空气质量低成本传感器的室内校准和性能评估

IF 3.9 3区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES Atmospheric Pollution Research Pub Date : 2024-09-01 DOI:10.1016/j.apr.2024.102299
Deepali Agrawal , Anil Kumar Saini , Aakash Chand Rai , Prateek Kala
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引用次数: 0

摘要

评估个人暴露于 PM2.5(空气动力直径小于 2.5 μm 的颗粒物)的情况需要在特定的地理和时间范围内精确监测 PM2.5 的浓度。低成本颗粒物传感器可在全球范围内满足这一需求,但对其进行校准却很困难。在这项研究中,使用各种气溶胶对四种低成本 PM 传感器(夏普 GP2Y1010AU0F、霍尼韦尔 HPMA115S0-XXX、Plantower PMSA003-A 和 Sensirion SPS30)进行了校准和测试。校准方法分为三个步骤:单独校准(每个传感器独立校准一种气溶胶类型;n = 1)、组合校准(特定型号的所有传感器一起校准一种特定气溶胶类型;n = 4)和通用校准(特定型号的所有传感器一起校准所有气溶胶;n = 16)。在每个校准阶段,传感器响应都使用线性、二次方、幂律和人工神经网络(ANN)算法进行处理。性能指标包括判定系数 (R2)、平均绝对百分比误差 (MAPE)、均方根误差 (RMSE) 和百分比变异系数 (% CV) 等,用于评估。在所有四种测试的传感器中,Sensirion SPS30 传感器的性能最佳,在使用通用 ANN 校准算法进行校准时,R2 值最小为 0.911。此外,在暴露于不同颗粒时,MAPE 小于 10%,RMSE 小于 7%。Sensirion SPS30 的传感器间变异性最低,CV%小于 6%。传感器在调查中识别了单分散聚苯乙烯胶乳 (PSL) 粒径。无论接触 0.3、0.46、0.60 或 1.0 μm 的 PSL,PMSA003 传感器报告的数量大小分布保持一致,与 Grimm 的结果不一致。随着 PSL 尺寸的增加,SPS30 的粒度分布向更大的粒度方向变化,但并不总是与 Grimm 的数据一致。随着 PSL 尺寸的增加,传感器的 PM1、PM2.5 和 PM10 质量比例也发生了变化。
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In chamber calibration and performance evaluation of air quality low-cost sensors

Assessing individual exposure to PM2.5 (particulate matter of aerodynamic diameter lesser than 2.5 μm) requires precise monitoring of PM2.5 concentrations at specific geographical and temporal scales. This demand is met globally by low-cost particulate matter sensors, although calibrating them is difficult. In this study, four low-cost PM sensors, Sharp GP2Y1010AU0F, Honeywell HPMA115S0-XXX, Plantower PMSA003-A, and Sensirion SPS30, were calibrated and tested using various aerosols. The calibration method has three steps: individual (considering each sensor independently to a single aerosol type; n = 1), combined (all sensors for a specific model together for a specific aerosol type; n = 4), and generic (all sensors for a given model together to all aerosols; n = 16). Sensor responses are processed using linear, quadratic, power-law, and artificial neural network (ANN) algorithms in each calibration stage. Performance metrics, including coefficient of determination (R2), mean absolute percentage error (MAPE), root mean square error (RMSE), and percentage coefficient of variation (% CV), were utilized for assessment. Amongst all the four tested sensors, the Sensirion SPS30 sensors gave the best performance with a minimum R2 value of 0.911 when calibrated with a generic ANN calibration algorithm. Also, the MAPE was less than 10 %, and the RMSE was less than 7 % when exposed to different particles. Sensirion SPS30 showed the lowest inter-sensor variability with % CV less than 6 %. Sensors identified monodisperse polystyrene latex (PSL) particle size in the investigation. Regardless of exposure to 0.3, 0.46, 0.60, or 1.0 μm PSL, the reported number size distribution for the PMSA003 sensor remained consistent and did not align with the results from Grimm. As the PSL size rose, the SPS30 size distribution changed towards larger particle sizes, although it did not always match Grimm data. As the PSL size increased, the sensor's PM1, PM2.5, and PM10 mass proportions altered.

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来源期刊
Atmospheric Pollution Research
Atmospheric Pollution Research ENVIRONMENTAL SCIENCES-
CiteScore
8.30
自引率
6.70%
发文量
256
审稿时长
36 days
期刊介绍: Atmospheric Pollution Research (APR) is an international journal designed for the publication of articles on air pollution. Papers should present novel experimental results, theory and modeling of air pollution on local, regional, or global scales. Areas covered are research on inorganic, organic, and persistent organic air pollutants, air quality monitoring, air quality management, atmospheric dispersion and transport, air-surface (soil, water, and vegetation) exchange of pollutants, dry and wet deposition, indoor air quality, exposure assessment, health effects, satellite measurements, natural emissions, atmospheric chemistry, greenhouse gases, and effects on climate change.
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