PubMed · 11579935
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H M Seip, K Aunan, H Vennemo, J Fang. 2001-09-28. Mitigating GHGs in developing countries.. https://doi.org/10.1126/science.293.5539.2391b
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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.
The objective of this research was to evaluate the reaction characteristics of CaOH2, HCl and SO2 in the flue gas emitted by a laboratory incinerator. The amount of sulfur retained in the residues (including the spray dryer ash and baghouse ash) was also evaluated in this study. The experimental parameters included HCl concentration (500-2000 ppm), SO2 concentration (500-2000 ppm), relative humidity (40-80% RH), and the addition of CaCl2 (30 wt.%). The results indicated that an HCl concentration of 500-2000 ppm did not affect HCl removal efficiency in the spray dryer at 150 degrees C and 45+/-5% RH. On the other hand, increase in SO2 concentration from 500 to 2000 ppm enhanced SO2 removal at 150 degrees C and 75+/-5% RH. Moreover, increase in removal efficiency of SO2 was more obvious when the relative humidity was greater than 80%. When the flue gas contained both HCl and SO2 simultaneously, the removal efficiency of SO2 could increase from 56.7 to 90.33% at HCl concentration of 236 ppm. However, when the concentration of HCl exceeded 535 ppm, the removal efficiency of SO2 decreased with increasing concentration of HCl. The removal efficiency of SO2 could be increase to 97.7% with the addition of CaCl2.
The Poisson process approach for studying the association between environmental covariates and recurrent events depends on the stratification of study period into intervals within which the baseline intensities are assumed constant. In this work we investigate the problem of bias and variance due to misspecification of this stratification. We suggest a cross-validation approach to choosing a stratification model to balance the trade-off between bias and variance. We also establish a connection between the Poisson process approach and case cross-over studies.