PubMed · 14232149
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P J LAWTHER. 1965. AIR POLLUTION.. https://pubmed.ncbi.nlm.nih.gov/14232149/
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Capturing the spatiotemporal distribution of pollutants in industrial parks remains challenging for regional air quality models because of their coarse resolution (3 km), resulting in uncertainties in local emission quantification. To address this, we developed the Integrated Multiscale Air Quality Modelling System for Industry (IAQMS-Industry), coupling the regional Nested Air Quality Prediction Modelling System (NAQPMS) with a city-scale chemical transport model. This framework integrates point-source locations and Gaussian plume dispersion to simulate particulate matter with a diameter smaller than 2.5 micrometres (PM2.5) at 100 m resolution. Applied to the Beijing Yi Zhuang and Tangshan industrial parks and evaluated against observations. The coupled model achieved a normalized mean bias (NMB) ranging from 3.1 % to 6.2 %, improving upon NAQPMS (-16.9 % to -7.7 %). Spatial analysis revealed that coarse regional grids underestimated the PM2.5​ concentrations at industrial sites by smoothing gradients, whereas IAQMS-Industry successfully resolved spatial patterns. Industrial point emissions accounted for 22.9 %-26.4 % of PM2.5 in the coupled model, which was significantly greater than the regional model estimates of 1.6 %-13.7 %. These findings indicate that regional models overestimate pollutant dispersion processes in industrial parks while underestimating local industrial impacts. By explicitly resolving point-source dynamics and linking them to regional transport, IAQMS-Industry provides a robust tool for designing targeted emission controls in industrial cities and balancing local air quality improvements with minimized regional pollution outflow. This study underscores the necessity of multiscale modelling for accurate source apportionment and informed environmental governance in industrial zones.
BACKGROUND AND PURPOSE: Many studies have reported increases in daily cardiovascular mortality and hospital admissions associated with increases in levels of air pollutants. However, little is known about the relationship between hospital admissions for stroke and air pollution. This study was undertaken to determine whether there is an association between air pollution and hospital admissions for stroke in Kaohsiung, Taiwan. METHODS: Data on a total of 23 179 stroke admissions were obtained for the period 1997 through 2000. The relative risk of hospital admissions was estimated with a case-crossover approach. RESULTS: In the single-pollutant models, on warm days (> or =20 degrees C), significant positive associations were found between levels of PM10, NO2, SO2, CO, and O3 and both primary intracerebral hemorrhage and ischemic stroke admissions. On cool days (<20 degrees C), only CO levels and ischemic stroke admissions were significantly associated. For the 2-pollutant models, PM10 and NO2 remained consistently and significantly associated with admissions for both types of stroke on warm days. We observed estimated relative risks of 1.54 (95% confidence interval [95%], 1.31 to 1.81) and 1.56 (95% CI, 1.32 to 1.84) for primary intracerebral hemorrhage for each interquartile range increase in PM10 and NO2. The values for ischemic stroke were 1.46 (95% CI, 1.32 to 1.61) and 1.55 (95% CI, 1.40 to 1.71), respectively. The effects of CO, SO2, and O3 were mostly nonsignificant when either NO2 or PM10 was controlled for. CONCLUSIONS: This study provides an association between exposure to air pollution and hospital admissions for stroke.
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