Human exposure to indoor air pollution in Ethiopian households

Trends, seasonal variations and forecasting of chronic respiratory disease morbidity in charcoal producing areas, northwest Ethiopia: time series analysis

Objective

This study analyzed the trend, seasonal variations and forecasting of chronic respiratory disease morbidity in charcoal producing areas, northwest Ethiopia, aiming to provide evidences in planning, designing strategies, and decision-makings for preparedness and resource allocation to prevent CRD and reduce public health burden in the future.

Materials and methods

The trend, seasonal variation, and forecasting for CRD were estimated using data collected from the three zones of Amhara region annual reports of DHIS2 records. Smoothing decomposition analysis was employed to demonstrate the trend and seasonal component of CRD. The ARIMA (2, 1, 2) (0, 0, 0) model was used to forecast CRD morbidity. The model's fitness was checked based on Bayesian information criteria. The stationarity of the data was assessed with a line chart and statistically with the Ljung-Box Q-test. SPSS version 27 was utilized for statistical analysis.

Results

The annual morbidity rate of CRD has shown an increasing trend in both sexes over a seven-year period among people aged 15 years and older. Seasonal variation in CRD morbidity was observed. The smoothing decomposition analysis depicted that the seasonal component was attributed to 44.47% and 19.16% of excess CRD cases in the period between September to November, and June to August, respectively. A substantial difference among the three zones of the Amhara region in CRD morbidity rate was noted, with the highest observed in the Awi zone. Forecasting with the ARIMA model revealed that CRD-related morbidity will continue to increase from 2020 to 2030.

Conclusion

The study revealed that the CRD morbidity rate has shown an increasing trend from 2013 to 2019. Seasonal variation in the CRD morbidity rate was observed, with the highest peak from September to November. The morbidity attributed to CRD will continue to increase for the next ten years (2020-2030). Therefore, this study could potentially play a groundbreaking role. Further study is warranted to understand the risk factors and facility readiness through a further understanding of seasonality and future trends.

Exposure of school children to particulate matter and inorganic gaseous pollutants in Hawassa city, Ethiopia

The detrimental consequences of air pollution on people, particularly vulnerable groups like children, have drawn a lot of attention globally. Studies on the levels and sources of particulate matter (PM2.5 and PM10) and inorganic gaseous pollutants (NO2, CO, and SO2) in primary schools in Africa, including Ethiopia, are scanty. Therefore, the objective of this study was to determine the levels of particulate matter and inorganic gaseous pollutants in primary schools in Hawassa, Ethiopia, and assess potential health risks. The levels of PM2.5 and PM10 were determined using a portable gas monitor device (HoldPeak Laser PM meter, HP 5800D), whereas NO2, CO, and SO2 levels were determined using the Aeroqual Series 500 Portable Air Quality Monitor (Aeroqual Ltd., New Zealand). The levels of PM2.5, PM10, and NO2 in all sampling sites ranged from 11-66.3, 30.8-399.7, and 60.5-152 µg/m3, respectively. The levels of PM2.5 and PM10 were found to be above the World Health Organization recommendations in 55% and 85% of the sampling sites, respectively. The hazard quotient (HQ) values for PM10 and PM2.5 ranged from 0.3 to 3.2 and 0.2 to 1.1, respectively. The Air Quality Index (AQI) at 40% and 30% of the outdoor sampling sites was unhealthy for sensitive groups due to exposure to PM2.5 and PM10, respectively. The levels of PM2.5 and PM10, as well as the AQI and HQ values, indicate a poor condition of the air in the schools, especially in the schools near busy traffic roads.

Household Air Pollution Related to Housing Characteristics and Cooking Conditions in Jimma Town, Ethiopia

Background

Globally, a substantial burden of disease is attributable to environmental risk factors including indoor air pollution. Nearly half of the world's population relies on solid fuel. Almost all (98.8%) residents in Ethiopia are dependent on biomass fuel as their basic source of energy for cooking. Thus, we set out to quantify the concentration of indoor air pollutants and household exposures in different housing characteristics and cooking conditions.

Methods

A survey was conducted in 280 randomly selected households in Jimma town, Ethiopia. A real-time concentration of fine particulate matters (PM2.5, PM10) and pollutants including carbon monoxide (CO), carbon dioxide (CO2), and volatile organic compounds (VOC) were measured using Laser PM2.5 Meter-5800D/5800E and Aeroqual's TM series 500 portable air quality monitors. Data on housing characteristics, kitchen configuration, and ventilation status were collected using observation checklist.

Results

The median concentrations of pollutants in all measured households were PM2.5; 294 µg/m3, PM10; 270 µg/m3, CO2; 577 mg/m3, CO; 7.9 mg/m3, and VOC; 1077 mg/m3. Households that used solid fuels had significantly higher concentration of PM2.5 (U = 53.0, p < 0.001), PM10 (U =63.0, p < 0.001),CO2 (U = 3519.50, p < 0.001), and CO (U = 3246.0, p < 0.001) than households that used clean fuel.

Conclusions

All households in this study were exposed to high concentration of indoor air pollutants that exceeded WHO's air quality standard Effective strategy should be put in place to reduce the emission of air pollutants and to set air quality management and improvements policy.

Assessment of the health impacts of air pollution exposure in East African countries

The health effects of air pollution remain a public concern worldwide. Using data from the Global Burden of Disease 2019 report, we statistically analyzed total mortality, disability-adjusted life years (DALY), and years of life lost (YLL) attributable to air pollution in eight East African countries between 1990 and 2019. We acquired ambient ozone (O3), PM2.5 concentrations and household air pollution (HAP) from the solid fuel from the State of Global Air report. The multilinear regression model was used to evaluate the predictability of YLLs by the air pollutants. We estimated the ratio rate for each health burden attributable to air pollution to compare the country's efforts in the reduction of air pollution health burden. This study found that the total number of deaths attributable to air pollution decreased by 14.26% for 30 years. The drop came from the reduction of 43.09% in mortality related to Lower Respiratory tract Infection (LRI). However, only five out of eight countries managed to decrease the total number of deaths attributable to air pollution with the highest decrease observed in Ethiopia (40.90%) and the highest increase in Somalia (67.49%). The linear regression model showed that HAP is the pollutant of the most concern in the region, with a 1% increase in HAP resulting in a 31.06% increase in regional YLL (R2 = 0.93; p < 0.05). With the increasing ground-level ozone, accompanied by the lack of adequate measures to reduce particulate pollutants, the health burdens attributable to air pollution are still a threat in the region.

Carbon monoxide as an indicator of indoor air quality

Carbon monoxide is a priority pollutant that is suitable as an indicator for assessing indoor air quality. Monitoring should preferably be embedded in an intelligent network of different sensors.

Kitchen fine particulate matter (PM2.5) concentrations from biomass fuel use in rural households of Northwest Ethiopia

Background

Combustion of solid biomass fuels using traditional stoves which is the daily routine for 3 billion people emits various air pollutants including fine particulate matter which is one of the widely recognized risk factors for various cardiorespiratory and other health problems. But, there is only limited evidences of kitchen PM2.5 concentrations in rural Ethiopia.

Objective

This study is aimed to estimate the 24-h average kitchen area concentrations of PM2.5 and to identify associated factors in rural households of northwest Ethiopia.

Method

The average kitchen area PM2.5 concentrations were measured using a low-cost light-scattering Particle and Temperature Sensor Plus (PATS+) for a 24-h sampling period. Data from the PATS+ was downloaded in electronic form for further analysis. Other characteristics were collected using face-to-face interviews. Independent sample t-test and one-way analysis of variance were used to test differences in PM2.5 concentrations between and among various characteristics, respectively.

Result

Mixed fuels were the most common cooking biomass fuel. The 24-h average kitchen PM2.5 concentrations was estimated to be 405 μg/m3, ranging from 52 to 965 μg/m3. The average concentrations were 639 vs. 336 μg/m3 (p < 0.001) in the thatched and corrugated iron sheet roof kitchens, respectively. The average concentration was also higher among mixed fuel users at 493 vs. 347 μg/m3 (p = 0.042) compared with firewood users and 493 vs. 233 μg/m3 (p = 0.007) as compared with crop residue fuel users. Statistically significant differences were also observed across starter fuel types 613 vs. 343 μg/m3 (p = 0.016) for kerosene vs. dried leaves and Injera baking events 523 vs. 343 μg/m3 (p < 0.001) for baked vs. not baked events.

Conclusion

The average kitchen PM2.5 concentrations in the study area exceeded the world health organization indoor air quality guideline value of 15 μg/m3 which can put pregnant women at greater risk and contribute to poor pregnancy outcomes. Thatched roof kitchen, mixed cooking fuel, kerosene fire starter, and Injera baking events were positively associated with high-level average kitchen PM2.5. concentration. Simple cost-effective interventions like the use of chimney-fitted improved stoves and sensitizing women about factors that aggravate kitchen PM2.5 concentrations could reduce kitchen PM 2.5 levels in the future.