An enhanced integrated approach to knowledgeable high-resolution environmental quality assessment

Abstract

Sustaining urban environmental quality requires effective policy measures that integrate local monitoring and contextualized high-resolution modelling with actionable scenarios. Knowledgeable decision making in this field can nowadays be supported by an array of atmospheric models, but their transfer into an Integrated Urban hydrometeorological, climate and environmental Services (IUS) remains challenging. Methodological aspects that are beyond pure technicalities of the model-to-model coupling are still poorly explored. Modeling downscaling chains lack their most user-relevant link – urban-to-neighborhood scale observations and models. This study looks at a socio-environmental context of the high-resolution atmospheric modeling in the case study of the Arctic urban cluster of Apatity and Kirovsk, Russia. We demonstrate that atmospheric dynamics of the lowermost, turbulent air layers is highly localized during the most influential episodes of atmospheric pollution. Urban micro-climates create strong circulations (winds) that are sensitive to the local environmental context. As the small-scale turbulence dynamics is not spatially resolved in meteorological downscaling or statistical modeling, capturing this local context requires specialized turbulence-resolving (large-eddy simulation) models. Societal acceptance of the urban modeling could be increased in the IUS with horizontally integrated modeling driven by localized scenarios. This study presents an enhanced integrated approach, which incorporates a large-eddy simulation model PALM into meteorological downscaling chains of a climate model (EC-EARTH), a numerical weather prediction – atmospheric chemical transport model (ENVIRO-HIRLAM) and a regional-scale meteorological model (COSMO-CLM). We discuss how this approach could be further developed into an environmental component of a digital “smart city”.