Comment on gmd-2023-22 DOI Creative Commons
Juan Antonio Añel

Published: June 15, 2023

Abstract. A comprehensive understanding of the effects meteorology, emissions, and chemistry on severe haze is critical in mitigation air pollution. However, such an greatly hindered by nonlinearity atmospheric systems. In this study, we developed quantitative decoupling analysis (QDA) method to quantify chemical reactions, their nonlinear interactions fine particulate matter (PM2.5) pollution running built-in scenario simulations each model step. Different from previous methods, QDA achieves a fully decomposed hourly changes PM2.5 concentration during events into seven parts, including pure meteorological contribution (M), emissions (E), (C), among these processes (i.e., ME, MC, EC, MCE). Via embedding Weather Research Forecasting–Nested Air Quality Prediction Modeling System, employed combined it with Integrated Process Rate study typical heavy episode Beijing. We evaluate performance against in situ quality observations describe analytical factors case. Results showed that M varied most significantly at different stages episode, 0.21 µg⋅m−3⋅h−1 accumulation stage −11.82 removal stage, indicating dominated fluctuation amplitude concentration. acted as important cleaner for non-polluting periods but stopped being effective instead became contributor tended grow rapidly under superimposed influence processes, which would probably mark beginning event. The E ranged 0.63 0.88 owing diurnal variation emissions. was shown increase level haze, becoming largest (0.37 µg⋅m−3⋅h−1) maintenance period, 25 % higher than pre-contamination period. And C+CE made significant stages, reactions are more polluted period other periods. Nonnegligible exist concentrations (−1.83 2.44 – something has generally been ignored studies development heavy-pollution control strategies. helpful eliminating interference obtaining purified result target process have indicative significances. ratio CE C positively correlated speed. For precursors like NH3, smaller value indicated NH3 deficient, thus reducing had efficient controlling effect PM2.5. This highlights can be used realize in-depth adverse conditions judge whether excessive or not. Not only provide researchers policymakers valuable information key behind pollution, also help modelers identify sources uncertainties numerical models.

Language: Английский

Haze Occurrence Caused by High Gas-to-Particle Conversion in Moisture Air under Low Pollutant Emission in a Megacity of China DOI Open Access
Qingxia Ma, Weisi Wang,

Dexin Liu

et al.

International Journal of Environmental Research and Public Health, Journal Year: 2022, Volume and Issue: 19(11), P. 6405 - 6405

Published: May 25, 2022

Haze occurred in Zhengzhou, a megacity the northern China, with PM2.5 as high 254 μg m−3 on 25 December 2019, despite emergency response measure of restriction emission anthropogenic pollutants which was implemented 19 for suppressing local air pollution. Air pollutant concentrations, chemical compositions, and origins particulate matter aerodynamic diameter smaller than 2.5 µm (PM2.5) between 5–26 were investigated to explore reasons haze occurrence. Results show that caused by efficient SO2-to-suflate NOx-to-nitrate conversions under relative humidity (RH) condition. In comparison period before (5–18 December) when low, concentration during (19–26 173 µg average 51% contributed sulfate (31 m−3) nitrate (57 m−3). The SO2-to-sulfate efficiently produced although two precursor gases SO2 NOx low. RH, more 70% consequence artificial water-vapor spreading urban reducing pollutants, key factor causing conversion rates be enlarged constriction period. addition, last 48 h movement parcels 19–26 stagnant, mass from surrounding areas within 200 km, indicating weather conditions favoring accumulation locally-originated pollutants. Although measures implemented, gas-to-particle stagnant moisture circumstances can still cause severe air. Since one it is likely had unexpected side effects some certain needs taken into consideration future studies.

Language: Английский

Citations

3
Particulate Matter 2.5 concentration prediction system based on uncertainty analysis and multi-model integration DOI
Yamei Chen, Jianzhou Wang, Runze Li

et al.

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 958, P. 177924 - 177924

Published: Dec. 9, 2024

Language: Английский

Citations

0
A quantitative decoupling analysis (QDA v1.0) method for assessing the contributions of meteorology, emissions, and chemistry to fine particulate pollution DOI Creative Commons
Junhua Wang, Baozhu Ge, Xueshun Chen

et al.

Published: May 2, 2023

Abstract. A comprehensive understanding of the effects meteorology, emissions, and chemistry on severe haze is critical in mitigation air pollution. However, such an greatly hindered by nonlinearity atmospheric systems. In this study, we developed quantitative decoupling analysis (QDA) method to quantify chemical reactions, their nonlinear interactions fine particulate matter (PM2.5) pollution running built-in scenario simulations each model step. Different from previous methods, QDA achieves a fully decomposed hourly changes PM2.5 concentration during events into seven parts, including pure meteorological contribution (M), emissions (E), (C), among these processes (i.e., ME, MC, EC, MCE). Via embedding Weather Research Forecasting–Nested Air Quality Prediction Modeling System, employed combined it with Integrated Process Rate study typical heavy episode Beijing. We evaluate performance against situ quality observations describe analytical factors case. Results showed that M varied most significantly at different stages episode, 0.21 µg⋅m−3⋅h−1 accumulation stage −11.82 removal stage, indicating dominated fluctuation amplitude concentration. acted as important cleaner for non-polluting periods but stopped being effective instead became contributor tended grow rapidly under superimposed influence processes, which would probably mark beginning event. The E ranged 0.63 0.88 owing diurnal variation emissions. was shown increase level haze, becoming largest (0.37 µg⋅m−3⋅h−1) maintenance period, 25 % higher than pre-contamination period. And C+CE made significant stages, reactions are more polluted period other periods. Nonnegligible exist concentrations (−1.83 2.44 – something has generally been ignored studies development heavy-pollution control strategies. helpful eliminating interference obtaining purified result target process have indicative significances. ratio CE C positively correlated speed. For precursors like NH3, smaller value indicated NH3 deficient, thus reducing had efficient controlling effect PM2.5. This highlights can be used realize in-depth adverse conditions judge whether excessive or not. Not only provide researchers policymakers valuable information key behind pollution, also help modelers identify sources uncertainties numerical models.

Language: Английский

Citations

0
Comment on gmd-2023-22 DOI Creative Commons
Junhua Wang, Baozhu Ge, Xueshun Chen

et al.

Published: June 2, 2023

Abstract. A comprehensive understanding of the effects meteorology, emissions, and chemistry on severe haze is critical in mitigation air pollution. However, such an greatly hindered by nonlinearity atmospheric systems. In this study, we developed quantitative decoupling analysis (QDA) method to quantify chemical reactions, their nonlinear interactions fine particulate matter (PM2.5) pollution running built-in scenario simulations each model step. Different from previous methods, QDA achieves a fully decomposed hourly changes PM2.5 concentration during events into seven parts, including pure meteorological contribution (M), emissions (E), (C), among these processes (i.e., ME, MC, EC, MCE). Via embedding Weather Research Forecasting–Nested Air Quality Prediction Modeling System, employed combined it with Integrated Process Rate study typical heavy episode Beijing. We evaluate performance against in situ quality observations describe analytical factors case. Results showed that M varied most significantly at different stages episode, 0.21 µg⋅m−3⋅h−1 accumulation stage −11.82 removal stage, indicating dominated fluctuation amplitude concentration. acted as important cleaner for non-polluting periods but stopped being effective instead became contributor tended grow rapidly under superimposed influence processes, which would probably mark beginning event. The E ranged 0.63 0.88 owing diurnal variation emissions. was shown increase level haze, becoming largest (0.37 µg⋅m−3⋅h−1) maintenance period, 25 % higher than pre-contamination period. And C+CE made significant stages, reactions are more polluted period other periods. Nonnegligible exist concentrations (−1.83 2.44 – something has generally been ignored studies development heavy-pollution control strategies. helpful eliminating interference obtaining purified result target process have indicative significances. ratio CE C positively correlated speed. For precursors like NH3, smaller value indicated NH3 deficient, thus reducing had efficient controlling effect PM2.5. This highlights can be used realize in-depth adverse conditions judge whether excessive or not. Not only provide researchers policymakers valuable information key behind pollution, also help modelers identify sources uncertainties numerical models.

Language: Английский

Citations

0
Comment on gmd-2023-22 DOI Creative Commons
Juan Antonio Añel

Published: June 15, 2023

Abstract. A comprehensive understanding of the effects meteorology, emissions, and chemistry on severe haze is critical in mitigation air pollution. However, such an greatly hindered by nonlinearity atmospheric systems. In this study, we developed quantitative decoupling analysis (QDA) method to quantify chemical reactions, their nonlinear interactions fine particulate matter (PM2.5) pollution running built-in scenario simulations each model step. Different from previous methods, QDA achieves a fully decomposed hourly changes PM2.5 concentration during events into seven parts, including pure meteorological contribution (M), emissions (E), (C), among these processes (i.e., ME, MC, EC, MCE). Via embedding Weather Research Forecasting–Nested Air Quality Prediction Modeling System, employed combined it with Integrated Process Rate study typical heavy episode Beijing. We evaluate performance against in situ quality observations describe analytical factors case. Results showed that M varied most significantly at different stages episode, 0.21 µg⋅m−3⋅h−1 accumulation stage −11.82 removal stage, indicating dominated fluctuation amplitude concentration. acted as important cleaner for non-polluting periods but stopped being effective instead became contributor tended grow rapidly under superimposed influence processes, which would probably mark beginning event. The E ranged 0.63 0.88 owing diurnal variation emissions. was shown increase level haze, becoming largest (0.37 µg⋅m−3⋅h−1) maintenance period, 25 % higher than pre-contamination period. And C+CE made significant stages, reactions are more polluted period other periods. Nonnegligible exist concentrations (−1.83 2.44 – something has generally been ignored studies development heavy-pollution control strategies. helpful eliminating interference obtaining purified result target process have indicative significances. ratio CE C positively correlated speed. For precursors like NH3, smaller value indicated NH3 deficient, thus reducing had efficient controlling effect PM2.5. This highlights can be used realize in-depth adverse conditions judge whether excessive or not. Not only provide researchers policymakers valuable information key behind pollution, also help modelers identify sources uncertainties numerical models.

Language: Английский

Citations

0