Brice Barret, Patrice Medina, Natalie Brett, Roman Pohorsky, Kathy Law, Slimane Bekki, Gilberto J. Fochesatto, Julia Schmale, Steve Arnold, Andrea Baccarini, Mauricio Busetto, Meeta Cesler-Maloney, Barbara D'Anna, Stefano Decesari, Jingqiu Maoe, Gianluca Pappaccogli, Joel Savarino, Federico Scoto, William R. Simpson
{"title":"在 ALPACA-2022 期间使用低成本传感器测量北极冬季边界层痕量气体(CO、O3、NO、NO2)的垂直剖面和表面分布情况","authors":"Brice Barret, Patrice Medina, Natalie Brett, Roman Pohorsky, Kathy Law, Slimane Bekki, Gilberto J. Fochesatto, Julia Schmale, Steve Arnold, Andrea Baccarini, Mauricio Busetto, Meeta Cesler-Maloney, Barbara D'Anna, Stefano Decesari, Jingqiu Maoe, Gianluca Pappaccogli, Joel Savarino, Federico Scoto, William R. Simpson","doi":"10.5194/egusphere-2024-2421","DOIUrl":null,"url":null,"abstract":"<strong>Abstract.</strong> Electrochemical gas sensors (EGSs) have been used to measure the surface distributions and vertical profiles of trace gases in the wintertime Arctic Boundary Layer during the Alaskan Layered Pollution and Chemical Analysis (ALPACA) field experiment in Fairbanks, Alaska in January–February 2022. The MICRO sensors for MEasurements of GASes (MICROMEGAS) instrument set up with CO, NO, NO<sub>2</sub> and O<sub>3 </sub>EGSs was operated on the ground at an outdoor reference site downtown Fairbanks for calibration, onboard a vehicle moving through the city and its surroundings and onboard a tethered balloon, the Helikite, at a site at the edge of the city. To calibrate the measurements, a set of machine learning (ML) calibration methods were tested. For each method, learning and prediction were performed with coincident MICROMEGAS and reference analyser measurements at the downtown site. For CO, the calibration parameters provided by the manufacturer led to the best agreement between the EGS and the reference analyser and no ML method was needed for calibration. The correlation coefficient R is 0.82 and the slope of the linear regression between MICROMEGAS and reference data is 1.12. The mean bias is not significant but the Root Mean Square Error (290 ppbv) is rather large because of CO concentrations reaching several ppmv downtown Fairbanks. For NO, NO<sub>2</sub> and O<sub>3</sub>, the best agreements for the prediction datasets were obtained with an artificial neural network, the Multi-Layer Perceptron. For these 3 gases, the correlation coefficients are higher than 0.95 and the slopes of linear regressions with the reference data are in the range 0.93–1.04. The mean biases which are 1±3 ppbv, 0±4 ppbv and 3±12 ppbv for NO<sub>2</sub>, O<sub>3</sub> and NO respectively are not significant. Measurements from the car round of January 21 are presented to highlight the ability of MICROMEGAS to quantify the surface variability of the target trace gases in Fairbanks and the surrounding hills. MICROMEGAS flew 11 times from the ground up to a maximum of 350 m a.g.l. onboard the Helikite at the site at the edge of the city. The statistics performed over the Helikite MICROMEGAS dataset show that the median vertical gas profiles are characterised by almost constant mixing ratios. The median values over the vertical are 140, 8, 4 and 32 ppbv for CO, NO, NO<sub>2</sub> and O<sub>3</sub>. Extreme values are detected with low O<sub>3</sub> and high NO<sub>2</sub> and NO concentrations between 100 and 150 m a.g.l. O<sub>3</sub> minimum levels (5<sup><em>th</em></sup> percentile) of 5 ppbv coincident with NO<sub>2</sub> maximum levels (95<sup><em>th</em></sup> percentile) of 40 ppbv occur around 200 m a.g.l. The peaks aloft are linked to pollution plumes originating from Fairbanks power plants such as documented with the flight of February 20.","PeriodicalId":8619,"journal":{"name":"Atmospheric Measurement Techniques","volume":"12 1","pages":""},"PeriodicalIF":3.2000,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Vertical profiles and surface distributions of trace gases (CO, O3, NO, NO2) in the Arctic wintertime boundary layer using low-cost sensors during ALPACA-2022\",\"authors\":\"Brice Barret, Patrice Medina, Natalie Brett, Roman Pohorsky, Kathy Law, Slimane Bekki, Gilberto J. Fochesatto, Julia Schmale, Steve Arnold, Andrea Baccarini, Mauricio Busetto, Meeta Cesler-Maloney, Barbara D'Anna, Stefano Decesari, Jingqiu Maoe, Gianluca Pappaccogli, Joel Savarino, Federico Scoto, William R. Simpson\",\"doi\":\"10.5194/egusphere-2024-2421\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<strong>Abstract.</strong> Electrochemical gas sensors (EGSs) have been used to measure the surface distributions and vertical profiles of trace gases in the wintertime Arctic Boundary Layer during the Alaskan Layered Pollution and Chemical Analysis (ALPACA) field experiment in Fairbanks, Alaska in January–February 2022. The MICRO sensors for MEasurements of GASes (MICROMEGAS) instrument set up with CO, NO, NO<sub>2</sub> and O<sub>3 </sub>EGSs was operated on the ground at an outdoor reference site downtown Fairbanks for calibration, onboard a vehicle moving through the city and its surroundings and onboard a tethered balloon, the Helikite, at a site at the edge of the city. To calibrate the measurements, a set of machine learning (ML) calibration methods were tested. For each method, learning and prediction were performed with coincident MICROMEGAS and reference analyser measurements at the downtown site. For CO, the calibration parameters provided by the manufacturer led to the best agreement between the EGS and the reference analyser and no ML method was needed for calibration. The correlation coefficient R is 0.82 and the slope of the linear regression between MICROMEGAS and reference data is 1.12. The mean bias is not significant but the Root Mean Square Error (290 ppbv) is rather large because of CO concentrations reaching several ppmv downtown Fairbanks. For NO, NO<sub>2</sub> and O<sub>3</sub>, the best agreements for the prediction datasets were obtained with an artificial neural network, the Multi-Layer Perceptron. For these 3 gases, the correlation coefficients are higher than 0.95 and the slopes of linear regressions with the reference data are in the range 0.93–1.04. The mean biases which are 1±3 ppbv, 0±4 ppbv and 3±12 ppbv for NO<sub>2</sub>, O<sub>3</sub> and NO respectively are not significant. Measurements from the car round of January 21 are presented to highlight the ability of MICROMEGAS to quantify the surface variability of the target trace gases in Fairbanks and the surrounding hills. MICROMEGAS flew 11 times from the ground up to a maximum of 350 m a.g.l. onboard the Helikite at the site at the edge of the city. The statistics performed over the Helikite MICROMEGAS dataset show that the median vertical gas profiles are characterised by almost constant mixing ratios. The median values over the vertical are 140, 8, 4 and 32 ppbv for CO, NO, NO<sub>2</sub> and O<sub>3</sub>. Extreme values are detected with low O<sub>3</sub> and high NO<sub>2</sub> and NO concentrations between 100 and 150 m a.g.l. O<sub>3</sub> minimum levels (5<sup><em>th</em></sup> percentile) of 5 ppbv coincident with NO<sub>2</sub> maximum levels (95<sup><em>th</em></sup> percentile) of 40 ppbv occur around 200 m a.g.l. The peaks aloft are linked to pollution plumes originating from Fairbanks power plants such as documented with the flight of February 20.\",\"PeriodicalId\":8619,\"journal\":{\"name\":\"Atmospheric Measurement Techniques\",\"volume\":\"12 1\",\"pages\":\"\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2024-08-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Atmospheric Measurement Techniques\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.5194/egusphere-2024-2421\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"METEOROLOGY & ATMOSPHERIC SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Atmospheric Measurement Techniques","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.5194/egusphere-2024-2421","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
Vertical profiles and surface distributions of trace gases (CO, O3, NO, NO2) in the Arctic wintertime boundary layer using low-cost sensors during ALPACA-2022
Abstract. Electrochemical gas sensors (EGSs) have been used to measure the surface distributions and vertical profiles of trace gases in the wintertime Arctic Boundary Layer during the Alaskan Layered Pollution and Chemical Analysis (ALPACA) field experiment in Fairbanks, Alaska in January–February 2022. The MICRO sensors for MEasurements of GASes (MICROMEGAS) instrument set up with CO, NO, NO2 and O3 EGSs was operated on the ground at an outdoor reference site downtown Fairbanks for calibration, onboard a vehicle moving through the city and its surroundings and onboard a tethered balloon, the Helikite, at a site at the edge of the city. To calibrate the measurements, a set of machine learning (ML) calibration methods were tested. For each method, learning and prediction were performed with coincident MICROMEGAS and reference analyser measurements at the downtown site. For CO, the calibration parameters provided by the manufacturer led to the best agreement between the EGS and the reference analyser and no ML method was needed for calibration. The correlation coefficient R is 0.82 and the slope of the linear regression between MICROMEGAS and reference data is 1.12. The mean bias is not significant but the Root Mean Square Error (290 ppbv) is rather large because of CO concentrations reaching several ppmv downtown Fairbanks. For NO, NO2 and O3, the best agreements for the prediction datasets were obtained with an artificial neural network, the Multi-Layer Perceptron. For these 3 gases, the correlation coefficients are higher than 0.95 and the slopes of linear regressions with the reference data are in the range 0.93–1.04. The mean biases which are 1±3 ppbv, 0±4 ppbv and 3±12 ppbv for NO2, O3 and NO respectively are not significant. Measurements from the car round of January 21 are presented to highlight the ability of MICROMEGAS to quantify the surface variability of the target trace gases in Fairbanks and the surrounding hills. MICROMEGAS flew 11 times from the ground up to a maximum of 350 m a.g.l. onboard the Helikite at the site at the edge of the city. The statistics performed over the Helikite MICROMEGAS dataset show that the median vertical gas profiles are characterised by almost constant mixing ratios. The median values over the vertical are 140, 8, 4 and 32 ppbv for CO, NO, NO2 and O3. Extreme values are detected with low O3 and high NO2 and NO concentrations between 100 and 150 m a.g.l. O3 minimum levels (5th percentile) of 5 ppbv coincident with NO2 maximum levels (95th percentile) of 40 ppbv occur around 200 m a.g.l. The peaks aloft are linked to pollution plumes originating from Fairbanks power plants such as documented with the flight of February 20.
期刊介绍:
Atmospheric Measurement Techniques (AMT) is an international scientific journal dedicated to the publication and discussion of advances in remote sensing, in-situ and laboratory measurement techniques for the constituents and properties of the Earth’s atmosphere.
The main subject areas comprise the development, intercomparison and validation of measurement instruments and techniques of data processing and information retrieval for gases, aerosols, and clouds. The manuscript types considered for peer-reviewed publication are research articles, review articles, and commentaries.