scholarly journals Development of a General Calibration Model and Long-Term Performance Evaluation of Low-Cost Sensors for Air Pollutant Gas Monitoring

2018 ◽  
Author(s):  
Carl Malings ◽  
Rebecca Tanzer ◽  
Aliaksei Hauryliuk ◽  
Sriniwasa P. N. Kumar ◽  
Naomi Zimmerman ◽  
...  
Keyword(s):  
Linear Models ◽  
Low Cost ◽  
Air Pollutant ◽  
Superior Performance ◽  
Calibration Model ◽  
Quadratic Regression ◽  
Calibration Models ◽  
Using Data ◽  
One Year

Abstract. Assessing the intra-city spatial distribution and temporal variability of air quality can be facilitated by a dense network of monitoring stations. However, the cost of implementing such a network can be prohibitive if traditional high-quality, expensive monitoring systems are used. To this end, the Real-time Affordable Multi-Pollutant (RAMP) monitor has been developed, which can measure up to five gases including the criteria pollutant gases carbon monoxide (CO), nitrogen dioxide (NO2), and ozone (O3), along with temperature and relative humidity. This study compares various algorithms to calibrate the RAMP measurements including linear and quadratic regression, clustering, neural networks, Gaussian processes, and random forests. Using data collected by more than sixty RAMP monitors over periods ranging up to eighteen months, it was found that quadratic regression models or a hybrid of random forest and linear models tend to be the most effective calibration models overall. In specific cases, other types of models can have comparable or even superior performance. Furthermore, generalized calibration models may be used instead of individual models with only a small reduction in overall performance. For long-term deployments, it is recommended that new models be developed each year, due to the noticeable change in performance when models for one year were used for processing data collected in the subsequent year. This makes annually-developed generalized calibration models even more useful since only a subset of deployed monitors are needed to build these models. These results will help guide future efforts in the calibration and use of low-cost sensor systems worldwide.

scholarly journals Development of a general calibration model and long-term performance evaluation of low-cost sensors for air pollutant gas monitoring

2019 ◽  
Vol 12 (2) ◽  
pp. 903-920 ◽  
Author(s):  
Carl Malings ◽  
Rebecca Tanzer ◽  
Aliaksei Hauryliuk ◽  
Sriniwasa P. N. Kumar ◽  
Naomi Zimmerman ◽  
...  
Keyword(s):  
Electrochemical Sensors ◽  
Low Cost ◽  
Air Pollutant ◽  
Calibration Model ◽  
Linear Regression Models ◽  
Quadratic Regression ◽  
Neural Network Models ◽  
Calibration Models ◽  
New Models

Abstract. Assessing the intracity spatial distribution and temporal variability in air quality can be facilitated by a dense network of monitoring stations. However, the cost of implementing such a network can be prohibitive if traditional high-quality, expensive monitoring systems are used. To this end, the Real-time Affordable Multi-Pollutant (RAMP) monitor has been developed, which can measure up to five gases including the criteria pollutant gases carbon monoxide (CO), nitrogen dioxide (NO2), and ozone (O3), along with temperature and relative humidity. This study compares various algorithms to calibrate the RAMP measurements including linear and quadratic regression, clustering, neural networks, Gaussian processes, and hybrid random forest–linear regression models. Using data collected by almost 70 RAMP monitors over periods ranging up to 18 months, we recommend the use of limited quadratic regression calibration models for CO, neural network models for NO, and hybrid models for NO2 and O3 for any low-cost monitor using electrochemical sensors similar to those of the RAMP. Furthermore, generalized calibration models may be used instead of individual models with only a small reduction in overall performance. Generalized models also transfer better when the RAMP is deployed to other locations. For long-term deployments, it is recommended that model performance be re-evaluated and new models developed periodically, due to the noticeable change in performance over periods of a year or more. This makes generalized calibration models even more useful since only a subset of deployed monitors are needed to build these new models. These results will help guide future efforts in the calibration and use of low-cost sensor systems worldwide.

scholarly journals Long-term behavior and stability of calibration models for NO and NO<sub>2</sub> low cost sensors

2022 ◽  
Author(s):  
Horim Kim ◽  
Michael Müller ◽  
Stephan Henne ◽  
Christoph Hüglin
Keyword(s):  
Electrochemical Sensors ◽  
Low Cost ◽  
Air Pollutant ◽  
Coefficient Of Determination ◽  
Monitoring Networks ◽  
Pollution Levels ◽  
Pollutant Concentrations ◽  
Air Quality Measurements ◽  
One Year

Abstract. Low-cost sensors are considered as exhibiting great potential to complement classical air quality measurements in existing monitoring networks. However, the use of low-cost sensors poses some challenges. In this study, the behavior and performance of electrochemical sensors for NO and NO2 were determined over a longer operating period in a real-world deployment. After careful calibration of the sensors, based on co-location with reference instruments at a rural traffic site during six months and by using robust linear regression and random forest regression, the coefficient of determination of both types of sensors were high (R2 > 0.9) and the root mean square error (RMSE) of NO and NO2 sensors were about 6.8 ppb and 3.5 ppb, respectively, for 10-minute mean concentrations. The RMSE of the NO2 sensors, however, more than doubled, when the sensors were deployed without re-calibration for a one-year period at other site types (including urban background locations), where the range and the variability of air pollutant concentrations differed from the calibration site. This indicates a significant effect of the re-location of the sensors on the quality of their data. During deployment, we found that the NO2 sensors are capable of distinguishing general pollution levels, but they proved unsuitable for accurate measurements, mainly due to significant biases. In order to investigate the long-term stability of the original calibration, the sensors were re-installed at the calibration site after deployment. Surprisingly, the coefficient of determination and the RMSE of the NO sensor remained almost unchanged after more than one year of operation. In contrast, the performance of the NO2 sensors clearly deteriorated as indicated by a higher RMSE (about 7.5 ppb, 10-minute mean concentrations) and a lower coefficient of determination (R2 = 0.59).

Increase associated risk of gynaecological cancer due to long-term exposure to high concentration of atmospheric SO2 industrial pollutant

2021 ◽  
pp. 1420326X2110036
Author(s):  
Qian Xu ◽  
Chan Lu ◽  
Rachael Gakii Murithi ◽  
Lanqin Cao
Keyword(s):  
Time Windows ◽  
Air Pollutant ◽  
Gynaecological Cancer ◽  
High Concentration ◽  
The Past ◽  
Short And Long Term ◽  
Using Data ◽  
Air Quality Monitoring Stations ◽  
Control Study

A cohort case–control study was conducted in XiangYa Hospital, Changsha, China, which involved 305 patients and 399 healthy women, from June 2010 to December 2018, to evaluate the association between Chinese women’s short- and long-term exposure to industrial air pollutant, SO2 and gynaecological cancer (GC). We obtained personal and family information from the XiangYa Hospital electronic computer medical records. Using data obtained from the air quality monitoring stations in Changsha, we estimated each woman’s exposure to the industrial air pollutant, sulphur dioxide (SO2), for different time windows, including the past 1, 5, 10 and 15 years before diagnosis of the disease. A multiple logistic regression model was used to assess the association between GC and SO2 exposure. GC was significantly associated with long-term SO2 exposure, with adjusted odds ratio (95% confidence interval) = 1.56 (1.10–2.21) and 1.81 (1.07–3.06) for a per interquartile range increase in the past 10 and 15 years, respectively. Sensitivity analysis showed that different groups reacted in different ways to long-term SO2 exposure. We concluded that long-term exposure to high concentration of industrial pollutant, SO2 is associated with the development of GC. This finding has implications for the prevention and reduction of GC.

scholarly journals Improving Air Pollutant Metal Oxide Sensor Quantification Practices through: An Exploration of Sensor Signal Normalization, Multi-Sensor and Universal Calibration Model Generation, and Physical Factors Such as Co-Location Duration and Sensor Age

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 645
Author(s):  
Kristen Okorn ◽  
Michael Hannigan
Keyword(s):  
Metal Oxide ◽  
Low Cost ◽  
Air Pollutant ◽  
Sensor System ◽  
Physical Factors ◽  
Time Averaging ◽  
Calibration Model ◽  
Sensor Signal ◽  
Metal Oxide Sensors ◽  
Signal Normalization

As low-cost sensors have become ubiquitous in air quality measurements, there is a need for more efficient calibration and quantification practices. Here, we deploy stationary low-cost monitors in Colorado and Southern California near oil and gas facilities, focusing our analysis on methane and ozone concentration measurement using metal oxide sensors. In comparing different sensor signal normalization techniques, we propose a z-scoring standardization approach to normalize all sensor signals, making our calibration results more easily transferable among sensor packages. We also attempt several different physical co-location schemes, and explore several calibration models in which only one sensor system needs to be co-located with a reference instrument, and can be used to calibrate the rest of the fleet of sensor systems. This approach greatly reduces the time and effort involved in field normalization without compromising goodness of fit of the calibration model to a significant extent. We also explore other factors affecting the performance of the sensor system quantification method, including the use of different reference instruments, duration of co-location, time averaging, transferability between different physical environments, and the age of metal oxide sensors. Our focus on methane and stationary monitors, in addition to the z-scoring standardization approach, has broad applications in low-cost sensor calibration and utility.

A Seasonally Coherent Calibration (SCC) Model for Postprocessing Numerical Weather Predictions

2019 ◽  
Vol 147 (10) ◽  
pp. 3633-3647 ◽  
Author(s):  
Q. J. Wang ◽  
Tony Zhao ◽  
Qichun Yang ◽  
David Robertson
Keyword(s):  
Weather Prediction ◽  
Model Performance ◽  
Statistical Characteristics ◽  
Lead Times ◽  
Model Parameters ◽  
Calibration Model ◽  
Numerical Weather ◽  
Calibration Models ◽  
Short Period ◽  
One Year

Abstract Statistical calibration of forecasts from numerical weather prediction (NWP) models aims to produce forecasts that are unbiased, reliable in ensemble spread, and as skillful as possible. We suggest that the calibrated forecasts should also be coherent in climatology, including seasonality, consistent with observations. This is especially important when forecasts approach climatology as forecast skill becomes low, such as at long lead times. However, it is challenging to achieve these aims when data available to establish sophisticated calibration models are limited. Many NWP models have only a short period of archived data, typically one year or less, when they become officially operational. In this paper, we introduce a seasonally coherent calibration (SCC) model for working effectively with limited archived NWP data. Detailed rationale and mathematical formulations are presented. In the development of the model, three issues are resolved. These are 1) constructing a calibration model that is sophisticated enough to allow for seasonal variation in the statistical characteristics of raw forecasts and observations, 2) bringing climatology that is representative of long-term statistics into the calibration model, and 3) reducing the number of model parameters through sensible reparameterization to make the model workable with short NWP dataset. A case study is conducted to examine model assumptions and evaluate model performance. We find that the model assumptions are sound, and the developed SCC model produces well-calibrated forecasts.

Performance Implications of Aligning CEO Functional Experiences with Competitive Strategies

2000 ◽  
Vol 26 (4) ◽  
pp. 733-762 ◽  
Author(s):  
Reginald M. Beal ◽  
Masoud Yasai-Ardekani
Keyword(s):  
Low Cost ◽  
Manufacturing Firms ◽  
Superior Performance ◽  
Competitive Strategies ◽  
Cost Leadership ◽  
Performance Consequences ◽  
Using Data ◽  
Performance Results

This study examines the performance consequences of aligning managerial functional experiences with generic competitive strategies and adopts a multidimensional view of generic competitive strategies involving low-cost leadership and several differentiation based strategies. Using data on a sample of 101 small manufacturing firms, the results of analysis provide substantial support for the alignment hypotheses. The study further tests a series of hypotheses on alignments between combined managerial experiences and hybrid strategies that combine low-cost leadership with differentiation based strategies. The findings indicate that superior performance results in conditions where managerial functional experiences are congruent with the requirements of particular generic or hybrid strategies.

Comparison Study on Friction-Welded Cu-Al Material and Pure Cu/Al

2015 ◽  
Vol 817 ◽  
pp. 374-378 ◽  
Author(s):  
Li Qiao ◽  
Hui Huang Yang ◽  
Jian Feng Sheng
Keyword(s):  
Low Cost ◽  
Salt Spray ◽  
Superior Performance ◽  
Temperature Cycle ◽  
Welding Seam ◽  
Weak Part ◽  
Potential Applications ◽  
Temperature Cycle Test ◽  
Pure Cu

Friction-weld Cu-Al has many potential applications to replace the traditional Cu or Al conductor as it has the superior performance and low cost. For ensuring the reliability of Al/Cu metal joints, the mechanical, electrical and long-term properties were investigated by comparing the properties of Cu and Al. The results show that the mechanical properties (tension, impact and hardness) of friction-welded Cu-Al are between the values of Cu and Al, and the welding seam is not the weakest part in mechanical. The electrical resistance of Cu-Al is also between the values of Cu and Al, and does not increase after long-term vibration test and high-low temperature cycle test. The welding seaming is a weak part for salt spray test, it is better to be protected for use.

Quantification of an Active Substance in a Tablet by NIR and Raman Spectroscopy

1998 ◽  
Vol 6 (1) ◽  
pp. 279-289 ◽  
Author(s):  
Ingela Jedvert ◽  
Mats Josefson ◽  
Frans Langkilde
Keyword(s):  
Raman Spectroscopy ◽  
Active Substance ◽  
Reference Method ◽  
Spectroscopic Technique ◽  
Calibration Model ◽  
Baseline Correction ◽  
Spectroscopic Techniques ◽  
Long Term Stability ◽  
Calibration Models

Spectroscopic techniques in combination with chemometrics give opportunities to analyse tablets without time-consuming sample preparation. The aim of the present study was to develop a method to quantify the active substance, isosorbide-5-mononitrate, in Imdur® 120 mg tablets either by NIR diffuse reflectance or Raman spectroscopy. The calibration set was selected to simulate, with the available samples, as closely as possible a full factorial design with three factors. The reference method was liquid chromatography (LC). Calibration models with different baseline correction methods, different parts of wavelength range and different measures of weights have been evaluated. The calibration model found for each spectroscopic technique is discussed. The accuracy for the spectroscopic techniques were equal in merit to the LC method. Both the NIR and the Raman calibrations also showed a good long-term stability. With the baseline correction methods used for the spectra, it was possible to analyse tablets after 1.5 years. In conclusion it is possible to quantify Imdur® 120 mg with either NIR or Raman spectroscopy.

On-line identification of silkworm pupae gender by short-wavelength near infrared spectroscopy and pattern recognition technology

2021 ◽  
pp. 096703352199974
Author(s):  
Yue Ma ◽  
Yichao Xu ◽  
Hui Yan ◽  
Guozheng Zhang
Keyword(s):  
Discriminant Analysis ◽  
Short Wavelength ◽  
Near Infrared ◽  
Low Cost ◽  
Calibration Model ◽  
Linear Discriminant ◽  
Line Identification ◽  
Silkworm Pupae ◽  
Calibration Models ◽  
On Line

The gender identification of silkworm pupae is a critical step in the sericulture industry's breeding process. In this study, a low cost, short-wavelength (815-1075 nm) near infrared (NIR) spectrometer combined with multivariate spectra evaluation methods was used to establish calibration models for the on-line identification of female and male pupae of eight silkworm varieties (Hibiscus, Jingsong, 932, Xiang Hui, 7532×Xiang Hui, Haoyue B, Jingsong B, and 7532). The diffuse reflection short-wavelength spectra were recorded, and then principal component analysis (PCA), linear discriminant analysis (LDA), and partial least squares discriminant analysis (PLSDA) were tested for calibration model development. The PCA and LDA results showed, that spectral differences between the female and male silkworm pupae existed, however, the two evaluation techniques could not separate the female and male silkworm pupae with the required accuracy. The PLSDA calibration models, on the other hand, could separate the pupae according to their gender with the necessary prediction accuracy of >98.44%. Thus, it has been proved, that a low-cost, short-wavelength range NIR spectrometer in combination with a PLSDA calibration routine can be successfully applied for the reliable on-line identification of female and male silkworm pupae.

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