geolocate dispersed pollution sources (unpaved roads, road dust, biomass and waste burning, construction activities, etc.). The operation of the survey includes route planning, training of field surveyors, field survey, data quality control and analysis. Through the survey, 786 dispersed sources of 14 distinct types were identified. Construction and Demolition waste, potholes, road dust and garbage dumps constitute 40 % of the sources. The concerned agencies and sub-departments were mapped through consultation with stakeholders, and sources were prioritised based on factors like population density, predominant wind direction, etc. A network of low-cost sensors is also being deployed, taking the different land use categories within the hotspot into consideration to study the impact of tackling these dispersed sources. The present approach was found to be both cost as well time effective and has the potential to scale and can be used for other scientific applications like spatial bias correction in air quality models. The approach can also be used to develop targeted strategies for improving air quality and mitigating the negative impacts of air pollution on human health and the environment.

How to cite: Khan, A., Dhandapan, S., Mendiratta, S., Rafiuddin, M., Singh, P., Biswas, N., Chadha, S., Ganguly, T., and Ganeshan, K.: An Integrated approach of dispersed source mapping and hyperlocal monitoring for air quality management: A case study of hotspots in Delhi, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16373, https://doi.org/10.5194/egusphere-egu23-16373, 2023.

Nigeria is the largest country in Africa by population. Currently, the population is estimated to be 219 million making it the 7^th largest country worldwide. Demographic trends suggest that rapid population growth will lead to a population of approximately 400 million by 2050, which would make it the 3^rd largest country worldwide. 

Air quality in Nigeria is routinely reported to be poor due to both natural and anthropogenic sources of air pollution.  There are a limited number of air monitoring stations within Nigeria, and a corresponding lack of long-term air quality data, with which to assess its long-term trends. With the advent of low-cost monitoring, there has been a recent upsurge in measurements in Nigeria, but these measurement campaigns tend to short term and difficult to discern long term trends from. Nonetheless, these measurements show clearly that particulate matter (PM) air pollution regularly exceeds the WHO guidelines for both PM₁₀ and PM_2.5 size fractions, and hence PM places a high health burden upon the population.

This study uses visibility readings in Nigeria, measured since the 1950s, to study and understand historical and contemporary levels of air pollution. Visibility is related to the atmospheric extinction coefficient that is largely determined by the amount of PM in the atmosphere. New machine learning calibration techniques allow for PM_2.5 mass concentrations to be estimated directed from visibility and other meteorological measurements.  This presentation will discuss the visibility derived PM findings for the different regions of Nigeria. It will highlight trends in both regional scale and more localized sources of PM.  The implications of population growth and other socio-economic factors upon potential air quality scenarios for Nigeria will also be discussed.

How to cite: Pope, F. and Nwokorie, V.: Visibility as a proxy for air quality in Nigeria from 1950 to 2020, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4512, https://doi.org/10.5194/egusphere-egu23-4512, 2023.

Anthropogenic activities emit particulate matter (PM) and gaseous substances that are harmful. PM has adverse effects on different parts of the body. Atmospheric pollution is a global threat with an increasing social and economic costs. Poor air quality is a concern in African cities, but governments have been too slow to react, one of the reasons being the scarcity of data on different air pollutants. Instruments based on low-cost sensors and Internet of Things are being considered as solution to evaluate the concentration of different pollutants. Increasing number of manufacturers are proposing sensing devices with good accuracy. Low-cost sensors are an alternative to expensive high graded equipment. They are cheap and can be easily deployed. Here we present the IoT4AQ project. It is funded by the International Astronomical Union (IAU). The main objective is to organize training sessions for researchers and students on the design and implementation of low-cost sensors for air quality monitoring. The project will use astronomy instrumentation knowledge and skills. Participants will be trained in IoT techniques showing how to build low-cost sensors-based instruments and deploy them. The project starts on February 2023, will last for two years and trainers will be invited on various aspects of the trainings. Two hands-on trainings and two online seminars will be organized each year. The project will be implemented in Senegal and the first year will see the participation of local trainees and in the second phase it will open to participants from other African countries. Specific objectives are: (1) organize hands-on trainings and online seminars on IoT and air quality monitoring, (2) train researchers, teachers, and students on various aspects of air quality monitoring and (3) improve Physics education in Africa through low-cost sensors and IoT. Expected outcome are as follows: (1) train a minimum of 100 participants on IoT and air quality monitoring; (2) improve the experimental skills of participants; and (3) increase awareness of the threat that represents atmospheric pollution.

How to cite: Tchanche, B. and Fall, I.: Internet of Things Lab for Air Quality Monitoring, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9753, https://doi.org/10.5194/egusphere-egu23-9753, 2023.

Air pollution is a major environmental concern that affects human health worldwide. Despite recent studies indicating ambient air pollution is a growing global concern strongly linked to rapid global urbanization, little has been done to monitor the air quality levels in Africa. Traditionally, air quality monitoring has relied on environmental monitoring stations, that are expensive to build and maintain. In Kenya, for example there is no publicly available national air quality monitoring data. Thus, low-cost sensors offer a practical and cost-effective means of monitoring air quality. We carried out a study in Juja town, located in central Kenya within the outskirts of Nairobi. Juja is one of the largest growing towns and is located along the busy Thika Superhighway. The purpose of this study was to assess the diurnal and seasonal variations of Ambient Particulate Matter (PM_2.5) in Juja, Kenya. The data was collected as from November 2019 to April 2021 at JKUAT Institute of Energy and Environmental Technology (IEET) department, a residential area within Toll and Kibariti and an additional site along the busy Thika Superhighway. The PM level was measured using the Purple Air Monitoring Sensor – PA-II-SD in μg/m³ on a 24hour cycle. The PM_2.5 level from the low-cost Purple Air Sensors were later calibrated against a reference BAM-1022 to yield corrected PM values. The results revealed that the overall PM_2.5 concentration was higher during the dry season (June - August 2020) compared to March - May 2020 (wet season) where it dropped by 5-10μg/m³ on average. The average daily PM_2.5 levels were recorded at 44μg/m³ (Pine Breeze), 20μg/m³ (Toll) and 16μg/m³ (Kibariti) all exceeding the WHO guideline of 15μg/m³. JKUAT had an annual mean concentration of 15μg/m³, also exceeding the WHO guidelines of 5μg/m³. The study also found that PM_2.5 levels were highly correlated with vehicle emissions, as the site closest to the highway had the highest PM_2.5 levels. The levels also peaked twice a day at 5am and 5pm, possibly due to morning and evening traffic. It is thus evident that traffic related emissions are a great concern within the town and effective mitigation measures are needed to protect the residents. In addition, comparing the month of April 2021 to the previous year, the daily mean dropped by 5-10μg/m³ – the period of the new Covid -19 lockdown. These results can then be used to model and predict urban air quality within the town. Overall, low-cost sensors have provided an increased availability of data that can be used to identify patterns and trends in air quality over time. Their use can also facilitate greater community engagement, as individuals and organizations can participate in data collection, monitoring and analysis. To conclude, this research provides an important tool for informing urban planning and environmental policies. By understanding the sources, patterns and impacts of air pollution, decision makers can develop strategies to address these issues and improve the health and well-being of urban residents.

How to cite: Kanyeria Ndiang'ui, J., Njogu, P., and Westervelt, D.: Monitoring the Diurnal and Seasonal Variation of Ambient of Ambient Particulate Matter (PM2.5) using Low-Cost Sensors in Juja, Kenya, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3805, https://doi.org/10.5194/egusphere-egu23-3805, 2023.

High-resolution spatial maps of air pollution can be useful for air quality management. In low- and middle-income countries, regulatory measurements of criteria pollutants are typically insufficient to generate spatial maps, due to the sparsely located monitoring stations. Alternatively, high-resolution spatial maps of air pollution can be achieved by dispersion (physics-based) and statistical regression (training-based) modelling. Resolutions of up to ~25 meters can be achieved by Land Use Regression (LUR) modelling based spatial predictions. In this study, we leveraged the high density of regulatory monitors located in New Delhi, India, and developed LUR models for all the major criteria pollutants (PM₁₀, PM_2.5, SO₂, NO₂, and Ozone). New Delhi is one of the most heavily polluted cities in the world. We used data from 40 continuous ambient air quality monitoring stations’ (CAAQMS) for the year 2019 to develop seasonal and annual LUR models, following the ESCAPE (European Study of Cohorts for Air Pollution Effects) stepwise supervised regression method. Model predictors included land use parameters, road lengths, rail track lengths, population, satellite pollution, and NDVI data, along with air pollution point source location data and reanalysis meteorology. The models were validated using leave one station out (LOSO) and 10-fold cross validations (CV). The model adjusted R² values varied between 0.08 and 0.64. Particle pollutant models (PM_2.5 and PM₁₀) performed better than those of gaseous pollutants. Further, ozone models performed the least. Across seasons, summer models performed the best (least) for PM (gaseous pollutants). Models with adjusted R² were used for spatial predictions at 50-m resolution for the Delhi National Capital Territory region. Spatio-seasonal characteristics of air pollution were studied using the generated high-resolution maps.

How to cite: Upadhya, A., Kulkarni, P., Kalshetty, M., Srishti, S., Kushwaha, M., Agrawal, P., and Vakacherla, S.: Development of land use regression (LUR) models for criteria air pollutants in Delhi: Use of regulatory monitoring data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5586, https://doi.org/10.5194/egusphere-egu23-5586, 2023.