Quantifying Contributions of Factors and Their Interactions to Aerosol Acidity with a Multiple-Linear-Regression-Based Framework: A Case Study in the Pearl River Delta, China
This study presents an approach using multiple linear regression to quantify the impact of meteorological parameters and chemical species on aerosol pH variance in an urban setting in the Pearl River Delta, China. Additionally, it assesses the contributions of interactions among these factors to the...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-01-01
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| Series: | Atmosphere |
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| Online Access: | https://www.mdpi.com/2073-4433/15/2/172 |
| _version_ | 1827344197049384960 |
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| author | Hong Ling Mingqi Deng Qi Zhang Lei Xu Shuzhen Su Xihua Li Liming Yang Jingying Mao Shiguo Jia |
| author_facet | Hong Ling Mingqi Deng Qi Zhang Lei Xu Shuzhen Su Xihua Li Liming Yang Jingying Mao Shiguo Jia |
| author_sort | Hong Ling |
| collection | DOAJ |
| description | This study presents an approach using multiple linear regression to quantify the impact of meteorological parameters and chemical species on aerosol pH variance in an urban setting in the Pearl River Delta, China. Additionally, it assesses the contributions of interactions among these factors to the variance in pH. The analysis successfully explains over 96% of the pH variance, attributing 85.8% to the original variables and 6.7% to bivariate interactions, with further contributions of 2.3% and 1.0% from trivariate and quadrivariate interactions, respectively. Our results highlight that meteorological factors, particularly temperature and humidity, are more influential than chemical components in affecting aerosol pH variance. Temperature alone accounts for 37.3% of the variance, while humidity contributes approximately 20%. On the chemical front, sulfate and ammonium are the most significant contributors, adding 14.3% and 9.1% to the pH variance, respectively. In the realm of bivariate interactions, the interplay between meteorological parameters and chemical components, especially the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>TNO</mi></mrow><mrow><mn>3</mn></mrow></msub><mo>–</mo><mi>RH</mi></mrow></semantics></math></inline-formula> pair, is exceptionally impactful, constituting 58.1% of the total contribution from interactions. In summary, this study illuminates the factors affecting aerosol pH variance and their interplay, suggesting the integration of statistical methods with thermodynamic models for enhanced understanding of aerosol acidity dynamics in the future. |
| first_indexed | 2024-03-07T22:42:37Z |
| format | Article |
| id | doaj.art-5f91dec26f104ce2ad7626f2c570be3f |
| institution | Directory Open Access Journal |
| issn | 2073-4433 |
| language | English |
| last_indexed | 2024-03-07T22:42:37Z |
| publishDate | 2024-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Atmosphere |
| spelling | doaj.art-5f91dec26f104ce2ad7626f2c570be3f2024-02-23T15:07:03ZengMDPI AGAtmosphere2073-44332024-01-0115217210.3390/atmos15020172Quantifying Contributions of Factors and Their Interactions to Aerosol Acidity with a Multiple-Linear-Regression-Based Framework: A Case Study in the Pearl River Delta, ChinaHong Ling0Mingqi Deng1Qi Zhang2Lei Xu3Shuzhen Su4Xihua Li5Liming Yang6Jingying Mao7Shiguo Jia8Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, ChinaSouthern Marine Science and Engineering Guangdong Laboratory (Zhuhai), School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, ChinaTianjin Academy of Eco-Environmental Sciences, Tianjin 300191, ChinaAppraisal Center for Environment and Engineering, Ministry of Ecology and Environment, Beijing 100041, ChinaGuangdong Dongguan Ecological Environment Monitoring Station, Dongguan 523009, ChinaGuangdong Dongguan Ecological Environment Monitoring Station, Dongguan 523009, ChinaDepartment of Chemical and Biomolecular Engineering, National University of Singapore, Singapore 117576, SingaporeScientific Research Academy of Guangxi Environmental Protection, Nanning 530022, ChinaSouthern Marine Science and Engineering Guangdong Laboratory (Zhuhai), School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, ChinaThis study presents an approach using multiple linear regression to quantify the impact of meteorological parameters and chemical species on aerosol pH variance in an urban setting in the Pearl River Delta, China. Additionally, it assesses the contributions of interactions among these factors to the variance in pH. The analysis successfully explains over 96% of the pH variance, attributing 85.8% to the original variables and 6.7% to bivariate interactions, with further contributions of 2.3% and 1.0% from trivariate and quadrivariate interactions, respectively. Our results highlight that meteorological factors, particularly temperature and humidity, are more influential than chemical components in affecting aerosol pH variance. Temperature alone accounts for 37.3% of the variance, while humidity contributes approximately 20%. On the chemical front, sulfate and ammonium are the most significant contributors, adding 14.3% and 9.1% to the pH variance, respectively. In the realm of bivariate interactions, the interplay between meteorological parameters and chemical components, especially the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>TNO</mi></mrow><mrow><mn>3</mn></mrow></msub><mo>–</mo><mi>RH</mi></mrow></semantics></math></inline-formula> pair, is exceptionally impactful, constituting 58.1% of the total contribution from interactions. In summary, this study illuminates the factors affecting aerosol pH variance and their interplay, suggesting the integration of statistical methods with thermodynamic models for enhanced understanding of aerosol acidity dynamics in the future.https://www.mdpi.com/2073-4433/15/2/172aerosol acidityinteractionsPearl River Delta (PRD)pH variance |
| spellingShingle | Hong Ling Mingqi Deng Qi Zhang Lei Xu Shuzhen Su Xihua Li Liming Yang Jingying Mao Shiguo Jia Quantifying Contributions of Factors and Their Interactions to Aerosol Acidity with a Multiple-Linear-Regression-Based Framework: A Case Study in the Pearl River Delta, China Atmosphere aerosol acidity interactions Pearl River Delta (PRD) pH variance |
| title | Quantifying Contributions of Factors and Their Interactions to Aerosol Acidity with a Multiple-Linear-Regression-Based Framework: A Case Study in the Pearl River Delta, China |
| title_full | Quantifying Contributions of Factors and Their Interactions to Aerosol Acidity with a Multiple-Linear-Regression-Based Framework: A Case Study in the Pearl River Delta, China |
| title_fullStr | Quantifying Contributions of Factors and Their Interactions to Aerosol Acidity with a Multiple-Linear-Regression-Based Framework: A Case Study in the Pearl River Delta, China |
| title_full_unstemmed | Quantifying Contributions of Factors and Their Interactions to Aerosol Acidity with a Multiple-Linear-Regression-Based Framework: A Case Study in the Pearl River Delta, China |
| title_short | Quantifying Contributions of Factors and Their Interactions to Aerosol Acidity with a Multiple-Linear-Regression-Based Framework: A Case Study in the Pearl River Delta, China |
| title_sort | quantifying contributions of factors and their interactions to aerosol acidity with a multiple linear regression based framework a case study in the pearl river delta china |
| topic | aerosol acidity interactions Pearl River Delta (PRD) pH variance |
| url | https://www.mdpi.com/2073-4433/15/2/172 |
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