哈萨克家庭的室内空气质量:评估烹饪活动产生的 PM2.5 水平

F. Karaca, Mert Guney, A. Agibayeva, Nurlan Otesh, M. Kulimbet, Natalya Glushkova, Yuefang Chang, Akira Sekikawa, K. Davletov
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摘要

本研究介绍了在典型的哈萨克民居中进行烹饪活动期间室内可吸入细颗粒物(PM2.5)的浓度估算模型,这些民居通常通风不良,排放水平较高。本研究的目的是确定影响烹饪过程中 PM2.5 浓度的因素,并阐明 PM2.5 浓度累积和降低的内在机制。这些都是通过一种结合 PM2.5 采样、监测和建模的方法来预测家庭 PM2.5 水平和估算每日浓度来实现的。具体地说,美国环保局的 IAQX v1.1 被用来模拟单区概念(厨房),模拟几个家庭中与烹饪活动有关的浓度。结果显示,在烹饪活动期间,PM2.5 浓度在 13 到 266 μg/m3 之间变化。厨房大小、空气交换特性、食物类型和烹饪方式等因素被认为是影响观察到的浓度的重要因素。该模型准确捕捉到了浓度趋势(R > 0.9)。然而,某些预测往往会高估测量结果,这是因为在选择空气交换和排放率时存在误差。烹饪活动对家庭空气污染物(HAP)PM2.5 水平的影响从 9% 到 94% 不等。值得注意的是,在一年中的非供暖期(相当于温暖的半年),烹饪的影响变得更加显著,并被确定为室内 PM2.5 浓度的主要贡献者。相反,在供暖期(即一年中较冷的部分),室外 PM 水平和家庭通风方式在调节室内空气浓度方面发挥着主要作用。本研究是中亚地区对家庭空气污染物进行评估的初步尝试之一,为了解哈萨克斯坦的室内空气质量提供了基础和见解。未来的研究建议包括开发考虑个人活动模式和特定房屋类型的先进模型,以提高准确性和代表性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Indoor air quality in Kazakh households: Evaluating PM2.5 levels generated by cooking activities
The present study introduces a concentration estimation model for indoor inhalable fine particles (PM2.5) during cooking activities in typical Kazakh houses, which are generally poorly ventilated with high emission levels. The aim of the present work is to identify factors influencing PM2.5 concentrations during cooking and elucidate the mechanisms underlying the build‐up and reduction of PM2.5 concentrations. These are achieved through a methodology that combines PM2.5 sampling, monitoring, and modeling to predict household PM2.5 levels and estimate daily concentrations. Specifically, USEPA's IAQX v1.1 was employed to simulate the one‐zone concept (kitchen) for concentrations related to cooking activities in several households. The results reveal that PM2.5 concentrations varied between 13 and 266 μg/m3 during cooking activities. Factors such as kitchen size, air exchange characteristics, and the type of food and cooking style were identified as important, influencing the observed concentrations. The model accurately captured concentration trends (R > 0.9). However, certain predictions tended to overestimate the measurements, attributing to inaccuracies in selecting air exchange and emission rates. Cooking activities contributed to household air pollutant (HAP) PM2.5 levels ranging from 9% to 94%. Notably, during the non‐heating period of the year (corresponding to the warmer half of the year), the impact of cooking became more significant and was identified as a major contributor to indoor PM2.5 concentrations. Conversely, during the heating period (i.e., the colder part of the year), outdoor PM levels and household ventilation practices played primary roles in regulating indoor air concentrations. This present study presents one of the initial efforts to assess household air pollutants in Central Asia, providing foundation and insights into the indoor air quality of Kazakh houses, where the understanding of indoor air quality remains limited. Future research recommendations include developing advanced models that account for individual activity patterns and specific house types for improved accuracy and representativeness.
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