Breaking the isothermal assumption in CFD air quality modeling: Solar irradiance effects on the wind velocity-concentration relationship

IF 13.3 1区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY
Sustainable Cities and Society Pub Date : 2026-02-01 Epub Date: 2026-01-09 DOI:10.1016/j.scs.2026.107135
Nicolas Reiminger , Cédric Wemmert , Loïc Maurer , José Vazquez , Xavier Jurado
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Abstract

This study examines how far solar irradiations modify the wind velocity–concentration relationship commonly used in isothermal computational fluid dynamics (CFD) modeling of urban air quality. The main aim is to evaluate the validity under non-isothermal conditions of this widely used relationship and to provide new insights into the influence of solar-induced thermal effects on urban pollutant dispersion. While this relationship enables long-term concentration estimates through extrapolation from a limited set of simulations—thus offering strong operational advantages—its validity under non-isothermal conditions remains untested. Yet, recent regulatory changes and empirical evidence increasingly highlight the limitations of the isothermal assumption, especially in capturing short-term pollutant dynamics influenced by solar-driven thermal effects. To address this gap, a systematic CFD analysis of pollutant dispersion within an idealized 5 × 5 urban building array was conducted. This array was exposed to varying inlet wind velocities and solar irradiance levels, under fixed solar position and thermal boundary conditions. Results reveal that thermally induced flow structures can significantly modify pollutant dispersion patterns, particularly under low wind and high irradiance conditions. However, as mechanical forcing increases, flow fields and resulting pollutant concentration distributions tend to converge, reducing the impact of thermal perturbations. A comparative analysis of simulated pollutant fields and those recalculated using the isothermal wind velocity–concentration relationship shows that the reliability of this approach depends on the balance between thermal and mechanical forcing. Under favorable conditions—i.e., high wind, low solar irradiance—using this relationship remains robust. Conversely, under solar-dominated scenarios, it introduces significant errors.
打破CFD空气质量模拟中的等温假设:太阳辐照度对风速-浓度关系的影响
本研究考察了太阳辐照对城市空气质量等温计算流体动力学(CFD)模型中常用的风速-浓度关系的影响程度。主要目的是评估这种广泛使用的关系在非等温条件下的有效性,并为太阳诱导的热效应对城市污染物扩散的影响提供新的见解。虽然这种关系可以通过从有限的模拟中推断出长期的浓度估计,从而提供强大的操作优势,但其在非等温条件下的有效性仍未经检验。然而,最近的监管变化和经验证据日益突出了等温假设的局限性,特别是在捕捉受太阳能驱动的热效应影响的短期污染物动态方面。为了解决这一差距,对理想的5 × 5城市建筑阵列中的污染物扩散进行了系统的CFD分析。在固定的太阳位置和热边界条件下,该阵列暴露于不同的入口风速和太阳辐照度水平。结果表明,热诱导流动结构可以显著改变污染物的扩散模式,特别是在低风和高辐照条件下。然而,随着机械力的增加,流场和由此产生的污染物浓度分布趋于收敛,减少了热扰动的影响。对模拟的污染物场与利用等温风速-浓度关系重新计算的污染物场的对比分析表明,这种方法的可靠性取决于热力和机械力之间的平衡。在有利的条件下,例如:例如,风大,太阳辐照度低——利用这种关系仍然是强有力的。相反,在太阳能主导的情况下,它会引入重大误差。
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来源期刊
Sustainable Cities and Society
Sustainable Cities and Society Social Sciences-Geography, Planning and Development
CiteScore
22.00
自引率
13.70%
发文量
810
审稿时长
27 days
期刊介绍: Sustainable Cities and Society (SCS) is an international journal that focuses on fundamental and applied research to promote environmentally sustainable and socially resilient cities. The journal welcomes cross-cutting, multi-disciplinary research in various areas, including: 1. Smart cities and resilient environments; 2. Alternative/clean energy sources, energy distribution, distributed energy generation, and energy demand reduction/management; 3. Monitoring and improving air quality in built environment and cities (e.g., healthy built environment and air quality management); 4. Energy efficient, low/zero carbon, and green buildings/communities; 5. Climate change mitigation and adaptation in urban environments; 6. Green infrastructure and BMPs; 7. Environmental Footprint accounting and management; 8. Urban agriculture and forestry; 9. ICT, smart grid and intelligent infrastructure; 10. Urban design/planning, regulations, legislation, certification, economics, and policy; 11. Social aspects, impacts and resiliency of cities; 12. Behavior monitoring, analysis and change within urban communities; 13. Health monitoring and improvement; 14. Nexus issues related to sustainable cities and societies; 15. Smart city governance; 16. Decision Support Systems for trade-off and uncertainty analysis for improved management of cities and society; 17. Big data, machine learning, and artificial intelligence applications and case studies; 18. Critical infrastructure protection, including security, privacy, forensics, and reliability issues of cyber-physical systems. 19. Water footprint reduction and urban water distribution, harvesting, treatment, reuse and management; 20. Waste reduction and recycling; 21. Wastewater collection, treatment and recycling; 22. Smart, clean and healthy transportation systems and infrastructure;
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