PubMed · 5954005
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Emergency exposure limits: pentaborane-9.. https://doi.org/10.1080/00028896609342815
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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.
Numerous epidemiological studies have demonstrated a positive association between ambient air pollution and adverse health effects including respiratory morbidity, asthma, and lung cancer. It has been suggested in some experimental studies that airborne particulate matter (PM) can produce inflammatory effects, but nothing is known about the possible proliferative and carcinogenic effects of these particles on cells of the lung. We show here that exposure of pulmonary epithelial cells, a cell type affected in acute lung injury, asthma, and lung carcinomas, to nontoxic concentrations of PM in vitro results in increases in c-jun kinase activity, levels of phosphorylated cJun immunoreactive protein, and transcriptional activation of activator protein-1-dependent gene expression. These changes are accompanied by elevations in numbers of cells incorporating 5'-bromodeoxyuridine, a marker of unscheduled DNA synthesis and/or cell proliferation. Data here are the first to demonstrate that interaction of ambient PM with target cells of the lung initiates a cell signaling cascade related causally to aberrant cell proliferation and carcinogenesis.
Seven independent assessments of diagnosis were obtained for 92 records of nontrauma emergency department visits in Saint John, New Brunswick, Canada, in 1994. The hospital database was 1.18 times as likely (p < 0.05) as six external physician raters to classify visits as cardiorespiratory, which was consistent for high- and low-pollution days. Kappa was 0.70 (95 percent confidence interval (CI) 0.68-0.73). Kappajs were: asthma, 0.69 (95% CI 0.64-0.73); chronic obstructive pulmonary disease, 0.78 (95% CI 0.74-0.83); respiratory infections, 0.53 (95% CI 0.49-0.57); cardiac, 0.84 (95% CI 0.79-0.88); and other, 0.66 (95% CI 0.62-0.71). Substantial or better interobserver agreement was seen, respiratory infections notwithstanding, and there was no evidence of diagnostic bias in relation to daily air pollution level.