Measurement report: Characterization and source apportionment of coarse particulate matter in Hong Kong: Insights into the constituents of unidentified mass and source origins in a coastal city in southern China

Coarse particulate matter (i.e., PM with aerodynamic diameter between 2.5 and 10 micrometers or PMcoarse) has been increasingly recognized of its importance in PM10 regulation because of its growing proportion in PM10 and the accumulative evidence for its adverse health impact. In this work, we present comprehensive PMcoarse speciation results obtained through a one-year long (January 2020–February 2021) joint PM10 and PM2.5 chemical speciation study in Hong Kong, a coastal and highly urbanized city in southern China. The annual average concentration of PMcoarse is 14.9 ± 8.6 μg m–3 (±standard deviation), accounting for 45 % of PM10 (32.9 ± 18.5 μg m–3). The measured chemical components explain ~75 % of the PMcoarse mass. The unexplained part is contributed by unmeasured geological components and residue liquid water content, supported by analyses by positive matrix factorization (PMF) and the thermodynamic equilibrium model ISORROPIA II. The PMcoarse mass is apportioned to four sources resolved by PMF, namely soil dust, copper-rich dust, fresh sea salt, and an aged sea salt factor containing secondary inorganic aerosols (mostly nitrate). Back-trajectory cluster analysis reveals significant variations in source contributions with the air mass origin. Under the influence of marine air mass, PMcoarse is the lowest (average = 8.0 μg m–3) and sea salt is the largest contributor (47 %), followed by the two dust factors (38 % in total). When the site receives air mass from the northern continental region, PMcoarse increased substantially to 21.2 μg m–3, with the two dust factors contributing 90 % of the aerosol mass. The potential dust source areas are mapped using the Concentration-Weighted Trajectory technique, showing either the Greater Bay Area or the greater part of southern China as the origin of fugitive dust emissions leading to elevated ambient PMcoarse loadings in Hong Kong. This study, first of this kind in our region, provides highly relevant guidance to other locations with similar monitoring needs. Additionally, the study findings point to the needs for further research on the sources, transport, aerosol processes, and health effects of PMcoarse.

Size-Specific Particulate Matter Associated With Acute Lower Respiratory Infection Outpatient Visits in Children: A Counterfactual Analysis in Guangzhou, China

The burden of lower respiratory infections is primarily evident in the developing countries. However, the association between size-specific particulate matter and acute lower respiratory infection (ALRI) outpatient visits in the developing countries has been less studied. We obtained data on ALRI outpatient visits (N = 105,639) from a tertiary hospital in Guangzhou, China between 2013 and 2019. Over-dispersed generalized additive Poisson models were employed to evaluate the excess risk (ER) associated with the size-specific particulate matter, such as inhalable particulate matter (PM10), coarse particulate matter (PMc), and fine particulate matter (PM2.5). Counterfactual analyses were used to examine the potential percent reduction of ALRI outpatient visits if the levels of air pollution recommended by the WHO were followed. There were 35,310 pneumonia, 68,218 bronchiolitis, and 2,111 asthma outpatient visits included. Each 10 μg/m3 increase of 3-day moving averages of particulate matter was associated with a significant ER (95% CI) of outpatient visits of pneumonia (PM2.5: 3.71% [2.91, 4.52%]; PMc: 9.19% [6.94, 11.49%]; PM10: 4.36% [3.21, 5.52%]), bronchiolitis (PM2.5: 3.21% [2.49, 3.93%]; PMc: 9.13% [7.09, 11.21%]; PM10: 3.12% [2.10, 4.15%]), and asthma (PM2.5: 3.45% [1.18, 5.78%]; PMc: 11.69% [4.45, 19.43%]; PM10: 3.33% [0.26, 6.49%]). The association between particulate matter and pneumonia outpatient visits was more evident in men patients and in the cold seasons. Counterfactual analyses showed that PM2.5 was associated with a larger potential decline of ALRI outpatient visits compared with PMc and PM10 (pneumonia: 11.07%, 95% CI: [7.99, 14.30%]; bronchiolitis: 6.30% [4.17, 8.53%]; asthma: 8.14% [2.65, 14.33%]) if the air pollutants were diminished to the level of the reference guidelines. In conclusion, short-term exposures to PM2.5, PMc, and PM10 are associated with ALRI outpatient visits, and PM2.5 is associated with the highest potential decline in outpatient visits if it could be reduced to the levels recommended by the WHO.

Predicting Lung Cancer in the United States: A Multiple Model Examination of Public Health Factors

In this research, we take a multivariate, multi-method approach to predicting the incidence of lung cancer in the United States. We obtain public health and ambient emission data from multiple sources in 2000–2013 to model lung cancer in the period 2013–2017. We compare several models using four sources of predictor variables: adult smoking, state, environmental quality index, and ambient emissions. The environmental quality index variables pertain to macro-level domains: air, land, water, socio-demographic, and built environment. The ambient emissions consist of Cyanide compounds, Carbon Monoxide, Carbon Disulfide, Diesel Exhaust, Nitrogen Dioxide, Tropospheric Ozone, Coarse Particulate Matter, Fine Particulate Matter, and Sulfur Dioxide. We compare various models and find that the best regression model has variance explained of 62 percent whereas the best machine learning model has 64 percent variance explained with 10% less error. The most hazardous ambient emissions are Coarse Particulate Matter, Fine Particulate Matter, Sulfur Dioxide, Carbon Monoxide, and Tropospheric Ozone. These ambient emissions could be curtailed to improve air quality, thus reducing the incidence of lung cancer. We interpret and discuss the implications of the model results, including the tradeoff between transparency and accuracy. We also review limitations of and directions for the current models in order to extend and refine them.