Using low-cost sensors to assess real-time comfort and air quality patterns in indoor households

Environmental science and pollution research international(2022)

引用 3|浏览17
暂无评分
摘要
People spend most of their time in indoor environments without knowing about the air quality in these spaces. In this study, indoor low-cost sensors were used (for 5 months) to assess the comfort and air quality patterns in two indoor households. To strengthen the robustness of the considered approach and build confidence in the obtained comfort and indoor air quality (IAQ) levels, the sensor measurements were also compared against information from reference monitoring equipment; in which, high correlation coefficients were obtained (> 0.85) and also low errors (on average 22%). The IAQ results were strongly influenced by the residents’ activity and behaviour, the outdoor weather conditions, and indoor/outdoor air pollution sources. Overall, the recommended values of temperature and relative humidity for the occupant’s comfort in indoor environments were not fulfilled. The highest particulate matter (PM) levels were recorded at the weekend (on average +14% higher), while maximum CO 2 and CO levels were obtained on the weekdays (on average +9% higher). PM daily profiles followed the outdoor concentrations with the maximum levels at the end of the night and the lowest values in the early morning/mid-afternoon. The highest and lowest CO 2 concentrations were registered in the early morning (< 1536 ppm) and mid-afternoon (< 627 ppm), respectively, while the CO daily profiles showed a high impact of outdoor emissions, with the minimum concentrations up to 0.81 mg m −3 (at 10 a.m. or 6 p.m.), and a maximum concentration of 1.87 mg m −3 (at 10 p.m.). Real-time comfort conditions and IAQ levels are a powerful approach to providing fast decisions to minimise human exposure and prevent negative health impacts.
更多
查看译文
关键词
Reference monitoring equipment,Particulate matter,Carbon dioxide,Carbon monoxide
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要