air quality Archives - Resilient Landscapes (RL)

Biomass fuel consumption and indoor air pollution from cooking appliances in refugee settings

Background
Indoor air pollution from reliance on firewood and charcoal remains a major health and environmental challenge in refugee and host communities. Although energy-efficient cooking technologies have the potential to reduce biomass fuel consumption and indoor air pollution, the comparative performance of different technologies under real-household conditions remains limited.

Objective
A study was conducted to quantify household cooking energy consumption and the resulting gas and particle concentrations from selected cooking technologies.

Methods
The study evaluated three cooking stoves: the Three-stone open fire, Lorena, and Traditional metallic stove (TMS), using firewood, charcoal, and briquettes. Eighteen cooking tests measured carbon monoxide (CO), carbon dioxide (CO2), fine particulate matter (PM₂.₅), fuel consumption, and cooking time.

Results
Firewood enabled the fastest cooking, while briquettes with the Lorena stove required twice the cooking time. The Lorena stove consumed slightly more firewood and substantially more briquettes than the TMS, but was more efficient with charcoal. CO levels when using firewood exceeded the World Health Organization (WHO) 1-hour guideline by 61% (Three-stone open fire) and 153% (Lorena), while briquettes remained within limits. Both ambient and cooking-related CO₂ concentrations remained below the Occupational Safety and Health Administration’s (OSHA) permissible exposure limit, whereas ambient PM₂.₅ concentrations averaged 28 µg/m³ , exceeding WHO air quality guidelines.

Conclusions
The study found context-dependent performance variations, challenging the assumption that improved cooking technologies are universally effective. Despite reducing cooking-related pollutants, briquettes and the Lorena stove alone cannot address elevated ambient PM₂.₅ levels, highlighting the need for integrated air quality interventions.

Air–Noise Pollution Linkages: Testing Innovative Community-Based Adaptation and Mitigation Strategies in Kenya

This case study was conducted in healthcare facilities in Kilifi and Nairobi to explore how environmental monitoring can address the mental health needs of vulnerable perinatal adolescents. Outdoor air quality sensors were installed at Kangemi and Kariobangi North health centers in Nairobi, and Mtwapa and Vipingo health centers in Kilifi, as well as in two households of perinatal adolescents. Community health workers collected air quality, noise exposure, and experiential data on stress and mood. Findings revealed site‑specific variations in PM2.5 concentrations, with Kariobangi recording the highest mean (29.45 µg/m³), far exceeding WHO’s 2021 guideline of 5 µg/m³. Noise monitoring showed consistently elevated exposure, with Kangemi averaging 52.2 dB, surpassing WHO’s recommended hospital threshold (less than 35-40 dB). Household monitoring highlighted operational challenges, including sensor deployment constraints and intra‑day variability. The study demonstrates that air and noise monitoring can strengthen health systems and improve patient care, but emphasizes the need for both mitigation (reducing pollution sources) and adaptation (coping strategies) to protect vulnerable populations.

Effects of smoke haze on respiratory clinic visits in Central Kalimantan, Indonesia according to different haze characteristics

Background: Smoke haze is a common air-pollution issue in Southeast Asia. Studies have suggested an elevated respiratory risk due to smoke-haze exposure. However, relevant studies have applied different exposure assessments in addressing haze effects and there is no unified definition of haze due to differences in its characteristics by location. The present study aimed to examine the effects of haze on respiratory health outcomes by analysing local fire activity and duration. Methods: Data for daily respiratory visits in Central Kalimantan were collected at local primary healthcare centers (‘puskesmas’) during the period spanning 2015–2019, encompassing two major haze episodes in the region. Particulate matter with aerodynamic diameter <10μm and fire hotspot counts were used to determine haze days, including fire-haze and non-fire-haze days. A space-time-stratified case-crossover design was used through a conditional quasi-Poisson regression model to examine the effects of haze vs. non-haze days in each subdivision, with lags of up to five days, for different haze definitions and durations. Results: The risk of respiratory visits was prominent during haze days but varied by haze characteristics. There was a 36.6% (95% confidence interval: 10.2%, 69.3%) and 74.4% (18.9%, 164.6%) increased risk of respiratory visits in Pulang Pisau Regency during haze and fire haze, respectively. The risk was pronounced when the haze was characterized by longer durations. Conclusion: Our findings suggest inconclusive effects of haze on respiratory visits to primary healthcare centers, although they appeared to be prominent in the area mainly dominated by fire haze. Haze characteristics should be analysed carefully for differences in risk patterns according to location.

Assessing the spatial distribution of aerosols and air quality over the Ganga River basin during COVID-19 lockdown phase-1

The present study aims to analyze the variations in aerosol optical depth (AOD), black carbon (BC), organic carbon (OC), sulfate (SO4), dust, sea salt, fine mode dust and sea salt, and air quality over the Ganga River basin (GB), during the nation-wise lockdown phase-1 due to the outbreak of COVID-19. The aerosol data have been obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) and Modern-Era Retrospective analysis for Research and Applications (MERRA-2) for the lockdown phase-1 (March 25 – April 15, 2020) and its corresponding average of the reference period (2001-2019). The total PM2.5 has been modeled over the GB based on the inputs from MERRA-2. The in-situ air quality index (AQI) values from cities across the GB have been obtained during pre-lockdown (February, 29 – March 20, 2020) and lockdown phase-1 period to evaluate changes. Non-parametric pairwise comparison is performed to evaluate the significant change in the pollutants including AOD, and quantile regression is used to explore the effect of meteorology on AOD and other pollutants. The results show a significant reduction (p ≤ 0.05) in AOD, BC, OC, SO4, dust, dust particulate matter (PM2.5), sea salt, sea salt PM2.5, and estimated total PM2.5 during the lockdown phase-1 with respect to the reference period. The analysis also reveals that meteorological factors do not play a vital role in the reduction of AOD during the lockdown phase-1 period. The estimated reductions for AOD, BC, OC, SO4, dust, dust PM2.5, sea salt, and sea salt PM2.5 are 33%, 21%, 24%, 20%, 18%, 17%, 64%, and 61%, respectively due to imposition of lockdown measures. As many as 28 cities in the GB have shown substantial improvement in the air quality during the lockdown phase-1 period. The reduction in the emission quantity and subsequent improvement in AQI has opened up a new discourse for combatting the persistent air quality issues for million-plus cities in particular and for the north Indian plain in general. The findings of this study thus provide insightful views to the environmentalists and policymakers for framing better emission policy to deal with the air quality issue.

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