PubMed · 16632106
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A Grimfeld, J Just. 2006-04-03. [Pollution and allergy].. https://doi.org/10.1016/j.revmed.2006.03.009
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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.
In this article we consider the interpretation of regression parameters used to represent 'chronic' or 'long-term' air pollution exposure effects. Although scientific interest typically lies in understanding such effects at the level of the individual, studies have generally employed a semi-ecological design; outcomes and confounder information are collected on individuals while exposure is only available at the aggregate-or group-level. A precise interpretation of results from a semi-ecological design must take into account the aggregated nature, both spatial and temporal, of the exposure measure. The most common analysis approach for assessing chronic exposure effects has been within the Cox proportional hazards model framework; specific analyses are tailored to accommodate the shortcomings of the available exposure information. We revisit the underlying assumptions of the Cox model and discuss the implications of two common aspects of chronic effects studies: time-dependent exposures and time-varying effects. Focusing on the consequences of temporal aggregation of exposure, we show that an estimate obtained from a time-aggregated semi-ecological design can correspond to very different underlying time-varying exposure and risk scenarios. Further, distinguishing which of these is correct is not possible from the semi-ecological data alone. Our goal is to highlight some statistical issues faced by existing studies of chronic air pollution effects, and aid in the development and planning of future studies.
Biofiltration of malodorous reduced sulphur compounds such as hydrogen sulphide has been confined to emissions that are at temperatures below 40 degrees C despite the fact that there are many industrial emissions (e.g. in the pulp and paper industry) at temperatures well above 40 degrees C. This paper describes our study on the successful treatment of hydrogen sulphide gas at temperatures of 40, 50, 60 and 70 degrees C using a microbial community obtained from a hot spring. Three biotrickling filter (BTF) systems were set up in parallel for a continuous run of 9 months to operate at three different temperatures, one of which was always at 40 degrees C as a mesophilic control and the other two were for exploring high-temperature operation up to 70 degrees C. The continuous experiment and a series of batch experiments in glass bottles (250 ml) showed that addition of glucose and monosodium glutamate enhanced thermophilic biofiltration of hydrogen sulphide gas and a removal rate of 40 g m(-3) h(-1) was achieved at 70 degrees C. We suggest that the glucose is acting as a carbon source for the existing microbial community in the BTFs, whereas glutamate is acting as a compatible solute. The use of such organic compounds to enhance biodegradation of hydrogen sulphide, particularly at high temperatures, has not been demonstrated to our knowledge and, hence, has opened up a range of possibilities for applying biofiltration to hot gas effluent.