Risk of COPD due to indoor air pollution from biomass cooking fuel: a systematic review and meta-analysis.

Chronic obstructive pulmonary disease (COPD) is one of the leading causes of mortality in developing nations. In this meta-analysis, we aimed to determine the association between indoor air pollution and risk of COPD. Database searches were conducted using indoor air pollution, biomass and COPD related terms to identify relevant articles. The eligible studies were case-control, retrospective cohort, cross-sectional studies and conducted in adults that assessed COPD using any diagnostic criteria. A total of 35 studies with 73,122 participants were included. The pooled analysis showed that exposure to indoor air pollution due to solid biomass fuels increased risk of COPD by 2.65 (95% confidence interval [CI] 2.13-3.31; n = 73,122) and chronic bronchitis by 2.89 (95% CI 2.18-3.82) times more compared to non-biomass fuels. The risk of COPD was higher in Africa region (odds ratio [OR] 3.19), Asia (OR 2.88), South America (OR 2.15), Europe (OR 2.30) and North America (OR 2.14). The results of our meta-analysis indicated that exposure to indoor air pollution due to biomass smoke is strongly associated with COPD.Abbreviations: CS: cross-sectional; CC: case-control; NR: not reported; ATS: American Thoracic Society; BMRC: British Medical Research Council; GOLD: Global Initiative for Obstructive Lung Disease; IAP: indoor air pollution; BMF: biomass fuel; CB: chronic bronchitis; OR: odds ratio; UCI; upper confidence interval; LCI: lower confidence interval; COPD: chronic obstructive pulmonary disease.

Chemical characteristics and source apportionment of PM2.5 using PCA/APCS, UNMIX, and PMF at an urban site of Delhi, India.

The present study investigated the comprehensive chemical composition [organic carbon (OC), elemental carbon (EC), water-soluble inorganic ionic components (WSICs), and major & trace elements] of particulate matter (PM2.5) and scrutinized their emission sources for urban region of Delhi. The 135 PM2.5 samples were collected from January 2013 to December 2014 and analyzed for chemical constituents for source apportionment study. The average concentration of PM2.5 was recorded as 121.9 ± 93.2 µg m-3 (range 25.1-429.8 µg m-3), whereas the total concentration of trace elements (Na, Ca, Mg, Al, S, Cl, K, Cr, Si, Ti, As, Br, Pb, Fe, Zn, and Mn) was accounted for ∼17% of PM2.5. Strong seasonal variation was observed in PM2.5 mass concentration and its chemical composition with maxima during winter and minima during monsoon seasons. The chemical composition of the PM2.5 was reconstructed using IMPROVE equation, which was observed to be in good agreement with the gravimetric mass. Source apportionment of PM2.5 was carried out using the following three different receptor models: principal component analysis with absolute principal component scores (PCA/APCS), which identified five major sources; UNMIX which identified four major sources; and positive matrix factorization (PMF), which explored seven major sources. The applied models were able to identify the major sources contributing to the PM2.5 and re-confirmed that secondary aerosols (SAs), soil/road dust (SD), vehicular emissions (VEs), biomass burning (BB), fossil fuel combustion (FFC), and industrial emission (IE) were dominant contributors to PM2.5 in Delhi. The influences of local and regional sources were also explored using 5-day backward air mass trajectory analysis, cluster analysis, and potential source contribution function (PSCF). Cluster and PSCF results indicated that local as well as long-transported PM2.5 from the north-west India and Pakistan were mostly pertinent.