Health risk assessment and source apportionment of PM2.5-bound toxic elements in the industrial city of Siheung, Korea.

The emission sources and their health risks of fine particulate matter (PM2.5) in Siheung, Republic of Korea, were investigated as a middle-sized industrial city. To identify the PM2.5 sources with error estimation, a positive matrix factorization model was conducted using daily mean speciated data from November 16, 2019, to October 2, 2020 (95 samples, 22 chemical species). As a result, 10 sources were identified: secondary nitrate (24.3%), secondary sulfate (18.8%), traffic (18.8%), combustion for heating (12.6%), biomass burning (11.8%), coal combustion (3.6%), heavy oil industry (1.8%), smelting industry (4.0%), sea salts (2.7%), and soil (1.7%). Based on the source apportionment results, health risks by inhalation of PM2.5 were assessed for each source using the concentration of toxic elements portioned. The estimated cumulative carcinogenic health risks from the coal combustion, heavy oil industry, and traffic sources exceeded the benchmark, 1E-06. Similarly, carcinogenic health risks from exposure to As and Cr exceeded 1E-05 and 1E-06, respectively, needing a risk reduction plan. The non-carcinogenic risk was smaller than the hazard index of one, implying low potential for adverse health effects. The probable locations of sources with relatively higher carcinogenic risks were tracked. In this study, health risk assessment was performed on the elements for which mass concentration and toxicity information were available; however, future research needs to reflect the toxicity of organic compounds, elemental carbon, and PM2.5 itself.

Social inequality, noise pollution, and quality of life of slum dwellers in Pokhara, Nepal.

This work is a cross-sectional comparative study conducted on 528 residents in the slum and non-slum areas of Pokhara, Nepal. Of the total number of respondents, 90.2% in the slums and 63.3% in the non-slums indicated the existence of a main source of noise, and 80.7% in the slums and 66.0% in the non-slums replied that they had been highly annoyed by noise. The indoor noise levels measured for 24 h were higher in slums than in non-slums, ranging from 59 to 78 dBA and from 51 to 69 dBA, respectively. The Mann-Whitney U test showed a significantly poorer status of slum dwellers in four health domains. Logistic regression analysis identified that living in a slum was a significant predictor (OR, 2.35; 95% CI, 1.35-4.09) of a low level of health. Meanwhile, a high level of noise annoyance was a good determinant (OR, 6.71; 95% CI, 3.13-14.36) of low quality of life among slum dwellers revealing a distinguishing negative effect of the high level of noise annoyance in the slum areas.