Land use regression for spatial distribution of urban particulate matter (PM10) and sulfur dioxide (SO2) in a heavily polluted city in Northeast China

Particulate material 10 μm (PM₁₀) and sulfur dioxide (SO₂) are representative air pollutants in Northeast China and may contribute more to the morbidity of respiratory and cardiovascular disease than may other pollutants. Up to now, there have been few studies on the relation between health effect and air pollution by PM₁₀ and SO₂ in Northeast China, which may be due to the lack of a model for determination of air pollution exposure. For the first time, we used daily concentration data and influencing factors (different type of land use, road length and population density, and weather conditions as well) to develop land use regression models for spatial distribution of PM₁₀ and SO₂ in a central city in Northeast China in both heating and non-heating months. The final models of SO₂ and PM₁₀ estimation showed good performance (heating months: R² = 0.88 for SO₂, R² = 0.88 for PM₁₀; non-heating months: R² = 0.79 for SO₂; R² = 0.87 for PM₁₀). Estimated concentrations of air pollutants were more affected by population density in heating seasons and land use area in non-heating seasons. We used the land use regression (LUR) models developed to predict pollutant levels in nine districts in Shenyang and conducted a correlation analysis between air pollutant levels and hospital admission rates for childhood asthma. There were high associations between asthma hospital admission rates and air pollution levels of SO₂ and PM₁₀, which indicated the usability of the LUR models and the need for more concern about the health effects of SO₂ and PM₁₀ in Northeast China. This study may contribute to epidemiological research on the relation between air pollutant exposure and typical chronic disease in Northeast China as well as providing the government with more scientific recommendations for air pollution prevention.